The Converging Effects of Different Categories of Antidepressants on the Brain: A Systematic Meta-Analysis of Public Transcriptional Profiling Data from the Hippocampus and Cortex

Background

Depression can be treated with traditional antidepressant pharmaceuticals targeting monoaminergic function, as well as with a variety of non-traditional drug classes and neuromodulatory interventions, such as electroconvulsive therapy.

Objective

To identify mechanisms of action shared across antidepressant treatment categories, we performed a systematic meta-analysis of public transcriptional profiling data from adult laboratory rodents (rats, mice). Our scope included clinically-used and clinically-effective antidepressant treatments, both pharmacological and neuromodulatory. The outcome variable was gene expression, as measured by microarray or RNA-Seq, from bulk dissected tissue from two brain regions linked to depression, the hippocampus and cortex.

Methods

Relevant datasets were identified in the Gemma database of curated, reprocessed transcriptional profiling data using pre-defined search terms and inclusion/exclusion criteria ( hippocampus: 6-24-2024, cortex: 7-10-2024). Differential expression results were extracted for all available genes, minimizing bias. For each gene, a random effects meta-analysis model was fit to the antidepressant vs. control effect sizes (Log2 Fold Changes) from each study for each brain region, with exploratory analyses examining traditional and non-traditional antidepressant categories separately.

Results

For the hippocampus, 15 relevant studies were identified, containing 22 antidepressant vs. control group comparisons. These treatment comparisons represented a collective n =313 samples, approximately half of which received traditional versus non-traditional antidepressants. Of the 16,439 genes with stable meta-analysis estimates, 58 were consistently differentially expressed (False Discovery Rate (FDR)<0.05) following treatment. Antidepressant effects were enriched in gene sets related to stress regulation, brain growth and plasticity, vascular and glial function, and immune function. Comparisons with findings from single nucleus RNA-Seq confirmed antidepressant effects on specific hippocampal cell types, including promoting an immature phenotype in dentate granule neurons. For the cortex, 14 studies were identified, containing 17 antidepressant vs. control group comparisons (collective n =260). Of the 14,344 genes with stable meta-analysis estimates, only one was consistently differentially expressed (FDR<0.05: Atp6v1b2 ), but the overall pattern of expression correlated with that observed in the hippocampus.

Conclusion

Genes and pathways that are consistently differentially expressed across treatment categories may serve as linchpins for antidepressant efficacy, providing promising targets for novel therapies. Future work should explore the relevance of these findings to human clinical populations, and explore potential heterogeneity introduced by sex, region, and drug category.

Key Points

• Depression can be treated with traditional antidepressants targeting monoaminergic function, as well as multiple other drug classes and non-pharmaceutical interventions.

• Understanding the congruent effects of different types of antidepressant treatments on sensitive brain regions, such as the hippocampus and cortex, can highlight essential mechanisms of action.

• A meta-analysis of public transcriptional profiling datasets identified genes and functional gene sets that are differentially expressed across antidepressant categories.

Plain Language Summary

Major depressive disorder is characterized by persistent depressed mood and loss of interest and pleasure in life. Worldwide, an estimated 5% of adults suffer from depression, making it a leading cause of disability. The current standard of care for depressed individuals includes psychotherapy and antidepressant medications that enhance signaling by monoamine neurotransmitters, such as serotonin and norepinephrine. Other treatments include non-traditional antidepressants that function via alternative, often unknown, mechanisms. To identify mechanisms of action shared across different categories of antidepressants, we performed a meta-analysis using public datasets to characterize changes in gene expression (mRNA) following treatment with both traditional and non-traditional antidepressants. We focused on the hippocampus and cortex, which are two brain regions that are sensitive to both depression and antidepressant usage. We found 59 genes that had consistently higher or lower levels of expression (mRNA) across antidepressant categories. The functions associated with these genes were diverse, including regulation of stress response, the immune system, brain growth and adaptability. These genes are worth investigating further as potential linchpins for antidepressant efficacy or as targets for novel therapies.

Graphical Abstract