Multipoint linkage analysis of the pseudoautosomal regions, using affectedsibling pairs

Affected sibling pairs are often the design of choice in linkage-analysis s tudies with the goal of identifying the genes that increase susceptibility to complex diseases. Methods for multipoint analysis based on sibling amoun t of sharing that is identical by descent are widely available, for both au tosomal and X-linked markers. Such methods have the advantage of making few assumptions about the mode of inheritance of the disease. However, with th is approach, data from the pseudoautosomal regions on the X chromosome pose special challenges. Same-sex sibling pairs will share, in that region of t he genome, more genetic material identical by descent, with and without the presence of a disease-susceptibility gene. This increased sharing will be more pronounced for markers closely linked to the sex-specific region. For the same reason, opposite-sex sibling pairs will share fewer alleles identi cal by descent. Failure to take this inequality in sharing into account may result in a false declaration of linkage if the study sample contains an e xcess of sex-concordant pairs, or a linkage may be missed when an excess of sex-discordant pairs is present. We propose a method to take into account this expected increase/decrease in sharing when markers in the pseudoautoso mal region are analyzed. For quantitative traits, we demonstrate, using the Haseman-Elston method, (1) the same inflation in type I error, in the abse nce of an appropriate correction, and (2) the inadequacy of permutation tes ts to estimate levels of significance when all phenotypic values are permut ed, irrespective of gender. The proposed method is illustrated with a genom e screen on 350 sibling pairs affected with type I diabetes.