title: Optimal strategies for mapping complex diseases in the presence of multiple loci.
abstract: Recent advances in genome technology have led to mapping and subsequent isolation, by positional cloning, of a number of genes for common and/or complex human diseases. It therefore will be possible to utilize information about a known locus in the search for additional, perhaps less penetrant, genes for a particular disease. It is also unclear, under these situations, what the optimal sampling strategy should be. To address these questions, we have calculated the expected LOD score for localizing one locus in a variety of two-locus models of disease, for four different pedigree structures, and under three different scenarios regarding knowledge/testing of one of the two loci. These design considerations are evaluated by use of a cost function that incorporates the costs of ascertaining different family structures, the relative costs of genotyping and mutation testing family members, and the amount of information provided by each family structure and testing scenario. The results indicate that, in most cases, affected sib pairs are a particularly poor strategy, especially when linkage or mutation data are available at the known locus. We also demonstrate that prescreening the sample of families for mutations at known susceptibility loci is, in general, a cost-effective strategy.
authors.affiliation: Unit of Genetic Epidemiology, International Agency for Research on Cancer, Lyon, France. goldgar@iarc.fr
authors.forename: D E
authors.initials: DE
authors.lastname: Goldgar
authors.forename: D F
authors.initials: DF
authors.lastname: Easton
mesh_terms: D002874:Chromosome Mapping / Q000191:economics / Q000379:methods*; D030342:Genetic Diseases, Inborn / Q000453:epidemiology / Q000235:genetics*; D005820:Genetic Testing; D006801:Humans; D008126:Lod Score; D008957:Models, Genetic; D009154:Mutation; D009679:Nuclear Family; D012107:Research Design; D012307:Risk Factors; D012494:Sampling Studies; D012680:Sensitivity and Specificity