Genetic markers anticipate response to citalopram in a majority of patients

Farrokh Alemi, Manaf Zargoush, Harold Erdman, Jee Vang, Steve Epstein, Fanous Ayman

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Objective: Scientists have concluded that genetic profiles cannot predict a large percentage of variation in response to citalopram, a common antidepressant. Using the same data, we examined if a different Conclusion can be arrived at when the results are personalized to fit specific patients. METHODS: We used data available through the Sequenced Treatment Alternatives to Relieve Depression database. We created three boosted Classification and Regression Trees to identify 16 subgroups of patients, among whom anticipation of positive or negative response to citalopram was significantly different from 0.5 (P≤0.1). Results: In a 10-fold cross-validation, this ensemble of trees made no predictions in 33% of cases. In the remaining 67% of cases, it accurately classified response to citalopram in 78% of cases. Conclusion: For the majority of the patients, genetic markers can be used to guide selection of citalopram. The rules identified in this study can help personalize prescription of antidepressants.

Original languageEnglish (US)
Pages (from-to)287-293
Number of pages7
JournalPsychiatric Genetics
Issue number6
StatePublished - Dec 2011
Externally publishedYes

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)
  • Psychiatry and Mental health
  • Biological Psychiatry


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