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


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)