Obesity is a serious international health problem that increases the risk of several common diseases. The genetic factors predisposing to obesity are poorly understood. A genome-wide search for type 2 diabetes–susceptibility genes identified a common variant in the FTO (fat mass and obesity associated) gene that predisposes to diabetes through an effect on body mass index (BMI). An additive association of the variant with BMI was replicated in 13 cohorts with 38,759 participants. The 16% of adults who are homozygous for the risk allele weighed about 3 kilograms more and had 1.67-fold increased odds of obesity when compared with those not inheriting a risk allele. This association was observed from age 7 years upward and reflects a specific increase in fat mass.

Circulating glucose levels are tightly regulated. To identify novel glycemic loci, we performed meta-analyses of 21 genome-wide associations studies informative for fasting glucose (FG), fasting insulin (FI) and indices of β-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 non-diabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with FG/HOMA-B and two associated with FI/HOMA-IR. These include nine new FG loci (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and FAM148B) and one influencing FI/HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB/TMEM195 with type 2 diabetes (T2D). Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify T2D risk loci, as well as loci that elevate FG modestly, but do not cause overt diabetes.

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explain one-fifth of heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ~2,000, ~3,700 and ~9,500 SNPs explained ~21%, ~24% and ~29% of phenotypic variance. Furthermore, all common variants together captured the majority (60%) of heritability. The 697 variants clustered in 423 loci enriched for genes, pathways, and tissue-types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin, and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.

The molecular mechanisms involved in the development of type 2 diabetes are poorly understood. Starting from genome-wide genotype data for 1924 diabetic cases and 2938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3757 additional cases and 5346 controls and by integration of our findings with equivalent data from other international consortia. We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B, and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8. Our findings provide insight into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect. The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes.

By combining genome-wide association data from 8,130 individuals with type 2 diabetes (T2D) and 38,987 controls of European descent and following up previously unidentified meta-analysis signals in a further 34,412 cases and 59,925 controls, we identified 12 new T2D association signals with combinedP < 5 × 10−8. These include a second independent signal at the KCNQ1 locus; the first report, to our knowledge, of an X-chromosomal association (near DUSP9); and a further instance of overlap between loci implicated in monogenic and multifactorial forms of diabetes (at HNF1A). The identified loci affect both beta-cell function and insulin action, and, overall, T2D association signals show evidence of enrichment for genes involved in cell cycle regulation. We also show that a high proportion of T2D susceptibility loci harbor independent association signals influencing apparently unrelated complex traits.

Genome-wide association (GWA) studies have identified multiple new genomic loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D)1-11. Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to discover loci at which common alleles have modest effects, we performed meta-analysis of three T2D GWA scans encompassing 10,128 individuals of European-descent and ~2.2 million SNPs (directly genotyped and imputed). Replication testing was performed in an independent sample with an effective sample size of up to 53,975. At least six new loci with robust evidence for association were detected, including the JAZF1 (p=5.0×10 −14 ), CDC123/CAMK1D (p=1.2×10 −10 ), TSPAN8/ LGR5 (p=1.1×10 −9 ), THADA (p=1.1×10 −9 ), ADAMTS9 (p=1.2×10 −8 ), and NOTCH2 (p=4.1×10 −8 ) gene regions. The large number of loci with relatively small effects indicates the value of large discovery and follow-up samples in identifying additional clues about the inherited basis of T2D.Genome-wide association studies are unbiased by previous hypotheses concerning candidate genes and pathways, but challenged by the modest effect sizes of individual common susceptibility variants and the need for stringent statistical thresholds. For example, the largest allelic odds ratio of any established common variant for T2D is ~1.35 (TCF7L2), with the nine other validated associations to common variants (excluding FTO, which has its primary effect through obesity) having allelic odds ratios between 1.1 and 1. 21-6,11,12. To augment power to detect additional loci of similar and/or smaller effect, we increased sample size by combining three previously published GWA studies (Diabetes Genetics Initiative [DGI], Finland-United States Investigation of NIDDM Genetics [FUSION], and Wellcome Trust Case Control Consortium [WTCCC])1-4, and extended SNP coverage by imputing untyped SNPs based on patterns of haplotype variation from the HapMap dataset13 (Table 1).We started with a set of genotyped autosomal SNPs that passed quality control (QC) filters in each study: in WTCCC, 393,143 SNPs from the Affymetrix 500k chip (MAF>0.01; 1,924 cases and 2,938 population-based controls from the Wellcome Trust Case Control Consortium3,4); in DGI, 378,860 Using these directly measured and imputed genotypes, we tested for association of each SNP with T2D in each study separately, corrected each study for residual population stratification, cryptic relatedness or technical artifacts using genomic control, and then combined these results in a genome-wide meta-analysis across a total of 10,128 samples (4,549 cases, 5,579 controls) (Methods; Supplementary Methods). We calculated that this sample size provides reasonable power to detect additional variants with properties similar to those previously identified by less formal data combination efforts1,2,4 (Supplementary Table 2). Unless otherwise indicated, results presented are derived from...

To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis.