1
|
Sperry MM, Oskotsky TT, Marić I, Kaushal S, Takeda T, Horvath V, Powers RK, Rodas M, Furlong B, Soong M, Prabhala P, Goyal G, Carlson KE, Wong RJ, Kosti I, Le BL, Logue J, Hammond H, Frieman M, Stevenson DK, Ingber DE, Sirota M, Novak R. Target-agnostic drug prediction integrated with medical record analysis uncovers differential associations of statins with increased survival in COVID-19 patients. PLoS Comput Biol 2023; 19:e1011050. [PMID: 37146076 PMCID: PMC10191356 DOI: 10.1371/journal.pcbi.1011050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 05/17/2023] [Accepted: 03/27/2023] [Indexed: 05/07/2023] Open
Abstract
Drug repurposing requires distinguishing established drug class targets from novel molecule-specific mechanisms and rapidly derisking their therapeutic potential in a time-critical manner, particularly in a pandemic scenario. In response to the challenge to rapidly identify treatment options for COVID-19, several studies reported that statins, as a drug class, reduce mortality in these patients. However, it is unknown if different statins exhibit consistent function or may have varying therapeutic benefit. A Bayesian network tool was used to predict drugs that shift the host transcriptomic response to SARS-CoV-2 infection towards a healthy state. Drugs were predicted using 14 RNA-sequencing datasets from 72 autopsy tissues and 465 COVID-19 patient samples or from cultured human cells and organoids infected with SARS-CoV-2. Top drug predictions included statins, which were then assessed using electronic medical records containing over 4,000 COVID-19 patients on statins to determine mortality risk in patients prescribed specific statins versus untreated matched controls. The same drugs were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus. Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins, including atorvastatin, were predicted to be active in > 50% of analyses. Analysis of the clinical database revealed that reduced mortality risk was only observed in COVID-19 patients prescribed a subset of statins, including simvastatin and atorvastatin. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent direct inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells. Statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared drug target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and clinically evaluate non-obvious mechanisms and derisk and accelerate drug repurposing opportunities.
Collapse
Affiliation(s)
- Megan M. Sperry
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
- Department of Biology, Tufts University, Medford, Massachusetts, United States of America
| | - Tomiko T. Oskotsky
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, California, United States of America
- Department of Pediatrics, University of California San Francisco, San Francisco, California, United States of America
| | - Ivana Marić
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, California, United States of America
- Center for Academic Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Shruti Kaushal
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| | - Takako Takeda
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| | - Viktor Horvath
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| | - Rani K. Powers
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| | - Melissa Rodas
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| | - Brooke Furlong
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| | - Mercy Soong
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| | - Pranav Prabhala
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| | - Girija Goyal
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| | - Kenneth E. Carlson
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| | - Ronald J. Wong
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, California, United States of America
- Center for Academic Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Idit Kosti
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, California, United States of America
- Department of Pediatrics, University of California San Francisco, San Francisco, California, United States of America
| | - Brian L. Le
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, California, United States of America
- Department of Pediatrics, University of California San Francisco, San Francisco, California, United States of America
| | - James Logue
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Holly Hammond
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Matthew Frieman
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - David K. Stevenson
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, California, United States of America
- Center for Academic Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Donald E. Ingber
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
- Vascular Biology Program and Department of Surgery, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Harvard John A. Paulson School of Engineering and Applied Sciences, Cambridge, Massachusetts, United States of America
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, California, United States of America
- Department of Pediatrics, University of California San Francisco, San Francisco, California, United States of America
| | - Richard Novak
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America
| |
Collapse
|
2
|
Lao US, Law CF, Baptista-Hon DT, Tomlinson B. Systematic Review and Meta-Analysis of Statin Use and Mortality, Intensive Care Unit Admission and Requirement for Mechanical Ventilation in COVID-19 Patients. J Clin Med 2022; 11:5454. [PMID: 36143101 PMCID: PMC9501062 DOI: 10.3390/jcm11185454] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 09/04/2022] [Accepted: 09/14/2022] [Indexed: 11/26/2022] Open
Abstract
There is mounting evidence that statin use is beneficial for COVID-19 outcomes. We performed a systematic review and meta-analysis to evaluate the association between statin use and mortality, intensive care unit (ICU) admission and mechanical ventilation in COVID-19 patients, on studies which provided covariate adjusted effect estimates, or performed propensity score matching. We searched PubMed, Embase, Web of Science and Scopus for studies and extracted odds or hazard ratios for specified outcome measures. Data synthesis was performed using a random-effects inverse variance method. Risk of bias, heterogeneity and publication bias were analyzed using standard methods. Our results show that statin use was associated with significant reductions in mortality (OR = 0.72, 95% CI: 0.67-0.77; HR = 0.74, 95% CI: 0.69, 0.79), ICU admission (OR = 0.94, 95% CI: 0.89-0.99; HR = 0.76, 95% CI: 0.60-0.96) and mechanical ventilation (OR = 0.84, 95% CI: 0.78-0.92; HR = 0.67, 95% CI: 0.47-0.97). Nevertheless, current retrospective studies are based on the antecedent use of statins prior to infection and/or continued use of statin after hospital admission. The results may not apply to the de novo commencement of statin treatment after developing COVID-19 infection. Prospective studies are lacking and necessary.
Collapse
Affiliation(s)
- Ut-Sam Lao
- Center for Biomedicine and Innovations, Faculty of Medicine, Macau University Science and Technology, Taipa, Macau SAR 999078, China
| | - Chak-Fun Law
- Center for Biomedicine and Innovations, Faculty of Medicine, Macau University Science and Technology, Taipa, Macau SAR 999078, China
| | - Daniel T. Baptista-Hon
- Center for Biomedicine and Innovations, Faculty of Medicine, Macau University Science and Technology, Taipa, Macau SAR 999078, China
- Division of Systems Medicine, School of Medicine, University of Dundee, Dundee DD1 4HN, UK
| | - Brian Tomlinson
- Center for Biomedicine and Innovations, Faculty of Medicine, Macau University Science and Technology, Taipa, Macau SAR 999078, China
| |
Collapse
|