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Updated: Jan 24, 2026

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
Published on: July 1, 2020
Genome-Wide Interaction and Pathway Association Studies for Body Mass Index
Hongxiao Jiao1, Yong Zang2, Miaomiao Zhang2
1Research Center of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
Abstract:
Objective: We investigated gene interactions (epistasis) for body mass index (BMI) in a European-American adult female cohort via genome-wide interaction analyses (GWIA) and pathway association analyses. Methods: Genome-wide pairwise interaction analyses were carried out for BMI in 493 extremely obese cases (BMI > 35 kg/m2) and 537 never-overweight controls (BMI < 25 kg/m2). To further validate the results, specific SNPs were selected based on the GWIA results for haplotype-based association studies. Pathway-based association analyses were performed using a modified Gene Set Enrichment Algorithm (GSEA) (GenGen program) to further explore BMI-related pathways using our genome wide association study (GWAS) data set, GIANT, ENGAGE, and DIAGRAM Consortia. Results: The EXOC4-1q23.1 interaction was associated with BMI, with the most significant epistasis between rs7800006 and rs10797020 (P = 2.63 × 10-11). In the pathway-based association analysis, Tob1 pathway showed the most significant association with BMI (empirical P < 0.001, FDR = 0.044, FWER = 0.040). These findings were further validated in different populations. Conclusion: Genome-wide pairwise SNP-SNP interaction and pathway analyses suggest that EXOC4 and TOB1-related pathways may contribute to the development of obesity.
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