Epistasis (gene-gene interaction) studies extend traditional GWAS, using a more realistic model at the expense of dramatically increased statistical and computational requirements. Several strategies can be employed to work around these drawbacks, including filtering interactions and using more sophisticated encoding strategies.
Epistasis analysis elucidates the genetic effects of interactions between multiple loci for understanding complex traits. However, the large computational demands and the high multiple testing burdens impede their discovery. We are evaluating gene-gene interactions associated with cardiac traits within the Ludwigshafen risk and cardiovascular (LURIC) Health Study by utilizing two filtering methods, main effect filtering from GWAS results and biological knowledge-based filtering and modeling through Biofilter software, to reduce the multiple testing burden. The LURIC study is an ongoing health study to elucidate the risk factors for cardiovascular diseases from genetics, environments, and medications. Emerging findings indicate significant gene-gene interactions involved in the cardiac phenotypes (see figure below) and demonstrate the utility of filtering methods to investigate the epistasis of common disease for improving the precision medicine (manuscript under review).
This work is supported by the USDA National Institute of Food and Agriculture and Hatch Appropriations under Project #PEN04275 and Accession #1018544. Genotyping of the LURIC study participants was supported by the 7th Framework Program AtheroRemo (grant agreement #201668) of the European Union.