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Record W4412791421 · doi:10.1016/j.phrs.2025.107894

Effect of ketamine and esketamine on RNA expression and its relevance for depression: A systematic review

2025· review· en· W4412791421 on OpenAlexaff
Claudia Pisanu, Rosana Carvalho Silva, Mattia Meattini, Massimo Gennarelli, Bernhard T. Baune, Alessio Squassina, Alessandra Minelli

Bibliographic record

VenuePharmacological Research · 2025
Typereview
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsDalhousie University
FundersHORIZON EUROPE Framework ProgrammeMinistero della SaluteEuropean Commission
KeywordsKetamineDepression (economics)Relevance (law)NeurosciencePsychologyComputational biologyMedicineBiologyEconomicsPolitical science

Abstract

fetched live from OpenAlex

Treatment-resistant depression (TRD) remains a challenge in psychiatry, necessitating novel therapeutic strategies beyond traditional monoaminergic antidepressants. Ketamine and its S-enantiomer esketamine have demonstrated rapid and robust antidepressant effects in TRD, probably through mechanisms involving glutamatergic modulation, neuroplasticity, and anti-inflammatory properties. However, the molecular underpinnings of these effects are not yet understood. This systematic review aimed to synthesize evidence from human and in vitro studies evaluating transcriptional changes associated with ketamine and esketamine treatment, to identify potential biomarkers and clarify molecular pathways relevant to their antidepressant properties. A systematic search conducted on PubMed and Scopus identified 12 studies assessing RNA expression following ketamine or esketamine treatment in patients with unipolar or bipolar depression or in human-derived cell models. Eligibility and quality were evaluated using PRISMA guidelines and a modified version of Downs and Black checklist. Twelve studies met inclusion criteria, only one of which explored the effect of esketamine, while all others focused on racemic ketamine. Five studies examined peripheral blood gene expression in patients with TRD, while seven assessed mRNA changes in vitro using human-derived cells. Transcriptome and candidate gene expression studies revealed modulation of genes and pathways related to glutamatergic signaling (GRM2, GRIN2D), immune regulation (STAT3, CCL22, IL6), and neuroplasticity (IGF2). No consistent peripheral biomarkers emerged, but transcriptional profiling revealed dynamic molecular responses to ketamine and esketamine. Ketamine and esketamine induce diverse transcriptional changes implicating neuroplastic, inflammatory, and metabolic pathways. Transcriptomic profiling offers a promising approach for uncovering biomarkers and mechanisms of antidepressant response, warranting further multi-omics, large-scale studies.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.007
Bibliometrics0.0130.013
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.161
GPT teacher head0.547
Teacher spread0.386 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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