Detection of complex genetic architecture using two-locus population differentiation: modeling epistasis

Recent advances in genetics have increased our understanding of epistasis as important in the genetics of complex phenotypes. However, current analytical methods often cannot detect epistasis, given the multiple testing burden. To address this, we extended our previous method, Evolutionary Triangulation (ET), that uses differences among populations in both disease prevalence and allele frequencies to filter SNPs from association studies to generate novel interaction models. We show that two-locus ET identified several co-evolving gene pairs, where both genes associate with the same disease, and that the number of such pairs is significantly greater than expected by chance. Traits found by two-locus ET included those related to pigmentation and schizophrenia. We then applied two-locus ET to the analysis of preterm birth (PTB) genetics. Using ET to filter SNPs at loci identified by genome-wide association studies (GWAS), we showed that ET derived PTB two-locus models are novel and were not seen when only the index SNPs were used to generate epistatic models. One gene pair, ADCY5 and KCNAB1 5′, was identified as significantly interacting in a model of gestational age (p as low as 3 × 10-3). Notably, the same ET SNPs in these genes showed significant interactions in three of four cohorts analyzed. The robustness of this gene pair and others, demonstrated that the ET method can be used without prior biological hypotheses based on SNP function to select variants for epistasis testing that could not be identified otherwise. Two-locus ET clearly increased the ability to identify epistasis in complex traits.