A mechanistic model and therapeutic interventions for COVID-19 involving a RAS-mediated bradykinin storm
- Oak Ridge National Laboratory, United States
- University of Tennessee Knoxville, United States
- University of Kentucky, United States
- Medical College of Wisconsin, United States
- Yale University, United States
- Cincinnati Children's Hospital Research Foundation, United States
Abstract
Neither the disease mechanism nor treatments for COVID-19 are currently known. Here we present a novel molecular mechanism for COVID-19 that provides therapeutic intervention points that can be addressed with existing FDA-approved pharmaceuticals. The entry point for the virus is ACE2, which is a component of the counteracting hypotensive axis of RAS, that produces the nonapeptide angiotensin1-9 from angiotensin I. Bradykinin is a potent, but often forgotten, part of the vasopressor system that induces hypotension and vasodilation 1, and is regulated by ACE and enhanced by angiotensin1-9 2. Here we perform a completely new analysis on gene expression data from cells of bronchoalveolar lavage samples from COVID-19 patients that were used to sequence the virus, but the host information was discarded 3. Comparison with lavage samples from controls identify a critical imbalance in RAS represented by decreased expression of ACE in combination with increases in ACE2, renin (REN) , angiotensin (AGT), key RAS receptors (AGTR2, AGTR1), kinogen (KNG) and the kallikrein enzymes (KLKB1, many of KLK-1-15) that activate it, and both bradykinin receptors (BDKRB1, BDKRB2). This very atypical pattern of the RAS is predicted to elevate bradykinin levels in multiple tissues and systems that will likely cause increases in vascular dilation, vascular permeability and hypotension. These bradykinin-driven outcomes explain many of the symptoms being observed in COVID-19.
Data availability
FASTQ files are available from the NCBI Sequence Read Archive (PRJNA605983 and PRJNA434133)https://www.ncbi.nlm.nih.gov/sraLeinonen, R., Sugawara, H., Shumway, M. and International Nucleotide Sequence Database Collaboration, 2010. The sequence read archive. Nucleic acids research, 39(suppl_1), pp.D19-D21.
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Microbiome and Inflammatory Interactions in Obese and Severe Asthmatic AdultsNCBI Sequence Read Archive, PRJNA434133.
Article and author information
Author details
Funding
Oak Ridge National Laboratory (LOIS:10074)
- Mike R Garvin
- J Izaak Miller
- Erica T Prates
- Daniel Jacobson
U.S. Department of Energy (National Virtual Biotechnology Laboratory)
- Mike R Garvin
- Christiane Alvarez
- J Izaak Miller
- Erica T Prates
- Angelica M Walker
- Daniel Jacobson
National Institutes of Health (U24 HL148865)
- Bruce Aronow
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Frank L van de Veerdonk, Radboud University Medical Center, Netherlands
Version history
- Received: May 21, 2020
- Accepted: July 6, 2020
- Accepted Manuscript published: July 7, 2020 (version 1)
- Accepted Manuscript updated: July 8, 2020 (version 2)
- Version of Record published: August 6, 2020 (version 3)
Copyright
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
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A mechanistic model and therapeutic interventions for COVID-19 involving a RAS-mediated bradykinin storm
eLife 9:e59177.
https://doi.org/10.7554/eLife.59177
Further reading
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- Medicine
- Microbiology and Infectious Disease
- Epidemiology and Global Health
- Immunology and Inflammation
eLife has published articles on a wide range of infectious diseases, including COVID-19, influenza, tuberculosis, HIV/AIDS, malaria and typhoid fever.
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- Computational and Systems Biology
Transcriptomic profiling became a standard approach to quantify a cell state, which led to accumulation of huge amount of public gene expression datasets. However, both reuse of these datasets or analysis of newly generated ones requires significant technical expertise. Here we present Phantasus - a user-friendly web-application for interactive gene expression analysis which provides a streamlined access to more than 96000 public gene expression datasets, as well as allows analysis of user-uploaded datasets. Phantasus integrates an intuitive and highly interactive JavaScript-based heatmap interface with an ability to run sophisticated R-based analysis methods. Overall Phantasus allows users to go all the way from loading, normalizing and filtering data to doing differential gene expression and downstream analysis. Phantasus can be accessed on-line at https://alserglab.wustl.edu/phantasus or can be installed locally from Bioconductor (https://bioconductor.org/packages/phantasus). Phantasus source code is available at https://github.com/ctlab/phantasus under MIT license.
