For investigating haplotype-environment interactions in case-control studies, one can implement statistical methods based either on a retrospective likelihood (modeling the probability of haplotype and environment conditional on disease status) or a prospective likelihood (modeling the probability of disease status conditional on haplotype and environment). Retrospective approaches are generally more powerful than prospective approaches, but require an explicit model of the joint distribution of haplotype and environmental factors in the sample with the latter being particularly unattractive to specify. To resolve this issue, we propose a number of simple retrospective procedures for haplotype-environment interaction analysis that do not require explicit modeling of environmental covariates in the sample. We first consider a cases-only procedure, followed by a simple likelihood for case-control data that is proportional to the full-retrospective likelihood. Finally, we consider a retrospective procedure for inference on haplotype-environment interaction effects in matched or finely-stratified case-control studies. Our methods are based on the assumptions that haplotypes and environmental covariates are independent in the target population and that disease is rare. We illustrate our approaches using case-control data from the Finland-United States Investigation of Non-Insulin Dependent Diabetes Mellitus (FUSION) genetic study and simulated data.
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Univ Alabama Birmingham, Dept Biostat, Sect Stat Genet, Birmingham, AL 35294 USAUniv Alabama Birmingham, Dept Biostat, Sect Stat Genet, Birmingham, AL 35294 USA
Li, Jun
Zhang, Kui
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Univ Alabama Birmingham, Dept Biostat, Sect Stat Genet, Birmingham, AL 35294 USAUniv Alabama Birmingham, Dept Biostat, Sect Stat Genet, Birmingham, AL 35294 USA
Zhang, Kui
Yi, Nengjun
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Univ Alabama Birmingham, Dept Biostat, Sect Stat Genet, Birmingham, AL 35294 USAUniv Alabama Birmingham, Dept Biostat, Sect Stat Genet, Birmingham, AL 35294 USA
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DKFZ, German Canc Res Ctr, Div Canc Epidemiol, Unit Genet Epidemiol,Dept Canc Epidemiol, DE-69120 Heidelberg, GermanyDKFZ, German Canc Res Ctr, Div Canc Epidemiol, Unit Genet Epidemiol,Dept Canc Epidemiol, DE-69120 Heidelberg, Germany
Hein, Rebecca
Beckmann, Lars
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DKFZ, German Canc Res Ctr, Div Canc Epidemiol, Unit Genet Epidemiol,Dept Canc Epidemiol, DE-69120 Heidelberg, GermanyDKFZ, German Canc Res Ctr, Div Canc Epidemiol, Unit Genet Epidemiol,Dept Canc Epidemiol, DE-69120 Heidelberg, Germany
Beckmann, Lars
Chang-Claude, Jenny
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DKFZ, German Canc Res Ctr, Div Canc Epidemiol, Unit Genet Epidemiol,Dept Canc Epidemiol, DE-69120 Heidelberg, GermanyDKFZ, German Canc Res Ctr, Div Canc Epidemiol, Unit Genet Epidemiol,Dept Canc Epidemiol, DE-69120 Heidelberg, Germany
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Univ Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USAUniv Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA
Lobach, Iryna
Sampson, Joshua
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NCI, Biostat Branch, Div Canc Epidemiol & Genet, NIH, Bethesda, MD 20892 USAUniv Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA
Sampson, Joshua
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Lobach, Siarhei
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Alekseyenko, Alexander
Piryatinska, Alexandra
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San Francisco State Univ, Dept Math, San Francisco, CA 94132 USAUniv Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA
Piryatinska, Alexandra
He, Tao
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San Francisco State Univ, Dept Math, San Francisco, CA 94132 USAUniv Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA
He, Tao
Zhang, Li
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Univ Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA
Univ Calif San Francisco, Dept Med, San Francisco, CA USAUniv Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA