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A Genome-Wide Association Study on Obesity and Obesity-Related Traits
Author(s) -
Kai Wang,
Weidong Li,
Hu Zhang,
Zuoheng Wang,
Joseph Glessner,
Struan F.A. Grant,
Hongyu Zhao,
Håkon Håkonarson,
R. Arlen Price
Publication year - 2011
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0018939
Subject(s) - genome wide association study , obesity , body mass index , overweight , single nucleotide polymorphism , waist , genotyping , genetic association , genetics , quantitative trait locus , biology , medicine , genotype , gene
Large-scale genome-wide association studies (GWAS) have identified many loci associated with body mass index (BMI), but few studies focused on obesity as a binary trait. Here we report the results of a GWAS and candidate SNP genotyping study of obesity, including extremely obese cases and never overweight controls as well as families segregating extreme obesity and thinness. We first performed a GWAS on 520 cases (BMI>35 kg/m 2 ) and 540 control subjects (BMI<25 kg/m 2 ), on measures of obesity and obesity-related traits. We subsequently followed up obesity-associated signals by genotyping the top ∼500 SNPs from GWAS in the combined sample of cases, controls and family members totaling 2,256 individuals. For the binary trait of obesity, we found 16 genome-wide significant signals within the FTO gene (strongest signal at rs17817449, P = 2.5×10 −12 ). We next examined obesity-related quantitative traits (such as total body weight, waist circumference and waist to hip ratio), and detected genome-wide significant signals between waist to hip ratio and NRXN3 (rs11624704, P = 2.67×10 −9 ), previously associated with body weight and fat distribution. Our study demonstrated how a relatively small sample ascertained through extreme phenotypes can detect genuine associations in a GWAS.

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