Analysis of Genetic Variants and Tissue-Specific Gene Expression in Obesity: A Bioinformatic Study

Obesity is a highly heritable and polygenic disorder, yet the biological interpretation of genome-wide association study (GWAS) signals remains incompletely resolved. This study applied an integrative bioinformatic framework to prioritize obesity-associated genetic variants and characterize their tissue-specific expression patterns. Obesity-related single-nucleotide polymorphisms (SNPs) were retrieved from the NHGRI–EBI GWAS Catalog and filtered using a genome-wide significance threshold (p < 1 × 10⁻⁸). Missense variants were prioritized for functional evaluation. Genomic annotation was performed using Ensembl, functional impact prediction was conducted via SNPnexus incorporating PolyPhen-2 classification, tissue-specific expression was analyzed using the GTEx Portal, and population-level allele frequencies were assessed using HaploReg v4.2. Among 1,502 identified obesity-associated SNPs, 15 genome-wide significant missense variants were prioritized. Functional prediction highlighted variants in SLC39A8, GIPR, and BDNF as having the highest potential biological impact. Tissue-specific profiling revealed coherent expression patterns across metabolically active tissues and central nervous system regions implicated in energy balance. A population-based analysis demonstrated substantial intercontinental differences in allele frequencies. This integrative analysis refines the biological interpretation of obesity-associated variants and provides a prioritized genomic framework to inform precision risk stratification and future pharmacogenomic strategies in obesity management.