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Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture.

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SGUL Authors: Strachan, David Peter

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Abstract

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

Item Type: Article
Additional Information: Author’s manuscript is made available for academic research only, and cannot be used for commercial purposes without prior permission of the copyright holders. Made available here with permission from the publisher.
Keywords: Anthropometry, Body Height, Body Mass Index, Case-Control Studies, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Meta-Analysis as Topic, Obesity, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Waist-Hip Ratio, Science & Technology, Life Sciences & Biomedicine, Genetics & Heredity, EXTREME OBESITY, BODY-MASS INDEX, MISSING HERITABILITY, COMMON VARIANTS, CONFER RISK, EARLY-ONSET, ASSOCIATION, POPULATION, EXPRESSION, SORTILIN, Developmental Biology, 11 Medical And Health Sciences, 06 Biological Sciences
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: Nature Genetics
ISSN: 1546-1718
Language: eng
Dates:
DateEvent
May 2013Published
PubMed ID: 23563607
Web of Science ID: WOS:000318158200011
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/107305
Publisher's version: https://doi.org/10.1038/ng.2606

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