Detecting linkage for a complex disease using simulated extended pedigrees.

Abstract

The simulated extended pedigree data of the Genetic Analysis Workshop 10 were used to examine the relationship between several quantitative traits (Q1-Q5), an environmental factor, age and sex and to identify genes contributing to the quantitative traits. A forward selection procedure was used to identify regression models for each trait. Residuals from these regression models were used as quantitative traits in linkage analysis. Two-point sib-pair analysis was performed on Replicate 1 of the data set using SIBPAL. Sixteen regions on 8 chromosomes yielded two-point p-values < 0.005 in Replicate 1. Two strategies for utilizing a second data set were evaluated. In a two-stage approach, only those regions with p-value < 0.005 in Replicate 1 were followed up in the second data set. Nine of these regions had p-values < 0.05 in Replicate 2; four were associated with major genes included in the generating model and the remaining five regions were false positives. An alternative strategy was to perform a repeat genome wide screen in the second data set. This strategy resulted in the identification of 20 regions with p-values < 0.05 in both replicates; five of which included major genes included in the generating model. Although the false positive rate increased when a complete genome screen was performed on both data sets, the two-stage screen, with a more stringent initial criterion for identifying suggestive linkages, had a higher rate of false negatives. For some studies, conducting two complete genome screens in a split-sample design may be worthwhile.