Robust transmission regression models for linkage and association

We present a general regression model that accounts for both linkage and li nkage disequilibrium (LD) when analyzing nuclear family data. The method do es not require LD to exist in order to evaluate linkage, but if LD does exi st, the power to detect linkage can increase due to improved information on linkage phase. The proposed method is general, allowing for a variety of t raits (e.g., binary affection status, categorical and quantitative phenotyp es), affecteds only analyses, and covariates. Covariates can be useful to a ssess heterogeneity of linkage and LD, as well as gene-environment interact ions. Other advantages of our methods are that: LD parameters are not defin ed without linkage, so that population stratification cannot bias the analy ses; a combined test for linkage and LD can be used to test for linkage; gi ven the existence of linkage, an adjusted LD test useful for fins mapping c an be constructed; covariate effects can be flexibly modeled; and families containing a single child and families containing multiple offspring can be combined for a single analysis (capitalizing on the LD information provide d by single-child families and the combined linkage and LD information prov ided by multiple offspring). The basic features of the regression model are presented, as well as discussions of potential applications and critical s tatistical issues. Genet. Epidemiol. 19(Suppl 1):S78-S84, 2000. (C) 2000 Wi ley-Liss, Inc.