A novel approach to detect cumulative genetic effects and genetic interactions in Crohn's disease.

Background: Genome-wide association studies have identified at least 71 Crohn's disease (CD) genetic risk loci, but the role of gene-gene interactions is unclear. The value of genetic variants in clinical practice is not defined because of limited explained heritability.
Methods: We examined model predictability of combining the 71 CD risk alleles and genetic interactions in an ongoing inflammatory bowel disease genome-wide association study. The Wellcome Trust Case Control Consortium inflammatory bowel disease genome-wide association study was used as a replicate cohort. We used logic regression, an adaptive regression methodology, to search for high-order binary predictors (e.g., single-nucleotide polymorphism [SNP] interactions).
Results: The combined 71 CD SNPs had good CD risk predictability (area under the curve of 0.75 and 0.73 in the 2 cohorts). Higher cumulative allele score predicted higher CD risk, but a relatively small difference in cumulative allele scores was observed between CD and controls (49 versus 47, P < 0.001). Through LR, we identified high-order genetic interactions and significantly improved the model predictability (area under the curve, from 0.75 to 0.77, P < 0.0001). A genetic interaction model, including NOD2, ATG16L1, IL10/IL19, C13orf31, and chr21q loci, was discovered and successfully replicated in the independent Wellcome Trust Case Control Consortium cohort. The explained heritability of the 71 CD SNPs alone was 24% and increased to 27% after adding the genetic interactions.
Conclusions: A novel approach allowed the identification and replication of genetic interactions among NOD2, ATG16L1, IL10/IL19, C13orf31, and chr21q loci. CD risk can be predicted by a model of 71 CD loci and improved by adding genetic interactions.