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Dimensionality and Genetic Correlates of Problem Behavior in Low-Income African American Adolescents
Shawn J Latendresse1, David B Henry2, Steven H Aggen3
1a Department of Psychology and Neuroscience , Baylor University.
Abstract:
Researchers have long observed that problem behaviors tend to cluster together, particularly among adolescents. Epidemiological studies have suggested that this covariation is due, in part, to common genetic influences, and a number of plausible candidates have emerged as targets for investigation. To date, however, genetic association studies of these behaviors have focused mostly on unidimensional models of individual phenotypes within European American samples. Herein, we compared a series of confirmatory factor models to best characterize the structure of problem behavior (alcohol and marijuana use, sexual behavior, and disruptive behavior) within a representative community-based sample of 592 low-income African American adolescents (50.3% female), ages 13 to 18. We further explored the extent to which 3 genes previously implicated for their role in similar behavioral dimensions (CHRM2, GABRA2, and OPRM1) independently accounted for variance within factors specified in the best-fitting model. Supplementary analyses were conducted to derive comparative estimates for the predictive utility of these genes in more traditional unidimensional models. Findings provide initial evidence for a bifactor structure of problem behavior among African American adolescents and highlight novel genetic correlates of specific behavioral dimensions otherwise undetected in an orthogonal syndromal factor. Implications of this approach include increased precision in the assessment of problem behavior, with corresponding increases in the reliability and validity of identified genetic associations. As a corollary, the comparison of primary and supplementary association analyses illustrates the potential for overlooking and/or overinterpreting meaningful genetic effects when failing to adequately account for phenotypic complexity.
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