Identification of potential genetic causal variants for obesity-related traits using statistical fine mapping.

ABSTRACT:

Background

Obesity is highly influenced by heritability and variant effects. While previous genome-wide association studies (GWASs) have successfully identified numerous genetic loci associated with obesity-related traits [body mass index (BMI) and waist-to-hip ratio (WHR)], most causal variants remain unidentified. The high degree of linkage disequilibrium (LD) throughout the genome makes it extremely difficult to distinguish the GWAS-associated SNPs that exert a true biological effect.

Objective

This study was to identify the potential causal variants having a biological effect on obesity-related traits.

Methods

We used Probabilistic Annotation INTegratOR, a Bayesian fine-mapping method, which incorporated genetic association data (GWAS summary statistics), LD struc

SUBMITTER: Gong R 

PROVIDER: S-EPMC11829812 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature