A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape
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2016
Authors
Ried, J.
Jeff, J.
Chu, A.
Bragg-Gresham, J.
Van Dongen, J.
Huffman, J.
Ahluwalia, T.
Cadby, G.
Eklund, N.
Eriksson, J.
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Nature Communications, 2016; 7(1):13357-1-13357-11
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Janina S. Ried, Janina M. Jeff, Audrey Y. Chu, Jennifer L. Bragg-Gresham ... Lyle J. Palmer … Jing Zhao … el al.
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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.
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© The Author(s) 2016. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/