title: Adjusting for confounding due to population admixture when estimating the effect of candidate genes on quantitative traits.
abstract: When analyzing the relationship between allelic variability and traits, a potential source of confounding is population admixture. An approach to adjusting for potential confounding due to population admixture when estimating the influence of allelic variability at a candidate gene is presented. The approach involves augmenting linear regression models with additional regressors. Family genotype data are used to define the regressors, and inclusion of the regressors ensures that, even in the presence of population admixture, the estimates of the regression coefficients that parameterize the influence of allelic variability on the trait are unbiased. The approach is illustrated through an analysis of the influence of apolipoprotein E genotype on plasma low density lipoprotein cholesterol concentrations.
authors.affiliation: Department of Statistics, Columbia University, New York, N.Y., USA.
authors.forename: Q
authors.initials: Q
authors.lastname: Yang
authors.forename: D
authors.initials: D
authors.lastname: Rabinowitz
authors.forename: C
authors.initials: C
authors.lastname: Isasi
authors.forename: S
authors.initials: S
authors.lastname: Shea
mesh_terms: D000483:Alleles; D001057:Apolipoproteins E / Q000235:genetics; D002648:Child; D008078:Cholesterol, LDL / Q000097:blood; D015986:Confounding Factors, Epidemiologic; D005828:Genetics, Population; D005838:Genotype; D006801:Humans; D016014:Linear Models; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D010375:Pedigree; D019655:Quantitative Trait, Heritable
chemical_list: D001057:Apolipoproteins E; D008078:Cholesterol, LDL