Type 2 and interferon inflammation regulate SARS-CoV-2 entry factor expression in the airway epithelium

doi:10.1038/s41467-020-18781-2

. 2020 Oct 12;11(1):5139.

doi: 10.1038/s41467-020-18781-2.

Type 2 and interferon inflammation regulate SARS-CoV-2 entry factor expression in the airway epithelium

Satria P Sajuthi^#¹, Peter DeFord^#¹, Yingchun Li¹, Nathan D Jackson¹, Michael T Montgomery¹, Jamie L Everman¹, Cydney L Rios¹, Elmar Pruesse¹, James D Nolin¹, Elizabeth G Plender¹, Michael E Wechsler², Angel C Y Mak³, Celeste Eng³, Sandra Salazar³, Vivian Medina⁴, Eric M Wohlford^{3

5}, Scott Huntsman³, Deborah A Nickerson^{6

7

8}, Soren Germer⁹, Michael C Zody⁹, Gonçalo Abecasis¹⁰, Hyun Min Kang¹⁰, Kenneth M Rice¹¹, Rajesh Kumar¹², Sam Oh³, Jose Rodriguez-Santana⁴, Esteban G Burchard^{3

13}, Max A Seibold^{14

15

16}

Affiliations

¹ Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA.
² Department of Medicine, National Jewish Health, Denver, CO, USA.
³ Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
⁴ Centro de Neumología Pediátrica, San Juan, Puerto Rico.
⁵ Division of Pediatric Allergy and Immunology, University of California San Francisco, San Francisco, CA, USA.
⁶ Department of Genome Sciences, University of Washington, Seattle, WA, USA.
⁷ Northwest Genomics Center, Seattle, WA, USA.
⁸ Brotman Baty Institute, Seattle, WA, USA.
⁹ New York Genome Center, New York City, NY, USA.
¹⁰ Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
¹¹ Department of Biostatistics, University of Washington, Seattle, WA, USA.
¹² Department of Pediatrics, Ann and Robert H. Lurie Children's Hospital of Chicago, Northwestern University, Chicago, IL, USA.
¹³ Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.
¹⁴ Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA. seiboldm@njhealth.org.
¹⁵ Department of Pediatrics, National Jewish Health, Denver, CO, USA. seiboldm@njhealth.org.
¹⁶ Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado-AMC, Aurora, CO, USA. seiboldm@njhealth.org.

^# Contributed equally.

PMID: 33046696
PMCID: PMC7550582
DOI: 10.1038/s41467-020-18781-2

Type 2 and interferon inflammation regulate SARS-CoV-2 entry factor expression in the airway epithelium

Satria P Sajuthi et al. Nat Commun. 2020.

. 2020 Oct 12;11(1):5139.

doi: 10.1038/s41467-020-18781-2.

Authors

Affiliations

¹ Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA.
² Department of Medicine, National Jewish Health, Denver, CO, USA.
³ Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
⁴ Centro de Neumología Pediátrica, San Juan, Puerto Rico.
⁵ Division of Pediatric Allergy and Immunology, University of California San Francisco, San Francisco, CA, USA.
⁶ Department of Genome Sciences, University of Washington, Seattle, WA, USA.
⁷ Northwest Genomics Center, Seattle, WA, USA.
⁸ Brotman Baty Institute, Seattle, WA, USA.
⁹ New York Genome Center, New York City, NY, USA.
¹⁰ Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
¹¹ Department of Biostatistics, University of Washington, Seattle, WA, USA.
¹² Department of Pediatrics, Ann and Robert H. Lurie Children's Hospital of Chicago, Northwestern University, Chicago, IL, USA.
¹³ Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.
¹⁴ Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA. seiboldm@njhealth.org.
¹⁵ Department of Pediatrics, National Jewish Health, Denver, CO, USA. seiboldm@njhealth.org.
¹⁶ Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado-AMC, Aurora, CO, USA. seiboldm@njhealth.org.

^# Contributed equally.

PMID: 33046696
PMCID: PMC7550582
DOI: 10.1038/s41467-020-18781-2

Abstract

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, an emerging virus that utilizes host proteins ACE2 and TMPRSS2 as entry factors. Understanding the factors affecting the pattern and levels of expression of these genes is important for deeper understanding of SARS-CoV-2 tropism and pathogenesis. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci for both ACE2 and TMPRSS2, that vary in frequency across world populations. We find TMPRSS2 is part of a mucus secretory network, highly upregulated by type 2 (T2) inflammation through the action of interleukin-13, and that the interferon response to respiratory viruses highly upregulates ACE2 expression. IL-13 and virus infection mediated effects on ACE2 expression were also observed at the protein level in the airway epithelium. Finally, we define airway responses to common coronavirus infections in children, finding that these infections generate host responses similar to other viral species, including upregulation of IL6 and ACE2. Our results reveal possible mechanisms influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.

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Conflict of interest statement

The authors declare no competing interests.

Figures

**Fig. 1. *ACE2* and *TMPRSS2* are expressed by multiple nasal airway cell types.**
a UMAP visualization of 8,291 cells derived from a human nasal airway epithelial brushing depicts multiple epithelial and immune cell types identified through unsupervised clustering. b Log Count Per Million (CPM) normalized expression of *ACE2* in epithelial and immune cell types. c Log CPM normalized expression of *TMPRSS2* in epithelial and immune cell types.

**Fig. 2. *TMPRSS2* is part of a T2 inflammation-induced mucus secretory network.**
a WGCNA identified networks of co-regulated genes related to mucus secretory function (black), T2 inflammation-induced mucus secretory function (pink), and canonical T2 inflammation biomarkers (saddle brown). *TMPRSS2* was within the pink network. Select pathway and cell-type enrichments for network genes are shown. Enrichment p-values were obtained from a one-sided hypergeometric test. Benjamini–Hochberg correction was used to control for false discovery rate. b Scatterplot revealing a strong positive correlation between *TMPRSS2* expression and summary (eigengene) expression of the T2 inflammatory, mucus secretory network. p-values were obtained from the two-sided Pearson correlation test. c Scatterplot revealing a strong positive correlation between *TMPRSS2* expression and summary (eigengene) expression of the canonical T2 inflammation biomarker network. p-values were obtained from the two-sided Pearson correlation test. d Box plots revealing strong upregulation of *TMPRSS2* expression among T2-high (n = 364) compared to T2-low (n = 331) subjects. Differential expression testing between T2-high and T2-low groups was performed using a two-sided Wilcoxon test. e Scatterplot revealing a strong negative correlation between *ACE2* expression and summary (eigengene) expression of the T2 inflammation mucus secretory network. p-values were obtained from the two-sided Pearson correlation test. f Scatterplot revealing a strong negative correlation between *ACE2* expression and summary (eigengene) expression of the canonical T2 inflammation biomarker network. p-values were obtained from the two-sided Pearson correlation test. g Box plots revealing strong downregulation of *ACE2* expression among T2-high (n = 364) compared to T2-low (n = 331) subjects. Differential expression testing between T2-high and T2-low groups was performed using a two-sided Wilcoxon test. Box centers give the median, upper and lower box bounds correspond to first and third quartiles and the upper/lower whiskers extend from the upper/lower bounds up to/down from the largest/smallest value, no further than 1.5 × IQR from the upper/lower bound (where IQR is the inter-quartile range). Data beyond the end of whiskers are plotted individually.

**Fig. 3. *ACE2* and *TMPRSS2* are both regulated by IL-13 in the airway epithelium.**
a Experimental schematic detailing the timeline for differentiation of basal airway epithelial cells into a mucociliary airway epithelium and treatment with chronic (10 days) or acute (72 h) IL-13 (10 ng mL⁻¹). b Box plots of count-normalized expression between paired (n = 5 pairs) nasal airway cultures (control/IL-13) revealing strong downregulation of bulk *ACE2* expression with IL-13 treatment. Differential expression results are from DESeq2. Benjamini–Hochberg correction was used to control for false discovery rate. c Box plots of count-normalized expression between paired (n = 5 pairs) nasal airway cultures (control/IL-13) revealing strong upregulation of bulk *TMPRSS2* expression with IL-13 treatment. Differential expression results are from DESeq2. Benjamini–Hochberg correction was used to control for false discovery rate. d UMAP visualization of 6,969 cells derived from control and IL-13 stimulated tracheal airway ALI cultures depict multiple epithelial cell types identified through unsupervised clustering. e Violin plots of normalized *ACE2* expression across epithelial cell types from tracheal airway ALI cultures, stratified by treatment (gray = control, red = IL-13). Differential expression using a two-sided Wilcoxon test was performed between control and IL-13-stimulated cells with significant differences in expression for a cell type indicated by a * (p < 0.05). p-values (left to right) = 0.62; 0.18; 2.8e−4; 0.66; 4.6e−6; 0.08; NA; 0.77; NA; NA; 0.12. f Violin plots of normalized *TMPRSS2* expression across epithelial cell types from tracheal airway ALI cultures, stratified by treatment (gray = control, red = IL-13). Differential expression using a two-sided Wilcoxon test was performed between control and IL-13-stimulated cells with significant differences in expression for a cell type indicated by a * (p < 0.05). p-values (left to right) = 9.4e−4; 1.4e−11; 0.51; 2.5e−14; 6.9e−117; 1.5e−38; 2.3e−4; 2.3e−10; 0.46; NA; 0.95. Box centers give the median, upper and lower box bounds correspond to first and third quartiles and the upper/lower whiskers extend from the upper/lower bounds up to/down from the largest/smallest value, no further than 1.5 × IQR from the upper/lower bound (where IQR is the inter-quartile range). Data beyond the end of whiskers are plotted individually.

**Fig. 4. *ACE2* is an interferon network gene regulated by a viral infection.**
a Scatterplot revealing a strong positive correlation between *ACE2* expression and summary (eigengene) expression of the cytotoxic immune response network (purple). p-values were obtained from a two-sided Pearson correlation test. b Scatterplot revealing a strong positive correlation between *ACE2* expression and summary (eigengene) expression of the interferon response network (tan). p-values were obtained from a two-sided Pearson correlation test. c WGCNA analysis identified networks of co-regulated genes related to cytotoxic immune response (purple) and interferon response (tan). *ACE2* was within the purple network. Select pathway and cell-type enrichments for network genes are shown. Enrichment p-values were obtained from a one-sided hypergeometric test. Benjamini–Hochberg correction was used to control for false discovery rate. d Box plots of count-normalized expression from GALA II nasal epithelial samples reveal strong upregulation of *ACE2* expression among interferon-high (n = 78) compared to interferon-low (n = 617) subjects. Differential expression results are from DESeq2. Benjamini–Hochberg correction was used to control for false discovery rate. e Pie graph depicting the percentage of each type of respiratory virus infection found among GALA II subjects in whom viral reads were found. f Experimental schematic detailing a timeline for differentiation of basal airway epithelial cells into a mucociliary airway epithelium and experimental infection with HRV-A16. g Box plots of count-normalized expression between paired (n = 5 pairs) nasal airway cultures (control/HRV-A16 infected) revealing strong upregulation of *ACE2* expression with HRV-A16 infection. Differential expression results are from DESeq2. Benjamini–Hochberg correction was used to control for false discovery rate. h Box plots of count-normalized expression between paired (n = 5 pairs) nasal airway cultures (control/HRV-A16-infected) revealing no effect of HRVA-16 on *TMPRSS2* expression. Differential expression results are from DESeq2. Benjamini–Hochberg correction was used to control for false discovery rate. Box centers give the median, upper and lower box bounds correspond to first and third quartiles and the upper/lower whiskers extend from the upper/lower bounds up to/down from the largest/smallest value, no further than 1.5 × IQR from the upper/lower bound (where IQR is the inter-quartile range). Data beyond the end of whiskers are plotted individually.

**Fig. 5. Airway surface ACE2 protein is regulated by IL-13 and viral infection.**
a–c Immunofluorescence staining of in vitro nasal airway epithelial ALI cultures (derived from a single GALA II asthmatic child) derived from vehicle-treated (a), 5 days IL-13(10 ng mL⁻¹) treated (b), and 24 h HRV-A infected epithelium (c). Representative images of ciliated cells (ACT; red) and ACE2-positive (white) cells. The nuclei were counterstained with DAPI (blue). ACE2 protein was located in the apical compartment and decreased with IL-13 treatment and increased in HRV-A infection. Scale bars: 60 μm. d Zoomed in image of c. e Quantification of apical ACE2-positive cells per 20x field for each condition in the IL-13/HRV mature culture stimulation experiment (n = 1 donor). p-values were obtained from a two-sided t-test. Data are presented as mean values ± SEM. f–h Immunofluorescence staining of in vitro nasal airway epithelial ALI cultures from a single child non-asthmatic donor derived from vehicle-treated (f), 21 days IL-13 (10 ng mL⁻¹) treated (g), and 21 days DAPT(5 μM) treated epithelium (h). Representative images of ciliated cells (ACT; red), basal cells (KRT5; green), and ACE2-positive (white) cells. The nuclei were counterstained with DAPI (blue). ACE2 protein located in the apical compartment and decreased in IL-13 treatment and increased in DAPT treatment. Scale bars: 60 μm. i Quantification of apical ACE2-positive cells per 20x field for each condition in the IL-13/DAPT differentiation experiment (n = 1 donor). p-values were obtained from a two-sided t-test. Data are presented as mean values ± SEM. j Immunofluorescence staining of in vivo trachea tissues from a single healthy donor. Representative images of ciliated cells (ACT; red), basal cells (KRT5; green), and ACE2-positive (white) cells. The nuclei were counterstained with DAPI (blue). ACE2 protein located in the apical compartment of ACT positive ciliated cells. Scale bars: 60 μm. All images were captured on the Echo Revolve R4 and images were cropped and resized using Affinity Designer. For each image, brightness and contrasts were uniformly adjusted relative to the brightest feature to balance exposure of each color channel.

**Fig. 6. Nasal airway *ACE2* and *TMPRSS2* are regulated by eQTL variants.**
a Locuszoom plot of *ACE2* eQTL signals. The lead eQTL variant (rs181603331) is highlighted with a purple dot. The strength of linkage disequilibrium (LD) between rs181603331 and other variants is discretely divided into five quantiles and mapped into five colors (dark blue, sky blue, green, orange, and red) sequentially from low LD to high LD. b Locuszoom plot of *TMPRSS2* eQTL signals. The three independent eQTL variants (rs1475908, rs2838057, rs74659079) and their LD with other variants (r²) are represented by red, blue, and green color gradient, respectively. c Box plots of normalized *ACE2* expression among the three genotypes of the lead *ACE2* eQTL variant (rs181603331). log₂A_FC = log₂ of the allelic fold change associated with the variant. (n: GG = 654, GT = 8, TT = 3). eQTL p-values were obtained from testing the additive genotype effect on gene expression using the linear regression model implemented in FastQTL. Benjamini–Hochberg correction was used to control for false discovery rate. d Box plots of normalized *TMPRSS2* expression among the three genotypes of the lead *TMPRSS2* eQTL variant (rs1475908). log₂A_FC = log₂ of the allelic fold change associated with the variant. (n: GG = 432, GA = 218, AA = 31). eQTL p-values were obtained from testing the additive genotype effect on gene expression using the linear regression model implemented in FastQTL. Benjamini–Hochberg correction was used to control for false discovery rate. e Bar plots depicting allele frequencies of the *ACE2* eQTL variant rs181603331 and *TMPRSS2* eQTL variants (rs1475908, rs2838057, rs74659079) across world populations. Allele frequency data were obtained from gnomAD v2.1.1. Box centers give the median, upper and lower box bounds correspond to first and third quartiles, and the upper/lower whiskers extend from the upper/lower bounds up to/down from the largest/smallest value, no further than 1.5× IQR from the upper/lower bound (where IQR is the inter-quartile range). Data beyond the end of whiskers are plotted individually.

**Fig. 7. Host response to CoV strains are similar to other respiratory viruses.**
a Box plots revealing a strong and equivalent upregulation of summary (eigengene [E_g]) expression for the interferon response network among ORV- and CoV-infected GALA II subjects (n = 22, 9 respectively), compared to uninfected subjects (n = 582). Differential expression analysis between infected and uninfected groups was performed with a two-sided t-test. b Box plots revealing a strong and equivalent upregulation of summary (eigengene [E_g]) expression for the cytotoxic immune response network among ORV- and CoV-infected GALA II subjects (n = 22, 9 respectively), compared to uninfected subjects (n = 582). Differential expression analysis between infected and uninfected groups was performed with a two-sided t-test. c Scatterplot showing the similarity in log₂FC differential expression of genes in ORV (x axis) and CoV (y axis) infected individuals relative to uninfected subjects. The color of the points corresponds to the group in which each gene was identified as significant (FDR < 0.05, absolute log₂FC > 0.5). The Pearson correlation coefficient of the significant genes (excluding the “Neither” category) is 0.95. Top enrichment terms for genes that were significantly differentially expressed in both virus infections (blue) are shown. d Top upstream regulators predicted by Ingenuity Pathway Analysis to be regulating the genes that were upregulated in CoV. Enrichment values for these CoV regulators, using the ORV upregulated genes are also shown. Enrichment p-values were obtained from IPA. No multiple comparison adjustment was performed. e Box plots revealing upregulation of *IL6* expression in virus-infected individuals (n: CoV⁺ = 9, ORV⁺ = 22, non-infected = 582). Differential expression analysis was performed with limma. Benjamini–Hochberg correction was used to control for false discovery rate. f Box plots revealing upregulation of *ACE2* expression in virus-infected individuals (n: CoV⁺ = 9, ORV⁺ = 22, non-infected=582). Differential expression analysis was performed with limma. Benjamini–Hochberg correction was used to control for false discovery rate. Box centers give the median, upper and lower box bounds correspond to first and third quartiles and the upper/lower whiskers extend from the upper/lower bounds up to/down from the largest/smallest value, no further than 1.5 × IQR from the upper/lower bound (where IQR is the inter-quartile range). Data beyond the end of whiskers are plotted individually.

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Type 2 and interferon inflammation strongly regulate SARS-CoV-2 related gene expression in the airway epithelium.
Sajuthi SP, DeFord P, Jackson ND, Montgomery MT, Everman JL, Rios CL, Pruesse E, Nolin JD, Plender EG, Wechsler ME, Mak AC, Eng C, Salazar S, Medina V, Wohlford EM, Huntsman S, Nickerson DA, Germer S, Zody MC, Abecasis G, Kang HM, Rice KM, Kumar R, Oh S, Rodriguez-Santana J, Burchard EG, Seibold MA. Sajuthi SP, et al. bioRxiv [Preprint]. 2020 Apr 10:2020.04.09.034454. doi: 10.1101/2020.04.09.034454. bioRxiv. 2020. Update in: Nat Commun. 2020 Oct 12;11(1):5139. doi: 10.1038/s41467-020-18781-2. PMID: 32511326 Free PMC article. Updated. Preprint.

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References

1. Wang C, Horby PW, Hayden FG, Gao GF. A novel coronavirus outbreak of global health concern. Lancet. 2020;395:470–473. doi: 10.1016/S0140-6736(20)30185-9. - DOI - PMC - PubMed
1. Zhu N, et al. A novel coronavirus from patients with pneumonia in China, 2019. N. Engl. J. Med. 2020;382:727–733. doi: 10.1056/NEJMoa2001017. - DOI - PMC - PubMed
1. Baud, D. et al. Real estimates of mortality following COVID-19 infection. Lancet Infect. Dis.20, 773 (2020). - PMC - PubMed
1. Du, Y. et al. Clinical features of 85 fatal cases of COVID-19 from Wuhan: a retrospective observational study. Am. J. Respir. Crit. Care Med.201, 1372–1379 (2020). - PMC - PubMed
1. Zhou F, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395:1054–1062. doi: 10.1016/S0140-6736(20)30566-3. - DOI - PMC - PubMed

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[1] Wang C, Horby PW, Hayden FG, Gao GF. A novel coronavirus outbreak of global health concern. Lancet. 2020;395:470–473. doi: 10.1016/S0140-6736(20)30185-9. - DOI - PMC - PubMed

[2] Wang C, Horby PW, Hayden FG, Gao GF. A novel coronavirus outbreak of global health concern. Lancet. 2020;395:470–473. doi: 10.1016/S0140-6736(20)30185-9. - DOI - PMC - PubMed

[3] Zhu N, et al. A novel coronavirus from patients with pneumonia in China, 2019. N. Engl. J. Med. 2020;382:727–733. doi: 10.1056/NEJMoa2001017. - DOI - PMC - PubMed

[4] Zhu N, et al. A novel coronavirus from patients with pneumonia in China, 2019. N. Engl. J. Med. 2020;382:727–733. doi: 10.1056/NEJMoa2001017. - DOI - PMC - PubMed

[5] Baud, D. et al. Real estimates of mortality following COVID-19 infection. Lancet Infect. Dis.20, 773 (2020). - PMC - PubMed

[6] Baud, D. et al. Real estimates of mortality following COVID-19 infection. Lancet Infect. Dis.20, 773 (2020). - PMC - PubMed

[7] Du, Y. et al. Clinical features of 85 fatal cases of COVID-19 from Wuhan: a retrospective observational study. Am. J. Respir. Crit. Care Med.201, 1372–1379 (2020). - PMC - PubMed

[8] Du, Y. et al. Clinical features of 85 fatal cases of COVID-19 from Wuhan: a retrospective observational study. Am. J. Respir. Crit. Care Med.201, 1372–1379 (2020). - PMC - PubMed

[9] Zhou F, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395:1054–1062. doi: 10.1016/S0140-6736(20)30566-3. - DOI - PMC - PubMed

[10] Zhou F, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395:1054–1062. doi: 10.1016/S0140-6736(20)30566-3. - DOI - PMC - PubMed

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Type 2 and interferon inflammation regulate SARS-CoV-2 entry factor expression in the airway epithelium

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Type 2 and interferon inflammation regulate SARS-CoV-2 entry factor expression in the airway epithelium

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