Type 1 Diabetes Genetic Risk in 109,954 Veterans With Adult-Onset Diabetes: The Million Veteran Program (MVP).

OBJECTIVE: To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates. RESEARCH DESIGN AND METHODS: Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%). RESULTS: T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and their characteristics resembled those of individuals with T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low-risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low GRS 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001. CONCLUSIONS: Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble those of people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates.

Construct validity of the 12-item Short Form Health Survey (SF-12) version 2 and the impact of lifestyle modifications on the health-related quality of life among Indian adults with prediabetes: results from the D-CLIP trial.

PURPOSE: This study aimed to validate the factor structure of the 12-item Short-Form (SF-12) health-related quality of life (HRQOL) survey for Indian adults and assess the impact of lifestyle modification on the SF-12 of Indian adults with prediabetes. METHODS: To validate the context-specific construct of the SF-12, two-factor confirmatory factor analysis (CFA) was performed using data from 1285 adults residing in Chennai, India, who screened for the Diabetes Community Lifestyle Improvement Program (D-CLIP). D-CLIP was a randomized controlled trial of 578 participants with prediabetes (283 treatment, 293 control), focusing on the effect of lifestyle modifications on the prevention of diabetes. Physical and mental component scores (PCS and MCS) were computed by using CFA standardized factor loadings. Multiple linear regression was subsequently conducted to estimate the effect of lifestyle modification on post-study changes of PCS and MCS among D-CLIP participants. RESULTS: Cronbach's alpha and CFA fit indices demonstrated acceptable reliability and model fit of the SF-12 for Indian adults. The intervention group showed greater mean change in PCS after study participation compared to the controls (1.63 ± 0.82, p = 0.046); no significant difference was observed for MCS between two groups (1.00 ± 0.85, p = 0.242). CONCLUSION: The study confirmed that the SF-12 is suitable for assessing the physical and mental health dimensions of HRQOL for Indian adults. Our findings suggest that the benefits of diabetes prevention lifestyle modification strategies may primarily enhance the physical well-being of adults with prediabetes. Further studies validating the SF-12 in a broader Asian Indian population are needed. TRIAL REGISTRATION: Clinicaltrials.gov, NCT01283308.

Pancreatic Beta Cell Function in Infants Varies by Maternal Weight.

The Asian Indian Beta Cell function (ABCs) in Infants Study examined the associations of maternal weight on infant pancreatic beta cell function across 7 months postpartum. Pregnant women aged 18-35 years were recruited in Hyderabad, India. Women were classified by first trimester weight as underweight (UW), BMI < 18.5 kg/m2; normal weight (NW), BMI 18.5-22.9 kg/m2; or overweight (OW), BMI 23.0 through <28.5 kg/m2. At age > 7 months, infants had an oral glucose tolerance test (OGTT, 1.75 g glucose/kg bodyweight) following a 3 h fast. Infant blood samples were assayed for C-peptide and glucose. Infant beta cell function (HOMA2-B; disposition index, DI) and insulin resistance (HOMA2-IR) were compared across maternal weight groups. Mothers (UW n = 63; NW n = 43; OW n = 29) had similar age at delivery and second trimester 50 g glucose challenge test results. Cord HOMA2-B values were 51% greater for IUW (83.5, SD 55.2) and 44% greater for IOW (79.9, SD 60.8) vs. INW (55.4, SD 51.5), forming a U-shaped relationship between maternal weight and HOMA2-B. No qualitative differences in HOMA2-IR were found at birth. However, at 7 months postpartum, HOMA2-IR changed most within IUW (-64% median reduction) and changed the least in IOW (-7% median reduction). At seven months postpartum, DI was higher in IUW vs. the other groups (geometric mean IUW 1.9 SD 2.5; INW 1.3 SD 2.6 or vs. IOW mean 1.2 SD 3.7), reflecting a +49% difference in DI. Evidence from this study illustrates adaptations in the pancreatic functional response of infants associated with the maternal nutritional environment.

Natural History of Type 2 Diabetes in Indians: Time to Progression.

OBJECTIVE: To describe the natural history of diabetes in Indians. RESEARCH DESIGN AND METHODS: Data are from participants older than 20 years in the Centre for Cardiometabolic Risk Reduction in South Asia longitudinal study. Glycemic states were defined per American Diabetes Association criteria. Markov models were used to estimate annual transition probabilities and sojourn time through states. RESULTS: Among 2,714 diabetes-free participants, 641 had isolated impaired fasting glucose (iIFG), and 341 had impaired glucose tolerance (IGT). The annual transition to diabetes for those with IGT was 13.9% (95% CI 12.0, 15.9) versus 8.6% (7.3, 9.8) for iIFG. In the normoglycemia ↔ iIFG → diabetes model, mean sojourn time in normoglycemia was 40.3 (34.6, 48.2) years, and sojourn time in iIFG was 9.7 (8.4, 11.4) years. For the normoglycemia ↔ IGT → diabetes model, mean sojourn time in normoglycemia was 34.5 (29.5, 40.8) years, and sojourn time in IGT was 6.1 (5.3, 7.1) years. CONCLUSIONS: Individuals reside in normoglycemia for 35-40 years; however, progression from prediabetes to diabetes is rapid.

Perceived stress and progression of cardiometabolic risk factors among South Asians with prediabetes in a lifestyle intervention trial.

AIMS: To examine associations between perceived stress and cardiometabolic risk factors in South Asians with prediabetes and assess whether a diabetes prevention program mitigates the impact of stress on cardiometabolic health. METHODS: We conducted a secondary analysis of the Diabetes Community Lifestyle Improvement Program, a lifestyle modification trial for diabetes prevention in India (n = 564). Indicators for cardiometabolic health (weight, waist circumference, blood pressure, glucose, HbA1c, and lipids) were measured at each visit while perceived stress was assessed via questionnaire at baseline. Multivariable linear regression assessed associations between stress and cardiometabolic parameters at baseline and 3-year follow up. RESULTS: At baseline, perceived stress was associated with higher weight (b=0.16; 95% CI: 0.04, 0.29) and waist circumference (b=0.11; 95% CI: 0.01, 0.21) but lower 30-minute postload glucose (b=-0.44; 95% CI: -0.76, -0.14) and LDL cholesterol (b=-0.40; 95% CI: -0.76, -0.03). Over the study period, perceived stress was associated with weight gain (b=0.20; 95% CI: 0.07, 0.33) and increased waist circumference (b=0.14; 95% CI: 0.04, 0.24). Additionally, higher perceived stress was associated with lower HDL cholesterol among the control arm (pinteraction = 0.02). CONCLUSIONS: Baseline stress was associated with negative cardiometabolic risk factor outcomes over time in those with prediabetes.

Evaluation of available risk scores to predict multiple cardiovascular complications for patients with type 2 diabetes mellitus using electronic health records.

Aims: Various cardiovascular risk prediction models have been developed for patients with type 2 diabetes mellitus. Yet few models have been validated externally. We perform a comprehensive validation of existing risk models on a heterogeneous population of patients with type 2 diabetes using secondary analysis of electronic health record data. Methods: Electronic health records of 47,988 patients with type 2 diabetes between 2013 and 2017 were used to validate 16 cardiovascular risk models, including 5 that had not been compared previously, to estimate the 1-year risk of various cardiovascular outcomes. Discrimination and calibration were assessed by the c-statistic and the Hosmer-Lemeshow goodness-of-fit statistic, respectively. Each model was also evaluated based on the missing measurement rate. Sub-analysis was performed to determine the impact of race on discrimination performance. Results: There was limited discrimination (c-statistics ranged from 0.51 to 0.67) across the cardiovascular risk models. Discrimination generally improved when the model was tailored towards the individual outcome. After recalibration of the models, the Hosmer-Lemeshow statistic yielded p-values above 0.05. However, several of the models with the best discrimination relied on measurements that were often imputed (up to 39% missing). Conclusion: No single prediction model achieved the best performance on a full range of cardiovascular endpoints. Moreover, several of the highest-scoring models relied on variables with high missingness frequencies such as HbA1c and cholesterol that necessitated data imputation and may not be as useful in practice. An open-source version of our developed Python package, cvdm, is available for comparisons using other data sources.

Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI.

This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Women's Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p < 1E-7) and 1,238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.

Correction: Blood-derived miRNA levels are not correlated with metabolic or anthropometric parameters in obese pre-diabetic subjects but with systemic inflammation.

[This corrects the article DOI: 10.1371/journal.pone.0263479.].

Potential misclassification of diabetes and prediabetes in the U.S.: Mismatched HbA1c and glucose in NHANES 2005-2016.

AIMS: To assess the prevalence and clinical implications of "mismatches" between HbA1c and glucose levels in the United States across the life course. METHODS: Participants ages 12-79 years from U.S. National Health and Nutrition Examination Survey (NHANES) 2005-2016 without known diagnosis of diabetes and who had a 75 g oral glucose tolerance test were included. Previously undiagnosed diabetes (DM), prediabetes, and normal glucose metabolism (NGM) were defined using American Diabetes Association cut-points. Mismatches were defined by the hemoglobin glycation index (HGI). RESULTS: In 10,361 participants, 5% and 41% had diabetes and prediabetes, respectively, by fasting or 2-hour glucose criteria. By HbA1c criteria, the high HGI tertile consisted of mostly abnormal classification (3% DM, 52% prediabetes) and the low HGI tertile contained mostly normal classification (78% NGM). Across all ages, 15% (weighted: 30 million individuals) had clinically significant mismatches of HGI magnitude ≥+0.5% (i.e., high mismatch) or ≤-0.5% (low mismatch). Mismatch was most common in older adults and non-Hispanic Black participants. CONCLUSIONS: Mismatches of clinically significant magnitude could lead to HbA1c-related misdiagnosis or inappropriate management in up to 30 million Americans. Older adults, non-Hispanic Black individuals, and others with high mismatches may benefit from complementing HbA1c with additional diagnostic and management strategies.

Association of family history of cardiometabolic diseases (CMDs) and individual health behaviours: Analysis of CARRS study from South Asia.

OBJECTIVES: Family history is considered as an important predictor of cardiovascular diseases (CVDs) and diabetes. Available research findings suggest that family history of chronic diseases is associated with perceived risk of disease and adoption of healthy behaviours. We examined the association between family history of cardio-metabolic diseases (CMDs) and healthy behaviours among adults without self-reported CMDs. METHODS: Cross-sectional data of 12,484 adults, without self-reported CMDs, from the baseline survey of Centre for cArdiometabolic Risk Reduction in South-Asia (CARRS) cohort study were analysed. RESULTS: Family history was positively associated with non-smoking and high fruits & vegetables consumption in the age group of 45-64 years and moderate to high physical activity in the age group ≥65 years after adjusting for sex, education, wealth index, city and body mass index. CONCLUSIONS: Understanding perceived risks and cultural or psychological factors related to family history through ethnographic studies may deepen understanding of these associations.

Blood-derived miRNA levels are not correlated with metabolic or anthropometric parameters in obese pre-diabetic subjects but with systemic inflammation.

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.

Associations between DNA methylation and BMI vary by metabolic health status: a potential link to disparate cardiovascular outcomes.

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 ß 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 ß 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.

Association between varying cut-points of intermediate hyperglycemia and risk of mortality, cardiovascular events and chronic kidney disease: a systematic review and meta-analysis.

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.

Incidence and pathophysiology of diabetes in South Asian adults living in India and Pakistan compared with US blacks and whites.

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/m2: 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 ß-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/m2), 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.

Incidence of diabetes in South Asian young adults compared to Pima Indians.

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/m2): 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/m2, however, the risk of diabetes was over five times in SA men than in Pima Indian men. Among those with BMI ≥30 kg/m2, 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.

Epigenome-wide association study of diet quality in the Women's Health Initiative and TwinsUK cohort.

BACKGROUND: Diet quality is a risk factor for chronic disease and mortality. Differential DNA methylation across the epigenome has been associated with chronic disease risk. Whether diet quality is associated with differential methylation is unknown. This study assessed whether diet quality was associated with differential DNA methylation measured across 445 548 loci in the Women's Health Initiative (WHI) and the TwinsUK cohort. DESIGN: The discovery cohort consisted of 4355 women from the WHI. The replication cohort consisted of 571 mono- and dizygotic twins from the TwinsUK cohort. DNA methylation was measured in whole blood using the Illumina Infinium HumanMethylation450 Beadchip. Diet quality was assessed using the Alternative Healthy Eating Index 2010 (AHEI-2010). A meta-analysis, stratified by study cohort, was performed using generalized linear models that regressed methylation on AHEI-2010, adjusting for cell composition, chip number and location, study characteristics, principal components of genetic relatedness, age, smoking status, race/ethnicity and body mass index (BMI). Statistical significance was defined as a false discovery rate < 0.05. Significant sites were tested for replication in the TwinsUK cohort, with significant replication defined by P < 0.05 and a consistent direction. RESULTS: Diet quality was significantly associated with differential DNA methylation at 428 cytosine-phosphate-guanine (CpG) sites in the discovery cohort. A total of 24 CpG sites were consistent with replication in the TwinsUK cohort, more than would be expected by chance (P = 2.7x10-4), with one site replicated in both the blood and adipose tissue (cg16379999 located in the body of SEL1L). CONCLUSIONS: Diet quality was associated with methylation at 24 CpG sites, several of which have been associated with adiposity, inflammation and dysglycaemia. These findings may provide insight into pathways through which diet influences chronic disease.

Cost-effectiveness of a Stepwise Approach vs Standard Care for Diabetes Prevention in India.

Importance: A stepwise approach that includes screening and lifestyle modification followed by the addition of metformin for individuals with high risk of diabetes is recommended to delay progression to diabetes; however, there is scant evidence regarding whether this approach is cost-effective. Objective: To estimate the cost-effectiveness of a stepwise approach in the Diabetes Community Lifestyle Improvement Program. Design, Setting, and Participants: This economic evaluation study included 578 adults with impaired glucose tolerance, impaired fasting glucose, or both. Participants were enrolled in the Diabetes Community Lifestyle Improvement Program, a randomized clinical trial with 3-year follow-up conducted at a diabetes care and research center in Chennai, India. Interventions: The intervention group underwent a 6-month lifestyle modification curriculum plus stepwise addition of metformin; the control group received standard lifestyle advice. Main Outcomes and Measures: Cost, health benefits, and incremental cost-effectiveness ratios (ICERs) were estimated from multipayer (including direct medical costs) and societal (including direct medical and nonmedical costs) perspectives. Costs and ICERs were reported in 2019 Indian rupees (INR) and purchasing power parity-adjusted international dollars (INT $). Results: The mean (SD) age of the 578 participants was 44.4 (9.3) years, and 364 (63.2%) were men. Mean (SD) body mass index was 27.9 (3.7), and the mean (SD) glycated hemoglobin level was 6.0% (0.5). Implementing lifestyle modification and metformin was associated with INR 10 549 (95% CI, INR 10 134-10 964) (INT $803 [95% CI, INT $771-834]) higher direct costs; INR 5194 (95% CI, INR 3187-INR 7201) (INT $395; 95% CI, INT $65-147) higher direct nonmedical costs, an absolute diabetes risk reduction of 10.2% (95% CI, 1.9% to 18.5%), and an incremental gain of 0.099 (95% CI, 0.018 to 0.179) quality-adjusted life-years per participant. From a multipayer perspective (including screening costs), mean ICERs were INR 1912 (INT $145) per 1 percentage point diabetes risk reduction, INR 191 090 (INT $14 539) per diabetes case prevented and/or delayed, and INR 196 960 (INT $14 986) per quality-adjusted life-year gained. In the scenario of a 50% increase or decrease in screening and intervention costs, the mean ICERs varied from INR 855 (INT $65) to INR 2968 (INT $226) per 1 percentage point diabetes risk reduction, from INR 85 495 (INT $6505) to INR 296 681 (INT $22 574) per diabetes case prevented, and from INR 88 121 (INT $6705) to INR 305 798 (INT $23 267) per quality-adjusted life-year gained. Conclusions and Relevance: The findings of this study suggest that a stepwise approach for diabetes prevention is likely to be cost-effective, even if screening costs for identifying high-risk individuals are added.

Clinical utility of 30-min plasma glucose for prediction of type 2 diabetes among people with prediabetes: Ancillary analysis of the diabetes community lifestyle improvement program.

AIMS: To examine the clinical utility of 30-min plasma glucose (30-min-PG) measurement during an oral glucose tolerance (OGTT) in predicting type 2 diabetes (T2DM). RESEARCH DESIGN AND METHODS: Data from a 3-year, randomized, controlled, primary prevention trial among 548 Asian Indians with prediabetes were analyzed. Participants underwent OGTT with PG measurements at fasting, 30-min, and 2-h at baseline and annually until the end of the study. Multivariable Cox regression models were constructed to calculate the risk of developing diabetes based on 30-min-PG levels. Improvement in prediction performance gained by adding an elevated level of 30-min-PG over prediabetic categories was calculated using the area-under-curve (AUC), net-reclassification (NRI), and integrated discrimination improvement (IDI) statistics. RESULTS: At the end of follow-up, 30.4% of individuals had been diagnosed with T2DM by ADA criteria. Based on the maximally selected log-rank statistics, the optimal 30-min-PG cut point for predicting incident T2DM was >182 mg/dl. Multivariable-adjusted Cox regression models showed an independent association between elevated 30-min-PG (>182 mg/dl) and incident diabetes (hazard ratio (95% CI): 1.85 [1.32, 2.59]; Dxy = 0.353, c-statistic = 0.676). The addition of an elevated 30-min-PG (>182 mg/dl) model significantly improved the prediction of diabetes (Δdeviance: -15.4; ΔAUC: 0.11; NRIcontinuous: 0.51; IDI: 0.08) compared with IFG model alone) in individuals with prediabetes. CONCLUSION: In prediabetic individuals, baseline 30-min-PG independently predicted T2DM and significantly improved reclassification and discrimination. Therefore, 30-min-PG should be considered as part of the routine testing in addition to FPG and 2-h-PG for better risk stratification.

Random plasma glucose predicts the diagnosis of diabetes.

AIMS/HYPOTHESIS: Early recognition of those at high risk for diabetes as well as diabetes itself can permit preventive management, but many Americans with diabetes are undiagnosed. We sought to determine whether routinely available outpatient random plasma glucose (RPG) would be useful to facilitate the diagnosis of diabetes. METHODS: Retrospective cohort study of 942,446 U.S. Veterans without diagnosed diabetes, ≥3 RPG in a baseline year, and ≥1 primary care visit/year during 5-year follow-up. The primary outcome was incident diabetes (defined by diagnostic codes and outpatient prescription of a diabetes drug). RESULTS: Over 5 years, 94,599 were diagnosed with diabetes [DIAB] while 847,847 were not [NONDIAB]. Baseline demographics of DIAB and NONDIAB were clinically similar, except DIAB had higher BMI (32 vs. 28 kg/m2) and RPG (150 vs. 107 mg/dl), and were more likely to have Black race (18% vs. 15%), all p<0.001. ROC area for prediction of DIAB diagnosis within 1 year by demographic factors was 0.701, and 0.708 with addition of SBP, non-HDL cholesterol, and smoking. These were significantly less than that for prediction by baseline RPG alone (≥2 RPGs at/above a given level, ROC 0.878, p<0.001), which improved slightly when other factors were added (ROC 0.900, p<0.001). Having ≥2 RPGs ≥115 mg/dl had specificity 77% and sensitivity 87%, and ≥2 RPGs ≥130 mg/dl had specificity 93% and sensitivity 59%. For predicting diagnosis within 3 and 5 years by RPG alone, ROC was reduced but remained substantial (ROC 0.839 and 0.803, respectively). CONCLUSIONS: RPG levels below the diabetes "diagnostic" range (≥200 mg/dl) provide good discrimination for follow-up diagnosis. Use of such levels-obtained opportunistically, during outpatient visits-could signal the need for further testing, allow preventive intervention in high risk individuals before onset of disease, and lead to earlier identification of diabetes.