Lin_2026_Genome.Biol__

BACKGROUND: Metabolic syndrome involves several lipid-related genes, including apolipoprotein A5 (APOA5), lipoprotein lipase (LPL), and cholesteryl ester transfer protein (CETP). Although individual SNP susceptibility has been reported, gene-gene interactions remain underexplored. To address this gap, we apply many-objective multifactor dimensionality reduction (MaODR)-previously developed by our group-to detect genegene interactions in unbalanced newly identified MetS and non-MetS subjects. RESULTS: Among 40,773 Taiwan Biobank participants (5,723 newly identified metabolic syndrome cases and 35,050 controls) after excluding smokers and individuals with chronic diseases, genome-wide association analysis identifies 35 significant SNPs. We detect a two-locus SNP-SNP interaction between APOA5 and LPL; the most significant genotype combination is rs331-GG with rs651821-CC (bootstrap odds ratio = 1.76; p = 9.61 x 10(2)). MaODR also reveals a three-way interaction among APOA5, LPL, and CETP. Furthermore, we find that the LPL, APOA5, BUD13, zinc finger protein 1 (ZPR1), APOC3, CETP, and APOE genes collectively contributed to MetS susceptibility, with SNPs of LPL showing a significant metabolic syndrome-associated effect and interacting with SNPs of the APOA5 and CETP genes. Genes linked to metabolic syndrome are enriched in cholesterol metabolism and the peroxisome proliferator-activated receptor signaling pathway. CONCLUSIONS: MaODR detects epistasis networks through SNP-SNP interactions in newly identified metabolic syndrome, highlighting APOA5-LPL and APOA5-LPL-CETP interaction models.