Genetic Prediction of Antidepressant Drug Response and Nonresponse in Korean Patients

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18
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SCOPUS

20

초록

Genetic polymorphism contributes to variation in response to drug treatment of depression. We conducted three independent 6-week treatment studies in outpatients with major depressive disorder (MDD) to develop a pharmacogenomic model predicting response and nonresponse. We screened candidate genomic markers for association with response to selective serotonin reuptake inhibitors (SSRIs). No patients had received any antidepressant drug treatment in the current episode of depression. Outcome evaluation was blinded to drug and genotype data. The prediction model derived from a development sample of 239 completer cases treated with SSRIs comprised haplotypes and polymorphisms related to serotonin synthesis, serotonin transport, glutamate receptors, and GABA synthesis. The model was evaluated prospectively for prediction of outcome in a validation sample of 176 new SSRI-treated completer cases. The model gave a prediction in 60% of these cases. Predictive values were 85% for predicted responders and 86% for predicted nonresponders, compared to prior probabilities of 66% for observed response and 34% for observed nonresponse in those cases (both P<0.001). Convergent cross-validation was obtained through failure of the model to predict outcomes in a third independent sample of 189 completer cases who received non-SSRI antidepressants. We suggest proof of principle for genetic guidance to use or avoid SSRIs in a majority of Korean depressed patients.

키워드

SEROTONIN TRANSPORTER GENE; STAR-ASTERISK-D; POLYMORPHISM 5-HTTLPR ASSOCIATION; TRYPTOPHAN HYDROXYLASE-2; MAJOR DEPRESSION; MESSENGER-RNA; PROMOTER; EXPRESSION; BRAIN; METAANALYSIS
제목
Genetic Prediction of Antidepressant Drug Response and Nonresponse in Korean Patients
저자
Lim, Shinn-Won; Won, Hong-Hee; Kim, Hyeran; Myung, Woojae; Kim, Seonwoo; Kim, Ka-Kyung; Carroll, Bernard J.; Kim, Jong-Won; Kim, Doh Kwan
DOI
10.1371/journal.pone.0107098
발행일
2014-09-16
유형
Article
저널명
PLoS ONE
권
9
호
9