The Effects of Antidepressants on the Hippocampus: A Meta-Analysis of Public Transcriptional Profiling Data
Background: Major depressive disorder (MDD) is characterised by persistent depressed mood and loss of interest and pleasure in life, known as anhedonia. The first line of treatment for MDD is antidepressant medication that enhances signaling by monoamine neurotransmitters, such as serotonin and dopamine. Other treatments include non-pharmaceutical treatments, such as electroconvulsive therapy and transmagnetic stimulation, and non-traditional pharmaceutical antidepressants that function via alternative, often unknown, mechanisms. Methods: To identify mechanisms of action shared across antidepressant categories, we examined changes in gene expression following treatment with both traditional and non-traditional antidepressants, using a meta-analysis of public transcriptional profiling data from laboratory rodents (rats, mice). We focused on the hippocampus, which is a brain region that is well-documented via neuro-imaging to show morphological changes in depression that reverse with antidepressant usage. We specifically focused on treatment during adulthood, and included both clinically-used antidepressants (both pharmaceutical and non-pharmaceutical) and treatments demonstrated to effectively treat depressive mood symptoms. The outcome variable was gene expression in bulk dissected hippocampus as measured by microarray or RNA-Seq. To conduct our project, we systematically reviewed available datasets in the Gemma database of curated, reprocessed transcriptional profiling data using pre-defined search terms and inclusion/exclusion criteria. We identified 15 relevant studies containing a total of 22 antidepressant vs. control group comparisons (collective n=352). For each gene, a random effects meta-analysis model was then fit to the antidepressant vs. control effect sizes (Log2 Fold Changes) extracted from each study. Results: Our meta-analysis yielded stable estimates for 16,439 genes, identifying 58 genes that were consistently differentially expressed (False Discovery Rate<0.05) across antidepressant experiments and categories. Of these genes, 23 were upregulated and 35 were downregulated. The functions associated with the differentially expressed genes were diverse, including modulation of the stress response, immune regulation, neurodevelopment and neuroplasticity. Conclusion: The genes that we identified as consistently differentially expressed across antidepressant categories may be worth investigating as potential linchpins for antidepressant efficacy or as targets for novel therapies.