Title:
Quantitative Trait Linkage Analysis in the Presence of Gene-age
Interactions in Genetic Effects
Abstract:
Linkage analysis has been one of the most widely used methods for
identifying regions of the human genome which contain genes responsible
for human
diseases. Evidence suggests that the effects of some of the trait causing
genes may vary with the age of an individual, giving rise to temporal
trends in genetic
effects. While linkage analysis methods have been proposed to analyze
longitudinal family data for exploring temporal trends, there are no
models to characterize such
trends nor methods for cross-sectional analysis of family data. Even the
longitudinal data analysis methods are not fully developed. Linkage
analysis routinely tends
to ignore such gene-by-age interactions. We extend variance component
linkage analysis methodology by allowing the variance components due to
the quantitative trait
locus (QTL) and that due to the polygenic effect to be age dependent. With
this model, we investigate the power of linkage analysis in the presence
of temporal
trends. We show that, ignoring the gene-by-age interactions, when present,
could jeopardize gene discovery significantly. Modeling such trends
explicitly leads to
substantial gain in power to detect linkage which is likely to enhance
gene discovery for complex traits.