title: Ordered-subset analysis (OSA) for family-based association mapping of complex traits.
abstract: Association analysis provides a powerful tool for complex disease gene mapping. However, in the presence of genetic heterogeneity, the power for association analysis can be low since only a fraction of the collected families may carry a specific disease susceptibility allele. Ordered-subset analysis (OSA) is a linkage test that can be powerful in the presence of genetic heterogeneity. OSA uses trait-related covariates to identify a subset of families that provide the most evidence for linkage. A similar strategy applied to genetic association analysis would likely result in increased power to detect association. Association in the presence of linkage (APL) is a family-based association test (FBAT) for nuclear families with multiple affected siblings that properly infers missing parental genotypes when linkage is present. We propose here APL-OSA, which applies the OSA method to the APL statistic to identify a subset of families that provide the most evidence for association. A permutation procedure is used to approximate the distribution of the APL-OSA statistic under the null hypothesis that there is no relationship between the family-specific covariate and the family-specific evidence for allelic association. We performed a comprehensive simulation study to verify that APL-OSA has the correct type I error rate under the null hypothesis. This simulation study also showed that APL-OSA can increase power relative to other commonly used association tests (APL, FBAT and FBAT with covariate adjustment) in the presence of genetic heterogeneity. Finally, we applied APL-OSA to a family study of age-related macular degeneration, where cigarette smoking was used as a covariate.
authors.affiliation: Center for Human Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA.
authors.forename: Ren-Hua
authors.initials: RH
authors.lastname: Chung
authors.forename: Silke
authors.initials: S
authors.lastname: Schmidt
authors.forename: Eden R
authors.initials: ER
authors.lastname: Martin
authors.forename: Elizabeth R
authors.initials: ER
authors.lastname: Hauser
mesh_terms: D000375:Aging; D000483:Alleles; D003198:Computer Simulation; D005787:Gene Frequency; D005808:Genes, Recessive; D008040:Genetic Linkage; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005838:Genotype; D006801:Humans; D008268:Macular Degeneration / Q000235:genetics; D008957:Models, Genetic; D015233:Models, Statistical; D015203:Reproducibility of Results; D012107:Research Design; D012907:Smoking