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0 0.5 1 1.5 2+ Hospitalization 67% Improvement Relative Risk Progression 57% Indomethacin  Gordon et al.  LATE TREATMENT Is late treatment with indomethacin beneficial for COVID-19? PSM retrospective 206 patients in the USA Study compares with celecoxib, results vs. placebo may differ Lower hospitalization (p=0.34) and progression (p=0.21), not sig. c19early.org Gordon et al., Science, December 2020 Favors indomethacin Favors celecoxib

Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms

Gordon et al., Science, doi:10.1126/science.abe9403
Dec 2020  
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Analysis of interactions between viral and human proteins for SARS-CoV-2, SARS-CoV-1, and MERS-CoV and genetic screening to identify host factors that enhance or inhibit viral infection.
Authors predict indomethacin will have antiviral activity for SARS-CoV-2 and perform a retrospective study of patients in the USA that started treatment within 21 days after COVID-19 infection - 103 with indomethacin, and 103 using a celecoxib, a clinically similar drug without predicted antiviral activity. There were fewer hospital visits and hospitalizations with indomethacin, without statistical significance.
risk of hospitalization, 66.7% lower, RR 0.33, p = 0.34, treatment 1 of 103 (1.0%), control 3 of 103 (2.9%), NNT 51, RSS and PSM, propensity score matching.
risk of progression, 57.1% lower, RR 0.43, p = 0.21, treatment 3 of 103 (2.9%), control 7 of 103 (6.8%), NNT 26, RSS and PSM, propensity score matching.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Gordon et al., 4 Dec 2020, retrospective, USA, peer-reviewed, 200 authors, this trial compares with another treatment - results may be better when compared to placebo. Contact: pbeltrao@ebi.ac.uk, marco.vignuzzi@pasteur.fr, cbasler@gsu.edu, verba@msg.ucsf, oren.rosenberg@ucsf.edu, a.peden@sheffield.ac.uk, robert.grosse@pharmakol.uni-freiburg.de, jeremy.rassen@aetion.com, garcia-sastre@mssm.edu, nevan.krogan@ucsf.edu, verba@msg.ucsf.edu, rosenberg@ucsf.edu, adolfo.garcia-sastre@mssm.edu.
This PaperIndomethacinAll
Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms
David E Gordon, Joseph Hiatt, Mehdi Bouhaddou, Veronica V Rezelj, Svenja Ulferts, Hannes Braberg, Alexander S Jureka, Kirsten Obernier, Jeffrey Z Guo, Jyoti Batra, Robyn M Kaake, Andrew R Weckstein, Tristan W Owens, Meghna Gupta, Sergei Pourmal, Erron W Titus, Merve Cakir, Margaret Soucheray, Michael Mcgregor, Zeynep Cakir, Gwendolyn Jang, Matthew J O’meara, Tia A Tummino, Ziyang Zhang, Helene Foussard, Ajda Rojc, Yuan Zhou, Dmitry Kuchenov, Ruth Hüttenhain, Jiewei Xu, Manon Eckhardt, Danielle L Swaney, Jacqueline M Fabius, Manisha Ummadi, Beril Tutuncuoglu, Ujjwal Rathore, Maya Modak, Paige Haas, Kelsey M Haas, Zun Zar Chi Naing, Ernst H Pulido, Ying Shi, Inigo Barrio-Hernandez, Danish Memon, Eirini Petsalaki, Alistair Dunham, Miguel Correa Marrero, David Burke, Cassandra Koh, Thomas Vallet, Jesus A Silvas, Caleigh M Azumaya, Christian Billesbølle, Axel F Brilot, Melody G Campbell, Amy Diallo, Miles Sasha Dickinson, Devan Diwanji, Nadia Herrera, Nick Hoppe, Huong T Kratochvil, Yanxin Liu, Gregory E Merz, Michelle Moritz, Henry C Nguyen, Carlos Nowotny, Cristina Puchades, Alexandrea N Rizo, Ursula Schulze-Gahmen, Amber M Smith, Ming Sun, Iris D Young, Jianhua Zhao, Daniel Asarnow, Justin Biel, Alisa Bowen, Julian R Braxton, Jen Chen, Cynthia M Chio, Un Seng Chio, Ishan Deshpande, Loan Doan, Bryan Faust, Sebastian Flores, Mingliang Jin, Kate Kim, Victor L Lam, Fei Li, Junrui Li, Yen-Li Li, Yang Li, Xi Liu, Megan Lo, Kyle E Lopez, Arthur A Melo, Frank R Moss III, Phuong Nguyen, Joana Paulino, Komal Ishwar Pawar, Jessica K Peters, Thomas H Pospiech Jr, Maliheh Safari, Smriti Sangwan, Kaitlin Schaefer, Paul V Thomas, Aye C Thwin, Raphael Trenker, Eric Tse, Tsz Kin Martin Tsui, Feng Wang, Natalie Whitis, Zanlin Yu, Kaihua Zhang, Yang Zhang, Fengbo Zhou, Daniel Saltzberg, Anthony J Hodder, Amber S Shun-Shion, Daniel M Williams, Kris M White, Romel Rosales, Thomas Kehrer, Lisa Miorin, Elena Moreno, Arvind H Patel, Suzannah Rihn, Mir M Khalid, Albert Vallejo-Gracia, Parinaz Fozouni, Camille R Simoneau, Theodore L Roth, David Wu, Mohd Anisul Karim, Maya Ghoussaini, Ian Dunham, Francesco Berardi, Sebastian Weigang, Maxime Chazal, Jisoo Park, James Logue, Marisa Mcgrath, Stuart Weston, Robert Haupt, C James Hastie, Matthew Elliott, Fiona Brown, Kerry A Burness, Elaine Reid, Mark Dorward, Clare Johnson, Stuart G Wilkinson, Anna Geyer, Daniel M Giesel, Carla Baillie, Samantha Raggett, Hannah Leech, Rachel Toth, Nicola Goodman, Kathleen C Keough, Abigail L Lind, Reyna J Klesh, Kafi R Hemphill, Jared Carlson-Stevermer, Jennifer Oki, Kevin Holden, Travis Maures, Katherine S Pollard, Andrej Sali, David A Agard, Yifan Cheng, James S Fraser, Adam Frost, Natalia Jura, Tanja Kortemme, Aashish Manglik, Daniel R Southworth, Robert M Stroud, Dario R Alessi, Paul Davies, Matthew B Frieman, Trey Ideker, Carmen Abate, Nolwenn Jouvenet, Georg Kochs, Brian Shoichet, Melanie Ott, Massimo Palmarini, Kevan M Shokat, Adolfo García-Sastre, Jeremy A Rassen, Robert Grosse, Oren S Rosenberg, Kliment A Verba, Christopher F Basler, Marco Vignuzzi, Andrew A Peden, Pedro Beltrao, Nevan J Krogan, Tristan W Owens, Meghna Gupta, Sergei Pourmal, Erron W Titus, Caleigh M Azumaya, Christian Billesbølle, Axel F Brilot, Melody G Campbell, Amy Diallo, Miles Sasha Dickinson, Devan Diwanji, Nadia Herrera, Nick Hoppe, Huong T Kratochvil, Yanxin Liu, Gregory E Merz, Michelle Moritz, Henry C Nguyen, Carlos Nowotny, Cristina Puchades, Alexandrea N Rizo, Ursula Schulze-Gahmen, Amber M Smith, Ming Sun, Iris D Young, Jianhua Zhao, Daniel Asarnow, Justin Biel, Alisa Bowen, Julian R Braxton, Jen Chen, Cynthia M Chio, Un Seng Chio, Ishan Deshpande, Loan Doan, Bryan Faust, Sebastian Flores, Mingliang Jin, Kate Kim, Victor L Lam, Fei Li, Junrui Li, Yen-Li Li, Yang Li, Xi Liu, Megan Lo, Kyle E Lopez, Arthur A Melo, Frank R Moss III, Phuong Nguyen, Joana Paulino, Komal Ishwar Pawar
Science, doi:10.1126/science.abe9403
The emergence of three lethal coronaviruses in <20 years and the urgency of the COVID-19 pandemic have prompted efforts to develop new therapeutic strategies, including by repurposing existing agents. After performing a comparative analysis of the three pathogenic human coronaviruses severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1), SARS-CoV-2, and Middle East respiratory syndrome coronavirus (MERS-CoV), we identified shared biology and host-directed drug targets to prioritize therapeutics with potential for rapid deployment against current and future coronavirus outbreaks. RATIONALE: Expanding on our recent SARS-CoV-2 interactome, we mapped the virus-host protein-protein interactions for SARS-CoV-1 and MERS-CoV and assessed the cellular localization of each viral protein across the three strains. We conducted two genetic screens of SARS-CoV-2 interactors to prioritize functionally-relevant host factors and structurally characterized one virus-host interaction. We then tested the clinical relevance of three more host factors by assessing risk in genetic cohorts or observing effectiveness of host factor-targeting drugs in realworld evidence. RESULTS: Quantitative comparison of the 389 interactors of SARS-CoV-2, 366 of SARS-CoV-1, and 296 of MERS-CoV highlighted interactions with host processes that are conserved across all three viruses, including where nonorthologous proteins from different virus strains seem to fill similar roles. We also localized each individually-expressed viral protein by microscopy and then raised and validated antisera against 14 SARS-CoV-2 proteins to determine their localization during infection. On the basis of two independent genetic perturbation screens, we identified 73 host factors that, when depleted, caused significant changes in SARS-CoV-2 replication. From this list of potential drug targets, we validated the biological and clinical relevance of Tom70, IL17RA, PGES-2, and SigmaR1. A 3-Å cryo-electron microscopy structure of Tom70, a mitochondrial import receptor, in complex with SARS-CoV-2 ORF9b, provides insight into how ORF9b may modulate the host immune response. Using curated genome-wide association study data, we found that individuals with genotypes corresponding to higher soluble IL17RA levels in plasma are at decreased risk of COVID-19 hospitalization. To demonstrate the value of our data for drug repurposing, we identified SARS-CoV-2 patients who were prescribed drugs against prioritized targets and asked how they fared compared with carefully matched patients treated with clinically similar drugs that do not inhibit SARS-CoV-2. Both indomethacin, an inhibitor of host factor PGES-2, and typical antipsychotics, selected for their interaction with sigma receptors, showed effectiveness against COVID-19 compared with celecoxib and atypical antipsychotics, respectively. CONCLUSION: By employing an integrative and collaborative approach, we identified conserved mechanisms across three..
resources and reagents should be directed to and will be fulfilled by N.J.K. (nevan.krogan@ucsf.edu). The MS proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD021588 (100) . An interactive version of PPI data can be found at https://kroganlab. ucsf.edu/network-maps. Atomic coordinates and the cryo-EM map of the reported Tom70-ORF9b structure have been deposited in the Protein Data Bank under accession code 7KDT and in the Electron Microscopy Data Bank under accession code EMD-22829. Expression vectors used in this study are readily available from the authors for biomedical researchers and educators in the nonprofit sector. The Aetion Evidence Platform used for the clinical analysis is available under license from Aetion, New York, NY. To protect patient privacy, data used in real-world analyses are available for inspection by qualified researchers under confidentiality and third-party agreements with Aetion and/or HealthVerity. This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/. This license does not apply to figures/photos/artwork or other content included in the article that is credited to a third party; obtain authorization from the rights..
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{ 'DOI': '10.1126/science.abe9403', 'ISSN': ['0036-8075', '1095-9203'], 'URL': 'http://dx.doi.org/10.1126/science.abe9403', 'abstract': '<jats:title>How lethal coronaviruses engage hosts</jats:title>\n' ' <jats:p>\n' ' Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is closely related ' 'to the deadly coronaviruses SARS-CoV-1 and Middle East respiratory syndrome coronavirus ' '(MERS-CoV). Considerable efforts are focused on developing treatments, and therapies that ' 'work across coronaviruses would be particularly valuable. Shedding light on the host factors ' 'hijacked by the viruses, Gordon\n' ' <jats:italic>et al.</jats:italic>\n' ' mapped the interactions between viral and human proteins for SARS-CoV-2, ' 'SARS-CoV-1, and MERS-CoV; analyzed the localization of viral proteins in human cells; and ' 'used genetic screening to identify host factors that either enhance or inhibit viral ' 'infection. For a subset of the interactions essential for the virus life cycle, the authors ' 'determined the cryo–electron microscopy structures and mined patient data to understand how ' 'targeting host factors may be relevant to clinical outcomes.\n' ' </jats:p>\n' ' <jats:p>\n' ' <jats:italic>Science</jats:italic>\n' ' , this issue p.\n' ' <jats:related-article xmlns:xlink="http://www.w3.org/1999/xlink" ' 'ext-link-type="doi" related-article-type="in-this-issue" ' 'xlink:href="10.1126/science.abe9403">eabe9403</jats:related-article>\n' ' </jats:p>', 'alternative-id': ['10.1126/science.abe9403'], 'author': [ { 'ORCID': 'http://orcid.org/0000-0001-7954-0306', 'affiliation': [ { 'name': 'Quantitative Biosciences Institute (QBI) COVID-19 Research Group ' '(QCRG), San Francisco, CA 94158, USA.'}, {'name': 'QBI, University of California, San Francisco, CA 94158, USA.'}, { 'name': 'Department of Cellular and Molecular Pharmacology, University of ' 'California, San Francisco, CA 94158, USA.'}, {'name': 'J. 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Late treatment
is less effective
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Treatments and other interventions are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
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