Association between polymorphisms in the dopamine transporter gene and depression: Evidence for a gene-environment interaction in a sample of juvenile detainees

Gerald J. Haeffel, Marya Getchell, Roman A. Koposov, Carolyn M. Yrigollen, Colin G. DeYoung, Britt Af Klinteberg, Lars Oreland, Vladislav V. Ruchkin, Elena L. Grigorenko

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56 Scopus citations

Abstract

Previous research has generated examples of how genetic and environmental factors can interact to create risk for psychopathology. Using a gene-by-environment (G × E) interaction design, we tested whether three polymorphisms in the dopamine transporter gene (DAT1, also referred to as SLC6A3, located at 5p15.33) interacted with maternal parenting style to predict first-onset episodes of depression. Participants were male adolescents (N = 176) recruited from a juvenile detention center in northern Russia. As hypothesized, one of the polymorphisms (rs40184) moderated the effect of perceived maternal rejection on the onset of major depressive disorder, as well as on suicidal ideation. Further, this G × E interaction was specific to depression; it did not predict clinically significant anxiety. These results highlight the need for further research investigating the moderating effects of dopaminergic genes on depression.

Original languageEnglish (US)
Pages (from-to)62-69
Number of pages8
JournalPsychological Science
Volume19
Issue number1
DOIs
StatePublished - Jan 2008

Bibliographical note

Funding Information:
This research was supported by Swedish Medical Research Council Grant 4145, awarded to Lars Oreland; funds from the Soderstrom–Koenig Fund to Lars Oreland and Britt af Klinteberg; funds from the Swedish Royal Academy of Sciences to Britt af Klinteberg and Elena L. Grigorenko; funds from Successful Intelligence to Elena L. Grigorenko; and funds from the American Psychological Foundation to Elena L. Grigorenko. We are grateful to all participants in the study for their willingness to participate. We also thank all our colleagues and assistants who made extremely valuable contributions at different stages of data collection, processing, and analysis. Finally, we thank Robyn Rissman for her editorial assistance and Nicole M. McNeil for her statistical expertise.

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