IFN-γ and TNF-α drive a CXCL10+ CCL2+ macrophage phenotype expanded in severe COVID-19 lungs and inflammatory diseases with tissue inflammation
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Background
Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies.
Methods
To identify cellular phenotypes that may be shared across tissues affected by disparate inflammatory diseases, we developed a meta-analysis and integration pipeline that models and removes the effects of technology, tissue of origin, and donor that confound cell-type identification. Using this approach, we integrated > 300,000 single-cell transcriptomic profiles from COVID-19-affected lungs and tissues from healthy subjects and patients with five inflammatory diseases: rheumatoid arthritis (RA), Crohn’s disease (CD), ulcerative colitis (UC), systemic lupus erythematosus (SLE), and interstitial lung disease. We tested the association of shared immune states with severe/inflamed status compared to healthy control using mixed-effects modeling. To define environmental factors within these tissues that shape shared macrophage phenotypes, we stimulated human blood-derived macrophages with defined combinations of inflammatory factors, emphasizing in particular antiviral interferons IFN-beta (IFN-β) and IFN-gamma (IFN-γ), and pro-inflammatory cytokines such as TNF.
Results
We built an immune cell reference consisting of > 300,000 single-cell profiles from 125 healthy or disease-affected donors from COVID-19 and five inflammatory diseases. We observed a CXCL10+ CCL2+ inflammatory macrophage state that is shared and strikingly abundant in severe COVID-19 bronchoalveolar lavage samples, inflamed RA synovium, inflamed CD ileum, and UC colon. These cells exhibited a distinct arrangement of pro-inflammatory and interferon response genes, including elevated levels of CXCL10 , CXCL9 , CCL2 , CCL3 , GBP1, STAT1 , and IL1B . Further, we found this macrophage phenotype is induced upon co-stimulation by IFN-γ and TNF-α.
Conclusions
Our integrative analysis identified immune cell states shared across inflamed tissues affected by inflammatory diseases and COVID-19. Our study supports a key role for IFN-γ together with TNF-α in driving an abundant inflammatory macrophage phenotype in severe COVID-19-affected lungs, as well as inflamed RA synovium, CD ileum, and UC colon, which may be targeted by existing immunomodulatory therapies.
Article activity feed
-
-
SciScore for 10.1101/2020.08.05.238360: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
Identifier Status Title NCT04337359 No longer available Ruxolitinib Managed Access Program (MAP) for Patients Diagno… NCT04359290 Active, not recruiting Ruxolitinib for Treatment … SciScore for 10.1101/2020.08.05.238360: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
Identifier Status Title NCT04337359 No longer available Ruxolitinib Managed Access Program (MAP) for Patients Diagno… NCT04359290 Active, not recruiting Ruxolitinib for Treatment of Covid-19 Induced Lung Injury AR… NCT04348695 Recruiting Study of Ruxolitinib Plus Simvastatin in the Prevention and … Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
-
SciScore for 10.1101/2020.08.05.238360: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources trea IFN IL FNh fi h fibTN rea IFN IL t d i t ti it wi wi Un an w w w Un -γ -α α -γ α F- IFN FFN TNF N I T nd a -α F TN CCL23 15 4 2 0 Fold change, TNF-α (vs untreated) f CCL2 IDO1 CXCL10 AN MRC1 4 3 2 1 0 P9 3 2 1 0 1A CXCL9 CLEC4A 3 2 1 0 ● ● γ o γ γ α d N- fibr fibro F- ate N-β L-4 N- ro - ro ro -α ed -β 4 N I IF fib FN ib ib F at N Lth ith T ntre IF d ith I ith f ith f TNtre IF I n w a w U Un α α γwαw F- N-γ w w w Un -γ -α α -γ α F-suggested: NoneRes…
SciScore for 10.1101/2020.08.05.238360: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources trea IFN IL FNh fi h fibTN rea IFN IL t d i t ti it wi wi Un an w w w Un -γ -α α -γ α F- IFN FFN TNF N I T nd a -α F TN CCL23 15 4 2 0 Fold change, TNF-α (vs untreated) f CCL2 IDO1 CXCL10 AN MRC1 4 3 2 1 0 P9 3 2 1 0 1A CXCL9 CLEC4A 3 2 1 0 ● ● γ o γ γ α d N- fibr fibro F- ate N-β L-4 N- ro - ro ro -α ed -β 4 N I IF fib FN ib ib F at N Lth ith T ntre IF d ith I ith f ith f TNtre IF I n w a w U Un α α γwαw F- N-γ w w w Un -γ -α α -γ α F-suggested: NoneResults from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.
-