BMI and Coronary Heart Disease Risk Among Low-Income and Underinsured Diabetic Patients

OBJECTIVEThe association between obesity and coronary heart disease (CHD) risk remains debatable, and no studies have assessed this association among diabetic patients. The aim of our study was to investigate the association between BMI and CHD risk among patients with type 2 diabetes.RESULTSDuring a mean follow-up period of 7.3 years, 7,414 subjects developed CHD. The multivariable-adjusted hazard ratios for CHD across levels of BMI at baseline (18.5–24.9, 25–29.9, 30–34.9, 35–39.9, and ≥40 kg/m²) were 1.00, 1.14 (95% CI 1.00–1.29), 1.27 (1.12–1.45), 1.54 (1.34–1.78), and 1.42 (1.23–1.64) (P_trend < 0.001) in men and 1.00, 0.95 (0.85–1.07), 0.95 (0.84–1.06), 1.06 (0.94–1.20), and 1.09 (1.00–1.22) (P_trend < 0.001) in women, respectively. When we used an updated mean or last visit value of BMI, the positive association between BMI and CHD risk did not change in men. However, the positive association of BMI with CHD changed to a U-shaped association in women when we used the last visit value of BMI.CONCLUSIONSOur study suggests that there is a positive association between BMI at baseline and during follow-up with the risk of CHD among patients with type 2 diabetes. We indicate a U-shaped association between BMI at the last visit and the risk of CHD among women with type 2 diabetes.     

Race/Ethnicity Disparities in Dysglycemia Among U.S. Women of Childbearing Age Found Mainly in the Nonoverweight/Nonobese

OBJECTIVE

To describe the burden of dysglycemia—abnormal glucose metabolism indicative of diabetes or high risk for diabetes—among U.S. women of childbearing age, focusing on differences by race/ethnicity.

RESEARCH DESIGN AND METHODS

Using U.S. National Health and Nutrition Examination Survey data (1999–2008), we calculated the burden of dysglycemia (i.e., prediabetes or diabetes from measures of fasting glucose, A1C, and self-report) in nonpregnant women of childbearing age (15–49 years) by race/ethnicity status. We estimated prevalence risk ratios (PRRs) for dysglycemia in subpopulations stratified by BMI (measured as kilograms divided by the square of height in meters), using predicted marginal estimates and adjusting for age, waist circumference, C-reactive protein, and socioeconomic factors.

RESULTS

Based on data from 7,162 nonpregnant women, representing >59,000,000 women nationwide, 19% (95% CI 17.2–20.9) had some level of dysglycemia, with higher crude prevalence among non-Hispanic blacks and Mexican Americans vs. non-Hispanic whites (26.3% [95% CI 22.3–30.8] and 23.8% [19.5–28.7] vs. 16.8% [14.4–19.6], respectively). In women with BMI <25 kg/m², dysglycemia prevalence was roughly twice as high in both non-Hispanic blacks and Mexican Americans vs. non-Hispanic whites. This relative increase persisted in adjusted models (PRR_adj 1.86 [1.16–2.98] and 2.23 [1.38–3.60] for non-Hispanic blacks and Mexican Americans, respectively). For women with BMI 25–29.99 kg/m², only non-Hispanic blacks showed increased prevalence vs. non-Hispanic whites (PRR_adj 1.55 [1.03–2.34] and 1.28 [0.73–2.26] for non-Hispanic blacks and Mexican Americans, respectively). In women with BMI >30 kg/m², there was no significant increase in prevalence of dysglycemia by race/ethnicity category.

CONCLUSIONS

Our findings show that dysglycemia affects a significant portion of U.S. women of childbearing age and that disparities by race/ethnicity are most prominent in the nonoverweight/nonobese.While national trends show that diabetes prevalence among all U.S. adults (men and women) has risen in recent years, seemingly concomitantly with rates of overweight and obesity, non-Hispanic blacks and Mexican Americans continue to be disproportionately affected, with rates almost twice those of non-Hispanic whites (1,2). This has also been the trend for impaired fasting glucose (IFG), a marker of future diabetes risk (1,2). Previous research on racial disparities of diabetes prevalence has focused on disparities for common risk factors for the disease: obesity and poverty, among others (3,4). However, findings from these studies show that there appears to be a residual effect of race/ethnicity (3,4), while controlling for the effect of BMI and social factors, with no concrete explanation as to why this might be so.Little attention has been paid specifically to investigating factors associated with disparity in glucose levels among women in their reproductive years. However, this proves an important population to target, not only because of the woman’s health needs and subsequent risk for type 2 diabetes (5), but also because of her role as a caregiver and the potential adverse consequences for her offspring if exposed to gestational hyperglycemia (6–8). We therefore conducted an analysis using U.S. national data to describe the burden of dysglycemia—diabetes, IFG, or high risk for diabetes by A1C criteria—among women of childbearing age, focusing specifically on differences by race/ethnicity. We also explored the extent to which measurements of obesity—measured by BMI and waist circumference—might modify these associations.     

Type 2 Diabetes Subgroups,Risk for Complications,and Differential Effects Due to an Intensive Lifestyle Intervention

OBJECTIVEWe reevaluated the Action for Health in Diabetes (Look AHEAD) intervention, incorporating diabetes subgroups, to identify whether intensive lifestyle intervention (ILI) is associated with differential risk for cardiovascular disease (CVD) by diabetes subgroup.RESEARCH DESIGN AND METHODSIn the Look AHEAD trial, 5,145 participants, aged 45–76 years, with type 2 diabetes (T2D) and overweight or obesity were randomly assigned to 10 years of ILI or a control condition of diabetes support and education. The ILI focused on weight loss through decreased caloric intake and increased physical activity. To characterize diabetes subgroups, we applied k-means clustering to data on age of diabetes diagnosis, BMI, waist circumference, and glycated hemoglobin. We examined whether relative intervention effects on the trial’s prespecified CVD outcomes varied among diabetes subgroups.RESULTSWe characterized four subgroups related to older age at diabetes onset (42% of sample), poor glucose control (14%), severe obesity (24%), and younger age at diabetes onset (20%). We observed interactions (all P < 0.05) between intervention and diabetes subgroups for three separate composite cardiovascular outcomes. Randomization to ILI was associated with increased risk for each cardiovascular outcome only among the poor-glucose-control subgroup (hazard ratio >1.32). Among the three other diabetes subgroups, ILI was not associated with increased risk for CVD.CONCLUSIONSAmong overweight and obese adults with T2D, a lifestyle intervention was associated with differential risk for CVD that was dependent on diabetes subgroup. Diabetes subgroups may be important to identify the patients who would achieve benefit and avoid harm from an ILI.     

Predictors of pregnancy after intrauterine insemination in women with polycystic ovary syndrome

ObjectiveTo evaluate the effects of body mass index (BMI) in patients with polycystic ovary syndrome (PCOS) undergoing controlled ovarian stimulation (COS) with intrauterine insemination (IUI).MethodsThis retrospective study evaluated couples with PCOS undergoing COS and IUI. The relationship between cumulative IUI pregnancy outcomes and BMI, treatment cycles, treatment schemes, number of dominant follicles, endometrial thickness, infertility duration and type of infertility was analysed.ResultsThe study evaluated 831 IUI cycles in 451 couples with PCOS. Compared with normoweight women, overweight and obese women required more human menopausal gonadotropin (hMG) doses and more days of COS. Gestational diabetes mellitus occurred more frequently in the obese group than in the other BMI groups. The clinical pregnancy and live birth rates in the hMG, clomiphene citrate (CC) + hMG and letrozole (LE) + hMG groups were significantly higher than those in the CC and LE groups. The clinical pregnancy rate was higher in the secondary infertility group compared with the primary infertility group.ConclusionObese women might require more hMG doses and more days of COS to overcome the effects of weight. As BMI increases, the incidence of gestational diabetes might also increase. The number of cycles and type of infertility may have a predictive value for pregnancy outcomes.     

Risk Factors for Incident Fracture in Older Adults With Type 2 Diabetes: The Framingham Heart Study

OBJECTIVETo identify risk factors for fracture in type 2 diabetes.RESEARCH DESIGN AND METHODSThis prospective study included members of the Framingham Original and Offspring Cohorts. Type 2 diabetes was defined as fasting plasma glucose >125 mg/dL or use of type 2 diabetes therapy. We used repeated-measures Cox proportional hazards regression to calculate hazard ratios (HRs) and 95% CIs for associations between potential predictors and incidence of fragility fracture.RESULTSParticipants included 793 individuals with type 2 diabetes. Mean ± SD age was 70 ± 10 years; 45% were women. A total of 106 incident fractures occurred over 1,437 observation follow-up intervals. Fracture incidence increased with age (adjusted HRs 1.00, 1.44 [95% CI 0.65, 3.16], and 2.40 [1.14, 5.04] for <60, 60–70, and >70 years, respectively; P_trend = 0.02), female sex (2.23 [1.26, 3.95]), HbA_1c (1.00, 2.10 [1.17, 3.75], and 1.29 [0.69, 2.41] for 4.45–6.46% [25–47 mmol/mol], 6.50–7.49% [48–58 mmol/mol], and 7.50–13.86% [58–128 mmol/mol]; P_trend =0.03), falls in past year (1.00, 1.87 [0.82, 4.28], and 3.29 [1.34, 8.09] for no falls, one fall, and two or more falls; P_trend =0.03), fracture history (2.05 [1.34, 3.12]), and lower grip strength (0.82 [0.69, 0.99] per 5-kg increase). Femoral neck bone mineral density, BMI, smoking, physical function, chronic diseases, medications, and physical function were not associated with fracture incidence.CONCLUSIONSPrior falls, fractures, low grip strength, and elevated HbA_1c are risk factors for fractures in older adults with type 2 diabetes. Evaluation of these factors may improve opportunities for early intervention and reduce fractures in this high-risk group.     

Changes in Plant-Based Diet Indices and Subsequent Risk of Type 2 Diabetes in Women and Men: Three U.S. Prospective Cohorts

OBJECTIVEWe evaluated the associations between changes in plant-based diets and subsequent risk of type 2 diabetes.RESEARCH DESIGN AND METHODSWe prospectively followed 76,530 women in the Nurses’ Health Study (NHS) (1986–2012), 81,569 women in NHS II (1991–2017), and 34,468 men in the Health Professionals Follow-up Study (1986–2016). Adherence to plant-based diets was assessed every 4 years with the overall plant-based diet index (PDI), healthful PDI (hPDI), and unhealthful PDI (uPDI). We used multivariable Cox proportional hazards models to estimate hazard ratios (HRs). We pooled results of the three cohorts using meta-analysis.RESULTSWe documented 12,627 cases of type 2 diabetes during 2,955,350 person-years of follow-up. After adjustment for initial BMI and initial and 4-year changes in alcohol intake, smoking, physical activity, and other factors, compared with participants whose indices remained relatively stable (±3%), participants with the largest decrease (>10%) in PDI and hPDI over 4 years had a 12–23% higher diabetes risk in the subsequent 4 years (pooled HR, PDI 1.12 [95% CI 1.05, 1.20], hPDI 1.23 [1.16, 1.31]). Each 10% increment in PDI and hPDI over 4 years was associated with a 7–9% lower risk (PDI 0.93 [0.91, 0.95], hPDI 0.91 [0.87, 0.95]). Changes in uPDI were not associated with diabetes risk. Weight changes accounted for 6.0–35.6% of the associations between changes in PDI and hPDI and diabetes risk.CONCLUSIONSImproving adherence to overall and healthful plant-based diets was associated with a lower risk of type 2 diabetes, whereas decreased adherence to such diets was associated with a higher risk.     

Change in Sleep Duration and Type 2 Diabetes: The Whitehall II Study

OBJECTIVEEvidence suggests that short and long sleep durations are associated with a higher risk of type 2 diabetes. Using successive data waves spanning >20 years, we examined whether a change in sleep duration is associated with incident diabetes.RESULTSCompared with the reference group of persistent 7-h sleepers, an increase of ≥2 h sleep per night was associated with a higher risk of incident diabetes (odds ratio 1.65 [95% CI 1.15, 2.37]) in analyses adjusted for age, sex, employment grade, and ethnic group. This association was partially attenuated by adjustment for BMI and change in weight (1.50 [1.04, 2.16]). An increased risk of incident diabetes was also seen in persistent short sleepers (average ≤5.5 h/night; 1.35 [1.04, 1.76]), but this evidence weakened on adjustment for BMI and change in weight (1.25 [0.96, 1.63]).CONCLUSIONSThis study suggests that individuals whose sleep duration increases are at an increased risk of type 2 diabetes. Greater weight and weight gain in this group partly explain the association.     

Alcohol Abstinence and the Risk of Atrial Fibrillation in Patients With Newly Diagnosed Type 2 Diabetes Mellitus: A Nationwide Population-Based Study

OBJECTIVETo investigate the effects of alcohol abstinence on prevention of new-onset atrial fibrillation (AF) in patients with type 2 diabetes mellitus (T2DM).RESEARCH DESIGN AND METHODSA total of 1,112,682 patients newly diagnosed with T2DM between 2011 and 2014 were identified from the Korean National Health Insurance Service database. After excluding those with a history of AF, 175,100 patients were included. The primary outcome was new-onset AF.RESULTSDuring a mean follow-up of 4.0 years, AF occurred in 4,174 patients. Those with heavy alcohol consumption (alcohol intake ≥40 g/day) before T2DM diagnosis had a higher risk of AF (adjusted hazard ratio [aHR] 1.22; 95% CI 1.06–1.41) compared with patients with no alcohol consumption. After T2DM diagnosis, those with moderate to heavy alcohol consumption (alcohol intake ≥20 g/day) who abstained from alcohol had a lower risk of AF (aHR 0.81; 95% CI 0.68–0.97) compared with constant drinkers. Alcohol abstinence showed consistent trends toward lower incident AF in all subgroups and was statistically significant in men (aHR 0.80; 95% CI 0.67–0.96), those aged >65 years (aHR 0.69; 95% CI 0.52–0.91), those with CHA₂DS₂-VASc score <3 points (aHR 0.71; 95% CI 0.59–0.86), noninsulin users (aHR 0.77; 95% CI 0.63–0.94), and those with BMI <25 kg/m² (aHR 0.68; 95% CI 0.53–0.88).CONCLUSIONSIn patients with newly diagnosed T2DM, alcohol abstinence was associated with a low risk of AF development. Lifestyle modifications, such as alcohol abstinence, in patients newly diagnosed with T2DM should be recommended to reduce the risk of AF.     

Human Immunodeficiency Virus Infection and Variation in Heart Failure Risk by Age,Sex, and Ethnicity: The HIV HEART Study

ObjectivesTo evaluate the risk of heart failure (HF) linked to human immunodeficiency virus (HIV) infection, how risk varies by demographic characteristics, and whether it is explained by atherosclerotic disease or risk factor treatment.Patients and MethodsWe performed a retrospective cohort study of persons with HIV (PWHs) from January 1, 2000, through December 31, 2016, frequency-matched 1:10 to persons without HIV on year of entry, age, sex, race/ethnicity, and treating facility. We evaluated the risk of incident HF associated with HIV infection, overall and by left ventricular systolic function, and whether HF risk varied by demographic characteristics.ResultsAmong 38,868 PWHs and 386,586 matched persons without HIV, mean ± SD age was 41.4±10.8 years, with 12.3% female, 21.1% Black, 20.5% Hispanic, and 3.9% Asian/Pacific Islander. During median follow-up of 3.8 years (interquartile range, 1.4-9.0 years), the rate (per 100 person-years) of incident HF was 0.23 in PWHs vs 0.15 in those without HIV (P<.001). The PWHs had a higher adjusted HF rate (adjusted hazard ratio [aHR], 1.73; 95% confidence interval [CI], 1.57 to 1.91), which was only modestly attenuated after accounting for interim acute coronary syndrome events. Results were similar by systolic function category. The adjusted risk of HF in PWHs was more prominent for those 40 years and younger (aHR, 2.45; 95% CI, 1.92 to 3.03), women (aHR, 2.48; 95% CI, 1.90 to 3.26), and Asian/Pacific Islanders (aHR, 2.46; 95% CI, 1.27 to 4.74).ConclusionHIV infection increases the risk of HF, which varied by demographic characteristics and was not primarily mediated through atherosclerotic disease pathways or differential use of cardiopreventive medications.     

Effects of Apnea,Obesity, and Statin Therapy on Proprotein Convertase Subtilisin/Kexin 9 Levels in Patients with Obstructive Sleep Apnea

ObjectivesObstructive sleep apnea (OSA) is a common condition closely related to obesity, insulin resistance, dyslipidemia, and cardiovascular disease. The aim of this study was to explore the possible relationship between OSA and proprotein convertase subtilisin/kexin type 9 (PCSK9).MethodsFull-night polysomnography was performed on 150 participants who were divided into three groups: controls, OSA patients on statin therapy, and OSA patients not on statin therapy. Biochemical markers, plasma low-density lipoprotein (LDL) and high-density lipoprotein (HDL) subclasses, and PCSK9 were determined.ResultsPCSK9 was highest in OSA patients on statins compared to the control group and to OSA patients not on statins (p = 0.036 and p = 0.039, respectively), after adjustment for body mass index (BMI). LDL diameter was greater in OSA patients not on statins compared to OSA patients on statins (p = 0.032). PCSK9 was highest in the group of patients with all three risk factors (diagnosed OSA, statins, BMI ≥25 kg/m²) compared to groups with no, one, and two risk factors (p = 0.031, p = 0.001, and p = 0.029, respectively). Presence of OSA, statin therapy, and BMI ≥25 kg/m² when combined were independently associated with higher levels of PCSK9 when adjusted for antihypertensive therapy, small dense LDL, and HDL 3c subclass (odds ratio = 2.849; interquartile range [1.026–7.912], p = 0.044).ConclusionStatin therapy was closely related to PCSK9. OSA along with obesity and statin use induces elevation of PCSK9.     

A comprehensive assessment of endothelial function in overweight women with and without polycystic ovary syndrome

PCOS (polycystic ovary syndrome) is associated with reproductive abnormalities, IR (insulin resistance) and elevated risk factors for CVD (cardiovascular disease) and Type 2 diabetes, including endothelial dysfunction. The present study aimed to assess a range of circulating markers of endothelial function in overweight women with and without PCOS. Overweight and obese age- and BMI (body mass index)-matched women with (n=80) and without (n=27) PCOS were assessed in a cross-sectional study. End-point measures were HOMA (homoeostasis model assessment)-IR, androgens, lipids, inflammatory markers [hsCRP (high-sensitivity C-reactive protein)] and endothelial function [FMD (flow-mediated dilation), ADMA (asymmetric dimethylarginine), PAI-1 (plasminogen activator inhibitor-1) and vWF (von Willebrand factor)]. Women with PCOS had elevated HOMA-IR (4.1+/-3.4 compared with 1.9+/-1.4), free androgen index (9.3+/-5.6 compared with 4.6+/-3.8), total cholesterol (5.2+/-1.0 compared with 4.7+/-0.9 mmol/l) and triacylglycerols (triglycerides; 1.4+/-0.7 compared with 0.9+/-0.3 mmol/l) (P<0.05 for all), but similar hsCRP compared with women without PCOS. With regard to endothelial function, women with PCOS had elevated ADMA (1.0+/-0.4 compared 0.3+/-0.1 mumol/l, P<0.001) and PAI-1 (5.6+/-1.8 compared with 4.6+/-1.1 units/ml, P=0.006), a trend towards worsened FMD (11.8+/-5.0 compared with 13.5+/-4.0%, P=0.075) and no difference in vWF compared with controls. For all subjects, ADMA (P=0.002) and PAI-1 (P<0.001) were increased with higher tertiles of HOMA-IR. Women with PCOS are hyperandrogenic, dyslipidaemic and have IR, and have risk factors for CVD and diabetes including increased circulating markers of endothelial function (ADMA and PAI-1) and a trend towards worse FMD as a global marker of endothelial function. In PCOS, deterioration in endothelial function is related to IR, hyperandrogenism and other factors.     

Serum Galectin-3 and Subsequent Risk of Coronary Heart Disease in Subjects With Childhood-Onset Type 1 Diabetes: A Cohort Study

OBJECTIVETo study whether serum galectin-3 and other biomarkers of inflammation predict coronary heart disease (CHD) in subjects with long-standing childhood-onset type 1 diabetes.RESEARCH DESIGN AND METHODSA population-based nationwide cohort of 299 subjects with type 1 diabetes diagnosed in Norway at <15 years of age during 1973–1982 was examined in 2002–2003 at a mean age of 33 years (range 21–44), with mean diabetes duration of 24 years (range 19–30). Subjects were followed through 31 December 2017 for their first CHD event registered by a hospitalization or cause of death using nationwide registries. Stored serum samples were available for 296 subjects and analyzed for interleukin-6 (IL-6), IL-6 receptor, IL-18, hs-CRP, matrix metalloproteinase-9, tissue inhibitor of metalloproteinase-1 (TIMP-1), galectin-3, and high-sensitivity troponin T. Adjusted hazard ratios (aHRs) for CHD per SD increase in biomarker were estimated using Cox regression.RESULTSOf 295 subjects, 40 (13.6%) had a documented CHD event during a mean follow-up of 14.4 years (range 0.5–16). IL-6 (aHR 1.32 [95% CI 1.07–1.63]), galectin-3 (aHR 1.44 [95% CI 1.09–1.80]), and TIMP-1 (aHR 1.37 [95% CI 1.04–1.81]) were significant predictors of CHD after adjustment for conventional risk factors.CONCLUSIONSGalectin-3 was significantly associated with future CHD in subjects with type 1 diabetes, and if the results are replicated in larger studies, it may aid in prediction together with conventional risk factors for CHD.     

Early Menopause and Cardiovascular Disease Risk in Women With or Without Type 2 Diabetes: A Pooled Analysis of 9,374 Postmenopausal Women

OBJECTIVEEarly menopause may be associated with higher cardiovascular disease (CVD) risk. Type 2 diabetes mellitus (T2DM), coupled with early menopause, may result in even greater CVD risk in women. We examined CVD risk in women with early compared with normal-age menopause, with and without T2DM overall, and by race/ethnicity.RESEARCH DESIGN AND METHODSWe pooled data from the Atherosclerosis Risk in Communities study, the Multi-Ethnic Study of Atherosclerosis, and the Jackson Heart Study. We included women with data on menopausal status, menopausal age, and T2DM, excluding pre- or perimenopausal women and those with prevalent CVD. Outcomes included incident coronary heart disease (CHD), stroke, heart failure (HF), and atherosclerotic cardiovascular disease (ASCVD) (CHD or stroke). We estimated the risk associated with early (<45 years) compared with normal-age menopause using Cox proportional hazards models. Covariates included age, race/ethnicity, education, BMI, blood pressure, cholesterol, smoking, alcohol consumption, antihypertensive medication, lipid-lowering medication, hormone therapy use, and pregnancy history.RESULTSWe included 9,374 postmenopausal women for a median follow-up of 15 years. We observed 1,068 CHD, 659 stroke, 1,412 HF, and 1,567 ASCVD events. T2DM significantly modified the effect of early menopause on CVD risk. Adjusted hazard ratios for early menopause and the outcomes were greater in women with T2DM versus those without (CHD 1.15 [95% CI 1.00, 1.33] vs. 1.09 [1.03, 1.15]; stroke 1.21 [1.04, 1.40] vs. 1.10 [1.04, 1.16]; ASCVD 1.29 [1.09, 1.51] vs. 1.10 [1.04, 1.17]; HF 1.18 [1.00, 1.39] vs. 1.09 [1.03, 1.16]). The modifying effect of T2DM on the association between early menopause and ASCVD was only statistically significant in Black compared with White women.CONCLUSIONSEarly menopause was associated with an increased risk for CVD in postmenopausal women. T2DM may further augment the risk, particularly in Black women.     

Novel Subgroups of Type 2 Diabetes Display Different Epigenetic Patterns That Associate With Future Diabetic Complications

OBJECTIVEType 2 diabetes (T2D) was recently reclassified into severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD), which have different risk of complications. We explored whether DNA methylation differs between these subgroups and whether subgroup-unique methylation risk scores (MRSs) predict diabetic complications.RESEARCH DESIGN AND METHODSGenome-wide DNA methylation was analyzed in blood from subjects with newly diagnosed T2D in discovery and replication cohorts. Subgroup-unique MRSs were built, including top subgroup-unique DNA methylation sites. Regression models examined whether MRSs associated with subgroups and future complications.RESULTSWe found epigenetic differences between the T2D subgroups. Subgroup-unique MRSs were significantly different in those patients allocated to each respective subgroup compared with the combined group of all other subgroups. These associations were validated in an independent replication cohort, showing that subgroup-unique MRSs associate with individual subgroups (odds ratios 1.6–6.1 per 1-SD increase, P < 0.01). Subgroup-unique MRSs were also associated with future complications. Higher MOD-MRS was associated with lower risk of cardiovascular (hazard ratio [HR] 0.65, P = 0.001) and renal (HR 0.50, P < 0.001) disease, whereas higher SIRD-MRS and MARD-MRS were associated with an increased risk of these complications (HR 1.4–1.9 per 1-SD increase, P < 0.01). Of 95 methylation sites included in subgroup-unique MRSs, 39 were annotated to genes previously linked to diabetes-related traits, including TXNIP and ELOVL2. Methylation in the blood of 18 subgroup-unique sites mirrors epigenetic patterns in tissues relevant for T2D, muscle and adipose tissue.CONCLUSIONSWe identified differential epigenetic patterns between T2D subgroups that associated with future diabetic complications. These data support a reclassification of diabetes and the need for precision medicine in T2D subgroups.     

Effects of Obesity on the Impact of Short-Term Changes in Anthropometric Measurements on Coronary Heart Disease in Women

ObjectiveTo assess the impact of short-term changes in body mass index (BMI), waist circumference (WC), hip circumference (HC), and waist-to-hip ratio on the risk of future coronary heart disease (CHD) among women.Participants and MethodsThe study sample consisted of 2468 women aged 30 years or older without cardiovascular disease at baseline who underwent 2 consecutive examinations, the first between January 31, 1999, and August 21, 2001, and second between October 20, 2001, and September 22, 2005, and were followed up until March 31, 2010. Cox proportional hazard regression was performed to estimate the hazard ratios (HRs) of the anthropometric measures for CHD events.ResultsDuring a mean follow-up of 6.6 years, CHD occurred in 127 of the study participants (5.1%). There were significant interactions between a BMI of 30 kg/m² or greater and anthropometric changes in prediction of CHD events (all P<.04). Among nonobese individuals, a 1-SD increase in HC changes, independent of WC and BMI changes, was inversely associated with risk of CHD events (HR, 0.60 [95% CI, 0.44-0.83]). Among obese individuals, a 1-SD increase in WC, independent of other changes, increased the risk of CHD. Conversely, a 1-SD increase in BMI decreased the risk of CHD by 35% (HR, 0.65 [95% CI, 0.45-0.94]).ConclusionIn this study, the impact of changes in anthropometric measures on CHD was modified by obesity at baseline. Among nonobese women, increases in HC could significantly reduce the risk of CHD events. Among obese individuals, although increases in WC were associated with a higher risk of CHD, increases in BMI decreased the risk.     

Type 2 Diabetes and COVID-19–Related Mortality in the Critical Care Setting: A National Cohort Study in England,March–July 2020

OBJECTIVETo describe the relationship between type 2 diabetes and all-cause mortality among adults with coronavirus disease 2019 (COVID-19) in the critical care setting.RESEARCH DESIGN AND METHODSThis was a nationwide retrospective cohort study in people admitted to hospital in England with COVID-19 requiring admission to a high dependency unit (HDU) or intensive care unit (ICU) between 1 March 2020 and 27 July 2020. Cox proportional hazards models were used to estimate 30-day in-hospital all-cause mortality associated with type 2 diabetes, with adjustment for age, sex, ethnicity, obesity, and other major comorbidities (chronic respiratory disease, asthma, chronic heart disease, hypertension, immunosuppression, chronic neurological disease, chronic renal disease, and chronic liver disease).RESULTSA total of 19,256 COVID-19–related HDU and ICU admissions were included in the primary analysis, including 13,809 HDU (mean age 70 years) and 5,447 ICU (mean age 58 years) admissions. Of those admitted, 3,524 (18.3%) had type 2 diabetes and 5,077 (26.4%) died during the study period. Patients with type 2 diabetes were at increased risk of death (adjusted hazard ratio [aHR] 1.23 [95% CI 1.14, 1.32]), and this result was consistent in HDU and ICU subsets. The relative mortality risk associated with type 2 diabetes decreased with higher age (age 18–49 years aHR 1.50 [95% CI 1.05, 2.15], age 50–64 years 1.29 [1.10, 1.51], and age ≥65 years 1.18 [1.09, 1.29]; P value for age–type 2 diabetes interaction = 0.002).CONCLUSIONSType 2 diabetes may be an independent prognostic factor for survival in people with severe COVID-19 requiring critical care treatment, and in this setting the risk increase associated with type 2 diabetes is greatest in younger people.     

Type 2 Diabetes,Metabolic Traits,and Risk of Heart Failure: A Mendelian Randomization Study

OBJECTIVEThe aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF).RESEARCH DESIGN AND METHODSSummary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators.RESULTSGenetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11–1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00–1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01–2.19; P = 0.042), although again with evidence of pleiotropy.CONCLUSIONSThese findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered.     

Use of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) for Improving the Accuracy of the Risk Classification of Type 1 Diabetes

OBJECTIVE

We studied the utility of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) for improving the accuracy of type 1 diabetes (T1D) risk classification in TrialNet Natural History Study (TNNHS) participants.

RESEARCH DESIGN AND METHODS

The cumulative incidence of T1D was compared between normoglycemic individuals with DPTRS values >7.00 and dysglycemic individuals in the TNNHS (n = 991). It was also compared between individuals with DPTRS values <7.00 or >7.00 among those with dysglycemia and those with multiple autoantibodies in the TNNHS. DPTRS values >7.00 were compared with dysglycemia for characterizing risk in Diabetes Prevention Trial-Type 1 (DPT-1) (n = 670) and TNNHS participants. The reliability of DPTRS values >7.00 was compared with dysglycemia in the TNNHS.

RESULTS

The cumulative incidence of T1D for normoglycemic TNNHS participants with DPTRS values >7.00 was comparable to those with dysglycemia. Among those with dysglycemia, the cumulative incidence was much higher (P < 0.001) for those with DPTRS values >7.00 than for those with values <7.00 (3-year risks: 0.16 for <7.00 and 0.46 for >7.00). Dysglycemic individuals in DPT-1 were at much higher risk for T1D than those with dysglycemia in the TNNHS (P < 0.001); there was no significant difference in risk between the studies among those with DPTRS values >7.00. The proportion in the TNNHS reverting from dysglycemia to normoglycemia at the next visit was higher than the proportion reverting from DPTRS values >7.00 to values <7.00 (36 vs. 23%).

CONCLUSIONS

DPTRS thresholds can improve T1D risk classification accuracy by identifying high-risk normoglycemic and low-risk dysglycemic individuals. The 7.00 DPTRS threshold characterizes risk more consistently between populations and has greater reliability than dysglycemia.Since the selection of participants for type 1 diabetes (T1D) prevention trials is based in large part on risk estimation, it is important to classify risk as accurately as possible. Study populations in those trials consist mainly of children, and the experimental treatments usually entail some degree of risk. Thus, a more accurate classification of risk would reduce potential harm in a vulnerable population. Improved risk classification could also result in a better assessment of efficacy with more representativeness of the findings by the inclusion of appropriate trial participants. Moreover, it could increase study efficiency by identifying more potential participants at high risk for T1D.Prevention trials have used the presence of autoantibodies and dysglycemia (abnormal glucose levels, but not in the diabetic range) to define the risk for T1D on the basis of available data (1–4). However, newer findings suggest that a reliance on dysglycemia to define risk could fail to optimize risk classification. Those with normoglycemia could be at substantial risk, since glucose levels within the normal range are predictive of T1D in autoantibody-positive individuals (5,6). Moreover, certain individuals with dysglycemia might not be at high risk, since other factors (7) could attenuate that risk.We have developed a T1D risk score (Diabetes Prevention Trial-Type 1 Risk Score [DPTRS]) from Diabetes Prevention Trial-Type 1 (DPT-1) data (7) that uses other factors, including the full range of glycemia, age, BMI, and C-peptide levels. The DPTRS was subsequently validated in the TrialNet Natural History Study (TNNHS) (8). This report will examine the use of the DPTRS for improving the accuracy of the risk classification of T1D.