title: Multilocus linkage tests based on affected relative pairs.
abstract: For complex diseases, recent interest has focused on methods that take into account joint effects at interacting loci. Conditioning on effects of disease loci at known locations can lead to increased power to detect effects at other loci. Moreover, use of joint models allows investigation of the etiologic mechanisms that may be involved in the disease. Here we present a method for simultaneous analysis of the joint genetic effects at several loci that uses affected relative pairs. The method is a generalization of the two-locus LOD-score analysis for affected sib pairs proposed by Cordell et al. We derive expressions for the relative risk, lambdaR, to a relative of an affected individual, in terms of the additive and epistatic components of variance at an arbitrary number of disease loci, and we show how these can be used to fit a likelihood model to the identity-by-descent sharing among pairs of affected relatives in extended pedigrees. We implement the method by use of a stepwise strategy in which, given evidence of linkage to disease at m-1 locations on the genome, we calculate the conditional likelihood curve across the genome for an mth disease locus, using multipoint methods similar to those proposed by Kruglyak et al. We evaluate the properties of our method by use of simulated data and present an application to real data from families with insulin-dependent diabetes mellitus.
authors.affiliation: Department of Medical Genetics, Wellcome Trust Centre for the Study of Molecular Mechanisms in Disease, Cambridge Institute for Medical Research, Addenbrookes Hospital, Cambridge, CB2 2XY, England, United Kingdom. heather.cordell@cimr.cam.ac.uk
authors.forename: H J
authors.initials: HJ
authors.lastname: Cordell
authors.forename: G C
authors.initials: GC
authors.lastname: Wedig
authors.forename: K B
authors.initials: KB
authors.lastname: Jacobs
authors.forename: R C
authors.initials: RC
authors.lastname: Elston
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; D004843:Epistasis, Genetic; D005260:Female; D030342:Genetic Diseases, Inborn / Q000235:genetics*; D008040:Genetic Linkage / Q000235:genetics*; D005819:Genetic Markers / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics; D006680:HLA Antigens / Q000235:genetics; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D016555:Matched-Pair Analysis; D008957:Models, Genetic; D009679:Nuclear Family; D010375:Pedigree; D019683:Penetrance; D012984:Software
chemical_list: D005819:Genetic Markers; D006680:HLA Antigens