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

Yu-Da Lin, Kuei-Hau Luo, Li-Yeh Chuang, Hung-Yi Chuang, Cheng-Hong Yang

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Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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Yu-Da Lin *Department of Business Computing, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.

Kuei-Hau Luo *Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung City, 807, Taiwan.

Li-Yeh ChuangDepartment of Chemical Engineering, and Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung City, Taiwan.

Hung-Yi Chuang *Department of Community Medicine, Kaohsiung Medicine University Hospital, Kaohsiung Medical University, Kaohsiung City, 807, Taiwan. ericch@kmu.edu.tw.

Cheng-Hong Yang *Department of Information Management, Tainan University of Technology, Tainan, Taiwan. chyang@nkust.edu.tw.

Funding

Kaohsiung Medical University Hospital KMUH113-3T03, KMUH114-4R85Research Center for Precision Environmental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan KMU-TC114A01the National Science and Technology Council, Taiwan NSTC 111-2221-E-165-002-MY3, NSTC 114-2221-E-165-001the National Science and Technology Council, Taiwan NSTC 111-2314-B-037-038-MY2, NSTC 114-2314-B-037-060the National Science and Technology Council, Taiwan NSTC 112-2221-E-992-105-MY3

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Abstract

backgroundMetabolic 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.

resultsAmong 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⁻

conclusionsMaODR detects epistasis networks through SNP-SNP interactions in newly identified metabolic syndrome, highlighting APOA5-LPL and APOA5-LPL-CETP interaction models.

Indexed as

Epistasis, GeneticGene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyMetabolic SyndromeApolipoprotein A-VApolipoproteins ACase-Control StudiesCholesterol Ester Transfer ProteinsFemaleHumansLipoprotein LipaseMaleMiddle AgedMultifactor Dimensionality ReductionPolymorphism, Single NucleotideAPOA5 protein, humanApolipoprotein A-VApolipoproteins ACETP protein, humanCholesterol Ester Transfer ProteinsLipoprotein LipaseLPL protein, humanGene‒gene interactionsMaODRMetabolic syndromeMultifactor dimensionality reductionSingle-nucleotide polymorphism

Identifiers

PMID42265768

DOI10.1186/s13059-026-04114-x

PMCPMC13670707

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