# Gene expression signatures of response to fluoxetine treatment: systematic review and meta-analyses

**Authors:** David G. Cooper, J. Paige Cowden, Patrick M. Vo, Parker A. Stanley, Jack T. Karbowski, Victoria S. Gaertig, Caiden J. Lukan, Ariel D. Worthington, Caleb A. Class

PMC · DOI: 10.1038/s41380-025-03118-6 · Molecular Psychiatry · 2025-07-17

## TL;DR

This study combines gene expression data from fluoxetine-treated humans and rodents to identify biological pathways linked to antidepressant response and resistance.

## Contribution

A systematic meta-analysis of gene expression data reveals consistently altered pathways in fluoxetine responders versus non-responders.

## Key findings

- 18 pathways were consistently different in responders vs. non-responders, including toll-like receptor and immune pathways.
- Signal transduction pathways were consistently affected by fluoxetine treatment in both human patients and rodent models.
- Most studies were in rodent models, highlighting a need for larger human cohort studies to better understand antidepressant response heterogeneity.

## Abstract

Genomic (and other ‘omic) data have provided valuable insights on the pharmacological signatures of antidepressant response, but results from individual studies are largely heterogeneous. In this work, we synthesized gene expression data for fluoxetine treatment in both human patients and rodent models, to better understand biological pathways affected by treatment, as well as those that may distinguish clinical or behavioral response.

Following the PRISMA guidelines, we searched the Gene Expression Omnibus (GEO) for studies profiling humans or rodent models with treatment of the antidepressant fluoxetine, excluding those not done in the context of depression or anxiety, in an irrelevant tissue type, or with fewer than three samples per group. Included studies were systematically reanalyzed by differential expression analysis and Gene Set Enrichment Analysis (GSEA). Individual pathway and gene statistics were synthesized across studies by three p-value combination methods, and then corrected for false discovery.

Of the 74 data sets that were screened, 20 were included: 18 in rodents, and two in tissue from human patients. Studies were highly heterogeneous in the comparisons of both treated vs. control samples and responders vs. non-responders, with 691 and 357 pathways, respectively, identified as significantly different between groups in at least one study. However, 18 pathways were identified as consistently different in responders vs. non-responders, including toll-like receptor (TLR) and other immune pathways. Signal transduction pathways were identified as consistently affected by fluoxetine treatment in depressed patients and rodent models.

These meta-analyses confirm known pathways and provide new hints toward antidepressant resistance, but more work is needed. Most included studies involved rodent models, and both patient studies had small cohorts. Additional large-cohort studies applying additional ‘omics technologies are necessary to understand the intricacies and heterogeneity of antidepressant response.

## Linked entities

- **Chemicals:** fluoxetine (PubChem CID 3386)
- **Diseases:** depression (MONDO:0002050), anxiety (MONDO:0005618)
- **Species:** Homo sapiens (taxon 9606), Mus musculus (taxon 10090)

## Full-text entities

- **Diseases:** depressed (MESH:D003866), anxiety (MESH:D001007)
- **Chemicals:** fluoxetine (MESH:D005473)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12532588/full.md

## References

3 references — full list in the complete paper: https://tomesphere.com/paper/PMC12532588/full.md

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Source: https://tomesphere.com/paper/PMC12532588