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Longitudinal modeling of genetic and environmental influences on self-reported availability of psychoactive substances: alcohol, cigarettes, marijuana, cocaine and stimulants

Published online by Cambridge University Press:  20 April 2007

NATHAN A. GILLESPIE
Affiliation:
Department of Psychiatry, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
KENNETH S. KENDLER
Affiliation:
Department of Psychiatry, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Department of Human Genetics, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
CAROL A. PRESCOTT
Affiliation:
Department of Psychology, University of Southern California, Los Angeles, CA, USA
STEVEN H. AGGEN
Affiliation:
Department of Psychiatry, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
CHARLES O. GARDNER
Affiliation:
Department of Psychiatry, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
KRISTEN JACOBSON
Affiliation:
Department of Psychiatry, The University of Chicago, IL, USA
MICHAEL C. NEALE
Affiliation:
Department of Psychiatry, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA

Abstract

Background. Although an obvious environmental factor influencing drug use, the sources of individual differences in drug availability (DA) are unknown.

Method. This report is based on 1788 adult males from the Mid-Atlantic Twin Registry who participated in a structured telephone interview that included retrospective assessments of DA (cigarette, alcohol, marijuana, cocaine and stimulants) between ages 8 and 25. We fitted a biometric dual change score (DCS) model, adapted for ordinal data, to model latent growth and estimate the genetic and environmental components of variance over time.

Results. DA, despite being considered an environmental risk factor, is under both genetic and environmental control. For cigarette, alcohol, marijuana and cocaine availability, there was an overall increase in additive genetic variance and a decline in shared environmental variance over time. Non-shared environmental variance remained steady. Stimulant availability did not follow this pattern. Instead, there was an upswing in shared environmental effects with increasing age.

Conclusion. We have modeled the genetic and environmental architecture of changes in DA across adolescence. The rise in additive genetic variance over time coincides with acceleration in the expression of individual differences, probably brought on by an increase in personal freedom and a reduction in social constraints. Understanding the etiology of DA is likely to reveal key components, acting directly or indirectly, in the pathway(s) leading to drug initiation, abuse and dependence.

Type
Original Article
Copyright
2007 Cambridge University Press

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