Background: Body mass index (BMI), a well-known risk factor for poor cardiovascular outcomes, is associated with differential DNA methylation (DNAm). Similarly, metabolic health has also been associated with changes in DNAm. It is unclear how overall metabolic health outside of BMI may modify the relationship between BMI and methylation profiles, and what consequences this may have on downstream cardiovascular disease. The purpose of this study was to identify cytosine-phosphate-guanine (CpG) sites at which the association between BMI and DNAm could be modified by overall metabolic health. Results: The discovery study population was derived from three Women’s Health Initiative (WHI) ancillary studies (n = 3977) and two Atherosclerosis Risk in Communities (ARIC) ancillary studies (n = 3520). Findings were validated in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort (n = 1200). Generalized linear models regressed methylation β values on the interaction between BMI and metabolic health Z score (BMI × MHZ) adjusted for BMI, MHZ, cell composition, chip number and location, study characteristics, top three ancestry principal components, smoking, age, ethnicity (WHI), and sex (ARIC). Among the 429,566 sites examined, differential associations between BMI × MHZ and DNAm were identified at 22 CpG sites (FDR q < 0.05), with one site replicated in MESA (cg18989722, in the TRAPPC9 gene). Three of the 22 sites were associated with incident coronary heart disease (CHD) in WHI. For each 0.01 unit increase in DNAm β value, the risk of incident CHD increased by 9% in one site and decreased by 6–10% in two sites over 25 years. Conclusions: Differential associations between DNAm and BMI by MHZ were identified at 22 sites, one of which was validated (cg18989722) and three of which were predictive of incident CHD. These sites are located in several genes related to NF-kappa-B signaling, suggesting a potential role for inflammation between DNA methylation and BMI-associated metabolic health.

Aims: To test the hypothesis that a 50-g oral glucose challenge test with 1-h glucose measurement would have superior performance compared with other opportunistic screening methods. Methods: In this prospective study in a Veterans Health Administration primary care clinic, the following test performances, measured by area under receiver-operating characteristic curves were compared: oral glucose challenge test; random glucose; and HbA1c level, using an oral glucose tolerance test as the ‘gold standard’. Results: The study population comprised 1535 people (mean age 56 years, BMI 30.3 kg/m2, 94% men, 74% black). By oral glucose tolerance test criteria, diabetes was present in 10% and high-risk prediabetes was present in 22% of the cohort. The plasma glucose challenge test provided area under receiver-operating characteristic curves of 0.85 (95% CI 0.78–0.91) to detect diabetes and 0.76 (95% CI 0.72–0.80) to detect high-risk dysglycaemia (diabetes or high-risk prediabetes), while area under receiver-operating characteristic curves for the capillary glucose challenge test were 0.82 (95% CI 0.75–0.89) and 0.73 (95% CI 0.69–0.77) for diabetes and high-risk dysglycaemia, respectively. Random glucose performed less well [plasma: 0.76 (95% CI 0.69–0.82) and 0.66 (95% CI 0.62–0.71), respectively; capillary: 0.72 (95% CI 0.65–0.80) and 0.64 (95% CI 0.59–0.68), respectively] and HbA1c performed even less well [0.67 (95% CI 0.57–0.76) and 0.63 (95% CI 0.58–0.68), respectively]. The cost of identifying one case of high-risk dysglycaemia with a plasma glucose challenge test would be $42 from a Veterans Affairs perspective, and $55 from a US Medicare perspective. Conclusions: Glucose challenge test screening, followed, if abnormal, by an oral glucose tolerance test, would be convenient and more accurate than other opportunistic tests. Use of glucose challenge test screening could improve management by permitting earlier therapy.

Cardiovascular disease (CVD) is the leading cause of mortality in South Asia, with rapidly increasing prevalence of hypertension, type 2 diabetes (T2DM) and hyperlipidemia over the last two decades. Atherosclerotic CVD (ASCVD) affects South Asians earlier in life and at lower body weights, which is not fully explained by differential burden of conventional risk factors. Heart failure (HF) is a complex clinical syndrome of heterogeneous structural phenotypes including two major clinical subtypes, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF). The prevalence of HF in South Asians is also rising with other metabolic diseases, and HFpEF develops at younger age and leaner body mass index in South Asians than in Whites. Recent genome-wide association studies, epigenome-wide association studies and metabolomic studies of ASCVD and HF have identified genes, metabolites and pathways associated with CVD traits. However, these findings were mostly driven by samples of European ancestry, which may not accurately represent the CVD risk at the molecular level, and the unique risk profile of CVD in South Asians. Such bias, while formulating hypothesis-driven research studies, risks missing important causal or predictive factors unique to South Asians. Importantly, a longitudinal design of multi-omic markers can capture the life-course risk and natural history related to CVD, and partially disentangle putative causal relationship between risk factors, multi-omic markers and subclinical and clinical ASCVD and HF. In conclusion, combining high-resolution untargeted metabolomics with epigenomics of rigorous, longitudinal design will provide comprehensive unbiased molecular characterization of subclinical and clinical CVD among South Asians. A thorough understanding of CVD-associated metabolomic profiles, together with advances in epigenomics and genomics, will lead to more accurate estimates of CVD progression and stimulate new strategies for improving cardiovascular health.

OBJECTIVE This study tests the effectiveness of expert guidelines for diabetes prevention: Lifestyle intervention with addition of metformin, when required, among people with prediabetes. RESEARCH DESIGN AND METHODS The Diabetes Community Lifestyle Improvement Program (D-CLIP) is a randomized, controlled, translation trial of 578 overweight/obese Asian Indian adults with isolated impaired glucose tolerance (iIGT), isolated impaired fasting glucose (iIFG), or IFG+IGT in Chennai, India. Eligible individuals were identified through community-based recruitment and randomized to standard lifestyle advice (control) or a 6-month, culturally tailored, U.S. Diabetes Prevention Program-based lifestyle curriculum plus stepwise addition of metformin (500 mg, twice daily) for participants at highest risk of conversion to diabetes at ≥4 months of follow-up. The primary outcome, diabetes incidence, was assessed biannually and compared across study arms using an intention-to-treat analysis. RESULTS During 3 years of follow-up, 34.9% of control and 25.7% of intervention participants developed diabetes (P = 0.014); the relative risk reduction (RRR) was 32% (95% CI 7-50), and the number needed to treat to prevent one case of diabetes was 9.8. The RRR varied by prediabetes type (IFG+IGT, 36%; iIGT, 31%; iIFG, 12%; P = 0.77) and was stronger in participants 50 years or older, male, or obese. Most participants (72.0%) required metformin in addition to lifestyle, although there was variability by prediabetes type (iIFG, 76.5%; IFG+IGT, 83.0%; iIGT, 51.3%). CONCLUSIONS Stepwise diabetes prevention in people with prediabetes can effectively reduce diabetes incidence by a third in community settings; however, people with iIFG may require different interventions.

Introduction Lifestyle change programs implemented within healthcare systems could reach many Americans, but their impact on cardiovascular disease (CVD) remains unclear. The MOVE! program is the largest lifestyle change program implemented in a healthcare setting in the U.S. This study aimed to determine whether MOVE! participation was associated with reduced CVD incidence. Methods This retrospective cohort study, analyzed in 2013–2015, used national Veterans Health Administration databases to identify MOVE! participants and eligible non-participants for comparison (2005–2012). Patients eligible for MOVE!—obese or overweight with a weight-related health condition, and no baseline CVD—were examined (N=1,463,003). Of these, 169,248 (12%) were MOVE! participants. Patients were 92% male, 76% white, with mean age 52 years and BMI of 32. The main outcome was incidence of CVD (ICD-9 and procedure codes for coronary artery disease, cerebrovascular disease, peripheral vascular disease, and heart failure). Results Adjusting for age, race, sex, BMI, statin use, and baseline comorbidities, over a mean 4.9 years of follow-up, MOVE! participation was associated with lower incidence of total CVD (hazard ratio [HR]=0.83, 95% CI=0.80, 0.86); coronary artery disease (HR=0.81, 95% CI=0.77, 0.86); cerebrovascular disease (HR=0.87, 95% CI=0.82, 0.92); peripheral vascular disease (HR=0.89, 95% CI=0.83, 0.94); and heart failure (HR=0.78, 95% CI=0.74, 0.83). The association between MOVE! participation and CVD incidence remained significant when examined across categories of race/ethnicity, BMI, diabetes, hypertension, smoking status, and statin use. Conclusions Although participation was limited, MOVE! was associated with reduced CVD incidence in a nationwide healthcare setting.

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As blood-derived miRNAs (c-miRNAs) are modulated by exercise and nutrition, we postulated that they might be used to monitor the effects of a lifestyle intervention (LI) to prevent diabetes development. To challenge this hypothesis, obese Asian Indian pre-diabetic patients were submitted to diet modifications and physical activity for 4 months (LI group) and compared to a control group which was given recommendations only. We have considered 2 periods of time to analyze the data, i.e.; a first one to study the response to the intervention (4 months), and a second one post-intervention (8 months). At basal, 4 months and 8 months post-intervention the levels of 17 c-miRNAs were quantified, selected either for their relevance to the pathology or because they are known to be modulated by physical activity or diet. Their variations were correlated with variations of 25 metabolic and anthropometric parameters and cytokines. As expected, fasting-glycaemia, insulin-sensitivity, levels of exercise- and obesity-induced cytokines were ameliorated after 4 months. In addition, the levels of 4 miRNAs (i.e.; miR-128-3p, miR-374a-5p, miR-221-3p, and miR-133a-3p) were changed only in the LI group and were correlated with metabolic improvement (insulin sensitivity, cytokine levels, waist circumference and systolic blood pressure). However, 8 months post-intervention almost all ameliorated metabolic parameters declined indicating that the volunteers did not continue the protocol on their own. Surprisingly, the LI positive effects on c-miRNA levels were still detected, and were even more pronounced 8 months post-intervention. In parallel, MCP-1, involved in tissue infiltration by immune cells, and Il-6, adiponectin and irisin, which have anti-inflammatory effects, continued to be significantly and positively modified, 8 months post-intervention. These data demonstrated for the first time, that c-miRNA correlations with metabolic parameters and insulin sensitivity are in fact only indirect and likely associated with the level systemic inflammation. More generally speaking, this important result explains the high variability between the previous studies designed to identify specific c-miRNAs associated with the severity of insulin-resistance. The results of all these studies should take into account the level of inflammation of the patients. In addition, this finding could also explain why, whatever the pathology considered (i.e.; cancers, diabetes, neurodegenerative disorders, inflammatory diseases) the same subset of miRNAs is always found altered in the blood of patients vs healthy subjects, as these pathologies are all associated with the development of inflammation.

Introduction We compared diabetes incidence in South Asians aged ≥45 years in urban India (Chennai and Delhi) and Pakistan (Karachi), two low-income and middle-income countries undergoing rapid transition, with blacks and whites in the US, a high-income country. Research design and methods We computed age-specific, sex-specific and body mass index (BMI)-specific diabetes incidence from the prospective Center for Cardiometabolic Risk Reduction in South Asia Study (n=3136) and the Atherosclerosis Risk in Communities Study (blacks, n=3059; whites, n=9924). We assessed factors associated with incident diabetes using Cox proportional hazards regression. Results South Asians have lower BMI and waist circumference than blacks and whites (median BMI, kg/m 2: 24.9 vs 28.2 vs 26.0; median waist circumference, cm 87.5 vs 96.0 vs 95.0). South Asians were less insulin resistant than blacks and whites (age-BMI-adjusted homeostatic model assessment of insulin resistance, μIU/mL/mmol/L: 2.30 vs 3.45 vs 2.59), and more insulin deficient than blacks but not whites (age-BMI-adjusted homeostasis model assessment of β-cell dysfunction, μIU/mL/mmol/L: 103.7 vs 140.6 vs 103.9). Age-standardized diabetes incidence (cases/1000 person-years (95% CI)) in South Asian men was similar to black men and 1.6 times higher (1.37 to 1.92) than white men (26.0 (22.2 to 29.8) vs 26.2 (22.7 to 29.7) vs 16.1 (14.8 to 17.4)). In South Asian women, incidence was slightly higher than black women and 3 times (2.61 to 3.66) the rate in white women (31.9 (27.5 to 36.2) vs 28.6 (25.7 to 31.6) vs 11.3 (10.2 to 12.3)). In normal weight (BMI <25 kg/m 2), diabetes incidence adjusted for age was 2.9 times higher (2.09 to 4.28) in South Asian men, and 5.3 times (3.64 to 7.54) in South Asian women than in white women. Conclusions South Asian adults have lower BMI and are less insulin resistant than US blacks and whites, but have higher diabetes incidence than US whites, especially in subgroups without obesity. Factors other than insulin resistance (ie, insulin secretion) may play an important role in the natural history of diabetes in South Asians.

Introduction South Asians (SA) and Pima Indians have high prevalence of diabetes but differ markedly in body size. We hypothesize that young SA will have higher diabetes incidence than Pima Indians at comparable body mass index (BMI) levels. Research design and methods We used prospective cohort data to estimate age-specific, sex, and BMI-specific diabetes incidence in SA aged 20-44 years living in India and Pakistan from the Center for Cardiometabolic Risk Reduction in South Asia Study (n=6676), and compared with Pima Indians, from Pima Indian Study (n=1852). Results At baseline, SA were considerably less obese than Pima Indians (BMI (kg/m 2): 24.4 vs 33.8; waist circumference (cm): 82.5 vs 107.0). Age-standardized diabetes incidence (cases/1000 person-years, 95% CI) was lower in SA than in Pima Indians (men: 14.2, 12.2-16.2 vs 37.3, 31.8-42.8; women: 14.8, 13.0-16.5 vs 46.1, 41.2-51.1). Risk of incident diabetes among 20-24-year-old Pima men and women was six times (relative risk (RR), 95% CI: 6.04, 3.30 to 12.0) and seven times (RR, 95% CI: 7.64, 3.73 to 18.2) higher as compared with SA men and women, respectively. In those with BMI <25 kg/m 2, however, the risk of diabetes was over five times in SA men than in Pima Indian men. Among those with BMI ≥30 kg/m 2, diabetes incidence in SA men was nearly as high as in Pima men. SA and Pima Indians had similar magnitude of association between age, sex, BMI, and insulin secretion with diabetes. The effect of family history was larger in SA, whereas that of insulin resistance was larger in Pima Indians Conclusions In the background of relatively low insulin resistance, higher diabetes incidence in SA is driven by poor insulin secretion in SA men. The findings call for research to improve insulin secretion in early natural history of diabetes.

Introduction We conducted a systematic review and meta-analysis to evaluate the updated evidence regarding prediabetes for predicting mortality, macrovascular and microvascular outcomes. Research design and methods We identified English language studies from MEDLINE, PubMed, OVID and Cochrane database indexed from inception to January 31, 2020. Paired reviewers independently identified 106 prospective studies, comprising nearly 1.85 million people, from 27 countries. Primary outcomes were all-cause mortality (ACM), cardiovascular mortality (CVDM), cardiovascular disease (CVD), coronary heart disease (CHD) and stroke. Secondary outcomes were heart failure, chronic kidney disease (CKD) and retinopathy. Results Impaired glucose tolerance was associated with ACM; HR 1.19, 95% CI (1.15 to 1.24), CVDM; HR 1.21, 95% CI (1.10 to 1.32), CVD; HR 1.18, 95% CI (1.11 to 1.26), CHD; HR; 1.13, 95% CI (1.05 to 1.21) and stroke; HR 1.24, 95% CI (1.06 to 1.45). Impaired fasting glucose (IFG) 110-125 mg/dL was associated with ACM; HR 1.17, 95% CI (1.13 to 1.22), CVDM; HR 1.20, 95% CI (1.09 to 1.33), CVD; HR 1.21, 95% CI (1.09 to 1.33), CHD; HR; 1.14, 95% CI (1.06 to 1.22) and stroke; HR 1.22, 95% CI (1.07 to 1.40). IFG 100-125 mg/dL was associated with ACM; HR 1.11, 95% CI (1.04 to 1.19), CVDM; HR 1.14, 95% CI (1.03 to 1.25), CVD; HR 1.15, 95% CI (1.05 to 1.25), CHD HR; 1.10, 95% CI (1.02 to 1.19) and CKD; HR; 1.09, 95% CI (1.01 to 1.18). Glycosylated hemoglobin A1c (HbA1c) 6.0%-6.4% was associated with ACM; HR 1.30, 95% CI (1.03 to 1.66), CVD; HR 1.32, 95% CI (1.00 to 1.73) and CKD; HR 1.50, 95% CI (1.32 to 1.70). HbA1c 5.7%-6.4% was associated with CVD HR 1.15, 95% CI (1.02 to 1.30), CHD; HR 1.28, 95% CI (1.13 to 1.46), stroke; HR 1.23, 95% CI (1.04 to 1.46) and CKD; HR 1.32, 95% CI (1.16 to 1.50). Conclusion Prediabetes is an elevated risk state for macrovascular and microvascular outcomes. The prevention and management of prediabetes should be considered.