SEMIPARAMETRIC ESTIMATION OF MAJOR GENE AND FAMILY-SPECIFIC RANDOM EFFECTS FOR AGE-OF-ONSET

Analysis of familial diseases with variable age of onset is a common p roblem in human genetics. Most existing methods make some parametric d istributional assumption on age of onset, and few methods have been de signed with the goal of testing the hypothesis of a Mendelian gene aga inst other hypotheses of familial dependence. We introduce the Cox mod el with major genetic and random familial effects to model age-of-onse t dependence patterns among family members and to incorporate family h eterogeneity. This model allows testing for and estimating major gene effects in the presence of residual correlations. Generalized maximum likelihood estimation using a Monte Carlo EM algorithm is used for par ameter estimation. The methods are illustrated by a simulated data set and a data set from a case-control family study of breast cancer.