SARS-CoV-2 (COVID-19) Adhesion Site Protein Upregulation in Small Airways, Type 2 Pneumocytes, and Alveolar Macrophages of Smokers and COPD – Possible Implications for Interstitial Fibrosis
Bibliographic record
Abstract
Background: Smokers and patients with COPD are highly susceptible to SARS-CoV-2 infection, leading to severe COVID-19. Methods: This cross-sectional study involved resected lung tissues from 16 patients with GOLD stage I or II COPD; of which 8 were current smokers COPD (COPD-CS), and 8 ex-smokers COPD (COPD-ES), 7 normal lung function smokers (NLFS), 9 patients with small airways disease (SAD), and 10 were never-smoking normal controls (NC). Immunostaining for ACE2, Furin, and TMPRSS2 was performed and analysed for percent expression in small airway epithelium (SAE) and counts for positively and negatively stained type 2 pneumocytes and alveolar macrophages (AMs) were done using Image ProPlus V7.0. Furthermore, primary small airway epithelial cells (pSAEC) were analysed by immunofluorescence after exposure to cigarette smoke extract (CSE). Results: ACE2, Furin, and TMPRSS2 expression significantly increased in SAE and type 2 pneumocytes in all the subjects (except Furin for NLFS) compared to NC (p < 0.001). Similar significance was observed for ACE2 positive AM (p < 0.002), except COPD-ES, which decreased in ACE2 positive AMs (p < 0.003). Total type 2 pneumocytes and AMs significantly increased in the pathological groups compared to NC (p < 0.01), except SAD (p = 0.08). However, AMs are significantly reduced in COPD-ES (p < 0.003). Significant changes were observed for tissue co-expression of Furin and TMPRSS2 with ACE2 in SAE, type 2 pneumocytes and AMs. These markers also negatively correlated with lung function parameters, such as FEV 1 /FVC % predicted, FEF25-75%, DLCO% predicted. A strong co-localisation and expression for ACE2 (p < 0.0001), Furin (p < 0.01), and TMPRSS2 (p < 0.0001) was observed in pSAEC treated with 1% CSE than controls. Discussion: The increased expression of ACE2, TMPRSS2 and Furin, in the SAE, type 2 pneumocytes and AMs of smokers and COPD are detrimental to lung function and proves that these patient groups could be more susceptible to severe COVID-19 infection. Increased type 2 pneumocytes suggest that these patients are vulnerable to developing post-COVID-19 interstitial pulmonary fibrosis or fibrosis in general. There could be a silently developing interstitial pathology in smokers and patients with COPD. This is the first comprehensive study to report such changes. Keywords: COVID-19, SARS-CoV-2, smoking, COPD, ACE2, type 2 pneumocytes, alveolar macrophages, epithelium
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".