Integrative analysis of functional genomic screening and clinical data identifies a protective role for spironolactone in severe COVID-19

We demonstrate that integrative analysis of CRISPR screening datasets enables network-based prioritiza-tion of prescription drugs modulating viral entry in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by developing a network-based approach called Rapid proXimity Guidance for Repurposing Investigational Drugs (RxGRID). We use our results to guide a propensity-score-matched, retrospective cohort study of 64,349 COVID-19 patients, showing that a top candidate drug, spironolactone, is associated with improved clinical prognosis, measured by intensive care unit (ICU) admission and mechanical ventilation rates. Finally, we show that spironolactone exerts a dose-dependent inhibitory effect on viral entry in human lung epithelial cells. Our RxGRID method presents a computational framework, implemented as an open -source software package, enabling genomics researchers to identify drugs likely to modulate a molecular phenotype of interest based on high-throughput screening data. Our results, derived from this method and supported by experimental and clinical analysis, add additional supporting evidence for a potential pro-tective role of the potassium-sparing diuretic spironolactone in severe COVID-19.

Automated summary

We developed a network-based approach called Rapid proXimity Guidance for Repurposing Investigational Drugs (RxGRID) to prioritize prescription drugs modulating SARS-CoV-2 viral entry. Using this method, we identified a top candidate drug called spironolactone, which was associated with improved clinical prognosis in a retrospective cohort study of COVID-19 patients. We also demonstrated that spironolactone inhibits viral entry in human lung epithelial cells in a dose-dependent manner. Our RxGRID method provides a computational framework for genomics researchers to identify drugs of interest based on high-throughput screening data.