Evaluation of screening strategies to detect an oligogenic disease

Using data simulated to reflect an oligogenic disease, we evaluated screening strategies based on lod-score and weighted pairwise correlation (WPC) analysis with respect to their ability to efficiently identify regions near disease loci. Lod-score analysis was done twice, once assuming a near-recessive mode of inheritance with a high penetrance and again assuming a semidominant mode of inheritance with lower penetrance. Under the near-recessive model, no disease loci were correctly identified, while there was one false positive result. Under the semidominant model, D1G31 was correctly identified, and there were two false positive results. Due to the lack of highly informative families and possible sensitivity to parameter misspecification, this poor performance was not unexpected. WPC, on the other hand, is assumption-free and thus potentially more powerful than a misspecified parametric model, but almost certainly less powerful than a well-specified parametric model. Using WPC modified to handle binary phenotypes with no age-of-onset, we found results closely resembling those under the semidominant model, although no markers near disease loci exceeded the theoretical critical value for WPC.