title: Multipoint linkage analysis of the pseudoautosomal regions, using affected sibling pairs.
abstract: Affected sibling pairs are often the design of choice in linkage-analysis studies with the goal of identifying the genes that increase susceptibility to complex diseases. Methods for multipoint analysis based on sibling amount of sharing that is identical by descent are widely available, for both autosomal and X-linked markers. Such methods have the advantage of making few assumptions about the mode of inheritance of the disease. However, with this approach, data from the pseudoautosomal regions on the X chromosome pose special challenges. Same-sex sibling pairs will share, in that region of the 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 identical 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 excess 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 pseudoautosomal region are analyzed. For quantitative traits, we demonstrate, using the Haseman-Elston method, (1) the same inflation in type I error, in the absence of an appropriate correction, and (2) the inadequacy of permutation tests to estimate levels of significance when all phenotypic values are permuted, irrespective of gender. The proposed method is illustrated with a genome screen on 350 sibling pairs affected with type I diabetes.
authors.affiliation: Genome Therapeutics Corporation, Waltham, MA, 02453, USA. josee.dupuis@genomecorp.com.
authors.forename: J
authors.initials: J
authors.lastname: Dupuis
authors.forename: P
authors.initials: P
authors.lastname: Van Eerdewegh
mesh_terms: D000483:Alleles; D002874:Chromosome Mapping / Q000379:methods* / Q000706:statistics & numerical data; D002877:Chromosomes, Human / Q000235:genetics*; D003198:Computer Simulation; D003922:Diabetes Mellitus, Type 1 / Q000235:genetics; D005260:Female; D018740:Genetic Heterogeneity; D020022:Genetic Predisposition to Disease / Q000235:genetics; D006801:Humans; D008126:Lod Score; D008297:Male; D016555:Matched-Pair Analysis; D008957:Models, Genetic; D020412:Multifactorial Inheritance; D009679:Nuclear Family; D019655:Quantitative Trait, Heritable; D015203:Reproducibility of Results; D012107:Research Design; D012727:Sex Characteristics; D014960:X Chromosome / Q000235:genetics*