title: Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation.
abstract: Purcell (Twin Res 5:554-571, 2002) proposed a bivariate biometric model for testing and quantifying the interaction between latent genetic influences and measured environments in the presence of gene-environment correlation. Purcell's model extends the Cholesky model to include gene-environment interaction. We examine a number of closely related alternative models that do not involve gene-environment interaction but which may fit the data as well as Purcell's model. Because failure to consider these alternatives could lead to spurious detection of gene-environment interaction, we propose alternative models for testing gene-environment interaction in the presence of gene-environment correlation, including one based on the correlated factors model. In addition, we note mathematical errors in the calculation of effect size via variance components in Purcell's model. We propose a statistical method for deriving and interpreting variance decompositions that are true to the fitted model.
authors.affiliation: Department of Health Studies, University of Chicago, 5841 S. Maryland Ave., MC 2007, Chicago, IL 60637, USA. prathouz@uchicago.edu
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Rathouz
authors.forename: Carol A
authors.initials: CA
authors.lastname: Van Hulle
authors.forename: Joseph Lee
authors.initials: JL
authors.lastname: Rodgers
authors.forename: Irwin D
authors.initials: ID
authors.lastname: Waldman
authors.forename: Benjamin B
authors.initials: BB
authors.lastname: Lahey
mesh_terms: D001699:Biometry; D003627:Data Interpretation, Statistical; D004777:Environment; D014644:Genetic Variation; D005823:Genetics; D006801:Humans; D008954:Models, Biological; D008957:Models, Genetic; D015233:Models, Statistical; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012106:Research; D018433:Twin Studies as Topic