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The influence of five monoamine genes on trajectories of depressive symptoms across adolescence and young adulthood

Published online by Cambridge University Press:  31 January 2012

Daniel E. Adkins ,
Jonathan K. Daw ,
Joseph L. McClay  and
Edwin J. C. G. van den Oord
Daniel E. Adkins*
Affiliation:
Virginia Commonwealth University
Jonathan K. Daw
Affiliation:
University of North Carolina at Chapel Hill
Joseph L. McClay
Affiliation:
Virginia Commonwealth University
Edwin J. C. G. van den Oord
Affiliation:
Virginia Commonwealth University
*
Address correspondence and reprint requests to: Daniel E. Adkins, Center for Biomarker Research and Personalized Medicine, Virginia Commonwealth University, McGuire Hall, Room 216A, 1112 East Clay Street, Richmond, VA 23298; E-mail: [email protected].
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Abstract

The influence of five monoamine candidate genes on depressive symptom trajectories in adolescence and young adulthood were examined in the Add Health genetic sample. Results indicated that, for all respondents, carriers of the dopamine receptor D4 5-repeat allele were characterized by distinct depressive symptom trajectories across adolescence and early adulthood. Similarly, for males, individuals with the monoamine oxidase A 3.5-repeat allele exhibited unique depressive symptom trajectories. Specifically, the trajectories of those with the dopamine receptor D4 5-repeat allele were characterized by rising levels in the transition to adulthood, while their peers were experiencing a normative drop in depressive symptom frequency. Conversely, males with the monoamine oxidase A 3.5-repeat allele were shown to experience increased distress in late adolescence. An empirical method for examining a wide array of allelic combinations was employed, and false discovery rate methods were used to control the risk of false positives due to multiple testing. Special attention was given to thoroughly interrogate the robustness of the putative genetic effects. These results demonstrate the value of combining dynamic developmental perspectives with statistical genetic methods to optimize the search for genetic influences on psychopathology across the life course.

Type
Regular Articles
Information
Development and Psychopathology , Volume 24 , Issue 1 , February 2012 , pp. 267 - 285
Copyright
Copyright © Cambridge University Press 2012

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