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Updated: Jul 7, 2026

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease
Published on: January 7, 2014
Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of
Paul J Rathouz1, Carol A Van Hulle, Joseph Lee Rodgers
1Department of Health Studies, University of Chicago, 5841 S. Maryland Ave., MC 2007, Chicago, IL 60637, USA. prathouz@uchicago.edu
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.
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