A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape
A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape
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.
Ried, J.S.
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Jeff, J.M.
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Chu, A.Y.
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Bragg-Gresham, J.L.
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Van Dongen, J.
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Couto Alves, A.
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Osmond, C.
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al, et
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23 November 2016
Ried, J.S.
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Jeff, J.M.
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Chu, A.Y.
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Bragg-Gresham, J.L.
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Van Dongen, J.
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Couto Alves, A.
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Osmond, C.
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al, et
df099e87-31d7-4ccf-a9fa-b92a380537f9
Ried, J.S., Jeff, J.M., Chu, A.Y., Bragg-Gresham, J.L., Van Dongen, J., Couto Alves, A., Osmond, C. and al, et
(2016)
A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape.
Nature Communications.
(doi:10.1038/ncomms13357).
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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ncomms13357
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Accepted/In Press date: 21 September 2016
Published date: 23 November 2016
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Local EPrints ID: 494946
URI: http://eprints.soton.ac.uk/id/eprint/494946
ISSN: 2041-1723
PURE UUID: 47769214-5869-4c51-a42e-1b6dd7fa585a
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Date deposited: 23 Oct 2024 16:58
Last modified: 30 Oct 2024 03:10
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Author:
J.S. Ried
Author:
J.M. Jeff
Author:
A.Y. Chu
Author:
J.L. Bragg-Gresham
Author:
J. Van Dongen
Author:
A. Couto Alves
Author:
et al
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