Chronic lung allograft dysfunction (CLAD) is the leading cause of mortality after lung transplantation, yet its molecular mechanisms remain poorly understood. To elucidate the pathogenesis of CLAD, we conducted a comprehensive single-cell transcriptomic analysis of CLAD lungs, integrating our generated datasets with approximately 1.6 million cells from 15 published studies of other fibrotic lung diseases. By applying pseudo-bulk approaches to mitigate batch effects, we identified molecular signatures specific to CLAD and those shared with idiopathic pulmonary fibrosis, COVID-19, and other fibrotic conditions. Our analysis revealed CLAD-specific cellular subsets including Fibro.AT2 cells, exhausted CD8+ T cells, and superactivated macrophages while suggesting that pathogenic keratin 17–positive, keratin 5–negative (KRT17+KRT5−) cells represent a common fibrotic mechanism across fibrotic lung diseases. Additionally, we performed donor-recipient cell deconvolution in lung allografts, uncovering distinct transcriptional programs and intercellular crosstalk between donor- and recipient-derived cells that drive allograft fibrosis. Recipient-derived stromal and immune cells showed enhanced pro-fibrotic and allograft rejection pathways compared with their donor counterparts. By leveraging insights from other fibrotic diseases to elucidate CLAD-specific mechanisms, our study provides a molecular framework for understanding CLAD pathogenesis and identifies potential therapeutic targets for this treatment-refractory condition.
Yuanqing Yan, Taisuke Kaihou, Emilia Lecuona, Xin Wu, Masahiko Shigemura, Haiying Sun, Chitaru Kurihara, Ruli Gao, Felix L. Nunez-Santana, G.R. Scott Budinger, Ankit Bharat
Usage data is cumulative from October 2025 through May 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 4,198 | 360 |
| 694 | 98 | |
| Figure | 1,568 | 0 |
| Supplemental data | 343 | 20 |
| Citation downloads | 250 | 0 |
| Totals | 7,053 | 478 |
| Total Views | 7,531 | |
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.