This is a competitive renewal application. The original proposal developed statistical methods for addressing sampling issues arising in human genetics research. The current proposal extends this work by developing methods to handle sampling differences across genetic linkage studies. Discovery of specific genetic influences on the development of complex disorders in humans can facilitate early diagnosis and prevention, and broaden understanding of the contributions of both nature and nurture to the development of illness. In recent years, increased interest in complex disorders has fueled rapid development of complex investigative techniques, which in principle makes it possible to map genes of even small to moderate effect. However, a dearth of methods for what is sometimes called 'meta-analysis,' or the mathematically rigorous evaluation of the overall statistical evidence based on multiple sets of genetic data, has made it extremely difficult in practice to interpret the aggregate results of even the most sophisticated data analyses.
The aim of this proposal is to develop and evaluate mathematically rigorous methods for representing the strength of the genetic evidence based on multiple sets of data, where the data are inherently heterogeneous. We propose a novel approach to this problem, which we call sequential Bayesian. This approach has conceptual and computational advantages over existing alternatives, and offers a fully general way to handle differences across data sets. The new approach will be thoroughly developed and evaluated by comparison with existing methods, based on both analytic work and simulations studies. The objective will be to produce a comprehensive set of guidelines for investigators interested in analyzing multiple sets of genetic data. The project will also serve as a critical adjunct to ongoing studies of autistic disorder and panic disorder, for which the question of how to interpret accumulated genetic linkage evidence, is increasingly urgent.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
2R01MH052841-07A1
Application #
6285810
Study Section
Mammalian Genetics Study Section (MGN)
Program Officer
Moldin, Steven Owen
Project Start
1994-09-30
Project End
2004-11-30
Budget Start
2000-12-01
Budget End
2001-11-30
Support Year
7
Fiscal Year
2001
Total Cost
$208,750
Indirect Cost
Name
University of Iowa
Department
Genetics
Type
Schools of Public Health
DUNS #
041294109
City
Iowa City
State
IA
Country
United States
Zip Code
52242
Wassink, Thomas H; Vieland, Veronica J; Sheffield, Val C et al. (2008) Posterior probability of linkage analysis of autism dataset identifies linkage to chromosome 16. Psychiatr Genet 18:85-91
Bartlett, Christopher W; Vieland, Veronica J (2005) Two novel quantitative trait linkage analysis statistics based on the posterior probability of linkage: application to the COGA families. BMC Genet 6 Suppl 1:S121
George, Andrew W; Mangin, LaVonne A; Bartlett, Christopher W et al. (2005) Calculation of multipoint likelihoods using flanking marker data: a simulation study. BMC Genet 6 Suppl 1:S44
Bartlett, Christopher W; Goedken, Rhinda; Vieland, Veronica J (2005) Effects of updating linkage evidence across subsets of data: reanalysis of the autism genetic resource exchange data set. Am J Hum Genet 76:688-95
Wassink, Thomas H; Losh, Molly; Frantz, Rebecca S et al. (2005) A case of autism and uniparental disomy of chromosome 1. Hum Genet 117:200-6
Vieland, Veronica J; Huang, Jian (2003) Two-locus heterogeneity cannot be distinguished from two-locus epistasis on the basis of affected-sib-pair data. Am J Hum Genet 73:223-32
Collaborative Linkage Study of Autism (2001) An autosomal genomic screen for autism. Am J Med Genet 105:609-15
Vieland, V J; Wang, K; Huang, J (2001) Power to detect linkage based on multiple sets of data in the presence of locus heterogeneity: comparative evaluation of model-based linkage methods for affected sib pair data. Hum Hered 51:199-208
Wassink, T H; Piven, J; Patil, S R (2001) Chromosomal abnormalities in a clinic sample of individuals with autistic disorder. Psychiatr Genet 11:57-63
Wang, K; Huang, J; Vieland, V J (2000) The consistency of the posterior probability of linkage. Ann Hum Genet 64:533-53