A Functional Variant of the Dimethylarginine Dimethylaminohydrolase-2 Gene Is Associated with Insulin Sensitivity

Background: Asymmetric dimethylarginine (ADMA) is an endogenous inhibitor of endothelial nitric oxide synthase, which was associated with insulin resistance. Dimethylarginine dimethylaminohydrolase (DDAH) is the major determinant of plasma ADMA. Examining data from the DIAGRAM+ (Diabetes Genetics Replication And Meta-analysis), we identified a variant (rs9267551) in the DDAH2 gene nominally associated with type 2 diabetes (P =3610 25). Methodology/Principal Findings: initially, we assessed the functional impact of rs9267551 in human endothelial cells (HUVECs), observing that the G allele had a lower transcriptional activity resulting in reduced expression of DDAH2 and decreased NO production in primary HUVECs naturally carrying it. We then proceeded to investigate whether this variant is associated with insulin sensitivity in vivo. To this end, two cohorts of nondiabetic subjects of European ancestry were studied. In sample 1 (n = 958) insulin sensitivity was determined by the insulin sensitivity index (ISI), while in sample 2 (n = 527) it was measured with a euglycemic-hyperinsulinemic clamp. In sample 1, carriers of the GG genotype had lower ISI than carriers of the C allele (67633 vs.79644; P = 0.003 after adjusting for age, gender, and BMI). ADMA levels were higher in subjects carrying the GG genotype than in carriers of the C allele (0.6860.14 vs. 0.5760.14 mmol/l; P = 0.04). In sample 2, glucose disposal was lower in GG carriers as compared with C carriers (9.364.1 vs. 11.064.2 mg6Kg 21 free fat mass6min 21; P = 0.009)

Physiologic Characterization of Type 2 Diabetes–Related Loci

For the past two decades, genetics has been widely explored as a tool for unraveling the pathogenesis of diabetes. Many risk alleles for type 2 diabetes and hyperglycemia have been detected in recent years through massive genome-wide association studies and evidence exists that most of these variants influence pancreatic β-cell function. However, risk alleles in five loci seem to have a primary impact on insulin sensitivity. Investigations of more detailed physiologic phenotypes, such as the insulin response to intravenous glucose or the incretion hormones, are now emerging and give indications of more specific pathologic mechanisms for diabetes-related risk variants. Such studies have shed light on the function of some loci but also underlined the complex nature of disease mechanism. In the future, sequencing-based discovery of low-frequency variants with higher impact on intermediate diabetes-related traits is a likely scenario and identification of new pathways involved in type 2 diabetes predisposition will offer opportunities for the development of novel therapeutic and preventative approaches

Predicting glycated hemoglobin levels in the non-diabetic general population:Development and validation of the DIRECT-DETECT prediction model - a DIRECT study

AIMS/HYPOTHESIS: To develop a prediction model that can predict HbA1c levels after six years in the non-diabetic general population, including previously used readily available predictors. METHODS: Data from 5,762 initially non-diabetic subjects from three population-based cohorts (Hoorn Study, Inter99, KORA S4/F4) were combined to predict HbA1c levels at six year follow-up. Using backward selection, age, BMI, waist circumference, use of anti-hypertensive medication, current smoking and parental history of diabetes remained in sex-specific linear regression models. To minimize overfitting of coefficients, we performed internal validation using bootstrapping techniques. Explained variance, discrimination and calibration were assessed using R2, classification tables (comparing highest/lowest 50% HbA1c levels) and calibration graphs. The model was externally validated in 2,765 non-diabetic subjects of the population-based cohort METSIM. RESULTS: At baseline, mean HbA1c level was 5.6% (38 mmol/mol). After a mean follow-up of six years, mean HbA1c level was 5.7% (39 mmol/mol). Calibration graphs showed that predicted HbA1c levels were somewhat underestimated in the Inter99 cohort and overestimated in the Hoorn and KORA cohorts, indicating that the model's intercept should be adjusted for each cohort to improve predictions. Sensitivity and specificity (95% CI) were 55.7% (53.9, 57.5) and 56.9% (55.1, 58.7) respectively, for women, and 54.6% (52.7, 56.5) and 54.3% (52.4, 56.2) for men. External validation showed similar performance in the METSIM cohort. CONCLUSIONS/INTERPRETATION: In the non-diabetic population, our DIRECT-DETECT prediction model, including readily available predictors, has a relatively low explained variance and moderate discriminative performance, but can help to distinguish between future highest and lowest HbA1c levels. Absolute HbA1c values are cohort-dependent

Association analysis of 31 common polymorphisms with type 2 diabetes and its related traits in Indian sib pairs

: AIMS/HYPOTHESIS: Evaluation of the association of 31 common single nucleotide polymorphisms (SNPs) with fasting glucose, fasting insulin, HOMA-beta cell function (HOMA-?), HOMA-insulin resistance (HOMA-IR) and type 2 diabetes in the Indian population. METHODS: We genotyped 3,089 sib pairs recruited in the Indian Migration Study from four cities in India (Lucknow, Nagpur, Hyderabad and Bangalore) for 31 SNPs in 24 genes previously associated with type 2 diabetes in European populations. We conducted within-sib-pair analysis for type 2 diabetes and its related quantitative traits. RESULTS: The risk-allele frequencies of all the SNPs were comparable with those reported in western populations. We demonstrated significant associations of CXCR4 (rs932206), CDKAL1 (rs7756992) and TCF7L2 (rs7903146, rs12255372) with fasting glucose, with ? values of 0.007 (p?=?0.05), 0.01 (p?=?0.01), 0.007 (p?=?0.05), 0.01 (p?=?0.003) and 0.08 (p?=?0.01), respectively. Variants in NOTCH2 (rs10923931), TCF-2 (also known as HNF1B) (rs757210), ADAM30 (rs2641348) and CDKN2A/B (rs10811661) significantly predicted fasting insulin, with ? values of -0.06 (p?=?0.04), 0.05 (p?=?0.05), -0.08 (p?=?0.01) and -0.08 (p?=?0.02), respectively. For HOMA-IR, we detected associations with TCF-2, ADAM30 and CDKN2A/B, with ? values of 0.05 (p?=?0.04), -0.07 (p?=?0.03) and -0.08 (p?=?0.02), respectively. We also found significant associations of ADAM30 (??=?-0.05; p?=?0.01) and CDKN2A/B (??=?-0.05; p?=?0.03) with HOMA-?. THADA variant (rs7578597) was associated with type 2 diabetes (OR 1.5; 95% CI 1.04, 2.22; p?=?0.03). CONCLUSIONS/INTERPRETATION: We validated the association of seven established loci with intermediate traits related to type 2 diabetes in an Indian population using a design resistant to population stratification

Physical activity attenuates the influence of FTO variants on obesity risk: A meta-analysis of 218,166 adults and 19,268 children

Background: The FTO gene harbors the strongest known susceptibility locus for obesity. While many individual studies have suggested that physical activity (PA) may attenuate the effect of FTO on obesity risk, other studies have not been able to confirm this interaction. To confirm or refute unambiguously whether PA attenuates the association of FTO with obesity risk, we meta-analyzed data from 45 studies of adults (n = 218,166) and nine studies of children and adolescents (n = 19,268). Methods and Findings: All studies identified to have data on the FTO rs9939609 variant (or any proxy [r2>0.8]) and PA were invited to participate, regardless of ethnicity or age of the participants. PA was standardized by categorizing it into a dichotomous variable (physically inactive versus active) in each study. Overall, 25% of adults and 13% of children were categorized as inactive. Interaction analyses were performed within each study by including the FTO×PA interaction term in an additive model, adjusting for age and sex. Subsequently, random effects meta-analysis was used to pool the interaction terms. In adults, the minor (A-) allele of rs9939609 increased the odds of obesity by 1.23-fold/allele (95% CI 1.20-1.26), but PA attenuated this effect (pinteraction= 0.001). More specifically, the minor allele of rs9939609 increased the odds of obesity less in the physically active group (odds ratio = 1.22/allele, 95% CI 1.19-1.25) than in the inactive group (odds ratio = 1.30/allele, 95% CI 1.24-1.36). No such interaction was found in children and adolescents. Concl