A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape.
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State: Public
Version: Final published version
State: Public
Version: Final published version
Serval ID
serval:BIB_785C16F5A5CA
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape.
Journal
Nature communications
ISSN
2041-1723 (Electronic)
ISSN-L
2041-1723
Publication state
Published
Issued date
23/11/2016
Volume
7
Pages
13357
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Publication Status: epublish
Abstract
Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
Pubmed
Open Access
Yes
Create date
02/12/2016 11:40
Last modification date
20/08/2019 14:35