Abstract
Previous genome-wide association studies on anthropometric measurements have identified more than 100 related loci, but only a small portion of heritability in obesity was explained. Here we present a bivariate twin study to look for the genetic variants associated with body mass index and waist-hip ratio, and to explore the obesity-related pathways in Northern Han Chinese. Cholesky decomposition model for 242 monozygotic and 140 dizygotic twin pairs indicated a moderate genetic correlation (r = 0.53, 95%CI: 0.42–0.64) between body mass index and waist-hip ratio. Bivariate genome-wide association analysis in 139 dizygotic twin pairs identified 26 associated SNPs with p < 10−5. Further gene-based analysis found 291 nominally associated genes (P < 0.05), including F12, HCRTR1, PHOSPHO1, DOCK2, DOCK6, DGKB, GLP1R, TRHR, MMP1, GPR55, CCK, and OR2AK2, as well as 6 enriched gene-sets with FDR < 0.05. Expression quantitative trait loci analysis identified rs2242044 as a significant cis-eQTL in both the normal adipose-subcutaneous (P = 1.7 × 10−9) and adipose-visceral (P = 4.4 × 10−15) tissue. These findings may provide an important entry point to unravel genetic pleiotropy in obesity traits.
Highlights
Obesity is a worldwide epidemic associated with increased morbidity and mortality, and greatly contributes to the global disease burden (Fall and Ingelsson, 2014)
The phenotypic correlation between body mass index (BMI) and waist-hip ratio (WHR) was 0.39 (P < 0.001) and further best fitting Cholesky decomposition model (AE) identified that the genetic correlation between the two phenotypes was 0.53 (95%CI: 0.42–0.64)
We mapped the genome-wide significant SNPs reported from previous meta-analyses, including 97 BMI loci (Locke et al, 2015), 49 WHR adjusted for BMI loci (Shungin et al, 2015) and 10 BMI loci in East Asian (Wen et al, 2012), to the region of 100 kilo-bases upstream and downstream from the 26 SNPs identified by our study
Summary
Obesity is a worldwide epidemic associated with increased morbidity and mortality, and greatly contributes to the global disease burden (Fall and Ingelsson, 2014). As illustrated from the Manhattan plot (Figure 3), none of the SNPs reached the genome-wide significance level, 26 SNPs involved in 10 genes that were suggestively associated with BMI-WHR (P < 10−5) were identified.
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