Estimating two-stage models for genetic influences on alcohol, tobacco or drug use initiation and dependence vulnerability in twin and family data
Estimating two-stage models for genetic influences on alcohol, tobacco or drug use initiation and dependence vulnerability in twin and family data
复制标题
DOI：
10.1375/1369052022983
复制
发表时间：
2002-04-01
期刊：
影响因子：
--
通讯作者：
Madden, PAF
中科院分区：
文献类型：
--
作者：
Heath, AC;Martin, NG;Madden, PAF
关于酒精、烟草或药物依赖风险的基因研究必须考虑到开始使用的风险因素和使用者的依赖或其他结果的风险因素部分重叠。除了在启动和依赖的遗传和环境风险因素完全重叠或不相关的极端情况下，对于如何最好地估计双胞胎和家庭数据中启动和依赖之间的遗传或环境相关性的程度，还没有达成共识。我们通过计算机模拟探索当启动只能定义为二元变量时，模型错误指定导致的遗传和环境参数估计的偏差。对于合理的模拟参数值，我们考虑的两阶段遗传模型产生了对依赖性的遗传和环境方差的估计，尽管有偏差，但与真实值并没有太大差异。然而，对启动和依赖之间的遗传（或环境）相关性的估计可能存在严重偏差，并且在不同的两阶段模型下可能存在显着差异。除非外部数据有利于选择一种特定模型，否则此类估计可能没有什么可信度。如果可以将起始作为多类别变量进行评估（例如从不与早发与晚发用户），并且至少有两个类别可在有依赖风险的用户中进行测量，则可以避免这些问题。在这些条件下，在某些分布假设下，恢复模拟的遗传和环境相关性成为可能。该模型对澳大利亚双胞胎吸烟数据的说明性应用证实了吸烟持续性的显着遗传性（42%），与开始吸烟的遗传影响的重叠最小。
Genetic research on risk of alcohol, tobacco or drug dependence must make allowance for the partial overlap of risk-factors for initiation of use, and risk-factors for dependence or other outcomes in users. Except in the extreme cases where genetic and environmental risk-factors for initiation and dependence overlap completely or are uncorrelated, there is no consensus about how best to estimate the magnitude of genetic or environmental correlations between Initiation and Dependence in twin and family data. We explore by computer simulation the biases to estimates of genetic and environmental parameters caused by model misspecification when Initiation can only be defined as a binary variable. For plausible simulated parameter values, the two-stage genetic models that we consider yield estimates of genetic and environmental variances for Dependence that, although biased, are not very discrepant from the true values. However, estimates of genetic (or environmental) correlations between Initiation and Dependence may be seriously biased, and may differ markedly under different two-stage models. Such estimates may have little credibility unless external data favor selection of one particular model. These problems can be avoided if Initiation can be assessed as a multiple-category variable (e.g. never versus early-onset versus later onset user), with at least two categories measurable in users at risk for dependence. Under these conditions, under certain distributional assumptions., recovery of simulated genetic and environmental correlations becomes possible, Illustrative application of the model to Australian twin data on smoking confirmed substantial heritability of smoking persistence (42%) with minimal overlap with genetic influences on initiation.