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• W29034788 abstract "We propose robust and e±cient tests and estimators for gene-environment/genedrug interactions in family-based association studies. The methodology is designed for studies in which haplotypes, quantitative phenotypes and complex exposure/treatment variables are analyzed. Using causal inference methodology, we derive family-based association tests and estimators for the genetic main effects and the interactions. The tests and estimators are robust against population admixture and stratīcation without requiring adjustment for confounding variables. We illustrate the practical relevance of our approach by an application to a COPD study. The data analysis suggests a gene-environment interaction between a SNP in the Serpine gene and smoking status/pack years of smoking that reduces the FEV1 volume by about 0.02 liter per pack year of smoking. Simulation studies show that the proposed methodology is su±ciently powered for realistic sample sizes and that it provides valid tests and effect size estimators in the presence of admixture and stratification. A unifying approach for haplotype analysis of quantitative traits in family-based association studies: Testing and estimating gene-environment interactions with complex exposure variables Stijn Vansteelandt, Dawn L. DeMeo, Jessica Su, Jordan Smoller, Amy J. Murphy, Matt McQueen, Kady Schneiter, Juan C. Celedon, Scott T. Weiss, Edwin K. Silverman and Christoph Lange" @default.
• W29034788 created "2016-06-24" @default.
• W29034788 creator A5002736890 @default.
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• W29034788 date "2006-01-01" @default.
• W29034788 modified "2023-09-23" @default.
• W29034788 title "A unifying approach for haplotype analysis of quantitative traits in family-based association studies: Testing and estimating gene-environment interactions with complex exposure variables" @default.
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• W29034788 hasPublicationYear "2006" @default.
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