TY - JOUR
T1 - Integrative analysis of functional genomic screening and clinical data identifies a protective role for spironolactone in severe COVID-19
AU - Cousins, Henry C.
AU - Kline, Adrienne Sarah
AU - Wang, Chengkun
AU - Qu, Yuanhao
AU - Zengel, James
AU - Carette, Jan
AU - Wang, Mengdi
AU - Altman, Russ B.
AU - Luo, Yuan
AU - Cong, Le
N1 - Funding Information:
This work was supported by the National Institutes of Health ( GM007365 and GM145402 to H.C.C., GM102365 to R.B.A., LM013337 to Y.L., GM141627 and HG011316 to L.C.), by the Donald and Delia Baxter Foundation (to L.C.), by the National Science Foundation ( 1953686 to M.W.), by the Knight-Hennessy Scholarships (to H.C.C.), and by a kind gift from the Weintz Family (to L.C.). The funding bodies had no role in the design of the study and collection, analysis, and interpretation of data or in writing the manuscript. Figure 1 and the graphical abstract were created using BioRender.
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/7/24
Y1 - 2023/7/24
N2 - 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.
AB - 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.
KW - CP: Microbiology
KW - CP: Systems biology
UR - http://www.scopus.com/inward/record.url?scp=85163354846&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85163354846&partnerID=8YFLogxK
U2 - 10.1016/j.crmeth.2023.100503
DO - 10.1016/j.crmeth.2023.100503
M3 - Article
C2 - 37529368
AN - SCOPUS:85163354846
SN - 2667-2375
VL - 3
JO - Cell Reports Methods
JF - Cell Reports Methods
IS - 7
M1 - 100503
ER -