Abstract
Introduction
Alcoholic hallucinosis (AH) is one of the severe complications of chronic alcoholism, characterized by psychotic symptoms such as auditory hallucinations and delusions. Haloperidol is widely used to treat AH; however, its therapy is often complicated by side effects. A personalized approach using pharmacogenetic testing (particularly the CYP2D6 polymorphism) allows individualization of haloperidol dosage, improving both safety and efficacy of therapy.
Materials and Methods
The study included 100 men diagnosed with “psychotic disorder induced by alcohol use.” Patients were randomized into two groups: the main group (45 patients) received haloperidol based on the results of pharmacogenetic testing, while the control group (55 patients) received standard dosing. Genotyping was conducted for the CYP2D6 1846G > A polymorphism. The effectiveness was assessed using the PANSS, UKU, and SAS scales.
Results
Genotyping showed an even distribution of CYP2D6 polymorphisms in both groups. The main group demonstrated a significant reduction in side effects and improvement in psychotic symptoms compared to the control group. Differences on the UKU, SAS, and PANSS scales reached statistical significance on days 3–5 of treatment.
Conclusion
Using pharmacogenetic testing to adjust haloperidol dosage improves therapy tolerability and accelerates the resolution of psychotic symptoms in patients with alcoholic hallucinosis, confirming the feasibility of a personalized approach in psychopharmacotherapy.
Keywords: alcoholic hallucinosis, haloperidol, pharmacogenetics, CYP2D6, personalized medicine, psychopharmacotherapy
Introduction
Alcoholic hallucinosis (AH) is one of the most serious psychiatric complications of chronic alcoholism. This syndrome, characterized predominantly by auditory hallucinations with delusional disorders and emotional disturbances, ranks second in frequency among alcoholic psychoses, second only to delirium tremens.1,2 Studies show that AH occurs in 0.4% of patients hospitalized with alcohol dependence, and this figure can increase to 7.5% among patients with severe forms of dependence.3
Effective treatment of AH requires a comprehensive approach, including both pharmacotherapy with antipsychotics and addressing alcohol dependence. However, therapy is often complicated by a high risk of relapse and the development of extrapyramidal symptoms, especially in patients with a long history of alcohol abuse and liver dysfunction.4
Haloperidol is widely used to treat alcoholic hallucinosis, especially in cases of acute psychosis caused by alcohol dependence. It is a first-generation antipsychotic that acts on dopamine receptors in the brain, helping to stabilize mood, thinking, and behavior in patients with psychotic symptoms such as hallucinations and delusional disorders.5
Pharmacogenetics plays a key role in personalizing haloperidol therapy, especially in patients with various genetic variants of metabolism. Studies have shown that genetic polymorphisms in genes such as CYP2D6 can significantly affect haloperidol metabolism and predispose patients to developing side effects such as extrapyramidal symptoms.6 Patients with slow metabolism caused by CYP2D6 polymorphisms require lower doses to achieve therapeutic effect and reduce the risk of adverse reactions.7 Moreover, the use of pharmacogenetic testing allows for individualization of haloperidol and other antipsychotic dosing, leading to improvements in both safety and efficacy of treatment.8
Based on our previous retrospective studies, we developed an algorithm for dosing haloperidol in patients with alcoholic hallucinosis, taking into account the genotype for the 1846G > A polymorphism of the CYP2D6 gene. According to this algorithm, patients with the GA genotype are recommended to reduce the starting dose of haloperidol by 25%, while patients with the AA genotype should reduce the dose by 50%.
The use of pharmacogenetic testing in prospective psychiatric studies has shown that this approach can significantly improve both the efficacy and safety of antipsychotic therapy. By personalizing dosage selection based on the patient’s genetic profile, such approaches minimize the risk of side effects, including extrapyramidal symptoms and drug metabolism disorders, which is especially important when using haloperidol.6 Additionally, pharmacogenetic testing demonstrates a positive pharmacoeconomic effect, reducing treatment costs by decreasing the frequency of hospitalizations and the need for side effect corrections.7 The introduction of this approach into clinical practice improves long-term treatment outcomes and increases patient adherence to therapy.8
Thus, the results of previous studies confirming the effectiveness of using pharmacogenetic testing to individualize antipsychotic dosing, including haloperidol, can significantly improve the safety and efficacy of therapy. Considering the positive pharmacoeconomic effect and reduction in the frequency of side effects, we decided to conduct this study aimed at evaluating the impact of pharmacogenetically oriented therapy on the treatment of patients with alcoholic hallucinosis.
Materials and Methods
The study included 100 men (mean age 37.2 ± 8.4 years) diagnosed with “Psychotic disorder due to alcohol use, predominantly hallucinatory (F10.52)”. All patients were hospitalized and included in the study within the first 24 hours after admission.
Key characteristics of the included patients were:
Presence of a specific diagnosis of psychotic disorder related to alcohol use.
No contraindications for taking haloperidol, the drug of choice for treating these conditions.
Negative rapid drug test results, which allowed exclusion of mixed substance use and focus on alcohol-induced psychosis.
Voluntary consent of patients to participate in the study after being informed about its objectives and potential risks.
Patients who did not meet the inclusion criteria or had chronic somatic diseases in the decompensation stage were excluded from the study. Exclusion also occurred if haloperidol intolerance was detected or if the patient refused to continue participation in the study.
Each patient underwent a collection of disease history, assessment of alcohol abuse patterns and dynamics of alcohol dependence, as well as specific assessment of the condition during acute alcoholic hallucinosis. Treatment was carried out in accordance with modern clinical guidelines and standards, using haloperidol at the discretion of the attending physician. To assess treatment effectiveness and side effects, psychometric scales PANSS, CGI-S and CGI-I, UKU side effect scale, and Simpson-Angus scale were used.
Biomarker studies were also conducted, including venous blood and morning urine samples for genotyping.
Among the patients, 45 people started haloperidol treatment at doses recommended based on pharmacogenetic testing results (main group). When prescribing medications to the remaining 55 patients and to exclude the factor of the doctor’s knowledge or lack of knowledge about the use of pharmacogenetic testing, the attending physicians received a report containing information that patients had normal genotypes for all studied markers, regardless of the patient’s actual genotype (comparison group). Randomization was conducted by assigning random numbers generated using the “=RANDBETWEEN()” function in Microsoft Excel 2021 (Microsoft Corp., USA).
Information on patient characteristics and comorbidities is presented in Table 1.
Table 1. Patient Characteristics and Comorbidities.
| Parameter | Main group (N = 45) | Comparison group (N = 55) | p* | |||
| Age, years | 36,5 ± 9,6 | 38,4 ± 8,7 | >0,999 | |||
| Weight, kg | 79,8 ± 14,7 | 83,3 ± 16,6 | >0,999 | |||
| Height, cm | 172,9 ± 25,9 | 176,8 ± 29,7 | >0,999 | |||
| Body Mass Index, kg/m2 | 24,1 ± 6,1 | 25,3 ± 5,3 | >0,999 | |||
| Alcoholic steatohepatitis, N (%) | 43 (95,6%) | 52 (94,5%) | >0,999 | |||
| Toxic encephalopathy, N (%) | 36 (80%) | 43 (78,2%) | >0,999 | |||
| Toxic polyneuropathy of upper limbs, N (%) | 11 (24,4%) | 14 (25,5%) | >0,999 | |||
| Toxic polyneuropathy of lower limbs, N (%) | 7 (15,6%) | 6 (10,9%) | >0,999 | |||
| Viral hepatitis C, N (%) | 4 (8,9%) | 5 (9,1%) | >0,999 | |||
| Gastric ulcer, N (%) | 3 (6,7%) | 2 (3,6%) | >0,999 | |||
| Duodenal ulcer, N (%) | 5 (11,1%) | 3 (5,5%) | >0,999 | |||
| Arterial hypertension, N (%) | 6 (13,3%) | 10 (18,2%) | >0,999 | |||
| Active smoking, N (%) | 41 (91,1%) | 51 (92,7%) | >0,999 | |||
| Duration of concomitant alcohol dependence, years | 7,1 ± 3,6 | 8,5 ± 4,0 | >0,999 | |||
| Age of onset, years | 18,6 ± 3,7 | 17,9 ± 3,5 | >0,999 | |||
| Amount of alcohol consumed daily, drinks | 35,2 ± 15,7 | 37,2 ± 17,0 | >0,999 |
The study was approved by the local ethics committee (LEC) of the Russian Medical Academy of Continuous Professional Education of the Ministry of Health of the Russian Federation. Before inclusion in the study, all patients were thoroughly explained the study objectives, procedures to be performed, and possible risks; they received the study protocol and brochure, and all their questions were answered. Then, written informed consent approved by the LEC was obtained.
For genotyping, venous blood samples collected in VACUETTE® vacuum tubes (Greiner Bio-One, Austria) during the first day after starting fluvoxamine therapy were used. Real-time polymerase chain reaction was performed using “Dtlite” amplifiers from DNA-Technology (Moscow, Russia) and the CFX96 Touch Real Time System with CFX Manager software from Bio-Rad Laboratories Inc. (USA), as well as “SNP-screen” kits from Syntol (Russia). This allowed the determination of single nucleotide polymorphisms (SNPs) CYP2D6*4 (1846G > A, rs3892097). Each “SNP-screen” kit used two allele-specific hybridizations, which allowed the determination of two alleles of the studied polymorphism separately on two fluorescence channels.
The results of pharmacogenetic testing were interpreted using the following algorithm developed by us based on conducted studies: carriers of the GA genotype for the 1846G > A polymorphism of the CYP2D6 gene were prescribed a starting dose 25% lower, carriers of the AA genotype—50% lower starting dose.
Statistical analysis was performed using the R programming language through Microsoft R Application Network (R version 3.3.2 from 31.10.2016) with the installed checkpoint package for version control of used statistical packages. The RStudio development environment version 1.0.136 was used for programming. Sample size calculation was performed using the “pwr” package. The normality of sample distributions was assessed using the Shapiro-Wilk W test and taken into account when choosing the analysis method. Differences were considered statistically significant at p < 0.05 (power over 80%). For comparison of two independent groups, the Mann-Whitney test or Student’s t-test (with Welch’s correction for unequal variances) with Benjamini-Hochberg correction for multiple tests was used. The study data are presented as median and interquartile range (Me [Q1; Q3]) or, in case of normal distribution, as arithmetic mean and standard deviation (Mean ± SD). To compare genotype frequencies and adverse side effects, Pearson’s χ2 test was used.
Results
Genotyping of study participants revealed the distribution of genotypes for the CYP2D6 1846G > A polymorphism as presented in Table 2. In the main group, the GG genotype was found in 33 patients (73.3%), and the GA genotype in 12 patients (26.7%). In the comparison group, the GG genotype was observed in 39 patients (70.9%), and the GA genotype in 16 patients (29.1%). The genotype distribution in both groups complied with the Hardy-Weinberg equilibrium, as confirmed by the obtained ≤ and p-values, and showed no statistically significant differences between groups (p > 0.05). This indicates an even distribution of genetic characteristics between groups and excludes the influence of genotype on group assignment.
Table 2. Distribution of Genotypes for the CYP2D6 1846G > A Polymorphism.
| Group | Genotype GG | Genitype GA | Total Number of Patients | HWE Chi-sq | p-value | |||||
| Main group | 39 (70.9%) | 16 (29.1%) | 55 (100%) | 1.593 | 0.207 | |||||
| Comparison group | 33 (73.3%) | 12 (26.7%) | 45 (100%) | 1.065 | 0.302 |
Analysis of clinical indicators dynamics demonstrated significant differences between the main and control groups on the UKU, SAS, and PANSS scales (see Tables 3–5).
Table 3. UKU Scale Scores in Patients with Different Genotypes on Days 1–5 of the Study.
| Parameter | Main group | Comparison group | p-value | |||
| UKU Day 1 | 1 [0; 1] | 1 [0; 1] | 0.41 | |||
| UKU Day 2 | 2.7 [1.8; 2.7] | 3 [2; 3] | <0.001 | |||
| UKU Day 3 | 4.25 [3.4; 5.1] | 5 [4; 6] | 0.01 | |||
| UKU Day 4 | 5.6 [4.8; 6.4] | 7 [6; 8] | <0.001 | |||
| UKU Day 5 | 6.5 [5.85; 7.15] | 10 [9; 11] | <0.001 |
Table 5. PANSS Scale Scores in Patients with Different Genotypes on Days 1–5 of the Study.
| Parameter | Main group | Comparison group | p-value | |||
| PANSS Day 1 | 14 [13; 15] | 14 [13; 15] | 0.15 | |||
| PANSS Day 2 | 10.2 [9.35; 11.05] | 12 [10; 13] | 0.002 | |||
| PANSS Day 3 | 8 [7.2; 8.8] | 10 [9; 11] | <0.001 | |||
| PANSS Day 4 | 6 [5.25; 6.75] | 8 [7; 9] | <0.001 | |||
| PANSS Day 5 | 1.2 [0.6; 1.8] | 2 [1; 2] | <0.001 |
On the UKU scale, which assesses therapy side effects, there was no difference between the groups on the first day of the study (median 1 [0; 1], p = 0.41). However, from the second day onwards, the main group showed a statistically significant reduction in side effect severity compared to the comparison group (p < 0.001).
On day 3, UKU scale medians were 4.25 [3.4; 5.1] in the main group and 5 [4; 6] in the comparison group (p = 0.01).
By day 5, median values in the main group decreased to 6.5 [5.85; 7.15], while in the comparison group they reached 10 [9; 11] (p < 0.001).
This indicates a more favorable tolerability profile in the main group, where haloperidol doses were adjusted based on pharmacogenetic testing. On the SAS scale, which assesses extrapyramidal symptoms, there were no significant differences between groups on the first day (median 10 [9; 11], p = 0.856). Starting from the second day, the main group showed a statistically significant reduction in extrapyramidal symptom severity compared to the comparison group (p < 0.001).
On day 3, median SAS values in the main group were 10.01 [9.24; 10.78] versus 13 [12; 14] in the comparison group (p < 0.001).
By day 5, indicators decreased to 10.8 [10.08; 11.52] in the main group and reached 15 [14; 16] in the comparison group (p < 0.001).
This suggests that individualized dose adjustment of haloperidol based on CYP2D6 genotype contributes to a reduction in extrapyramidal side effects. The dynamics on the PANSS scale, used to assess psychopathological symptoms, also demonstrated faster and more pronounced improvement in the main group.
On day 1, there were no differences between groups (median 14 [13; 15], p = 0.15).
From day 2, indicators in the main group began to decrease more significantly (p = 0.002 and less).
On day 3, PANSS medians were 8 [7.2; 8.8] in the main group and 10 [9; 11] in the comparison group (p < 0.001).
By day 5, median values decreased to 1.2 [0.6; 1.8] in the main group versus 2 [1; 2] in the comparison group (p < 0.001).
This indicates more effective relief of psychotic symptoms when using a personalized approach to haloperidol dosing. Thus, the dynamics of changes on the UKU, SAS, and PANSS scales demonstrate statistically significant differences between the main and control groups at different stages of the study, indicating a more favorable dynamic in the main group.
Discussion
This study evaluated the effectiveness of using a personalized clinical decision support system for dosing haloperidol in patients with alcoholic hallucinosis based on pharmacogenetic markers. The results showed that individual adjustment of haloperidol dosage according to the CYP2D6 genotype contributes to a significant improvement in both therapy effectiveness and tolerability.
The distribution of genotypes for the CYP2D6 1846G > A polymorphism was similar in the main and control groups, which excludes the influence of genetic differences on the study results. This suggests that the observed differences in clinical indicators are due to the personalized approach to drug dosing.
Analysis of dynamics on the UKU, SAS, and PANSS scales demonstrated statistically significant advantages in the main group. Patients receiving haloperidol doses adjusted for genotype experienced fewer side effects and faster improvement in psychotic symptoms compared to the control group. These data are consistent with the results of previous studies confirming the effectiveness of pharmacogenetically oriented therapy in psychiatry.
Previously, similar studies were mainly conducted on patients with other mental disorders and without considering comorbidity with alcohol dependence. Our study is unique in that it focuses on patients with alcoholic hallucinosis, in whom drug metabolism features may be particularly significant due to the effect of alcohol on liver enzyme systems.
Studies conducted by other authors also indicate the importance of pharmacogenetic testing when prescribing psychotropic drugs. For example, studies have shown that adjusting the dose of antipsychotics based on the CYP2D6 genotype can reduce the risk of extrapyramidal symptoms and increase therapy effectiveness.
Advantages of the study:
Randomized double-blind design: The use of reports with normal genotypes for the control group allowed excluding the influence of the doctor’s knowledge about the patient’s genotype on dose selection, which enhances the reliability of the results.
Focus on alcoholic hallucinosis: Unlike previous studies, our study is focused on a specific group of patients, which expands the understanding of pharmacogenetics application in various clinical situations.
Application of clear dosing algorithms: The use of a developed algorithm for dose adjustment based on the CYP2D6 genotype provides standardization of the approach and the possibility of its implementation in clinical practice.
Despite the significant results obtained, the study has several limitations:
Sample size: Although the sample was sufficient to identify statistically significant differences, larger studies could confirm and expand our findings.
Group homogeneity: All participants were men of a certain age range, which may limit the generalization of results to other patient groups, including women and individuals of other age categories.
Short-term observation: The study covered only the first five days of therapy. Long-term effects of pharmacogenetically oriented dosing, including the impact on relapses and chronic course of the disease, were not evaluated.
Limitation on genetic markers: We investigated only the 1846G > A polymorphism of the CYP2D6 gene. Other genetic variations that may affect haloperidol metabolism and response to therapy were not considered.
To confirm and expand our results, further studies are needed that could:
Include more diverse and larger patient samples, including different gender and age groups.
Evaluate long-term clinical outcomes and impact on patients’ quality of life.
Investigate additional pharmacogenetic markers and their combined effect on metabolism and therapy effectiveness.
Study the economic efficiency of implementing pharmacogenetic testing in clinical practice.
Conclusion
The obtained data confirm the feasibility of using pharmacogenetic testing when prescribing haloperidol to patients with alcoholic hallucinosis. Individualization of therapy based on genetic markers contributes to improving the effectiveness and safety of treatment, which is of great importance for practical psychiatry and addiction medicine.
Table 4. SAS Scale Scores in Patients with Different Genotypes on Days 1–5 of the Study.
| Parameter | Main group | Comparison group | p-value | |||
| SAS Day 1 | 10 [9; 11] | 10 [9; 11] | 0.856 | |||
| SAS Day 2 | 10.2 [9.35; 11.05] | 12 [11; 13] | <0.001 | |||
| SAS Day 3 | 10.01 [9.24; 10.78] | 13 [12; 14] | <0.001 | |||
| SAS Day 4 | 11.2 [10.4; 12] | 14 [12.5; 15] | <0.001 | |||
| SAS Day 5 | 10.8 [10.08; 11.52] | 15 [14; 16] | <0.001 |
Footnotes
Practical Significance
Therapy optimization: A personalized approach allows for selecting the optimal drug dose for each patient, taking into account their genetic characteristics.
Reduction of side effects: Decreasing the risk of adverse reactions improves patient adherence to treatment and enhances their quality of life.
Economic efficiency: Shortening hospitalization periods and reducing costs for treating complications can lower overall healthcare system expenses.
Acknowledgments
This study was conducted with the support of grant No. 22-15-00190 “Personalized approach to haloperidol prescription in patients with acute alcoholic hallucinosis, using pharmacogenetic, pharmacometabolomic, and pharmacotranscriptomic biomarkers.”
Contributor Information
VYu Skryabin, Skryabin, PhD, MD, head of clinical department, Moscow Research and Practical Centre on Addictions of the Moscow Department of Healthcare, Moscow, Russia; Associate professor of addiction psychiatry department, Russian Medical Academy of Continuous Professional Education of the Ministry of Health of the Russian Federation, Moscow, Russian Federation..
AE Petukhov, Petukhov, PhD, MD, clinical laboratory diagnostician of the analytical toxicology lab of the Reference center for psychoactive substances use monitoring, Moscow Research and Practical Centre on Addictions of the Moscow Department of Healthcare, Moscow, Russia..
SA Pozdniakov, Pozdniakov, researcher of the laboratory of genetics and fundamental studies, Moscow Research and Practical Centre on Addictions of the Moscow Department of Healthcare, Moscow, Russia..
VA Ivanchenko, Ivanchenko, laboratory assistant, Moscow Research and Practical Centre on Addictions of the Moscow Department of Healthcare, Moscow, Russia..
IA Zaytsev, Zaytsev, laboratory assistant, Moscow Research and Practical Centre on Addictions of the Moscow Department of Healthcare, Moscow, Russia..
SS Miroshkin, Miroshkin, head of clinical department, Moscow Research and Practical Centre on Addictions of the Moscow Department of Healthcare, Moscow, Russia..
SI Sokolova, Sokolova, head of clinical department, Moscow Research and Practical Centre on Addictions of the Moscow Department of Healthcare, Moscow, Russia..
IV Bure, Bure, Department, Research Institute of Molecular and Personalized Medicine, Russian Medical Academy of Continuous Professional Education of the Ministry of Health of the Russian Federation, Moscow, Russian Federation..
VV Smirnov, Smirnov, Dr. Pharm. Sc., Head of the scientific and production complex FGBU “SSC Institute of Immunology” FMBA of Russia, National Research Center—Institute of Immunology Federal Medical-Biological Agency of Russia, Moscow, Russian Federation..
DA Sychev, Sychev, corresponding member of the Academy of Sciences of Russia, MD, PhD, MD, professor, rector, head of clinical pharmacology and therapy department, Russian Medical Academy of Continuous Professional Education of the Ministry of Health of the Russian Federation, Moscow, Russian Federation..
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