Hundreds of variants clustered in genomic loci and biological pathways affect human height

Allen, Hana Lango, Estrada, Karol, Lettre, Guillaume, Berndt, Sonja I., Weedon, Michael N., Rivadeneira, Fernando, Willer, Cristen J., Jackson, Anne U., Vedantam, Sailaja, Raychaudhuri, Soumya, Nyholt, Dale, Martin, Nicholas G., Montgomery, Grant W. and Visscher, Peter M. (2010) Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature, 467 7317: 832-838. doi:10.1038/nature09410

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Author Allen, Hana Lango
Estrada, Karol
Lettre, Guillaume
Berndt, Sonja I.
Weedon, Michael N.
Rivadeneira, Fernando
Willer, Cristen J.
Jackson, Anne U.
Vedantam, Sailaja
Raychaudhuri, Soumya
Nyholt, Dale
Martin, Nicholas G.
Montgomery, Grant W.
Visscher, Peter M.
Title Hundreds of variants clustered in genomic loci and biological pathways affect human height
Journal name Nature   Check publisher's open access policy
ISSN 0028-0836
Publication date 2010-10-14
Sub-type Article (original research)
DOI 10.1038/nature09410
Volume 467
Issue 7317
Start page 832
End page 838
Total pages 7
Place of publication London, U.K.
Publisher Nature Publishing Group
Collection year 2011
Language eng
Formatted 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 alreadydiscovered 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.
© 2010 Macmillan Publishers Limited. All rights reserved.
Keyword Wide association analysis
Common variants
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Over 200 listed authors.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2011 Collection
School of Medicine Publications
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Citation counts: TR Web of Science Citation Count  Cited 517 times in Thomson Reuters Web of Science Article | Citations
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Created: Thu, 31 Mar 2011, 10:15:11 EST by Debbie Banks on behalf of School of Medicine