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.

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders 1 . They are heritable 2 , 3 and etiologically related 4 , 5 behaviors that have been resistant to gene discovery efforts 6 – 11 . In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures.

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.

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.

Recently, we reported a method to estimate the proportion of phenotypic variance explained by all SNPs from genome-wide association studies, and estimated that half of the heritability for human height was captured by common SNPs. Here we partition genetic variation for height, body mass index (BMI), von Willebrand factor (vWF) and QT interval (QTi) onto chromosomes and chromosome segments, using 586,898 SNPs genotyped on 11,586 unrelated individuals. We estimate that ~45%, ~17%, ~25% and ~21% of variance in height, BMI, vWF and QTi, respectively, can be explained by considering all autosomal SNPs simultaneously, and a further ~0.5–1% by X-chromosome SNPs for height, BMI and vWF. We show that variance explained by each chromosome for height and QTi is proportional to the total gene length on that chromosome. In genome-wide analyses, common SNPs in or near genes explain more variation than SNPs between genes. We propose a novel approach to estimate variation due to cryptic relatedness and population stratification. Our results provide further evidence that a substantial proportion of heritability is accounted for by causal variants in linkage disequilibrium with common SNPs; that height, BMI and QTi are highly polygenic traits; and that the additive variation explained by a part of the genome is approximately proportional to the total length of DNA contained within genes therein.

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS) including 26,488 cases and 83,964 controls of European, East Asian, South Asian, and Mexican and Mexican American ancestry. We observed significant excess in directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven novel T2D susceptibility loci. Furthermore, we observed considerable improvements in fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterisation of complex trait loci, and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

Chronic kidney disease (CKD) is a significant public health problem, and recent genetic studies have identified common CKD susceptibility variants. The CKDGen consortium performed a meta-analysis of genome-wide association data in 67,093 Caucasian individuals from 20 population-based studies to identify new susceptibility loci for reduced renal function, estimated by serum creatinine (eGFRcrea), cystatin C (eGFRcys), and CKD (eGFRcrea <60 ml/min/1.73m2; n = 5,807 CKD cases). Follow-up of the 23 genome-wide significant loci (p<5×10−8) in 22,982 replication samples identified 13 novel loci for renal function and CKD (in or near LASS2, GCKR, ALMS1, TFDP2, DAB2, SLC34A1, VEGFA, PRKAG2, PIP5K1B, ATXN2, DACH1, UBE2Q2, and SLC7A9) and 7 creatinine production and secretion loci (CPS1, SLC22A2, TMEM60, WDR37, SLC6A13, WDR72, BCAS3). These results further our understanding of biologic mechanisms of kidney function by identifying loci potentially influencing nephrogenesis, podocyte function, angiogenesis, solute transport, and metabolic functions of the kidney.

To characterise type 2 diabetes (T2D) associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D cases and 132,532 controls of European ancestry after imputation using the 1000 Genomes multi-ethnic reference panel. Promising association signals were followed-up in additional data sets (of 14,545 or 7,397 T2D cases and 38,994 or 71,604 controls). We identified 13 novel T2D-associated loci (p<5×10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common SNVs. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion, and in adipocytes, monocytes and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.