Bivariate Linkage Analysis of Disease and Age of Onset Using Copula Models

• Activity Number: 144
• Type: Invited
• Date/Time: Monday, August 9, 2004 : 2:00 PM to 3:50 PM
• Sponsor: ENAR
• Author(s): Jian Huang*+
• Companies: University of Iowa
• Keywords: age of onset ; gene-mapping ; likelihood ; modifier genes ; pleiotropy ; semiparametrics

Abstract

In the analysis of linkage between a disease and genetic markers, the primary outcome variable is usually the disease status (affected/unaffected). For many diseases with variable ages of onset, such as breast cancer, Huntington's disease, type 1 diabetes, among others, it is useful to incorporate age of onset information in the linkage analysis. Indeed, age of onset has been successfully used in the linkage analysis of breast cancer as a covariate to classify a heterogeneous sample into more homogeneous groups, so that the power is increased in detecting linkage of the dichotomous trait. We consider the case in which age of onset is considered as a quantitative trait and propose a semiparametric model based on copulas that incorporate age of onset variable into the linkage analysis of dichotomous traits. Two genetic models will used in the consideration of the statistical model: pleiotropy: the affection status and age of onset are affect by the same gene(s); and modifier genes--there are modifier genes different from the disease gene that influnce age of onset. Simulation studies and an example will be used to illustrate the proposed method.