Genome-wide association and MaODR-based multi-locus interaction analyses reveal a susceptibility gene network for newly identified metabolic syndrome

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 gene‒gene interactions in unbalanced newly identified MetS and non-MetS subjects. 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 × 10⁻ 2 ⁰). 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. MaODR detects epistasis networks through SNP-SNP interactions in newly identified metabolic syndrome, highlighting APOA5 – LPL and APOA5 – LPL – CETP interaction models.