Moscati Arden, Verhulst Brad, McKee Kevin, Silberg Judy, Eaves Lindon
Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.
Behav Genet. 2018 Jan;48(1):22-33. doi: 10.1007/s10519-017-9882-y. Epub 2017 Nov 17.
Understanding the factors that contribute to behavioral traits is a complex task, and partitioning variance into latent genetic and environmental components is a useful beginning, but it should not also be the end. Many constructs are influenced by their contextual milieu, and accounting for background effects (such as gene-environment correlation) is necessary to avoid bias. This study introduces a method for examining the interplay between traits, in a longitudinal design using differential items in sibling pairs. The model is validated via simulation and power analysis, and we conclude with an application to paternal praise and ADHD symptoms in a twin sample. The model can help identify what type of genetic and environmental interplay may contribute to the dynamic relationship between traits using a cross-lagged panel framework. Overall, it presents a way to estimate and explicate the developmental interplay between a set of traits, free from many common sources of bias.
了解导致行为特征的因素是一项复杂的任务,将方差划分为潜在的遗传和环境成分是一个有益的开端,但不应就此止步。许多构念受到其背景环境的影响,考虑背景效应(如基因 - 环境相关性)对于避免偏差是必要的。本研究介绍了一种在纵向设计中使用同胞对中的差异项目来检验特征之间相互作用的方法。该模型通过模拟和功效分析进行了验证,最后我们将其应用于双胞胎样本中的父亲赞扬和多动症症状。该模型可以帮助使用交叉滞后面板框架识别哪种类型的遗传和环境相互作用可能导致特征之间的动态关系。总体而言,它提供了一种方法来估计和解释一组特征之间的发展性相互作用,而不受许多常见偏差来源的影响。