UMMS Affiliation

Department of Psychiatry

Publication Date

2020-05-17

Document Type

Article

Disciplines

Genetic Phenomena | Genetics and Genomics | Mental and Social Health | Pharmacology, Toxicology and Environmental Health | Psychiatry | Psychiatry and Psychology

Abstract

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.

Keywords

Citalopram, Depression, Escitalopram, GeneSight, Medication Blood Levels, Pharmacokinetics

Rights and Permissions

© 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

10.1016/j.psychres.2020.113017

Source

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

Journal/Book/Conference Title

Psychiatry research

Comments

Full author list omitted for brevity. For the full list of authors, see article.

Related Resources

Link to Article in PubMed

PubMed ID

32485484

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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