Poster Presentation GENEMAPPERS 2024

Exploring the anti-depressive effects of statins using transcriptomic signature matching and Mendelian randomisation (#73)

Jiayue-Clara Jiang 1 , Chenwen Hu 2 , Andrew M McIntosh 3 , Sonia Shah 1
  1. Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia
  2. University of Queensland, St Lucia, QLD, Australia
  3. Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom

New treatments for depression are needed to meet the unmet patient needs, and drug repurposing represents a time- and cost-effective approach. Cholesterol-lowering statins are widely used for treating cardiovascular diseases, and observational studies and randomised controlled trials have reported inconsistent findings on their anti-depressive effects. In this study, we explored the anti-depressive potential of statins and the underlying mechanisms using genomics approaches, namely transcriptional signature matching and Mendelian randomisation (MR).

Using the Connectivity Map (CMap) database, we compared the gene expression signatures from human cell lines treated with statins and antidepressants, and found substantial similarities. Pathway enrichment analysis on genes perturbed in the same direction by the two drug classes demonstrated concordant impacts on diverse biological and metabolic pathways, as well as various immune and inflammatory pathways.

To explore the causal effects of statins on depression, we performed MR analysis, a statistical genomics method, to explore the association of genetically predicted HMGCR inhibition (the primary target of statins) with depression risk and related symptoms, as well as immune-related traits based on findings from CMap analysis. Through MR, we did not identify any association between genetically predicted HMGCR inhibition and depression risk; however, our findings showed extensive associations between HMGCR inhibition with changes in monocyte and platelet-related metrics, both of which were previously linked to depression. Further analysis of the off-target effects of statins indicates that statins could potentially modulate diverse immune phenomena via both on and off-target (via ITGAL inhibition) effects.

Our findings suggest that statins induce antidepressant-like cellular responses in human cell lines, and can potentially confer anti-depressive effects by modulating immune pathways. Our findings warrant pre-clinical investigation of the causal role of these shared pathways in depression, and clinical trials that further investigate the effects of statins in alleviating depressive symptoms, particularly amongst patients with an inflammatory phenotype.