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Record W3157204177 · doi:10.64719/pb.4393

Impact of the Omics-Based Biomarkers on the Fluvoxamine’s Steady-State Concentration, Efficacy and Safety in Patients with Affective Disorders Comorbid with Alcohol Use Disorder

2025· article· en· W3157204177 on OpenAlex
M. S. Zastrozhin, VYu Smirnov, А. К. Застрожина, Elena Kaverina, Dina Klepikov, Е. А. Гришина, Kristina Ryzhikova, Irina V. Bure, Evgeny Bryun, Д. А. Сычев

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePsychopharmacology Bulletin · 2025
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsSKiN Health
Fundersnot available
KeywordsFluvoxamineCYP2D6CYP2C19MedicinePharmacologyAdverse effectInternal medicineMajor depressive disorderCYP3AFluoxetineCytochrome P450Metabolism

Abstract

fetched live from OpenAlex

Introduction: Fluvoxamine is commonly administered to patients with recurrent depressive disorder. Some of these patients do not show adequate response to the therapy with fluvoxamine, whereas many of them experience dose-dependent adverse drug reactions. Previous research revealed that CYP2D6 is involved in the metabolism of fluvoxamine, the activity of which is highly dependent on the polymorphism of the gene encoding it. Objective: The objective of this study was to investigate the effect of polymorphisms of the CYP3A4, CYP2C9, CYP3A5, ABCB1, CYP2C19, SCL6A4, and 5-HTR2A genes on the concentration/dose indicator of fluvoxamine and on the CYP3A expression level obtained by measuring the miR-27b plasma concentration levels in patients suffering from a recurrent depressive disorder. Material and Methods: Our study included 105 patients with recurrent depressive disorder (average age – 37.5 ± 13.2 years). The treatment regimen included fluvoxamine in an average daily dose of 117.6 ± 44.3 mg per week. Therapy efficacy was assessed using the international psychometric scales. Therapy safety was assessed using the UKU Side-Effect Rating Scale. For genotyping and estimation of the microRNA (miRNA) plasma levels, we performed the real-time polymerase chain reaction. The activity of CYP3A was evaluated using the HPLC-MS/MS method by the content of the endogenous substrate of the given isoenzyme and its metabolite in urine (6b-HC/cortisol). Therapeutic drug monitoring has been performed using HPLC-MS/MS. Results: Our study didn’t reveal any statistically significant results in terms of the treatment efficacy and safety of the therapy. We also didn’t reveal a statistical significance for the concentration/dose indicator of fluvoxamine in patients with different genotypes. Analysis of the results of the pharmacotranscriptomic part of the study didn’t demonstrate the statistically significant difference in the miR-27b plasma levels in patients with different genotypes. At the same time, correlation analysis didn’t reveal a statistically significant relationship between the fluvoxamine efficacy profile evaluated by changes in HAMD scale scores and the miR-27b plasma concentration: r s = –0.012, p = 0.63. Also, we didn’t reveal the correlation between the miRNA concentration and safety profile: rs = –0.175, p = 0.30. In addition, we didn’t reveal the relationship between the CYP3A enzymatic activity and the miR-27b plasma concentration: r s = –0.197, p < 0.32. However, the difference in the CYP3A enzymatic activity in carriers of AG and GG genotypes of the 6986A > G polymorphism of CYP3A5 gene has been revealed: (AG) 4.72 [1.18; 8.45] vs (GG) 9.23 [5.12; 15.53], p-value = 0.23. Conclusion: Thus, the effect of genetic polymorphism of the CYP3A4, CYP2C9, CYP2C9, CYP3A5, ABCB1, CYP2C19, CYP2C19, CYP2C19, SCL6A4, 5-HTR2A gene on the efficacy and safety profiles of fluvoxamine was not demonstrated in a group of 105 patients with depressive disorder and alcohol use disorder.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.273
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it