BACKGROUND There are no known serum biomarkers that provide mechanistic insight or prognostic enrichment for post–COVID-19 pulmonary fibrosis.METHODS We tested associations of serum biomarkers with radiographic fibrosis-like abnormalities (reticulation, traction bronchiectasis, or honeycombing) on thoracic computed tomography (CT) scans 4 months, 15 months, and 3 years after hospitalization in an American discovery cohort of severe-to-critical COVID-19 survivors, and externally validated findings in 2 Canadian cohorts of moderate-to-critical COVID-19 survivors. In the discovery cohort, we investigated the dose-response relationship of the biomarker with CT-derived airway-to-lung ratio. We performed single-cell RNA sequencing (scRNA-seq) of transbronchial lung biopsies from COVID-19 survivors obtained 3 years after COVID-19 hospitalization and conducted immunofluorescence analysis of COVID-19 lung explants.RESULTS Among 150 discovery cohort participants, only higher levels of circulating club cell secretory protein-16 (CC16, encoded by the SCGB1A1 gene) at hospital discharge, 4 months, 15 months, and 3 years were associated with thoracic CT fibrosis-like abnormalities in cross-sectional and longitudinal analyses. Higher CC16 levels were associated with thoracic CT fibrosis-like abnormalities in 2 validation cohorts (n = 56 and n = 37). CC16 levels were linearly associated with increased airway-to-lung ratio. scRNA-seq revealed increased proportions of epithelial cells expressing SCGB1A1 and SCGB1A1/MUC5B in COVID-19 survivors with fibrosis. Immunofluorescence analysis of COVID-19 lung explants demonstrated increased numbers of SCGB1A1-expressing epithelial cells only in small (<100 μm) airways, with 3-fold more CC16/MUC5B-coexpressing cells in respiratory bronchioles..CONCLUSION. Higher CC16 levels are associated with CT fibrosis-like abnormalities for up to 3 years following moderate-to-critical COVID-19. Increased CC16 reflects dysregulated small airway epithelial progenitor cell remodeling and increased expansion of CC16+MUC5B+ epithelial cells in respiratory bronchioles after COVID-19.TRIAL REGISTRATION Not applicable.FUNDING Department of Defense, NIH, and Japan Society for the Promotion of Science for Young Scientists.
Matthew R. Baldwin, Ansley E. Jones, David Zhang, Chandan Gurung, Zain Khan, Anjali Saqi, Xuehan Yang, Ying Wei, Renu Nandakumar, Scarlett O. Murphy, Claire F. McGroder, Faisal Shaikh, Selim Arcasoy, Luke Benvenuto, Harpreet Grewal, Benjamin M. Smith, Eric A. Hoffman, Agnes C.Y. Yuen, Parteek Johal, Christopher Carlsten, Christopher J. Ryerson, J. Brent Richards, Alyson W. Wong, Tomoko Nakanishi, Aditi S. Shah, Christine Kim Garcia
Usage data is cumulative from July 2026 through July 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 150 | 0 |
| 28 | 0 | |
| Figure | 41 | 0 |
| Table | 3 | 0 |
| Supplemental data | 17 | 0 |
| Citation downloads | 8 | 0 |
| Totals | 247 | 0 |
| Total Views | 247 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.