Model-free linkage analysis with covariates confirms linkage of prostate cancer to chromosomes 1 and 4

As with many complex genetic diseases, genome scans for prostate cancer hav e given conflicting results, often failing to provide replication of previo us findings. One factor contributing to the lack of consistency across stud ies is locus heterogeneity, which can weaken or even eliminate evidence for linkage that is present only in a subset of families. Currently, most anal yses either fail to account for locus heterogeneity or attempt to account f or it only by partitioning data sets into smaller and smaller portions. In the present study, we model locus heterogeneity among affected sib pairs wi th prostate cancer by including covariates in the linkage analysis that ser ve as surrogate measures of between-family linkage differences. The model i s a modification of the Olson conditional logistic model for affected relat ive pairs. By including Gleason score, age at onset, male-to-male transmiss ion, and/or number of affected first-degree family members as covariates, w e detected linkage near three locations that were previously identified by linkage (1q24-25 [HPC1; LOD score 3.25, P = .00012], 1q42.2-43 [PCAP; LOD s core 2.84, P = .0030], and 4q [LOD score 2.80, P = .00038]), near the andro gen-receptor locus on Xq12-13 (AR; LOD score 3.06, P = .00053), and at five new locations (LOD score > 2.5). Without covariates, only a few weak-to-mo derate linkage signals were found, none of which replicate findings of prev ious genome scans. We conclude that covariate-based linkage analysis greatl y improves the likelihood that linked regions will be found by incorporatio n of information about heterogeneity within the sample.