Understanding the causal mechanisms of antidepressant exposure and response

This proposal will use genomic approaches to advance our mechanistic understanding of antidepressant action and response. We will leverage recent advances in causal inference, electronic health data and genomic datasets to deliver real-world antidepressant exposure and response data at an unprecedented scale to better understand the active ingredients of how antidepressants work and why individuals vary in their response. We will openly share new methods and datasets generated from this project. This proposal will deliver mechanistic insights, paving the way for clinical predictors of antidepressant action, framed by lived experience throughout.

Our key goals are to:

1. Develop measures of antidepressant exposure and response from NHS electronic health records, linked to research studies and genomic datasets
2. Provide large, publicly available genome-wide association study datasets of antidepressant exposure and response
3. Provide association study datasets of antidepressant exposure and genomic markers (DNA methylation, protein expression, metabolites)
4. Use these genomic association datasets to improve our mechanistic understanding of antidepressant actions and response
5. Test the results from our genetic studies in experimental cell-based in vitro models
6. Conduct our research in collaboration with individuals with lived experience to increase trust, facilitate research that is relevant and important to patients, and improve dissemination and impact.