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Genetically Informed Regression Analysis: Application to Aggression Prediction by Inattention and Hyperactivity in Children and Adults
Behavior Genetics ( IF 2.6 ) Pub Date : 2020-12-01 , DOI: 10.1007/s10519-020-10025-9
Dorret I Boomsma 1, 2 , Toos C E M van Beijsterveldt 1 , Veronika V Odintsova 1, 2 , Michael C Neale 3 , Conor V Dolan 1, 2
Affiliation  

We present a procedure to simultaneously fit a genetic covariance structure model and a regression model to multivariate data from mono- and dizygotic twin pairs to test for the prediction of a dependent trait by multiple correlated predictors. We applied the model to aggressive behavior as an outcome trait and investigated the prediction of aggression from inattention (InA) and hyperactivity (HA) in two age groups. Predictions were examined in twins with an average age of 10 years (11,345 pairs), and in adult twins with an average age of 30 years (7433 pairs). All phenotypes were assessed by the same, but age-appropriate, instruments in children and adults. Because of the different genetic architecture of aggression, InA and HA, a model was fitted to these data that specified additive and non-additive genetic factors (A and D) plus common and unique environmental (C and E) influences. Given appropriate identifying constraints, this ADCE model is identified in trivariate data. We obtained different results for the prediction of aggression in children, where HA was the more important predictor, and in adults, where InA was the more important predictor. In children, about 36% of the total aggression variance was explained by the genetic and environmental components of HA and InA. Most of this was explained by the genetic components of HA and InA, i.e., 29.7%, with 22.6% due to the genetic component of HA. In adults, about 21% of the aggression variance was explained. Most was this was again explained by the genetic components of InA and HA (16.2%), with 8.6% due to the genetic component of InA.



中文翻译:

遗传信息回归分析:在儿童和成人注意力不集中和多动症预测中的应用

我们提出了一种同时拟合遗传协方差结构模型和回归模型的程序,以对来自单卵和异卵双胞胎的多变量数据进行拟合,以测试多个相关预测因子对依赖性状的预测。我们将该模型应用于攻击行为作为结果特征,并研究了两个年龄组中注意力不集中 (InA) 和多动 (HA) 攻击行为的预测。对平均年龄为 10 岁的双胞胎(11,345 对)和平均年龄为 30 岁的成年双胞胎(7433 对)进行了预测。在儿童和成人中,所有表型均通过相同但适合年龄的仪器进行评估。由于攻击的不同遗传结构,InA 和 HA,为这些数据拟合了一个模型,该模型指定了加性和非加性遗传因素(A 和 D)以及常见和独特的环境(C 和 E)影响。给定适当的识别约束,这个 ADCE 模型在三变量数据中被识别。我们在预测儿童攻击性方面获得了不同的结果,其中 HA 是更重要的预测因子,而在成人中,InA 是更重要的预测因子。在儿童中,大约 36% 的总攻击性变异是由 HA 和 InA 的遗传和环境成分解释的。其中大部分是由 HA 和 InA 的遗传成分解释的,即 29.7%,22.6% 是由于 HA 的遗传成分。在成年人中,大约 21% 的攻击性变异得到了解释。大多数情况下,这再次由 InA 和 HA 的遗传成分(16.2%)解释,其中 8 个。

更新日期:2020-12-01
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