SummaryEducational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease.

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic, pulse pressure) to date in over one million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also reveal shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

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.

Smoking is a leading global cause of disease and mortality1. We performed a genomewide meta-analytic association study of smoking-related behavioral traits in a total sample of 41,150 individuals drawn from 20 disease, population, and control cohorts. Our analysis confirmed an effect on smoking quantity (SQ) at a locus on 15q25 (P=9.45e-19) that includes three genes encoding neuronal nicotinic acetylcholine receptor subunits (CHRNA5, CHRNA3, CHRNB4). We used data from the 1000 Genomes project to investigate the region using imputation, which allowed analysis of virtually all common variants in the region and offered a five-fold increase in coverage over the HapMap. This increased the spectrum of potentially causal single nucleotide polymorphisms (SNPs), which included a novel SNP that showed the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.

Atrial fibrillation (AF) affects over 33 million individuals worldwide1 and has a complex heritability.2 We conducted the largest meta-analysis of genome-wide association studies for AF to date, consisting of over half a million individuals including 65,446 with AF. In total, we identified 97 loci significantly associated with AF including 67 of which were novel in a combined-ancestry analysis, and 3 in a European specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait loci (eQTL) analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.

Pulmonary function measures are heritable traits that predict morbidity and mortality and define chronic obstructive pulmonary disease (COPD). We tested genome-wide association with forced expiratory volume in 1 s (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) in the SpiroMeta consortium (n = 20,288 individuals of European ancestry). We conducted a meta-analysis of top signals with data from direct genotyping (n ≤ 32,184 additional individuals) and in silico summary association data from the CHARGE Consortium (n = 21,209) and the Health 2000 survey (n ≤ 883). We confirmed the reported locus at 4q31 and identified associations with FEV1 or FEV1/FVC and common variants at five additional loci: 2q35 in TNS1 (P = 1.11 × 10−12), 4q24 in GSTCD (2.18 × 10−23), 5q33 in HTR4 (P = 4.29 × 10−9), 6p21 in AGER (P = 3.07 × 10−15) and 15q23 in THSD4 (P = 7.24 × 10−15). mRNA analyses showed expression of TNS1, GSTCD, AGER, HTR4 and THSD4 in human lung tissue. These associations offer mechanistic insight into pulmonary function regulation and indicate potential targets for interventions to alleviate respiratory disease.

The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of U.S. military veterans. We genotyped 312,571 MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least 1 blood lipid measurement including 57,332 blacks and 24,743 Hispanics, we tested up to ~32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total N > 600,000). Through a focus on mutations predicted to result in a loss of gene function and a phenome-wide association study, we propose novel indications for pharmaceutical inhibitors targeting PCSK9 (abdominal aortic aneurysm), ANGPTL4 (type 2 diabetes), and PDE3B (triglycerides and coronary disease).

We screened DNA sequence variants on an exome-focused genotyping array in >300,000 participants with replication in >280,000 participants and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice revealed lipid changes consistent with the human data. We utilized mapped variants to address four clinically relevant questions and found the following: (1) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease; (2) outside of the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (3) only some mechanisms of lowering LDL-C seemed to increase risk for type 2 diabetes; and (4) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (e.g., TM6SF2, PNPLA3) tracked with higher liver fat, higher risk for type 2 diabetes, and lower risk for coronary artery disease whereas TG-lowering alleles involved in peripheral lipolysis (e.g., LPL, ANGPTL4) had no effect on liver fat but lowered risks for both type 2 diabetes and coronary artery disease.