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.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, we conducted genome-wide association meta-analyses of waist and hip circumference-related traits in up to 224,459 individuals. We identified 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (WHRadjBMI) and an additional 19 loci newly associated with related waist and hip circumference measures (P<5×10−8). Twenty of the 49 WHRadjBMI loci showed significant sexual dimorphism, 19 of which displayed a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation, and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control.

Statement LF and DAvH analysed UK GWAS data, selected SNPs and designed assays for golden gate genotyping. Substantial contributions to sample collections were made by DAvH, LD, GKTH, PH, JRFW, DSS (UK2 cases); DPS, WLMcA (1958 cohort controls); CJM, WV, MLM (DUTCH samples); VT, FMS, COM, NPK, DK (IRISH samples). UKGWAS genotyping was performed as described in PD lab2. KAH extracted UKGWAS and UK2 celiac DNA samples and performed UK2 sample golden gate genotyping. GrahamT and AWR prepared Irish DNA samples. GrahamT, AWR and KAH performed Irish sample golden gate genotyping. UK2 and IRISH genotyping was performed in CAM lab, DP performed quality control steps. AZ prepared DUTCH celiac and control DNA samples, and AZ and JR performed DUTCH sample golden gate genotyping in CW lab. DVH and KAH performed final golden gate genotype clustering on all samples, with assistance from RG. LD and DAvH collected Paxgene RNA celiac blood samples, GH extracted Paxgene RNA, GH and MB performed expression chips in CW lab, GH and LF analysed expression data. GosiaT performed IL18RAP re-sequencing. MCW processed intestinal biopsies, MB and MCW performed expression chips in CW lab, MCW and GH analysed expression data. DJP performed analysis of genes in intestinal T cell subsets. KAH and GH performed bioinformatics and annotation of celiac risk variant regions DAvH, RMM, CW were Principal Investigators and directed respectively the UK, IRISH and DUTCH sample collections and with RJP designed overall strategy and obtained funding for the study. DAvH directed the entire study, performed statistical analysis and generated the figures. DAvH and CW wrote the paper. RMcG, FT and WMMcL performed additional statistical analysis. To identify additional celiac disease susceptibility genes, we recently tested 310,605 SNPs in a genome wide association study of 778 celiac cases and 1,422 population controls from the United Kingdom (UKGWAS), using the Illumina HumanHap300 BeadChip2. The only SNP outside the HLA region demonstrating genome-wide significance was rs13119723 on 4q27, located in a ∼500 kb block of linkage disequilibrium (LD) containing the IL2 and IL21 genes2. Independent replication of SNPs from the IL2-IL21 region was established in both Dutch and Irish collections of celiac patients and controls. We estimate, using the current markers, that the IL2-IL21 region explains less than 1% of the increased familial risk to celiac disease, suggesting that there are additional unidentified susceptibility genes. Since we observed a greater number of significantly associated SNPs in the UKGWAS than would be expected by chance, we proceeded to study >1,000 of the most significant UKGWAS association results in a further 1,643 celiac cases and 3,406 controls from three independent European celiac disease collections. This two-stage strategy, involving a joint analysis of all data, substantially reduces the genotyping requirements versus performing whole genome genotyping on all samples and has been shown to maintain sufficient statistical power3. ...