Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Transitorium 2B03, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.
Amsterdam Public Health Research Institute, Amsterdam Medical Centre, Amsterdam, The Netherlands.
Behav Genet. 2021 May;51(3):237-249. doi: 10.1007/s10519-020-10035-7. Epub 2021 Feb 1.
The assumption in the twin model that genotypic and environmental variables are uncorrelated is primarily made to ensure parameter identification, not because researchers necessarily think that these variables are uncorrelated. Although the biasing effects of such correlations are well understood, a method to estimate these parameters in the twin model would be useful. Here we explore the possibility of relaxing this assumption by adding polygenic scores to the (univariate) twin model. We demonstrate that this extension renders the additive genetic (A)-common environmental (C) covariance (σ) identified. We study the statistical power to reject σ = 0 in the ACE model and present the results of simulations.
双生子模型的基本假设是基因型和环境变量是不相关的，主要是为了确保参数识别，而不是因为研究人员认为这些变量是不相关的。虽然这些相关性的偏倚效应已经得到很好的理解，但在双生子模型中估计这些参数的方法将是有用的。在这里，我们通过向（单变量）双生子模型中添加多基因分数来探索放松这一假设的可能性。我们证明了这种扩展使得加性遗传（A）-共同环境（C）协方差（σ）得以识别。我们研究了在 ACE 模型中拒绝 σ=0 的统计功效，并给出了模拟结果。
