Department of Education, Faculty of Behavioral and Social Sciences, University of Amsterdam, Nieuwe Prinsengracht 130, 1018 VZ, Amsterdam, The Netherlands.
J Stud Alcohol Drugs. 2010 Jan;71(1):5-14. doi: 10.15288/jsad.2010.71.5.
Among Finnish adolescent twins, we compared (a) a model that describes a direct impact of liability to tobacco use on cannabis and other illicit drug use with (b) a model that included a shared underlying liability for these substances. Furthermore, the extent to which genetic and environmental influences contribute to the covariation between liabilities to use these substances was examined.
Tobacco and illicit drug use were assessed at age 17.5 years. Twin data on 3,744 individuals were analyzed using standard biometrical methods. Two alternative multivariate models were fi t and compared with Mx, a statistical program for genetic model fitting.
The multivariate model, including a direct impact of the initiation of tobacco use on illicit drug use, provided the best fit to the data. In this model, the total variation in the initiation of illicit drugs was decomposed to genetic factors (32%), common environmental factors (20%), unique environmental factors (8%), and a component due to initiation of smoking (40%). Most variation in the progression of illicit drug use was the result of initiation of smoking and illicit drug use (83%).
Liability to initiate smoking directly affects illicit drug use in our best-fitting model. Our findings suggest that several common genetic influences may be related to tobacco use and illicit drugs but that a search for specific genes underlying illicit drug use is justifi ed as well. Such specific genes may hold a key to understanding biological vulnerabilities that lead to illicit drug use, which could aid in the development of targeted interventions.
在芬兰青少年双胞胎中,我们比较了(a)一个描述易患烟草使用对大麻和其他非法药物使用直接影响的模型,以及(b)一个包含这些物质共同潜在易患性的模型。此外,还研究了遗传和环境影响在这些物质使用易患性的协变中所占的程度。
在 17.5 岁时评估烟草和非法药物的使用情况。使用标准生物计量方法分析了 3744 名个体的双胞胎数据。使用遗传模型拟合的统计程序 Mx 拟合并比较了两种替代的多变量模型。
包括烟草使用对非法药物使用的直接影响的多变量模型为数据提供了最佳拟合。在这个模型中,非法药物使用开始的总变化被分解为遗传因素(32%)、共同环境因素(20%)、独特环境因素(8%)和吸烟开始的一个组成部分(40%)。非法药物使用进展的大部分变化是吸烟和非法药物使用开始的结果(83%)。
在我们的最佳拟合模型中,吸烟易患性直接影响非法药物的使用。我们的研究结果表明,几种共同的遗传影响可能与烟草使用和非法药物有关,但也有理由寻找非法药物使用背后的特定基因。这些特定的基因可能是理解导致非法药物使用的生物脆弱性的关键,这有助于开发有针对性的干预措施。