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. 2011 Jul;41(4):459-75.
doi: 10.1007/s10519-010-9417-2. Epub 2010 Dec 12.

Psychometric and genetic architecture of substance use disorder and behavioral disinhibition measures for gene association studies

Brian M Hicks  1 , Benjamin D Schalet, Stephen M Malone, William G Iacono, Matt McGue
Affiliations

Psychometric and genetic architecture of substance use disorder and behavioral disinhibition measures for gene association studies

Brian M Hicks et al. Behav Genet. 2011 Jul.

Abstract

Using large twin, family, and adoption studies conducted at the Minnesota Center for Twin and Family Research, we describe our efforts to develop measures of substance use disorder (SUD) related phenotypes for targets in genome wide association analyses. Beginning with a diverse set of relatively narrow facet-level measures, we identified 5 constructs of intermediate complexity: nicotine, alcohol consumption, alcohol dependence, illicit drug, and behavioral disinhibition. The 5 constructs were moderately correlated (mean r = .57) reflecting a general externalizing liability to substance abuse and antisocial behavior. Analyses of the twin and adoption data revealed that this general externalizing liability accounted for much of the genetic risk in each of the intermediate-level constructs, though each also exhibited significant unique genetic and environmental risk. Additional analyses revealed substantial effects for age and sex, significant shared environmental effects, and that the mechanism of these shared environmental effects operates via siblings rather than parents. Our results provide a foundation for genome wide association analyses to detect risk alleles for SUDs as well as novel insights into genetic and environmental risk for SUDs.

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Figures

Figure 1
Figure 1
Results of confirmatory factor analyses depicting the hierarchical structure of substance use disorder and behavioral disinhibition measures.
Figure 2
Figure 2
Alcohol consumption factor scores plotted as a function of age, separately for male and female participants. The size of the circles is proportional to the number of participants with that age. For the purpose of visual presentation, the regression lines were fit using a piecewise linear regression fitting the data separately for the offspring (≤ 21 years) and parent (≥ 28 years) participants.
Figure 3
Figure 3
Behavioral disinhibition factor scores plotted as a function of age, separately for male and female participants. The size of the circles is proportional to the number of participants with that age. For the purpose of visual presentation, the regression lines were fit using a piecewise linear regression fitting the data separately for the offspring (≤ 21 years) and parent (≥ 28 years) participants.
Figure 4
Figure 4
Path diagram of a bivariate ACE Cholesky model for scores on the higher-order externalizing factor and the lower-order nicotine factor. This model decomposes the variance into additive genetic (A1, A2), shared environmental (C1, C2), and nonshared environmental (E1, E2) effects. a11, c11, and e11 are paths representing effects on externalizing only. a21, c21, and e21 are effects on externalizing that also contribute to nicotine. a22, c22, and e22 are effects that are unique to nicotine.
See this image and copyright information in PMC

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