Skip to main navigation menu Skip to main content Skip to site footer

Personalized Pharmacotherapy with haloperidol for Patients with Acute Alcohol-Drinking Psychoses Based on Omics Biomarkers

Abstract

Modern pharmacotherapy for psychotic disorders aims to personalize treatment based on genetic markers that affect drug metabolism.
Objective. The study aimed — to assess the influence of CYP2D6*4 and CYP2D6*3 genetic polymorphisms on the efficacy and safety of haloperidol treatment in patients with acute alcoholic hallucinosis.
Material and methods. The study included 100 patients undergoing haloperidol treatment. Symptom assessment was performed with Simpson-Angus scale (SAS) and Positive and Negative Syndrome scale (PANSS), along with measurements of the drug’s steady-state concentration. Genotyping and microRNA analysis were conducted to determine metabolic characteristics.
Results. Patients with the CYP2D6*4 GG and GA genotypes showed statistically significant improvements by SAS and PANSS scales (p < 0.0001). Differences in the steady-state concentration of haloperidol were also significant between these genotypes (p = 0.01). No such differences were observed for the CYP2D6*3 genotype.
Conclusion. CYP2D6 genetic variations can significantly affect the efficacy and safety of haloperidol, highlighting the need for pharmacogenetic testing to optimize the treatment of psychotic disorders.

Keywords

pharmacogenetics, haloperidol, alcoholic hallucinosis, CYP2D6*4, CYP2D6*3, drug metabolism, personalized medicine, psychotic disorders, microRNA, steady-state concentration

PDF (Русский)

References

  1. Jones B.C., Tarasova O.A., Haas J.V. et al. Comprehensive review of polymorphism in cytochrome P450 enzymes and its clinical impact in drug metabolism // Ann Pharmacother. – 2021. – Vol. 55 (10). – Pp. 1109–1122. – htpps://doi.org/10.1177/1060028020981782
  2. Martinez C., Rietbrock S., Wise L. et al. Antipsychotic dosing for patients with polymorphic CYP2D6 and CYP2C19 genes: a systematic review on the role of pharmacogenetic tests // J Psychiatr Res. – 2021. – Vol. 132. – Pp. 16–29. – htpps://doi.org/10.1016/j.jpsychires.2020.09.028
  3. Zhang A., Sun H., Wang P. et al. Recent and potential developments of biofluid analyses in metabolomics // J Proteomics. – 2021. – Vol. 224. – Art. 103822. – htpps://doi.org/10.1016/j.jprot.2020.103822
  4. Wei Y., Zhang X., Zheng Z., Feng W. Role of microRNAs in drug metabolism and resistance in pediatric patients // Pediatr Res. – 2022. – Vol. 91(3). – Pp. 507–516. – htpps://doi.org/10.1038/s41390-021-01362-4
  5. Li M., Zhou X., Shegog E.J., Pan Z. The role of genetic polymorphisms in antipsychotics response and treatment outcomes in schizophrenia // Mol Psychiatry. – 2021. – Vol. 26 (6). – Pp. 1730–1746. – htpps://doi.org/10.1038/s41380-020-00930-w
  6. Smith G., Van Hout M.C. A review of the current research on the role of metabolomics in the diagnosis of psychiatric disorders // Psychiatry Res. – 2021. – Vol. 300. – P. 113798. – htpps://doi.org/10.1016/j.psychres.2021.113798
  7. Zhang Y., Li X., Ciric B. et al. MicroRNA expression profiling in multiple sclerosis: A genomics and bioinformatics approach // Front Immunol. – 2021. – Vol. 12. – Pp. 625–626. – htpps://doi.org/10.3389/fimmu.2021.625626
  8. Huang Z., Robinson S., Shaw D. et al. Integration of metabolomics and transcriptomics in nanotoxicology: a novel approach to understand the mechanism of nanomaterial toxicity // Toxicol Lett. – 2021. – Vol. 342. – Pp. 1–9. – htpps://doi.org/10.1016/j.toxlet.2021.01.011
  9. Opler L.A., Kay S.R., Lindenmayer J.P., Fiszbein A. Structured Clinical Interview Positive and Negative Syndrome Scale (SCI-PANSS). – Multi-Health Systems Inc., Toronto. – 1999. – No. 4. – Art. 15. – https://doi.org/10.1093/schbul/13.2.261
  10. Мосолов С.Н. Шкалы психометрической оценки симптоматики шизофрении и концепция позитивных и негативных расстройств. – М.: Новый цвет, 2001. – 240 с.
  11. Guy W. Clinical Global Impressions (CGI) Scale, Modified // Rush J.A. (ed.). Task Force for the Handbook of Psychiatric Measures. Handbook of Psychiatric Measures (1st ed.). – Washington, DC: American Psychiatric Association, 2008. – 864 p.
  12. Lingjærde O., Ahlfors U.G., Bech P. et al. The UKU side effect rating scale. A new comprehensive rating scale for psychotropic drugs and a cross-sectional study of side effects in neuroleptic-treated patients // Acta Psychatr Scand. – 1987. – Vol. 76. – Art. 334. – https://doi.org/10.1111/j.1600-0447.1987.tb10566.x
  13. Simpson G.M., Angus J.W. A rating scale for extrapyramidal side effects // Acta Psychiatr Scand Suppl. – 1970. – Vol. 212. – Pp. 11–19. – htpps://doi.org/10.1111/j.1600-0447.1970.tb02066.x
  14. Zastrozhin M.S., Skryabin V.Y., Smirnov V.V. et al. Effects of CYP2D6 activity on the efficacy and safety of mirtazapine in patients with depressive disorders and comorbid alcohol use disorder // Can J Physiol Pharmacol. – 2019. – Vol. 97 (8). – Pp. 781–785. – htpps://doi.org/10.1139/cjpp-2019-0177
  15. Sychev D.A., Zastrozhin M.S., Smirnov V.V. et al. The correlation between CYP2D6 isoenzyme activity and haloperidol efficacy and safety profile in patients with alcohol addiction during the exacerbation of the addiction // Pharmgenomics Pers Med. – 2016. – Vol. 9. – Pp. 89–95. – htpps://doi.org/10.2147/PGPM.S110385
  16. Skryabin V., Zastrozhin M., Parkhomenko A. et al. Genetic testing is superior over endogenous pharmacometabolomic markers to predict safety of haloperidol in patients with alcohol-induced psychotic disorder // Curr Drug Metab. – 2022. – Vol. 23 (13). – Pp. 1067– 1071. – htpps://doi.org/10.2174/1389200224666221228112643

Downloads

Download data is not yet available.