A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape.
| Authors | |
| 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. |
| Year of Publication | 2016
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| Journal | Nat Commun
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| Volume | 7
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| Pages | 13357
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| Date Published | 2016 Nov 23
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| ISSN | 2041-1723
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| DOI | 10.1038/ncomms13357
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| PubMed ID | 27876822
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| PubMed Central ID | PMC5114527
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| Links | |
| Grant list | P30 DK020541 / DK / NIDDK NIH HHS / United States
P30 DK063491 / DK / NIDDK NIH HHS / United States
R01 HL117626 / HL / NHLBI NIH HHS / United States
UL1 TR000124 / TR / NCATS NIH HHS / United States
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