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. 2023 Aug;58(4):363-367.
doi: 10.1177/00185787231155842. Epub 2023 Feb 22.

Investigating the Use of Pharmacogenetic and Pharmacometabolomic Markers to Predict Haloperidol Efficacy and Safety Rates

Affiliations

Investigating the Use of Pharmacogenetic and Pharmacometabolomic Markers to Predict Haloperidol Efficacy and Safety Rates

Valentin Yurievich Skryabin et al. Hosp Pharm. 2023 Aug.

Abstract

Background: Haloperidol is commonly prescribed to patients with alcohol-induced psychotic disorder (AIPD). Notably however, individuals differ extensively with regards to therapeutic response and adverse drug reactions (ADRs). Previous studies have shown that haloperidol biotransformation is mainly metabolized by CYP2D6. Objective: The objective of our study was to investigate the use of pharmacogenetic (CYP2D6*4 genetic polymorphism) and pharmacometabolomic biomarkers to predict haloperidol efficacy and safety rates. Material and Methods: The study enrolled 150 patients with AIPD. Therapy included haloperidol in a daily dose of 5 to 10 mg/day by injections for 5 days. Efficacy and safety of treatment were evaluated using the validated psychometric scales PANSS, UKU, and SAS. Results: No association of the urinary 6-НО-ТНВС/pinoline ratio values which could be evidence of the CYP2D6 activity level with both the efficacy and safety rates of haloperidol was demonstrated. However, a statistically significant association between haloperidol safety profile and CYP2D6*4 genetic polymorphism was demonstrated (P < .001). Conclusion: To predict haloperidol efficacy and safety rates, utilization of pharmacogenetic testing that defines CYP2D6*4 genetic polymorphism is found preferable over the use of the pharmacometabolomic marker in a clinical setting.

Keywords: CYP2D6; alcohol-induced psychotic disorder; haloperidol; omics biomarkers; personalized medicine; pharmacogenetics; pharmacometabolomics.

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Conflict of interest statement

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Data from the psychometric assessments and side-effect rating scales in patients with different genotypes on day 6 of the study. Note. PANSS = Positive and Negative Syndrome Scale; SAS = Simpson-Angus Scale; UKU = Ugvald for Kliniske Undersgelser Side Effect Rating Scale.
Figure 2.
Figure 2.
Differences in the 6-НО-ТНВС/pinoline ratio values in patients with different genotypes. Note. 6-НО-ТНВС = 6-hydroxy-1,2,3,4-tetrahydro-beta-carboline.
Figure 3.
Figure 3.
Correlations between the 6-НО-ТНВС/pinoline ratio on day 6 of follow-up and the dynamics of the UKU (A) and SAS (B) scales. Note. 6-НО-ТНВС = 6-hydroxy-1,2,3,4-tetrahydro-beta-carboline; SAS = Simpson-Angus Scale; UKU = Ugvald for Kliniske Undersgelser Side Effect Rating Scale.

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