bioRxivPathology
Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19
J. T. H. Lee, S. N. Barnett, K. Roberts, H. Ashwin, L. Milross, J.-W. Cho, A. Huseynov, B. Woodhams, A. Aivazidis, T. Li, J. Majo, P. C. Guerrero, M. Lee, A. M. A. Miranda, Z. Jablonska, V. Arena, B. Hanley, M. Osborn, V. Uhlmann, X.-N. Xu, G. R. McLean, S. A. Teichmann, A. M. Randi, A. Filby, P. M. Kaye, , O. A. Bayraktar
Abstract
The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 donor lungs with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage (DAD). We identify changes in cellular composition across progressive DAD, including waves of molecularly distinct macrophages and depleted epithelial and endothelial populations throughout different types of tissue damage. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early DAD, and fibrosis-related collagens in organised DAD. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early DAD. These results provide the first comprehensive, spatially resolved atlas of DAD stages, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways across alveolar damage progression.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: cell-cell communication
- approach: deep learning
- approach: statistical model
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