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

2.50
Hdl Handle:
http://hdl.handle.net/11287/620282
Title:
A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape
Authors:
Ried, J.S. et al; Hattersley, Andrew T.
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.
Citation:
A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape. Nature Communications 2016 Nov 23;7:13357
Publisher:
Nature
Journal:
Nature Communications
Issue Date:
Nov-2016
URI:
http://hdl.handle.net/11287/620282
DOI:
10.1038/ncomms13357
PubMed ID:
27876822
Additional Links:
http://dx.doi.org/10.1038/ncomms13357
Note:
This article is freely available via Open Access. Click on the Additional Link above to access the full-text.
Type:
Journal Article
Language:
en
Appears in Collections:
Diabetes/Endocrine Services; 2016 RD&E publications

Full metadata record

DC FieldValue Language
dc.contributor.authorRied, J.S. et alen
dc.contributor.authorHattersley, Andrew T.en
dc.date.accessioned2017-03-14T14:56:56Z-
dc.date.available2017-03-14T14:56:56Z-
dc.date.issued2016-11-
dc.identifier.citationA principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape. Nature Communications 2016 Nov 23;7:13357en
dc.identifier.pmid27876822-
dc.identifier.doi10.1038/ncomms13357-
dc.identifier.urihttp://hdl.handle.net/11287/620282-
dc.description.abstractLarge 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.en
dc.language.isoenen
dc.publisherNatureen
dc.relation.urlhttp://dx.doi.org/10.1038/ncomms13357en
dc.subjectWessex Classification Subject Headings::Endocrinology::Diabetesen
dc.titleA principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shapeen
dc.typeJournal Articleen
dc.identifier.journalNature Communicationsen
dc.description.noteThis article is freely available via Open Access. Click on the Additional Link above to access the full-text.en
dc.type.versionPublisheden

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