Abstract: medRxiv preprint doi: https://doi.org/10.1101/2022.07.02.22277181; this version posted July 6, 2022. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Integrative analysis of viral entry networks and clinical outcomes identifies a protective role for spironolactone in severe COVID-19 Henry Cousins1,2,*, Adrienne Sarah Kline3, Chengkun Wang4,5, Yuanhao Qu4,5, Mengdi Wang6, Russ Altman1,4,7,8,*, Yuan Luo3,*, Le Cong4,5,* 1 Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA 2 Medical Scientist Training Program, Stanford University School of Medicine, Stanford, CA, USA 3 Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA 4 Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA 5 Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA 6 Department of Electronic Engineering, Princeton University, Princeton, NJ, USA 7 Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA 8 Department of Bioengineering, Stanford University, Stanford, CA, USA * Correspondence to: cousinsh@stanford.edu (H.C.), russ.altman@stanford.edu (R.A.), Yuan.Luo@northwestern.edu (Y.L.), congle@stanford.edu (L.C.) ABSTRACT Treatment strategies that target host entry factors have proven an effective means of impeding viral entry in HIV and may be more robust to viral evolution than drugs targeting viral proteins directly. High-throughput functional screens provide an unbiased means of identifying genes that influence the infection of host cells, while retrospective cohort analysis can measure the real-world, clinical potential of repurposing existing therapeutics as antiviral treatments. Here, we combine these two powerful methods to identify drugs that alter the clinical course of COVID-19 by targeting host entry factors. We demonstrate that integrative analysis of genomewide CRISPR screening datasets enables network-based prioritization of drugs modulating viral entry, and we identify three common medications (spironolactone, quetiapine, and carvedilol) based on their network proximity to putative host factors. To understand the drugs’ real-world impact, we perform a propensity-score-matched, retrospective cohort study of 64,349 COVID-19 patients and show that spironolactone use is associated with improved clinical prognosis, measured by both ICU admission and mechanical ventilation rates. Finally, we show that spironolactone exerts a dose-dependent inhibitory effect on viral entry in a human lung epithelial cell line. Our results suggest that spironolactone may improve clinical outcomes in COVID-19 through tissue-dependent inhibition of viral entry. Our work further provides a potential approach to integrate functional genomics with real-world evidence for drug repurposing. NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2022.07.02.22277181; this version posted July 6, 2022. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse..