Quotes

• “It is not the answer that enlightens, but the question.” (Eugène Ionesco)
  
• “Where would be the merit if heroes were never afraid?” (Alphonse Daudet)
  
• “In wartime a man is called a hero. It doesn’t make him any braver, and he runs for his life. But at least it’s a hero who is running away.” (Jean Giraudoux)
  
• “Love is worth whatever it costs.” (Françoise Sagan)
  
• “It is healthier to see the good points of others than to analyze our own bad ones.” (-ll-)
  
• “When a man has dreamed of winning something by a colossal stroke of luck, he is prone to neglect petty but more practical ways of attaining it.” (-ll-)
  
• “I find war detestable but those who praise it without participating in it even more so.” (Romain Rolland)
  
• “There is something sadder to lose than life – the reason for living; Sadder than to lose one’s possessions is to lose one’s hope.” (Paul Claudel)
  
• “This is rather as if you imagine a puddle waking up one morning and thinking, ‘This is an interesting world I find myself in — an interesting hole I find myself in — fits me rather neatly, doesn’t it? In fact it fits me staggeringly well, must have been made to have me in it!’ This is such a powerful idea that as the sun rises in the sky and the air heats up and as, gradually, the puddle gets smaller and smaller, frantically hanging on to the notion that everything’s going to be alright, because this world was meant to have him in it, was built to have him in it; so the moment he disappears catches him rather by surprise. I think this may be something we need to be on the watch out for.” (Douglas Adams)
  
• “The Englishman of 1750 was closer in material things to Caesar’s legionnaires than to his own great-grandchildren.” (Walter Scheidel, Escape from Rome (The Princeton Economic History of the Western World, Princeton University Press))
  
• “In the Western world, […] mature male stature rose by five inches between the late eighteenth and the late twentieth centuries.” (-ll-)
  
• People exaggerate both happiness and unhappiness; we are never so fortunate nor so unfortunate as people say we are. (/On amplifie également le malheur et le bonheur, nous ne sommes jamais ni si malheureux, ni si heureux qu’on le dit.) (Honoré de Balzac)
  
• “When women love, they forgive everything, even our crimes; when they do not love, they cannot forgive anything, not even our virtues.” (/Lorsque les femmes nous aiment, elles nous pardonnent tout, même nos crimes; lorsqu’elles ne nous aiment pas, elles ne nous pardonnent rien, pas même nos vertus!) (-ll-)
  
• “Those who spend too fast never grow rich.” (/Qui dépense trop n’est jamais riche) (-ll-)
  
• “Numerical results of mathematical problems can be tested by comparing them to observed numbers, or to a commonsense estimate of observable numbers. […] Yet every teacher knows that students achieve incredible things in this respect. Some students are not disturbed at all when they find 16,130 ft. for the length of the boat and 8 years, 2 months for the age of the captain who is, by the way, known to be a grandfather. Such neglect of the obvious does not show necessarily stupidity but rather indifference toward artificial problems. […] [A] teacher of mathematics has a great opportunity. If he fills his allotted time with drilling his students in routine operations he kills their interest, hampers their intellectual development, and misuses his opportunity. But if he challenges the curiosity of his students by setting them problems proportionate to their knowledge, and helps them to solve their problems with stimulating questions, he may give them a taste for, and some means of, independent thinking.” (George Pólya, How to Solve It. Princeton University Press)
  
• “If you can’t solve a problem, then there is an easier problem you can’t solve. Find it.” (-ll-)
  
• “No idea is really bad, unless we are uncritical. What is really bad is to have no idea at all. […] in theoretical matters, the best of ideas is hurt by uncritical acceptance and thrives on critical examination.” (-ll-)
  
• “Let us sum up. Recollecting formerly solved problems with the same or a similar unknown (formerly proved theorems with the same or a similar conclusion) we have a good chance to start in the right direction and we may conceive a plan of the solution. In simple cases, which are the most frequent in less advanced classes, the most elementary problems with the same unknown (theorems with the same conclusion) are usually sufficient. Trying to recollect problems with the same unknown is an obvious and common-sense device […]. It is rather surprising that such a simple and useful device is not more widely known […] neither students nor teachers of mathematics can afford to ignore the proper use of the suggestion: Look at the unknown! And try to think of a familiar problem having the same or a similar unknown.” (-ll-)
  
• “Speaking and thinking are closely connected, the use of words assists the mind. […] choosing a suitable notation may contribute essentially to understanding the problem. […] A good notation should be unambiguous, pregnant, easy to remember; it should avoid harmful second meanings, and take advantage of useful second meanings; the order and connection of signs should suggest the order and connection of things. […] we should choose our notation carefully, and have some good reason for our choice. […] Not only the most hopeless boys in the class but also quite intelligent students may have an aversion for algebra. There is always something arbitrary and artificial about notation; to learn a new notation is a burden for the memory. The intelligent student refuses to assume the burden if he does not see any compensation for it. The intelligent student is justified in his aversion for algebra if he is not given ample opportunity to convince himself by his own experience that the language of mathematical symbols assists the mind. To help him to such experience is an important task of the teacher, one of his most important tasks.” (-ll-)
  
• “Pedantry and mastery are opposite attitudes toward rules. […] To apply a rule to the letter, rigidly, unquestioningly, in cases where it fits and in cases where it does not fit, is pedantry. Some pedants are poor fools; they never did understand the rule which they apply so conscientiously and so indiscriminately. Some pedants are quite successful; they understood their rule, at least in the beginning (before they became pedants), and chose a good one that fits in many cases and fails only occasionally. To apply a rule with natural ease, with judgment, noticing the cases where it fits, and without ever letting the words of the rule obscure the purpose of the action or the opportunities of the situation, is mastery.” (-ll-)
  
• “L’amour est un tyran qui n’épargne personne.” (/Love is a tyrant, sparing none.) (Pierre Corneille)
  
• “To conquer without risk is to triumph without glory.” (-ll-)
  
• “Il faut bonne mémoire après qu’on a menti.” (/It takes a good memory to keep up a lie.) (-ll-)
  
• “The immune system functions so well that most of the time we do not notice it is actually working at all. However, it is continuously active, preventing severe infection from the micro-organisms which colonize our skin and our gut, and suppressing the chronic virus infections most of us picked up as infants. […] There are [even] data to suggest that mate choice (including in humans) can be driven by olfactory signals derived from […] MHC molecules — such that those with divergent MHC types are chosen, hence maximizing the number of different MHC molecules available to the offspring.” (Paul Klenerman – The Immune System: A Very Short Introduction, Oxford University Press)
  
• “Music expresses that which cannot be said and on which it is impossible to be silent.” (Victor Hugo)
  
• “Being a husband is a whole-time job. That is why so many husbands fail. They can’t give their entire attention to it.” (Arnold Bennett)
  
• “Journalists say a thing that they know isn’t true, in the hope that if they keep on saying it long enough it will be true.” (-ll-) (They are wrong, and people should really stop taking those people seriously – see part ii. here)
  
• “Dying is a very dull, dreary affair. And my advice to you is to have nothing whatever to do with it.” (W. Somerset Maugham)
  
• “People ask you for criticism, but they only want praise.” (-ll-)
  
• “Unfortunately, theories that explain everything often explain very little.” (William Bynum. The History of Medicine: A Very Short Introduction (p. 76). Oxford University Press)
  
• “Whatever the system of medical care, in Western societies, third-party arrangements are the norm in hospital payments, so large are the bills. The costs of building, heating, lighting, maintaining, equipping, and staffing these complex institutions have been an increasing concern for the past century. The guaranteeing body has been variously the state, the municipality, a religious organization, an insurance company, a charitable group, individual governors, a rich benefactor, or a combination of these. […] the drive for efficiency, and the adoption of business models, characterizes almost all modern hospitals. […] While developed nations can take the surveillance and regulations of public health for granted, or be incensed when they fail, […] the problems encountered in poorer parts of the world would not have surprised Edwin Chadwick or other advocates in 19th-century Europe. Issues of child and maternal mortality, epidemic diseases, poverty, and poor sanitation are still with us.” (Ibid., pp. 127-128, 136)
  
• “I used to watch a lot of news and commentary until one day I tried to tally up what I had learned during a month of it and found the quantity of facts could fit on a postage stamp.” (Zach Weiner)
  
• “Eppur si muove…” (Galileo Galilei)
  
• “Birds born in a cage think flying is an illness.” (Alejandro Jodorowsky)

A few diabetes papers of interest

i. Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes.

Some observations from the paper:

“Type 1 diabetes is preceded by the presence of preclinical, persistent islet autoantibodies (1). Autoantibodies against insulin (IAA) (2), GAD (GADA), insulinoma-associated antigen 2 (IA-2A) (3), and/or zinc transporter 8 (ZnT8A) (4) are typically present prior to development of symptomatic hyperglycemia and progression to clinical disease. These autoantibodies may develop many years before onset of type 1 diabetes, and increasing autoantibody number and titers have been associated with increased risk of progression to disease (5–7).

Identical twins have an increased risk of progression of islet autoimmunity and type 1 diabetes after one twin is diagnosed, although reported rates have been highly variable (30–70%) (8–11). This risk is increased if the proband twin develops diabetes at a young age (12). Concordance rates for type 1 diabetes in monozygotic twins with long-term follow-up is >50% (13). Risk for development of islet autoimmunity and type 1 diabetes for nonidentical twins is thought to be similar to non-twin siblings (risk of 6–10% for diabetes) (14). Full siblings who inherit both high-risk HLA (HLA DQA1*05:01 DR3/4*0302) haplotypes identical to their proband sibling with type 1 diabetes have a much higher risk for development of diabetes than those who share only one or zero haplotypes (55% vs. 5% by 12 years of age, respectively; P = 0.03) (15). Despite sharing both HLA haplotypes with their proband, siblings without the HLA DQA1*05:01 DR3/4*0302 genotype had only a 25% risk for type 1 diabetes by 12 years of age (15).”

“The TrialNet Pathway to Prevention Study (previously the TrialNet Natural History Study; 16) has been screening relatives of patients with type 1 diabetes since 2004 and follows these subjects with serial autoantibody testing for the development of islet autoantibodies and type 1 diabetes. The study offers longitudinal monitoring for autoantibody-positive subjects through HbA_1c testing and oral glucose tolerance tests (OGTTs).”

“The purpose of this study was to evaluate the prevalence of islet autoantibodies and analyze a logistic regression model to test the effects of genetic factors and common twin environment on the presence or absence of islet autoantibodies in identical twins, nonidentical twins, and full siblings screened in the TrialNet Pathway to Prevention Study. In addition, this study analyzed the presence of islet autoantibodies (GADA, IA-2A, and IAA) and risk of type 1 diabetes over time in identical twins, nonidentical twins, and full siblings followed in the TrialNet Pathway to Prevention Study. […] A total of 48,051 sibling subjects were initially screened (288 identical twins, 630 nonidentical twins, and 47,133 full siblings). Of these, 48,026 had an initial screening visit with GADA, IA2A, and IAA results (287 identical twins, 630 nonidentical twins, and 47,109 full siblings). A total of 17,226 participants (157 identical twins, 283 nonidentical twins and 16,786 full siblings) were followed for a median of 2.1 years (25th percentile 1.1 year and 75th percentile 4.0 years), with follow-up defined as at least ≥12 months follow-up after initial screening visit.”

“At the initial screening visit, GADA was present in 20.2% of identical twins (58 out of 287), 5.6% of nonidentical twins (35 out of 630), and 4.7% of full siblings (2,205 out of 47,109) (P < 0.0001). Additionally, IA-2A was present primarily in identical twins (9.4%; 27 out of 287) and less so in nonidentical twins (3.3%; 21 out of 630) and full siblings (2.2%; 1,042 out of 47,109) (P = 0.0001). Nearly 12% of identical twins (34 out of 287) were positive for IAA at initial screen, whereas 4.6% of nonidentical twins (29 out of 630) and 2.5% of full siblings (1,152 out of 47,109) were initially IAA positive (P < 0.0001).”

“At 3 years of follow-up, the risk for development of GADA was 16% for identical twins, 5% for nonidentical twins, and 4% for full siblings (P < 0.0001) (Fig. 1A). The risk for development of IA-2A by 3 years of follow-up was 7% for identical twins, 4% for nonidentical twins, and 2% for full siblings (P = 0.0005) (Fig. 1B). At 3 years of follow-up, the risk of development of IAA was 10% for identical twins, 5% for nonidentical twins, and 4% for full siblings (P = 0.006) […] In initially autoantibody-negative subjects, 1.5% of identical twins, 0% of nonidentical twins, and 0.5% of full siblings progressed to diabetes at 3 years of follow-up (P = 0.18) […] For initially single autoantibody–positive subjects, at 3 years of follow-up, 69% of identical twins, 13% of nonidentical twins, and 12% of full siblings developed type 1 diabetes (P < 0.0001) […] Subjects who were positive for multiple autoantibodies at screening had a higher risk of developing type 1 diabetes at 3 years of follow-up with 69% of identical twins, 72% of nonidentical twins, and 47% of full siblings developing type 1 diabetes (P = 0.079)”

“Because TrialNet is not a birth cohort and the median age at screening visit was 11 years overall, this study would not capture subjects who had initial seroconversion at a young age and then progressed through the intermediate stage of multiple antibody positivity before developing diabetes.”

“This study of >48,000 siblings of patients with type 1 diabetes shows that at initial screening, identical twins were more likely to have at least one positive autoantibody and be positive for GADA, IA-2A, and IAA than either nonidentical twins or full siblings. […] risk for development of type 1 diabetes at 3 years of follow-up was high for both single and multiple autoantibody–positive identical twins (62–69%) and multiple autoantibody–positive nonidentical twins (72%) compared with 47% for initially multiple autoantibody–positive full siblings and 12–13% for initially single autoantibody–positive nonidentical twins and full siblings. To our knowledge, this is the largest prediagnosis study to evaluate the effects of genetic factors and common twin environment on the presence or absence of islet autoantibodies.

In this study, younger age, male sex, and genetic factors were significantly associated with expression of IA-2A, IAA, more than one autoantibody, and more than two autoantibodies, whereas only genetic factors were significant for GADA. An influence of common twin environment (E) was not seen. […] Previous studies have shown that identical twin siblings of patients with type 1 diabetes have a higher concordance rate for development of type 1 diabetes compared with nonidentical twins, although reported rates for identical twins have been highly variable (30–70%) […]. Studies from various countries (Australia, Denmark, Finland, Great Britain, and U.S.) have reported concordance rates for nonidentical twins ∼5–15% […]. Concordance rates have been higher when the proband was diagnosed at a younger age (8), which may explain the variability in these reported rates. In this study, autoantibody-negative nonidentical and identical twins had a low risk of type 1 diabetes by 3 years of follow-up. In contrast, once twins developed autoantibodies, risk for type 1 diabetes was high for multiple autoantibody nonidentical twins and both single and multiple autoantibody identical twins.”

…

ii. A Type 1 Diabetes Genetic Risk Score Can Identify Patients With GAD65 Autoantibody–Positive Type 2 Diabetes Who Rapidly Progress to Insulin Therapy.

This is another paper in the ‘Predicting Diabetes Using Genetic Risk Scores‘ segment from the February edition of Diabetes Care – multiple other papers on related topics were also included in that edition, so if you’re interested in the genetics of diabetes it may be worth checking out.

Some observations from the paper:

“Type 2 diabetes is a progressive disease due to a gradual reduction in the capacity of the pancreatic islet cells (β-cells) to produce insulin (1). The clinical course of this progression is highly variable, with some patients progressing very rapidly to requiring insulin treatment, whereas others can be successfully treated with lifestyle changes or oral agents for many years (1,2). Being able to identify patients likely to rapidly progress may have clinical utility in prioritization monitoring and treatment escalation and in choice of therapy.

It has previously been shown that many patients with clinical features of type 2 diabetes have positive GAD65 autoantibodies (GADA) and that the presence of this autoantibody is associated with faster progression to insulin (3,4). This is often termed latent autoimmune diabetes in adults (LADA) (5,6). However, the predictive value of GADA testing is limited in a population with clinical type 2 diabetes, with many GADA-positive patients not requiring insulin treatment for many years (4,7). Previous research has suggested that genetic variants in the HLA region associated with type 1 diabetes are associated with more rapid progression to insulin in patients with clinically defined type 2 diabetes and positive GADA (8).

We have recently developed a type 1 diabetes genetic risk score (T1D GRS), which provides an inexpensive ($70 in our local clinical laboratory and <$20 where DNA has been previously extracted), integrated assessment of a person’s genetic susceptibility to type 1 diabetes (9). The score is composed of 30 type 1 diabetes risk variants weighted for effect size and aids discrimination of type 1 diabetes from type 2 diabetes. […] We aimed to determine if the T1D GRS could predict rapid progression to insulin (within 5 years of diagnosis) over and above GADA testing in patients with a clinical diagnosis of type 2 diabetes treated without insulin at diagnosis.”

“We examined the relationship between GADA, T1D GRS, and progression to insulin therapy using survival analysis in 8,608 participants with clinical type 2 diabetes initially treated without insulin therapy. […] In this large study of participants with a clinical diagnosis of type 2 diabetes, we have found that type 1 genetic susceptibility alters the clinical implications of a positive GADA when predicting rapid time to insulin. GADA-positive participants with high T1D GRS were more likely to require insulin within 5 years of diagnosis, with 48% progressing to insulin in this time in contrast to only 18% in participants with low T1D GRS. The T1D GRS was independent of and additive to participant’s age of diagnosis and BMI. However, T1D GRS was not associated with rapid insulin requirement in participants who were GADA negative.”

“Our findings have clear implications for clinical practice. The T1D GRS represents a novel clinical test that can be used to enhance the prognostic value of GADA testing. For predicting future insulin requirement in patients with apparent type 2 diabetes who are GADA positive, T1D GRS may be clinically useful and can be used as an additional test in the screening process. However, in patients with type 2 diabetes who are GADA negative, there is no benefit gained from genetic testing. This is unsurprising, as the prevalence of underlying autoimmunity in patients with a clinical phenotype of type 2 diabetes who are GADA negative is likely to be extremely low; therefore, most GADA-negative participants with high T1D GRS will have nonautoimmune diabetes. The use of this two-step testing approach may facilitate a precision medicine approach to patients with apparent type 2 diabetes; patients who are likely to progress rapidly are identified for targeted management, which may include increased monitoring, early therapy intensification, and/or interventions aimed at slowing progression (36,37).

The costs of analyzing the T1D GRS are relatively modest and may fall further, as genetic testing is rapidly becoming less expensive (38). […] In conclusion, a T1D GRS alters the clinical implications of a positive GADA test in patients with clinical type 2 diabetes and is independent of and additive to clinical features. This therefore represents a novel test for identifying patients with rapid progression in this population.”

…

iii. Retinopathy and RAAS Activation: Results From the Canadian Study of Longevity in Type 1 Diabetes.

“Diabetic retinopathy is the most common cause of preventable blindness in individuals ages 20–74 years and is the most common vascular complication in type 1 and type 2 diabetes (1–3). On the basis of increasing severity, diabetic retinopathy is classified into nonproliferative diabetic retinopathy (NPDR), defined in early stages by the presence of microaneurysms, retinal vascular closure, and alteration, or proliferative diabetic retinopathy (PDR), defined by the growth of new aberrant blood vessels (neovascularization) susceptible to hemorrhage, leakage, and fibrosis (4). Diabetic macular edema (DME) can be present at any stage of retinopathy and is characterized by increased vascular permeability leading to retinal thickening.

Important risk factors for the development of retinopathy continue to be chronic hyperglycemia, hyperlipidemia, hypertension, and diabetes duration (5,6). Given the systemic nature of these risk factors, cooccurrence of retinopathy with other vascular complications is common in patients with diabetes.”

“A key pathway implicated in diabetes-related small-vessel disease is overactivation of neurohormones. Activation of the neurohormonal renin-angiotensin-aldosterone system (RAAS) pathway predominates in diabetes in response to hyperglycemia and sodium retention. The RAAS plays a pivotal role in regulating systemic BP through vasoconstriction and fluid-electrolyte homeostasis. At the tissue level, angiotensin II (ANGII), the principal mediator of the RAAS, is implicated in fibrosis, oxidative stress, endothelial damage, thrombosis, inflammation, and vascular remodeling. Of note, systemic RAAS blockers reduce the risk of progression of eye disease but not DKD [Diabetic Kidney Disease, US] in adults with type 1 diabetes with normoalbuminuria (12).

Several longitudinal epidemiologic studies of diabetic retinopathy have been completed in type 1 diabetes; however, few have studied the relationships between eye, nerve, and renal complications and the influence of RAAS activation after prolonged duration (≥50 years) in adults with type 1 diabetes. As a result, less is known about mechanisms that persist in diabetes-related microvascular complications after long-standing diabetes. Accordingly, in this cross-sectional analysis from the Canadian Study of Longevity in Type 1 Diabetes involving adults with type 1 diabetes for ≥50 years, our aims were to phenotype retinopathy stage and determine associations between the presence of retinopathy and other vascular complications. In addition, we examined the relationship between retinopathy stage and renal and systemic hemodynamic function, including arterial stiffness, at baseline and dynamically after RAAS activation with an infusion of exogenous ANGII.”

“Of the 75 participants, 12 (16%) had NDR [no diabetic retinopathy], 24 (32%) had NPDR, and 39 (52%) had PDR […]. At baseline, those with NDR had lower mean HbA_1c compared with those with NPDR and PDR (7.4 ± 0.7% and 7.5 ± 0.9%, respectively; P for trend = 0.019). Of note, those with more severe eye disease (PDR) had lower systolic and diastolic BP values but a significantly higher urine albumin-to-creatine ratio (UACR) […] compared with those with less severe eye disease (NPDR) or with NDR despite higher use of RAAS inhibitors among those with PDR compared with NPDR or NDR. History of cardiovascular and peripheral vascular disease history was significantly higher in participants with PDR (33.3%) than in those with NPDR (8.3%) or NDR (0%). Diabetic sensory polyneuropathy was prevalent across all groups irrespective of retinopathy status but was numerically higher in the PDR group (95%) than in the NPDR (86%) or NDR (75%) groups. No significant differences were observed in retinal thickness across the three groups.”

One quick note: This was mainly an eye study, but some of the other figures here are well worth taking note of. 3 out of 4 people in the supposedly low-risk group without eye complications had sensory polyneuropathy after 50 years of diabetes.

“Conclusions

Hyperglycemia contributes to the pathogenesis of diabetic retinopathy through multiple interactive pathways, including increased production of advanced glycation end products, IGF-I, vascular endothelial growth factor, endothelin, nitric oxide, oxidative damage, and proinflammatory cytokines (29–33). Overactivation of the RAAS in response to hyperglycemia also is implicated in the pathogenesis of diabetes-related complications in the retina, nerves, and kidney and is an important therapeutic target in type 1 diabetes. Despite what is known about these underlying pathogenic mechanisms in the early development of diabetes-related complications, whether the same mechanisms are active in the setting of long-standing type 1 diabetes is not known. […] In this study, we observed that participants with PDR were more likely to be taking RAAS inhibitors, to have a higher frequency of cardiovascular or peripheral vascular disease, and to have higher UACR levels, likely reflecting the higher overall risk profile of this group. Although it is not possible to determine why some patients in this cohort developed PDR while others did not after similar durations of type 1 diabetes, it seems unlikely that glycemic control alone is sufficient to fully explain the observed between-group differences and differing vascular risk profiles. Whereas the NDR group had significantly lower mean HbA_1c levels than the NPDR and PDR groups, differences between participants with NPDR and those with PDR were modest. Accordingly, other factors, such as differences in vascular function, neurohormones, growth factors, genetics, and lifestyle, may play a role in determining retinopathy severity at the individual level.

The association between retinopathy and risk for DKD is well established in diabetes (34). In the setting of type 2 diabetes, patients with high levels of UACR have twice the risk of developing diabetic retinopathy than those with normal UACR levels. For example, Rodríguez-Poncelas et al. (35) demonstrated that impaired renal function is linked with increased diabetic retinopathy risk. Consistent with these studies and others, the PDR group in this Canadian Study of Longevity in Type 1 Diabetes demonstrated significantly higher UACR, which is associated with an increased risk of DKD progression, illustrating that the interaction between eye and kidney disease progression also may exist in patients with long-standing type 1 diabetes. […] In conclusion, retinopathy was prevalent after prolonged type 1 diabetes duration, and retinopathy severity associated with several measures of neuropathy and with higher UACR. Differential exaggerated responses to RAAS activation in the peripheral vasculature of the PDR group highlights that even in the absence of DKD, neurohormonal abnormalities are likely still operant, and perhaps accentuated, in patients with PDR even after long-standing type 1 diabetes duration.”

…

iv. Clinical and MRI Features of Cerebral Small-Vessel Disease in Type 1 Diabetes.

“Type 1 diabetes is associated with a fivefold increased risk of stroke (1), with cerebral small-vessel disease (SVD) as the most common etiology (2). Cerebral SVD in type 1 diabetes, however, remains scarcely investigated and is challenging to study in vivo per se owing to the size of affected vasculature (3); instead, MRI signs of SVD are studied. In this study, we aimed to assess the prevalence of cerebral SVD in subjects with type 1 diabetes compared with healthy control subjects and to characterize diabetes-related variables associated with SVD in stroke-free people with type 1 diabetes.”

“RESEARCH DESIGN AND METHODS This substudy was cross-sectional in design and included 191 participants with type 1 diabetes and median age 40.0 years (interquartile range 33.0–45.1) and 30 healthy age- and sex-matched control subjects. All participants underwent clinical investigation and brain MRIs, assessed for cerebral SVD.

RESULTS Cerebral SVD was more common in participants with type 1 diabetes than in healthy control subjects: any marker 35% vs. 10% (P = 0.005), cerebral microbleeds (CMBs) 24% vs. 3.3% (P = 0.008), white matter hyperintensities 17% vs. 6.7% (P = 0.182), and lacunes 2.1% vs. 0% (P = 1.000). Presence of CMBs was independently associated with systolic blood pressure (odds ratio 1.03 [95% CI 1.00–1.05], P = 0.035).”

“Conclusions

Cerebral SVD is more common in participants with type 1 diabetes than in healthy control subjects. CMBs especially are more prevalent and are independently associated with hypertension. Our results indicate that cerebral SVD starts early in type 1 diabetes but is not explained solely by diabetes-related vascular risk factors or the generalized microvascular disease that takes place in diabetes (7).

There are only small-scale studies on cerebral SVD, especially CMBs, in type 1 diabetes. Compared with the current study, one study with similar diabetes characteristics (i.e., diabetes duration, glycemic control, and blood pressure levels) as in the current study, but lacking a control population, showed a higher prevalence of WMHs, with more than half of the participants affected, but similar prevalence of lacunes and lower prevalence of CMBs (8). In another study, including 67 participants with type 1 diabetes and 33 control subjects, there was no difference in WMH prevalence but a higher prevalence of CMBs in participants with type 1 diabetes and retinopathy compared with control subjects (9). […] In type 1 diabetes, albuminuria and systolic blood pressure independently increase the risk for both ischemic and hemorrhagic stroke (12). […] We conclude that cerebral SVD is more common in subjects with type 1 diabetes than in healthy control subjects. Future studies will focus on longitudinal development of SVD in type 1 diabetes and the associations with brain health and cognition.”

…

v. The Legacy Effect in Type 2 Diabetes: Impact of Early Glycemic Control on Future Complications (The Diabetes & Aging Study).

“In the U.S., an estimated 1.4 million adults are newly diagnosed with diabetes every year and present an important intervention opportunity for health care systems. In patients newly diagnosed with type 2 diabetes, the benefits of maintaining an HbA_1c <7.0% (<53 mmol/mol) are well established. The UK Prospective Diabetes Study (UKPDS) found that a mean HbA_1c of 7.0% (53 mmol/mol) lowers the risk of diabetes-related end points by 12–32% compared with a mean HbA_1c of 7.9% (63 mmol/mol) (1,2). Long-term observational follow-up of this trial revealed that this early glycemic control has durable effects: Reductions in microvascular events persisted, reductions in cardiovascular events and mortality were observed 10 years after the trial ended, and HbA_1c values converged (1). Similar findings were observed in the Diabetes Control and Complications Trial (DCCT) in patients with type 1 diabetes (2–4). These posttrial observations have been called legacy effects (also metabolic memory) (5), and they suggest the importance of early glycemic control for the prevention of future complications of diabetes. Although these clinical trial long-term follow-up studies demonstrated legacy effects, whether legacy effects exist in real-world populations, how soon after diabetes diagnosis legacy effects may begin, or for what level of glycemic control legacy effects may exist are not known.

In a previous retrospective cohort study, we found that patients with newly diagnosed diabetes and an initial 10-year HbA_1c trajectory that was unstable (i.e., changed substantially over time) had an increased risk for future microvascular events, even after adjusting for HbA_1c exposure (6). In the same cohort population, this study evaluates associations between the duration and intensity of glycemic control immediately after diagnosis and the long-term incidence of future diabetic complications and mortality. We hypothesized that a glycemic legacy effect exists in real-world populations, begins as early as the 1st year after diabetes diagnosis, and depends on the level of glycemic exposure.”

“RESEARCH DESIGN AND METHODS This cohort study of managed care patients with newly diagnosed type 2 diabetes and 10 years of survival (1997–2013, average follow-up 13.0 years, N = 34,737) examined associations between HbA_1c <6.5% (<48 mmol/mol), 6.5% to <7.0% (48 to <53 mmol/mol), 7.0% to <8.0% (53 to <64 mmol/mol), 8.0% to <9.0% (64 to <75 mmol/mol), or ≥9.0% (≥75 mmol/mol) for various periods of early exposure (0–1, 0–2, 0–3, 0–4, 0–5, 0–6, and 0–7 years) and incident future microvascular (end-stage renal disease, advanced eye disease, amputation) and macrovascular (stroke, heart disease/failure, vascular disease) events and death, adjusting for demographics, risk factors, comorbidities, and later HbA_1c.

RESULTS Compared with HbA_1c <6.5% (<48 mmol/mol) for the 0-to-1-year early exposure period, HbA_1c levels ≥6.5% (≥48 mmol/mol) were associated with increased microvascular and macrovascular events (e.g., HbA_1c 6.5% to <7.0% [48 to <53 mmol/mol] microvascular: hazard ratio 1.204 [95% CI 1.063–1.365]), and HbA_1c levels ≥7.0% (≥53 mmol/mol) were associated with increased mortality (e.g., HbA_1c 7.0% to <8.0% [53 to <64 mmol/mol]: 1.290 [1.104–1.507]). Longer periods of exposure to HbA_1c levels ≥8.0% (≥64 mmol/mol) were associated with increasing microvascular event and mortality risk.

CONCLUSIONS Among patients with newly diagnosed diabetes and 10 years of survival, HbA_1c levels ≥6.5% (≥48 mmol/mol) for the 1st year after diagnosis were associated with worse outcomes. Immediate, intensive treatment for newly diagnosed patients may be necessary to avoid irremediable long-term risk for diabetic complications and mortality.”

Do note that the effect sizes here are very large and this stuff seems really quite important. Judging from the results of this study, if you’re newly diagnosed and you only obtain a HbA_1c of say, 7.3% in the first year, that may translate into a close to 30% increased risk of death more than 10 years into the future, compared to a scenario of an HbA_1c of 6.3%. People who did not get their HbA_1c measured within the first 3 months after diagnosis had a more than 20% increased risk of mortality during the study period. This seems like critical stuff to get right.

…

vi. Event Rates and Risk Factors for the Development of Diabetic Ketoacidosis in Adult Patients With Type 1 Diabetes: Analysis From the DPV Registry Based on 46,966 Patients.

“Diabetic ketoacidosis (DKA) is a life-threatening complication of type 1 diabetes mellitus (T1DM) that results from absolute insulin deficiency and is marked by acidosis, ketosis, and hyperglycemia (1). Therefore, prevention of DKA is one goal in T1DM care, but recent data indicate increased incidence (2).

For adult patients, only limited data are available on rates and risk factors for development of DKA, and this complication remains epidemiologically poorly characterized. The Diabetes Prospective Follow-up Registry (DPV) has followed patients with diabetes from 1995. Data for this study were collected from 2000 to 2016. Inclusion criteria were diagnosis of T1DM, age at diabetes onset ≥6 months, patient age at follow-up ≥18 years, and diabetes duration ≥1 year to exclude DKA at manifestation. […] In total, 46,966 patients were included in this study (average age 38.5 years [median 21.2], 47.6% female). The median HbA_1c was 7.7% (61 mmol/mol), median diabetes duration was 13.6 years, and 58.3% of the patients were treated in large diabetes centers.

On average, 2.5 DKA-related hospital admissions per 100 patient-years (PY) were observed (95% CI 2.1–3.0). The rate was highest in patients aged 18–30 years (4.03/100 PY) and gradually declined with increasing age […] No significant differences between males (2.46/100 PY) and females (2.59/100 PY) were found […] Patients with HbA_1c levels <7% (53 mmol/mol) had significantly fewer DKA admissions than patients with HbA_1c ≥9% (75 mmol/mol) (0.88/100 PY vs. 6.04/100 PY; P < 0.001)”

“Regarding therapy, use of an insulin pump (continuous subcutaneous insulin infusion [CSII]) was not associated with higher DKA rates […], while patients aged 31–50 years on CSII showed lower rates than patients using multiple daily injections (2.21 vs. 3.12/100 PY; adjusted P < 0.05) […]. Treatment in a large center was associated with lower DKA-related hospital admissions […] In both adults and children, poor metabolic control was the strongest predictor of hospital admission due to DKA. […] In conclusion, the results of this study identify patients with T1DM at risk for DKA (high HbA_1c, diabetes duration 5–10 years, migrants, age 30 years and younger) in real-life diabetes care. These at-risk individuals may need specific attention since structured diabetes education has been demonstrated to specifically reduce and prevent this acute complication.”

Viruses

This book is not great, but it’s also not bad – I ended up giving it three stars on goodreads, being much closer to 2 stars than 4. It’s a decent introduction to the field of virology, but not more than that. Below some quotes and links related to the book’s coverage.

…

“[I]t was not until the invention of the electron microscope in 1939 that viruses were first visualized and their structure elucidated, showing them to be a unique class of microbes. Viruses are not cells but particles. They consist of a protein coat which surrounds and protects their genetic material, or, as the famous immunologist Sir Peter Medawar (1915–87) termed it, ‘a piece of bad news wrapped up in protein’. The whole structure is called a virion and the outer coat is called the capsid. Capsids come in various shapes and sizes, each characteristic of the virus family to which it belongs. They are built up of protein subunits called capsomeres and it is the arrangement of these around the central genetic material that determines the shape of the virion. For example, pox viruses are brick-shaped, herpes viruses are icosahedral (twenty-sided spheres), the rabies virus is bullet-shaped, and the tobacco mosaic virus is long and thin like a rod […]. Some viruses have an outer layer surrounding the capsid called an envelope. […] Most viruses are too small to be seen under a light microscope. In general, they are around 100 to 500 times smaller than bacteria, varying in size from 20 to 300 nanometres in diameter […] Inside the virus capsid is its genetic material, or genome, which is either RNA or DNA depending on the type of virus […] Viruses usually have between 4 and 200 genes […] Cells of free-living organisms, including bacteria, contain a variety of organelles essential for life such as ribosomes that manufacture proteins, mitochondria, or other structures that generate energy, and complex membranes for transporting molecules within the cell, and also across the cell wall. Viruses, not being cells, have none of these and are therefore inert until they infect a living cell. Then they hijack a cell’s organelles and use what they need, often killing the cell in the process. Thus viruses are obliged to obtain essential components from other living things to complete their life cycle and are therefore called obligate parasites.”

“Plant viruses either enter cells through a break in the cell wall or are injected by a sap-sucking insect vector like aphids. They then spread very efficiently from cell to cell via plasmodesmata, pores that transport molecules between cells. In contrast, animal viruses infect cells by binding to specific cell surface receptor molecules. […] Once a virus has bound to its cellular receptor, the capsid penetrates the cell and its genome (DNA or RNA) is released into the cell cytoplasm. The main ‘aim’ of a virus is to reproduce successfully, and to do this its genetic material must download the information it carries. Mostly, this will take place in the cell’s nucleus where the virus can access the molecules it needs to begin manufacturing its own proteins. Some large viruses, like pox viruses, carry genes for the enzymes they need to make their proteins and so are more self-sufficient and can complete the whole life cycle in the cytoplasm. Once inside a cell, DNA viruses simply masquerade as pieces of cellular DNA, and their genes are transcribed and translated using as much of the cell’s machinery as they require. […] Because viruses have a high mutation rate, significant evolutionary change, estimated at around 1 per cent per year for HIV, can be measured over a short timescale. […] RNA viruses have no proof-reading system so they have a higher mutation rate than DNA viruses. […] By constantly evolving, […] viruses appear to have honed their skills for spreading from one host to another to reach an amazing degree of sophistication. For instance, the common cold virus (rhinovirus), while infecting cells lining the nasal cavities, tickles nerve endings to cause sneezing. During these ‘explosions’, huge clouds of virus-carrying mucus droplets are forcefully ejected, then float in the air until inhaled by other susceptible hosts. Similarly, by wiping out sheets of cells lining the intestine, rotavirus prevents the absorption of fluids from the gut cavity. This causes severe diarrhea and vomiting that effectively extrudes the virus’s offspring back into the environment to reach new hosts. Other highly successful viruses hitch a ride from one host to another with insects. […] As a virus’s generation time is so much shorter than ours, the evolution of genetic resistance to a new human virus is painfully slow, and constantly leaves viruses with the advantage.”

“The phytoplankton is a group of organisms that uses solar energy and carbon dioxide to generate energy by photosynthesis. As a by-product of this reaction, they produce almost half of the world’s oxygen and are therefore of vital importance to the chemical stability of the planet. Phytoplankton forms the base of the whole marine food-web, being grazed upon by zooplankton and young marine animals which in turn fall prey to fish and higher marine carnivores. By infecting and killing plankton microbes, marine viruses control the dynamics of all these essential populations and their interactions. For example, the common and rather beautiful phytoplankton Emiliania huxleyi regularly undergoes blooms that turn the ocean surface an opaque blue over areas so vast that they can be detected from space by satellites. These blooms disappear as quickly as they arise, and this boom-and-bust cycle is orchestrated by the viruses in the community that specifically infect E. huxleyi. Because they can produce thousands of offspring from every infected cell, virus numbers amplify in a matter of hours and so act as a rapid-response team, killing most of the bloom microbes in just a few days. […] Overall, marine viruses kill an estimated 20-40 per cent of marine bacteria every day, and as the major killer of marine microbes, they profoundly affect the carbon cycle by the so-called ‘viral shunt‘.”

“By the end of 2015 WHO reported 36.7 million people living with HIV globally, 70 per cent of whom are in sub-Saharan Africa. Since the first identification of HIV-induced acquired immunodeficiency syndrome (AIDS) approximately 78 million people have been infected with HIV, causing around 35 million deaths […] Antiviral drugs are key in curtailing HIV spread and are being rolled out worldwide, with present coverage of around 46 per cent of those in need. […] The HIVs are most closely related to primate retroviruses called simian immunodeficiency viruses (SIVs) and it is now clear that these HIV-like viruses have jumped from primates to humans in central Africa on several occasions in the past giving rise to human infections with HIV-1 types M, N, O, and P as well as HIV-2. Yet only one of these viruses, HIV-1 type M, has succeeded in spreading globally. The ancestor of this virus has been traced to a subspecies of chimpanzees (Pan troglodytes troglodytes), among whom it can cause an AIDS-like disease. Since these animals are hunted for bush meat, it is most likely that human infection occurred by blood contamination during the killing and butchering process. This event probably took place in south-east Cameroon where chimpanzees carrying an SIV most closely related to HIV-1 type M live.”

“Flu viruses are paramyxoviruses with an RNA genome with eight genes that are segmented, meaning that instead of being a continuous RNA chain, each gene forms a separate strand. The H (haemaglutinin) and N (neuraminidase) genes are the most important in stimulating protective host immunity. There are sixteen different H and nine different N genes, all of which can be found in all combinations in bird flu viruses. Because these genes are separate RNA strands, on occasions they become mixed up, or recombined. So if two flu A viruses with different H and/or N genes infect a single cell, the offspring will carry varying combinations of genes from the two parent viruses. Most of these viruses will be unable to infect humans, but occasionally a new virus strain is produced that can jump directly to humans and cause a pandemic. […] The emergence of almost all recent novel flu viruses has been traced to China where they circulate freely among animals kept in cramped conditions in farms and live bird markets. […] once established in humans their spread has been much enhanced by travel, particularly air travel that can take a virus inside a traveller across the globe before they even realize they are infected. […] With over a billion people worldwide boarding international flights every year, novel viruses have an efficient mechanism for rapid spread.”

“Once an acute emerging virus such as a new strain of flu is successfully established in a population, it generally settles into a mode of cyclical epidemics during which many susceptible people are infected and become immune to further attack. When most are immune, the virus moves on, only returning when a new susceptible population has emerged, which generally consists of those born since the last epidemic. Before vaccination programmes became widespread, young children suffered from a series of well-recognized infectious diseases called the ‘childhood infections’. These included measles, mumps, rubella, and chickenpox, all caused by viruses […] following the introduction of vaccine programmes these have become a rarity, particularly in the developed world. […] Of the three viruses, measles is the most infectious and produces the severest disease. It killed millions of children each year before vaccination was introduced in the mid-20th century. Even today, this virus kills over 70,000 children annually in countries with low vaccine coverage. […] In developing countries, measles kills 1-5 per cent of those it infects”.

“Smallpox virus is in a class of its own as the world’s worst killer virus. It first infected humans at least 5,000 years ago and killed around 300 million in the 20th century alone. The virus killed up to 30 per cent of those it infected, scarring and blinding many of the survivors. […] Worldwide, eradication of smallpox was declared in 1980.”

“Viruses spread between hosts in many different ways, but those that cause acute epidemics generally utilize fast and efficient methods, such as the airborne or faecal-oral routes. […] Broadly speaking, virus infections are distinguished by the organs they affect, with airborne viruses mainly causing respiratory illnesses, […] and those transmitted by faecal-oral contamination causing intestinal upsets, with nausea, vomiting, and diarrhoea. There are literally thousands of viruses capable of causing human epidemics […] worldwide, acute respiratory infections, mostly viral, cause an estimated four million deaths a year in children under 5. […] Most people get two or three colds a year, suggesting that the immune system, which is so good at protecting us against a second attack of measles, mumps, or rubella, is defeated by the common cold virus. But this is not the case. In fact, there are so many viruses that cause the typical symptoms of blocked nose, headache, malaise, sore throat, sneezing, coughing, and sometimes fever, that even if we live for a hundred years, we will not experience them all. The common cold virus, or rhinovirus, alone has over one hundred different types, and there are many other viruses that infect the cells lining the nose and throat and cause similar symptoms, often with subtle variations. […] Viruses that target the gut are just as diverse as respiratory viruses […] Rotaviruses are a major cause of gastroenteritis globally, particularly targeting children under 5. The disease varies in severity […] rotaviruses cause over 600,000 infant deaths a year worldwide […] Noroviruses are the second most common cause of viral gastroenteritis after rotaviruses, producing a milder disease of shorter duration. These viruses account for around 23 million cases of gastroenteritis every year […] Many virus families such as rotaviruses that rely on faecal-oral transmission and cause gastroenteritis in humans produce the same symptoms in animals, resulting in great economic loss to the farming industry. […] over the centuries, Rinderpest virus, the cause of cattle plague, has probably been responsible for more loss and hardship than any other. […] Rinderpest is classically described by the three Ds: discharge, diarrhoea, and death, the latter being caused by fluid loss with rapid dehydration. The disease kills around 90 per cent of animals infected. Rinderpest used to be a major problem in Europe and Asia, and when it was introduced into Africa in the late 19th century it killed over 90 per cent of cattle, with devastating economic loss. The Global Rinderpest Eradication Programme was set up in the 1980s aiming to use the effective vaccine to rid the world of the virus by 2010. This was successful, and in October 2010 the disease was officially declared eradicated, the first animal disease and second infectious disease ever to be eliminated.”

“At present, 1.8 million virus-associated cancers are diagnosed worldwide annually. This accounts for 18 per cent of all cancers, but since these human tumour viruses were only identified fairly recently, it is probable that there are several more out there waiting to be discovered. […] Primary liver cancer is a major global health problem, being one of the ten most common cancers worldwide, with over 250,000 cases diagnosed every year and only 5 per cent of sufferers surviving five years. The tumour is more common in men than women and is most prevalent in sub-Saharan Africa and South East Asia where the incidence reaches over 30 per 100,000 population per year, compared to fewer than 5 per 100,000 in the USA and Europe. Up to 80 per cent of these tumours are caused by a hepatitis virus, the remainder being related to liver damage from toxic agents such as alcohol. […] hepatitis B and C viruses cause liver cancer. […] a large study carried out on 22,000 men in Taiwan in the 1990s showed that those persistently infected with HBV were over 200 times more likely than non-carriers to develop liver cancer, and that over half the deaths in this group were due to liver cancer or cirrhosis. […] A vaccine against HBV is available, and its use has already caused a decline in HBV-related liver cancer in Taiwan, where a vaccination programme was implemented in the 1980s”.

“Most persistent viruses have evolved to cause mild or even asymptomatic infections, since a life-threatening disease would not only be detrimental to the host but also deprive the virus of its home. Indeed, some viruses apparently cause no ill effects at all, and have been discovered only by chance. One example is TTV, a tiny DNA virus found in 1997 during the search for the cause of hepatitis and named after the initials (TT) of the patient from whom it was first isolated. We now know that TTV, and its relative TTV-like mini virus, represent a whole spectrum of similar viruses that are carried by almost all humans, non-human primates, and a variety of other vertebrates, but so far they have not been associated with any disease. With modern, highly sensitive molecular techniques for identifying non-pathogenic viruses, we can expect to find more of these silent passengers in the future. […] Historically, diagnosis and treatment of virus infections have lagged far behind those of bacterial diseases and are only now catching up. […] Diagnostic laboratories are still unable to find a culprit virus in many so-called ‘viral’ meningitis, encephalitis, and respiratory infections. This strongly suggests that there are many pathogenic viruses waiting to be discovered”.

“There is no doubt that although vaccines are expensive to prepare and test, they are the safest, easiest, and most cost-effective way of controlling infectious diseases worldwide.”

…

Virology. Virus. RNA virus. DNA virus. Retrovirus. Reverse transcriptase. Integrase. Provirus.
Germ theory of disease.
Antonie van Leeuwenhoek. Louis Pasteur. Robert Koch. Adolf Mayer. Dmitri Ivanovsky. Martinus Beijerinck.
Tobacco mosaic virus.
Mimivirus.
Viral evolution – origins.
White spot syndrome.
Fibropapillomatosis.
Acyrthosiphon pisum.
Vibrio_cholerae#Genome (Vibrio cholerae are bacteria, but viruses play a very important role here regarding the toxin-producing genes – “Only cholera bacteria infected with the toxigenic phage are pathogenic to humans”).
Yellow fever.
Dengue fever.
CCR5.
Immune system. Cytokine. Interferon. Macrophage. Lymphocyte. Antigen. CD4⁺+ T cells. CD8+ T-cell. Antibody. Regulatory T cell. Autoimmunity.
Zoonoses.
Arbovirus. Coronavirus. SARS-CoV. MERS-CoV. Ebolavirus. Henipavirus. Influenza virus. H5N1. HPAI. H7N9. Foot-and-mouth disease. Monkeypox virus. Chikungunya virus. Schmallenberg virus. Zika virus. Rift valley fever. Bluetongue disease. Arthrogryposis. West Nile fever. Chickenpox. Polio. Bocavirus.
Sylvatic cycle.
Nosocomial infections.
Subacute sclerosing panencephalitis.
Herpesviridae. CMV. Herpes simplex virus. Epstein–Barr virus. Human herpesvirus 6. Human betaherpesvirus 7. Kaposi’s sarcoma-associated herpesvirus (KSHV). Varicella-zoster virus (VZV). Infectious mononucleosis. Hepatitis. Rous sarcoma virus. Human T-lymphotropic virus. Adult t cell leukemia. HPV. Cervical cancer.
Oncovirus. Myc.
Variolation. Edward Jenner. Mary Wortley Montagu. Benjamin Jesty. James Phipps. Joseph Meister. Jonas Salk. Albert Sabin.
Marek’s disease. Rabies. Post-exposure prophylaxis.
Vaccine.
Aciclovir. Oseltamivir.
PCR.

 

A few diabetes papers of interest

i. Glycemic Control and Risk of Infections Among People With Type 1 or Type 2 Diabetes in a Large Primary Care Cohort Study. From the paper:

“Infections are widely considered to be a source of significant health care costs and to reduce quality of life among people with diabetes mellitus (DM) (1). Nevertheless, relatively few, large, well-designed, epidemiological studies have explored relationships between poorer control of DM and infections; previous studies have important limitations (1). Most randomized controlled trials (RCTs) of DM control have not investigated the effect of improved glycemic control on infections and are unlikely to do so at present because of the high cost and lack of good-quality supporting observational evidence. […] A recent review of higher-quality population-based epidemiological studies found clinically important (∼1.5–3.5 times higher) infection risks associated with poorer DM control in some studies (usually defined as a glycated hemoglobin [HbA_1c] level >7–8% [53–64 mmol/mol]) (1). However, the studies were inconsistent, generating uncertainty about the evidence.

A key concern with previous work is that the measurement of HbA_1c usually was made at or near to the time of the infection, so any association could be explained by reverse causality. Any infectious disease episode can itself have an adverse effect on glycemic control, a process known as stress hyperglycemia (4); hence, blood glucose or HbA_1c measurements near the time of an infection may be elevated, rendering determination of the chronology and relationship between the two difficult. Several studies with serial HbA_1c measurements have shown that the stress hyperglycemia response can be substantial (4–6). Another important issue is that studies of incident DM often use measurements of HbA_1c obtained during initial presentation, and these typically do not represent subsequent levels after initiation of treatment; use of such measurements may obscure associations between usual HbA_1c level and infection risk. Other limitations of previous work include a lack of consideration of type of DM (especially T1DM) and fewer older people with DM. The current study uses a large English primary care database with repeated HbA_1c measurements wherein we can classify individuals more precisely in terms of their baseline glycemic control as well as ensure that these HbA_1c measurements were made before the infection episode.”

“With the use of English primary care data, average glycated hemoglobin (HbA_1c) during 2008–2009 was estimated for 85,312 patients with DM ages 40–89 years. Infection rates during 2010–2015 compiled from primary care, linked hospital, and mortality records were estimated across 18 infection categories and further summarized as any requiring a prescription or hospitalization or as cause of death. Poisson regression was used to estimate adjusted incidence rate ratios (IRRs) by HbA_1c categories across all DM, and type 1 and type 2 DM separately. IRRs also were compared with 153,341 age-sex-practice–matched controls without DM. Attributable fractions (AF%) among patients with DM were estimated for an optimal control scenario (HbA_1c 6–7% [42–53 mmol/mol]).”

“Crude infection rates during 2010–2015 estimated across 18 different categories confirmed consistently higher rates among patients with DM […]. Long-term infection risk rose with increasing HbA_1c for most outcomes. Compared with patients without DM, those with DM and optimal control (HbA_1c 6–7% [42–53 mmol/mol], IRR 1.41 [95% CI 1.36–1.47]) and poor control (≥11% [97 mmol/mol], 4.70 [4.24–5.21]) had elevated hospitalization risks for infection. In patients with type 1 DM and poor control, this risk was even greater (IRR 8.47 [5.86–12.24]). Comparisons within patients with DM confirmed the risk of hospitalization with poor control (2.70 [2.43–3.00]) after adjustment for duration and other confounders. AF% of poor control were high for serious infections, particularly bone and joint (46%), endocarditis (26%), tuberculosis (24%), sepsis (21%), infection-related hospitalization (17%), and mortality (16%). […] even patients with DM with good control were at an increased risk compared with matched controls without DM. Thus, compared with patients without DM, patients with DM and good control (mean HbA_1c 6–7%, IRR 1.41 [95% CI 1.36–1.47]) and those with poor control (≥11%, 4.70 [4.24–5.21]) had elevated hospitalization risks for infection. These risks were higher among patients with T1DM. For example, patients with T1DM with a mean HbA_1c ≥11%, had more than eight times the risk of hospitalization than their matched controls without DM (IRR 8.47 [5.86–12.24]), whereas for T2DM, this was four times higher (4.31 [3.88–4.80]). […] Patients with T1DM […] had higher rates of hospitalization (1.12 [1.01–1.24]) and death as a result of infection (1.42 [1.03–1.96]) than patients with T2DM, even after accounting for duration of DM.”

“In terms of the overall population effect, almost one-half of bone and joint infections among patients with DM were attributed to poor control. […] The most novel and concerning finding is the substantial proportion of other serious infections statistically attributable to poor glycemic control, particularly endocarditis, tuberculosis, and sepsis. Between 20 and 30% of these infections in the English DM population could be attributed to poor control. […] [W]e estimated AF% for the three summary groupings […] plus individual infection types […] across HbA_1c categories for patients with DM compared with the optimal control scenario of 6–7%. The largest AF% estimate was for bone and joint infections, with 46.0% of hospitalizations being attributed to HbA_1c values outside of the range 6–7%. Other large AF% estimates were observed for endocarditis (26.2%) and tuberculosis (23.7%), but CIs were wide. Sepsis (20.8%), pneumonia (15.3%), skin infections (cellulitis 14.0%, other 12.1%), and candidiasis (16.5%) all produced AF% estimates of ≥10%. Overall, 15.7% of infection-related deaths, 16.5% of infection-related hospitalizations, and 6.8% of infections requiring a prescription were attributed to values of HbA_1c outside the 6–7% range.”

“Prevalence of diagnosed T2DM has tripled in the U.K. over the past 20 years (17). Although some improvements in glycemic control also have been observed over this period, our analyses show that substantial numbers of patients still have very poor glycemic control (e.g., 16% of patients with T2DM and 41% of patients with T1DM had a mean HbA_1c >9%). […] 14% of patients with DM in the current study were hospitalized for infection during follow-up […] The U.K. has a relatively low prevalence of DM and good control on the basis of international comparisons (18); therefore, in many low- and middle-income countries, the burden of infections attributable to poor glycemic control could be substantially higher (19).”

“A variety of mechanisms may link DM and hyperglycemia with infection response (1,20–22). Diabetes progression itself is associated with immune dysfunction; autoimmunity in T1DM and low-grade chronic inflammation in T2DM (1). Hyperglycemia may also have adverse effects on several types of immune cells (19,23); alter cytokine and chemokine gene expression (24), and inhibit effects of complement (25). Other important mechanisms may include peripheral diabetic neuropathy because this results in a loss of sensation and reduced awareness of minor injuries (13). Alongside ischemia, often as a result of related peripheral arterial disease, neuropathy can result in impaired barrier defenses, skin ulcers, and lesions with poor wound healing and an increased risk of secondary infections (19). Although numerous mechanisms exist, nearly all involve poor glycemic control. Thus, that improved control would reduce infections seems likely […] Overall, the current analyses demonstrate a strong and likely causal association between hyperglycemia and infection risk for both T1DM and T2DM. DM duration and other markers of severity cannot explain the increased risk, nor can longer duration explain the increased risk for T1DM compared with T2DM. This remains the case in older people in whom infections are common and often severe and more uncertainty exists about the vascular benefits of improving DM control. Substantial proportions of serious infections can be attributed to poor control, even though DM is managed well in the U.K. by international standards. Interventions to reduce infection risk largely have been ignored by the DM community and should be a high priority for future research.”

…

ii. Poor Metabolic Control in Children and Adolescents With Type 1 Diabetes and Psychiatric Comorbidity. Some observations from the paper:

“Type 1 diabetes in childhood has been found to be associated with an increased risk of psychiatric comorbidities (1–3), which might intensify the burden of disease and accelerate metabolic deterioration (4–6), subsequently increasing the risk of mortality and long-term complications such as retinopathy, nephropathy, and neuropathy (7–9).

Metabolic dysregulation is closely linked to age and diabetes duration, showing a peak in adolescence and early adulthood (10,11). Early adolescence is also characterized as a time of psychological vulnerability (12), in which the incidence of major psychiatric disorders increases (13). A diagnosis of type 1 diabetes in early adolescence seems to increase psychological distress (1,2), and three large population-based studies have shown higher rates of psychiatric disorders in children and adolescents with type 1 diabetes compared with the general population (1–3). In particular, increased risk was seen for depression, anxiety, and eating disorders, where the pathogenesis is considered to involve reactive mechanisms and imbalances in the diathesis-stress system (1–3,14).”

“Despite clinical and research evidence that a child with type 1 diabetes often receives more than one psychiatric diagnosis (1,3), most studies evaluate one disorder at a time (4–6,16–20). Motivated by findings that Danish children and adolescents with type 1 diabetes have a higher risk of developing a psychiatric disorder compared with the background population (2), we performed two studies based on the NPR and the Danish Registry of Childhood and Adolescent Diabetes (DanDiabKids). […] The NPR contains psychiatric and somatic diagnoses from all inpatient admissions to Danish public hospitals since 1977. […] The register has used the ICD-10 since 1994 (22,23). Data on registration of psychiatric and type 1 diabetes diagnoses were collected from the NPR, covering 1996 to April 2015. DanDiabKids collects information on all children and adolescents diagnosed with type 1 diabetes before the age of 15 years and monitors them until they are transferred to adult clinics at ∼18 years of age. All public hospital pediatric units must supply annual data on all patients with diabetes to DanDiabKids. […] DanDiabKids contains annual data on all registered patients since 1996, including information on quality indicators, demographic variables, associated conditions, diabetes classification, diabetes family history, growth, self-management, and treatment variables. DanDiabKids now covers 99% of all Danish children and adolescents diagnosed with type 1 diabetes before the age of 15 years. […] Our study population was generated by merging data from DanDiabKids and the NPR. The inclusion criteria were registration with type 1 diabetes in DanDiabKids, age at onset <15 years, year of onset 1995–2014, and year of birth after 1980.”

“After merging DanDiabKids with the NPR, 4,725 children and adolescents with type 1 diabetes were identified […]. Characteristics for the included subjects were as follows: mean age at onset of diabetes was 8.98 years (SD 3.81), birth year ranged from 1980 to 2013, mean age at last visit was 14.6 years (3.7), 2,462 (52.1%) were boys, mean duration of diabetes at last visit was 5.65 years (3.7), 4,434 (93.8%) were of Danish origin, 254 (5.4%) were immigrants or offspring of immigrants, and 36 (0.8%) had unknown ethnicity. […] The observed number of SH [severe hypoglycemia, US] and DKA events per 100 person-years was respectively 10.7 (SH) and 3.2 (DKA) in patients with neurodevelopmental/constitutional psychiatric disorder, 12.1 (SH) and 3.7 (DKA) in patients with potentially reactive psychiatric disorder, 12.3 (SH) and 6.4 (DKA) in patients with both types of psychiatric disorders, and 8.1 (SH) and 1.8 (DKA) in patients without psychiatric disorder. […] Among the 4,725 children and adolescents included in the study, 1,035 were diagnosed with at least one psychiatric disorder at some point. Of these, a total of 175 received their first psychiatric diagnosis before the onset of type 1 diabetes, 575 during pediatric care, and 285 were diagnosed after referral to adult care. […] Anxiety disorders were the most common (n = 492), followed by “behavioral and emotional disorders” (n = 310), mood disorders (n = 205), psychoactive substance misuse disorders (n = 190), and disorders of inattention and hyperactivity (ADHD/attention-deficit disorder [ADD]) (n = 172). Of the 1,035 patients, 46% were diagnosed with two or more psychiatric disorders and 22.8% were diagnosed with three or more psychiatric disorders.”

“Shortly after type 1 diabetes diagnosis, a higher estimated risk of psychiatric disorders was evident among patients who were 10–15 years old at onset of type 1 diabetes. However, after 15–20 years with diabetes, the differences among the groups leveled out at a risk of ∼30% […] Children with high mean HbA_1c levels (>8.5% [>70 mmol/mol]) during the first 2 years showed the highest estimated risk of developing a psychiatric disorder, although these differences also appear to level out after 15–20 years with type 1 diabetes. […] The mean HbA_1c level was higher in children with a psychiatric disorder (0.22% [95% CI 0.15; 0.29]; 2.45 mmol/mol [1.67; 3.22]) compared with children with no psychiatric disorder (P < 0.001) […] High HbA_1c levels in the early period after type 1 diabetes onset seem to be a possible indicator for subsequent psychiatric disorders, and having a psychiatric disorder was associated with higher HbA_1c levels, especially in patients with disorders of putative reactive pathogenesis. Given that the Kaplan-Meier plots showed that the estimated risk of being diagnosed with a psychiatric disorder within a period of 15–20 years of type 1 diabetes onset was close to 30% in most groups, our finding highlights an important clinical problem.”

“The estimated risk of developing a psychiatric disorder during the 15–20 years after type 1 diabetes diagnosis is high. The most vulnerable period appeared to be adolescence. Patients with poorly regulated diabetes shortly after onset had a higher estimated risk of developing psychiatric comorbidities. Young patients diagnosed with a psychiatric disorder had more episodes of DKA, and those diagnosed within the reactive spectrum had higher HbA_1c levels. Children and adolescents with type 1 diabetes, and in particular those who fail to reach treatment goals, should be systematically evaluated regarding psychological vulnerabilities.”

…

iii. Development of Microvascular Complications and Effect of Concurrent Risk Factors in Type 1 Diabetes: A Multistate Model From an Observational Clinical Cohort Study.

“The prevalence of type 1 diabetes has increased over the past decades (1,2). Increased life expectancy means that people live longer with diabetes (3–5); thus, potentially more years are lived with both macrovascular and microvascular complications (6,7). Type 1 diabetes is a complex disease, which develops in various complication states, and co-occurrence of multiple microvascular complications frequently is seen (8). So far, most studies are of a single complication, and the association between the worsening of one complication and the incidence of another is well described, although independently of other complications (9,10). At the same time, a sizeable group of individuals seems to be protected from microvascular complications (11–14), and some live several decades with type 1 diabetes without developing complications. Advanced statistical models, such as multistate models, offer an opportunity to explore the transition through various disease states and to quantify progression rates while considering the concurrent complication burden (15,16), that is, the complication burden at a given time point in the observation window.

Strong evidence indicates that some risk factors play a role in all types of microvascular complications. For example, the effects of the duration of diabetes and poor glycemic control are well documented (17–20). For other risk factors, such as hypertension, an association has been established mainly for retinopathy and diabetic kidney disease (21,22). Adverse cholesterol levels and previous cardiovascular disease (CVD) are indisputably associated with a higher risk of macrovascular complications (23) and may play a role in the development of microvascular complications (24). […] The complex interplay between microvascular complications and risk factors has been explored only to a limited extent. In this study, we developed a multistate model of microvascular complications to describe in detail complication development in type 1 diabetes. We describe the development of sequences of diabetes-related microvascular complications at various states and examine the associations between selected risk factors, both alone and combined with existing complication burden, and incidence of (further) microvascular complications.”

“In total, 5,031 individuals with type 1 diabetes were registered at the SDCC during the study period. We excluded 1,203 because of missing data for diabetic kidney disease, retinopathy, and/or neuropathy, which left 3,828 eligible individuals to be included in the study. Of these, 242 were first seen in the final state with three complications, which left 3,586 available for analysis, corresponding to 22,946 person-years (PY) […] The median follow-up time was 7.8 years (25th–75th percentile 3.3–10.7 years). HbA_1c level at the end of follow-up was lower than at entry, whereas the levels of blood pressure, lipids, and BMI were unchanged. An increase in the use of all cardioprotective medications was observed.”

“We identified 523 individuals who developed diabetic kidney disease during the study. Of these, 84 events occurred in individuals with no complications (IR 12.9 per 1,000 PY), 221 in individuals with retinopathy (25.7 per 1,000 PY), 27 in individuals with neuropathy (36.6 per 1,000 PY), and 191 in individuals with both neuropathy and retinopathy (61.8 per 1,000 PY). […] In the adjusted model, individuals with both retinopathy and neuropathy had a threefold higher risk of diabetic kidney disease than individuals without complications. […] A total of 482 individuals developed neuropathy during follow-up. Of these, 75 incidents occurred in individuals with no complications (IR 11.5 per 1,000 PY), 14 in individuals with diabetic kidney disease (20.6 per 1,000 PY), 234 in individuals with retinopathy (27.2 per 1,000 PY), and 159 in individuals with both retinopathy and diabetic kidney disease (50.2 per 1,000 PY). Individuals with both retinopathy and diabetic kidney disease had a 70% higher risk of developing neuropathy than individuals without complications […] In total, we recorded 649 individuals with incident retinopathy from any previous complication state. Of these, 459 incidents occurred in individuals with no complications (IR 70.7 per 1,000 PY), 74 in individuals with diabetic kidney disease (109.1 per 1,000 PY), 71 in individuals with neuropathy (96.6 per 1,000 PY), and 45 in individuals with both neuropathy and diabetic kidney disease (224.7 per 1,000 PY). Individuals with both diabetic kidney disease and neuropathy had a twofold higher IRR of developing retinopathy than individuals without complications”.

“Baseline and concurrent values of HbA_1c, systolic blood pressure, eGFR, and baseline CVD status were all strongly associated with a higher risk of developing diabetic kidney disease. […] The analysis that included complication state revealed that individuals without any other complications than CVD had an almost three times higher risk of diabetic kidney disease than individuals without either CVD or microvascular complications. […] Duration of diabetes, baseline and concurrent value of HbA_1c, systolic blood pressure, and baseline LDL cholesterol values were all factors associated with a higher risk of developing retinopathy. None of the effects of the modifiable risk factors on retinopathy were modified by complication burden. […] men with diabetic kidney disease had a higher risk of developing retinopathy than women with diabetic kidney disease. […] All investigated risk factors, except LDL cholesterol, were associated with incidence of neuropathy at both baseline and concurrent levels.”

“[W]e conducted a sensitivity analysis with retinopathy defined as severe nonproliferative or proliferative retinopathy. The prevalence and incidence of retinopathy were much lower, but all associations were similar to the main analysis […]. We found no effect modification by lipid-lowering or antihypertensive treatment. […] We found a stepwise higher risk of any microvascular complication in individuals with higher concurrent complication burden. Baseline and concurrent HbA_1c levels, systolic blood pressure, and duration of diabetes were associated with the development of all three microvascular complications. For most risk factors, we did not find evidence that concurrent complication burden modified the association with complication development. […] Concurrent HbA_1c level was a strong risk factor for all microvascular complications, even when we adjusted for age, duration, and other traditional risk factors. The overall effects were of similar magnitude to the effect of baseline levels of HbA_1c and to other reports (11,29).”

“The presented results are interpreted in the frame of a multistate model design, and the use of clinical data makes the results highly relevant in similar health care settings. However, because of the observational study design, we cannot draw conclusions about causality. The positive associations among complications might reflect that diabetic kidney disease takes the longest time to develop, whereas retinopathy and neuropathy develop faster. Associations of two disease complications to a third might not be causal. However, that the risk of a third complication, even after adjustment for multiple confounders, is higher regardless of the previous combination of complications indicates that an association cannot be explained by these risk factors alone. In addition, concurrent risk factor levels may be subject to reverse causality. The current results should be seen as a benchmark for others who aim to explore the occurrence of microvascular complications as a function of the concurrent total complication burden in individuals with type 1 diabetes. […] The findings demonstrate that high concurrent complication burden elevates the risk of all three investigated microvascular complications: diabetic kidney disease, retinopathy, and neuropathy. This means that if an individual develops a complication, the clinician should be aware of the increased risk of developing more complications. […] For most risk factors, including HbA_1c, we found no evidence that the effect on the development of microvascular complications was modified by the burden of concurrent complications.”

…

iv. Long-term Glycemic Control and Dementia Risk in Type 1 Diabetes.

“[P]rior work has established type 1 diabetes as a risk factor for dementia (15). However, the relationship between glycemic control and subsequent risk of dementia in those with type 1 diabetes remains unclear. Hemoglobin A_1c (HbA_1c) is an established measure that integrates glucose control over the prior 2–3 months and is widely used to guide clinical management of type 1 diabetes (16,17). Cumulative glycemic exposure, as measured by multiple HbA_1c measures over time, has previously been used to evaluate glycemic trajectories and their association with a number of diabetes complications (18,19). Electronic health records capture HbA_1c values collected over time allowing for a more thorough long-term characterization of glycemic exposure than is reflected by a single HbA_1c measure. In this study, we leverage data [from northern California, US] collected over a span of 19 years to examine the association of cumulative glycemic exposure, as measured by repeated HbA_1c values, with incident dementia among older adults with type 1 diabetes. We also examine the potential for a threshold of glycemic exposure above or below which risk of dementia increases.”

“The final analytic cohort consisted of 3,433 individuals (mean age at cohort entry = 56.1 years old; 47.1% female) […]. On average, individuals who developed dementia during follow-up were older at cohort entry (64.4 vs. 55.7 years) and were more likely to have a history of stroke (7.7% compared with 3.5%) at baseline. The mean follow-up time was 6.3 years (median 4.8 years [interquartile range (IQR) 1.7, 9.9]), and the mean number of HbA_1c measurements was 13.5 (median 9.0 [IQR 3.0, 20.00]). By the end of follow-up on 30 September 2015, 155 members (4.5%) were diagnosed with dementia, 860 (25.1%) had a lapse of at least 90 days in membership coverage, 519 (15.1%) died without a dementia diagnosis, and 1,899 (55.3%) were still alive without dementia diagnosis. Among the 155 members who developed dementia over follow-up, the mean age at dementia diagnosis was 64.6 years (median 63.6 years [IQR 56.1, 72.3]).”

“In Cox proportional hazards models, dementia risk was higher in those with increased exposure to HbA_1c 8–8.9% (64–74 mmol/mol) and ≥9% (≥75 mmol/mol) and lower in those with HbA_1c 6–6.9% (42–52 mmol/mol) and 7–7.9% (53–63 mmol/mol). In fully adjusted models, compared with those with minimal exposure (<10% of HbA_1c measurements) to HbA_1c 8–8.9% and ≥9%, those with prolonged exposure (≥75% of measurements) were 2.51 and 2.13 times more likely to develop dementia, respectively (HbA_1c 8–8.9% fully adjusted hazard ratio [aHR] 2.51 [95% CI 1.23, 5.11] and HbA1c ≥9% aHR 2.13 [95% CI 1.13, 4.01]) […]. In contrast, prolonged exposure to HbA_1c 6–6.9 and 7–7.9% was associated with a 58% lower and 61% lower risk of dementia, respectively (HbA_1c 6–6.9% aHR 0.42 [95% CI 0.21, 0.83] and HbA_1c 7–7.9% aHR 0.39 [95% CI 0.18, 0.83]). […] Results were similar in Cox models examining cumulative glycemic exposure based on whether a majority (>50%) of an individual’s available HbA_1c measurements fell into the following categories of HbA_1c: <6, 6–6.9, 7–7.9, 8–8.9, and ≥9% […]. Majority exposure to HbA_1c 8–8.9 and ≥9% was associated with an increased risk of dementia (HbA_1c 8–8.9% aHR 1.65 [95% CI 1.06, 2.57] and HbA_1c ≥9% aHR 1.79 [95% CI 1.11, 2.90]), while majority exposure to HbA_1c 6–6.9 and 7–7.9% was associated with a reduced risk of dementia (HbA_1c 6–6.9% aHR 0.55 [95% CI 0.34, 0.88] and HbA_1c 7–7.9% aHR 0.55 [95% CI 0.37, 0.82]). Majority exposure to HbA_1c <6% (<42 mmol/mol) was associated with increased dementia risk in age-adjusted models (HR 2.06 [95% CI 1.11, 3.82]), though findings did not remain significant in fully adjusted models (aHR 1.45 [95% CI 0.71, 2.92]). Findings were similar in sensitivity analyses among the subset of members who were ≥65 years of age at baseline (n = 1,082 [32% of the sample]), though the increased risk associated with majority time at HbA_1c ≥9% was no longer statistically significant”.

“In this large sample of older adults with type 1 diabetes, we found that cumulative exposure to higher levels of HbA_1c (8–8.9 and ≥9%) was associated with an increased risk of dementia, while cumulative exposure to well-controlled HbA_1c (6–6.9 and 7–7.9%) was associated with a decreased risk of dementia. In fully adjusted models, compared with those with minimal exposure to HbA_1c 8–8.9% and HbA_1c ≥9%, those with prolonged exposure were more than twice as likely to develop dementia over the course of follow-up […]. By contrast, dementia risk was ∼60% lower among those with prolonged exposure to well-controlled HbA_1c (6–6.9 and 7–7.9%) compared with those with minimal time at well-controlled levels of HbA_1c.”

“Our results complement and extend previous studies that have reported an association between chronic hyperglycemia and decreased cognitive function in children and adolescents with type 1 diabetes (25,26), as well as studies reporting an association between poor glycemic control and decreased cognitive functioning in middle-aged adults with type 1 diabetes and older adults with type 2 diabetes (7–11). Our findings are also consistent with previous studies that found an increased dementia risk associated with poorer glycemic control among adults with type 2 diabetes and adults without diabetes (11–13). Whether these findings applied to dementia risk among older adults with type 1 diabetes was previously unknown.”

“In our study of 3,433 older adults with type 1 diabetes, 155 (4.5%) individuals developed dementia over an average of 6.3 years of follow-up. Among those who developed dementia, the average age at dementia diagnosis was 64.6 years. A large-scale study using administrative health data from 1998 to 2011 in England reported a similar incidence of dementia among a subset of adults aged ≥50 years with type 1 diabetes (3.99% developed dementia), though the average length of follow-up was not reported for this specific age-group (15). Prior studies have also found type 1 diabetes to be a risk factor for dementia (15) and have reported the average age at onset of dementia to be 2–5 years earlier in those with diabetes compared with those without diabetes (27,28). Taken together, these results provide further evidence that older adults with type 1 diabetes are at increased risk of developing dementia and may have increased risk at younger ages than the general population. Our results, however, suggest that effective glycemic control could be an important tool for reducing risk of dementia among older adults with type 1 diabetes.”

“Pathophysiological mechanisms by which glycemic control may affect dementia risk are still poorly understood but are hypothesized to result from structural brain abnormalities stemming from chronic exposure to hyperglycemia and/or recurrent severe hypoglycemia. Studies in adults and youth with type 1 diabetes have reported an association between chronic hyperglycemia (defined using lifetime HbA_1c history and using retinopathy as an indicator of chronic exposure) and gray matter density loss (35–37). Studies examining the association between severe hypoglycemic events and changes in brain structure have been less consistent, with some reporting increased gray matter density loss and a higher prevalence of cortical atrophy in those with a history of frequent exposure to severe hypoglycemia (36,38), while another study reported no association (37). In the ACCORD MIND (Action to Control Cardiovascular Risk in Diabetes Memory in Diabetes) trial, compared with standard glycemic control, intensive glycemic control was associated with greater total brain volume, suggesting that intensive glycemic control may reduce brain atrophy related to diabetes (39). […] Understanding why glycemic patterns are associated with dementia is a much-needed area for future study, particularly with regard of the potential role of intercurrent micro- and macrovascular complications.”

…

v. A Comparison of the 2017 American College of Cardiology/American Heart Association Blood Pressure Guideline and the 2017 American Diabetes Association Diabetes and Hypertension Position Statement for U.S. Adults With Diabetes.

“Hypertension is one of the most common comorbidities among adults with diabetes. Prior studies have estimated the prevalence of hypertension to be twice as high among adults with diabetes compared with age-matched control subjects without diabetes (1,2). Among adults with diabetes, the presence of hypertension has been associated with a two times higher risk for cardiovascular disease (CVD) events and mortality (3,4).

The 2017 American College of Cardiology (ACC)/American Heart Association (AHA) Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults provides a comprehensive set of recommendations for the diagnosis and treatment of hypertension among adults, including those with diabetes (5). This guideline defines hypertension in adults, including those with diabetes, as an average systolic blood pressure (SBP) ≥130 mmHg or diastolic blood pressure (DBP) ≥80 mmHg […]. According to this guideline, pharmacological antihypertensive treatment should be initiated in adults with diabetes if they have an average SBP ≥130 mmHg or DBP ≥80 mmHg, and the treatment goal is SBP <130 mmHg and DBP <80 mmHg (5).

The American Diabetes Association (ADA) published a position statement on diabetes and hypertension in 2017 that recommends blood pressure (BP) levels different from the ACC/AHA guideline for defining hypertension and for initiating pharmacological antihypertensive treatment (for both, SBP ≥140 mmHg or DBP ≥90 mmHg) (6). The ADA position statement recommends that BP goals should be individualized based on patient priorities and clinician judgment. Treatment goals for those taking antihypertensive medication are SBP <140 mmHg and DBP <90 mmHg, with SBP <130 mmHg and DBP <80 mmHg to be considered for those with high CVD risk as long as these levels can be achieved without undo treatment burden.

The purpose of the current study was to estimate the impact of differences in the definition of hypertension and recommendations for pharmacological antihypertensive treatment initiation and intensification of therapy in U.S. adults with diabetes according to the ACC/AHA guideline and the ADA diabetes and hypertension position statement (5,6). To accomplish these goals, we analyzed data from the U.S. National Health and Nutrition Examination Survey (NHANES).”

“According to data from NHANES 2011–2016, 56.6% (95% CI 53.3, 59.9) of U.S. adults with diabetes were taking antihypertensive medication. Of U.S. adults with diabetes, 57.4% (53.1, 61.6) of those not taking and 80.2% (76.6, 83.4) of those taking antihypertensive medication had high CVD risk. Among U.S. adults with diabetes, those with high CVD risk (history of CVD or 10-year ASCVD risk ≥10%) were on average 15–20 years older and the prevalence of smoking and chronic kidney disease was 10–20% higher when compared with their counterparts without high CVD risk […]. Among U.S. adults with diabetes without high CVD risk, the mean 10-year and 30-year predicted CVD risks were 3.8% (3.5, 4.2) and 25.0% (23.4, 26.6), respectively, for those not taking antihypertensive medication and 5.8% (5.3, 6.4) and 37.4% (34.5, 40.3), respectively, for those taking antihypertensive medication.

The prevalence of hypertension was 77.1% (95% CI 73.9, 80.0) according to the ACC/AHA guideline and 66.3% (63.4, 69.1) according to the ADA position statement […]. Overall, 10.8% (9.0, 12.8) of U.S. adults with diabetes had hypertension according to the ACC/AHA guideline but not the ADA position statement. Among U.S. adults with diabetes not taking antihypertensive medication, 52.8% (47.7, 57.8), 24.8% (20.6, 29.6) and 22.4% (19.2, 25.9) were recommended antihypertensive medication initiation by neither document, by the 2017 ACC/AHA guideline only, and by both documents, respectively […]. Among U.S. adults with diabetes taking antihypertensive medication, 45.3% (41.3, 49.4), 4.3% (2.8, 6.6), and 50.4% (46.5, 54.2) had an average BP that met the goal in both documents, was above the ACC/AHA goal but not the ADA goal, and was above the goals in both documents, respectively […] The overall agreement between the ACC/AHA guideline and the ADA position statement was 89.2% (87.2, 91.0) for the presence of hypertension, 75.2% (70.4, 79.4) for the recommendation to initiate antihypertensive medication, and 95.7% (93.4, 97.2) for having a BP above the recommended treatment goal. “

“Based on both the ACC/AHA guideline and ADA position statement, 17.8 (95% CI 16.2, 19.3) million U.S. adults with diabetes had hypertension […]. An additional 2.9 (2.3, 3.5) million U.S. adults had hypertension based on the ACC/AHA guideline only. Among U.S. adults with diabetes not taking antihypertensive medication, 2.6 (2.1, 3.1) million were recommended to initiate antihypertensive medication by both the ACC/AHA guideline and the ADA position statement with an additional 2.9 (2.3, 3.5) million recommended to initiate antihypertensive medication by the ACC/AHA guideline only […]. Among U.S. adults with diabetes taking antihypertensive medication, 7.6 (6.8, 8.5) million had a BP above the goal in both documents, with an additional 700,000 (400,000, 900,000) having a BP above the goal recommended in the ACC/AHA guideline only […]. Among U.S. adults with diabetes not taking antihypertensive medication, the mean 10-year CVD risk was 10.7% (95% CI 9.4, 12.0) for those not recommended treatment initiation by either the ACC/AHA guideline or the ADA position statement, 14.6% (11.5, 17.6) for those recommended treatment initiation by the ACC/AHA guideline but not the ADA position statement, and 23.2% (19.5, 27.0) among those recommended treatment initiation by the ACC/AHA guideline and the ADA position statement […]. The mean 30-year CVD risk exceeded 25% in each of these groups. Among U.S. adults with diabetes taking antihypertensive medication, the mean 10-year CVD risk was 10.6% (9.4, 12.0), 6.5% (CI 5.6, 7.3), and 33.8% (32.1, 35.5) among those with above-goal BP according to neither document, the ACC/AHA guideline only, and both documents, respectively […]. The 30-year CVD risk exceeded 40% in each group.”

“In conclusion, the current study demonstrates a high degree of concordance between the 2017 ACC/AHA BP guideline and the 2017 ADA position statement on diabetes and hypertension. Using either document, the majority of U.S. adults with diabetes have hypertension. A substantial proportion of U.S. adults with diabetes not taking antihypertensive medication are recommended to initiate treatment by both documents […] Among U.S. adults with diabetes not taking antihypertensive medication, 75.2% had an identical recommendation for initiation of antihypertensive drug therapy according to the ACC/AHA guideline and the ADA position statement. The majority of those who were recommended to initiate pharmacological antihypertensive therapy according to the ACC/AHA guideline but not the ADA position statement had high CVD risk. […] At the population level, the ACC/AHA guideline and ADA position statement have more similarities than differences. However, at the individual level, some patients with diabetes will have fundamental changes in their care depending on which advice is followed. The decision to initiate and intensify antihypertensive medication should always be individualized, based on discussions between patients and their clinicians. Both the ACC/AHA BP guideline and ADA position statement acknowledge the need to individualize treatment decisions to align with patients’ interests.”

…

vi. Treatment-induced neuropathy of diabetes: an acute, iatrogenic complication of diabetes.

“Treatment-induced neuropathy in diabetes (also referred to as insulin neuritis) is considered a rare iatrogenic small fibre neuropathy caused by an abrupt improvement in glycaemic control in the setting of chronic hyperglycaemia. The prevalence and risk factors of this disorder are not known. In a retrospective review of all individuals referred to a tertiary care diabetic neuropathy clinic over 5 years, we define the proportion of individuals that present with and the risk factors for development of treatment-induced neuropathy in diabetes. Nine hundred and fifty-four individuals were evaluated for a possible diabetic neuropathy. Treatment-induced neuropathy in diabetes was defined as the acute onset of neuropathic pain and/or autonomic dysfunction within 8 weeks of a large improvement in glycaemic control—specified as a decrease in glycosylated haemoglobin A1C (HbA1c) of ≥2% points over 3 months. Detailed structured neurologic examinations, glucose control logs, pain scores, autonomic symptoms and other microvascular complications were measured every 3–6 months for the duration of follow-up. Of 954 patients evaluated for diabetic neuropathy, 104/954 subjects (10.9%) met criteria for treatment-induced neuropathy in diabetes with an acute increase in neuropathic or autonomic symptoms or signs coinciding with a substantial decrease in HbA1c. Individuals with a decrease in HbA1c had a much greater risk of developing a painful or autonomic neuropathy than those individuals with no change in HbA1c (P < 0.001), but also had a higher risk of developing retinopathy (P < 0.001) and microalbuminuria (P < 0.001). There was a strong correlation between the magnitude of decrease in HbA1c, the severity of neuropathic pain (R = 0.84, P < 0.001), the degree of parasympathetic dysfunction (R = −0.52, P < 0.01) and impairment of sympathetic adrenergic function as measured by fall in blood pressure on tilt-table testing (R = −0.63, P < 0.001). With a decrease in HbA1c of 2–3% points over 3 months there was a 20% absolute risk of developing treatment-induced neuropathy in diabetes, with a decrease in HbA1c of >4% points over 3 months the absolute risk of developing treatment-induced neuropathy in diabetes exceeded 80%. Treatment-induced neuropathy of diabetes is an underestimated iatrogenic disorder associated with diffuse microvascular complications. Rapid glycaemic change in patients with uncontrolled diabetes increases the risk of this complication.”

“Typically, individuals with TIND reported the onset of severe burning pain (pain scores 4–10/10) within 2–6 weeks of the improvement in glucose control. Burning pain was present in all subjects with TIND. Paraesthesias were present in 93/104 subjects and shooting pain in 88/104 subjects. Hyperalgesia and allodynia were common in the distribution of the pain. […] Individuals with TIND all reported ongoing sleep disturbances typically described as difficulty with sleep initiation and sleep duration secondary to neuropathic pain. These individuals reported no record of sleep problems prior to the development of TIND. […] Erectile dysfunction was noted in 28/31 males with TIND, compared to 135/417 males without TIND (P < 0.001, X²). […] Seventy-three individuals completed autonomic testing within 2–5 months of the onset of neuropathic pain. […] The results for both groups, in all tests, were abnormal compared to age-related normative values. There were strong correlations between the magnitude of decrease in HbA1c over 3 months and worsening autonomic function. A greater change in HbA1c resulted in worsening parasympathetic function as determined by the expiratory to inspiratory ratio (R = −0.52, P < 0.01) and the Valsalva ratio (R = −0.55, P < 0.01). Greater sympathetic adrenergic dysfunction also correlated with a greater change in HbA1c over 3 months as determined by the fall in systolic blood pressure during tilt-table test (R = −0.63, P < 0.001), the fall in blood pressure during phase 2 of the Valsalva manoeuvre (R = 0.49, P < 0.001), and the diminished phase 4 blood pressure overshoot during the Valsalva manoeuvre (R = −0.59, P < 0.001). […] individuals with type 1 diabetes had greater autonomic dysfunction than those with type 2 diabetes across all tests. The slopes of the regression lines describing the correlation between the change in HbA1c and a particular autonomic test did not differ by the type of diabetes, or by the type of treatment used to control glucose.”

“Most patients with TIND had rapid progression of retinopathy that developed in conjunction with the onset of neuropathic pain […] Prior to development of TIND, 65/104 individuals had no retinopathy, 35/104 had non-proliferative retinopathy, whereas 4/104 had proliferative retinopathy. Twelve months after the development of TIND, 10/104 individuals had no retinopathy, 54/104 had non-proliferative retinopathy and 40/104 had proliferative retinopathy (P < 0.001, Fisher’s exact test). Prior to development of TIND, 18/104 had evidence of microalbuminuria, while 12 months after the development of TIND, 87/104 had evidence of microalbuminuria (P < 0.001, X²).”

“TIND is a small fibre and autonomic neuropathy that appears after rapid improvements in glucose control. In this manuscript, we demonstrate that: (i) there is an unexpectedly high proportion of individuals with TIND in a tertiary referral diabetic clinic; (ii) the risk of developing TIND is associated with the magnitude and rate of change in HbA1c; (iii) neuropathic pain and autonomic dysfunction severity correlate with the magnitude of change in HbA1c; (iv) patients with Type 1 diabetes and a history of eating disorders are at high risk for developing TIND; and (v) TIND can occur with use of insulin or oral hypoglycaemic agents. […] TIND differs from the most prevalent generalized neuropathy of diabetes, the distal sensory-motor polyneuropathy, in several respects. The neuropathic pain has an acute onset, appearing within 8 weeks of glycaemic change, in contrast with the more insidious onset in the distal sensory-motor polyneuropathy […]. The pain in TIND is more severe, and poorly responsive to interventions including opioids, whereas most patients with distal sensory-motor polyneuropathy respond to non-opioid interventions […]. Although the distribution of the pain is length-dependent in individuals with TIND, it is frequently far more extensive than in distal sensory-motor polyneuropathy and the associated allodynia and hyperalgesia are much more prevalent […]. Autonomic symptoms and signs are common, prominent and appear acutely, in contrast to the relatively lower prevalence, gradual onset and slow progression in distal sensory-motor polyneuropathy […]. Finally, both the pain and autonomic features may be reversible in some patients […].

Our data indicate that the severity of TIND is associated with the magnitude of the change of HbA1c, however, it is also clear that the rate of change is important (e.g. a 4% point fall in the HbA1c will have a greater impact if occurring over 3 months than over 6 months). The pathogenic mechanisms whereby this change in glucose results in nerve damage and/or dysfunction are not known. Proposed mechanisms include endoneurial ischaemia due to epineurial arterio-venous shunts […], apoptosis due to glucose deprivation […], microvascular neuronal damage due to recurrent hypoglycaemia […], and ectopic firing of regenerating axon sprouts, but these possibilities are unproven. […] Additional mechanistic studies are necessary to determine the underlying pathophysiology.”

Oncology (I)

I really disliked the ‘Pocket…’ part of this book, so I’ll sort of pretend to overlook this aspect also in my coverage of the book here. This’ll be a hard thing to do, given the way the book is written – I refer to my goodreads review for details, I’ll include only one illustrative quote from that review here:

“In terms of content, the book probably compares favourably with many significantly longer oncology texts (mainly, but certainly not only, because of the publication date). In terms of readability it compares unfavourably to an Egyptian translation of Alan Sokal’s 1996 article in Social Text, if it were translated by a 12-year old dyslexic girl.”

I don’t yet know in how much detail I’ll blog the book; this may end up being the only post about the book, or I may decide to post a longer sequence of posts. The book is hard to blog, which is an argument against covering it in detail – and also the reason why I haven’t already blogged it – but some of the content included in the book is really, really nice stuff to know, which is a strong argument in favour of covering at least some of the material here. The book has a lot of stuff, so regardless of the level of detail of my future coverage a lot of interesting stuff will of necessity have been left out.

My coverage below includes some observations and links related to the first 100 pages of the book.

…

“Understanding Radiation Response: The 4 Rs of Radiobiology
Repair of sublethal damage
Reassortment of cells w/in the cell cycle
Repopulation of cells during the course of radiotherapy
Reoxygenation of hypoxic cells […]

*Oxygen enhances DNA damage induced by free radicals, thereby facilitating the indirect action of IR [ionizing radiation, US] *Biologically equivalent dose can vary by a factor of 2–3 depending upon the presence or absence of oxygen (referred to as the oxygen enhancement ratio) *Poorly oxygenated postoperative beds frequently require higher doses of RT than preoperative RT [radiation therapy] […] Chemotherapy is frequently used sequentially or concurrently w/radiotherapy to maximize therapeutic benefit. This has improved pt outcomes although also a/w ↑ overall tox. […] [Many chemotherapeutic agents] show significant synergy with RT […] Mechanisms for synergy vary widely: Include cell cycle effects, hypoxic cell sensitization, & modulation of the DNA damage response”.

“Specific dose–volume relationships have been linked to the risk of late organ tox. […] *Dose, volume, underlying genetics, and age of the pt at the time of RT are critical determinants of the risk for 2° malignancy *The likelihood of 2° CA is correlated w/dose, but there is no threshold dose below which there is no additional risk of 2° malignancy *Latent period for radiation-induced solid tumors is generally between 10 and 60 y […]. Latent period for leukemias […] is shorter — peak between 5 & 7 y.”

“The immune system plays an important role in CA surveillance; Rx’s that modulate & amplify the immune system are referred to as immunotherapies […] tumors escape the immune system via loss of molecules on tumor cells important for immune activation […]; tumors can secrete immunosuppressing cytokines (IL-10 & TGF-β) & downregulate IFN-γ; in addition, tumors often express nonmutated self-Ag, w/c the immune system will, by definition, not react against; tumors can express molecules that inhibit T-cell function […] Ubiquitous CD47 (Don’t eat me signal) with ↑ expression on tumor cells mediates escape from phagocytosis. *Tumor microenvironment — immune cells are found in tumors, the exact composition of these cells has been a/w [associated with, US] pt outcomes; eg, high concentration of tumor-infiltrating lymphocytes (CD8+ cells) are a/w better outcomes & ↑ response to chemotherapy, Tregs & myeloid-derived suppressor cells are a/w worse outcomes, the exact role of Th17 in tumors is still being elucidated; the milieu of cytokines & chemokines also plays a role in outcome; some cytokines (VEGF, IL-1, IL-8) lead to endothelial cell proliferation, migration, & activation […] Expression of PD-L1 in tumor microenvironment can be indicator of improved likelihood of response to immune checkpoint blockade. […] Tumor mutational load correlates w/increased response to immunotherapy (NEJM; 2014;371:2189.).”

“Over 200 hereditary CA susceptibility syndromes, most are rare […]. Inherited CAs arise from highly penetrant germline mts [mutations, US]; “familial” CAss may be caused by interaction of low-penetrance genes, gene–environment interactions, or both. […] Genetic testing should be done based on individual’s probability of being a mt carrier & after careful discussion & informed consent”.

“Pharmacogenetics: Effect of heritable genes on response to drugs. Study of single genes & interindividual differences in drug metabolizing enzymes. Pharmacogenomics: Effect of inherited & acquired genetic variation on drug response. Study of the functions & interactions of all genes in the genome & how the overall variability of drug response may be used to predict the right tx in individual pts & to design new drugs. Polymorphisms: Common variations in a DNA sequence that may lead to ↓ or ↑ activity of the encoded gene (SNP, micro- & minisatellites). SNPs: Single nucleotide polymorphisms that may cause an amino acid exchange in the encoded protein, account for >90% of genetic variation in the human genome.”

“Tumor lysis syndrome [TLS] is an oncologic emergency caused by electrolyte abnormalities a/w spontaneous and/or tx-induced cell death that can be potentially fatal. […] 4 key electrolyte abnormalities 2° to excessive tumor/cell lysis: *Hyperkalemia *Hyperphosphatemia *Hypocalcemia *Hyperuricemia (2° to catabolism of nucleic acids) […] Common Malignancies Associated with a High Risk of Developing TLS in Adult Patients [include] *Acute leukemias [and] *High-grade lymphomas such as Burkitt lymphoma & DLBCL […] [Disease] characteristics a/w TLS risk: Rapidly progressive, chemosensitive, myelo- or lymphoproliferative [disease] […] [Patient] characteristics a/w TLS risk: *Baseline impaired renal function, oliguria, exposure to nephrotoxins, hyperuricemia *Volume depletion/inadequate hydration, acidic urine”.

“Hypercalcemia [affects] ~10–30% of all pts w/malignancy […] Symptoms: Polyuria/polydipsia, intravascular volume depletion, AKI, lethargy, AMS [Altered Mental Status, US], rarely coma/seizures; N/V [nausea/vomiting, US] […] Osteolytic Bone Lesions [are seen in] ~20% of all hyperCa of malignancy […] [Treat] underlying malignancy, only way to effectively treat, all other tx are temporizing”.

“National Consensus Project definition: Palliative care means patient and family-centered care that optimizes quality of life by anticipating, preventing, and treating suffering. Palliative care throughout the continuum of illness involves addressing physical, intellectual, emotional, social, and spiritual needs to facilitate patient autonomy, access to information, and choice.” […] *Several RCTs have supported the integration of palliative care w/oncologic care, but specific interventions & models of care have varied. Expert panels at NCCN & ASCO recently reviewed the data to release evidence-based guidelines. *NCCN guidelines (2016): “Palliative care should be initiated by the primary oncology team and then augmented by collaboration with an interdisciplinary team of palliative care experts… All cancer patients should be screened for palliative care needs at their initial visit, at appropriate intervals, and as clinically indicated.” *ASCO guideline update (2016): “Inpatients and outpatients with advanced cancer should receive dedicated palliative care services, early in the disease course, concurrent with active tx. Referral of patients to interdisciplinary palliative care teams is optimal […] Essential Components of Palliative Care (ASCO) *Rapport & relationship building w/pts & family caregivers *Symptom, distress, & functional status mgmt (eg, pain, dyspnea, fatigue, sleep disturbance, mood, nausea, or constipation) *Exploration of understanding & education about illness & prognosis *Clarification of tx goals *Assessment & support of coping needs (eg, provision of dignity therapy) *Assistance w/medical decision making *Coordination w/other care providers *Provision of referrals to other care providers as indicated […] Useful Communication Tips *Use open-ended questions to elicit pt concerns *Clarify how much information the pt would like to know […] Focus on what can be done (not just what can’t be done) […] Remove the phrase “do everything” from your medical vocabulary […] Redefine hope by supporting realistic & achievable goals […] make empathy explicit”.

…

Some links:

Radiation therapy.
Brachytherapy.
External beam radiotherapy.
Image-guided radiation therapy.
Stereotactic Radiosurgery.
Total body irradiation.
Cancer stem cell.
Cell cycle.
Carcinogenesis. Oncogene. Tumor suppressor gene. Principles of Cancer Therapy: Oncogene and Non-oncogene Addiction.
Cowden syndrome. Peutz–Jeghers syndrome. Familial Atypical Multiple Mole Melanoma Syndrome. Li–Fraumeni syndrome. Lynch syndrome. Turcot syndrome. Muir–Torre syndrome. Von Hippel–Lindau disease. Gorlin syndrome. Werner syndrome. Birt–Hogg–Dubé syndrome. Neurofibromatosis type I. -ll- type 2.
Knudson hypothesis.
DNA sequencing.
Cytogenetics.
Fluorescence in situ hybridization.
CAR T Cell therapy.
Antimetabolite. Alkylating antineoplastic agent. Antimicrotubule agents/mitotic inhibitors. Chemotherapeutic agents. Topoisomerase inhibitor. Monoclonal antibodies. Bisphosphonates. Proteasome inhibitors. [The book covers all of these agents, and others I for one reason or another decided not to include, in great detail, listing many different types of agents and including notes on dosing, pharmacokinetics & pharmacodynamics, associated adverse events and drug interactions etc. These parts of the book were very interesting, but they are impossible to blog – US).
Syndrome of inappropriate antidiuretic hormone secretion.
Acute lactic acidosis (“Often seen w/liver mets or rapidly dividing heme malignancies […] High mortality despite aggressive tx [treatment]”).
Superior vena cava syndrome.

100 Cases in Orthopaedics and Rheumatology (II)

Below I have added some links related to the last half of the book’s coverage, as well as some more observations from the book.

…

Scaphoid fracture. Watson’s test. Dorsal intercalated segment instability. (“Non-union is not uncommon as a complication after scaphoid fractures because the blood supply to this bone is poor. Smokers have a higher incidence of non-union. Occasionally, the blood supply is poor enough to lead to avascular necrosis. If non-union is not detected, subsequent arthritis in the wrist can develop.”)
Septic arthritis. (“Septic arthritis is an orthopaedic emergency. […] People with septic arthritis are typically unwell with fevers and malaise and the joint pain is severe. […] Any acutely hot or painful joint is septic arthritis until proven otherwise.”)
Rheumatoid arthritis. (“[RA is] the most common of the inflammatory arthropathies. […] early-morning stiffness and pain, combined with soft-tissue rather than bony swelling, are classic patterns for inflammatory disease. Although […] RA affects principally the small joints of the hands (and feet), it may progress to involve any synovial joint and may be complicated by extra-articular features […] family history [of the disease] is not unusual due to the presence of susceptibility genes such as HLA-DR. […] Not all patients with RA have rheumatoid factor (RF), and not all patients with RF have RA; ACPA has greater specificity for RA than rheumatoid factor. […] Medical therapy focuses on disease-modifying anti-rheumatic drugs (DMARDs) such as methotrexate, sulphasalazine, leflunomide and hydroxychloroquine which may be used individually or in combination. […] Disease activity in RA is measured by the disease activity score (DAS), which is a composite score of the clinical evidence of synovitis, the current inflammatory response and the patient’s own assessment of their health. […] Patients who have high disease activity as determined by the DAS and have either failed or failed to tolerate standard disease modifying therapy qualify for biologic therapy – monoclonal antibodies that are directed against key components of the inflammatory response. […] TNF-α blockade is highly effective in up to 70 per cent of patients, reducing both inflammation and the progressive structural damage associated with severe active disease.”)
Ankylosing spondylitis. Ankylosis. Schober’s index. Costochondritis.
Mononeuritis multiplex. (“Mononeuritis multiplex arises due to interruption of the vasa nervorum, the blood supply to peripheral nerves […] Mononeuritis multiplex is commonly caused by diabetes or vasculitis. […] Vasculitis – inflammation of blood vessels and subsequent obstruction to blood flow – can be primary (idiopathic) or secondary, in which case it is associated with an underlying condition such as rheumatoid arthritis. The vasculitides are classified according to the size of the vessel involved. […] Management of mononeuritis multiplex is based on potent immunosuppression […] and the treatment of underlying infections such as hepatitis.”)
Multiple myeloma. Bence-Jones protein. (“The combination of bone pain and elevated ESR and calcium is suggestive of multiple myeloma.”)
Osteoporosis. DEXA scan. T-score. (“Postmenopausal bone loss is the most common cause of osteoporosis, but secondary osteoporosis may occur in the context of a number of medical conditions […] Steroid-induced osteoporosis is a significant problem in medical practice. […] All patients receiving corticosteroids should have bone protection […] Pharmacological treatment in the form of calcium supplementation and biphosphonates to reduce osteoclast activity is effective but compliance is typically poor.”)
Osteomalacia. Rickets. Craniotabes.
Paget’s disease (see also this post). (“In practical terms, the main indication to treat Paget’s disease is pain […] although bone deformity or compression syndromes (or risk thereof) would also prompt therapy. The treatment of choice is a biphosphonate to diminish osteoclast activity”).
Stress fracture. Female athlete triad. (“Stress fractures are overuse injuries and occur when periosteal resorption exceeds bone formation. They are commonly seen in two main patient groups: soldiers may suffer so-called march fractures in the metatarsals, while athletes may develop them in different sites according to their sporting activity. Although the knee is a common site in runners due to excess mechanical loading, stress fractures may also result in non-weight-bearing sites due to repetitive and excessive traction […]. The classic symptom […] is of pain that occurs throughout running and crucially persists with rest; this is in contrast to shin splints, a traction injury to the tibial periosteum in which the pain diminishes somewhat with continued activity […] The crucial feature of rehabilitation is a graded return to sport to prevent progression or recurrence.”)
Psoriatic arthritis. (“Arthropathy and rash is a common combination in rheumatology […] Psoriatic arthritis is a common inflammatory arthropathy that affects up to 15 per cent of those with psoriasis. […] Nail disease is very helpful in differentiating psoriatic arthritis from other forms of inflammatory arthropathy.”)
Ehlers–Danlos syndromes. Marfan syndrome. Beighton (hypermobility) score.
Carpal tunnel syndrome. (“Carpal tunnel syndrome is the most common entrapment neuropathy […] The classic symptoms are of tingling in the sensory distribution of the median nerve (i.e. the lateral three and a half digits); loss of thumb abduction is a late feature. Symptoms are often worse at night (when the hand might be quite painful) and in certain postures […] The majority of cases are idiopathic, but pregnancy and rheumatoid arthritis are very common precipitating causes […] The majority of patients will respond well to conservative management […] If these measures fail, corticosteroid injection into the carpal tunnel can be very effective in up to 80 per cent of patients. Surgical decompression should be reserved for those with persistent disabling symptoms or motor loss.”)
Mixed connective tissue disease.
Crystal arthropathy. Tophus. Uric acid nephropathy. Chondrocalcinosis. (“In any patient presenting with an acutely painful and swollen joint, the most important diagnoses to consider are septic arthritis and crystal arthropathy. Crystal arthropathy such as gout is more common than septic arthritis […] Gout may be precipitated by diuretics, renal impairment and aspirin use”).
Familial Mediterranean fever. Amyloidosis.
Systemic lupus erythematosus (see also this). Jaccoud arthropathy. Lupus nephritis. (“Renal disease is the most feared complication of SLE.”)
Scleroderma. Raynaud’s phenomenon. (“Scleroderma is an uncommon disorder characterized by thickening of the skin and, to a greater or lesser degree, fibrosis of internal organs.”)
Henoch-Schönlein purpura. Cryoglobulinemia. (“Purpura are the result of a spontaneous extravasation of blood from the capillaries into the skin. If small they are known as petechiae, when they are large they are termed ecchymoses. There is an extensive differential diagnosis for purpura […] The combination of palpable purpura (distributed particularly over the buttocks and extensor surfaces of legs), abdominal pain, arthritis and renal disease is a classic presentation of Henoch–Schönlein purpura (HSP). HSP is a distinct and frequently self-limiting small-vessel vasculitis that can affect any age; but the majority of cases present in children aged 2–10 years, in whom the prognosis is more benign than the adult form, often remitting entirely within 3–4 months. The abdominal pain may mimic a surgical abdomen and can presage intussusception, haemorrhage or perforation. The arthritis, in contrast, is relatively mild and tends to affect the knees and ankles.”)
Rheumatic fever.
Erythema nodosum. (“Mild idiopathic erythema nodosum […] needs no specific treatment”).
Rheumatoid lung disease. Bronchiolitis obliterans. Methotrexate-induced pneumonitis. Hamman–Rich syndrome.
Antiphospholipid syndrome. Sapporo criteria. (“Antiphospholipid syndrome is a hypercoagulable state characterized by recurrent arteriovenous thrombosis and/or pregnancy morbidity in the presence of either a lupus anticoagulant or anticardiolipin antibody (both phospholipid-related proteins). […] The most common arteriovenous thrombotic events in antiphospholipid syndrome are deep venous thrombosis and pulmonary embolus […], but any part of the circulation may be involved, with arterial events such as myocardial infarction and stroke carrying a high mortality rate. Poor placental circulation is thought to be responsible for the high pregnancy morbidity, with recurrent first- and second-trimester loss and a higher rate of pre-eclampsia being typical clinical features.”)
Still’s disease. (“Consider inflammatory disease in cases of pyrexia of unknown origin.”)
Polymyalgia rheumatica. Giant cell arteritis. (“[P]olymyalgia rheumatica (PMR) [is] a systemic inflammatory syndrome affecting the elderly that is characterized by bilateral pain and stiffness in the shoulders and hip girdles. The stiffness can be profound and limits mobility although true muscle weakness is not a feature. […] The affected areas are diffusely tender, with movements limited by pain. […] care must be taken not to attribute joint inflammation to PMR until other diagnoses have been excluded; for example, a significant minority of RA patients may present with a polymyalgic onset. […] The treatment for PMR is low-dose corticosteroids. […] Many physicians would consider a dramatic response to low-dose prednisolone as almost diagnostic for PMR, so if a patients symptoms do not improve rapidly it is wise to re-evaluate the original diagnosis.”)
Relapsing polychondritis. (“Relapsing polychondritis is characterized histologically by inflammatory infiltration and later fibrosis of cartilage. Any cartilage, in any location, is at risk. […] Treatment of relapsing polychondritis is with corticosteroids […] Surgical reconstruction of collapsed structures is not an option as the deformity tends to continue postoperatively.”)
Dermatomyositis. Gottron’s Papules.
Enteropathic arthritis. (“A seronegative arthritis may develop in up to 15 per cent of patients with any form of inflammatory bowel disease, including ulcerative colitis (UC), Crohn’s disease or microscopic and collagenous colitis. The most common clinical presentations are a peripheral arthritis […] and spondyloarthritis.”)
Reflex sympathetic dystrophy.
Whipple’s disease. (“Although rare, consider Whipple’s disease in any patient presenting with malabsorption, weight loss and arthritis.”)
Wegener’s granulomatosis. (“Small-vessel vasculitis may cause a pulmonary-renal syndrome. […] The classic triad of Weneger’s granulomatosis is the presence of upper and lower respiratory tract disease and renal impairment.”)
Reactive arthritis. Reiter’s syndrome. (“Consider reactive arthritis in any patient presenting with a monoarthropathy. […] Reactive arthritis is generally benign, with up to 80 per cent making a full recovery.”)
Sarcoidosis. Löfgren syndrome.
Polyarteritis nodosa. (“Consider mesenteric ischaemia in any patient presenting with a systemic illness and postprandial abdominal pain.”)
Sjögren syndrome. Schirmer’s test.
Behçet syndrome.
Lyme disease. Erythema chronicum migrans. (“The combination of rash leading to arthralgia and cranial neuropathy is a classic presentation of Lyme disease.”)
Takayasu arteritis. (“Takayasu’s arteritis is an occlusive vasculitis leading to stenoses of the aorta and its principal branches. The symptoms and signs of the disease depend on the distribution of the affected vessel but upper limbs are generally affected more commonly than the iliac tributaries. […] the disease is a chronic relapsing and remitting condition […] The mainstay of treatment is high-dose corticosteroids plus a steroid-sparing agent such as methotrexate. […] Cyclophosphamide is reserved for those patients who do not achieve remission with standard therapy. Surgical intervention such as bypass or angioplasty may improve ischaemic symptoms once the inflammation is under control.”)
Lymphoma.
Haemarthrosis. (“Consider synovial tumours in a patient with unexplained haemarthrosis.”)
Juvenile idiopathic arthritis.
Drug-induced lupus erythematosus. (“Drug-induced lupus (DIL) generates a different spectrum of clinical manifestations from idiopathic disease. DIL is less severe than idiopathic SLE, and nephritis or central nervous system involvement is very rare. […] The most common drugs responsible for a lupus-like syndrome are procainamide, hydralazine, quinidine, isoniazid, methyldopa, chlorpromazine and minocycline. […] Treatment involves stopping the offending medication and the symptoms will gradually resolve.”)
Churg–Strauss syndrome.

A few diabetes papers of interest

i. Clinical Inertia in Type 2 Diabetes Management: Evidence From a Large, Real-World Data Set.

“Despite clinical practice guidelines that recommend frequent monitoring of HbA_1c (every 3 months) and aggressive escalation of antihyperglycemic therapies until glycemic targets are reached (1,2), the intensification of therapy in patients with uncontrolled type 2 diabetes (T2D) is often inappropriately delayed. The failure of clinicians to intensify therapy when clinically indicated has been termed “clinical inertia.” A recently published systematic review found that the median time to treatment intensification after an HbA_1c measurement above target was longer than 1 year (range 0.3 to >7.2 years) (3). We have previously reported a rather high rate of clinical inertia in patients uncontrolled on metformin monotherapy (4). Treatment was not intensified early (within 6 months of metformin monotherapy failure) in 38%, 31%, and 28% of patients when poor glycemic control was defined as an HbA_1c >7% (>53 mmol/mol), >7.5% (>58 mmol/mol), and >8% (>64 mmol/mol), respectively.

Using the electronic health record system at Cleveland Clinic (2005–2016), we identified a cohort of 7,389 patients with T2D who had an HbA_1c value ≥7% (≥53 mmol/mol) (“index HbA_1c”) despite having been on a stable regimen of two oral antihyperglycemic drugs (OADs) for at least 6 months prior to the index HbA_1c. This HbA_1c threshold would generally be expected to trigger treatment intensification based on current guidelines. Patient records were reviewed for the 6-month period following the index HbA_1c, and changes in diabetes therapy were evaluated for evidence of “intensification” […] almost two-thirds of patients had no evidence of intensification in their antihyperglycemic therapy during the 6 months following the index HbA_1c ≥7% (≥53 mmol/mol), suggestive of poor glycemic control. Most alarming was the finding that even among patients in the highest index HbA_1c category (≥9% [≥75 mmol/mol]), therapy was not intensified in 44% of patients, and slightly more than half (53%) of those with an HbA_1c between 8 and 8.9% (64 and 74 mmol/mol) did not have their therapy intensified.”

“Unfortunately, these real-world findings confirm a high prevalence of clinical inertia with regard to T2D management. The unavoidable conclusion from these data […] is that physicians are not responding quickly enough to evidence of poor glycemic control in a high percentage of patients, even in those with HbA_1c levels far exceeding typical treatment targets.”

…

ii. Gestational Diabetes Mellitus and Diet: A Systematic Review and Meta-analysis of Randomized Controlled Trials Examining the Impact of Modified Dietary Interventions on Maternal Glucose Control and Neonatal Birth Weight.

“Medical nutrition therapy is a mainstay of gestational diabetes mellitus (GDM) treatment. However, data are limited regarding the optimal diet for achieving euglycemia and improved perinatal outcomes. This study aims to investigate whether modified dietary interventions are associated with improved glycemia and/or improved birth weight outcomes in women with GDM when compared with control dietary interventions. […]

From 2,269 records screened, 18 randomized controlled trials involving 1,151 women were included. Pooled analysis demonstrated that for modified dietary interventions when compared with control subjects, there was a larger decrease in fasting and postprandial glucose (−4.07 mg/dL [95% CI −7.58, −0.57]; P = 0.02 and −7.78 mg/dL [95% CI −12.27, −3.29]; P = 0.0007, respectively) and a lower need for medication treatment (relative risk 0.65 [95% CI 0.47, 0.88]; P = 0.006). For neonatal outcomes, analysis of 16 randomized controlled trials including 841 participants showed that modified dietary interventions were associated with lower infant birth weight (−170.62 g [95% CI −333.64, −7.60]; P = 0.04) and less macrosomia (relative risk 0.49 [95% CI 0.27, 0.88]; P = 0.02). The quality of evidence for these outcomes was low to very low. Baseline differences between groups in postprandial glucose may have influenced glucose-related outcomes. […] we were unable to resolve queries regarding potential concerns for sources of bias because of lack of author response to our queries. We have addressed this by excluding these studies in the sensitivity analysis. […] after removal of the studies with the most substantial methodological concerns in the sensitivity analysis, differences in the change in fasting plasma glucose were no longer significant. Although differences in the change in postprandial glucose and birth weight persisted, they were attenuated.”

“This review highlights limitations of the current literature examining dietary interventions in GDM. Most studies are too small to demonstrate significant differences in our primary outcomes. Seven studies had fewer than 50 participants and only two had more than 100 participants (n = 125 and 150). The short duration of many dietary interventions and the late gestational age at which they were started (38) may also have limited their impact on glycemic and birth weight outcomes. Furthermore, we cannot conclude if the improvements in maternal glycemia and infant birth weight are due to reduced energy intake, improved nutrient quality, or specific changes in types of carbohydrate and/or protein. […] These data suggest that dietary interventions modified above and beyond usual dietary advice for GDM have the potential to offer better maternal glycemic control and infant birth weight outcomes. However, the quality of evidence was judged as low to very low due to the limitations in the design of included studies, the inconsistency between their results, and the imprecision in their effect estimates.”

…

iii. Lifetime Prevalence and Prognosis of Prediabetes Without Progression to Diabetes.

“Impaired fasting glucose, also termed prediabetes, is increasingly prevalent and is associated with adverse cardiovascular risk (1). The cardiovascular risks attributed to prediabetes may be driven primarily by the conversion from prediabetes to overt diabetes (2). Given limited data on outcomes among nonconverters in the community, the extent to which some individuals with prediabetes never go on to develop diabetes and yet still experience adverse cardiovascular risk remains unclear. We therefore investigated the frequency of cardiovascular versus noncardiovascular deaths in people who developed early- and late-onset prediabetes without ever progressing to diabetes.”

“We used data from the Framingham Heart Study collected on the Offspring Cohort participants aged 18–77 years at the time of initial fasting plasma glucose (FPG) assessment (1983–1987) who had serial FPG testing over subsequent examinations with continuous surveillance for outcomes including cause-specific mortality (3). As applied in prior epidemiological investigations (4), we used a case-control design focusing on the cause-specific outcome of cardiovascular death to minimize the competing risk issues that would be encountered in time-to-event analyses. To focus on outcomes associated with a given chronic glycemic state maintained over the entire lifetime, we restricted our analyses to only those participants for whom data were available over the life course and until death. […] We excluded individuals with unknown age of onset of glycemic impairment (i.e., age ≥50 years with prediabetes or diabetes at enrollment). […] We analyzed cause-specific mortality, allowing for relating time-varying exposures with lifetime risk for an event (4). We related glycemic phenotypes to cardiovascular versus noncardiovascular cause of death using a case-control design, where cases were defined as individuals who died of cardiovascular disease (death from stroke, heart failure, or other vascular event) or coronary heart disease (CHD) and controls were those who died of other causes.”

“The mean age of participants at enrollment was 42 ± 7 years (43% women). The mean age at death was 73 ± 10 years. […] In our study, approximately half of the individuals presented with glycemic impairment in their lifetime, of whom two-thirds developed prediabetes but never diabetes. In our study, these individuals had lower cardiovascular-related mortality compared with those who later developed diabetes, even if the prediabetes onset was early in life. However, individuals with early-onset prediabetes, despite lifelong avoidance of overt diabetes, had greater propensity for death due to cardiovascular or coronary versus noncardiovascular disease compared with those who maintained lifelong normal glucose status. […] Prediabetes is a heterogeneous entity. Whereas some forms of prediabetes are precursors to diabetes, other types of prediabetes never progress to diabetes but still confer increased propensity for death from a cardiovascular cause.”

…

iv. Learning From Past Failures of Oral Insulin Trials.

“Very recently one of the largest type 1 diabetes prevention trials using daily administration of oral insulin or placebo was completed. After 9 years of study enrollment and follow-up, the randomized controlled trial failed to delay the onset of clinical type 1 diabetes, which was the primary end point. The unfortunate outcome follows the previous large-scale trial, the Diabetes Prevention Trial–Type 1 (DPT-1), which again failed to delay diabetes onset with oral insulin or low-dose subcutaneous insulin injections in a randomized controlled trial with relatives at risk for type 1 diabetes. These sobering results raise the important question, “Where does the type 1 diabetes prevention field move next?” In this Perspective, we advocate for a paradigm shift in which smaller mechanistic trials are conducted to define immune mechanisms and potentially identify treatment responders. […] Mechanistic trials will allow for better trial design and patient selection based upon molecular markers prior to large randomized controlled trials, moving toward a personalized medicine approach for the prevention of type 1 diabetes.”

“Before a disease can be prevented, it must be predicted. The ability to assess risk for developing type 1 diabetes (T1D) has been well documented over the last two decades (1). Using genetic markers, human leukocyte antigen (HLA) DQ and DR typing (2), islet autoantibodies (1), and assessments of glucose tolerance (intravenous or oral glucose tolerance tests) has led to accurate prediction models for T1D development (3). Prospective birth cohort studies Diabetes Autoimmunity Study in the Young (DAISY) in Colorado (4), Type 1 Diabetes Prediction and Prevention (DIPP) study in Finland (5), and BABYDIAB studies in Germany have followed genetically at-risk children for the development of islet autoimmunity and T1D disease onset (6). These studies have been instrumental in understanding the natural history of T1D and making T1D a predictable disease with the measurement of antibodies in the peripheral blood directed against insulin and proteins within β-cells […]. Having two or more islet autoantibodies confers an ∼85% risk of developing T1D within 15 years and nearly 100% over time (7). […] T1D can be predicted by measuring islet autoantibodies, and thousands of individuals including young children are being identified through screening efforts, necessitating the need for treatments to delay and prevent disease onset.”

“Antigen-specific immunotherapies hold the promise of potentially inducing tolerance by inhibiting effector T cells and inducing regulatory T cells, which can act locally at tissue-specific sites of inflammation (12). Additionally, side effects are minimal with these therapies. As such, insulin and GAD have both been used as antigen-based approaches in T1D (13). Oral insulin has been evaluated in two large randomized double-blinded placebo-controlled trials over the last two decades. First in the Diabetes Prevention Trial–Type 1 (DPT-1) and then in the TrialNet clinical trials network […] The DPT-1 enrolled relatives at increased risk for T1D having islet autoantibodies […] After 6 years of treatment, there was no delay in T1D onset. […] The TrialNet study screened, enrolled, and followed 560 at-risk relatives over 9 years from 2007 to 2016, and results have been recently published (16). Unfortunately, this trial failed to meet the primary end point of delaying or preventing diabetes onset.”

“Many factors influence the potency and efficacy of antigen-specific therapy such as dose, frequency of dosing, route of administration, and, importantly, timing in the disease process. […] Over the last two decades, most T1D clinical trial designs have randomized participants 1:1 or 2:1, drug to placebo, in a double-blind two-arm design, especially those intervention trials in new-onset T1D (18). Primary end points have been delay in T1D onset for prevention trials or stimulated C-peptide area under the curve at 12 months with new-onset trials. These designs have served the field well and provided reliable human data for efficacy. However, there are limitations including the speed at which these trials can be completed, the number of interventions evaluated, dose optimization, and evaluation of mechanistic hypotheses. Alternative clinical trial designs, such as adaptive trial designs using Bayesian statistics, can overcome some of these issues. Adaptive designs use accumulating data from the trial to modify certain aspects of the study, such as enrollment and treatment group assignments. This “learn as we go” approach relies on biomarkers to drive decisions on planned trial modifications. […] One of the significant limitations for adaptive trial designs in the T1D field, at the present time, is the lack of validated biomarkers for short-term readouts to inform trial adaptations. However, large-scale collaborative efforts are ongoing to define biomarkers of T1D-specific immune dysfunction and β-cell stress and death (9,22).”

“T1D prevention has proven much more difficult than originally thought, challenging the paradigm that T1D is a single disease. T1D is indeed a heterogeneous disease in terms of age of diagnosis, islet autoantibody profiles, and the rate of loss of residual β-cell function after clinical onset. Children have a much more rapid loss of residual insulin production (measured as C-peptide area under the curve following a mixed-meal tolerance test) after diagnosis than older adolescents and adults (23,24), indicating that childhood and adult-onset T1D are not identical. Further evidence for subtypes of T1D come from studies of human pancreata of T1D organ donors in which children (0–14 years of age) within 1 year of diagnosis had many more inflamed islets compared with older adolescents and adults aged 15–39 years old (25). Additionally, a younger age of T1D onset (<7 years) has been associated with higher numbers of CD20⁺ B cells within islets and fewer insulin-containing islets compared with an age of onset ≥13 years associated with fewer CD20⁺ islet infiltrating cells and more insulin-containing islets (26,27). This suggests a much more aggressive autoimmune process in younger children and distinct endotypes (a subtype of a condition defined by a distinct pathophysiologic mechanism), which has recently been proposed for T1D (27).”

“Safe and specific therapies capable of being used in children are needed for T1D prevention. The vast majority of drug development involves small biotechnology companies, specialty pharmaceutical firms, and large pharmaceutical companies, more so than traditional academia. A large amount of preclinical and clinical research (phase 1, 2, and 3 studies) are needed to advance a drug candidate through the development pipeline to achieve U.S. Food and Drug Administration (FDA) approval for a given disease. A recent analysis of over 4,000 drugs from 835 companies in development during 2003–2011 revealed that only 10.4% of drugs that enter clinical development at phase 1 (safety studies) advance to FDA approval (32). However, the success rate increases 50% for the lead indication of a drug, i.e., a drug specifically developed for one given disease (32). Reasons for this include strong scientific rationale and early efficacy signals such as correlating pharmacokinetic (drug levels) to pharmacodynamic (drug target effects) tests for the lead indication. Lead indications also tend to have smaller, better-defined “homogenous” patient populations than nonlead indications for the same drug. This would imply that the T1D field needs more companies developing drugs specifically for T1D, not type 2 diabetes or other autoimmune diseases with later testing to broaden a drug’s indication. […] In a similar but separate analysis, selection biomarkers were found to substantially increase the success rate of drug approvals across all phases of drug development. Using a selection biomarker as part of study inclusion criteria increased drug approval threefold from 8.4% to 25.9% when used in phase 1 trials, 28% to 46% when transitioning from a phase 2 to phase 3 efficacy trial, and 55% to 76% for a phase 3 trial to likelihood of approval (33). These striking data support the concept that enrichment of patient enrollment at the molecular level is a more successful strategy than heterogeneous enrollment in clinical intervention trials. […] Taken together, new drugs designed specifically for children at risk for T1D and a biomarker selecting patients for a treatment response may increase the likelihood for a successful prevention trial; however, experimental confirmation in clinical trials is needed.”

…

v. Metabolic Karma — The Atherogenic Legacy of Diabetes: The 2017 Edwin Bierman Award Lecture.

“Cardiovascular (CV) disease remains the major cause of mortality and is associated with significant morbidity in both type 1 and type 2 diabetes (1–4). Despite major improvements in the management of traditional risk factors, including hypertension, dyslipidemia, and glycemic control prevention, retardation and reversal of atherosclerosis, as manifested clinically by myocardial infarction, stroke, and peripheral vascular disease, remain a major unmet need in the population with diabetes. For example, in the Steno-2 study and in its most recent report of the follow-up phase, at least a decade after cessation of the active treatment phase, there remained a high risk of death, primarily from CV disease despite aggressive control of the traditional risk factors, in this originally microalbuminuric population with type 2 diabetes (5,6). In a meta-analysis of major CV trials where aggressive glucose lowering was instituted […] the beneficial effect of intensive glycemic control on CV disease was modest, at best (7). […] recent trials with two sodium–glucose cotransporter 2 inhibitors, empagliflozin and canagliflozin (11,12), and two long-acting glucagon-like peptide 1 agonists, liraglutide and semaglutide (13,14), have reported CV benefits that have led in some of these trials to a decrease in CV and all-cause mortality. However, even with these recent positive CV outcomes, CV disease remains the major burden in the population with diabetes (15).”

“This unmet need of residual CV disease in the population with diabetes remains unexplained but may occur as a result of a range of nontraditional risk factors, including low-grade inflammation and enhanced thrombogenicity as a result of the diabetic milieu (16). Furthermore, a range of injurious pathways as a result of chronic hyperglycemia previously studied in vitro in endothelial cells (17) or in models of microvascular complications may also be relevant and are a focus of this review […] [One] major factor that is likely to promote atherosclerosis in the diabetes setting is increased oxidative stress. There is not only increased generation of ROS from diverse sources but also reduced antioxidant defense in diabetes (40). […] vascular ROS accumulation is closely linked to atherosclerosis and vascular inflammation provide the impetus to consider specific antioxidant strategies as a novel therapeutic approach to decrease CV disease, particularly in the setting of diabetes.”

“One of the most important findings from numerous trials performed in subjects with type 1 and type 2 diabetes has been the identification that previous episodes of hyperglycemia can have a long-standing impact on the subsequent development of CV disease. This phenomenon known as “metabolic memory” or the “legacy effect” has been reported in numerous trials […] The underlying explanation at a molecular and/or cellular level for this phenomenon remains to be determined. Our group, as well as others, has postulated that epigenetic mechanisms may participate in conferring metabolic memory (51–53). In in vitro studies initially performed in aortic endothelial cells, transient incubation of these cells in high glucose followed by subsequent return of these cells to a normoglycemic environment was associated with increased gene expression of the p65 subunit of NF-κB, NF-κB activation, and expression of NF-κB–dependent proteins, including MCP-1 and VCAM-1 (54).

In further defining a potential epigenetic mechanism that could explain the glucose-induced upregulation of genes implicated in vascular inflammation, a specific histone methylation mark was identified in the promoter region of the p65 gene (54). This histone 3 lysine 4 monomethylation (H3K4m1) occurred as a result of mobilization of the histone methyl transferase, Set7. Furthermore, knockdown of Set7 attenuated glucose-induced p65 upregulation and prevented the persistent upregulation of this gene despite these endothelial cells returning to a normoglycemic milieu (55). These findings, confirmed in animal models exposed to transient hyperglycemia (54), provide the rationale to consider Set7 as an appropriate target for end-organ protective therapies in diabetes. Although specific Set7 inhibitors are currently unavailable for clinical development, the current interest in drugs that block various enzymes, such as Set7, that influence histone methylation in diseases, such as cancer (56), could lead to agents that warrant testing in diabetes. Studies addressing other sites of histone methylation as well as other epigenetic pathways including DNA methylation and acetylation have been reported or are currently in progress (55,57,58), particularly in the context of diabetes complications. […] As in vitro and preclinical studies increase our knowledge and understanding of the pathogenesis of diabetes complications, it is likely that we will identify new molecular targets leading to better treatments to reduce the burden of macrovascular disease. Nevertheless, these new treatments will need to be considered in the context of improved management of traditional risk factors.”

…

vi. Perceived risk of diabetes seriously underestimates actual diabetes risk: The KORA FF4 study.

“According to the International Diabetes Federation (IDF), almost half of the people with diabetes worldwide are unaware of having the disease, and even in high-income countries, about one in three diabetes cases is not diagnosed [1,2]. In the USA, 28% of diabetes cases are undiagnosed [3]. In DEGS1, a recent population-based German survey, 22% of persons with HbA1c ≥ 6.5% were unaware of their disease [4]. Persons with undiagnosed diabetes mellitus (UDM) have a more than twofold risk of mortality compared to persons with normal glucose tolerance (NGT) [5,6]; many of them also have undiagnosed diabetes complications like retinopathy and chronic kidney disease [7,8]. […] early detection of diabetes and prediabetes is beneficial for patients, but may be delayed by patients´ being overly optimistic about their own health. Therefore, it is important to address how persons with UDM or prediabetes perceive their diabetes risk.”

“The proportion of persons who perceived their risk of having UDM at the time of the interview as “negligible”, “very low” or “low” was 87.1% (95% CI: 85.0–89.0) in NGT [normal glucose tolerance individuals], 83.9% (81.2–86.4) in prediabetes, and 74.2% (64.5–82.0) in UDM […]. The proportion of persons who perceived themselves at risk of developing diabetes in the following years ranged from 14.6% (95% CI: 12.6–16.8) in NGT to 20.6% (17.9–23.6) in prediabetes to 28.7% (20.5–38.6) in UDM […] In univariate regression models, perceiving oneself at risk of developing diabetes was associated with younger age, female sex, higher school education, obesity, self-rated poor general health, and parental diabetes […] the proportion of better educated younger persons (age ≤ 60 years) with prediabetes, who perceived themselves at risk of developing diabetes was 35%, whereas this figure was only 13% in less well educated older persons (age > 60 years).”

“The present study shows that three out of four persons with UDM [undiagnosed diabetes mellitus] believed that the probability of having undetected diabetes was low or very low. In persons with prediabetes, more than 70% believed that they were not at risk of developing diabetes in the next years. People with prediabetes were more inclined to perceive themselves at risk of diabetes if their self-rated general health was poor, their mother or father had diabetes, they were obese, they were female, their educational level was high, and if they were younger. […] People with undiagnosed diabetes or prediabetes considerably underestimate their probability of having or developing diabetes. […] perceived diabetes risk was lower in men, lower educated and older persons. […] Our results showed that people with low and intermediate education strongly underestimate their risk of diabetes and may qualify as target groups for detection of UDM and prediabetes.”

“The present results were in line with results from the Dutch Hoorn Study [18,19]. Adriaanse et al. reported that among persons with UDM, only 28.3% perceived their likeliness of having diabetes to be at least 10% [18], and among persons with high risk of diabetes (predicted from a symptom risk questionnaire), the median perceived likeliness of having diabetes was 10.8% [19]. Again, perceived risk did not fully reflect the actual risk profiles. For BMI, there was barely any association with perceived risk of diabetes in the Dutch study [19].”

Blood (I)

As I also mentioned on goodreads I was far from impressed with the first few pages of this book – but I read on, and the book actually turned out to include a decent amount of very reasonable coverage. Taking into consideration the way the author started out the three star rating should be considered a high rating, and in some parts of the book the author covers very complicated stuff in a really very decent manner, considering the format of the book and its target group.

Below I have added some quotes and some links to topics/people/ideas/etc. covered in the first half of the book.

…

“[Clotting] makes it difficult to study the components of blood. It also [made] it impossible to store blood for transfusion [in the past]. So there was a need to find a way to prevent clotting. Fortunately the discovery that the metal calcium accelerated the rate of clotting enabled the development of a range of compounds that bound calcium and therefore prevented this process. One of them, citrate, is still in common use today [here’s a relevant link, US] when blood is being prepared for storage, or to stop blood from clotting while it is being pumped through kidney dialysis machines and other extracorporeal circuits. Adding citrate to blood, and leaving it alone, will result in gravity gradually separating the blood into three layers; the process can be accelerated by rapid spinning in a centrifuge […]. The top layer is clear and pale yellow or straw-coloured in appearance. This is the plasma, and it contains no cells. The bottom layer is bright red and contains the dense pellet of red cells that have sunk to the bottom of the tube. In-between these two layers is a very narrow layer, called the ‘buffy coat’ because of its pale yellow-brown appearance. This contains white blood cells and platelets. […] red cells, white cells, and platelets […] define the primary functions of blood: oxygen transport, immune defence, and coagulation.”

“The average human has about five trillion red blood cells per litre of blood or thirty trillion […] in total, making up a quarter of the total number of cells in the body. […] It is clear that the red cell has primarily evolved to perform a single function, oxygen transportation. Lacking a nucleus, and the requisite machinery to control the synthesis of new proteins, there is a limited ability for reprogramming or repair. […] each cell [makes] a complete traverse of the body’s circulation about once a minute. In its three- to four-month lifetime, this means every cell will do the equivalent of 150,000 laps around the body. […] Red cells lack mitochondria; they get their energy by fermenting glucose. […] A prosaic explanation for their lack of mitochondria is that it prevents the loss of any oxygen picked up from the lungs on the cells’ journey to the tissues that need it. The shape of the red cell is both deformable and elastic. In the bloodstream each cell is exposed to large shear forces. Yet, due to the properties of the membrane, they are able to constrict to enter blood vessels smaller in diameter than their normal size, bouncing back to their original shape on exiting the vessel the other side. This ability to safely enter very small openings allows capillaries to be very small. This in turn enables every cell in the body to be close to a capillary. Oxygen consequently only needs to diffuse a short distance from the blood to the surrounding tissue; this is vital as oxygen diffusion outside the bloodstream is very slow. Various pathologies, such as diabetes, peripheral vascular disease, and septic shock disturb this deformability of red blood cells, with deleterious consequences.”

“Over thirty different substances, proteins and carbohydrates, contribute to an individual’s blood group. By far the best known are the ABO and Rhesus systems. This is not because the proteins and carbohydrates that comprise these particular blood group types are vitally important for red cell function, but rather because a failure to account for these types during a blood transfusion can have catastrophic consequences. The ABO blood group is sugar-based […] blood from an O person can be safely given to anyone (with no sugar antigens this person is a ‘universal’ donor). […] As all that is needed to convert A and B to O is to remove a sugar, there is commercial and medical interest in devising ways to do this […] the Rh system […] is protein-based rather than sugar based. […] Rh proteins sit in the lipid membrane of the cell and control the transport of molecules into and out of the cell, most probably carbon dioxide and ammonia. The situation is complex, with over thirty different subgroups relating to subtle differences in the protein structure.”

“Unlike the red cells, all white cell subtypes contain nuclei. Some also contain on their surface a set of molecules called the ‘major histocompatibility complex’ (MHC). In humans, these receptors are also called ‘human leucocyte antigens’ (HLA). Their role is to recognize fragments of protein from pathogens and trigger the immune response that will ultimately destroy the invaders. Crudely, white blood cells can be divided into those that attack ‘on sight’ any foreign material — whether it be a fragment of inanimate material such as a splinter or an invading microorganism — and those that form part of a defence mechanism that recognizes specific biomolecules and marshals a slower, but equally devastating response. […] cells of the non-specific (or innate) immune system […] are divided into those that have nuclei with multiple lobed shapes (polymorphonuclear leukocytes or PMN) and those that have a single lobe nucleus ([…] ‘mononuclear leucocytes‘ or ‘MN’). PMN contain granules inside them and so are sometimes called ‘granulocytes‘.”

“Neutrophils are by far the most abundant PMN, making up over half of the total white blood cell count. The primary role of a neutrophil is to engulf a foreign object such as an invading microorganism. […] Eosinophils and basophils are the least abundant PMN cell type, each making up less than 2 per cent of white blood cells. The role of basophils is to respond to tissue injury by triggering an inflammatory response. […] When activated, basophils and mast cells degranulate, releasing molecules such as histamine, leukotrienes, and cytokines. Some of these molecules trigger an increase in blood flow causing redness and heat in the damaged site, others sensitize the area to pain. Greater permeability of the blood vessels results in plasma leaking out of the vessels and into the surrounding tissue at an increased rate, causing swelling. […] This is probably an evolutionary adaption to prevent overuse of a damaged part of the body but also helps to bring white cells and proteins to the damaged, inflamed area. […] The main function of eosinophils is to tackle invaders too large to be engulfed by neutrophils, such as the multicellular parasitic tapeworms and nematodes. […] Monocytes are a type of mononuclear leucocyte (MN) making up about 5 per cent of white blood cells. They spend even less tiem in the circulation than neutrophils, generally less than ten hours, but their time in the blood circulation does not end in death. Instead, they are converted into a cell called a ‘macrophage‘ […] Their role is similar to the neutrophil, […] the ultimate fate of both the red blood cell and the neutrophil is to be engulfed by a macrophage. An excess of monocytes in a blood count (monocytosis) is an indicator of chronic inflammation”.

“Blood has to flow freely. Therefore, the red cells, white cells, and platelets are all suspended in a watery solution called ‘plasma’. But plasma is more than just water. In fact if it were only water all the cells would burst. Plasma has to have a very similar concentration of molecules and ions as the cells. This is because cells are permeable to water. So if the concentration of dissolved substances in the plasma was significantly higher than that in the cells, water would flow from the cells to the plasma in an attempt to equalize this gradient by diluting the plasma; this would result in cell shrinkage. Even worse, if the concentration in the plasma was lower than in the cells, water would flow into the cells from the plasma, and the resulting pressure increase would burst the cells, releasing all their contents into the plasma in the process. […] Plasma contains much more than just the ions required to prevent cells bursting or shrinking. It also contains key components designed to assist in cellular function. The protein clotting factors that are part of the coagulation cascade are always present in low concentrations […] Low levels of antibodies, produced by the lymphocytes, circulate […] In addition to antibodies, the plasma contains C-reactive proteins, Mannose-binding lectin and complement proteins that function as ‘opsonins‘ […] A host of other proteins perform roles independent of oxygen delivery or immune defence. By far the most abundant protein in serum is albumin. […] Blood is the transport infrastructure for any molecule that needs to be moved around the body. Some, such as the water-soluble fuel glucose, and small hormones like insulin, dissolve freely in the plasma. Others that are less soluble hitch a ride on proteins [….] Dangerous reactive molecules, such as iron, are also bound to proteins, in this case transferrin.”

“Immunoglobulins are produced by B lymphocytes and either remain bound on the surface of the cell (as part of the B cell receptor) or circulate freely in the plasma (as antibodies). Whatever their location, their purpose is the same – to bind to and capture foreign molecules (antigens). […] To perform the twin role of binding the antigen and the phagocytosing cell, immunoglobulins need to have two distinct parts to their structure — one that recognizes the foreign antigen and one that can be recognized — and destroyed — by the host defence system. The host defence system does not vary; a specific type of immunoglobulin will be recognized by one of the relatively few types of immune cells or proteins. Therefore this part of the immunoglobulin structure is not variable. But the nature of the foreign antigen will vary greatly; so the antigen-recognizing part of the structure must be highly variable. It is this that leads to the great variety of immunoglobulins. […] within the blood there is an army of potential binding sites that can recognize and bind to almost any conceivable chemical structure. Such variety is why the body is able to adapt and kill even organisms it has never encountered before. Indeed the ability to make an immunoglobulin recognize almost any structure has resulted in antibody binding assays being used historically in diagnostic tests ranging from pregnancy to drugs testing.”

“[I]mmunoglobulins consist of two different proteins — a heavy chain and a light chain. In the human heavy chain there are about forty different V (variable) segments, twenty-five different D (Diversity) segments, and six J (Joining) segments. The light chain also contains variable V and J segments. A completed immunoglobulin has a heavy chain with only one V, D, and J segment, and a light chain with only one V and D segment. It is the shuffling of these segments during development of the mature B lymphocyte that creates the diversity required […] the hypervariable regions are particularly susceptible to mutation during development. […] A separate class of immunoglobulin-like molecules also provide the key to cell-to-cell communication in the immune system. In humans, with the exception of the egg and sperm cells, all cells that possess a nucleus also have a protein on their surface called ‘Human Leucocyte Antigen (HLA) Class I’. The function of HLA Class I is to display fragments (antigens) of all the proteins currently being made inside the cell. It therefore acts like a billboard displaying the current highlights of cellular activity. Any proteins recognized as non-self by cytotoxic T cell lymphocytes will result in the whole cell being targeted for destruction […]. Another form of HLA, Class II, is only present on the surface of specialized cells of the immune system termed antigen presenting cells. In contrast to HLA Class I, the surface of HLA Class II cells displays antigens that originate from outside of the cell.”

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Galen.
Bloodletting.
Marcello Malpighi.
William Harvey. De Motu Cordis.
Andreas Vesalius. De humani corporis fabrica.
Ibn al-Nafis. Michael Servetus. Realdo Colombo. Andrea Cesalpino.
Pulmonary circulation.
Hematopoietic stem cell. Bone marrow. Erythropoietin.
Hemoglobin.
Anemia.
Peroxidase.
Lymphocytes. NK cells. Granzyme. B lymphocytes. T lymphocytes. Antibody/Immunoglobulin. Lymphoblast.
Platelet. Coagulation cascade. Fibrinogen. Fibrin. Thrombin. Haemophilia. Hirudin. Von Willebrand disease. Haemophilia A. -ll- B.
Tonicity. Colloid osmotic pressure.
Adaptive immune system. Vaccination. Variolation. Antiserum. Agostino Bassi. Muscardine. Louis Pasteur. Élie Metchnikoff. Paul Ehrlich.
Humoral immunity. Membrane attack complex.
Niels Kaj Jerne. David Talmage. Frank Burnet. Clonal selection theory. Peter Medawar.
Susumu Tonegawa.

A few diabetes papers of interest

i. Reevaluating the Evidence for Blood Pressure Targets in Type 2 Diabetes.

“There is general consensus that treating adults with type 2 diabetes mellitus (T2DM) and hypertension to a target blood pressure (BP) of <140/90 mmHg helps prevent cardiovascular disease (CVD). Whether more intensive BP control should be routinely targeted remains a matter of debate. While the American Diabetes Association (ADA) BP guidelines recommend an individualized assessment to consider different treatment goals, the American College of Cardiology/American Heart Association BP guidelines recommend a BP target of <130/80 mmHg for most individuals with hypertension, including those with T2DM (1–3).

In large part, these discrepant recommendations reflect the divergent results of the Action to Control Cardiovascular Risk in Diabetes-BP trial (ACCORD-BP) among people with T2DM and the Systolic Blood Pressure Intervention Trial (SPRINT), which excluded people with diabetes (4,5). Both trials evaluated the effect of intensive compared with standard BP treatment targets (<120 vs. <140 mmHg systolic) on a composite CVD end point of nonfatal myocardial infarction or stroke or death from cardiovascular causes. SPRINT also included unstable angina and acute heart failure in its composite end point. While ACCORD-BP did not show a significant benefit from the intervention (hazard ratio [HR] 0.88; 95% CI 0.73–1.06), SPRINT found a significant 25% relative risk reduction on the primary end point favoring intensive therapy (0.75; 0.64–0.89).”

“To some extent, CVD mechanisms and causes of death differ in T2DM patients compared with the general population. Microvascular disease (particularly kidney disease), accelerated vascular calcification, and diabetic cardiomyopathy are common in T2DM (13–15). Moreover, the rate of sudden cardiac arrest is markedly increased in T2DM and related, in part, to diabetes-specific factors other than ischemic heart disease (16). Hypoglycemia is a potential cause of CVD mortality that is specific to diabetes (17). In addition, polypharmacy is common and may increase CVD risk (18). Furthermore, nonvascular causes of death account for approximately 40% of the premature mortality burden experienced by T2DM patients (19). Whether these disease processes may render patients with T2DM less amenable to derive a mortality benefit from intensive BP control, however, is not known and should be the focus of future research.

In conclusion, the divergent results between ACCORD-BP and SPRINT are most readily explained by the apparent lack of benefit of intensive BP control on CVD and all-cause mortality in ACCORD-BP, rather than differences in the design, population characteristics, or interventions between the trials. This difference in effects on mortality may be attributable to differential mechanisms underlying CVD mortality in T2DM, to chance, or to both. These observations suggest that caution should be exercised extrapolating the results of SPRINT to patients with T2DM and support current ADA recommendations to individualize BP targets, targeting a BP of <140/90 mmHg in the majority of patients with T2DM and considering lower BP targets when it is anticipated that individual benefits outweigh risks.”

…

ii. Modelling incremental benefits on complications rates when targeting lower HbA1c levels in people with Type 2 diabetes and cardiovascular disease.

“Glucose‐lowering interventions in Type 2 diabetes mellitus have demonstrated reductions in microvascular complications and modest reductions in macrovascular complications. However, the degree to which targeting different HbA_1c reductions might reduce risk is unclear. […] Participant‐level data for Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) participants with established cardiovascular disease were used in a Type 2 diabetes‐specific simulation model to quantify the likely impact of different HbA_1c decrements on complication rates. […] The use of the TECOS data limits our findings to people with Type 2 diabetes and established cardiovascular disease. […] Ten‐year micro‐ and macrovascular rates were estimated with HbA_1c levels fixed at 86, 75, 64, 53 and 42 mmol/mol (10%, 9%, 8%, 7% and 6%) while holding other risk factors constant at their baseline levels. Cumulative relative risk reductions for each outcome were derived for each HbA_1c decrement. […] Of 5717 participants studied, 72.0% were men and 74.2% White European, with a mean (sd) age of 66.2 (7.9) years, systolic blood pressure 134 (16.9) mmHg, LDL‐cholesterol 2.3 (0.9) mmol/l, HDL‐cholesterol 1.13 (0.3) mmol/l and median Type 2 diabetes duration 9.6 (5.1–15.6) years. Ten‐year cumulative relative risk reductions for modelled HbA_1c values of 75, 64, 53 and 42 mmol/mol, relative to 86 mmol/mol, were 4.6%, 9.3%, 15.1% and 20.2% for myocardial infarction; 6.0%, 12.8%, 19.6% and 25.8% for stroke; 14.4%, 26.6%, 37.1% and 46.4% for diabetes‐related ulcer; 21.5%, 39.0%, 52.3% and 63.1% for amputation; and 13.6%, 25.4%, 36.0% and 44.7 for single‐eye blindness. […] We did not investigate outcomes for renal failure or chronic heart failure as previous research conducted to create the model did not find HbA_1c to be a statistically significant independent risk factor for either condition, therefore no clinically meaningful differences would be expected from modelling different HbA_1c levels 11.”

“For microvascular complications, the absolute median estimates tended to be lower than for macrovascular complications at the same HbA_1c level, but cumulative relative risk reductions were greater. For amputation the 10‐year absolute median estimate for a modelled constant HbA_1c of 86 mmol/mol (10%) was 3.8% (3.7, 3.9), with successively lower values for each modelled 1% HbA_1c decrement. Compared with the 86 mmol/mol (10%) HbA_1c level, median relative risk reductions for amputation were 21.5% (21.1, 21.9) at 75 mmol/mol (9%) increasing to 52.3% (52.0, 52.6) at 53 mmol/mol (7%). […] Relative risk reductions in micro‐ and macrovascular complications for each 1% HbA_1c reduction were similar for each decrement. The exception was all‐cause mortality, where the relative risk reductions for 1% HbA_1c decrements were greater at higher baseline HbA_1c levels. These simulated outcomes differ from the Diabetes Control and Complications Trial outcome in people with Type 1 diabetes, where lowering HbA_1c from higher baseline levels had a greater impact on microvascular risk reduction 18.”

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iii. Laser photocoagulation for proliferative diabetic retinopathy (Cochrane review).

“Diabetic retinopathy is a complication of diabetes in which high blood sugar levels damage the blood vessels in the retina. Sometimes new blood vessels grow in the retina, and these can have harmful effects; this is known as proliferative diabetic retinopathy. Laserphotocoagulation is an intervention that is commonly used to treat diabetic retinopathy, in which light energy is applied to the retinawith the aim of stopping the growth and development of new blood vessels, and thereby preserving vision. […] The aim of laser photocoagulation is to slow down the growth of new blood vessels in the retina and thereby prevent the progression of visual loss (Ockrim 2010). Focal laser photocoagulation uses the heat of light to seal or destroy abnormal blood vessels in the retina. Individual vessels are treated with a small number of laser burns.

PRP [panretinal photocoagulation, US] aims to slow down the growth of new blood vessels in a wider area of the retina. Many hundreds of laser burns are placed on the peripheral parts of the retina to stop blood vessels from growing (RCOphth 2012). It is thought that the anatomic and functional changes that result from photocoagulation may improve the oxygen supply to the retina, and so reduce the stimulus for neovascularisation (Stefansson 2001). Again the exact mechanisms are unclear, but it is possible that the decreased area of retinal tissue leads to improved oxygenation and a reduction in the levels of anti-vascular endothelial growth factor. A reduction in levels of anti-vascular endothelial growth factor may be important in reducing the risk of harmful new vessels forming. […] Laser photocoagulation is a well-established common treatment for DR and there are many different potential strategies for delivery of laser treatment that are likely to have different effects. A systematic review of the evidence for laser photocoagulation will provide important information on benefits and harms to guide treatment choices. […] This is the first in a series of planned reviews on laser photocoagulation. Future reviews will compare different photocoagulation techniques.”

“We identified a large number of trials of laser photocoagulation of diabetic retinopathy (n = 83) but only five of these studies were eligible for inclusion in the review, i.e. they compared laser photocoagulation with currently available lasers to no (or deferred) treatment. Three studies were conducted in the USA, one study in the UK and one study in Japan. A total of 4786 people (9503 eyes) were included in these studies. The majority of participants in four of these trials were people with proliferative diabetic retinopathy; one trial recruited mainly people with non-proliferative retinopathy.”

“At 12 months there was little difference between eyes that received laser photocoagulation and those allocated to no treatment (or deferred treatment), in terms of loss of 15 or more letters of visual acuity (risk ratio (RR) 0.99, 95% confidence interval (CI) 0.89 to1.11; 8926 eyes; 2 RCTs, low quality evidence). Longer term follow-up did not show a consistent pattern, but one study found a 20% reduction in risk of loss of 15 or more letters of visual acuity at five years with laser treatment. Treatment with laser reduced the risk of severe visual loss by over 50% at 12 months (RR 0.46, 95% CI 0.24to 0.86; 9276 eyes; 4 RCTs, moderate quality evidence). There was a beneficial effect on progression of diabetic retinopathy with treated eyes experiencing a 50% reduction in risk of progression of diabetic retinopathy (RR 0.49, 95% CI 0.37 to 0.64; 8331 eyes; 4 RCTs, low quality evidence) and a similar reduction in risk of vitreous haemorrhage (RR 0.56, 95% CI 0.37 to 0.85; 224 eyes; 2RCTs, low quality evidence).”

“Overall there is not a large amount of evidence from RCTs on the effects of laser photocoagulation compared to no treatment or deferred treatment. The evidence is dominated by two large studies conducted in the US population (DRS 1978; ETDRS 1991). These two studies were generally judged to be at low or unclear risk of bias, with the exception of inevitable unmasking of patients due to differences between intervention and control. […] In current clinical guidelines, e.g. RCOphth 2012, PRP is recommended in high-risk PDR. The recommendation is that “as retinopathy approaches the proliferative stage, laser scatter treatment (PRP) should be increasingly considered to prevent progression to high risk PDR” based on other factors such as patients’ compliance or planned cataract surgery.

These recommendations need to be interpreted while considering the risk of visual loss associated with different levels of severity of DR, as well as the risk of progression. Since PRP reduces the risk of severe visual loss, but not moderate visual loss that is more related to diabetic maculopathy, most ophthalmologists judge that there is little benefit in treating non-proliferative DR at low risk of severe visual damage, as patients would incur the known adverse effects of PRP, which, although mild, include pain and peripheral visual field loss and transient DMO [diabetic macular oedema, US]. […] This review provides evidence that laser photocoagulation is beneficial in treating diabetic retinopathy. […] based on the baseline risk of progression of the disease, and risk of visual loss, the current approach of caution in treating non-proliferative DR with laser would appear to be justified.

By current standards the quality of the evidence is not high, however, the effects on risk of progression and risk of severe visual loss are reasonably large (50% relative risk reduction).”

…

iv. Immune Recognition of β-Cells: Neoepitopes as Key Players in the Loss of Tolerance.

I should probably warn beforehand that this one is rather technical. It relates reasonably closely to topics covered in the molecular biology book I recently covered here on the blog, and if I had not read that book quite recently I almost certainly would not have been able to read the paper – so the coverage below is more ‘for me’ than ‘for you’. Anyway, some quotes:

“Prior to the onset of type 1 diabetes, there is progressive loss of immune self-tolerance, evidenced by the accumulation of islet autoantibodies and emergence of autoreactive T cells. Continued autoimmune activity leads to the destruction of pancreatic β-cells and loss of insulin secretion. Studies of samples from patients with type 1 diabetes and of murine disease models have generated important insights about genetic and environmental factors that contribute to susceptibility and immune pathways that are important for pathogenesis. However, important unanswered questions remain regarding the events that surround the initial loss of tolerance and subsequent failure of regulatory mechanisms to arrest autoimmunity and preserve functional β-cells. In this Perspective, we discuss various processes that lead to the generation of neoepitopes in pancreatic β-cells, their recognition by autoreactive T cells and antibodies, and potential roles for such responses in the pathology of disease. Emerging evidence supports the relevance of neoepitopes generated through processes that are mechanistically linked with β-cell stress. Together, these observations support a paradigm in which neoepitope generation leads to the activation of pathogenic immune cells that initiate a feed-forward loop that can amplify the antigenic repertoire toward pancreatic β-cell proteins.”

“Enzymatic posttranslational processes that have been implicated in neoepitope generation include acetylation (10), citrullination (11), glycosylation (12), hydroxylation (13), methylation (either protein or DNA methylation) (14), phosphorylation (15), and transglutamination (16). Among these, citrullination and transglutamination are most clearly implicated as processes that generate neoantigens in human disease, but evidence suggests that others also play a role in neoepitope formation […] Citrulline, which is among the most studied PTMs in the context of autoimmunity, is a diagnostic biomarker of rheumatoid arthritis (RA). […] Anticitrulline antibodies are among the earliest immune responses that are diagnostic of RA and often correlate with disease severity (18). We have recently documented the biological consequences of citrulline modifications and autoimmunity that arise from pancreatic β-cell proteins in the development of T1D (19). In particular, citrullinated GAD65 and glucose-regulated protein (GRP78) elicit antibody and T-cell responses in human T1D and in NOD diabetes, respectively (20,21).”

“Carbonylation is an irreversible, iron-catalyzed oxidative modification of the side chains of lysine, arginine, threonine, or proline. Mitochondrial functions are particularly sensitive to carbonyl modification, which also has detrimental effects on other intracellular enzymatic pathways (30). A number of diseases have been linked with altered carbonylation of self-proteins, including Alzheimer and Parkinson diseases and cancer (27). There is some data to support that carbonyl PTM is a mechanism that directs unstable self-proteins into cellular degradation pathways. It is hypothesized that carbonyl PTM [post-translational modification] self-proteins that fail to be properly degraded in pancreatic β-cells are autoantigens that are targeted in T1D. Recently submitted studies have identified several carbonylated pancreatic β-cell neoantigens in human and murine models of T1D (27). Among these neoantigens are chaperone proteins that are required for the appropriate folding and secretion of insulin. These studies imply that although some PTM self-proteins may be direct targets of autoimmunity, others may alter, interrupt, or disturb downstream metabolic pathways in the β-cell. In particular, these studies indicated that upstream PTMs resulted in misfolding and/or metabolic disruption between proinsulin and insulin production, which provides one explanation for recent observations of increased proinsulin-to-insulin ratios in the progression of T1D (31).”

“Significant hypomethylation of DNA has been linked with several classic autoimmune diseases, such as SLE, multiple sclerosis, RA, Addison disease, Graves disease, and mixed connective tissue disease (36). Therefore, there is rationale to consider the possible influence of epigenetic changes on protein expression and immune recognition in T1D. Relevant to T1D, epigenetic modifications occur in pancreatic β-cells during progression of diabetes in NOD mice (37). […] Consequently, DNMTs [DNA methyltransferases] and protein arginine methyltransferases are likely to play a role in the regulation of β-cell differentiation and insulin gene expression, both of which are pathways that are altered in the presence of inflammatory cytokines. […] Eizirik et al. (38) reported that exposure of human islets to proinflammatory cytokines leads to modulation of transcript levels and increases in alternative splicing for a number of putative candidate genes for T1D. Their findings suggest a mechanism through which alternative splicing may lead to the generation of neoantigens and subsequent presentation of novel β-cell epitopes (39).”

“The phenomenon of neoepitope recognition by autoantibodies has been shown to be relevant in a variety of autoimmune diseases. For example, in RA, antibody responses directed against various citrullinated synovial proteins are remarkably disease-specific and routinely used as a diagnostic test in the clinic (18). Appearance of the first anticitrullinated protein antibodies occurs years prior to disease onset, and accumulation of additional autoantibody specificities correlates closely with the imminent onset of clinical arthritis (44). There is analogous evidence supporting a hierarchical emergence of autoantibody specificities and multiple waves of autoimmune damage in T1D (3,45). Substantial data from longitudinal studies indicate that insulin and GAD65 autoantibodies appear at the earliest time points during progression, followed by additional antibody specificities directed at IA-2 and ZnT8.”

“Multiple autoimmune diseases often cluster within families (or even within one person), implying shared etiology. Consequently, relevant insights can be gleaned from studies of more traditional autoantibody-mediated systemic autoimmune diseases, such as SLE and RA, where inter- and intramolecular epitope spreading are clearly paradigms for disease progression (47). In general, early autoimmunity is marked by restricted B- and T-cell epitopes, followed by an expanded repertoire coinciding with the onset of more significant tissue pathology […] Akin to T1D, other autoimmune syndromes tend to cluster to subcellular tissues or tissue components that share biological or biochemical properties. For example, SLE is marked by autoimmunity to nucleic acid–bearing macromolecules […] Unlike other systemic autoantibody-mediated diseases, such as RA and SLE, there is no clear evidence that T1D-related autoantibodies play a pathogenic role. Autoantibodies against citrulline-containing neoepitopes of proteoglycan are thought to trigger or intensify arthritis by forming immune complexes with this autoantigen in the joints of RA patients with anticitrullinated protein antibodies. In a similar manner, autoantibodies and immune complexes are hallmarks of tissue pathology in SLE. Therefore, it remains likely that autoantibodies or the B cells that produce them contribute to the pathogenesis of T1D.”

“In summation, the existing literature demonstrates that oxidation, citrullination, and deamidation can have a direct impact on T-cell recognition that contributes to loss of tolerance.”

“There is a general consensus that the pathogenesis of T1D is initiated when individuals who possess a high level of genetic risk (e.g., susceptible HLA, insulin VNTR, PTPN22 genotypes) are exposed to environmental factors (e.g., enteroviruses, diet, microbiome) that precipitate a loss of tolerance that manifests through the appearance of insulin and/or GAD autoantibodies. This early autoimmunity is followed by epitope spreading, increasing both the number of antigenic targets and the diversity of epitopes within these targets. These processes create a feed-forward loop antigen release that induces increasing inflammation and increasing numbers of distinct T-cell specificities (64). The formation and recognition of neoepitopes represents one mechanism through which epitope spreading can occur. […] mechanisms related to neoepitope formation and recognition can be envisioned at multiple stages of T1D pathogenesis. At the level of genetic risk, susceptible individuals may exhibit a genetically driven impairment of their stress response, increasing the likelihood of neoepitope formation. At the level of environmental exposure, many of the insults that are thought to initiate T1D are known to cause neoepitope formation. During the window of β-cell destruction that encompasses early autoimmunity through dysglycemia and diagnosis of T1D it remains unclear when neoepitope responses appear in relation to “classic” responses to insulin and GAD65. However, by the time of onset, neoepitope responses are clearly present and remain as part of the ongoing autoimmunity that is present during established T1D. […] The ultimate product of both direct and indirect generation of neoepitopes is an accumulation of robust and diverse autoimmune B- and T-cell responses, accelerating the pathological destruction of pancreatic islets. Clearly, the emergence of sophisticated methods of tissue and single-cell proteomics will identify novel neoepitopes, including some that occur at near the earliest stages of disease. A detailed mechanistic understanding of the pathways that lead to specific classes of neoepitopes will certainly suggest targets of therapeutic manipulation and intervention that would be hoped to impede the progression of disease.”

…

v. Diabetes technology: improving care, improving patient‐reported outcomes and preventing complications in young people with Type 1 diabetes.

“With the evolution of diabetes technology, those living with Type 1 diabetes are given a wider arsenal of tools with which to achieve glycaemic control and improve patient‐reported outcomes. Furthermore, the use of these technologies may help reduce the risk of acute complications, such as severe hypoglycaemia and diabetic ketoacidosis, as well as long‐term macro‐ and microvascular complications. […] Unfortunately, diabetes goals are often unmet and people with Type 1 diabetes too frequently experience acute and long‐term complications of this condition, in addition to often having less than ideal psychosocial outcomes. Increasing realization of the importance of patient‐reported outcomes is leading to diabetes care delivery becoming more patient‐centred. […] Optimal diabetes management requires both the medical and psychosocial needs of people with Type 1 diabetes and their caregivers to be addressed. […] The aim of this paper was to demonstrate how, by incorporating technology into diabetes care, we can increase patient‐centered care, reduce acute and chronic diabetes complications, and improve clinical outcomes and quality of life.”

[The paper’s Table 2 on page 422 of the pdf-version is awesome, it includes a lot of different Hba1c estimates from various patient populations all across the world. The numbers included in the table are slightly less awesome, as most populations only achieve suboptimal metabolic control.]

“The risks of all forms of complications increase with higher HbA_1c concentration, increasing diabetes duration, hypertension, presence of other microvascular complications, obesity, insulin resistance, hyperlipidaemia and smoking 6. Furthermore, the Diabetes Research in Children (DirecNet) study has shown that individuals with Type 1 diabetes have white matter differences in the brain and cognitive differences compared with individuals without Type 1 diabetes. These studies showed that the degree of structural differences in the brain were related to the degree of chronic hyperglycaemia, hypoglycaemia and glucose variability 7. […] In addition to long‐term complications, people with Type 1 diabetes are also at risk of acute complications. Severe hypoglycaemia, a hypoglycaemic event resulting in altered/loss of consciousness or seizures, is a serious complication of insulin therapy. If unnoticed and untreated, severe hypoglycaemia can result in death. […] The incidence of diabetic ketoacidosis, a life‐threatening consequence of diabetes, remains unacceptably high in children with established diabetes (Table 5). The annual incidence of ketoacidosis was 5% in the Prospective Diabetes Follow‐Up Registry (DPV) in Germany and Austria, 6.4% in the National Paediatric Diabetes Audit (NPDA), and 7.1% in the Type 1 Diabetes Exchange (T1DX) registry 10. Psychosocial factors including female gender, non‐white race, lower socio‐economic status, and elevated HbA_1c all contribute to increased risk of diabetic ketoacidosis 11.”

“Depression is more common in young people with Type 1 diabetes than in young people without a chronic disease […] Depression can make it more difficult to engage in diabetes self‐management behaviours, and as a result, contributes to suboptimal glycaemic control and lower rates of self‐monitoring of blood glucose (SMBG) in young people with Type 1 diabetes 15. […] Unlike depression, diabetes distress is not a clinical diagnosis but rather emotional distress that comes from the burden of living with and managing diabetes 16. A recent systematic review found that roughly one‐third of young people with Type 1 diabetes (age 10–20 years) have some level of diabetes distress and that diabetes distress was consistently associated with higher HbA_1c and worse self‐management 17. […] Eating and weight‐related comorbidities also exist for individuals with Type 1 diabetes. There is a higher incidence of obesity in individuals with Type 1 diabetes on intensive insulin therapy. […] Adolescent girls and young adult women with Type 1 diabetes are more likely to omit insulin for weight loss and have disordered eating habits 20.”

“In addition to screening for and treating depression and diabetes distress to improve overall diabetes management, it is equally important to assess quality of life as well as positive coping factors that may also influence self‐management and well‐being. For example, lower scores on the PROMIS^® measure of global health, which assesses social relationships as well as physical and mental well‐being, have been linked to higher depression scores and less frequent blood glucose checks 13. Furthermore, coping strategies such as problem‐solving, emotional expression, and acceptance have been linked to lower HbA_1c and enhanced quality of life 21.”

“Self‐monitoring of blood glucose via multiple finger sticks for capillary blood samples per day has been the ‘gold standard’ for glucose monitoring, but SMBG only provides glucose measurements as snapshots in time. Still, the majority of young people with Type 1 diabetes use SMBG as their main method to assess glycaemia. Data from the T1DX registry suggest that an increased frequency of SMBG is associated with lower HbA_1c levels 23. The development of continuous glucose monitoring (CGM) provides more values, along with the rate and direction of glucose changes. […] With continued use, CGM has been shown to decrease the incidence of hypoglycaemia and HbA_1c levels 26. […] Insulin can be administered via multiple daily injections or continuous subcutaneous insulin infusion (insulin pumps). Over the last 30 years, insulin pumps have become smaller with more features, making them a valuable alternative to multiple daily injections. Insulin pump use in various registries ranges from as low as 5.9% among paediatric patients in the New Zealand national register 28 to as high as 74% in the German/Austrian DPV in children aged <6 years (Table 2) 29. Recent data suggest that consistent use of insulin pumps can result in improved HbA_1c values and decreased incidence of severe hypoglycaemia 30, 31. Insulin pumps have been associated with improved quality of life 32. The data on insulin pumps and diabetic ketoacidosis are less clear.”

“The majority of Type 1 diabetes management is carried out outside the clinical setting and in individuals’ daily lives. People with Type 1 diabetes must make complex treatment decisions multiple times daily; thus, diabetes self‐management skills are central to optimal diabetes management. Unfortunately, many people with Type 1 diabetes and their caregivers are not sufficiently familiar with the necessary diabetes self‐management skills. […] Parents are often the first who learn these skills. As children become older, they start receiving more independence over their diabetes care; however, the transition of responsibilities from caregiver to child is often unstructured and haphazard. It is important to ensure that both individuals with diabetes and their caregivers have adequate self‐management skills throughout the diabetes journey.”

“In the developed world (nations with the highest gross domestic product), 87% of the population has access to the internet and 68% report using a smartphone 39. Even in developing countries, 54% of people use the internet and 37% own smartphones 39. In many areas, smartphones are the primary source of internet access and are readily available. […] There are >1000 apps for diabetes on the Apple App Store and the Google Play store. Many of these apps have focused on nutrition, blood glucose logging, and insulin dosing. Given the prevalence of smartphones and the interest in having diabetes apps handy, there is the potential for using a smartphone to deliver education and decision support tools. […] The new psychosocial position statement from the ADA recommends routine psychosocial screening in clinic. These recommendations include screening for: 1) depressive symptoms annually, at diagnosis, or with changes in medical status; 2) anxiety and worry about hypoglycaemia, complications and other diabetes‐specific worries; 3) disordered eating and insulin omission for purposes of weight control; 4) and diabetes distress in children as young as 7 or 8 years old 16. Implementation of in‐clinic screening for depression in young people with Type 1 diabetes has already been shown to be feasible, acceptable and able to identify individuals in need of treatment who may otherwise have gone unnoticed for a longer period of time which would have been having a detrimental impact on physical health and quality of life 13, 40. These programmes typically use tablets […] to administer surveys to streamline the screening process and automatically score measures 13, 40. This automation allows psychologists and social workers to focus on care delivery rather than screening. In addition to depression screening, automated tablet‐based screening for parental depression, distress and anxiety; problem‐solving skills; and resilience/positive coping factors can help the care team understand other psychosocial barriers to care. This approach allows the development of patient‐ and caregiver‐centred interventions to improve these barriers, thereby improving clinical outcomes and complication rates.”

“With the advent of electronic health records, registries and downloadable medical devices, people with Type 1 diabetes have troves of data that can be analysed to provide insights on an individual and population level. Big data analytics for diabetes are still in the early stages, but present great potential for improving diabetes care. IBM Watson Health has partnered with Medtronic to deliver personalized insights to individuals with diabetes based on device data 48. Numerous other systems […] allow people with Type 1 diabetes to access their data, share their data with the healthcare team, and share de‐identified data with the research community. Data analysis and insights such as this can form the basis for the delivery of personalized digital health coaching. For example, historical patterns can be analysed to predict activity and lead to pro‐active insulin adjustment to prevent hypoglycaemia. […] Improvements to diabetes care delivery can occur at both the population level and at the individual level using insights from big data analytics.”

…

vi. Route to improving Type 1 diabetes mellitus glycaemic outcomes: real‐world evidence taken from the National Diabetes Audit.

“While control of blood glucose levels reduces the risk of diabetes complications, it can be very difficult for people to achieve. There has been no significant improvement in average glycaemic control among people with Type 1 diabetes for at least the last 10 years in many European countries 6.

The National Diabetes Audit (NDA) in England and Wales has shown relatively little change in the levels of HbA_1c being achieved in people with Type 1 diabetes over the last 10 years, with >70% of HbA_1c results each year being >58 mmol/mol (7.5%) 7.

Data for general practices in England are published by the NDA. NHS Digital publishes annual prescribing data, including British National Formulary (BNF) codes 7, 8. Together, these data provide an opportunity to investigate whether there are systematic associations between HbA_1c levels in people with Type 1 diabetes and practice‐level population characteristics, diabetes service levels and use of medication.”

“The Quality and Outcomes Framework (a payment system for general practice performance) provided a baseline list of all general practices in England for each year, the practice list size and number of people (both with Type 1 and Type 2 diabetes) on their diabetes register. General practice‐level data of participating practices were taken from the NDA 2013–2014, 2014–2015 and 2015–2016 (5455 practices in the last year). They include Type 1 diabetes population characteristics, routine review checks and the proportions of people achieving target glycaemic control and/or being at higher glycaemic risk.

Diabetes medication data for all people with diabetes were taken from the general practice prescribing in primary care data for 2013–2014, 2014–2015 and 2015–2016, including insulin and blood glucose monitoring (BGM) […] A total of 20 indicators were created that covered the epidemiological, service, medication, technological, costs and outcomes performance for each practice and year. The variance in these indicators over the 4‐year period and among general practices was also considered. […] The values of the indicators found to be in the 90^th percentile were used to quantify the potential of highest performing general practices. […] In total 13 085 practice‐years of data were analysed, covering 437 000 patient‐years of management.”

“There was significant variation among the participating general practices (Fig. 3) in the proportion of people achieving target glycaemic control target [percentage of people with HbA_1c ≤58 mmol/mol (7.5%)] and in the proportion at high glycaemic risk [percentage of people with HbA_1c >86 mmol/mol (10%)]. […] Our analysis showed that, at general practice level, the median target glycaemic control attainment was 30%, while the 10th percentile was 16%, and the 90^th percentile was 45%. The corresponding median for the high glycaemic risk percentage was 16%, while the 10th percentile (corresponding to the best performing practices) was 6% and the 90^th percentile (greatest proportion of Type 1 diabetes at high glycaemic risk) was 28%. Practices in the deciles for both lowest target glycaemic control and highest high glycaemic risk had 49% of the results in the 58–86 mmol/mol range. […] A very wide variation was found in the percentage of insulin for presumed pump use (deduced from prescriptions of fast‐acting vial insulin), with a median of 3.8% at general practice level. The 10th percentile was 0% and the 90^th percentile was 255% of the median inferred pump usage.”

“[O]ur findings suggest that if all practices optimized service and therapies to the levels achieved by the top decile then 16 100 (7%) more people with Type 1 diabetes would achieve the glycaemic control target of 58 mmol/mol (7.5%) and 11 500 (5%) fewer people would have HbA_1c >86 mmol/mol (10%). Put another way, if the results for all practices were at the top decile level, 36% vs 29% of people with Type 1 diabetes would achieve the glycaemic control target of HbA_1c ≤ 58 mmol/mol (7.5%), and as few as 10% could have HbA_1c levels > 86 mmol/mol (10%) compared with 15% currently (Fig. 6). This has significant implications for the potential to improve the longer‐term outcomes of people with Type 1 diabetes, given the close link between glycaemia and complications in such individuals 5, 10, 11.”

“We found that the significant variation among the participating general practices (Fig. 2) in terms of the proportion of people with HbA_1c ≤58 mmol/mol (7.5%) was only partially related to a lower proportion of people with HbA_1c >86 mmol/mol (10%). There was only a weak relationship between level of target glycaemia achieved and avoidance of very suboptimal glycaemia. The overall r² value was 0.6. This suggests that there is a degree of independence between these outcomes, so that success factors at a general practice level differ for people achieving optimal glycaemia vs those factors affecting avoiding a level of at risk glycaemia.”

Molecular biology (II)

Below I have added some more quotes and links related to the book’s coverage:

…

“[P]roteins are the most abundant molecules in the body except for water. […] Proteins make up half the dry weight of a cell whereas DNA and RNA make up only 3 per cent and 20 per cent respectively. […] The approximately 20,000 protein-coding genes in the human genome can, by alternative splicing, multiple translation starts, and post-translational modifications, produce over 1,000,000 different proteins, collectively called ‘the proteome‘. It is the size of the proteome and not the genome that defines the complexity of an organism. […] For simple organisms, such as viruses, all the proteins coded by their genome can be deduced from its sequence and these comprise the viral proteome. However for higher organisms the complete proteome is far larger than the genome […] For these organisms not all the proteins coded by the genome are found in any one tissue at any one time and therefore a partial proteome is usually studied. What are of interest are those proteins that are expressed in specific cell types under defined conditions.”

“Enzymes are proteins that catalyze or alter the rate of chemical reactions […] Enzymes can speed up reactions […] but they can also slow some reactions down. Proteins play a number of other critical roles. They are involved in maintaining cell shape and providing structural support to connective tissues like cartilage and bone. Specialized proteins such as actin and myosin are required [for] muscular movement. Other proteins act as ‘messengers’ relaying signals to regulate and coordinate various cell processes, e.g. the hormone insulin. Yet another class of protein is the antibodies, produced in response to foreign agents such as bacteria, fungi, and viruses.”

“Proteins are composed of amino acids. Amino acids are organic compounds with […] an amino group […] and a carboxyl group […] In addition, amino acids carry various side chains that give them their individual functions. The twenty-two amino acids found in proteins are called proteinogenic […] but other amino acids exist that are non-protein functioning. […] A peptide bond is formed between two amino acids by the removal of a water molecule. […] each individual unit in a peptide or protein is known as an amino acid residue. […] Chains of less than 50-70 amino acid residues are known as peptides or polypeptides and >50-70 as proteins, although many proteins are composed of more than one polypeptide chain. […] Proteins are macromolecules consisting of one or more strings of amino acids folded into highly specific 3D-structures. Each amino acid has a different size and carries a different side group. It is the nature of the different side groups that facilitates the correct folding of a polypeptide chain into a functional tertiary protein structure.”

“Atoms scatter the waves of X-rays mainly through their electrons, thus forming secondary or reflected waves. The pattern of X-rays diffracted by the atoms in the protein can be captured on a photographic plate or an image sensor such as a charge coupled device placed behind the crystal. The pattern and relative intensity of the spots on the diffraction image are then used to calculate the arrangement of atoms in the original protein. Complex data processing is required to convert the series of 2D diffraction or scatter patterns into a 3D image of the protein. […] The continued success and significance of this technique for molecular biology is witnessed by the fact that almost 100,000 structures of biological molecules have been determined this way, of which most are proteins.”

“The number of proteins in higher organisms far exceeds the number of known coding genes. The fact that many proteins carry out multiple functions but in a regulated manner is one way a complex proteome arises without increasing the number of genes. Proteins that performed a single role in the ancestral organism have acquired extra and often disparate functions through evolution. […] The active site of an enzyme employed in catalysis is only a small part of the protein, leaving spare capacity for acquiring a second function. […] The glycolytic pathway is involved in the breakdown of sugars such as glucose to release energy. Many of the highly conserved and ancient enzymes from this pathway have developed secondary or ‘moonlighting’ functions. Proteins often change their location in the cell in order to perform a ‘second job’. […] The limited size of the genome may not be the only evolutionary pressure for proteins to moonlight. Combining two functions in one protein can have the advantage of coordinating multiple activities in a cell, enabling it to respond quickly to changes in the environment without the need for lengthy transcription and translational processes.”

“Post-translational modifications (PTMs) […] is [a] process that can modify the role of a protein by addition of chemical groups to amino acids in the peptide chain after translation. Addition of phosphate groups (phosphorylation), for example, is a common mechanism for activating or deactivating an enzyme. Other common PTMs include addition of acetyl groups (acetylation), glucose (glucosylation), or methyl groups (methylation). […] Some additions are reversible, facilitating the switching between active and inactive states, and others are irreversible such as marking a protein for destruction by ubiquitin. [The difference between reversible and irreversible modifications can be quite important in pharmacology, and if you’re curious to know more about these topics Coleman’s drug metabolism text provide great coverage of related topics – US.] Diseases caused by malfunction of these modifications highlight the importance of PTMs. […] in diabetes [h]igh blood glucose lead to unwanted glocosylation of proteins. At the high glucose concentrations associated with diabetes, an unwanted irreversible chemical reaction binds the gllucose to amino acid residues such as lysines exposed on the protein surface. The glucosylated proteins then behave badly, cross-linking themselves to the extracellular matrix. This is particularly dangerous in the kidney where it decreases function and can lead to renal failure.”

“Twenty thousand protein-coding genes make up the human genome but for any given cell only about half of these are expressed. […] Many genes get switched off during differentiation and a major mechanism for this is epigenetics. […] an epigenetic trait […] is ‘a stably heritable phenotype resulting from changes in the chromosome without alterations in the DNA sequence’. Epigenetics involves the chemical alteration of DNA by methyl or other small molecular groups to affect the accessibility of a gene by the transcription machinery […] Epigenetics can […] act on gene expression without affecting the stability of the genetic code by modifying the DNA, the histones in chromatin, or a whole chromosome. […] Epigenetic signatures are not only passed on to somatic daughter cells but they can also be transferred through the germline to the offspring. […] At first the evidence appeared circumstantial but more recent studies have provided direct proof of epigenetic changes involving gene methylation being inherited. Rodent models have provided mechanistic evidence. […] the importance of epigenetics in development is highlighted by the fact that low dietary folate, a nutrient essential for methylation, has been linked to higher risk of birth defects in the offspring.” […on the other hand, well…]

“The cell cycle is divided into phases […] Transition from G1 into S phase commits the cell to division and is therefore a very tightly controlled restriction point. Withdrawal of growth factors, insufficient nucleotides, or energy to complete DNA replication, or even a damaged template DNA, would compromise the process. Problems are therefore detected and the cell cycle halted by cell cycle inhibitors before the cell has committed to DNA duplication. […] The cell cycle inhibitors inactive the kinases that promote transition through the phases, thus halting the cell cycle. […] The cell cycle can also be paused in S phase to allow time for DNA repairs to be carried out before cell division. The consequences of uncontrolled cell division are so catastrophic that evolution has provided complex checks and balances to maintain fidelity. The price of failure is apoptosis […] 50 to 70 billion cells die every day in a human adult by the controlled molecular process of apoptosis.”

“There are many diseases that arise because a particular protein is either absent or a faulty protein is produced. Administering a correct version of that protein can treat these patients. The first commercially available recombinant protein to be produced for medical use was human insulin to treat diabetes mellitus. […] (FDA) approved the recombinant insulin for clinical use in 1982. Since then over 300 protein-based recombinant pharmaceuticals have been licensed by the FDA and the European Medicines Agency (EMA) […], and many more are undergoing clinical trials. Therapeutic proteins can be produced in bacterial cells but more often mammalian cells such as the Chinese hamster ovary cell line and human fibroblasts are used as these hosts are better able to produce fully functional human protein. However, using mammalian cells is extremely expensive and an alternative is to use live animals or plants. This is called molecular pharming and is an innovative way of producing large amounts of protein relatively cheaply. […] In plant pharming, tobacco, rice, maize, potato, carrots, and tomatoes have all been used to produce therapeutic proteins. […] [One] class of proteins that can be engineered using gene-cloning technology is therapeutic antibodies. […] Therapeutic antibodies are designed to be monoclonal, that is, they are engineered so that they are specific for a particular antigen to which they bind, to block the antigen’s harmful effects. […] Monoclonal antibodies are at the forefront of biological therapeutics as they are highly specific and tend not to induce major side effects.”

“In gene therapy the aim is to restore the function of a faulty gene by introducing a correct version of that gene. […] a cloned gene is transferred into the cells of a patient. Once inside the cell, the protein encoded by the gene is produced and the defect is corrected. […] there are major hurdles to be overcome for gene therapy to be effective. One is the gene construct has to be delivered to the diseased cells or tissues. This can often be difficult […] Mammalian cells […] have complex mechanisms that have evolved to prevent unwanted material such as foreign DNA getting in. Second, introduction of any genetic construct is likely to trigger the patient’s immune response, which can be fatal […] once delivered, expression of the gene product has to be sustained to be effective. One approach to delivering genes to the cells is to use genetically engineered viruses constructed so that most of the viral genome is deleted […] Once inside the cell, some viral vectors such as the retroviruses integrate into the host genome […]. This is an advantage as it provides long-lasting expression of the gene product. However, it also poses a safety risk, as there is little control over where the viral vector will insert into the patient’s genome. If the insertion occurs within a coding gene, this may inactivate gene function. If it integrates close to transcriptional start sites, where promoters and enhancer sequences are located, inappropriate gene expression can occur. This was observed in early gene therapy trials [where some patients who got this type of treatment developed cancer as a result of it. A few more details here – US] […] Adeno-associated viruses (AAVs) […] are often used in gene therapy applications as they are non-infectious, induce only a minimal immune response, and can be engineered to integrate into the host genome […] However, AAVs can only carry a small gene insert and so are limited to use with genes that are of a small size. […] An alternative delivery system to viruses is to package the DNA into liposomes that are then taken up by the cells. This is safer than using viruses as liposomes do not integrate into the host genome and are not very immunogenic. However, liposome uptake by the cells can be less efficient, resulting in lower expression of the gene.”

…

Links:

One gene–one enzyme hypothesis.
Molecular chaperone.
Protein turnover.
Isoelectric point.
Gel electrophoresis. Polyacrylamide.
Two-dimensional gel electrophoresis.
Mass spectrometry.
Proteomics.
Peptide mass fingerprinting.
Worldwide Protein Data Bank.
Nuclear magnetic resonance spectroscopy of proteins.
Immunoglobulins. Epitope.
Western blot.
Immunohistochemistry.
Crystallin. β-catenin.
Protein isoform.
Prion.
Gene expression. Transcriptional regulation. Chromatin. Transcription factor. Gene silencing. Histone. NF-κB. Chromatin immunoprecipitation.
The agouti mouse model.
X-inactive specific transcript (Xist).
Cell cycle. Cyclin. Cyclin-dependent kinase.
Retinoblastoma protein pRb.
Cytochrome c. Caspase. Bcl-2 family. Bcl-2-associated X protein.
Hybridoma technology. Muromonab-CD3.
Recombinant vaccines and the development of new vaccine strategies.
Knockout mouse.
Adenovirus Vectors for Gene Therapy, Vaccination and Cancer Gene Therapy.
Genetically modified food. Bacillus thuringiensis. Golden rice.

 

A few (more) diabetes papers of interest

Earlier this week I covered a couple of papers, but the second paper turned out to include a lot of interesting stuff so I decided to cut the post short and postpone my coverage of the other papers I’d intended to cover in that post until a later point in time; this post includes some of those other papers I’d intended to cover in that post.

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i. TCF7L2 Genetic Variants Contribute to Phenotypic Heterogeneity of Type 1 Diabetes.

“Although the autoimmune destruction of β-cells has a major role in the development of type 1 diabetes, there is growing evidence that the differences in clinical, metabolic, immunologic, and genetic characteristics among patients (1) likely reflect diverse etiology and pathogenesis (2). Factors that govern this heterogeneity are poorly understood, yet these may have important implications for prognosis, therapy, and prevention.

The transcription factor 7 like 2 (TCF7L2) locus contains the single nucleotide polymorphism (SNP) most strongly associated with type 2 diabetes risk, with an ∼30% increase per risk allele (3). In a U.S. cohort, heterozygous and homozygous carriers of the at-risk alleles comprised 40.6% and 7.9%, respectively, of the control subjects and 44.3% and 18.3%, respectively, of the individuals with type 2 diabetes (3). The locus has no known association with type 1 diabetes overall (4–8), with conflicting reports in latent autoimmune diabetes in adults (8–16). […] Our studies in two separate cohorts have shown that the type 2 diabetes–associated TCF7L2 genetic variant is more frequent among specific subsets of individuals with autoimmune type 1 diabetes, specifically those with fewer markers of islet autoimmunity (22,23). These observations support a role of this genetic variant in the pathogenesis of diabetes at least in a subset of individuals with autoimmune diabetes. However, whether individuals with type 1 diabetes and this genetic variant have distinct metabolic abnormalities has not been investigated. We aimed to study the immunologic and metabolic characteristics of individuals with type 1 diabetes who carry a type 2 diabetes–associated allele of the TCF7L2 locus.”

“We studied 810 TrialNet participants with newly diagnosed type 1 diabetes and found that among individuals 12 years and older, the type 2 diabetes–associated TCF7L2 genetic variant is more frequent in those presenting with a single autoantibody than in participants who had multiple autoantibodies. These TCF7L2 variants were also associated with higher mean C-peptide AUC and lower mean glucose AUC levels at the onset of type 1 diabetes. […] These findings suggest that, besides the well-known link with type 2 diabetes, the TCF7L2 locus may play a role in the development of type 1 diabetes. The type 2 diabetes–associated TCF7L2 genetic variant identifies a subset of individuals with autoimmune type 1 diabetes and fewer markers of islet autoimmunity, lower glucose, and higher C-peptide at diagnosis. […] A possible interpretation of these data is that TCF7L2-encoded diabetogenic mechanisms may contribute to diabetes development in individuals with limited autoimmunity […]. Because the risk of progression to type 1 diabetes is lower in individuals with single compared with multiple autoantibodies, it is possible that in the absence of this type 2 diabetes–associated TCF7L2 variant, these individuals may have not manifested diabetes. If that is the case, we would postulate that disease development in these patients may have a type 2 diabetes–like pathogenesis in which islet autoimmunity is a significant component but not necessarily the primary driver.”

“The association between this genetic variant and single autoantibody positivity was present in individuals 12 years or older but not in children younger than 12 years. […] The results in the current study suggest that the type 2 diabetes–associated TCF7L2 genetic variant plays a larger role in older individuals. There is mounting evidence that the pathogenesis of type 1 diabetes varies by age (31). Younger individuals appear to have a more aggressive form of disease, with faster decline of β-cell function before and after onset of disease, higher frequency and severity of diabetic ketoacidosis, which is a clinical correlate of severe insulin deficiency, and lower C-peptide at presentation (31–35). Furthermore, older patients are less likely to have type 1 diabetes–associated HLA alleles and islet autoantibodies (28). […] Taken together, we have demonstrated that individuals with autoimmune type 1 diabetes who carry the type 2 diabetes–associated TCF7L2 genetic variant have a distinct phenotype characterized by milder immunologic and metabolic characteristics than noncarriers, closer to those of type 2 diabetes, with an important effect of age.”

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ii. Heart Failure: The Most Important, Preventable, and Treatable Cardiovascular Complication of Type 2 Diabetes.

“Concerns about cardiovascular disease in type 2 diabetes have traditionally focused on atherosclerotic vasculo-occlusive events, such as myocardial infarction, stroke, and limb ischemia. However, one of the earliest, most common, and most serious cardiovascular disorders in patients with diabetes is heart failure (1). Following its onset, patients experience a striking deterioration in their clinical course, which is marked by frequent hospitalizations and eventually death. Many sudden deaths in diabetes are related to underlying ventricular dysfunction rather than a new ischemic event. […] Heart failure and diabetes are linked pathophysiologically. Type 2 diabetes and heart failure are each characterized by insulin resistance and are accompanied by the activation of neurohormonal systems (norepinephrine, angiotensin II, aldosterone, and neprilysin) (3). The two disorders overlap; diabetes is present in 35–45% of patients with chronic heart failure, whether they have a reduced or preserved ejection fraction.”

“Treatments that lower blood glucose do not exert any consistently favorable effect on the risk of heart failure in patients with diabetes (6). In contrast, treatments that increase insulin signaling are accompanied by an increased risk of heart failure. Insulin use is independently associated with an enhanced likelihood of heart failure (7). Thiazolidinediones promote insulin signaling and have increased the risk of heart failure in controlled clinical trials (6). With respect to incretin-based secretagogues, liraglutide increases the clinical instability of patients with existing heart failure (8,9), and the dipeptidyl peptidase 4 inhibitors saxagliptin and alogliptin are associated with an increased risk of heart failure in diabetes (10). The likelihood of heart failure with the use of sulfonylureas may be comparable to that with thiazolidinediones (11). Interestingly, the only two classes of drugs that ameliorate hyperinsulinemia (metformin and sodium–glucose cotransporter 2 inhibitors) are also the only two classes of antidiabetes drugs that appear to reduce the risk of heart failure and its adverse consequences (12,13). These findings are consistent with experimental evidence that insulin exerts adverse effects on the heart and kidneys that can contribute to heart failure (14). Therefore, physicians can prevent many cases of heart failure in type 2 diabetes by careful consideration of the choice of agents used to achieve glycemic control. Importantly, these decisions have an immediate effect; changes in risk are seen within the first few months of changes in treatment. This immediacy stands in contrast to the years of therapy required to see a benefit of antidiabetes drugs on microvascular risk.”

“As reported by van den Berge et al. (4), the prognosis of patients with heart failure has improved over the past two decades; heart failure with a reduced ejection fraction is a treatable disease. Inhibitors of the renin-angiotensin system are a cornerstone of the management of both disorders; they prevent the onset of heart failure and the progression of nephropathy in patients with diabetes, and they reduce the risk of cardiovascular death and hospitalization in those with established heart failure (3,15). Diabetes does not influence the magnitude of the relative benefit of ACE inhibitors in patients with heart failure, but patients with diabetes experience a greater absolute benefit from treatment (16).”

“The totality of evidence from randomized trials […] demonstrates that in patients with diabetes, heart failure is not only common and clinically important, but it can also be prevented and treated. This conclusion is particularly significant because physicians have long ignored heart failure in their focus on glycemic control and their concerns about the ischemic macrovascular complications of diabetes (1).”

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iii. Closely related to the above study: Mortality Reduction Associated With β-Adrenoceptor Inhibition in Chronic Heart Failure Is Greater in Patients With Diabetes.

“Diabetes increases mortality in patients with chronic heart failure (CHF) and reduced left ventricular ejection fraction. Studies have questioned the safety of β-adrenoceptor blockers (β-blockers) in some patients with diabetes and reduced left ventricular ejection fraction. We examined whether β-blockers and ACE inhibitors (ACEIs) are associated with differential effects on mortality in CHF patients with and without diabetes. […] We conducted a prospective cohort study of 1,797 patients with CHF recruited between 2006 and 2014, with mean follow-up of 4 years.”

“RESULTS Patients with diabetes were prescribed larger doses of β-blockers and ACEIs than were patients without diabetes. Increasing β-blocker dose was associated with lower mortality in patients with diabetes (8.9% per mg/day; 95% CI 5–12.6) and without diabetes (3.5% per mg/day; 95% CI 0.7–6.3), although the effect was larger in people with diabetes (interaction P = 0.027). Increasing ACEI dose was associated with lower mortality in patients with diabetes (5.9% per mg/day; 95% CI 2.5–9.2) and without diabetes (5.1% per mg/day; 95% CI 2.6–7.6), with similar effect size in these groups (interaction P = 0.76).”

“Our most important findings are:

• Higher-dose β-blockers are associated with lower mortality in patients with CHF and LVSD, but patients with diabetes may derive more benefit from higher-dose β-blockers.

• Higher-dose ACEIs were associated with comparable mortality reduction in people with and without diabetes.

• The association between higher β-blocker dose and reduced mortality is most pronounced in patients with diabetes who have more severely impaired left ventricular function.

• Among patients with diabetes, the relationship between β-blocker dose and mortality was not associated with glycemic control or insulin therapy.”

“We make the important observation that patients with diabetes may derive more prognostic benefit from higher β-blocker doses than patients without diabetes. These data should provide reassurance to patients and health care providers and encourage careful but determined uptitration of β-blockers in this high-risk group of patients.”

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iv. Diabetes, Prediabetes, and Brain Volumes and Subclinical Cerebrovascular Disease on MRI: The Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS).

“Diabetes and prediabetes are associated with accelerated cognitive decline (1), and diabetes is associated with an approximately twofold increased risk of dementia (2). Subclinical brain pathology, as defined by small vessel disease (lacunar infarcts, white matter hyperintensities [WMH], and microhemorrhages), large vessel disease (cortical infarcts), and smaller brain volumes also are associated with an increased risk of cognitive decline and dementia (3–7). The mechanisms by which diabetes contributes to accelerated cognitive decline and dementia are not fully understood, but contributions of hyperglycemia to both cerebrovascular disease and primary neurodegenerative disease have been suggested in the literature, although results are inconsistent (2,8). Given that diabetes is a vascular risk factor, brain atrophy among individuals with diabetes may be driven by increased cerebrovascular disease. Brain magnetic resonance imaging (MRI) provides a noninvasive opportunity to study associations of hyperglycemia with small vessel disease (lacunar infarcts, WMH, microhemorrhages), large vessel disease (cortical infarcts), and brain volumes (9).”

“Overall, the mean age of participants [(n = 1,713)] was 75 years, 60% were women, 27% were black, 30% had prediabetes (HbA_1c 5.7 to <6.5%), and 35% had diabetes. Compared with participants without diabetes and HbA_1c <5.7%, those with prediabetes (HbA_1c 5.7 to <6.5%) were of similar age (75.2 vs. 75.0 years; P = 0.551), were more likely to be black (24% vs. 11%; P < 0.001), have less than a high school education (11% vs. 7%; P = 0.017), and have hypertension (71% vs. 63%; P = 0.012) (Table 1). Among participants with diabetes, those with HbA_1c <7.0% versus ≥7.0% were of similar age (75.4 vs. 75.1 years; P = 0.481), but those with diabetes and HbA_1c ≥7.0% were more likely to be black (39% vs. 28%; P = 0.020) and to have less than a high school education (23% vs. 16%; P = 0.031) and were more likely to have a longer duration of diabetes (12 vs. 8 years; P < 0.001).”

“Compared with participants without diabetes and HbA_1c <5.7%, those with diabetes and HbA_1c ≥7.0% had smaller total brain volume (β −0.20 SDs; 95% CI −0.31, −0.09) and smaller regional brain volumes, including frontal, temporal, occipital, and parietal lobes; deep gray matter; Alzheimer disease signature region; and hippocampus (all P < 0.05) […]. Compared with participants with diabetes and HbA_1c <7.0%, those with diabetes and HbA_1c ≥7.0% had smaller total brain volume (P < 0.001), frontal lobe volume (P = 0.012), temporal lobe volume (P = 0.012), occipital lobe volume (P = 0.008), parietal lobe volume (P = 0.015), deep gray matter volume (P < 0.001), Alzheimer disease signature region volume (0.031), and hippocampal volume (P = 0.016). Both participants with diabetes and HbA_1c <7.0% and those with prediabetes (HbA_1c 5.7 to <6.5%) had similar total and regional brain volumes compared with participants without diabetes and HbA_1c <5.7% (all P > 0.05). […] No differences in the presence of lobar microhemorrhages, subcortical microhemorrhages, cortical infarcts, and lacunar infarcts were observed among the diabetes-HbA_1c categories (all P > 0.05) […]. Compared with participants without diabetes and HbA_1c <5.7%, those with diabetes and HbA_1c ≥7.0% had increased WMH volume (P = 0.016). The WMH volume among participants with diabetes and HbA_1c ≥7.0% was also significantly greater than among those with diabetes and HbA_1c <7.0% (P = 0.017).”

“Those with diabetes duration ≥10 years were older than those with diabetes duration <10 years (75.9 vs. 75.0 years; P = 0.041) but were similar in terms of race and sex […]. Compared with participants with diabetes duration <10 years, those with diabetes duration ≥10 years has smaller adjusted total brain volume (β −0.13 SDs; 95% CI −0.20, −0.05) and smaller temporal lobe (β −0.14 SDs; 95% CI −0.24, −0.03), parietal lobe (β − 0.11 SDs; 95% CI −0.21, −0.01), and hippocampal (β −0.16 SDs; 95% CI −0.30, −0.02) volumes […]. Participants with diabetes duration ≥10 years also had a 2.44 times increased odds (95% CI 1.46, 4.05) of lacunar infarcts compared with those with diabetes duration <10 years”.

“Conclusions
In this community-based population, we found that ARIC-NCS participants with diabetes with HbA1c ≥7.0% have smaller total and regional brain volumes and an increased burden of WMH, but those with prediabetes (HbA1c 5.7 to <6.5%) and diabetes with HbA1c <7.0% have brain volumes and markers of subclinical cerebrovascular disease similar to those without diabetes. Furthermore, among participants with diabetes, those with more-severe disease (as measured by higher HbA1c and longer disease duration) had smaller total and regional brain volumes and an increased burden of cerebrovascular disease compared with those with lower HbA1c and shorter disease duration. However, we found no evidence that associations of diabetes with smaller brain volumes are mediated by cerebrovascular disease.

The findings of this study extend the current literature that suggests that diabetes is strongly associated with brain volume loss (11,25–27). Global brain volume loss (11,25–27) has been consistently reported, but associations of diabetes with smaller specific brain regions have been less robust (27,28). Similar to prior studies, the current results show that compared with individuals without diabetes, those with diabetes have smaller total brain volume (11,25–27) and regional brain volumes, including frontal and occipital lobes, deep gray matter, and the hippocampus (25,27). Furthermore, the current study suggests that greater severity of disease (as measured by HbA_1c and diabetes duration) is associated with smaller total and regional brain volumes. […] Mechanisms whereby diabetes may contribute to brain volume loss include accelerated amyloid-β and hyperphosphorylated tau deposition as a result of hyperglycemia (29). Another possible mechanism involves pancreatic amyloid (amylin) infiltration of the brain, which then promotes amyloid-β deposition (29). […] Taken together, […] the current results suggest that diabetes is associated with both lower brain volumes and increased cerebrovascular pathology (WMH and lacunes).”

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v. Interventions to increase attendance for diabetic retinopathy screening (Cochrane review).

“The primary objective of the review was to assess the effectiveness of quality improvement (QI) interventions that seek to increase attendance for DRS in people with type 1 and type 2 diabetes.

Secondary objectives were:
To use validated taxonomies of QI intervention strategies and behaviour change techniques (BCTs) to code the description of interventions in the included studies and determine whether interventions that include particular QI strategies or component BCTs are more effective in increasing screening attendance;
To explore heterogeneity in effect size within and between studies to identify potential explanatory factors for variability in effect size;
To explore differential effects in subgroups to provide information on how equity of screening attendance could be improved;
To critically appraise and summarise current evidence on the resource use, costs and cost effectiveness.”

“We included 66 RCTs conducted predominantly (62%) in the USA. Overall we judged the trials to be at low or unclear risk of bias. QI strategies were multifaceted and targeted patients, healthcare professionals or healthcare systems. Fifty-six studies (329,164 participants) compared intervention versus usual care (median duration of follow-up 12 months). Overall, DRS [diabetic retinopathy screening] attendance increased by 12% (risk difference (RD) 0.12, 95% confidence interval (CI) 0.10 to 0.14; low-certainty evidence) compared with usual care, with substantial heterogeneity in effect size. Both DRS-targeted (RD 0.17, 95% CI 0.11 to 0.22) and general QI interventions (RD 0.12, 95% CI 0.09 to 0.15) were effective, particularly where baseline DRS attendance was low. All BCT combinations were associated with significant improvements, particularly in those with poor attendance. We found higher effect estimates in subgroup analyses for the BCTs ‘goal setting (outcome)’ (RD 0.26, 95% CI 0.16 to 0.36) and ‘feedback on outcomes of behaviour’ (RD 0.22, 95% CI 0.15 to 0.29) in interventions targeting patients, and ‘restructuring the social environment’ (RD 0.19, 95% CI 0.12 to 0.26) and ‘credible source’ (RD 0.16, 95% CI 0.08 to 0.24) in interventions targeting healthcare professionals.”

“Ten studies (23,715 participants) compared a more intensive (stepped) intervention versus a less intensive intervention. In these studies DRS attendance increased by 5% (RD 0.05, 95% CI 0.02 to 0.09; moderate-certainty evidence).”

“Overall, we found that there is insufficient evidence to draw robust conclusions about the relative cost effectiveness of the interventions compared to each other or against usual care.”

“The results of this review provide evidence that QI interventions targeting patients, healthcare professionals or the healthcare system are associated with meaningful improvements in DRS attendance compared to usual care. There was no statistically significant difference between interventions specifically aimed at DRS and those which were part of a general QI strategy for improving diabetes care.”

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vi. Diabetes in China: Epidemiology and Genetic Risk Factors and Their Clinical Utility in Personalized Medication.

“The incidence of type 2 diabetes (T2D) has rapidly increased over recent decades, and T2D has become a leading public health challenge in China. Compared with European descents, Chinese patients with T2D are diagnosed at a relatively young age and low BMI. A better understanding of the factors contributing to the diabetes epidemic is crucial for determining future prevention and intervention programs. In addition to environmental factors, genetic factors contribute substantially to the development of T2D. To date, more than 100 susceptibility loci for T2D have been identified. Individually, most T2D genetic variants have a small effect size (10–20% increased risk for T2D per risk allele); however, a genetic risk score that combines multiple T2D loci could be used to predict the risk of T2D and to identify individuals who are at a high risk. […] In this article, we review the epidemiological trends and recent progress in the understanding of T2D genetic etiology and further discuss personalized medicine involved in the treatment of T2D.”

“Over the past three decades, the prevalence of diabetes in China has sharply increased. The prevalence of diabetes was reported to be less than 1% in 1980 (2), 5.5% in 2001 (3), 9.7% in 2008 (4), and 10.9% in 2013, according to the latest published nationwide survey (5) […]. The prevalence of diabetes was higher in the senior population, men, urban residents, individuals living in economically developed areas, and overweight and obese individuals. The estimated prevalence of prediabetes in 2013 was 35.7%, which was much higher than the estimate of 15.5% in the 2008 survey. Similarly, the prevalence of prediabetes was higher in the senior population, men, and overweight and obese individuals. However, prediabetes was more prevalent in rural residents than in urban residents. […] the 2013 survey also compared the prevalence of diabetes among different races. The crude prevalence of diabetes was 14.7% in the majority group, i.e., Chinese Han, which was higher than that in most minority ethnic groups, including Tibetan, Zhuang, Uyghur, and Muslim. The crude prevalence of prediabetes was also higher in the Chinese Han ethnic group. The Tibetan participants had the lowest prevalence of diabetes and prediabetes (4.3% and 31.3%).”

“[T]he prevalence of diabetes in young people is relatively high and increasing. The prevalence of diabetes in the 20- to 39-year age-group was 3.2%, according to the 2008 national survey (4), and was 5.9%, according to the 2013 national survey (5). The prevalence of prediabetes also increased from 9.0% in 2008 to 28.8% in 2013 […]. Young people suffering from diabetes have a higher risk of chronic complications, which are the major cause of mortality and morbidity in diabetes. According to a study conducted in Asia (6), patients with young-onset diabetes had higher mean concentrations of HbA_1c and LDL cholesterol and a higher prevalence of retinopathy (20% vs. 18%, P = 0.011) than those with late-onset diabetes. In the Chinese, patients with early-onset diabetes had a higher risk of nonfatal cardiovascular disease (7) than did patients with late-onset diabetes (odds ratio [OR] 1.91, 95% CI 1.81–2.02).”

“As approximately 95% of patients with diabetes in China have T2D, the rapid increase in the prevalence of diabetes in China may be attributed to the increasing rates of overweight and obesity and the reduction in physical activity, which is driven by economic development, lifestyle changes, and diet (3,11). According to a series of nationwide surveys conducted by the China Physical Fitness Surveillance Center (12), the prevalence of overweight (BMI ≥23.0 to <27.5 kg/m²) in Chinese adults aged 20–59 years increased from 37.4% in 2000 to 39.2% in 2005, 40.7% in 2010, and 41.2% in 2014, with an estimated increase of 0.27% per year. The prevalence of obesity (BMI ≥27.5 kg/m²) increased from 8.6% in 2000 to 10.3% in 2005, 12.2% in 2010, and 12.9% in 2014, with an estimated increase of 0.32% per year […]. The prevalence of central obesity increased from 13.9% in 2000 to 18.3% in 2005, 22.1% in 2010, and 24.9% in 2014, with an estimated increase of 0.78% per year. Notably, T2D develops at a considerably lower BMI in the Chinese population than that in European populations. […] The relatively high risk of diabetes at a lower BMI could be partially attributed to the tendency toward visceral adiposity in East Asian populations, including the Chinese population (13). Moreover, East Asian populations have been found to have a higher insulin sensitivity with a much lower insulin response than European descent and African populations, implying a lower compensatory β-cell function, which increases the risk of progressing to overt diabetes (14).”

“Over the past two decades, linkage analyses, candidate gene approaches, and large-scale GWAS have successfully identified more than 100 genes that confer susceptibility to T2D among the world’s major ethnic populations […], most of which were discovered in European populations. However, less than 50% of these European-derived loci have been successfully confirmed in East Asian populations. […] there is a need to identify specific genes that are associated with T2D in other ethnic populations. […] Although many genetic loci have been shown to confer susceptibility to T2D, the mechanism by which these loci participate in the pathogenesis of T2D remains unknown. Most T2D loci are located near genes that are related to β-cell function […] most single nucleotide polymorphisms (SNPs) contributing to the T2D risk are located in introns, but whether these SNPs directly modify gene expression or are involved in linkage disequilibrium with unknown causal variants remains to be investigated. Furthermore, the loci discovered thus far collectively account for less than 15% of the overall estimated genetic heritability.”

“The areas under the receiver operating characteristic curves (AUCs) are usually used to assess the discriminative accuracy of an approach. The AUC values range from 0.5 to 1.0, where an AUC of 0.5 represents a lack of discrimination and an AUC of 1 represents perfect discrimination. An AUC ≥0.75 is considered clinically useful. The dominant conventional risk factors, including age, sex, BMI, waist circumference, blood pressure, family history of diabetes, physical activity level, smoking status, and alcohol consumption, can be combined to construct conventional risk factor–based models (CRM). Several studies have compared the predictive capacities of models with and without genetic information. The addition of genetic markers to a CRM could slightly improve the predictive performance. For example, one European study showed that the addition of an 11-SNP GRS to a CRM marginally improved the risk prediction (AUC was 0.74 without and 0.75 with the genetic markers, P < 0.001) in a prospective cohort of 16,000 individuals (37). A meta-analysis (38) consisting of 23 studies investigating the predictive performance of T2D risk models also reported that the AUCs only slightly increased with the addition of genetic information to the CRM (median AUC was increased from 0.78 to 0.79). […] Despite great advances in genetic studies, the clinical utility of genetic information in the prediction, early identification, and prevention of T2D remains in its preliminary stage.”

“An increasing number of studies have highlighted that early nutrition has a persistent effect on the risk of diabetes in later life (40,41). China’s Great Famine of 1959–1962 is considered to be the largest and most severe famine of the 20th century […] Li et al. (43) found that offspring of mothers exposed to the Chinese famine have a 3.9-fold increased risk of diabetes or hyperglycemia as adults. A more recent study (the Survey on Prevalence in East China for Metabolic Diseases and Risk Factors [SPECT-China]) conducted in 2014, among 6,897 adults from Shanghai, Jiangxi, and Zhejiang provinces, had the same conclusion that famine exposure during the fetal period (OR 1.53, 95% CI 1.09–2.14) and childhood (OR 1.82, 95% CI 1.21–2.73) was associated with diabetes (44). These findings indicate that undernutrition during early life increases the risk of hyperglycemia in adulthood and this association is markedly exaggerated when facing overnutrition in later life.”

Systems Biology (II)

Some observations from the book’s chapter 3 below:

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“Without regulation biological processes would become progressively more and more chaotic. In living cells the primary source of information is genetic material. Studying the role of information in biology involves signaling (i.e. spatial and temporal transfer of information) and storage (preservation of information). Regarding the role of the genome we can distinguish three specific aspects of biological processes: steady-state genetics, which ensure cell-level and body homeostasis; genetics of development, which controls cell differentiation and genesis of the organism; and evolutionary genetics, which drives speciation. […] The ever growing demand for information, coupled with limited storage capacities, has resulted in a number of strategies for minimizing the quantity of the encoded information that must be preserved by living cells. In addition to combinatorial approaches based on noncontiguous genes structure, self-organization plays an important role in cellular machinery. Nonspecific interactions with the environment give rise to coherent structures despite the lack of any overt information store. These mechanisms, honed by evolution and ubiquitous in living organisms, reduce the need to directly encode large quantities of data by adopting a systemic approach to information management.”

“Information is commonly understood as a transferable description of an event or object. Information transfer can be either spatial (communication, messaging or signaling) or temporal (implying storage). […] The larger the set of choices, the lower the likelihood [of] making the correct choice by accident and — correspondingly — the more information is needed to choose correctly. We can therefore state that an increase in the cardinality of a set (the number of its elements) corresponds to an increase in selection indeterminacy. This indeterminacy can be understood as a measure of “a priori ignorance”. […] Entropy determines the uncertainty inherent in a given system and therefore represents the relative difficulty of making the correct choice. For a set of possible events it reaches its maximum value if the relative probabilities of each event are equal. Any information input reduces entropy — we can therefore say that changes in entropy are a quantitative measure of information. […] Physical entropy is highest in a state of equilibrium, i.e. lack of spontaneity (∆G = 0,0) which effectively terminates the given reaction. Regulatory processes which counteract the tendency of physical systems to reach equilibrium must therefore oppose increases in entropy. It can be said that a steady inflow of information is a prerequisite of continued function in any organism. As selections are typically made at the entry point of a regulatory process, the concept of entropy may also be applied to information sources. This approach is useful in explaining the structure of regulatory systems which must be “designed” in a specific way, reducing uncertainty and enabling accurate, error-free decisions.”

“The fire ant exudes a pheromone which enables it to mark sources of food and trace its own path back to the colony. In this way, the ant conveys pathing information to other ants. The intensity of the chemical signal is proportional to the abundance of the source. Other ants can sense the pheromone from a distance of several (up to a dozen) centimeters and thus locate the source themselves. […] As can be expected, an increase in the entropy of the information source (i.e. the measure of ignorance) results in further development of regulatory systems — in this case, receptors capable of receiving signals and processing them to enable accurate decisions. Over time, the evolution of regulatory mechanisms increases their performance and precision. The purpose of various structures involved in such mechanisms can be explained on the grounds of information theory. The primary goal is to select the correct input signal, preserve its content and avoid or eliminate any errors.”

“Genetic information stored in nucleotide sequences can be expressed and transmitted in two ways:
a. via replication (in cell division);
b. via transcription and translation (also called gene expression […])
Both processes act as effectors and can be triggered by certain biological signals transferred on request.
Gene expression can be defined as a sequence of events which lead to the synthesis of proteins or their products required for a particular function. In cell division, the goal of this process is to generate a copy of the entire genetic code (S phase), whereas in gene expression only selected fragments of DNA (those involved in the requested function) are transcribed and translated. […] Transcription calls for exposing a section of the cell’s genetic code and although its product (RNA) is short-lived, it can be recreated on demand, just like a carbon copy of a printed text. On the other hand, replication affects the entire genetic material contained in the cell and must conform to stringent precision requirements, particularly as the size of the genome increases.”

“The magnitude of effort involved in replication of genetic code can be visualized by comparing the DNA chain to a zipper […]. Assuming that the zipper consists of three pairs of interlocking teeth per centimeter (300 per meter) and that the human genome is made up of 3 billion […] base pairs, the total length of our uncoiled DNA in “zipper form” would be equal to […] 10,000 km […] If we were to unfasten the zipper at a rate of 1 m per second, the entire unzipping process would take approximately 3 months […]. This comparison should impress upon the reader the length of the DNA chain and the precision with which individual nucleotides must be picked to ensure that the resulting code is an exact copy of the source. It should also be noted that for each base pair the polymerase enzyme needs to select an appropriate matching nucleotide from among four types of nucleotides present in the solution, and attach it to the chain (clearly, no such problem occurs in zippers). The reliability of an average enzyme is on the order of 10^-3–10^-4, meaning that one error occurs for every 1,000–10,000 interactions between the enzyme and its substrate. Given this figure, replication of 3*10⁹ base pairs would introduce approximately 3 million errors (mutations) per genome, resulting in a highly inaccurate copy. Since the observed reliability of replication is far higher, we may assume that some corrective mechanisms are involved. Really, the remarkable precision of genetic replication is ensured by DNA repair processes, and in particular by the corrective properties of polymerase itself.”

“Many mutations are caused by the inherent chemical instability of nucleic acids: for example, cytosine may spontaneously convert to uracil. In the human genome such an event occurs approximately 100 times per day; however uracil is not normally encountered in DNA and its presence alerts defensive mechanisms which correct the error. Another type of mutation is spontaneous depurination, which also triggers its own, dedicated error correction procedure. Cells employ a large number of corrective mechanisms […] DNA repair mechanisms may be treated as an “immune system” which protects the genome from loss or corruption of genetic information. The unavoidable mutations which sometimes occur despite the presence of error correction-mechanisms can be masked due to doubled presentation (alleles) of genetic information. Thus, most mutations are recessive and not expressed in the phenotype. As the length of the DNA chain increases, mutations become more probable. It should be noted that the number of nucleotides in DNA is greater than the relative number of aminoacids participating in polypeptide chains. This is due to the fact that each aminoacid is encoded by exactly three nucleotides — a general principle which applies to all living organisms. […] Fidelity is, of course, fundamentally important in DNA replication as any harmful mutations introduced in its course are automatically passed on to all successive generations of cells. In contrast, transcription and translation processes can be more error-prone as their end products are relatively short-lived. Of note is the fact that faulty transcripts appear in relatively low quantities and usually do not affect cell functions, since regulatory processes ensure continued synthesis of the required substances until a suitable level of activity is reached. Nevertheless, it seems that reliable transcription of genetic material is sufficiently significant for cells to have developed appropriate proofreading mechanisms, similar to those which assist replication. […] the entire information pathway — starting with DNA and ending with active proteins — is protected against errors. We can conclude that fallibility is an inherent property of genetic information channels, and that in order to perform their intended function, these channels require error correction mechanisms.”

“The discrete nature of genetic material is an important property which distinguishes prokaryotes from eukaryotes. […] The ability to select individual nucleotide fragments and construct sequences from predetermined “building blocks” results in high adaptability to environmental stimuli and is a fundamental aspect of evolution. The discontinuous nature of genes is evidenced by the presence of fragments which do not convey structural information (introns), as opposed to structure-encoding fragments (exons). The initial transcript (pre-mRNA) contains introns as well as exons. In order to provide a template for protein synthesis, it must undergo further processing (also known as splicing): introns must be cleaved and exon fragments attached to one another. […] Recognition of intron-exon boundaries is usually very precise, while the reattachment of adjacent exons is subject to some variability. Under certain conditions, alternative splicing may occur, where the ordering of the final product does not reflect the order in which exon sequences appear in the source chain. This greatly increases the number of potential mRNA combinations and thus the variety of resulting proteins. […] While access to energy sources is not a major problem, sources of information are usually far more difficult to manage — hence the universal tendency to limit the scope of direct (genetic) information storage. Reducing the length of genetic code enables efficient packing and enhances the efficiency of operations while at the same time decreasing the likelihood of errors. […] The number of genes identified in the human genome is lower than the number of distinct proteins by a factor of 4; a difference which can be attributed to alternative splicing. […] This mechanism increases the variety of protein structures without affecting core information storage, i.e. DNA sequences. […] Primitive organisms often possess nearly as many genes as humans, despite the essential differences between both groups. Interspecies diversity is primarily due to the properties of regulatory sequences.”

“The discontinuous nature of genes is evolutionarily advantageous but comes at the expense of having to maintain a nucleus where such splicing processes can be safely conducted, in addition to efficient transport channels allowing transcripts to penetrate the nuclear membrane. While it is believed that at early stages of evolution RNA was the primary repository of genetic information, its present function can best be described as an information carrier. Since unguided proteins cannot ensure sufficient specificity of interaction with nucleic acids, protein-RNA complexes are used often in cases where specific fragments of genetic information need to be read. […] The use of RNA in protein complexes is common across all domains of the living world as it bridges the gap between discrete and continuous storage of genetic information.”

“Epigenetic differentiation mechanisms are particularly important in embryonic development. […] Unlike the function of mature organisms, embryonic programming refers to structures which do not yet exist but which need to be created through cell proliferation and differentiation. […] Differentiation of cells results in phenotypic changes. This phenomenon is the primary difference between development genetics and steady-state genetics. Functional differences are not, however, associated with genomic changes: instead they are mediated by the transcriptome where certain genes are preferentially selected for transcription while others are suppressed. […] In a mature, specialized cell only a small portion of the transcribable genome is actually expressed. The remainder of the cell’s genetic material is said to be silenced. Gene silencing is a permanent condition. Under normal circumstances mature cells never alter their function, although such changes may be forced in a laboratory setting […] Cells which make up the embryo at a very early stage of development are pluripotent, meaning that their purpose can be freely determined and that all of their genetic information can potentially be expressed (under certain conditions). […] At each stage of the development process the scope of pluripotency is reduced until, ultimately, the cell becomes monopotent. Monopotency implies that the final function of the cell has already been determined, although the cell itself may still be immature. […] functional dissimilarities between specialized cells are not associated with genetic mutations but rather with selective silencing of genes. […] Most genes which determine biological functions have a biallelic representation (i.e. a representation consisting of two alleles). The remainder (approximately 10 % of genes) is inherited from one specific parent, as a result of partial or complete silencing of their sister alleles (called paternal or maternal imprinting) which occurs during gametogenesis. The suppression of a single copy of the X chromosome is a special case of this phenomenon.”

“Evolutionary genetics is subject to two somewhat contradictory criteria. On the one hand, there is clear pressure on accurate and consistent preservation of biological functions and structures while on the other hand it is also important to permit gradual but persistent changes. […] the observable progression of adaptive traits which emerge as a result of evolution suggests a mechanism which promotes constructive changes over destructive ones. Mutational diversity cannot be considered truly random if it is limited to certain structures or functions. […] Approximately 50 % of the human genome consists of mobile segments, capable of migrating to various positions in the genome. These segments are called transposons and retrotransposons […] The mobility of genome fragments not only promotes mutations (by increasing the variability of DNA) but also affects the stability and packing of chromatin strands wherever such mobile sections are reintegrated with the genome. Under normal circumstances the activity of mobile sections is tempered by epigenetic mechanisms […]; however in certain situations gene mobility may be upregulated. In particular, it seems that in “prehistoric” (remote evolutionary) times such events occurred at a much faster pace, accelerating the rate of genetic changes and promoting rapid evolution. Cells can actively promote mutations by way of the so-called AID process (activity-dependent cytosine deamination). It is an enzymatic mechanism which converts cytosine into uracil, thereby triggering repair mechanisms and increasing the likelihood of mutations […] The existence of AID proves that cells themselves may trigger evolutionary changes and that the role of mutations in the emergence of new biological structures is not strictly passive.”

“Regulatory mechanisms which receive signals characterized by high degrees of uncertainty, must be able to make informed choices to reduce the overall entropy of the system they control. This property is usually associated with development of information channels. Special structures ought to be exposed within information channels connecting systems of different character as for example linking transcription to translation or enabling transduction of signals through the cellular membrane. Examples of structures which convey highly entropic information are receptor systems associated with blood coagulation and immune responses. The regulatory mechanism which triggers an immune response relies on relatively simple effectors (complement factor enzymes, phages and killer cells) coupled to a highly evolved receptor system, represented by specific antibodies and organized set of cells. Compared to such advanced receptors the structures which register the concentration of a given product (e.g. glucose in blood) are rather primitive. Advanced receptors enable the immune system to recognize and verify information characterized by high degrees of uncertainty. […] In sequential processes it is usually the initial stage which poses the most problems and requires the most information to complete successfully. It should come as no surprise that the most advanced control loops are those associated with initial stages of biological pathways.”

Endocrinology (part 3 – adrenal glands)

Some observations from chapter 3 below.

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“The normal adrenal gland weigh 4-5g. The cortex represents 90% of the normal gland and surrounds the medulla. […] Glucocorticoid (cortisol […]) production occurs from the zona fasciculata, and adrenal androgens arise from the zona reticularis. Both of these are under the control of ACTH [see also my previous post about the book – US], which regulates both steroid synthesis and also adrenocortical growth. […] Mineralocorticoid (aldosterone […]) synthesis occurs in zona glomerulosa, predominantly under the control of the renin-angiotensin system […], although ACTH also contributes to its regulation. […] The adrenal gland […] also produces sex steroids in the form of dehydroepiandrostenedione (DHEA) and androstenedione. The synthetic pathway is under the control of ACTH. Urinary steroid profiling provides quantitative information on the biosynthetic and catabolic pathways. […] CT is the most widely used modality for imaging the adrenal glands. […] MRI can also reliably detect adrenal masses >5-10mm in diameter and, in some circumstances, provides additional information to CT […] PET can be useful in locating tumours and metastases. […] Adrenal vein sampling (AVS) […] can be useful to lateralize an adenoma or to differentiate an adenoma from bilateral hyperplasia. […] AVS is of particular value in lateralizing small aldosterone-producing adenomas that cannot easily be visualized on CT or MRI. […] The procedure should only be undertaken in patients in whom surgery is feasible and desired […] [and] should be carried out in specialist centres only; centres with <20 procedures per year have been shown to have poor success rates”.

“The majority of cases of mineralocorticoid excess are due to excess aldosterone production, […] typically associated with hypertension and hypokalemia. *Primary hyperaldosteronism is a disorder of autonomous aldosterone hypersecretion with suppressed renin levels. *Secondary hyperaldosteronism occurs when aldosterone hypersecretion occurs 2° [secondary, US] to elevated circulating renin levels. This is typical of heart failure, cirrhosis, or nephrotic syndrome but can also be due to renal artery stenosis and, occasionally, a very rare renin-producing tumour (reninoma). […] Primary hyperaldosteronism is present in around 10% of hypertensive patients. It is the most prevalent form of secondary hypertension. […] Aldosterone causes renal sodium retention and potassium loss. This results in expansion of body sodium content, leading to suppression of renal renin synthesis. The direct action of aldosterone on the distal nephron causes sodium retention and loss and hydrogen and potassium ions, resulting in a hypokalaemic alkalosis, although serum potassium […] may be normal in up to 50% of cases. Aldosterone has pathophysiological effects on a range of other tissues, causing cardiac fibrosis, vascular endothelial dysfunction, and nephrosclerosis. […] hypertension […] is often resistant to conventional therapy. […] Hypokalaemia is usually asymptomatic. […] Occasionally, the clinical syndrome of hyperaldosteronism is not associated with excess aldosterone. […] These conditions are rare.”

“Bilateral adrenal hyperplasia [make up] 60% [of cases of primary hyperaldosteronism]. […] Conn’s syndrome (aldosterone-producing adrenal adenoma) [make up] 35%. […] The pathophysiology of bilateral adrenal hyperplasia is not understood, and it is possible that it represents an extreme end of the spectrum of low renin essential hypertension. […] Aldosterone-producing carcinoma[s] [are] [r]are and usually associated with excessive secretion of other corticosteroids (cortisol, androgen, oestrogen). […] Indications [for screening include:] *Patients resistant to conventional antihypertensive medication (i.e. not controlled on three agents). *Hypertension associated with hypokalaemia […] *Hypertension developing before age of 40 years. […] Confirmation of autonomous aldosterone production is made by demonstrating failure to suppress aldosterone in face of sodium/volume loading. […] A number of tests have been described that are said to differentiate between the various subtypes of 1° [primary, US] aldosteronism […]. However, none of these are sufficiently specific to influence management decisions”.

“Laparoscopic adrenalectomy is the treatment of choice for aldosterone-secreting adenomas […] and laparoscopic adrenalectomy […] has become the procedure of choice for removal of most adrenal tumours. *Hypertension is cured in about 70%. *If it persists […], it is more amenable to medical treatment. *Overall, 50% become normotensive in 1 month and 70% within 1 year. […] Medical therapy remains an option for patients with bilateral disease and those with a solitary adrenal adenoma who are unlikely to be cured by surgery, who are unfit for operation, or who express a preference for medical management. *The mineralocorticoid receptor antagonist spironolactone […] has been used successfully for many years to treat hypertension and hypokalaemia associated with bilateral adrenal hyperplasia […] Side effects are common – particularly gynaecomastia and impotence in ♂, menstrual irregularities in ♀, and GI effects. […] Eplerenone […] is a mineralocorticoid receptor antagonist without antiandrogen effects and hence greater selectivity and less side effects than spironolactone. *Alternative drugs include the potassium-sparing diuretics amiloride and triamterene.”

“Cushing’s syndrome results from chronic excess cortisol [see also my second post in this series] […] The causes may be classified as ACTH-dependent and ACTH-independent. […] ACTH-independent Cushing’s syndrome […] is due to adrenal tumours (benign and malignant), and is responsible for 10-15% of cases of Cushing’s syndrome. […] Benign adrenocortical adenomas (ACA) are usually encapsulated and <4cm in diameter. They are usually associated with pure glucocorticoid excess. *Adrenocortical carcinomas (ACC) are usually >6cm in diameter, […] and are not infrequently associated with local invasion and metastases at the time of diagnosis. Adrenal carcinomas are characteristically associated with the excess secretion of several hormones; most frequently found is the combination of cortisol and androgen (precursors) […] ACTH-dependent Cushing’s results in bilateral adrenal hyperplasia, thus one has to firmly differentiate between ACTH-dependent and independent causes of Cushing’s before assuming bilateral adrenal hyperplasia as the primary cause of disease. […] It is important to note that, in patients with adrenal carcinoma, there may also be features related to excessive androgen production in ♀ and also a relatively more rapid time course of development of the syndrome. […] Patients with ACTH-independent Cushing’s syndrome do not suppress cortisol […] on high-dose dexamethasone testing and fail to show a rise in cortisol and ACTH following administration of CRH. […] ACTH-independent causes are adrenal in origin, and the mainstay of further investigation is adrenal imaging by CT”.

“Adrenal adenomas, which are successfully treated with surgery, have a good prognosis, and recurrence is unlikely. […] Bilateral adrenalectomy [in the context of bilateral adrenal hyperplasia] is curative. Lifelong glucocorticoid and mineralocorticoid treatment is [however] required. […] The prognosis for adrenal carcinoma is very poor despite surgery. Reports suggest a 5-year survival of 22% and median survival time of 14 months […] Treatment of adrenocortical carcinoma (ACC) should be carried out in a specialist centre, with expert surgeons, oncologists, and endocrinologists with extensive treatment in treating ACC. This improves survival.”

“Adrenal insufficiency [AI, US] is defined by the lack of cortisol, i.e. glucocorticoid deficiency, may be due to destruction of the adrenal cortex (1°, Addison’s disease and congenital adrenal hyperplasia (CAH) […] or due to disordered pituitary and hypothalamic function (2°). […] *Permanent adrenal insufficiency is found in 5 in 10,000 population. *The most frequent cause is hypothalamic-pituitary damage, which is the cause of AI in 60% of affected patients. *The remaining 40% of cases are due to primary failure of the adrenal to synthesize cortisol, almost equal prevalence of Addison’s disease (mostly of autoimmune origin, prevalence 0.9-1.4 in 10,000) and congenital adrenal hyperplasia (0.7-1.0 in 10,000). *2° adrenal insufficiency due to suppression of pituitary-hypothalamic function by exogenously administered, supraphysiological glucocorticoid doses for treatment of, for example, COPD or rheumatoid arthritis, is much more common (50-200 in 10,000 population). However, adrenal function in these patients can recover”.

“[In primary AI] [a]drenal gland destruction or dysfunction occurs due to a disease process which usually involves all three zones of the adrenal cortex, resulting in inadequate glucocorticoid, mineralocorticoid, and adrenal androgen precursor secretion. The manifestations of insufficiency do not usually appear until at least 90% of the gland has been destroyed and are usually gradual in onset […] Acute adrenal insufficiency may occur in the context of acute septicaemia […] Mineralocorticoid deficiency leads to reduced sodium retention and hyponatraemia and hypotension […] Androgen deficiency presents in ♀ with reduced axillary and pubic hair and reduced libido. (Testicular production of androgens is more important in ♂). [In secondary AI] [i]nadequate ACTH results in deficient cortisol production (and ↓ androgens in ♀). […] Mineralocorticoid secretion remains normal […] The onset is usually gradual, with partial ACTH deficiency resulting in reduced response to stress. […] Lack of stimulation of skin MC1R due to ACTH deficiency results in pale skin appearance. […] [In 1° adrenal insufficiency] hyponatraemia is present in 90% and hyperkalaemia in 65%. […] Undetectable serum cortisol is diagnostic […], but the basal cortisol is often in the normal range. A cortisol >550nmol/L precludes the diagnosis. At times of acute stress, an inappropriately low cortisol is very suggestive of the diagnosis.”

“Autoimmune adrenalitis[:] Clinical features[:] *Anorexia and weight loss (>90%). *Tiredness. *Weakness – generalized, no particular muscle groups. […] Dizziness and postural hypotension. *GI symptoms – nausea and vomiting, abdominal pain, diarrhea. *Arthralgia and myalgia. […] *Mediated by humoral and cell-mediated immune mechanisms. Autoimmune insufficiency associated with polyglandular autoimmune syndrome is more common in ♀ (70%). *Adrenal cortex antibodies are present in the majority of patients at diagnosis, and […] they are still found in approximately 70% of patients 10 years later. Up to 20% patients/year with [positive] antibodies develop adrenal insufficiency. […] *Antiadrenal antibodies are found in <2% of patients with other autoimmune endocrine disease (Hashimoto’s thyroiditis, diabetes mellitus, autoimmune hypothyroidism, hypoparathyroidism, pernicious anemia). […] antibodies to other endocrine glands are commonly found in patients with autoimmune adrenal insufficiency […] However, the presence of antibodies does not predict subsequent manifestation of organ-specific autoimmunity. […] Patients with type 1 diabetes mellitus and autoimmune thyroid disease only rarely develop autoimmune adrenal insufficiency. Approximately 60% of patients with Addison’s disease have other autoimmune or endocrine disorders. […] The adrenals are small and atrophic in chronic autoimmune adrenalitis.”

“Autoimmune polyglandular syndrome (APS) type 1[:] *Also known as autoimmune polyendocrinopathy, candidiasis, and ectodermal dystrophy (APECED). […] [C]hildhood onset. *Chronic mucocutaneous candidiasis. *Hypoparathyroidism (90%), 1° adrenal insufficiency (60%). *1° gonadal failure (41%) – usually after Addison’s diagnosis. *1° hypothyroidism. *Rarely hypopituitarism, diabetes insipidus, type 1 diabetes mellitus. […] APS type 2[:] *Adult onset. *Adrenal insufficiency (100%). 1° autoimmune thyroid disease (70%) […] Type 1 diabetes mellitus (5-20%) – often before Addison’s diagnosis. *1° gonadal failure in affected women (5-20%). […] Schmidt’s syndrome: *Addison’s disease, and *Autoimmune hypothyroidism. *Carpenter syndrome: *Addison’s disease, and *Autoimmune hypothyroidism, and/or *Type 1 diabetes mellitus.”

“An adrenal incidentaloma is an adrenal mass that is discovered incidentally upon imaging […] carried out for reasons other than a suspected adrenal pathology.  […] *Autopsy studies suggest incidence prevalence of adrenal masses of 1-6% in the general population. *Imagining studies suggest that adrenal masses are present 2-3% in the general population. Incidence increases with ageing, and 8-10% of 70-year olds harbour an adrenal mass. […] It is important to determine whether the incidentally discovered adrenal mass is: *Malignant. *Functioning and associated with excess hormonal secretion.”

A few diabetes papers of interest

i. Chronic Fatigue in Type 1 Diabetes: Highly Prevalent but Not Explained by Hyperglycemia or Glucose Variability.

“Fatigue is a classical symptom of hyperglycemia, but the relationship between chronic fatigue and diabetes has not been systematically studied. […] glucose control [in diabetics] is often suboptimal with persistent episodes of hyperglycemia that may result in sustained fatigue. Fatigue may also sustain in diabetic patients because it is associated with the presence of a chronic disease, as has been demonstrated in patients with rheumatoid arthritis and various neuromuscular disorders (2,3).

It is important to distinguish between acute and chronic fatigue, because chronic fatigue, defined as severe fatigue that persists for at least 6 months, leads to substantial impairments in patients’ daily functioning (4,5). In contrast, acute fatigue can largely vary during the day and generally does not cause functional impairments.

Literature provides limited evidence for higher levels of fatigue in diabetic patients (6,7), but its chronicity, impact, and determinants are unknown. In various chronic diseases, it has been proven useful to distinguish between precipitating and perpetuating factors of chronic fatigue (3,8). Illness-related factors trigger acute fatigue, while other factors, often cognitions and behaviors, cause fatigue to persist. Sleep disturbances, low self-efficacy concerning fatigue, reduced physical activity, and a strong focus on fatigue are examples of these fatigue-perpetuating factors (8–10). An episode of hyperglycemia or hypoglycemia could trigger acute fatigue for diabetic patients (11,12). However, variations in blood glucose levels might also contribute to chronic fatigue, because these variations continuously occur.

The current study had two aims. First, we investigated the prevalence and impact of chronic fatigue in a large sample of type 1 diabetic (T1DM) patients and compared the results to a group of age- and sex-matched population-based controls. Secondly, we searched for potential determinants of chronic fatigue in T1DM.”

“A significantly higher percentage of T1DM patients were chronically fatigued (40%; 95% CI 34–47%) than matched controls (7%; 95% CI 3–10%). Mean fatigue severity was also significantly higher in T1DM patients (31 ± 14) compared with matched controls (17 ± 9; P < 0.001). T1DM patients with a comorbidity_mr [a comorbidity affecting patients’ daily functioning, based on medical records – US] or clinically relevant depressive symptoms [based on scores on the Beck Depression Inventory for Primary Care – US] were significantly more often chronically fatigued than patients without a comorbidity_mr (55 vs. 36%; P = 0.014) or without clinically relevant depressive symptoms (88 vs. 31%; P < 0.001). Patients who reported neuropathy, nephropathy, or cardiovascular disease as complications of diabetes were more often chronically fatigued […] Chronically fatigued T1DM patients were significantly more impaired compared with nonchronically fatigued T1DM patients on all aspects of daily functioning […]. Fatigue was the most troublesome symptom of the 34 assessed diabetes-related symptoms. The five most troublesome symptoms were overall sense of fatigue, lack of energy, increasing fatigue in the course of the day, fatigue in the morning when getting up, and sleepiness or drowsiness”.

“This study establishes that chronic fatigue is highly prevalent and clinically relevant in T1DM patients. While current blood glucose level was only weakly associated with chronic fatigue, cognitive behavioral factors were by far the strongest potential determinants.”

“Another study found that type 2 diabetic, but not T1DM, patients had higher levels of fatigue compared with healthy controls (7). This apparent discrepancy may be explained by the relatively small sample size of this latter study, potential selection bias (patients were not randomly selected), and the use of a different fatigue questionnaire.”

“Not only was chronic fatigue highly prevalent, fatigue also had a large impact on T1DM patients. Chronically fatigued T1DM patients had more functional impairments than nonchronically fatigued patients, and T1DM patients considered fatigue as the most burdensome diabetes-related symptom.

Contrary to what was expected, there was at best a weak relationship between blood glucose level and chronic fatigue. Chronically fatigued T1DM patients spent slightly less time in hypoglycemia, but average glucose levels, glucose variability, hyperglycemia, or HbA_1c were not related to chronic fatigue. In type 2 diabetes mellitus also, no relationship was found between fatigue and HbA_1c (7).”

“Regarding demographic characteristics, current health status, diabetes-related factors, and fatigue-related cognitions and behaviors as potential determinants of chronic fatigue, we found that sleeping problems, physical activity, self-efficacy concerning fatigue, age, depression, and pain were significantly associated with chronic fatigue in T1DM. Although depression was strongly related, it could not completely explain the presence of chronic fatigue (38), as 31% was chronically fatigued without having clinically relevant depressive symptoms.”

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Some comments may be worth adding here. It’s important to note to people who may not be aware of this that although chronic fatigue is a weird entity that’s hard to get a handle on (and, to be frank, is somewhat controversial), specific organic causes have been identified that greatly increases the risk. Many survivors of cancer experience chronic fatigue (see e.g. this paper, or wikipedia), and chronic fatigue is also not uncommon in a kidney failure setting (“The silence of renal disease creeps up on us (doctors and patients). Do not dismiss odd chronic symptoms such as fatigue or ‘not being quite with it’ without considering checking renal function” (Oxford Handbook of Clinical Medicine, 9th edition. My italics – US)). As observed above, linkage with RA and some neuromuscular disorders has also been observed. The brief discussion of related topics in Houghton & Grey made it clear to me that some people with chronic fatigue are almost certainly suffering from an organic illness which has not been diagnosed or treated. Here’s a relevant quote from that book’s coverage: “it is unusual to find a definite organic cause for fatigue. However, consider anaemia, thyroid dysfunction, Addison’s disease and hypopituitarism.” It’s sort of neat, if you think about the potential diabetes-fatigue link investigated by the guys above, that some of these diseases are likely to be relevant, as type 1 diabetics are more likely to develop them (anemia is not linked to diabetes, as far as I know, and I believe the relationship between autoimmune hypophysitis – which is a cause of hypopituitarism – and type 1 diabetes is at best unclear, but the others are definitely involved) due to their development being caused by some of the same genetic mutations which cause type 1 diabetes; the combinations of some of these diseases even have fancy names of their own, like ‘Type I Polyglandular Autoimmune Syndrome’ and ‘Schmidt Syndrome’ (if you’re interested here are a couple of medscape links). It’s noteworthy that although most of these diseases are uncommon in the general population, their incidence/prevalence is likely to be greatly increased in type 1 diabetics due to the common genetic pathways at play (variants regulating T-cell function seem to be important, but there’s no need to go into these details here). Sperling et al. note in their book that: “Hypothyroid or hyperthyroid AITD [autoimmune thyroid disease] has been observed in 10–24% of patients with type 1 diabetes”. In one series including 151 patients with APS [/PAS]-2, when they looked at disease combinations they found that: “Of combinations of the component diseases, [type 1] diabetes with thyroid disease was the most common, occurring in 33%. The second, diabetes with adrenal insufficiency, made up 15%” (same source).

It seems from estimates like these likely that a not unsubstantial proportion of type 1 diabetics over time go on to develop other health problems that might if unaddressed/undiagnosed cause fatigue, and this may in my opinion be a potentially much more important cause than direct metabolic effects such as hyperglycemia, or chronic inflammation. If this is the case you’d however expect to see a substantial sex difference, as the autoimmune syndromes are in general much more likely to hit females than males. I’m not completely sure how to interpret a few of the results reported, but to me it doesn’t look like the sex differences in this study are anywhere near ‘large enough’ to support such an explanatory model, though. Another big problem is also that fatigue seems to be more common in young patients, which is weird; most long-term complications display significant (positive) duration dependence, and when diabetes is a component of an autoimmune syndrome diabetes tend to develop first, with other diseases hitting later, usually in middle age. Duration and age are strongly correlated, and a negative duration dependence in a diabetes complication setting is a surprising and unusual finding that needs to be explained, badly; it’s unexpected and may in my opinion be the sign of a poor disease model. It’d make more sense for disease-related fatigue to present late, rather than early, I don’t really know what to make of that negative age gradient. ‘More studies needed’ (preferably by people familiar with those autoimmune syndromes..), etc…

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ii. Risk for End-Stage Renal Disease Over 25 Years in the Population-Based WESDR Cohort.

“It is well known that diabetic nephropathy is the leading cause of end-stage renal disease (ESRD) in many regions, including the U.S. (1). Type 1 diabetes accounts for >45,000 cases of ESRD per year (2), and the incidence may be higher than in people with type 2 diabetes (3). Despite this, there are few population-based data available regarding the prevalence and incidence of ESRD in people with type 1 diabetes in the U.S. (4). A declining incidence of ESRD has been suggested by findings of lower incidence with increasing calendar year of diagnosis and in comparison with older reports in some studies in Europe and the U.S. (5–8). This is consistent with better diabetes management tools becoming available and increased renoprotective efforts, including the greater use of ACE inhibitors and angiotensin type II receptor blockers, over the past two to three decades (9). Conversely, no reduction in the incidence of ESRD across enrollment cohorts was found in a recent clinic-based study (9). Further, an increase in ESRD has been suggested for older but not younger people (9). Recent improvements in diabetes care have been suggested to delay rather than prevent the development of renal disease in people with type 1 diabetes (4).

A decrease in the prevalence of proliferative retinopathy by increasing calendar year of type 1 diabetes diagnosis was previously reported in the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) cohort (10); therefore, we sought to determine if a similar pattern of decline in ESRD would be evident over 25 years of follow-up. Further, we investigated factors that may mediate a possible decline in ESRD as well as other factors associated with incident ESRD over time.”

“At baseline, 99% of WESDR cohort members were white and 51% were male. Individuals were 3–79 years of age (mean 29) with diabetes duration of 0–59 years (mean 15), diagnosed between 1922 and 1980. Four percent of individuals used three or more daily insulin injections and none used an insulin pump. Mean HbA_1c was 10.1% (87 mmol/mol). Only 16% were using an antihypertensive medication, none was using an ACE inhibitor, and 3% reported a history of renal transplant or dialysis (ESRD). At 25 years, 514 individuals participated (52% of original cohort at baseline, n = 996) and 367 were deceased (37% of baseline). Mean HbA_1c was much lower than at baseline (7.5%, 58 mmol/mol), the decline likely due to the improvements in diabetes care, with 80% of participants using intensive insulin management (three or more daily insulin injections or insulin pump). The decline in HbA_1c was steady, becoming slightly steeper following the results of the DCCT (25). Overall, at the 25-year follow-up, 47% had proliferative retinopathy, 53% used aspirin daily, and 54% reported taking antihypertensive medications, with the majority (87%) using an ACE inhibitor. Thirteen percent reported a history of ESRD.”

“Prevalence of ESRD was negligible until 15 years of diabetes duration and then steadily increased with 5, 8, 10, 13, and 14% reporting ESRD by 15–19, 20–24, 25–29, 30–34, and 35+ years of diabetes duration, respectively. […] After 15 years of diagnosis, prevalence of ESRD increased with duration in people diagnosed from 1960 to 1980, with the lowest increase in people with the most recent diagnosis. People diagnosed from 1922 to 1959 had consistent rather than increasing levels of ESRD with duration of 20+ years. If not for their greater mortality (at the 25-year follow-up, 48% of the deceased had been diagnosed prior to 1960), an increase with duration may have also been observed.

From baseline, the unadjusted cumulative 25-year incidence of ESRD was 17.9% (95% CI 14.3–21.5) in males, 10.3% (7.4–13.2) in females, and 14.2% (11.9–16.5) overall. For those diagnosed in 1970–1980, the cumulative incidence at 14, 20, and 25 years of follow-up (or ∼15–25, 20–30, and 25–35 years diabetes duration) was 5.2, 7.9, and 9.3%, respectively. At 14, 20, and 25 years of follow-up (or 35, 40, and 45 up to 65+ years diabetes duration), the cumulative incidence in those diagnosed during 1922–1969 was 13.6, 16.3, and 18.8%, respectively, consistent with the greater prevalence observed for these diagnosis periods at longer duration of diabetes.”

“The unadjusted hazard of ESRD was reduced by 70% among those diagnosed in 1970–1980 as compared with those in 1922–1969 (HR 0.29 [95% CI 0.19–0.44]). Duration (by 10%) and HbA_1c (by an additional 10%) partially mediated this association […] Blood pressure and antihypertensive medication use each further attenuated the association. When fully adjusted for these and [other risk factors included in the model], period of diagnosis was no longer significant (HR 0.89 [0.55–1.45]). Sensitivity analyses for the hazard of incident ESRD or death due to renal disease showed similar findings […] The most parsimonious model included diabetes duration, HbA_1c, age, sex, systolic and diastolic blood pressure, and history of antihypertensive medication […]. A 32% increased risk for incident ESRD was found per increasing year of diabetes duration at 0–15 years (HR 1.32 per year [95% CI 1.16–1.51]). The hazard plateaued (1.01 per year [0.98–1.05]) after 15 years of duration of diabetes. Hazard of ESRD increased with increasing HbA_1c (1.28 per 1% or 10.9 mmol/mol increase [1.14–1.45]) and blood pressure (1.51 per 10 mmHg increase in systolic pressure [1.35–1.68]; 1.12 per 5 mmHg increase in diastolic pressure [1.01–1.23]). Use of antihypertensive medications increased the hazard of incident ESRD nearly fivefold [this finding is almost certainly due to confounding by indication, as also noted by the authors later on in the paper – US], and males had approximately two times the risk as compared with females. […] Having proliferative retinopathy was strongly associated with increased risk (HR 5.91 [3.00–11.6]) and attenuated the association between sex and ESRD.”

“The current investigation […] sought to provide much-needed information on the prevalence and incidence of ESRD and associated risk specific to people with type 1 diabetes. Consistent with a few previous studies (5,7,8), we observed decreased prevalence and incidence of ESRD among individuals with type 1 diabetes diagnosed in the 1970s compared with prior to 1970. The Epidemiology of Diabetes Complications (EDC) Study, another large cohort of people with type 1 diabetes followed over a long period of time, reported cumulative incidence rates of 2–6% for those diagnosed after 1970 and with similar duration (7), comparable to our findings. Slightly higher cumulative incidence (7–13%) reported from older studies at slightly lower duration also supports a decrease in incidence of ESRD (28–30). Cumulative incidences through 30 years in European cohorts were even lower (3.3% in Sweden [6] and 7.8% in Finland [5]), compared with the 9.3% noted for those diagnosed during 1970–1980 in the WESDR cohort. The lower incidence could be associated with nationally organized care, especially in Sweden where a nationwide intensive diabetes management treatment program was implemented at least a decade earlier than recommendations for intensive care followed from the results of the DCCT in the U.S.”

“We noted an increased risk of incident ESRD in the first 15 years of diabetes not evident at longer durations. This pattern also demonstrated by others could be due to a greater earlier risk among people most genetically susceptible, as only a subset of individuals with type 1 diabetes will develop renal disease (27,28). The risk plateau associated with greater durations of diabetes and lower risk associated with increasing age may also reflect more death at longer durations and older ages. […] Because age and duration are highly correlated, we observed a positive association between age and ESRD only in univariate analyses, without adjustment for duration. The lack of adjustment for diabetes duration may have, in part, explained the increasing incidence of ESRD shown with age for some people in a recent investigation (9). Adjustment for both age and duration was found appropriate after testing for collinearity in the current analysis.”

“In conclusion, this U.S. population-based report showed a lower prevalence and incidence of ESRD among those more recently diagnosed, explained by improvements in glycemic and blood pressure control over the last several decades. Even lower rates may be expected for those diagnosed during the current era of diabetes care. Intensive diabetes management, especially for glycemic control, remains important even in long-standing diabetes as potentially delaying the development of ESRD.“

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iii. Earlier Onset of Complications in Youth With Type 2 Diabetes.

The prevalence of type 2 diabetes in youth is increasing worldwide, coinciding with the rising obesity epidemic (1,2). […] Diabetes is associated with both microvascular and macrovascular complications. The evolution of these complications has been well described in type 1 diabetes (6) and in adult type 2 diabetes (7), wherein significant complications typically manifest 15–20 years after diagnosis (8). Because type 2 diabetes is a relatively new disease in children (first described in the 1980s), long-term outcome data on complications are scant, and risk factors for the development of complications are incompletely understood. The available literature suggests that development of complications in youth with type 2 diabetes may be more rapid than in adults, thus afflicting individuals at the height of their individual and social productivity (9). […] A small but notable proportion of type 2 diabetes is associated with a polymorphism of hepatic nuclear factor (HNF)-1α, a transcription factor expressed in many tissues […] It is not yet known what effect the HNF-1α polymorphism has on the risk of complications associated with diabetes.”

“The main objective of the current study was to describe the time course and risk factors for microvascular complications (nephropathy, retinopathy, and neuropathy) and macrovascular complications (cardiac, cerebrovascular, and peripheral vascular diseases) in a large cohort of youth [diagnosed with type 2 diabetes] who have been carefully followed for >20 years and to compare this evolution with that of youth with type 1 diabetes. We also compared vascular complications in the youth with type 2 diabetes with nondiabetic control youth. Finally, we addressed the impact of HNF-1α G319S on the evolution of complications in young patients with type 2 diabetes.”

“All prevalent cases of type 2 diabetes and type 1 diabetes (control group 1) seen between January 1986 and March 2007 in the DER-CA for youth aged 1–18 years were included. […] The final type 2 diabetes cohort included 342 youth, and the type 1 diabetes control group included 1,011. The no diabetes control cohort comprised 1,710 youth matched to the type 2 diabetes cohort from the repository […] Compared with the youth with type 1 diabetes, the youth with type 2 diabetes were, on average, older at the time of diagnosis and more likely to be female. They were more likely to have a higher BMIz, live in a rural area, have a low SES, and have albuminuria at diagnosis. […] one-half of the type 2 diabetes group was either a heterozygote (GS) or a homozygote (SS) for the HNF-1α polymorphism […] At the time of the last available follow-up in the DER-CA, the youth with diabetes were, on average, between 15 and 16 years of age. […] The median follow-up times in the repository were 4.4 (range 0–27.4) years for youth with type 2 diabetes, 6.7 ( 0–28.2) years for youth with type 1 diabetes, and 6.0 (0–29.9) years for nondiabetic control youth.”

“After controlling for low SES, sex, and BMIz, the risk associated with type 2 versus type 1 diabetes of any complication was an HR of 1.47 (1.02–2.12, P = 0.04). […] In the univariate analysis, youth with type 2 diabetes were at significantly higher risk of developing any vascular (HR 6.15 [4.26–8.87], P < 0.0001), microvascular (6.26 [4.32–9.10], P < 0.0001), or macrovascular (4.44 [1.71–11.52], P < 0.0001) disease compared with control youth without diabetes. In addition, the youth with type 2 diabetes had an increased risk of opthalmologic (19.49 [9.75–39.00], P < 0.0001), renal (16.13 [7.66–33.99], P < 0.0001), and neurologic (2.93 [1.79–4.80], P ≤ 0.001) disease. There were few cardiovascular, cerebrovascular, and peripheral vascular disease events in all groups (five or fewer events per group). Despite this, there was still a statistically significant higher risk of peripheral vascular disease in the type 2 diabetes group (6.25 [1.68–23.28], P = 0.006).”

“Differences in renal and neurologic complications between the two diabetes groups began to occur before 5 years postdiagnosis, whereas differences in ophthalmologic complications began 10 years postdiagnosis. […] Both cardiovascular and cerebrovascular complications were rare in both groups, but peripheral vascular complications began to occur 15 years after diagnosis in the type 2 diabetes group […] The presence of HNF-1α G319S polymorphism in youth with type 2 diabetes was found to be protective of complications. […] Overall, major complications were rare in the type 1 diabetes group, but they occurred in 1.1% of the type 2 diabetes cohort at 10 years, in 26.0% at 15 years, and in 47.9% at 20 years after diagnosis (P < 0.001) […] youth with type 2 diabetes have a higher risk of any complication than youth with type 1 diabetes and nondiabetic control youth. […] The time to both renal and neurologic complications was significantly shorter in youth with type 2 diabetes than in control youth, whereas differences were not significant with respect to opthalmologic and cardiovascular complications between cohorts. […] The current study is consistent with the literature, which has shown high rates of cardiovascular risk factors in youth with type 2 diabetes. However, despite the high prevalence of risk, this study reports low rates of clinical events. Because the median follow-up time was between 5 and 8 years, it is possible that a longer follow-up period would be required to correctly evaluate macrovascular outcomes in young adults. Also possible is that diagnoses of mild disease are not being made because of a low index of suspicion in 20- and 30-year-old patients.”

“In conclusion, youth with type 2 diabetes have an increased risk of complications early in the course of their disease. Microvascular complications and cardiovascular risk factors are highly prevalent, whereas macrovascular complications are rare in young adulthood. HbA_1c is an important modifiable risk factor; thus, optimizing glycemic control should remain an important goal of therapy.”

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iv. HbA_1c and Coronary Heart Disease Risk Among Diabetic Patients.

“We prospectively investigated the association of HbA_1c at baseline and during follow-up with CHD risk among 17,510 African American and 12,592 white patients with type 2 diabetes. […] During a mean follow-up of 6.0 years, 7,258 incident CHD cases were identified. The multivariable-adjusted hazard ratios of CHD associated with different levels of HbA_1c at baseline (<6.0 [reference group], 6.0–6.9, 7.0–7.9, 8.0–8.9, 9.0–9.9, 10.0–10.9, and ≥11.0%) were 1.00, 1.07 (95% CI 0.97–1.18), 1.16 (1.04–1.31), 1.15 (1.01–1.32), 1.26 (1.09–1.45), 1.27 (1.09–1.48), and 1.24 (1.10–1.40) (P trend = 0.002) for African Americans and 1.00, 1.04 (0.94–1.14), 1.15 (1.03–1.28), 1.29 (1.13–1.46), 1.41 (1.22–1.62), 1.34 (1.14–1.57), and 1.44 (1.26–1.65) (P trend <0.001) for white patients, respectively. The graded association of HbA_1c during follow-up with CHD risk was observed among both African American and white diabetic patients (all P trend <0.001). Each one percentage increase of HbA_1c was associated with a greater increase in CHD risk in white versus African American diabetic patients. When stratified by sex, age, smoking status, use of glucose-lowering agents, and income, this graded association of HbA_1c with CHD was still present. […] The current study in a low-income population suggests a graded positive association between HbA_1c at baseline and during follow-up with the risk of CHD among both African American and white diabetic patients with low socioeconomic status.”

A few more observations from the conclusions:

“Diabetic patients experience high mortality from cardiovascular causes (2). Observational studies have confirmed the continuous and positive association between glycemic control and the risk of cardiovascular disease among diabetic patients (4,5). But the findings from RCTs are sometimes uncertain. Three large RCTs (7–9) designed primarily to determine whether targeting different glucose levels can reduce the risk of cardiovascular events in patients with type 2 diabetes failed to confirm the benefit. Several reasons for the inconsistency of these studies can be considered. First, small sample sizes, short follow-up duration, and few CHD cases in some RCTs may limit the statistical power. Second, most epidemiological studies only assess a single baseline measurement of HbA_1c with CHD risk, which may produce potential bias. The recent analysis of 10 years of posttrial follow-up of the UKPDS showed continued reductions for myocardial infarction and death from all causes despite an early loss of glycemic differences (10). The scientific evidence from RCTs was not sufficient to generate strong recommendations for clinical practice. Thus, consensus groups (AHA, ACC, and ADA) have provided a conservative endorsement (class IIb recommendation, level of evidence A) for the cardiovascular benefits of glycemic control (11). In the absence of conclusive evidence from RCTs, observational epidemiological studies might provide useful information to clarify the relationship between glycemia and CHD risk. In the current study with 30,102 participants with diabetes and 7,258 incident CHD cases during a mean follow-up of 6.0 years, we found a graded positive association by various HbA_1c intervals of clinical relevance or by using HbA_1c as a continuous variable at baseline and during follow-up with CHD risk among both African American and white diabetic patients. Each one percentage increase in baseline and follow-up HbA_1c was associated with a 2 and 5% increased risk of CHD in African American and 6 and 11% in white diabetic patients. Each one percentage increase of HbA_1c was associated with a greater increase in CHD risk in white versus African American diabetic patients.”

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v. Blood Viscosity in Subjects With Normoglycemia and Prediabetes.

“Blood viscosity (BV) is the force that counteracts the free sliding of the blood layers within the circulation and depends on the internal cohesion between the molecules and the cells. Abnormally high BV can have several negative effects: the heart is overloaded to pump blood in the vascular bed, and the blood itself, more viscous, can damage the vessel wall. Furthermore, according to Poiseuille’s law (1), BV is inversely related to flow and might therefore reduce the delivery of insulin and glucose to peripheral tissues, leading to insulin resistance or diabetes (2–5).

It is generally accepted that BV is increased in diabetic patients (6–8). Although the reasons for this alteration are still under investigation, it is believed that the increase in osmolarity causes increased capillary permeability and, consequently, increased hematocrit and viscosity (9). It has also been suggested that the osmotic diuresis, consequence of hyperglycemia, could contribute to reduce plasma volume and increase hematocrit (10).

Cross-sectional studies have also supported a link between BV, hematocrit, and insulin resistance (11–17). Recently, a large prospective study has demonstrated that BV and hematocrit are risk factors for type 2 diabetes. Subjects in the highest quartile of BV were >60% more likely to develop diabetes than their counterparts in the lowest quartile (18). This finding confirms previous observations obtained in smaller or selected populations, in which the association between hemoglobin or hematocrit and occurrence of type 2 diabetes was investigated (19–22).

These observations suggest that the elevation in BV may be very early, well before the onset of diabetes, but definite data in subjects with normal glucose or prediabetes are missing. In the current study, we evaluated the relationship between BV and blood glucose in subjects with normal glucose or prediabetes in order to verify whether alterations in viscosity are appreciable in these subjects and at which blood glucose concentration they appear.”

“According to blood glucose levels, participants were divided into three groups: group A, blood glucose <90 mg/dL; group B, blood glucose between 90 and 99 mg/dL; and group C, blood glucose between 100 and 125 mg/dL. […] Hematocrit (P < 0.05) and BV (P between 0.01 and 0.001) were significantly higher in subjects with prediabetes and in those with blood glucose ranging from 90 to 99 mg/dL compared with subjects with blood glucose <90 mg/dL. […] The current study shows, for the first time, a direct relationship between BV and blood glucose in nondiabetic subjects. It also suggests that, even within glucose values ​​considered completely normal, individuals with higher blood glucose levels have increases in BV comparable with those observed in subjects with prediabetes. […] Overall, changes in viscosity in diabetic patients are accepted as common and as a result of the disease. However, the relationship between blood glucose, diabetes, and viscosity may be much more complex. […] the main finding of the study is that BV significantly increases already at high-normal blood glucose levels, independently of other common determinants of hemorheology. Intervention studies are needed to verify whether changes in BV can influence the development of type 2 diabetes.”

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vi. Higher Relative Risk for Multiple Sclerosis in a Pediatric and Adolescent Diabetic Population: Analysis From DPV Database.

“Type 1 diabetes and multiple sclerosis (MS) are organ-specific inflammatory diseases, which result from an autoimmune attack against either pancreatic β-cells or the central nervous system; a combined appearance has been described repeatedly (1–3). For children and adolescents below the age of 21 years, the prevalence of type 1 diabetes in Germany and Austria is ∼19.4 cases per 100,000 population, and for MS it is 7–10 per 100,000 population (4–6). A Danish cohort study revealed a three times higher risk for the development of MS in patients with type 1 diabetes (7). Further, an Italian study conducted in Sardinia showed a five times higher risk for the development of type 1 diabetes in MS patients (8,9). An American study on female adults in whom diabetes developed before the age of 21 years yielded an up to 20 times higher risk for the development of MS (10).

These findings support the hypothesis of clustering between type 1 diabetes and MS. The pathogenesis behind this association is still unclear, but T-cell cross-reactivity was discussed as well as shared disease associations due to the HLA-DRB1-DQB1 gene loci […] The aim of this study was to evaluate the prevalence of MS in a diabetic population and to look for possible factors related to the co-occurrence of MS in children and adolescents with type 1 diabetes using a large multicenter survey from the Diabetes Patienten Verlaufsdokumentation (DPV) database.”

“We used a large database of pediatric and adolescent type 1 diabetic patients to analyze the RR of MS co-occurrence. The DPV database includes ∼98% of the pediatric diabetic population in Germany and Austria below the age of 21 years. In children and adolescents, the RR for MS in type 1 diabetes was estimated to be three to almost five times higher in comparison with the healthy population.”

A few diabetes papers of interest

i. Neurocognitive Functioning in Children and Adolescents at the Time of Type 1 Diabetes Diagnosis: Associations With Glycemic Control 1 Year After Diagnosis.

“Children and youth with type 1 diabetes are at risk for developing neurocognitive dysfunction, especially in the areas of psychomotor speed, attention/executive functioning, and visuomotor integration (1,2). Most research suggests that deficits emerge over time, perhaps in response to the cumulative effect of glycemic extremes (3–6). However, the idea that cognitive changes emerge gradually has been challenged (7–9). Ryan (9) argued that if diabetes has a cumulative effect on cognition, cognitive test performance should be positively correlated with illness duration. Yet he found comparable deficits in psychomotor speed (the most commonly noted area of deficit) in adolescents and young adults with illness duration ranging from 6 to 25 years. He therefore proposed a diathesis model in which cognitive declines in diabetes are especially likely to occur in more vulnerable patients, at crucial periods, in response to illness-related events (e.g., severe hyperglycemia) known to have an impact on the central nervous system (CNS) (8). This model accounts for the finding that cognitive deficits are more likely in children with early-onset diabetes, and for the accelerated cognitive aging seen in diabetic individuals later in life (7). A third hypothesized crucial period is the time leading up to diabetes diagnosis, during which severe fluctuations in blood glucose and persistent hyperglycemia often occur. Concurrent changes in blood-brain barrier permeability could result in a flood of glucose into the brain, with neurotoxic effects (9).”

“In the current study, we report neuropsychological test findings for children and adolescents tested within 3 days of diabetes diagnosis. The purpose of the study was to determine whether neurocognitive impairments are detectable at diagnosis, as predicted by the diathesis hypothesis. We hypothesized that performance on tests of psychomotor speed, visuomotor integration, and attention/executive functioning would be significantly below normative expectations, and that differences would be greater in children with earlier disease onset. We also predicted that diabetic ketoacidosis (DKA), a primary cause of diabetes-related neurological morbidity (12) and a likely proxy for severe peri-onset hyperglycemia, would be associated with poorer performance.”

“Charts were reviewed for 147 children/adolescents aged 5–18 years (mean = 10.4 ± 3.2 years) who completed a short neuropsychological screening during their inpatient hospitalization for new-onset type 1 diabetes, as part of a pilot clinical program intended to identify patients in need of further neuropsychological evaluation. Participants were patients at a large urban children’s hospital in the southwestern U.S. […] Compared with normative expectations, children/youth with type 1 diabetes performed significantly worse on GPD, GPN, VMI, and FAS (P < 0.0001 in all cases), with large decrements evident on all four measures (Fig. 1). A small but significant effect was also evident in DSB (P = 0.022). High incidence of impairment was evident on all neuropsychological tasks completed by older participants (aged 9–18 years) except DSF/DSB (Fig. 2).”

“Deficits in neurocognitive functioning were evident in children and adolescents within days of type 1 diabetes diagnosis. Participants performed >1 SD below normative expectations in bilateral psychomotor speed (GP) and 0.7–0.8 SDs below expected performance in visuomotor integration (VMI) and phonemic fluency (FAS). Incidence of impairment was much higher than normative expectations on all tasks except DSF/DSB. For example, >20% of youth were impaired in dominant hand fine-motor control, and >30% were impaired with their nondominant hand. These findings provide provisional support for Ryan’s hypothesis (7–9) that the peri-onset period may be a time of significant cognitive vulnerability.

Importantly, deficits were not evident on all measures. Performance on measures of attention/executive functioning (TMT-A, TMT-B, DSF, and DSB) was largely consistent with normative expectations, as was reading ability (WRAT-4), suggesting that the below-average performance in other areas was not likely due to malaise or fatigue. Depressive symptoms at diagnosis were associated with performance on TMT-B and FAS, but not on other measures. Thus, it seems unlikely that depressive symptoms accounted for the observed motor slowing.

Instead, the findings suggest that the visual-motor system may be especially vulnerable to early effects of type 1 diabetes. This interpretation is especially compelling given that psychomotor impairment is the most consistently reported long-term cognitive effect of type 1 diabetes. The sensitivity of the visual-motor system at diabetes diagnosis is consistent with a growing body of neuroimaging research implicating posterior white matter tracts and associated gray matter regions (particularly cuneus/precuneus) as areas of vulnerability in type 1 diabetes (30–32). These regions form part of the neural system responsible for integrating visual inputs with motor outputs, and in adults with type 1 diabetes, structural pathology in these regions is directly correlated to performance on GP [grooved pegboard test] (30,31). Arbelaez et al. (33) noted that these brain areas form part of the “default network” (34), a system engaged during internally focused cognition that has high resting glucose metabolism and may be especially vulnerable to glucose variability.”

“It should be noted that previous studies (e.g., Northam et al. [3]) have not found evidence of neurocognitive dysfunction around the time of diabetes diagnosis. This may be due to study differences in measures, outcomes, and/or time frame. We know of no other studies that completed neuropsychological testing within days of diagnosis. Given our time frame, it is possible that our findings reflect transient effects rather than more permanent changes in the CNS. Contrary to predictions, we found no association between DKA at diagnosis and neurocognitive performance […] However, even transient effects could be considered potential indicators of CNS vulnerability. Neurophysiological changes at the time of diagnosis have been shown to persist under certain circumstances or for some patients. […] [Some] findings suggest that some individuals may be particularly susceptible to the effects of glycemic extremes on neurocognitive function, consistent with a large body of research in developmental neuroscience indicating individual differences in neurobiological vulnerability to adverse events. Thus, although it is possible that the neurocognitive impairments observed in our study might resolve with euglycemia, deficits at diagnosis could still be considered a potential marker of CNS vulnerability to metabolic perturbations (both acute and chronic).”

“In summary, this study provides the first demonstration that type 1 diabetes–associated neurocognitive impairment can be detected at the time of diagnosis, supporting the possibility that deficits arise secondary to peri-onset effects. Whether these effects are transient markers of vulnerability or represent more persistent changes in CNS awaits further study.”

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ii. Association Between Impaired Cardiovascular Autonomic Function and Hypoglycemia in Patients With Type 1 Diabetes.

“Cardiovascular autonomic neuropathy (CAN) is a chronic complication of diabetes and an independent predictor of cardiovascular disease (CVD) morbidity and mortality (1–3). The mechanisms of CAN are complex and not fully understood. It can be assessed by simple cardiovascular reflex tests (CARTs) and heart rate variability (HRV) studies that were shown to be sensitive, noninvasive, and reproducible (3,4).”

“HbA_1c fails to capture information on the daily fluctuations in blood glucose levels, termed glycemic variability (GV). Recent observations have fostered the notion that GV, independent of HbA_1c, may confer an additional risk for the development of micro- and macrovascular diabetes complications (8,9). […] the relationship between GV and chronic complications, specifically CAN, in patients with type 1 diabetes has not been systematically studied. In addition, limited data exist on the relationship between hypoglycemic components of the GV and measures of CAN among subjects with type 1 diabetes (11,12). Therefore, we have designed a prospective study to evaluate the impact and the possible sustained effects of GV on measures of cardiac autonomic function and other cardiovascular complications among subjects with type 1 diabetes […] In the present communication, we report cross-sectional analyses at baseline between indices of hypoglycemic stress on measures of cardiac autonomic function.”

“The following measures of CAN were predefined as outcomes of interests and analyzed: expiration-to-inspiration ratio (E:I), Valsalva ratio, 30:15 ratios, low-frequency (LF) power (0.04 to 0.15 Hz), high-frequency (HF) power (0.15 to 0.4 Hz), and LF/HF at rest and during CARTs. […] We found that LBGI [low blood glucose index] and AUC [area under the curve] hypoglycemia were associated with reduced LF and HF power of HRV [heart rate variability], suggesting an impaired autonomic function, which was independent of glucose control as assessed by the HbA_1c.”

“Our findings are in concordance with a recent report demonstrating attenuation of the baroreflex sensitivity and of the sympathetic response to various cardiovascular stressors after antecedent hypoglycemia among healthy subjects who were exposed to acute hypoglycemic stress (18). Similar associations […] were also reported in a small study of subjects with type 2 diabetes (19). […] higher GV and hypoglycemic stress may have an acute effect on modulating autonomic control with inducing a sympathetic/vagal imbalance and a blunting of the cardiac vagal control (18). The impairment in the normal counter-regulatory autonomic responses induced by hypoglycemia on the cardiovascular system could be important in healthy individuals but may be particularly detrimental in individuals with diabetes who have hitherto compromised cardiovascular function and/or subclinical CAN. In these individuals, hypoglycemia may also induce QT interval prolongation, increase plasma catecholamine levels, and lower serum potassium (19,20). In concert, these changes may lower the threshold for serious arrhythmia (19,20) and could result in an increased risk of cardiovascular events and sudden cardiac death. Conversely, the presence of CAN may increase the risk of hypoglycemia through hypoglycemia unawareness and subsequent impaired ability to restore euglycemia (21) through impaired sympathoadrenal response to hypoglycemia or delayed gastric emptying. […] A possible pathogenic role of GV/hypoglycemic stress on CAN development and progressions should be also considered. Prior studies in healthy and diabetic subjects have found that higher exposure to hypoglycemia reduces the counter-regulatory hormone (e.g., epinephrine, glucagon, and adrenocorticotropic hormone) and blunts autonomic nervous system responses to subsequent hypoglycemia (21). […] Our data […] suggest that wide glycemic fluctuations, particularly hypoglycemic stress, may increase the risk of CAN in patients with type 1 diabetes.”

“In summary, in this cohort of relatively young and uncomplicated patients with type 1 diabetes, GV and higher hypoglycemic stress were associated with impaired HRV reflective of sympathetic/parasympathetic dysfunction with potential important clinical consequences.”

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iii. Elevated Levels of hs-CRP Are Associated With High Prevalence of Depression in Japanese Patients With Type 2 Diabetes: The Diabetes Distress and Care Registry at Tenri (DDCRT 6).

“In the last decade, several studies have been published that suggest a close association between diabetes and depression. Patients with diabetes have a high prevalence of depression (1) […] and a high prevalence of complications (3). In addition, depression is associated with mortality in these patients (4). […] Because of this strong association, several recent studies have suggested the possibility of a common biological pathway such as inflammation as an underlying mechanism of the association between depression and diabetes (5). […] Multiple mechanisms are involved in the association between diabetes and inflammation, including modulation of lipolysis, alteration of glucose uptake by adipose tissue, and an indirect mechanism involving an increase in free fatty acid levels blocking the insulin signaling pathway (10). Psychological stress can also cause inflammation via innervation of cytokine-producing cells and activation of the sympathetic nervous systems and adrenergic receptors on macrophages (11). Depression enhances the production of inflammatory cytokines (12–14). Overproduction of inflammatory cytokines may stimulate corticotropin-releasing hormone production, a mechanism that leads to hypothalamic-pituitary axis activity. Conversely, cytokines induce depressive-like behaviors; in studies where healthy participants were given endotoxin infusions to trigger cytokine release, the participants developed classic depressive symptoms (15). Based on this evidence, it could be hypothesized that inflammation is the common biological pathway underlying the association between diabetes and depression.”

“[F]ew studies have examined the clinical role of inflammation and depression as biological correlates in patients with diabetes. […] In this study, we hypothesized that high CRP [C-reactive protein] levels were associated with the high prevalence of depression in patients with diabetes and that this association may be modified by obesity or glycemic control. […] Patient data were derived from the second-year survey of a diabetes registry at Tenri Hospital, a regional tertiary care teaching hospital in Japan. […] 3,573 patients […] were included in the study. […] Overall, mean age, HbA_1c level, and BMI were 66.0 years, 7.4% (57.8 mmol/mol), and 24.6 kg/m², respectively. Patients with major depression tended to be relatively young […] and female […] with a high BMI […], high HbA_1c levels […], and high hs-CRP levels […]; had more diabetic nephropathy […], required more insulin therapy […], and exercised less […]”.

“In conclusion, we observed that hs-CRP levels were associated with a high prevalence of major depression in patients with type 2 diabetes with a BMI of ≥25 kg/m². […] In patients with a BMI of <25 kg/m², no significant association was found between hs-CRP quintiles and major depression […] We did not observe a significant association between hs-CRP and major depression in either of HbA_1c subgroups. […] Our results show that the association between hs-CRP and diabetes is valid even in an Asian population, but it might not be extended to nonobese subjects. […] several factors such as obesity and glycemic control may modify the association between inflammation and depression. […] Obesity is strongly associated with chronic inflammation.”

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iv. A Novel Association Between Nondipping and Painful Diabetic Polyneuropathy.

“Sleep problems are common in painful diabetic polyneuropathy (PDPN) (1) and contribute to the effect of pain on quality of life. Nondipping (the absence of the nocturnal fall in blood pressure [BP]) is a recognized feature of diabetic cardiac autonomic neuropathy (CAN) and is attributed to the abnormal prevalence of nocturnal sympathetic activity (2). […] This study aimed to evaluate the relationship of the circadian pattern of BP with both neuropathic pain and pain-related sleep problems in PDPN […] Investigating the relationship between PDPN and BP circadian pattern, we found patients with PDPN exhibited impaired nocturnal decrease in BP compared with those without neuropathy, as well as higher nocturnal systolic BP than both those without DPN and with painless DPN. […] in multivariate analysis including comorbidities and most potential confounders, neuropathic pain was an independent determinant of ∆ in BP and nocturnal systolic BP.”

“PDPN could behave as a marker for the presence and severity of CAN. […] PDPN should increasingly be regarded as a condition of high cardiovascular risk.”

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v. Reduced Testing Frequency for Glycated Hemoglobin, HbA_1c, Is Associated With Deteriorating Diabetes Control.

I think a potentially important take-away from this paper, which they don’t really talk about, is that when you’re analyzing time series data in research contexts where the HbA_1c variable is available at the individual level at some base frequency and you then encounter individuals for whom the HbA_1c variable is unobserved in such a data set for some time periods/is not observed at the frequency you’d expect, such (implicit) missing values may not be missing at random (for more on these topics see e.g. this post). More specifically, in light of the findings of this paper I think it would make a lot of sense to default to an assumption of missing values being an indicator of worse-than-average metabolic control during the unobserved period of the time series in question when doing time-to-event analyses, especially in contexts where the values are missing for an extended period of time.

The authors of the paper consider metabolic control an outcome to be explained by the testing frequency. That’s one way to approach these things, but it’s not the only one and I think it’s also important to keep in mind that some patients also sometimes make a conscious decision not to show up for their appointments/tests; i.e. the testing frequency is not necessarily fully determined by the medical staff, although they of course have an important impact on this variable.

Some observations from the paper:

“We examined repeat HbA_1c tests (400,497 tests in 79,409 patients, 2008–2011) processed by three U.K. clinical laboratories. We examined the relationship between retest interval and 1) percentage change in HbA_1c and 2) proportion of cases showing a significant HbA_1c rise. The effect of demographics factors on these findings was also explored. […] Figure 1 shows the relationship between repeat requesting interval (categorized in 1-month intervals) and percentage change in HbA_1c concentration in the total data set. From 2 months onward, there was a direct relationship between retesting interval and control. A testing frequency of >6 months was associated with deterioration in control. The optimum testing frequency in order to maximize the downward trajectory in HbA_1c between two tests was approximately four times per year. Our data also indicate that testing more frequently than 2 months has no benefit over testing every 2–4 months. Relative to the 2–3 month category, all other categories demonstrated statistically higher mean change in HbA_1c (all P < 0.001). […] similar patterns were observed for each of the three centers, with the optimum interval to improvement in overall control at ∼3 months across all centers.”

“[I]n patients with poor control, the pattern was similar to that seen in the total group, except that 1) there was generally a more marked decrease or more modest increase in change of HbA_1c concentration throughout and, consequently, 2) a downward trajectory in HbA_1c was observed when the interval between tests was up to 8 months, rather than the 6 months as seen in the total group. In patients with a starting HbA_1c of <6% (<42 mmol/mol), there was a generally linear relationship between interval and increase in HbA_1c, with all intervals demonstrating an upward change in mean HbA_1c. The intermediate group showed a similar pattern as those with a starting HbA_1c of <6% (<42 mmol/mol), but with a steeper slope.”

“In order to examine the potential link between monitoring frequency and the risk of major deterioration in control, we then assessed the relationship between testing interval and proportion of patients demonstrating an increase in HbA_1c beyond the normal biological and analytical variation in HbA_1c […] Using this definition of significant increase as a ≥9.9% rise in subsequent HbA_1c, our data show that the proportion of patients showing this magnitude of rise increased month to month, with increasing intervals between tests for each of the three centers. […] testing at 2–3-monthly intervals would, at a population level, result in a marked reduction in the proportion of cases demonstrating a significant increase compared with annual testing […] irrespective of the baseline HbA_1c, there was a generally linear relationship between interval and the proportion demonstrating a significant increase in HbA_1c, though the slope of this relationship increased with rising initial HbA_1c.”

“Previous data from our and other groups on requesting patterns indicated that relatively few patients in general practice were tested annually (5,6). […] Our data indicate that for a HbA_1c retest interval of more than 2 months, there was a direct relationship between retesting interval and control […], with a retest frequency of greater than 6 months being associated with deterioration in control. The data showed that for diabetic patients as a whole, the optimum repeat testing interval should be four times per year, particularly in those with poorer diabetes control (starting HbA_1c >7% [≥53 mmol/mol]). […] The optimum retest interval across the three centers was similar, suggesting that our findings may be unrelated to clinical laboratory factors, local policies/protocols on testing, or patient demographics.”

It might be important to mention that there are important cross-country differences in terms of how often people with diabetes get HbA_1c measured – I’m unsure of whether or not standards have changed since then, but at least in Denmark a specific treatment goal of the Danish Regions a few years ago was whether or not 95% of diabetics had had their HbA_1c measured within the last year (here’s a relevant link to some stuff I wrote about related topics a while back).

A few diabetes papers of interest

i. Glycated Hemoglobin and All-Cause and Cause-Specific Mortality in Singaporean Chinese Without Diagnosed Diabetes: The Singapore Chinese Health Study.

“Previous studies have reported that elevated levels of HbA_1c below the diabetes threshold (<6.5%) are associated with an increased risk for cardiovascular morbidity and mortality (3–12). Yet, this research base is not comprehensive, and data from Chinese populations are scant, especially in those without diabetes. This gap in the literature is important since Southeast Asian populations are experiencing epidemic rates of type 2 diabetes and related comorbidities with a substantial global health impact (13–16).

Overall, there are few cohort studies that have examined the etiologic association between HbA_1c levels and all-cause and cause-specific mortality. There is even lesser insight on the nature of the relationship between HbA_1c and significant clinical outcomes in Southeast Asian populations. Therefore, we examined the association between HbA_1c and all-cause and cause-specific mortality in the Singapore Chinese Health Study (SCHS).”

“The design of the SCHS has been previously summarized (17). Briefly, the cohort was drawn from men and women, aged 45–74 years, who belonged to one of the major dialect groups (Hokkien or Cantonese) of Chinese in Singapore. […] Between April 1993 and December 1998, 63,257 individuals completed an in-person interview that included questions on usual diet, demographics, height and weight, use of tobacco, usual physical activity, menstrual and reproductive history (women only), medical history including history of diabetes diagnosis by a physician, and family history of cancer. […] At the follow-up interview (F1), which occurred in 1999–2004, subjects were asked to update their baseline interview information. […] The study population derived from 28,346 participants of the total 54,243 who were alive and participated at F1, who provided consent at F1 to collect subsequent blood samples (a consent rate of ∼65%). The participants for this study were a random selection of individuals from the full study population who did not report a history of diabetes or CVD at the baseline or follow-up interview and reported no history of cancer.”

“During 74,890 person-years of follow-up, there were 888 total deaths, of which 249 were due to CVD, 388 were due to cancer, and 169 were recorded as respiratory mortality. […] There was a positive association between HbA_1c and age, BMI, and prevalence of self-reported hypertension, while an inverse association was observed between educational attainment and HbA_1c. […] The crude mortality rate was 1,186 deaths per 100,000 person-years. The age- and sex-standardized mortality rates for all-cause, CVD, and cerebrovascular each showed a J-shaped pattern according to HbA_1c level. The CHD and cancer mortality rates were higher for HbA_1c ≥6.5% (≥48 mmol/mol) and otherwise displayed no apparent pattern. […] There was no association between any level of HbA_1c and respiratory causes of death.”

“Chinese men and women with no history of cancer, reported diabetes, or CVD with an HbA_1c level ≥6.5% (≥48 mmol/mol) were at a significant increased risk of mortality during follow-up relative to their peers with an HbA_1c of 5.4–5.6% (36–38 mmol/mol). No other range of HbA_1c was significantly associated with risk of mortality during follow-up, and in secondary analyses, when the HbA_1c level ≥6.5% (≥48 mmol/mol) was divided into four categories, this increased risk was observed in all four categories; thus, these data represent a clear threshold association between HbA_1c and mortality in this population. These results are consistent with previous prospective cohort studies identifying chronically high HbA_1c, outside of diabetes, to be associated with increased risk for all-cause and CVD-related mortality (3–12,22).”

“Hyperglycemia is a known risk factor for CVD, not limited to individuals with diabetes. This may be in part due to the vascular damage caused by oxidative stress in periods of hypo- and hyperglycemia (23,24). For individuals with impaired fasting glucose and impaired glucose tolerance, increased oxidative stress and endothelial dysfunction are present before the onset of diabetes (25). The association between chronically high levels of HbA_1c and development of and death from cancer is not as well defined (9,26–30). Abnormal metabolism may play a role in cancer development and death. This is important, considering cancer is the leading cause of death in Singapore for adults 15–59 years of age (31). Increased risk for cancer mortality was found in individuals with impaired glucose tolerance (30). […] Hyperinsulinemia and IGF-I are associated with increased cancer risk, possibly through mitogenic effects and tumor formation (27,28,37). This is the basis for the insulin-cancer hypothesis. Simply put, chronic levels of hyperinsulinemia reduce the production of IGF binding proteins 1 and 2. The absence of these proteins results in excess bioactive IGF-I, supporting tumor development (38). Chronic hyperglycemia, indicating high levels of insulin and IGF-I, may explain inhibition of cell apoptosis, increased cell proliferation, and increased cancer risk (39).”

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ii. The Cross-sectional and Longitudinal Associations of Diabetic Retinopathy With Cognitive Function and Brain MRI Findings: The Action to Control Cardiovascular Risk in Diabetes (ACCORD) Trial.

“Brain imaging studies suggest that type 2 diabetes–related microvascular disease may affect the central nervous system in addition to its effects on other organs, such as the eye and kidney. Histopathological evidence indicates that microvascular disease in the brain can lead to white matter lesions (WMLs) visible with MRI of the brain (1), and risk for them is often increased by type 2 diabetes (2–6). Type 2 diabetes also has recently been associated with lower brain volume, particularly gray matter volume (7–9).

The association between diabetic retinopathy and changes in brain tissue is of particular interest because retinal and cerebral small vessels have similar anatomy, physiology, and embryology (10). […] the preponderance of evidence suggests diabetic retinopathy is associated with increased WML burden (3,12–14), although variation exists. While cross-sectional studies support a correlation between diabetic retinopathy and WMLs (2,3,6,15), diabetic retinopathy and brain atrophy (16), diabetic retinopathy and psychomotor speed (17,18), and psychomotor speed and WMLs (5,19,20), longitudinal evidence demonstrating the assumed sequence of disease development, for example, vascular damage of eye and brain followed by cognitive decline, is lacking.

Using Action to Control Cardiovascular Risk in Diabetes (ACCORD) data, in which a subset of participants received longitudinal measurements of diabetic retinopathy, cognition, and MRI variables, we analyzed the 1) cross-sectional associations between diabetic retinopathy and evidence of brain microvascular disease and 2) determined whether baseline presence or severity of diabetic retinopathy predicts 20- or 40-month changes in cognitive performance or brain microvascular disease.”

“The ACCORD trial (21) was a multicenter randomized trial examining the effects of intensive glycemic control, blood pressure, and lipids on cardiovascular disease events. The 10,251 ACCORD participants were aged 40–79 years, had poorly controlled type 2 diabetes (HbA_1c > 7.5% [58.5 mmol/mol]), and had or were at high risk for cardiovascular disease. […] The ACCORD-Eye sample comprised 3,472 participants who did not report previous vitrectomy or photocoagulation surgery for proliferative diabetic retinopathy at baseline […] ACCORD-MIND included a subset of 2,977 ACCORD participants who completed a 30-min cognitive testing battery, 614 of whom also had useable scans from the MRI substudy (23,24). […] ACCORD-MIND had visits at three time points: baseline, 20 months, and 40 months. MRI of the brain was completed at baseline and the 40-month time point.”

“Baseline diabetic retinopathy was associated with more rapid 40-month declines in DSST and MMSE [Mini-Mental State Examination] when adjusting for demographics and lifestyle factors in model 1 […]. Moreover, increasing severity of diabetic retinopathy was associated with increased amounts of decline in DSST [Digit Symbol Substitution Test] performance (−1.30, −1.76, and −2.81 for no, mild, and moderate/severe NPDR, respectively; P = 0.003) […Be careful about how to interpret that p-value – see below, US] . The associations remained virtually unchanged after further adjusting for vascular and diabetes risk factors, depression, and visual acuity using model 2.”

“This longitudinal study provides new evidence that diabetic retinopathy is associated with future cognitive decline in persons with type 2 diabetes and confirms the finding from the Edinburgh Type 2 Diabetes Study derived from cross-sectional data that lifetime cognitive decline is associated with diabetic retinopathy (32). We found that the presence of diabetic retinopathy, independent of visual acuity, predicts greater declines in global cognitive function measured with the MMSE and that the magnitude of decline in processing speed measured with the DSST increased with increasing severity of baseline diabetic retinopathy. The association with psychomotor speed is consistent with prior cross-sectional findings in community-based samples of middle-aged (18) and older adults (17), as well as prospective studies of a community-based sample of middle-aged adults (33) and patients with type 1 diabetes (34) showing that retinopathy with different etiologies predicted a subsequent decline in psychomotor speed. This study extends these findings to patients with type 2 diabetes.”

“we tested a number of different associations but did not correct P values for multiple testing” [Aargh!, US.]

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iii. Incidence of Remission in Adults With Type 2 Diabetes: The Diabetes & Aging Study.

(Note to self before moving on to the paper: these people identified type 1 diabetes by self-report or diabetes onset at <30 years of age, treated with insulin only and never treated with oral agents).

“It is widely believed that type 2 diabetes is a chronic progressive condition, which at best can be controlled, but never cured (1), and that once treatment with glucose-lowering medication is initiated, it is required indefinitely and is intensified over time (2,3). However, a growing body of evidence from clinical trials and case-control studies (4–6) has reported the remission of type 2 diabetes in certain populations, most notably individuals who received bariatric surgery. […] Despite the clinical relevance and importance of remission, little is known about the incidence of remission in community settings (11,12). Studies to date have focused largely on remission after gastric bypass or relied on data from clinical trials, which have limited generalizability. Therefore, we conducted a retrospective cohort study to describe the incidence rates and variables associated with remission among adults with type 2 diabetes who received usual care, excluding bariatric surgery, in a large, ethnically diverse population. […] 122,781 individuals met our study criteria, yielding 709,005 person-years of total follow-up time.”

“Our definitions of remission were based on the 2009 ADA consensus statement (10). “Partial remission” of diabetes was defined as having two or more consecutive subdiabetic HbA_1c measurements, all of which were in the range of 5.7–6.4% [39–46 mmol/mol] over a period of at least 12 months. “Complete remission” was defined as having two or more consecutive normoglycemic HbA_1c measurements, all of which were <5.7% [<39 mmol/mol] over a period of at least 12 months. “Prolonged remission” was defined as having two or more consecutive normoglycemic HbA_1c measurements, all of which were <5.7% [<39 mmol/mol] over a period of at least 60 months. Each definition of remission requires the absence of pharmacologic treatment during the defined observation period.”

“The average age of participants was 62 years, 47.1% were female, and 51.6% were nonwhite […]. The mean (SD) interval between HbA_1c tests in the remission group was 256 days (139 days). The mean interval (SD) between HbA_1c tests among patients not in the remission group was 212 days (118 days). The median time since the diagnosis of diabetes in our cohort was 5.9 years, and the average baseline HbA_1c level was 7.4% [57 mmol/mol]. The 18,684 individuals (15.2%) in the subset with new-onset diabetes, defined as ≤2 years since diagnosis, were younger, were more likely to have their diabetes controlled by diet, and had fewer comorbidities […] The incidence densities of partial, complete, and prolonged remission in the full cohort were 2.8 (95% CI 2.6–2.9), 0.24 (95% CI 0.20–0.28), and 0.04 (95% CI 0.01–0.06) cases per 1,000 person-years, respectively […] The 7-year cumulative incidences of partial, complete, and prolonged remission were 1.5% (95% CI 1.4–1.5%), 0.14% (95% CI 0.12–0.16%), and 0.01% (95% CI 0.003–0.02%), respectively. The 7-year cumulative incidence of any remission decreased with longer time since diagnosis from a high of 4.6% (95% CI 4.3–4.9%) for individuals diagnosed with diabetes in the past 2 years to a low of 0.4% (95% CI 0.3–0.5%) in those diagnosed >10 years ago. The 7-year cumulative incidence of any remission was much lower for individuals using insulin (0.05%; 95% CI 0.03–0.1%) or oral agents (0.3%; 95% CI 0.2–0.3%) at baseline compared with diabetes patients not using medication at baseline (12%; 95% CI 12–13%).”

“In this large cohort of insured adults with type 2 diabetes not treated with bariatric surgery, we found that 1.5% of individuals with recent evidence of clinical diabetes achieved at least partial remission over a 7-year period. If these results were generalized to the 25.6 million U.S. adults living with type 2 diabetes in 2010 (25), they would suggest that 384,000 adults could experience remission over the next 7 years. However, the rate of prolonged remission was extremely rare (0.007%), translating into only 1,800 adults in the U.S. experiencing remission lasting at least 5 years. To provide context, 1.7% of the cohort died, while only 0.8% experienced any level of remission, during the calendar year 2006. Thus, the chances of dying were higher than the chances of any remission. […] Although remission of type 2 diabetes is uncommon, it does occur in patients who have not undergone surgical interventions. […] Our analysis shows that remission is rare and variable. The likelihood of remission is more common among individuals with early-onset diabetes and those not treated with glucose-lowering medications at the point of diabetes diagnosis. Although rare, remission can also occur in individuals with more severe diabetes and those previously treated with insulin.”

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iv. Blood pressure control for diabetic retinopathy (Cochrane review).

“Diabetic retinopathy is a common complication of diabetes and a leading cause of visual impairment and blindness. Research has established the importance of blood glucose control to prevent development and progression of the ocular complications of diabetes. Simultaneous blood pressure control has been advocated for the same purpose, but findings reported from individual studies have supported varying conclusions regarding the ocular benefit of interventions on blood pressure. […] The primary aim of this review was to summarize the existing evidence regarding the effect of interventions to control or reduce blood pressure levels among diabetics on incidence and progression of diabetic retinopathy, preservation of visual acuity, adverse events, quality of life, and costs. A secondary aim was to compare classes of anti-hypertensive medications with respect to the same outcomes.”

“We included 15 RCTs, conducted primarily in North America and Europe, that had enrolled 4157 type 1 and 9512 type 2 diabetic participants, ranging from 16 to 2130 participants in individual trials. […] Study designs, populations, interventions, and lengths of follow-up (range one to nine years) varied among the included trials. Overall, the quality of the evidence for individual outcomes was low to moderate.”

“The evidence from these trials supported a benefit of more intensive blood pressure control intervention with respect to 4- to 5-year incidence of diabetic retinopathy (estimated risk ratio (RR) 0.80; 95% confidence interval (CI) 0.71 to 0.92) and the combined outcome of incidence and progression (estimated RR 0.78; 95% CI 0.63 to 0.97). The available evidence provided less support for a benefit with respect to 4- to 5-year progression of diabetic retinopathy (point estimate was closer to 1 than point estimates for incidence and combined incidence and progression, and the CI overlapped 1; estimated RR 0.88; 95% CI 0.73 to 1.05). The available evidence regarding progression to proliferative diabetic retinopathy or clinically significant macular edema or moderate to severe loss of best-corrected visual acuity did not support a benefit of intervention on blood pressure: estimated RRs and 95% CIs 0.95 (0.83 to 1.09) and 1.06 (0.85 to 1.33), respectively, after 4 to 5 years of follow-up. Findings within subgroups of trial participants (type 1 and type 2 diabetics; participants with normal blood pressure levels at baseline and those with elevated levels) were similar to overall findings.”

“The available evidence supports a beneficial effect of intervention to reduce blood pressure with respect to preventing diabetic retinopathy for up to 4 to 5 years. However, the lack of evidence to support such intervention to slow progression of diabetic retinopathy or to prevent other outcomes considered in this review, along with the relatively modest support for the beneficial effect on incidence, weakens the conclusion regarding an overall benefit of intervening on blood pressure solely to prevent diabetic retinopathy.”

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v. Early Atherosclerosis Relates to Urinary Albumin Excretion and Cardiovascular Risk Factors in Adolescents With Type 1 Diabetes: Adolescent Type 1 Diabetes cardio-renal Intervention Trial (AdDIT).

“Children with type 1 diabetes are at greatly increased risk for the development of both renal and cardiovascular disease in later life (1,2). Evidence is accumulating that these two complications may have a common pathophysiology, with endothelial dysfunction a key early event.

Microalbuminuria is a recognized marker of endothelial damage (3) and predicts progression to proteinuria and diabetic nephropathy, as well as to atherosclerosis (4) and increased cardiovascular risk (5). It is, however, rare in adolescents with type 1 diabetes who more often have higher urinary albumin excretion rates within the normal range, which are associated with later progression to microalbuminuria and proteinuria (6).”

“The Adolescent Type 1 Diabetes cardio-renal Intervention Trial (AdDIT) (10) is designed to examine the impact of minor differences in albumin excretion in adolescents on the initiation and progression of cardiovascular and renal disease. The primary cardiovascular end point in AdDIT is carotid intima-media thickness (cIMT). Subclinical atherosclerosis can be detected noninvasively using high-resolution ultrasound to measure the intima-media thickness (IMT) of the carotid arteries, which predicts cardiovascular morbidity and mortality (11,12). […] The primary aim of this study was to examine the relationship of increased urinary albumin excretion and cardiovascular risk factors in adolescents with type 1 diabetes with structural arterial wall changes. We hypothesized that even minor increases in albumin excretion would be associated with early atherosclerosis but that this would be detectable only in the abdominal aorta. […] A total of 406 adolescents, aged 10–16 years, with type 1 diabetes for more than 1 year, recruited in five centers across Australia, were enrolled in this cross-sectional study”.

“Structural changes in the aorta and carotid arteries could be detected in >50% of adolescents with type 1 diabetes […] The difference in aIMT [aortic intima-media thickness] between type 1 diabetic patients and age- and sex-matched control subjects was equivalent to that seen with a 5- to 6-year age increase in the type 1 diabetic patients. […] Aortic IMT was […] able to better differentiate adolescents with type 1 diabetes from control subjects than was carotid wall changes. Aortic IMT enabled detection of the very early wall changes that are present with even small differences in urinary albumin excretion. This not only supports the concept of early intervention but provides a link between renal and cardiovascular disease.

The independent relationship between aIMT and urinary albumin excretion extends our knowledge of the pathogenesis of cardiovascular and renal disease in type 1 diabetes by showing that the first signs of the development of cardiovascular disease and diabetic nephropathy are related. The concept that microalbuminuria is a marker of a generalized endothelial damage, as well as a marker of renal disease, has been recognized for >20 years (3,20,21). Endothelial dysfunction is the first critical step in the development of atherosclerosis (22). Early rises in urinary albumin excretion precede the development of microalbuminuria and proteinuria (23). It follows that the first structural changes of atherosclerosis could relate to the first biochemical changes of diabetic nephropathy. To our knowledge, this is the first study to provide evidence of this.”

“In conclusion, atherosclerosis is detectable from early adolescence in type 1 diabetes. Its early independent associations are male sex, age, systolic blood pressure, LDL cholesterol, and, importantly, urinary albumin excretion. […] Early rises in urinary albumin excretion during adolescence not only are important for determining risk of progression to microalbuminuria and diabetic nephropathy but also may alert the clinician to increased risk of cardiovascular disease.”

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vi. Impact of Islet Autoimmunity on the Progressive β-Cell Functional Decline in Type 2 Diabetes.

“Historically, type 2 diabetes (T2D) has not been considered to be immune mediated. However, many notable discoveries in recent years have provided evidence to support the concept of immune system involvement in T2D pathophysiology (1–5). Immune cells have been identified in the pancreases of phenotypic T2D patients (3–5). Moreover, treatment with interleukin-1 receptor agonist improves β-cell function in T2D patients (6–8). These studies suggest that β-cell damage/destruction mediated by the immune system may be a component of T2D pathophysiology.

Although the β-cell damage and destruction in autoimmune diabetes is most likely T-cell mediated (T), immune markers of autoimmune diabetes have primarily centered on the presence of circulating autoantibodies (Abs) to various islet antigens (9–15). Abs commonly positive in type 1 diabetes (T1D), especially GAD antibody (GADA) and islet cell Abs (ICA), have been shown to be more common in patients with T2D than in nondiabetic control populations, and the presence of multiple islet Abs, such as GADA, ICA, and tyrosine phosphatase-2 (insulinoma-associated protein 2 [IA-2]), have been demonstrated to be associated with an earlier need for insulin treatment in adult T2D patients (14,16–20).”

“In this study, we observed development of islet autoimmunity, measured by islet Abs and islet-specific T-cell responses, in 61% of the phenotypic T2D patients. We also observed a significant association between positive islet-reactive T-cell responses and a more rapid decline in β-cell function as assessed by FCP and glucagon-SCP responses. […] The results of this pilot study led us to hypothesize that islet autoimmunity is present or will develop in a large portion of phenotypic T2D patients and that the development of islet autoimmunity is associated with a more rapid decline in β-cell function. Moreover, the prevalence of islet autoimmunity in most previous studies is grossly underestimated because these studies have not tested for islet-reactive T cells in T2D patients but have based the presence of autoimmunity on antibody testing alone […] The results of this pilot study suggest important changes to our understanding of T2D pathogenesis by demonstrating that the prevalence of islet autoimmune development is not only more prevalent in T2D patients than previously estimated but may also play an important role in β-cell dysfunction in the T2D disease process.”

Gastrointestinal Function in Diabetes (II)

Some more observations from the book below.

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“In comparison with other parts of the gastrointestinal tract, the human oesophagus is a relatively simple organ with relatively simple functions. Despite this simplicity, disordered oesophageal function is not uncommon. […] The human oesophagus is a muscular tube that connects the pharyngeal cavity to the stomach. […] The most important functions of the human oesophagus and its sphincters are to propel swallowed food boluses to the stomach and to prevent gastro-oesophageal and oesophagopharyngeal reflux. […] Whereas the passage of liquid and solid food boluses through the oesophagus, and even acid gastrooesophageal reflux, are usually not perceived, the likelihood of perception is greater under pathological circumstances […] However, the relationship between oesophageal perception and stimulation is highly variable, e.g. patients with severe oesophagitis may deny any oesophageal symptom, while others with an endoscopically normal oesophagus may suffer from severe reflux symptoms.”

“While it is clear that oesophageal dysfunction occurs frequently in diabetes mellitus, there is considerable variation in the reported prevalence between different studies. […] Numerous studies have shown that oesophageal transit, as measured with radionuclide techniques, is slower in patients with diabetes than in age- and sex-matched healthy controls […] oesophageal transit appears to be delayed in 40–60% of patients with long-standing diabetes […] Although information relating to the prevalence of manometric abnormalities of the oesophagus [relevant link] is limited, the available data indicate that these are evident in approximately 50% of patients with diabetes […] A variety of oesophageal motor abnormalities has been demonstrated in patients with diabetes mellitus […]. These include a decreased amplitude […] and number […] of peristaltic contractions […], and an increased incidence of simultaneous […] and nonpropagated [10] contractions, as well as abnormal wave forms [17,30,32]. […] there is unequivocal evidence of damage to the extrinsic nerve supply to the oesophagus in diabetes mellitus. The results of examination of the oesophagus in 20 patients who died from diabetes disclosed histologic abnormalities in 18 of them […] The available information indicates that the prevalence of gastro-oesophageal reflux disease is higher in diabetes. Murray and co-workers studied 20 diabetic patients (14 type 1, six type 2), of whom nine (45%) were found to have excessive gastro-oesophageal acid reflux […] In a larger study of 50 type 1 diabetic patients without symptoms or history of gastro-oesophageal disease, abnormal gastro-oesophageal reflux, defined as a percentage of time with esophageal pH < 4 exceeding 3.5%, was detected in 14 patients (28%) [37].”

“Several studies have shown that the gastrointestinal motor responses to various stimuli are impaired during acute hyperglycaemia in both healthy subjects and diabetic patients […] acute hyperglycaemia reduces LOS [lower oesophageal sphincter, US] pressure and impairs oesophageal motility […] Several studies have shown that abnormal oesophageal motility is more frequent in diabetic patients who have evidence of peripheral or autonomic neuropathy than in those without […] In one of the largest studies that focused on the relationship between neuropathy and disordered oesophageal function, 50 […] insulin-requiring diabetics were stratified into three groups: (a) patients without peripheral neuropathy (n = 18); (b) patients with peripheral neuropathy but no autonomic neuropathy (n = 20); and (c) patients with both peripheral and autonomic neuropathy (n = 12). Radionuclide oesophageal emptying was found to be abnormal in 55%, 70% and 83% of patients in groups A, B and C, respectively [17]. […] It must be emphasised, however, that although several studies have provided evidence for the existence of a relationship between disordered oesophageal function and diabetic autonomic neuropathy, this relationship is relatively weak [13,14,17,27,37,49].”

“There is considerable disagreement in the literature as to the prevalence of symptoms of oesophageal dysfunction in diabetes mellitus. Some publications indicate that patients with diabetes mellitus usually do not complain about oesophageal symptoms, even when severe oesophageal dysfunction is present. […] However, in other studies a high prevalence of oesophageal symptoms in diabetics has been documented. For example, 27% of 137 unselected diabetics attending an outpatient clinic admitted to having dysphagia when specifically asked […] The poor association between oesophageal dysfunction and symptoms in patients with diabetes may reflect impaired perception of oesophageal stimuli caused by neuropathic abnormalities in afferent pathways. The development of symptoms and signs of gastro-oesophageal reflux disease in diabetics may in part be counteracted by a decrease in gastric acid secretion [59]. […] [However] oesophageal acid exposure is increased in about 40% of diabetics and it is known that the absence of reflux symptoms does not exclude the presence of severe oesophagitis and/or Barrett’s metaplasia. Due to impaired oesophageal perception, the proportion of asymptomatic patients with reflux disease may be higher in the presence of diabetes than when diabetes is absent. It might, therefore, be argued that a screening upper gastrointestinal endoscopy should be performed in diabetic patients, even when no oesophageal or gastric symptoms are reported. However, [a] more cost-effective
and realistic approach may be to perform endoscopy in diabetics with other risk factors for reflux disease, in particular severe obesity. […] Since upper gastrointestinal symptoms correlate poorly with objective abnormalities of gastrointestinal motor function in diabetes, the symptomatic benefit that could be expected from correction of these motor abnormalities is questionable. […] Little or nothing is known about the prognosis of disordered oesophageal function in diabetes. Long-term follow-up studies are lacking.”

“Abnormally delayed gastric emptying, or gastroparesis, was once considered to be a rare sequela of diabetes mellitus, occurring occasionally in patients who had long-standing diabetes complicated by symptomatic autonomic neuropathy, and inevitably associated with both intractable upper gastrointestinal symptoms and a poor prognosis [1]. Consequent upon the development of a number of techniques to quantify gastric motility […] and the rapid expansion of knowledge relating to both normal and disordered gastric motor function in humans over the last ∼ 20 years, it is now recognised that these concepts are incorrect. […] Delayed gastric emptying represents a frequent, and clinically important, complication of diabetes mellitus. […] Cross-sectional studies […] have established that gastric emptying of solid, or nutrient liquid, meals is abnormally slow in some 30–50% of outpatients with longstanding type 1 [7–20] or type 2 [20–26] diabetes […]. Early studies, using insensitive barium contrast techniques to quantify gastric emptying, clearly underestimated the prevalence substantially [1,27]. The reported prevalence of delayed gastric emptying is highest when gastric emptying of both solid and nutrient-containing liquids (or semi-solids) are measured, either simultaneously or on separate occasions [17,28,29], as there is a relatively poor correlation between gastric emptying of solids and liquids in diabetes [28–30]. […] It is now recognised that delayed gastric emptying also occurs frequently (perhaps about 30%) in children and adolescents with type 1 diabetes [37–39]. […] intragastric meal distribution is also frequently abnormal in outpatients with diabetes, with increased retention of food in both the proximal and distal stomach [31,33]. The former may potentially be important in the aetiology of gastro-oesophageal reflux [34], which appears to occur more frequently in patients with diabetes […] Diabetic gastroparesis is often associated with motor dysfunction in other areas of the gut, e.g. oesophageal transit is delayed in some 50% of patients with long-standing diabetes [8].”

“Overall patterns of gastric emptying are critically dependent on the physical and chemical composition of a meal, so that there are substantial differences between solids, semi-solids, nutrient liquids and non-nutrient liquids [70]. […] The major factor regulating gastric emptying of nutrients (liquids and ‘liquefied’ solids) is feedback inhibition, triggered by receptors that are distributed throughout the small intestine [72]; as a result of this inhibition, nutrient-containing liquids usually empty from the stomach at an overall rate of about 2 kcal/min, after an initial emptying phase that may be somewhat faster [73]. These small intestinal receptors also respond to pH, osmolality and distension, as well as nutrient content. […] While the differential emptying rates of solids, nutrient and non-nutrient liquids when ingested alone is well established, there is much less information about the interaction between different meal components. When liquids and solids are consumed together, liquids empty preferentially (∼ 80% before the solid starts to empty) […] and the presence of a solid meal results in an overall slowing of a simultaneously ingested liquid [71,75,76]. Therefore, while it is clear that the stomach can, to some extent, regulate the emptying of liquids and solids separately, the mechanisms by which this is accomplished remain poorly defined. Extracellular fat has a much lower density than water and is liquid at body temperature. The pattern of gastric emptying of fat, and its effects on emptying of other meal components are, therefore, dependent on posture — in the left lateral posture oil accumulates in the stomach and empties early, which markedly delays emptying of a nutrient liquid [77]. Gastric emptying is also influenced by patterns of previous nutrient intake. In healthy young and older subjects, supplementation of the diet with glucose is associated with acceleration of gastric emptying of glucose [78,79], while short-term starvation slows gastric emptying”.

“[I]n animal models of diabetes a number of morphological changes are evident in the autonomic nerves supplying the gut and the myenteric plexus, including a reduction in the number of myelinated axons in the vagosympathetic trunk and neurons in the dorsal root ganglia, abnormalities in neurotransmitters […] as well as a reduced number of interstitial cells of Cajal in the fundus and antrum [89–92]. In contrast, there is hitherto little evidence of a fixed pathological process in the neural tissue of humans with diabetes […] While a clear-cut association between disordered gastrointestinal function in diabetes mellitus and the presence of autonomic neuropathy remains to be established, it is now recognised that acute changes in the blood glucose concentration have a substantial, and reversible, effect on gastric (as well as oesophageal, intestinal, gallbladder and anorectal) motility, in both healthy subjects and patients with diabetes […] Marked hyperglycaemia (blood glucose concentration ∼ 15 mmol/l) affects motility in every region of the gastrointestinal tract [103]. […] In healthy subjects [114] and patients with uncomplicated type 1 diabetes […] gastric emptying is accelerated markedly during hypoglycaemia […] this response is likely to be important in the counterregulation of hypoglycaemia. It is not known whether the magnitude of the effect of hypoglycaemia on gastric emptying is influenced by gastroparesis and/or autonomic neuropathy. Recent studies have established that changes in the blood glucose concentration within the normal postprandial range also influence gastric emptying and motility [104–106]; emptying of solids and nutrient-containing liquids is slower at a blood glucose of 8 mmol/l than at 4 mmol/l in both healthy subjects and patients with type 1 diabetes […] Recent studies suggest that the rate of gastric emptying is a significant factor in postprandial hypotension. The latter, which may lead to syncope and falls, is an important clinical problem, particularly in the elderly and patients with autonomic dysfunction (usually diabetes mellitus), occurring more frequently than orthostatic hypotension [154].”

“Gastric emptying is potentially an important determinant of oral drug absorption; most orally administered drugs (including alcohol) are absorbed more slowly from the stomach than from the small intestine because the latter has a much greater surface area [179,180]. Thus, delayed gastric emptying (particularly that of tablets or capsules, which are not degraded easily in the stomach) and a reduction in antral phase 3 activity, may potentially lead to fluctuations in the serum concentrations of orally administered drugs. This may be particularly important when a rapid onset of drug effect is desirable, as with some oral hypoglycaemic drugs […]. There is relatively little information about drug absorption in patients with diabetic gastroparesis [179] and additional studies are required.”

“Glycated haemoglobin is influenced by both fasting and postprandial glucose levels; while their relative contributions have not been defined precisely [181], it is clear that improved overall glycaemic control, as assessed by glycated haemoglobin, can be achieved by lowering postprandial blood glucose concentrations, even at the expense of higher fasting glucose levels [182]. Accordingly, the control of postprandial blood glucose levels, as opposed to glycated haemoglobin, now represents a specific target for treatment […] It remains to be established whether postprandial glycaemia per se, including the magnitude of postprandial hyperglycaemic spikes, has a distinct role in the pathogenesis of diabetic complications, but there is increasing data to support this concept [181,183,184]. It is also possible that the extent of blood glucose fluctuations is an independent determinant of the risk for long-term diabetic complications [184]. […] postprandial blood glucose levels are potentially determined by a number of factors, including preprandial glucose concentrations, the glucose content of a meal, small intestinal delivery and absorption of nutrients, insulin secretion, hepatic glucose metabolism and peripheral insulin sensitivity. Although the relative contribution of these factors remains controversial, and is likely to vary with time after a meal, it is now recognised that gastric emptying accounts for at least 35% of the variance in peak glucose levels after oral glucose (75 g) in both healthy individuals and patients with type 2 diabetes […] It is also clear that even modest perturbations in gastric emptying of carbohydrate have a major effect on postprandial glycaemia [76,79]. […] it appears that much of the observed variation in the glycaemic response to different food types (‘glycaemic indices’) in both normal subjects and patients with diabetes is attributable to differences in rates of gastric emptying [103]. […] In type 1 patients with gastroparesis […] less insulin is initially required to maintain euglycaemia after a meal when compared to those with normal gastric emptying [187]. […] There are numerous uncontrolled reports supporting the concept […] that in type 1 patients gastroparesis is a risk factor for poor glycaemic control.”

“The potential for the modulation of gastric emptying, by dietary or pharmacological means, to minimise postprandial glucose excursions and optimise glycaemic control, represents a novel approach to the optimisation of glycaemic control in diabetes, which is now being explored actively. It is important to appreciate that the underlying strategies are likely to differ fundamentally between type 1 and type 2 diabetes. In type 1 diabetes, interventions that improve the coordination between nutrient absorption and the action of exogenous insulin are likely to be beneficial, even in those patients who have delayed gastric emptying, i.e. by accelerating or even slowing gastric emptying, so that the rate of nutrient delivery (and hence absorption) is more predictable. In contrast, in type 2 diabetes, it may be anticipated that slowing of the absorption of nutrients would be desirable […] In the treatment of type 2 diabetes mellitus, dietary modifications potentially represent a more attractive and cost-effective approach than drugs […] A number of dietary strategies may slow carbohydrate absorption […] an increase in dietary fibre […] Fat is a potent inhibitor of gastric emptying and […] these effects may be dependent on posture [77]; there is the potential for relatively small quantities of fat given immediately before consumption of, or with, a meal to slow gastric emptying of other meal components, so that the postprandial rise in blood glucose is minimised [210] (this is analogous to the slowing of alcohol absorption and liquid gastric emptying when alcohol is ingested after a solid meal, rather than in the fasted state [75]). […] there is evidence that the suppression of subsequent food intake by the addition of fat to a meal may exceed the caloric value of the fat load [212]. In the broadest sense, the glycaemic response to a meal is also likely to be critically dependent on whether food from the previous meal is still present in the stomach and/or small intestine at the time of its ingestion, so that glucose tolerance may be expected to be worse in the fasted state […] than after a meal.”

“At present it is not known whether normalisation of gastric emptying in either type 1 or type 2 patients with gastroparesis improves glycaemic control. […] prokinetic drugs would not be expected to have a beneficial effect on glycaemic control in type 2 patients who are not using insulin. Erythromycin may, however, as a result of its interaction with motilin receptors, also stimulate insulin secretion (and potentially improve glycaemic control by this mechanism) in type 2 diabetes [220] […] It should […] be recognised that any drug that slows gastric emptying has the potential to induce or exacerbate upper gastrointestinal symptoms, delay oral drug absorbtion and impair the counter-regulation of glycaemia. […] At present, the use of prokinetic drugs (mainly cisapride, domperidone, metoclopramide and erythromycin) forms the mainstay of therapy [167,244–259], and most patients will require drug treatment. In general, these drugs all result in dose-related improvements in gastric emptying after acute administration […] The response to prokinetic therapy (magnitude of acceleration in gastric emptying) tends to be greater when gastric emptying is more delayed. It should be recognised that relatively few controlled studies have evaluated the effects of ‘prolonged’ (> 8 weeks) prokinetic therapy, that in many studies the sample sizes have been small, and that the assessments of gastrointestinal symptoms have, not infrequently, been suboptimal; furthermore, the results of some of these studies have been negative [32]. There have hitherto been relatively few randomised controlled trials of high quality, and those that are available differ substantially in design. […] In general, there is a poor correlation between effects on symptoms and gastric emptying — prokinetic drugs may improve symptoms by effects unrelated to acceleration of gastric emptying or central anti-emetic properties [254].”

“Autoimmune factors are well recognised to play a role in the aetiology of type 1 diabetes [316,317]. In such patients there is an increased prevalence of autoimmune aggression against non-endocrine tissues, including the gastric mucosa. The reported prevalence of parietal cell antibodies in patients with type 1 diabetes is in the range 5–28%, compared to 1.4–12% in non-diabetic controls […] The autoimmune response to parietal cell antibodies may lead to atrophic gastritis, pernicious anaemia and iron deficiency anaemia […] Parietal cell antibodies can inhibit the secretion of intrinsic factor, which is necessary for the absorption of vitamin B12, potentially resulting in pernicious anaemia. The prevalence of latent and overt pernicious anaemia in type 1 diabetes has been reported to be 1.6–4% and 0.4%, respectively […] screening for parietal cell antibodies in patients with type 1 diabetes currently appears inappropriate. However, there should be a low threshold for further investigation in those patients presenting with anaemia”.

Utility of Research Autopsies for Understanding the Dynamics of Cancer

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A few links:
Pancreatic cancer.
Jaccard index.
Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer.
Epitope.
Tissue-specific mutation accumulation in human adult stem cells during life.
Epigenomic reprogramming during pancreatic cancer progression links anabolic glucose metabolism to distant metastasis.

Infectious Disease Surveillance (III)

I have added some more observations from the book below.

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“Zoonotic diseases are infections transmitted between animals and humans […]. A recent survey identified more than 1,400 species of human disease–causing agents, over half (58%) of which were zoonotic [2]. Moreover, nearly three-quarters (73%) of infectious diseases considered to be emerging or reemerging were zoonotic [2]. […] In many countries there is minimal surveillance for live animal imports or imported wildlife products. Minimal surveillance prevents the identification of wildlife trade–related health risks to the public, agricultural industry, and native wildlife [36] and has led to outbreaks of zoonotic diseases […] Southeast Asia [is] a hotspot for emerging zoonotic diseases because of rapid population growth, high population density, and high biodiversity […] influenza virus in particular is of zoonotic importance as multiple human infections have resulted from animal exposure [77–79].”

“[R]abies is an important cause of death in many countries, particularly in Africa and Asia [85]. Rabies is still underreported throughout the developing world, and 100-fold underreporting of human rabies is estimated for most of Africa [44]. Reasons for underreporting include lack of public health personnel, difficulties in identifying suspect animals, and limited laboratory capacity for rabies testing. […] Brucellosis […] is transmissible to humans primarily through consumption of unpasteurized milk or dairy products […] Brucella is classified as a category B bioterrorism agent [90] because of its potential for aerosolization [I should perhaps here mention that the book coverage does overlaps a bit with that of Fong & Alibek’s book – which I covered here – but that I decided against covering those topics in much detail here – US] […] The key to preventing brucellosis in humans is to control or eliminate infections in animals [91–93]; therefore, veterinarians are crucial to the identification, prevention, and control of brucellosis [89]. […] Since 1954 [there has been] an ongoing eradication program involving surveillance testing of cattle at slaughter, testing at livestock markets, and whole-herd testing on the farm [in the US] […] Except for endemic brucellosis in wildlife in the Greater Yellowstone Area, all 50 states and territories in the United States are free of bovine brucellosis [94].”

“Because of its high mortality rate in humans in the absence of early treatment, Y. pestis is viewed as one of the most pathogenic human bacteria [101]. In the United States, plague is most often found in the Southwest where it is transmitted by fleas and maintained in rodent populations [102]. Deer mice and voles typically serve as maintenance hosts [and] these animals are often resistant to plague [102]. In contrast, in amplifying host species such as prairie dogs, ground squirrels, chipmunks, and wood rats, plague spreads rapidly and results in high mortality [103]. […] Human infections with Y. pestis can result in bubonic, pneumonic, or septicemic plague, depending on the route of exposure. Bubonic plague is most common; however, pneumonic plague poses a more serious public health risk since it can be easily transmitted person-to-person through inhalation of aerosolized bacteria […] Septicemic plague is characterized by bloodstream infection with Y. pestis and can occur secondary to pneumonic or bubonic forms of infection or as a primary infection [6,60].
Plague outbreaks are often correlated with animal die-offs in the area [104], and rodent control near human residences is important to prevent disease [103]. […] household pets can be an important route of plague transmission and flea control in dogs and cats is an important prevention measure [105]. Plague surveillance involves monitoring three populations for infection: vectors (e.g., fleas), humans, and rodents [106]. In the past 20 years, the numbers of human cases of plague reported in the United States have varied from 1 to 17 cases per year [90]. […] Since rodent species are the main reservoirs of the bacteria, these animals can be used for sentinel surveillance to provide an early warning of the public health risk to humans [106]. […] Rodent die-offs can often be an early indicator of a plague outbreak”.

“Zoonotic disease surveillance is crucial for protection of human and animal health. An integrated, sustainable system that collects data on incidence of disease in both animals and humans is necessary to ensure prompt detection of zoonotic disease outbreaks and a timely and focused response [34]. Currently, surveillance systems for animals and humans [operate] largely independently [34]. This results in an inability to rapidly detect zoonotic diseases, particularly novel emerging diseases, that are detected in the human population only after an outbreak occurs [109]. While most industrialized countries have robust disease surveillance systems, many developing countries currently lack the resources to conduct both ongoing and real-time surveillance [34,43].”

“Acute hepatitis of any cause has similar, usually indistinguishable, signs and symptoms. Acute illness is associated with fever, fatigue, nausea, abdominal pain, followed by signs of liver dysfunction, including jaundice, light to clay-colored stool, dark urine, and easy bruising. The jaundice, dark urine, and abnormal stool are because of the diminished capacity of the inflamed liver to handle the metabolism of bilirubin, which is a breakdown product of hemoglobin released as red blood cells are normally replaced. In severe hepatitis that is associated with fulminant liver disease, the liver’s capacity to produce clotting factors and to clear potential toxic metabolic products is severely impaired, with resultant bleeding and hepatic encephalopathy. […] An effective vaccine to prevent hepatitis A has been available for more than 15 years, and incidence rates of hepatitis A are dropping wherever it is used in routine childhood immunization programs. […] Currently, hepatitis A vaccine is part of the U.S. childhood immunization schedule recommended by the Advisory Committee on Immunization Practices (ACIP) [31].”

“Chronic hepatitis — persistent and ongoing inflammation that can result from chronic infection — usually has minimal to no signs or symptoms […] Hepatitis B and C viruses cause acute hepatitis as well as chronic hepatitis. The acute component is often not recognized as an episode of acute hepatitis, and the chronic infection may have little or no symptoms for many years. With hepatitis B, clearance of infection is age related, as is presentation with symptoms. Over 90% of infants exposed to HBV develop chronic infection, while <1% have symptoms; 5–10% of adults develop chronic infection, but 50% or more have symptoms associated with acute infection. Among those who acquire hepatitis C, 15–45% clear the infection; the remainder have lifelong infection unless treated specifically for hepatitis C.”

“[D]ata are only received on individuals accessing care. Asymptomatic acute infection and poor or unavailable measurements for high risk populations […] have resulted in questionable estimates of the prevalence and incidence of hepatitis B and C. Further, a lack of understanding of the different types of viral hepatitis by many medical providers [18] has led to many undiagnosed individuals living with chronic infection, who are not captured in disease surveillance systems. […] Evaluation of acute HBV and HCV surveillance has demonstrated a lack of sensitivity for identifying acute infection in injection drug users; it is likely that most cases in this population go undetected, even if they receive medical care [36]. […] Best practices for conducting surveillance for chronic hepatitis B and C are not well established. […] The role of health departments in responding to infectious diseases is typically responding to acute disease. Response to chronic HBV infection is targeted to prevention of transmission to contacts of those infected, especially in high risk situations. Because of the high risk of vertical transmission and likely development of chronic disease in exposed newborns, identification and case management of HBV-infected pregnant women and their infants is a high priority. […] For a number of reasons, states do not conduct uniform surveillance for chronic hepatitis C. There is not agreement as to the utility of surveillance for chronic HCV infection, as it is a measurement of prevalent rather than incident cases.”

“Among all nationally notifiable diseases, three STDs (chlamydia, gonorrhea, and syphilis) are consistently in the top five most commonly reported diseases annually. These three STDs made up more than 86% of all reported diseases in the United States in 2010 [2]. […] The true burden of STDs is likely to be higher, as most infections are asymptomatic [4] and are never diagnosed or reported. A synthesis of a variety of data sources estimated that in 2008 there were over 100 million prevalent STDs and nearly 20 million incident STDs in the United States [5]. […] Nationally, 72% of all reported STDs are among persons aged 15–24 years [3], and it is estimated that 1 in 4 females aged 14–19 has an STD [7]. […] In 2011, the rates of chlamydia, gonorrhea, and primary and secondary syphilis among African-­Americans were, respectively, 7.5, 16.9, and 6.7 times the rates among whites [3]. Additionally, men who have sex with men (MSM) are disproportionately infected with STDs. […] several analyses have shown risk ratios above 100 for the associations between being an MSM and having syphilis or HIV [9,10]. […] Many STDs can be transmitted congenitally during pregnancy or birth. In 2008, over 400,000 neonatal deaths and stillbirths were associated with syphilis worldwide […] untreated chlamydia and gonorrhea can cause ophthalmia neonatorum in newborns, which can result in blindness [13]. The medical and societal costs for STDs are high. […] One estimate in 2008 put national costs at $15.6 billion [15].”

“A significant challenge in STD surveillance is that the term “STD” encompasses a variety of infections. Currently, there are over 35 pathogens that can be transmitted sexually, including bacteria […] protozoa […] and ectoparasites […]. Some infections can cause clinical syndromes shortly after exposure, whereas others result in no symptoms or have a long latency period. Some STDs can be easily diagnosed using self-collected swabs, while others require a sample of blood or a physical examination by a clinician. Consequently, no one particular surveillance strategy works for all STDs. […] The asymptomatic nature of most STDs limits inferences from case­-based surveillance, since in order to be counted in this system an infection must be diagnosed and reported. Additionally, many infections never result in disease. For example, an estimated 90% of human papillomavirus (HPV) infections resolve on their own without sequelae [24]. As such, simply counting infections may not be appropriate, and sequelae must also be monitored. […] Strategies for STD surveillance include case reporting; sentinel surveillance; opportunistic surveillance, including use of administrative data and positivity in screened populations; and population-­based studies […] the choice of strategy depends on the type of STD and the population of interest.”

“Determining which diseases and conditions should be included in mandatory case reporting requires balancing the benefits to the public health system (e.g., utility of the data) with the costs and burdens of case reporting. While many epidemiologists and public health practitioners follow the mantra “the more data, the better,” the costs (in both dollars and human resources) of developing and maintaining a robust case­-based reporting system can be large. Case­-based surveillance has been mandated for chlamydia, gonorrhea, syphilis, and chancroid nationally; but expansion of state­-initiated mandatory reporting for other STDs is controversial.”

Harnessing phenotypic heterogeneity to design better therapies

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Unlike many of the IAS lectures I’ve recently blogged this one is a new lecture – it was uploaded earlier this week. I have to say that I was very surprised – and disappointed – that the treatment strategy discussed in the lecture had not already been analyzed in a lot of detail and been implemented in clinical practice for some time. Why would you not expect the composition of cancer cell subtypes in the tumour microenvironment to change when you start treatment – in any setting where a subgroup of cancer cells has a different level of responsiveness to treatment than ‘the average’, that would to me seem to be the expected outcome. And concepts such as drug holidays and dose adjustments as treatment responses to evolving drug resistance/treatment failure seem like such obvious approaches to try out here (…the immunologists dealing with HIV infection have been studying such things for decades). I guess ‘better late than never’.

A few papers mentioned/discussed in the lecture:

Impact of Metabolic Heterogeneity on Tumor Growth, Invasion, and Treatment Outcomes.
Adaptive vs continuous cancer therapy: Exploiting space and trade-offs in drug scheduling.
Exploiting evolutionary principles to prolong tumor control in preclinical models of breast cancer.