Pathway-induced allelic spectra of diseases in the presence of strong genetic effects.

Complex diseases are frequently modeled as following an additive model that excludes both intra- and inter-locus interaction, while at the same time reports on non-additive biological structures are ample, prominently featuring numerous metabolic and signaling pathways. Using extensive forward population simulations, we explored the impact of three basic pathway motifs on the relationship between epidemiological parameters, including disease prevalence, relative risk, sibling recurrence risk as well as causal variant number and allele frequency. We found that some but not all pathway motifs can shift the relationships between these parameters in comparison to the classical additive liability threshold model. The strongest deviations were observed with linear, cascade-like motifs that form an integral part of many reported pathways. We also modeled maturity-onset diabetes of the young (MODY) as a combination of different basic pathway motifs and observed a good concordance in epidemiological parameter values between our simulated data under this model and those reported in the literature. Given the widespread nature of pathways, including those in the etiology of human diseases, our results re-emphasize the need for non-additive interaction modeling of genetic variants to become an additional standard approach in analyzing human genetic data.