Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have... Show moreMost common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits(1), but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait(2,3). The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways. Show less
Smoking is a common risk factor for many diseases(1). We conducted genome-wide association meta-analyses for the number of cigarettes smoked per day (CPD) in smokers (n = 31,266) and smoking... Show moreSmoking is a common risk factor for many diseases(1). We conducted genome-wide association meta-analyses for the number of cigarettes smoked per day (CPD) in smokers (n = 31,266) and smoking initiation (n = 46,481) using samples from the ENGAGE Consortium. In a second stage, we tested selected SNPs with in silico replication in the Tobacco and Genetics (TAG) and Glaxo Smith Kline (Ox-GSK) consortia cohorts (n = 45,691 smokers) and assessed some of those in a third sample of European ancestry (n = 9,040). Variants in three genomic regions associated with CPD (P < 5 x 10(-8)), including previously identified SNPs at 15q25 represented by rs1051730[A] (effect size = 0.80 CPD, P = 2.4 x 10(-69)), and SNPs at 19q13 and 8p11, represented by rs4105144[C] (effect size = 0.39 CPD, P = 2.2 x 10(-12)) and rs6474412-T (effect size = 0.29 CPD, P = 1.4 x 10(-8)), respectively. Among the genes at the two newly associated loci are genes encoding nicotine-metabolizing enzymes (CYP2A6 and CYP2B6) and nicotinic acetylcholine receptor subunits (CHRNB3 and CHRNA6), all of which have been highlighted in previous studies of smoking and nicotine dependence2-4. Nominal associations with lung cancer were observed at both 8p11 (rs6474412[T], odds ratio (OR) = 1.09, P = 0.04) and 19q13 (rs4105144[C], OR = 1.12, P = 0.0006). Show less
