Using data from a large Australian twin sample we examined the extent to which genetic variation in the Big Three personality dimensions (positive emotionality, negative emotionality, and constraint) and their lower-order components explained genetic variation in the risk for disordered gambling (DG) among men and women. Genetic influences contributing to individual differences in normal-range personality traits explained over 40% of the genetic risk for DG, with a larger contribution among women than among men. The largest and most robust contributions came from the higher-order personality dimension of negative emotionality and its two lower-order dimensions of alienation and aggression. Surprisingly, low self-control was associated with the genetic risk for DG only among women, and risk-taking/sensation-seeking did not explain genetic risk for DG in either sex. The results of this study have implications for the causes of comorbidity between DG and other psychiatric disorders, the search for genes associated with DG risk, and the possibility of sex differences in the etiology of DG. Using a broad-band inventory of personality supports the conclusion that there probably is a substantial proportion of genetic variation in DG that cannot be explained by individual differences in personality.
A genetic factor model is introduced for decomposition of group differences of the means of phenotypic behavior as well as individual differences when the research variables under consideration are ordered categorical. The model employs the general Genetic Factor Model proposed by Neale and Cardon (Methodology for genetic studies of twins and families, 1992) and, more specifically, the extension proposed by Dolan et al. (Behav Genet 22: 319–335, 1992) which enables decomposition of group differences of the means associated with genetic and environmental factors. Using a Latent Response Variable (LRV) formulation (Muthén and Asparouhov, Latent variable analysis with categorical outcomes: multiple-group and growth modeling in Mplus. Mplus web notes: No. 4, Version 5, 2002), proportional differences of response categories between groups are modeled within the genetic factor model in terms of the distributional differences of latent response variables assumed to underlie the observed ordered categorical variables. Use of the proposed model is illustrated using a measure of conservatism in the data collected from the Australian Twin Registry.
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