Pharmaco-psychiatry and gut microbiome: a systematic review of effects of psychotropic drugs for bipolar disorder
Bibliographic record
Abstract
Despite being one of the most common and debilitating mood disorders, bipolar disorder is often misdiagnosed and undertreated. Its pathogenesis is complex, with significant patient variability and inconsistent treatment effectiveness. The brain-gut-microbiota axis plays a critical role in bipolar disorder by modulating neurotransmitter secretion, gut peptides and systemic inflammation. However, the mechanisms by which psychotropic treatments influence gut microbiota composition and their implications for clinical outcomes remain poorly understood. This systematic review evaluated the impact of psychotropic drugs on gut microbiota and their potential role in bipolar disorder treatment outcomes. A comprehensive search across Ovid MEDLINE, Embase, APA PsycINFO, Scopus and PubMed yielded 314 articles, of which 12 met the inclusion criteria (last search: 13 August 2024). The studies included were those on adults with bipolar disorder type I or II receiving psychopharmacological treatments; those with group comparisons (e.g. healthy controls vs. medicated vs. non-medicated) investigating gut microbiome changes; and no restrictions applied to psychotic features, comorbid anxiety or prior treatment responses. Exclusions involved individual case reports, incomplete conference submissions or early terminated studies lacking efficacy analysis. Cochrane ROBINS-I V2 tool was used to measure the risk of bias, and the GRADE approach was utilized to rate the certainty of evidence in included studies. Two authors independently extracted data into Excel spreadsheets, categorizing demographic and clinical characteristics, describing microbiome analytic methods and summarizing findings on gut microbiome changes post-treatment. Given the high variability in methods and outcome measures across studies, all details were reported without data conversion. Data synthesis reveals that psychotropic treatments, including quetiapine and lithium, influence gut microbiota by increasing the abundance of beneficial bacteria supporting gut health and pathogenic bacteria linked to metabolic dysfunction. Notably, female patients exhibited more significant changes in microbial diversity following psychotropic treatment. Additionally, patients treated with psychotropics showed an increased prevalence of gut bacteria associated with multidrug antibiotic resistance. In bipolar patients treated with quetiapine, responders - those experiencing improved depressive symptom scores - displayed distinct gut microbiome profiles more closely resembling those of healthy individuals compared with non-responders. Responders also exhibited neural connectivity patterns similar to healthy subjects. These findings underscore the complex dual impact of psychotropic medications on gut microbiota, with potential consequences for both gut and mental health. While the enrichment of beneficial bacteria may support gut health, the rise in antibiotic-resistant and metabolically disruptive bacteria is concerning. Study limitations include methodological heterogeneity, inclusions of other psychiatric disorders, a high risk of bias in some studies due to incomplete statistical analyses or insufficient control for confounding factors and potential duplication of study populations arising from overlapping authorship. Further research is essential to elucidate the functional consequences of these microbial shifts and their influence on treatment efficacy. Nevertheless, this review highlights the potential of utilizing gut microbiota profiles to inform personalized treatment strategies, optimize therapeutic outcomes and minimize side effects in bipolar disorder. This study was registered with Open Science Framework (https://doi.org/10.17605/OSF.IO/3GUZR).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".