Twin Family Study of Vulnerability to Substance Abuse

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DESCRIPTION (provided by applicant): We seek to continue the longitudinal study and data analysis of two population-based cohorts consisting of 666 twin pairs. The younger cohort, originally recruited at age 11, prior to significant substance use, will be followed through age 24-25. The older cohort, originally recruited at age 17, will be assessed through age 29-30. We hypothesize that an inherited predisposition to substance use disorder (SUD) is expressed through psychiatric, personality, psychosocial, and psychophysiological characteristics related to behavioral disinhibition and negative affective states that can be traced to pre-adolescence. Our findings to date suggest that externalizing disorders are highly comorbid and familial, associated with the personality dimension of constraint, and predictive of the development of adult antisocial behavior and SUDs. The liability for this collection of attributes is heritable and associated with reduced amplitude of the P3 event-related potential and individual differences in autonomic reactivity. However, findings from our younger cohort indicate that during early adolescence, a substantial shared environmental contribution to the development of externalizing and SUDs is present, with specific environmental factors like parent-child conflict likely to have etiologic significance. The personality dimension of negative emotionality and internalizing psychopathology are also associated with the development of SUDs, but predicted effects are less consistent than for behavioral disinhibition. We aim to identify mechanisms through which genetic and environmentally mediated risk factors translate into outcomes and understand how important life transitions contribute to the persistence and desistance of substance abuse. We will also establish immortalized DNA cell lines to facilitate future studies examining candidate gene associations with SUD phenotypes, investigate trajectories related to the development of SUDs using latent growth modeling, and evaluate models for gene-environment contributions to their development.