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Integrating gene expression and clinical data to identify drug repurposing candidates for hyperlipidemia and hypertension

Wu, P., Feng, Q., Kerchberger, V.E., Nelson, S.D., Chen, Q., Li, B., Edwards, T.L., Cox, N.J., Phillips, E.J., Stein, C.M., Roden, D.M., Denny, J.C. and Wei, W-Q (2022) Integrating gene expression and clinical data to identify drug repurposing candidates for hyperlipidemia and hypertension. Nature Communications, 13 (1). Art. 46.

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Free to read: https://doi.org/10.1038/s41467-021-27751-1
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Abstract

Discovering novel uses for existing drugs, through drug repurposing, can reduce the time, costs, and risk of failure associated with new drug development. However, prioritizing drug repurposing candidates for downstream studies remains challenging. Here, we present a high-throughput approach to identify and validate drug repurposing candidates. This approach integrates human gene expression, drug perturbation, and clinical data from publicly available resources. We apply this approach to find drug repurposing candidates for two diseases, hyperlipidemia and hypertension. We screen >21,000 compounds and replicate ten approved drugs. We also identify 25 (seven for hyperlipidemia, eighteen for hypertension) drugs approved for other indications with therapeutic effects on clinically relevant biomarkers. For five of these drugs, the therapeutic effects are replicated in the All of Us Research Program database. We anticipate our approach will enable researchers to integrate multiple publicly available datasets to identify high priority drug repurposing opportunities for human diseases.

Item Type: Journal Article
Murdoch Affiliation(s): Institute for Immunology and Infectious Diseases
Publisher: Springer Nature
Copyright: © 2022 The Authors.
URI: http://researchrepository.murdoch.edu.au/id/eprint/63638
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