title: Allele-sharing statistics using information on family history.
abstract: When conducting genetic studies for complex traits, large samples are commonly required to detect new genetic factors. A possible strategy to decrease the sample size is to reduce heterogeneity using available information. In this paper we propose a new class of model-free linkage analysis statistics which takes into account the information given by the ungenotyped affected relatives (positive family history). This information is included into the scoring function of classical allele-sharing statistics. We studied pedigrees of affected sibling pairs with one ungenotyped affected relative. We show that, for rare allele common complex diseases, the proposed method increases the expected power to detect linkage. Allele-sharing methods were applied to the symptomatic osteoarthritis GARP study where taking into account the family-history increased considerably the evidence of linkage in the region of the DIO2 susceptibility locus.
authors: Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, The Netherlands. a.callegaro@lumc.nl
authors: A
authors: A
authors: Callegaro
authors: I
authors: I
authors: Meulenbelt
authors: M
authors: M
authors: Kloppenburg
authors: P E
authors: PE
authors: Slagboom
authors: J J
authors: JJ
authors: Houwing-Duistermaat
mesh_terms: D000483:Alleles; D018740:Genetic Heterogeneity; D008040:Genetic Linkage; D006801:Humans; D007453:Iodide Peroxidase / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D010003:Osteoarthritis / Q000235:genetics; D010375:Pedigree; D035781:Siblings; D018709:Statistics, Nonparametric; D000097564:Iodothyronine Deiodinase Type II
chemical_list: D007453:Iodide Peroxidase; D000097564:Iodothyronine Deiodinase Type II