Department of Psychiatry
Genetic Phenomena | Genetics and Genomics | Mental and Social Health | Pharmacology, Toxicology and Environmental Health | Psychiatry | Psychiatry and Psychology
Pharmacogenomic tests used to guide clinical treatment for major depressive disorder (MDD) must be thoroughly validated. One important assessment of validity is the ability to predict medication blood levels, which reflect altered metabolism. Historically, the metabolic impact of individual genes has been evaluated; however, we now know that multiple genes are often involved in medication metabolism. Here, we evaluated the ability of individual pharmacokinetic genes (CYP2C19, CYP2D6, CYP3A4) and a combinatorial pharmacogenomic test (GeneSight Psychotropic(R); weighted assessment of all three genes) to predict citalopram/escitalopram blood levels in patients with MDD. Patients from the Genomics Used to Improve DEpression Decisions (GUIDED) trial who were taking citalopram/escitalopram at screening and had available blood level data were included (N=191). In multivariate analysis of the individual genes and combinatorial pharmacogenomic test separately (adjusted for age, smoking status), the F statistic for the combinatorial pharmacogenomic test was 1.7 to 2.9-times higher than the individual genes, showing that it explained more variance in citalopram/escitalopram blood levels. In multivariate analysis of the individual genes and combinatorial pharmacogenomic test together, only the combinatorial pharmacogenomic test remained significant. Overall, this demonstrates that the combinatorial pharmacogenomic test was a superior predictor of citalopram/escitalopram blood levels compared to individual genes.
Citalopram, Depression, Escitalopram, GeneSight, Medication Blood Levels, Pharmacokinetics
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© 2020 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).T
DOI of Published Version
Shelton RC, Parikh SV, Law RA, Rothschild AJ, Thase ME, Dunlop BW, DeBattista C, Conway CR, Forester BP, Macaluso M, Hain DT, Aguilar AL, Brown K, Lewis DJ, Jablonski MR, Greden JF. Combinatorial Pharmacogenomic Algorithm is Predictive of Citalopram and Escitalopram Metabolism in Patients with Major Depressive Disorder. Psychiatry Res. 2020 May 17;290:113017. doi: 10.1016/j.psychres.2020.113017. Epub ahead of print. PMID: 32485484. Link to article on publisher's site
Shelton RC, Rothschild AJ. (2020). Combinatorial Pharmacogenomic Algorithm is Predictive of Citalopram and Escitalopram Metabolism in Patients with Major Depressive Disorder. Psychiatry Publications. https://doi.org/10.1016/j.psychres.2020.113017. Retrieved from https://escholarship.umassmed.edu/psych_pp/953
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