Depression is a chronic, debilitating mental health condition that continues to lack aetiological consensus, whilst affecting around 322 million people globally. Selective serotonin re-uptake inhibitors (SSRIs), are generally the first line of treatment for depression, due to their higher tolerance and efficacy compared to other antidepressant drug classes. Despite their popularity, around 25% of individuals taking SSRIs are reported to be unresponsive to treatment1. In addition, the mechanisms of action of the SSRIs remain unclear, limiting our ability to appropriately utilise these drugs in the most efficient and successful way.
For the first time, the gene expression profiles of six prescribed SSRIs have been examined in detail using cell-based drug perturbation signatures from the CLUE Connectivity Map database. Comparative analysis demonstrated low correlation between the SSRI signatures, suggesting diverse effects of SSRIs. Network analysis of the signatures captured both shared and unique biological pathways perturbed by SSRIs. Perturbed biological pathways spanned known nervous system and depression-related pathways, as well as cholesterol, endocrine, immune system, and ribosomal effects. Hub genes identified through analysis of the SSRI protein interaction networks, alongside known targets of the SSRIs, underwent summary-based Mendelian Randomisation analysis to assess potential causal relationships between these genes and depression-related traits. Statistically significant associations were found between the CD40 hub gene and the risk of major depressive disorder (MDD). Suggestive associations were also found between cholesterol-related hub genes such as FADS1, as well as immune and endocrine-related hub genes and the risk of MDD.
This work has provided data-driven and hypothesis-free results, with known effects of the drugs and pathways associated with depression confirming the validity of this approach. Novel genes and drug mechanisms of action have also been uncovered, furthering our understanding of the biological processes underpinning SSRI use and depression pathogenesis, while providing data-driven direction for future research.