title: The trimmed-haplotype test for linkage disequilibrium.
abstract: Single-marker linkage-disequilibrium (LD) methods cannot fully describe disequilibrium in an entire chromosomal region surrounding a disease allele. With the advent of myriad tightly linked microsatellite markers, we have an opportunity to extend LD analysis from single markers to multiple-marker haplotypes. Haplotype analysis has increased statistical power to disclose the presence of a disease locus in situations where it correctly reflects the historical process involved. For maximum efficiency, evidence of LD ought to come not just from a single haplotype, which may well be rare, but in addition from many similar haplotypes that could have descended from the same ancestral founder but have been trimmed in succeeding generations. We present such an analysis, called the "trimmed-haplotype method." We focus on chromosomal regions that are small enough that disequilibrium in significant portions of them may have been preserved in some pedigrees and yet that contain enough markers to minimize coincidental occurrence of the haplotype in the absence of a disease allele: perhaps regions 1-2 cM in length. In general, we could have no idea what haplotype an ancestral founder carried generations ago, nor do we usually have a precise chromosomal location for the disease-susceptibility locus. Therefore, we must search through all possible haplotypes surrounding multiple locations. Since such repeated testing obliterates the sampling distribution of the test, we employ bootstrap methods to calculate significance levels. Trimmed-haplotype analysis is performed on family data in which genotypes have been assembled into haplotypes. It can be applied either to conventional parent-affected-offspring triads or to multiplex pedigrees. We present a method for summarizing the LD evidence, in any pedigree, that can be employed in trimmed-haplotype analysis as well as in other methods.
authors.affiliation: Virginia Institute for Psychiatric and Behavioral Genetics, Medical College of Virginia, Virginia Commonwealth University, Richmond, VA, 23298, USA. cmaclean@bara.psi.vcu.edu
authors.forename: C J
authors.initials: CJ
authors.lastname: MacLean
authors.forename: R B
authors.initials: RB
authors.lastname: Martin
authors.forename: P C
authors.initials: PC
authors.lastname: Sham
authors.forename: H
authors.initials: H
authors.lastname: Wang
authors.forename: R E
authors.initials: RE
authors.lastname: Straub
authors.forename: K S
authors.initials: KS
authors.lastname: Kendler
mesh_terms: D000483:Alleles; D002874:Chromosome Mapping / Q000379:methods* / Q000706:statistics & numerical data; D002877:Chromosomes, Human / Q000235:genetics; D005260:Female; D005787:Gene Frequency / Q000235:genetics; D030342:Genetic Diseases, Inborn / Q000235:genetics; D018740:Genetic Heterogeneity; D005819:Genetic Markers / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics; D006239:Haplotypes / Q000235:genetics*; D006720:Homozygote; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics*; D008297:Male; D008957:Models, Genetic; D009154:Mutation / Q000235:genetics; D010375:Pedigree; D011336:Probability; D011995:Recombination, Genetic / Q000235:genetics; D012984:Software
chemical_list: D005819:Genetic Markers