title: A haplotype-based test of association using data from cohort and nested case-control epidemiologic studies.
abstract: Haplotype-based risk models can lead to powerful methods for detecting the association of a disease with a genomic region of interest. In population-based studies of unrelated individuals, however, the haplotype status of some subjects may not be discernible without ambiguity from available locus-specific genotype data. A score test for detecting haplotype-based association using genotype data has been developed in the context of generalized linear models for analysis of data from cross-sectional and retrospective studies. In this article, we develop a test for association using genotype data from cohort and nested case-control studies where subjects are prospectively followed until disease incidence or censoring (end of follow-up) occurs. Assuming a proportional hazard model for the haplotype effects, we derive an induced hazard function of the disease given the genotype data, and hence propose a test statistic based on the associated partial likelihood. The proposed test procedure can account for differential follow-up of subjects, can adjust for possibly time-dependent environmental co-factors and can make efficient use of valuable age-at-onset information that is available on cases. We provide an algorithm for computing the test statistic using readily available statistical software. Utilizing simulated data in the context of two genomic regions GPX1 and GPX3, we evaluate the validity of the proposed test for small sample sizes and study its power in the presence and absence of missing genotype data.
authors.affiliation: Biostatistics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20852, USA. chenjin@mail.nih.gov
authors.forename: Jinbo
authors.initials: J
authors.lastname: Chen
authors.forename: Ulrike
authors.initials: U
authors.lastname: Peters
authors.forename: Charles
authors.initials: C
authors.lastname: Foster
authors.forename: Nilanjan
authors.initials: N
authors.lastname: Chatterjee
mesh_terms: D000465:Algorithms; D016022:Case-Control Studies; D015331:Cohort Studies; D005787:Gene Frequency; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease / Q000235:genetics; D005979:Glutathione Peroxidase / Q000235:genetics; D006239:Haplotypes; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D009369:Neoplasms / Q000453:epidemiology / Q000235:genetics / Q000517:prevention & control; D020641:Polymorphism, Single Nucleotide; D012107:Research Design; D000094765:Glutathione Peroxidase GPX1
chemical_list: D005819:Genetic Markers; C486484:GPX3 protein, human; D005979:Glutathione Peroxidase; D000094765:Glutathione Peroxidase GPX1; C000722067:GPX1 protein, human