Combinatorial Pharmacogenomic Algorithm is Predictive of Citalopram and Escitalopram Metabolism in Patients with Major Depressive Disorder

• Published in: Psychiatry research 2020-08, Vol.290, p.113017, Article 113017
• Main Authors: Shelton, Richard C., Parikh, Sagar V., Law, Rebecca A., Rothschild, Anthony J., Thase, Michael E., Dunlop, Boadie W., DeBattista, Charles, Conway, Charles R., Forester, Brent P., Macaluso, Matthew, Hain, Daniel T., Aguilar, Aime Lopez, Brown, Krystal, Lewis, David J., Jablonski, Michael R., Greden, John F.
• Format: Article
• Language: English
• Subjects: Adult; Algorithms; Antidepressive Agents - blood; Antidepressive Agents - pharmacokinetics; Antidepressive Agents - therapeutic use; Citalopram; Citalopram - blood; Citalopram - pharmacokinetics; Citalopram - therapeutic use; Cytochrome P-450 CYP2C19 - genetics; Cytochrome P-450 CYP2D6 - genetics; Cytochrome P-450 CYP2D6 - metabolism; Cytochrome P-450 CYP3A - genetics; Cytochrome P-450 CYP3A - metabolism; Depression; Depressive Disorder, Major - blood; Depressive Disorder, Major - drug therapy; Depressive Disorder, Major - genetics; Escitalopram; Female; GeneSight; Humans; Male; Medication Blood Levels; Middle Aged; Pharmacogenetics; Pharmacogenomic Testing; Pharmacokinetics; Serotonin Uptake Inhibitors - blood; Serotonin Uptake Inhibitors - pharmacokinetics; Serotonin Uptake Inhibitors - therapeutic use; Treatment Outcome
• ISSN: 0165-1781; 1872-7123
• DOI: 10.1016/j.psychres.2020.113017

•Pharmacogenomic tests should predict variation in medication blood levels•Individual genes involved in citalopram metabolism predicted blood levels•A combinatorial pharmacogenomic algorithm predicted citalopram blood levels•The combinatorial test was a better predictor than the individual component genes 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®; 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.