title: Comparisons of case-selection approaches based on allele sharing and/or disease severity index: application to the GAW14 simulated data.
abstract: For mapping complex disease traits, linkage studies are often followed by a case-control association strategy in order to identify disease-associated genes/single-nucleotide polymorphisms (SNPs). Substantial efforts are required in selecting the most informative cases from a large collection of affected individuals in order to maximize the power of the study, while taking into consideration study cost. In this article, we applied and extended three case-selection strategies that use allele-sharing information method for families with multiple affected offspring to select most informative cases using additional information on disease severity. Our results revealed that most significant associations, as measured by the lowest p-values, were obtained from a strategy that selected a case with the most allele sharing with other affected sibs from linked families ("linked-best"), despite reduction in sample size resulting from discarding unlinked families. Moreover, information on disease severity appears to be useful to improve the ability to detect associations between markers and disease loci.
authors.affiliation: Department of Neurology, Boston University School of Public Health, Boston, Massachusetts, USA. liuc@bu.edu
authors.forename: Chunyu
authors.initials: C
authors.lastname: Liu
authors.forename: L Adrienne
authors.initials: LA
authors.lastname: Cupples
authors.forename: Josée
authors.initials: J
authors.lastname: Dupuis
mesh_terms: D000483:Alleles; D016022:Case-Control Studies; D016009:Chi-Square Distribution; D002874:Chromosome Mapping; D003198:Computer Simulation; D003226:Congresses as Topic; D030541:Databases, Genetic; D004194:Disease / Q000235:genetics*; D005260:Female; D005787:Gene Frequency / Q000235:genetics; D005819:Genetic Markers; D005828:Genetics, Population; D006801:Humans; D008297:Male; D010375:Pedigree; D035781:Siblings
chemical_list: D005819:Genetic Markers