Deciphering the genetic landscape of obesity: a data-driven approach to identifying plausible causal genes and therapeutic targets.

ABSTRACT:

Objectives

Genome-wide association studies (GWAS) have successfully revealed numerous susceptibility loci for obesity. However, identifying the causal genes, pathways, and tissues/cell types responsible for these associations remains a challenge, and standardized analysis workflows are lacking. Additionally, due to limited treatment options for obesity, there is a need for the development of new pharmacological therapies. This study aimed to address these issues by performing step-wise utilization of knowledgebase for gene prioritization and assessing the potential relevance of key obesity genes as therapeutic targets.

Methods and results

First, we generated a list of 28,787 obesity-associated SNPs from the publicly available GWAS dataset (approximately 800,000 individuals i

SUBMITTER: Ang MY 

PROVIDER: S-EPMC10678330 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature