title: Robust multipoint simultaneous identical-by-descent mapping for two linked loci.
abstract: A challenging issue in genetic mapping of complex human diseases is localizing disease susceptibility genes when the genetic effects are small to moderate. There are greater complexities when multiple loci are linked to a chromosomal region. Liang et al. [Hum Hered 2001;51:64-78] proposed a robust multipoint method that can simultaneously estimate both the position of a trait locus and its effect on disease status by using affected sib pairs (ASPs). Based on the framework of generalized estimating equations (GEEs), the estimate and standard error of the position of a trait locus are robust to different genetic models. To utilize other relative pairs collected in pedigree data, Schaid et al. [Am J Hum Genet 2005;76:128-138] extended Liang's method to various types of affected relative pairs (ARPs) by two approaches: unconstrained and constrained methods. However, the above methods are limited to situations in which only one trait locus exists on the chromosome of interest. The mean functions are no longer correctly specified when there are multiple causative loci linked to a chromosomal region. To overcome this, Biernacka et al. [Genet Epidemiol 2005;28:33-47] considered the multipoint methods for ASPs to allow for two linked disease genes. We further generalize the approach to cover other types of ARPs. To reflect realistic situations for complex human diseases, we set modest sizes of genetic effects in our simulation. Our results suggest that several hundred independent pedigrees are needed, and markers with high information, to provide reliable estimates of trait locus positions and their confidence intervals. Bootstrap resampling can correct the downward bias of the robust variance for location estimates. These methods are applied to a prostate cancer linkage study on chromosome 20 and compared with the results for the one-locus model [Am J Hum Genet 2005;76:128-138]. We have implemented the multipoint IBD mapping for one and two linked loci in our software GEEARP, which allows analyses for five general types of ARPs.
authors.affiliation: Institute of Epidemiology, National Taiwan University, Taipei, Taiwan.
authors.forename: Wan-Yu
authors.initials: WY
authors.lastname: Lin
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Schaid
mesh_terms: D015982:Bias; D002874:Chromosome Mapping / Q000379:methods* / Q000706:statistics & numerical data; D002890:Chromosomes, Human, Pair 20 / Q000235:genetics; D005260:Female; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D006801:Humans; D008297:Male; D008957:Models, Genetic; D010375:Pedigree; D011471:Prostatic Neoplasms / Q000235:genetics; D035781:Siblings; D012984:Software
chemical_list: D005819:Genetic Markers