Incremental risk of developing type 2 diabetes mellitus (T2D) starts at low Body Mass Index (BMI) in Asian Indians: Analysis from India Heart Watch (IHW).

Menstrual cycle characteristics and risk of coronary heart disease and type 2 diabetes

In 2009, President Obama signed an Executive Order calling for strategies to improve the health of Asian Americans and to seek data on the health disparities in Asian American subgroups.1 Data on Asian American subgroups are scarce and many health disparities remain unknown. The purpose of this Advisory is to highlight the gaps in existing research on cardiovascular disease (CVD) among Asian Americans, and to serve as a call to action on behalf of the American Heart Association to address these areas of need. Asian Americans are the fastest growing racial/ethnic group in the United States, representing 25% of all foreign-born people in the United States.2 They are projected to reach nearly 34 million by 2050.3 Several major Federal surveys (eg, the American Community Survey, the National Health Interview Survey, and the Behavioral Risk Factor Surveillance Survey) only recently started to classify Asian Americans into 7 subgroups: Asian Indian, Chinese, Filipino, Korean, Japanese, Vietnamese, and Other Asian. The first six of these subgroups together constitute >90% of Asian Americans in the United States.4 Although some data are available on Asian subgroups from these major federal surveys, in general, these data are not available for public use because of the privacy concerns resulting from the small sample sizes within subgroups. This situation limits their utility for health-related research. Because health surveys and questionnaires almost universally combine persons of Asian ancestry into a single group, the heterogeneity within this classification is masked. Socioeconomic and cultural factors have been found to be associated with CVD and its risk factors, which is why it is important to understand these differences among Asian subgroups. The Table shows the number of persons in each group based on the most recent US Census data available (American Community Survey, 2008), with the recognition that …

The Genetics of Type 2 Diabetes in Youth: Where We Are and the Road Ahead

Background. Type-2 diabetes (T2D) is 2– 4 fold more common amongst Indian Asians than North American and European whites, and is a major contributor to two-fold higher cardiovascular disease mortality in Asians. We investigated whether genetic variation in the validated T2D genes, contributes to the increased risk of T2D amongst Indian Asians, compared to European whites. Methods. We examined the association of genetic variants in the 16 validated T2D genes with T2D amongst 9,776 Indian Asian and 4,407 European white men and women, aged 35–75 years, participating in the London Life Sciences Prospective Population (LOLIPOP) study. Genotyping was performed by competitive allele-specific PCR (KASPar). Results. Indian Asians had higher T2D prevalence (20.9% vs 8.7%, P<0.001), despite lower age (50.3±10.9 vs 52.1±11.6, P<0.001) and body mass index (26.9±4.1 vs 27.6±4.7, P<0.001), compared to Europeans. Genotyping confirmed association of WFS1, SLC30A8, PPARG, IGF2BP2, TCF7L2, JAZF1, CDKN2A/B, HHEX/IDE and FTO with T2D in both populations (P<0.05). Associations of CDKAL1 , KCNJ11, THADA, CDC123-CAMK1D, ADAMTS9, TSPAN8-LGR5 or NOTCH2 with T2D did not reach statistical significance. SNP risk allele frequency was higher for six, but lower for nine, in Indian Asians compared to Europeans. In regression analysis, risk of T2D remained 3.6 (95%CI 3.2– 4.1, P<0.001) fold higher amongst Indian Asians compared to Europeans, despite adjustment for age, body mass index and known genetic factors. Discussion. Known genetic variants show similar association with T2D, and have similar risk allele frequencies, amongst Indian Asians and Europeans. These genetic factors do not account for the three-fold increased risk of T2D amongst Indian Asians.

Background: Recently, a dietary index reflecting adherence to the 2017 French food-based dietary guidelines, the Programme National Nutrition Santé - guidelines score 2 (PNNS-GS2), has been developed, but evidence on its level of adherence and incident type 2 diabetes (T2D) risk is limited. Objective: We aimed to investigate the association between adherence to the simplified PNNS-GS2 (sPNNS-GS2) and the risk of incident T2D in a French cohort of women. Methods: Between 1993 and 2014, 71,450 women aged over 18 years were examined, and thereafter followed up for the occurrence of T2D within the E3N-EPIC prospective cohort. Dietary data were collected at baseline via a food frequency questionnaire, and the sPNNS-GS2 was derived for each participant. Multivariable Cox regression models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) of T2D for continuous and quintile groups of the sPNNS-GS2. Effect modification by body mass index (BMI) and mediation by BMI and waist-hip ratio (WHR) were explored. Results: The mean age was 52.9 years (SD 6.7). During a mean follow-up of 19 years, 3679 incident T2D cases were identified and validated. There was a linear association between adherence to sPNNS-GS2 and T2D risk (P non-linear = 0.85). In the fully adjusted model, each 1-SD increase in the sPNNS-GS2 was associated with a 8% decrease risk of T2D [HR (95% CI), 0.92 (0.89, 0.95)]. Compared to those with the lowest adherence (first quintile), the third [HR (95% CI), 0.91 (0.82, 1.00)] up to the fifth quintile group [HR (95% CI), 0.79 (0.71, 0.88)] had a lower T2D risk. There was a sPNNS-GS2 x BMI interaction on T2D risk (P interaction < 0.01) but not with WHR. The overall association was partly mediated by BMI (18%) and WHR (59%). Conclusion: Higher adherence to the 2017 French food-based dietary guidelines was associated with a lower risk of T2D in women. Furthermore, our mediation analysis suggests that the lower risk of T2D in women associated with adherence to the sPNNS-GS2 is partly mediated by obesity measured by BMI or WHR.

Egg consumption and risk of incident type 2 diabetes in men: the Kuopio Ischaemic Heart Disease Risk Factor Study

Background: A number of individual metabolites have been identified for their relationship with type 2 diabetes (T2D) risk. We sought to evaluate a pattern of T2D metabolites to estimate the collective impact of these markers on elevating the risk of progression to T2D among high risk women with a history of gestational diabetes mellitus (GDM). Methods: We conducted a prospective nested case-control study among women with a history of GDM in the Nurses’ Health Study II longitudinal cohort. Three panels of plasma metabolites were assayed via liquid chromatography tandem mass spectroscopy among 175 T2D cases and 175 controls, matched for age and fasting status at blood draw in 1997-1999. Incident type 2 diabetes cases occurred a median of 7 years after blood collection (range 1-15 years). Based on the published literature, we identified 38 metabolites associated with T2D and available among our measured panels, including branched-chain and other amino acids, lipids, and others. Metabolite levels were log-transformed and standardized. We derived a T2D MET SCORE, summing across the points corresponding to individuals’ assigned quintile level for each of the 38 metabolites. We estimated the odds ratios (OR) and 95% confidence intervals (CI) for the association of the T2D MET SCORE with incident T2D risk using multivariable conditional logistic regression models, adjusted for age, fasting status, body mass index (BMI), physical activity, and other established T2D risk factors. Results: Cases and controls were on average 43 years at blood draw with a mean of BMI 28.6 kg/m 2 . In the model adjusted for age and fasting status, the T2D MET SCORE was significantly associated with a step-wise increase in T2D risk across quartiles (Q1: [reference]; Q2: OR=2.5 CI=1.2, 5.6; Q3: OR=7.0 CI=3.2, 15.2; Q4: OR=10.9 CI=4.7, 24.9). Adjusting for BMI and other risk factors attenuated the relationship, although the score remained significantly associated with T2D risk (Q4 vs. Q1: OR=7.2 CI=2.5, 20.3). The T2D MET SCORE was associated with T2D risk among both obese and non-obese women (p for interaction=0.4). A BCAA sub-score (3 metabolites) and a lipid sub-score (16 metabolites) were also positively associated with T2D risk (BCAA Q4 vs. Q1: OR=3.5 CI=1.4, 8.8; lipids Q4 vs. Q1: OR=3.6 CI=1.4, 9.1). Conclusions: A pattern of high-risk circulating metabolites is significantly associated with progression from GDM to type 2 diabetes later in life.

Graves' disease (GD) is an autoimmune disease associated with an increased incidence of other autoimmune diseases. To investigate the causality between GD and Diabetes mellitus (DM), we designed bidirectional two-sample Mendelian randomization (MR) and multivariable MR (MVMR) studies. Single-nucleotide polymorphisms (SNPs) associated with GD, thyroid peroxidase (TPO), thyroglobulin (Tg), thyroid-stimulating hormone (TSH), type 1 diabetes (T1D), and type 2 diabetes (T2D) were obtained from the IEU Open GWAS and FinnGen biobank databases. For the forward MR study, we used GD (sample size = 458,620) as the exposure and T1D (sample size = 520,580) and T2D (sample size = 211,766) as the outcomes. Next, high risk of T1D and T2D were used as exposure variables, and GD was used as the outcome variable for the reverse MR analysis. Finally, MVMR analysis was conducted to investigate the probable relationship between DM and indicators for thyroid function like TPO, Tg, and TSH. The inverse variance weighting (IVW) was used as the main method. Finally, the heterogeneity and sensitivity were assessed. There were 27, 88, and 55 SNPs associated with GD, T1D, and T2D, respectively. A significant causal connection between higher genetic liability of GD and the risk of T2D (OR [95% CI] = 1.059 [1.025-1.095], P = 5.53e-04) was found in the forward MR analysis. Comparatively, the significant causal relationship between higher genetic liability of GD and the risk of T1D was not demonstrated (OR [95% CI] = 0.998[0.927,1.074], P=0.949). However, reverse MR suggested that there was a genetic susceptibility to T1D that increased the likelihood of developing GD (OR [95% CI] = 1.173[1.117,1.231], P = 1.913e-10), while T2D did not (OR [95% CI] = 0.963 [0.870-1.066], P = 0.468). Furthermore, there was inadequate evidence to suggest that abnormal TSH, TPO, and Tg levels increase the risk of incident T1D or T2D in individuals with GD. MVMR revealed no causal relationship among Tg, TSH, TPO, T1D, or T2D. There was no increased risk of T1D with an increase in genetic susceptibility to GD, although higher genetic susceptibility to T1D has been shown to be associated with increased risk of developing GD. A unidirectional causal relationship between the genetic liability for GD and increased risk of T2D was observed using MR analyses. MVMR analysis showed no statistically relevant causality between the genetic liability for TSH, TPO, or Tg and the risk of either T1D or T2D.

Timing of inter‐generational prevention of adiposity and type 2 diabetes

Background: Increasing evidence supports a biologically plausible association between delayed conception and metabolic dysfunction, including insulin resistance and inflammation; however, few studies have assessed whether infertility is associated with metabolic diseases such as type 2 diabetes (T2D) later in life. Objective: We prospectively evaluated the association between a history of infertility and T2D risk in a large cohort of women. Methods: Participants of the Nurses’ Health Study II self-reported their infertility status (>12 months attempting a pregnancy), lifestyle characteristics, and several health-related outcomes, via biennial questionnaires (1989-2011). Those reporting infertility were asked to cite the clinical reason(s), if known. Exposure status was updated every two years and carried forward to represent “ever”. Cox proportional hazards models estimated the relative risk (HR) and 95% confidence interval (CI) comparing participants with a history of infertility versus none. Multivariable models adjusted for age, body mass index (BMI), physical activity, healthful dietary pattern score, smoking, alcohol consumption, and several other lifestyle factors. Results: Participants (N=115,750) were on average 35 years old (range 25-44) with a BMI of 24.1 (SD=5.0) at baseline, with 91.7% Caucasian. Twenty-one percent (n=24,118) reported a history of infertility at baseline or follow-up. Incident T2D was reported in 5,414 participants during follow-up (2.6 cases/1,000 person-years). Women with a history of infertility had a significant 21% greater risk of T2D compared to women without infertility after adjusting for several T2D risk factors (multivariable HR=1.21, CI=1.14, 1.29). Infertility due to ovulation disorders was associated with a 47% greater risk of T2D (HR=1.47, CI=1.33, 1.64), and tubal blockage with a 32% greater risk (HR=1.32, CI=1.09, 1.61), compared to no infertility. Other reasons for infertility were not associated with T2D risk, including cervical mucus disorder (HR=1.09, CI=0.80, 1.48), male factor (HR=1.13, CI=0.96, 1.32), and “other” (HR=1.08, CI=0.90, 1.28). Tests for interaction did not indicate significant effect modification across BMI categories for total infertility (BMI<25: HR=1.34, CI=1.03, 1.74; BMI 25-29: HR=1.38, CI=1.18, 1.60; BMI 30+: HR=1.15, CI=1.07, 1.34; p-interaction=0.13). Effect modification by BMI category was suggested for infertility due to ovulation disorders (BMI<25: HR=2.14, CI=1.58, 3.67; BMI 25-29: HR=1.43, CI=1.08, 1.89; BMI 30+: HR=1.35, CI=1.20, 1.52; p-interaction=0.06). Conclusions: Among women, a history of infertility is significantly associated with T2D later in life, specifically infertility due to ovulation disorders and tubal blockage.

Fat-rich diets are involved in many disorders such as obesity and type 2 diabetes (T2D). The Pro12Ala variant of peroxisome proliferator-activated receptor-γ (PPARγ) is known to modulate body mass index (BMI) and T2D risk. Our aim was to study the interaction effect between PPARγ gene (PPARG) polymorphisms Pro12Ala and 1431C>T and fat intake on incident T2D and BMI in a 9-year prospective cohort drawn from the French general population, the D.E.S.I.R. (Data from an Epidemiological Study on the Insulin Resistance Syndrome) study (n=4676). Nutritional intake was assessed by a food frequency self-questionnaire completed by each participant. Statistical analyses included logistic regression, analysis of covariance and haplotype analysis, with adjustment for confounding variables. A high fat consumption (the third sex-specific tertile of fat intake, as a percentage of energy intake) was associated with an increased T2D risk among ProPro and CC homozygotes (P(interaction)=0.05, odds ratio (OR) (95% confidence interval (95% CI))=1.73 (1.19-2.52) P=0.004 and OR=1.85 (1.27-2.71) P=0.001, respectively) but not in Ala and T carriers. There was a significant interaction effect between Pro12Ala and 1431C>T on BMI (P(interaction)=0.004); Ala was associated with lower BMI in CC homozygotes and with higher BMI in T carriers while the opposite was found for ProPro. There was also an interaction effect between Pro12Ala and dietary fat intake on BMI (P(interaction)=0.02); AlaAla individuals had a higher BMI than Pro carriers among high fat consumers (27.1 ± 1.0 versus 24.9 ± 0.1 for AlaAla and Pro+, respectively). There was no interaction effect between the 1431C>T single-nucleotide polymorphism and fat intake on BMI. Our results indicate strong genetic and nutritional interaction effects on BMI and T2D risk at the PPARG locus in a general population.

Background:The EAT-Lancet Commission has promulgated a sustainable dietary guideline and recommended that it was designed to improve the human health and support environmental sustainability.Objective:This research was designed to explore the association between this healthy diet pattern (EAT-Lancet diet pattern, EAT-LDP) and risk of type 2 diabetes (T2D).Methods:Between 2006 and 2010, a total of 59,849 participants from the UK Biobank without diabetes, cardiovascular disease, or cancers were included at baseline. The EAT-LDP score was constructed on the sum of 14 food components and then categorized into three tertiles. Multivariable Cox proportional hazards regression models were conducted to explore the association between EAT-LDP score and the risk of incident T2D. A mediation analysis was also implemented to disentangle the role of body mass index (BMI) and waist circumference in the relationship between EAT-LDP score and T2D.Results:During a median follow-up of 10 years, 2,461 incident T2D cases were recorded. In analyses that compared tertile 3 of the EAT-LDP score (highest) with tertile 1 (lowest), the hazard ratio (HR) for T2D was 0.81 (95% CI: 0.72–0.90) after adjusting for sociodemographic status and health-related factors. Participants who reported a one-point increase in the diet score were associated with a 6% decrease in risk of T2D (HR: 0.94, 95% CI: 0.91–0.97). A significant indirect association was observed between the EAT-LDP score and T2D (β: 0.66, 95% CI: 0.65–0.67), indicating that 44% of the association of EAT-LDP score with T2D was mediated by BMI. Additionally, 40% of the association of EAT-LDP score with T2D was mediated by waist circumference was also observed.Conclusions:Our findings indicate that a higher adherence to EAT-LDP contributes to lower risk of T2D. Further independent validation is needed to be conducted before applying the EAT-LDP to inform dietary guidelines.

Health hazards of obesity have been recognized for centuries, appearing, for example, in writings attributed to Hippocrates. From the later decades of the 20th century through the present, there have been numerous epidemiological studies of the relationship between excess weight and the total, or all-cause, mortality rate,1 a critical cumulative measure of the public health impact of any health condition. Using body mass index (BMI), an indicator of relative weight for height (weight [kg]/height [m]2) and a frequently used surrogate for assessment of excess body fat, these studies have found linear, U-shaped, or J-shaped relationships between total mortality and BMI. That is, in some studies, both the thin and the obese were more likely to die than those in between. There is, however, always a point at which increasing BMI is associated with increasing mortality risk, but the BMI at which this occurs varies across studies and populations.2 Currently,3 overweight in adults is defined as a BMI of 25.0 to <30.0 kg/m2 and obesity as a BMI of ≥30.0 kg/m2 (Table 1). A number of studies have found no significant relationship between BMI in the overweight range and mortality rate4 and have shown the nadir of mortality risk to be in the overweight range. In particular, commentaries in both the lay press5–7 and scientific literature2,8,9 subsequent to recent reports from National Health and Nutrition Examination Surveys (NHANES)10,11 have highlighted the confusion and controversy regarding this issue. Some have interpreted the recent data to mean that overweight is not detrimental to health and is not in itself a public health concern and that drawing attention to the need for weight loss in this range will have negative effects on the health and well-being of the general population.8 Others have argued …

Introduction: Given its role in ovarian follicle development, circulating anti-Müllerian hormone (AMH) is correlated with timing of menopause. Accordingly, women with higher AMH levels become menopausal at a higher age. Previous research suggests that a higher age at menopause is associated with a decreased risk of type 2 diabetes (T2D). In contrast, AMH levels are increased in women with polycystic ovary syndrome (PCOS), who have a higher risk of insulin resistance and T2D than women without PCOS. However, it is not clear yet whether AMH actually plays a role in the development of T2D. We aimed to investigate whether plasma AMH levels and age-related AMH trajectories are associated with risk of T2D in women. Hypothesis: Higher age-specific plasma AMH levels are associated with a decreased risk of T2D. Methods: We analyzed longitudinal data from 3104 female participants, aged 20-60 years at recruitment, in the population-based Doetinchem Cohort Study. In total, we analyzed 12460 plasma AMH measurements. We calculated age-specific AMH tertiles, to account for the strong AMH-age correlation. Cox Proportional hazards models adjusted for known risk factors for diabetes were used to assess the relation between age-specific AMH tertiles and T2D. We applied linear mixed models to compare age-related AMH trajectories between T2D cases and non-cases. Results: After a median follow-up of 20 years, 163 incident T2D cases were identified. Higher age-specific AMH levels were associated with a lower risk of T2D (hazard ratio (HR) T2vsT1 = 0.77, 95%CI: 0.53-1.11; HR T3vsT1 =0.62, 95%CI: 0.40-0.94; p for trend = 0.02). These findings were supported by predicted AMH trajectories, which suggested that plasma AMH levels were lower at younger ages and declined at a slower rate in women who were diagnosed with T2D compared to women who were not. However, differences in trajectories between T2D cases and non-cases were not statistically significant. Conclusions: We observed that women with higher age-specific AMH levels were at a lower risk of T2D. In addition, our longitudinal analyses may suggest that AMH is lower in women who develop T2D compared to women who do not. These findings are in line with previous studies that observed that a higher age at menopause was associated with a decreased risk of T2D.

TIGER: The gene expression regulatory variation landscape of human pancreatic islets.