Abstract
We demonstrate that integrative analysis of CRISPR screening datasets enables network-based prioritization 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 protective role of the potassium-sparing diuretic spironolactone in severe COVID-19.
Original language | English (US) |
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Article number | 100503 |
Journal | Cell Reports Methods |
Volume | 3 |
Issue number | 7 |
DOIs | |
State | Published - Jul 24 2023 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Genetics
- Biochemistry, Genetics and Molecular Biology (miscellaneous)
- Biochemistry
- Radiology Nuclear Medicine and imaging
- Biotechnology
- Computer Science Applications
Keywords
- CP: Microbiology
- CP: Systems biology