Hundreds of variants clustered in genomic loci and biological pathways affect human height
Author(s)
Type
Journal Article
Abstract
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 identified more than 600 variants associated with human traits1, 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 trait2, 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.
Date Issued
2010-10-14
Date Acceptance
2010-07-28
Citation
Nature, 2010, 467 (7317), pp.832-838
ISSN
0028-0836
Publisher
NATURE PUBLISHING GROUP
Start Page
832
End Page
838
Journal / Book Title
Nature
Volume
467
Issue
7317
Copyright Statement
© 2010, Rights Managed by Nature Publishing Group
Sponsor
Medical Research Council (MRC)
Grant Number
G0600331
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
MULTIDISCIPLINARY SCIENCES
WIDE ASSOCIATION ANALYSIS
COMMON VARIANTS
HERITABILITY
POPULATION
ADULT
STRATIFICATION
DISEASES
TRAITS
GROWTH
SNPS
Publication Status
Published