Analysis of 32 common susceptibility genetic variants and their combined effect in predicting risk of Type 2 diabetes and related traits in Indians.Diabet Med 2012; 29(1):121-7DM
Recent genome-wide association studies have identified several Type 2 diabetes-related loci. We investigated the effect of susceptibility genetic variants, individually, together and in combination with conventional risk factors, on Type 2 diabetes and diabetes-related traits in Indians.
We genotyped 33 variants in 1808 Indian patients and 1549 control subjects and performed association analyses with Type 2 diabetes and related traits using an additive model for individual variant and for genetic risk score based on 32 polymorphisms. The discriminatory value of genetic risk over conventional risk factors was analysed using receiver-operating characteristics curve analysis.
The allelic odds ratio ranged from 1.01 (95% CI 0.85-1.19) to 1.66 (95% CI 1.32-2.01) for single-variant analyses. Although, only 16 variants had significant odds ratios, the direction of association for others was similar to earlier reports. The odds ratio for Type 2 diabetes at each genetic risk score point was 1.11 (95% CI 1.09-1.14; P = 5.6 × 10(-17)) and individuals with extremes of genetic risk score (≥ 29.0 and ≤ 17.0) had a 7.5-fold difference in risk of Type 2 diabetes. The discrimination rate between control subjects and patients improved marginally on addition of genetic risk score to conventional risk factors (area under curve = 0.959 and 0.963, respectively; P = 0.001). Of all the quantitative traits analysed, MC4R variants showed strong association with BMI (P = 4.1 × 10(-4)), fat mass per cent (P = 2.4 × 10(-4)) and other obesity-related traits, including waist circumference and hip circumference (P = 2.0 × 10(-3) for both), as well as insulin resistance (P =0.02).
We replicated the association of well-established common variants with Type 2 diabetes in Indians and observed a similar association as reported in Western populations. Combined analysis of 32 variants aids identification of subgroups at increased risk of Type 2 diabetes, but adds only a minor advantage over conventional risk factors.