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| Status |
Public on Sep 17, 2021 |
| Title |
Immune signatures underlying post-acute COVID-19 lung sequelae |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
Other
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| Summary |
Although a substantial proportion of severe COVID-19 pneumonia survivors exhibit long-term pulmonary sequalae, the underlying mechanisms or associated local and systemic immune correlates are not known. Here, we have performed high dimensional characterization of the pathophysiological and immune traits of aged COVID-19 convalescents, and correlated the local and systemic immune profiles with pulmonary function and lung imaging. In this cohort of aged COVID-19 convalescents, chronic lung impairment was accompanied by persistent systemic inflammation and respiratory immune alterations. Detailed evaluation of the lung immune compartment revealed dysregulated respiratory CD8+ T cell responses that likely underlie the impaired lung function following acute COVID-19 during aging. Single cell transcriptomic analysis identified the potential pathogenic subsets of respiratory CD8+ T cells causing persistent tissue conditions following COVID-19. Our results have revealed key pathophysiological and immune traits that support the development of lung sequelae following SARS-CoV2 pneumonia during aging, with implications for the treatment of chronic COVID-19 symptoms.
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| Overall design |
single-cell RNA-seq / TCR-seq assay of PBMC or BAL T cells from aged COVID-19 convalescents or healthy donors
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| Contributor(s) |
Li C, Wu Y, Li Y, Sun J |
| Citation(s) |
34591653 |
| Submission date |
Jun 04, 2021 |
| Last update date |
Nov 22, 2021 |
| Contact name |
Jie Sun |
| Organization name |
Mayo Clinic
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| Street address |
200 First Street SW
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| City |
Rochester |
| State/province |
MN |
| ZIP/Postal code |
55905 |
| Country |
USA |
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| Platforms (1) |
| GPL20301 |
Illumina HiSeq 4000 (Homo sapiens) |
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| Samples (14)
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| Relations |
| BioProject |
PRJNA735258 |
| SRA |
SRP322777 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE176201_RAW.tar |
168.6 Mb |
(http)(custom) |
TAR (of CSV, H5) |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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