Dissecting the obesity disease landscape: Identifying gene-gene interactions that are highly associated with body mass index

Rishika De, Michael V. Holmes, Jason H. Moore, Marylyn D. Ritchie, Shefali S. Verma, Folkert W. Asselbergs, Brendan J. Keating, Diane Gilbert-Diamond

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Despite heritability estimates of 40-70% for obesity, less than 2% of its variation is explained by Body Mass Index (BMI) associated loci that have been identified so far. Epistasis, or gene-gene interactions are a plausible source to explain portions of the missing heritability of BMI. Using genotypic data from 18,686 individuals across five study cohorts - ARIC, CARDIA, FHS, CHS, MESA - we filtered SNPs (Single Nucleotide Polymorphisms) using two parallel approaches. SNPs were filtered either on the strength of their main effects of association with BMI, or on the number of knowledge sources supporting a specific SNP-SNP interaction in the context of obesity. Filtered SNPs were specifically analyzed for interactions that are highly associated with BMI using QMDR (Quantitative Multifactor Dimensionality Reduction). QMDR is a nonparametric, genetic model-free method that detects nonlinear interactions in the context of a quantitative trait. We identified seven novel, epistatic models with a Bonferroni corrected p-value of association < 0.06. Prior experimental evidence helps explain the plausible biological interactions highlighted within our results and their relationship with obesity. We identified interactions between genes involved in mitochondrial dysfunction (POLG2), cholesterol metabolism (SOAT2), lipid metabolism (CYP11B2), cell adhesion (EZR), cell proliferation (MAP2K5), and insulin resistance (IGF1R). This study highlights a novel approach for discovering gene-gene interactions by combining methods such as QMDR with traditional statistics.

Original languageEnglish (US)
Title of host publicationInternational Conference on Systems Biology, ISB
EditorsLing-Yun Wu, Yong Wang, Luonan Chen, Xiang-Sun Zhang
PublisherIEEE Computer Society
Pages124-131
Number of pages8
ISBN (Electronic)9781479972944
DOIs
StatePublished - Dec 17 2014
Event8th International Conference on Systems Biology, ISB 2014 - Qingdao, China
Duration: Aug 24 2014Aug 27 2014

Other

Other8th International Conference on Systems Biology, ISB 2014
CountryChina
CityQingdao
Period8/24/148/27/14

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science Applications

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    De, R., Holmes, M. V., Moore, J. H., Ritchie, M. D., Verma, S. S., Asselbergs, F. W., Keating, B. J., & Gilbert-Diamond, D. (2014). Dissecting the obesity disease landscape: Identifying gene-gene interactions that are highly associated with body mass index. In L-Y. Wu, Y. Wang, L. Chen, & X-S. Zhang (Eds.), International Conference on Systems Biology, ISB (pp. 124-131). [6990744] IEEE Computer Society. https://doi.org/10.1109/ISB.2014.6990744