Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation
Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation
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DOI：
10.1007/s10519-008-9193-4
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发表时间：
2008-05-01
影响因子：
2.6
通讯作者：
Lahey, Benjamin B.
中科院分区：
文献类型：
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作者：
Rathouz, Paul J.;Van Hulle, Carol A.;Lahey, Benjamin B.
珀塞尔（Twin Res 5：554-571，2002）提出了一种双变量生物计量模型，用于在存在基因-环境相关性的情况下测试和量化潜在遗传影响与测量环境之间的相互作用。珀塞尔的模型扩展了Cholesky模型，包括基因-环境相互作用。我们研究了一些密切相关的替代模型，不涉及基因-环境相互作用，但可能适合的数据以及珀塞尔的模型。由于不考虑这些替代方案可能会导致虚假的检测基因-环境相互作用，我们提出了替代模型来测试基因-环境相互作用的基因-环境相关性的存在下，包括一个基于相关因素模型。此外，我们注意到在珀塞尔模型中通过方差分量计算效应量的数学错误。我们提出了一个统计方法，用于推导和解释方差分解，是真实的拟合模型。
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.