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Lookup NU author(s): Dr Emily StephensonORCiD, Dr Win Tun, Professor Muzlifah Haniffa
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2025 The Author(s). Patients with end-stage kidney disease (ESKD) are at high risk of severe COVID-19. We performed longitudinal single-cell immune profiling of ESKD patients with COVID-19. Transcriptome, surface proteome, and immunoreceptor sequencing data were generated on 580,040 high-quality cells, derived from 187 samples from 61 patients. For a subset of individuals, we obtained samples before and during infection, allowing intra-individual comparison. Longitudinal profiling demonstrated distinct temporal gene expression trajectories in severe/critical versus mild/moderate COVID-19. We identified a population of transcriptionally distinct monocytes that emerged in peripheral blood following glucocorticoid treatment. Evaluation of clonal T cell dynamics showed that the fastest expanding clones were enriched in known SARS-CoV-2-specific sequences and shared across multiple patients. Comparison with external datasets revealed upregulation of immune cell TGF-β pathway expression in ESKD, irrespective of COVID-19 status. Our data delineate the temporal dynamics of the immune response in COVID-19 in a high-risk population.
Author(s): Stephenson E, Macdonald-Dunlop E, Dratva LM, Lindeboom RGH, Tuong ZK, Tun WM, Kretschmer L, Buang NB, Ballereau S, Cabantaus M, Penalver A, Prigmore E, Ferdinand JR, Stewart BJ, Gisby J, Malik TH, Clarke CL, Medjeral-Thomas N, Prendecki M, McAdoo S, Portet A, Willicombe M, Sandhu E, Pickering MC, Botto M, Teichmann SA, Haniffa M, Clatworthy MR, Thomas DC, Peters JE
Publication type: Article
Publication status: Published
Journal: Cell Genomics
Year: 2025
Volume: 5
Issue: 8
Print publication date: 13/08/2025
Online publication date: 17/06/2025
Acceptance date: 16/05/2025
Date deposited: 10/07/2025
ISSN (electronic): 2666-979X
Publisher: Cell Press
URL: https://doi.org/10.1016/j.xgen.2025.100918
DOI: 10.1016/j.xgen.2025.100918
Data Access Statement: De-identified patient single-cell count matrix and associated metadata are available at the COVID-19 Cell Atlas web portal as an h5ad file (on covid19cellatlas.org/index.patient.html, link for direct download at https://covid19.cog.sanger.ac.uk/eskd_covid19.h5ad). Original code has been deposited on Zenodo at https://doi.org/10.5281/zenodo.15358026. All are publicly available as of the date of publication. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.
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