COVID-19 lung disease shares driver AT2 cytopathic features with Idiopathic pulmonary fibrosis

Abstract

Background

In the aftermath of Covid-19, some patients develop a fibrotic lung disease, i.e., p ost- C OVID-19 l ung d isease (PCLD), for which we currently lack insights into pathogenesis, disease models, or treatment options.

Method

Using an AI-guided approach, we analyzed > 1000 human lung transcriptomic datasets associated with various lung conditions using two viral pandemic signatures (ViP and sViP) and one covid lung-derived signature. Upon identifying similarities between COVID-19 and idiopathic pulmonary fibrosis (IPF), we subsequently dissected the basis for such similarity from molecular, cytopathic, and immunologic perspectives using a panel of IPF-specific gene signatures, alongside signatures of alveolar type II (AT2) cytopathies and of prognostic monocyte-driven processes that are known drivers of IPF. Transcriptome-derived findings were used to construct protein-protein interaction (PPI) network to identify the major triggers of AT2 dysfunction. Key findings were validated in hamster and human adult lung organoid (ALO) pre-clinical models of COVID-19 using immunohistochemistry and qPCR.

Findings

COVID-19 resembles IPF at a fundamental level; it recapitulates the gene expression patterns (ViP and IPF signatures), cytokine storm (IL15-centric) and the AT2 cytopathic changes, e.g., injury, DNA damage, arrest in a transient, damage-induced progenitor state, and senescence-associated secretory phenotype (SASP). These immunocytopathic features were induced in pre-clinical COVID models (ALO and hamster) and reversed with effective anti-CoV-2 therapeutics in hamsters. PPI-network analyses pinpointed ER stress as one of the shared early triggers of both diseases, and IHC studies validated the same in the lungs of deceased subjects with COVID-19 and SARS-CoV-2-challenged hamster lungs. Lungs from tg - mice, in which ER stress is induced specifically in the AT2 cells, faithfully recapitulate the host immune response and alveolar cytopathic changes that are induced by SARS-CoV-2.

Interpretation

Like IPF, COVID-19 may be driven by injury-induced ER stress that culminates into progenitor state arrest and SASP in AT2 cells. The ViP signatures in monocytes may be key determinants of prognosis. The insights, signatures, disease models identified here are likely to spur the development of therapies for patients with IPF and other fibrotic interstitial lung disease.

Funding

This work was supported by the National Institutes for Health grants R01-GM138385 and AI155696 and funding from the Tobacco-Related disease Research Program (R01RG3780).

One Sentence Summary

Severe COVID-19 triggers cellular processes seen in fibrosing Interstitial Lung Disease

ScreenIT

Dec 2, 2021

SciScore for 10.1101/2021.11.28.470269: (What is this?)

Please note, not all rigor criteria are appropriate for all manuscripts.

Table 1: Rigor

Ethics	Consent: At the time of enrollment, all COVID-19 donors provided written informed consent to participate in the present and future studies. Field Sample Permit: Animal studies were approved and performed in accordance with Scripps Research IACUC Protocol #20-000328. IACUC: Animal studies were approved and performed in accordance with Scripps Research IACUC Protocol #20-000328.
Sex as a biological variable	not detected.
Randomization	IHC Quantification: IHC images were randomly sampled at different 300x300 pixel regions of interest (ROI).
Blinding	not detected.
Power Analysis	not detected.

Table 2: Resources

Antibodies
Sentences	Resources
We chose three different groups of samples: uninfected control, …

SciScore for 10.1101/2021.11.28.470269: (What is this?)

Please note, not all rigor criteria are appropriate for all manuscripts.

Table 1: Rigor

Ethics	Consent: At the time of enrollment, all COVID-19 donors provided written informed consent to participate in the present and future studies. Field Sample Permit: Animal studies were approved and performed in accordance with Scripps Research IACUC Protocol #20-000328. IACUC: Animal studies were approved and performed in accordance with Scripps Research IACUC Protocol #20-000328.
Sex as a biological variable	not detected.
Randomization	IHC Quantification: IHC images were randomly sampled at different 300x300 pixel regions of interest (ROI).
Blinding	not detected.
Power Analysis	not detected.

Table 2: Resources

Antibodies
Sentences	Resources
We chose three different groups of samples: uninfected control, SARS-CoV-2 challenge after Den3 (antibody to dengue virus), and SARS-CoV-2 challenge after Anti-CoV2 (CC12.2; a potent SARS-CoV-2 neutralizing antibodies)28. Immunohistochemistry: COVID-19 samples were inactivated by storing in 10% formalin for 2 days and then transferred to zinc-formalin solution for another 3 days.	Anti-CoV2 suggested: None antibodies)28 suggested: None
Tissues were then incubated with the following antibodies: rabbit GRP78/ BIP polyclonal antibody (1:500 dilution; proteintech®, Rosemont, IL, USA; catalog# 11587-1-AP), rabbit p53 polyclonal antibody (1:200 dilution ; proteintech®, Rosemont, IL, USA; catalog# 21891-1-AP), rabbit Cytokeratin 8 polyclonal antibody (1:2000 dilution; proteintech®, Rosemont, IL, USA; catalog# 10384-1-AP), and rabbit Claudin 4-specific polyclonal antibody (1:200 dilution, proteintech®, Rosemont, IL, USA; catalog# 16195-1-AP) for 1.5 hours at room temperature in a humidified chamber then rinsed with TBS twice for 3 minutes each.	p53 suggested: (Proteintech Cat# 21891-1-AP, RRID:AB_10896826) Cytokeratin suggested: (Proteintech Cat# 10384-1-AP, RRID:AB_10638912)
Sections were incubated with horse anti-rabbit (Vector Laboratories, Burlingame, USA; catalog# MP-7401) secondary antibodies for 30 minutes at room temperature in a humidified chamber and then washed with TBS or TBST 3x, 5 minutes each.	anti-rabbit suggested: (Vector Laboratories Cat# MP-7401, RRID:AB_2336529)
Software and Algorithms
Sentences	Resources
The nodes between the seed nodes were fetched using the connecting shortest paths and their components from the human protein interaction dataset of the STRING database19.	STRING suggested: (STRING, RRID:SCR_005223)
Standard t-tests were performed using python scipy.stats.ttest_ind package (version 0.19.0) with Welch’s Two Sample t-test (unpaired, unequalvariance (equal_var=False), and unequal sample size) parameters.	scipy suggested: (SciPy, RRID:SCR_008058)
Pathway analysis of gene lists were carried out via the Reactome database and CluGo algorithm.	Reactome suggested: (Reactome, RRID:SCR_003485)
Violin, Swarm and Bubble plots are created using python seaborn package version 0.10.1.	python suggested: (IPython, RRID:SCR_001658) seaborn suggested: (seaborn, RRID:SCR_018132)
The raw data and processed data were deposited in Gene Expression Omnibus under accession no. GSE157057.	Gene Expression Omnibus suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
Detailed methods (text) Figures 2 Tables 0 Supplemental datasheets– 1-5: Supplemental Information 1: Excel datasheet with a list of transcriptomic datasets that were used in this work.	Excel suggested: None

Results from OddPub: Thank you for sharing your code and data.

Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

As for the limitations of this study, it remains unclear how to model progressive lung fibrosis in vitro and hence, no attempt was made to do so. Our results suggest that AT2 cells alone may be insufficient for such modeling because a specific host immune response that is carried in the PBMCs is a clear determinant as to who progresses and who does not. Although AT2-specific modulation of ER-stress pathway and SARS-CoV-challenged (treated vs untreated) hamsters were used to go beyond association and establish causation, our study did not attempt to inhibit/reverse fibrosis in COVID-19 by acting on any profibrogenic cellular pathway/process. Development of novel chemical matter/biologicals and validation of the therapeutic efficacy of such agents will take time, but if successful, our findings show that their benefits will likely transcend beyond PCLD into IPF and other fibrotic lung conditions such as IPF. In conclusion, this transdisciplinary work provides insights into the pathogenesis of PCLD, formally defines the fibrogenic processes in the lung, and rigorously validates high value gene signatures or even targets (i.e., IL15, senescence pathways, etc.) to track and manipulate the same. The insights, tools, computationally vetted disease models and biomarkers (prognostic gene signatures) identified here are likely to spur the development of therapies for patients with fibrotic interstitial lung disease of diverse causes, including IPF, all of whom have limited or no good t...

Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

Identifier	Status	Title
NCT0440557080	Trial number did not resolve on clinicaltrials.gov. Is the number correct?	NA
NCT04856111	Recruiting	Pirfenidone vs. Nintedanib for Fibrotic Lung Disease After C…
NCT04653831	Recruiting	Treatment With Pirfenidone for COVID-19 Related Severe ARDS

Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

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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.

Results from scite Reference Check: We found no unreliable references.

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