Journal article
Spatial transcriptomic characterization of COVID-19 pneumonitis identifies immune circuits related to tissue injury
- Abstract:
- Severe lung damage in COVID-19 involves complex interactions between diverse populations of immune and stromal cells. In this study, we used a spatial transcriptomics approach to delineate the cells, pathways and genes present across the spectrum of histopathological damage in COVID-19 lung tissue. We applied correlation network-based approaches to deconvolve gene expression data from areas of interest within well preserved post-mortem lung samples from three patients. Despite substantial inter-patient heterogeneity we discovered evidence for a common immune cell signaling circuit in areas of severe tissue that involves crosstalk between cytotoxic lymphocytes and pro-inflammatory macrophages. Expression of IFNG by cytotoxic lymphocytes was associated with induction of chemokines including CXCL9, CXCL10 and CXCL11 which are known to promote the recruitment of CXCR3+ immune cells. The tumour necrosis factor (TNF) superfamily members BAFF ( TNFSF13B ) and TRAIL ( TNFSF10 ) were found to be consistently upregulated in the areas with severe tissue damage. We used published spatial and single cell SARS-CoV-2 datasets to confirm our findings in the lung tissue from additional cohorts of COVID-19 patients. The resulting model of severe COVID-19 immune-mediated tissue pathology may inform future therapeutic strategies. <h4>One Sentence Summary</h4> Spatial analysis identifies IFNγ response signatures as focal to severe alveolar damage in COVID-19 pneumonitis.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 8.9MB, Terms of use)
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- Publisher copy:
- 10.1172/jci.insight.157837
Authors
+ National Institute for Health Research
More from this funder
- Grant:
- NF-SI-0617-10015
- NF-SI-0515-10005
- Publisher:
- American Society for Clinical Investigation
- Journal:
- JCI Insight More from this journal
- Volume:
- 8
- Issue:
- 2
- Article number:
- e157837
- Publication date:
- 2023-01-24
- Acceptance date:
- 2022-11-30
- DOI:
- EISSN:
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2379-3708
- Language:
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English
- Keywords:
- Pubs id:
-
1187261
- Local pid:
-
pubs:1187261
- Deposit date:
-
2023-10-17
Terms of use
- Copyright holder:
- Cross et al
- Copyright date:
- 2021
- Rights statement:
- © 2023, Cross et al. This is an open access article published under the terms of the Creative Commons Attribution 4.0 International License.
- Licence:
- CC Attribution (CC BY)
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