Presentation Information
[PE2-12]Systematic functional annotation of obesity-associated SNPs detectable through GWAS
○ANG MIA YANG1,2, Fumihiko Takeuchi1, Norihiro Kato1,2 (1.Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan, 2.Department of Clinical Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan)
Introduction
Obesity is a multifactorial disorder, defined by excessive fat accumulation in the body. While GWAS have successfully identified a large number of susceptibility loci for obesity, the underlying mechanisms remain to be clarified.
Objective
To systematically perform functional annotation of obesity-associated SNPs detectable through GWAS.
Method
Based on publicly-available GWAS data, we performed a series of functional annotation of obesity-associated SNPs using databases with each developed for diverse purposes, i.e., RegulomeDB, CardioGxE, TWAS-hub, Expression Atlas and DisGeNET; all of these help us identify a set of genes that are important to the pathogenesis of obesity. Also, we performed pathway enrichment analysis and reconstructed protein-protein interaction (PPI) network using Enrichr and STRING databases, respectively.
Results
We collated a total of 171,726 obesity-associated SNPs, which were grouped into 1,051 unique loci. Our functional annotation identified ~100 genes, including 60 eQTL genes (e.g., ADCY3 and SPI1), 16 genes with significant gene-environment interactions (e.g., PPARG and TCF7L2), 39 TWAS genes detectable in obesity-associated tissues. Pathway enrichment analysis revealed significant GO terms, including glucose homeostasis and regulation of insulin secretion, among the functional genes thus identified. PPI network analysis further indicated energy intake and expenditure to be a principal driver of obesity.
Conclusions
The outcomes of our study provide targets and clues for future functional analyses on the pathogenesis of obesity.
Obesity is a multifactorial disorder, defined by excessive fat accumulation in the body. While GWAS have successfully identified a large number of susceptibility loci for obesity, the underlying mechanisms remain to be clarified.
Objective
To systematically perform functional annotation of obesity-associated SNPs detectable through GWAS.
Method
Based on publicly-available GWAS data, we performed a series of functional annotation of obesity-associated SNPs using databases with each developed for diverse purposes, i.e., RegulomeDB, CardioGxE, TWAS-hub, Expression Atlas and DisGeNET; all of these help us identify a set of genes that are important to the pathogenesis of obesity. Also, we performed pathway enrichment analysis and reconstructed protein-protein interaction (PPI) network using Enrichr and STRING databases, respectively.
Results
We collated a total of 171,726 obesity-associated SNPs, which were grouped into 1,051 unique loci. Our functional annotation identified ~100 genes, including 60 eQTL genes (e.g., ADCY3 and SPI1), 16 genes with significant gene-environment interactions (e.g., PPARG and TCF7L2), 39 TWAS genes detectable in obesity-associated tissues. Pathway enrichment analysis revealed significant GO terms, including glucose homeostasis and regulation of insulin secretion, among the functional genes thus identified. PPI network analysis further indicated energy intake and expenditure to be a principal driver of obesity.
Conclusions
The outcomes of our study provide targets and clues for future functional analyses on the pathogenesis of obesity.