Variance components analysis for genetic linkage of time to onset for disease.

Abstract

We compared two variance components methods for detecting genes that influence time to onset for a complex disease using simulated data. We first divided the extended families into nuclear families. The first method fitted variance components to the martingale residuals, which were obtained from first fitting a proportional hazards model to the time to onset data for the trait, allowing for the quantitative traits Q1-Q5, sex, age, and the environmental factor. The second method treated time to onset among the affected individuals as a quantitative trait adjusting for the same factors as in the first method. Power of these analyses were similar for either approach. However, we found an excess of false-positive results when fitting the martingale residual model or the affected-only model to identify genetic factors linked to chromosome 6. Applying a power transformation to the martingale residuals decreased the type I error rate and increased the power of tests for genetic linkage. We also found that robust variance correction lead to test with a slightly lower type I error rate, perhaps because the robust variance correction adjusts for the fact that we did not specifically model the effects of the mitochondrial factor in our analysis.