Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk.

Blood pressure is a heritable trait influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (≥140 mm Hg systolic blood pressure or ≥90 mm Hg diastolic blood pressure). Even small increments in blood pressure are associated with an increased risk of cardiovascular events. This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention.

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-ß), 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 ß 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 ß 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 ß 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 (ß = -0.05; p = 0.01) and CDKN2A/B (ß = -0.05; p = 0.03) with HOMA-ß. 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.

Analysis of 32 common susceptibility genetic variants and their combined effect in predicting risk of Type 2 diabetes and related traits in Indians.

AIMS: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.

Evaluation of seven common lipid associated loci in a large Indian sib pair study.

BACKGROUND: Genome wide association studies (GWAS), mostly in Europeans have identified several common variants as associated with key lipid traits. Replication of these genetic effects in South Asian populations is important since it would suggest wider relevance for these findings. Given the rising prevalence of metabolic disorders and heart disease in the Indian sub-continent, these studies could be of future clinical relevance. METHODS: We studied seven common variants associated with a variety of lipid traits in previous GWASs. The study sample comprised of 3178 sib-pairs recruited as participants for the Indian Migration Study (IMS). Associations with various lipid parameters and quantitative traits were analyzed using the Fulker genetic association model. RESULTS: We replicated five of the 7 main effect associations with p-values ranging from 0.03 to 1.97x10(-7). We identified particularly strong association signals at rs662799 in APOA5 (beta=0.18 s.d, p=1.97 x 10(-7)), rs10503669 in LPL (beta =-0.18 s.d, p=1.0 x 10(-4)) and rs780094 in GCKR (beta=0.11 s.d, p=0.001) loci in relation to triglycerides. In addition, the GCKR variant was also associated with total cholesterol (beta=0.11 s.d, p=3.9x10(-4)). We also replicated the association of rs562338 in APOB (p=0.03) and rs4775041 in LIPC (p=0.007) with LDL-cholesterol and HDL-cholesterol respectively. CONCLUSIONS: We report associations of five loci with various lipid traits with the effect size consistent with the same reported in Europeans. These results indicate an overlap of genetic effects pertaining to lipid traits across the European and Indian populations.

Associations of FTO and MC4R Variants with Obesity Traits in Indians and the Role of Rural/Urban Environment as a Possible Effect Modifier.

Few studies have investigated the association between genetic variation and obesity traits in Indian populations or the role of environmental factors as modifiers of these relationships. In the context of rapid urbanisation, resulting in significant lifestyle changes, understanding the aetiology of obesity is important. We investigated associations of FTO and MC4R variants with obesity traits in 3390 sibling pairs from four Indian cities, most of whom were discordant for current dwelling (rural or urban). The FTO variant rs9939609 predicted increased weight (0.09 Z-scores, 95% CI: 0.03, 0.15) and BMI (0.08 Z-scores, 95% CI: 0.02, 0.14). The MC4R variant rs17782313 was weakly associated with weight and hip circumference (P < .05). There was some indication that the association between FTO and weight was stronger in urban than that in rural dwellers (P for interaction = .03), but no evidence for effect modification by diet or physical activity. Further studies are needed to investigate ways in which urban environment may modify genetic risk of obesity.