A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape.
Nat Commun
; 7: 13357, 2016 11 23.
Article
in En
| MEDLINE
| ID: mdl-27876822
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.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Anthropometry
/
Principal Component Analysis
/
Body Size
/
Models, Genetic
Type of study:
Prognostic_studies
/
Systematic_reviews
Limits:
Humans
Language:
En
Journal:
Nat Commun
Journal subject:
BIOLOGIA
/
CIENCIA
Year:
2016
Document type:
Article
Affiliation country:
Germany
Country of publication:
United kingdom