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Pharmacogenomic study of side-effects for antidepressant treatment options in STAR*D

Published online by Cambridge University Press:  01 November 2011

S. L. Clark*
Affiliation:
Center for Biomarker Research and Personalized Medicine, Medical College of Virginia, Virginia Commonwealth University, Richmond, VA, USA
D. E. Adkins
Affiliation:
Center for Biomarker Research and Personalized Medicine, Medical College of Virginia, Virginia Commonwealth University, Richmond, VA, USA
K. Aberg
Affiliation:
Center for Biomarker Research and Personalized Medicine, Medical College of Virginia, Virginia Commonwealth University, Richmond, VA, USA
J. M. Hettema
Affiliation:
Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
J. L. McClay
Affiliation:
Center for Biomarker Research and Personalized Medicine, Medical College of Virginia, Virginia Commonwealth University, Richmond, VA, USA
R. P. Souza
Affiliation:
Laboratory of Neurosciences, Universidade Do Extremo Sul Catarinense, Criciuma, SC, Brazil
E. J. C. G. van den Oord
Affiliation:
Center for Biomarker Research and Personalized Medicine, Medical College of Virginia, Virginia Commonwealth University, Richmond, VA, USA
*
*Address for correspondence: Dr S. L. Clark, Center for Biomarker Research and Personalized Medicine, School of Pharmacy, McGuire Hall, Room 216A, P.O. Box 980533, Richmond, VA 23298-0581, USA. (Email: slclark2@vcu.edu)

Abstract

Background

Understanding individual differences in susceptibility to antidepressant therapy side-effects is essential to optimize the treatment of depression.

Method

We performed genome-wide association studies (GWAS) to search for genetic variation affecting the susceptibility to side-effects. The analysis sample consisted of 1439 depression patients, successfully genotyped for 421K single nucleotide polymorphisms (SNPs), from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Outcomes included four indicators of side-effects: general side-effect burden, sexual side-effects, dizziness and vision/hearing-related side-effects. Our criterion for genome-wide significance was a prespecified threshold ensuring that, on average, only 10% of the significant findings are false discoveries.

Results

Thirty-four SNPs satisfied this criterion. The top finding indicated that 10 SNPs in SACM1L mediated the effects of bupropion on sexual side-effects (p=4.98×10−7, q=0.023). Suggestive findings were also found for SNPs in MAGI2, DTWD1, WDFY4 and CHL1.

Conclusions

Although our findings require replication and functional validation, this study demonstrates the potential of GWAS to discover genes and pathways that could mediate adverse effects of antidepressant medication.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2011

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