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A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Ried, Janina S 
Jeff M, Janina 
Chu, Audrey Y 
Bragg-Gresham, Jennifer L 
van Dongen, Jenny 

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.

Description

Keywords

Anthropometry, Body Size, Genome-Wide Association Study, Genotype, Humans, Models, Genetic, Principal Component Analysis

Journal Title

Nat Commun

Conference Name

Journal ISSN

2041-1723
2041-1723

Volume Title

7

Publisher

Springer Science and Business Media LLC
Sponsorship
Medical Research Council (MC_UU_12015/1)
European Commission FP6 Coordination or networking actions (CA) (SP23-CT-2005-006438)
Medical Research Council (G0701863)
Medical Research Council (MC_UU_12015/5)
Medical Research Council (MC_UU_12015/2)
Medical Research Council (MC_U106179472)