Article ; Online: Investigation of liquid biopsy analytes in peripheral blood of individuals after SARS-CoV-2 infection.
2023 Volume 90, Page(s) 104519
Abstract: ... The identification and stratification of at-risk SARS-CoV-2 infected individuals is vital to providing appropriate ... Within our patient cohort, 73 had received at least 1 dose of vaccination prior to SARS-CoV-2 infection ... biopsy signal after active SARS-CoV-2 infection. More research is needed to stratify PACS and ...
| Abstract | Background: Post-acute COVID-19 syndrome (PACS) is linked to severe organ damage. The identification and stratification of at-risk SARS-CoV-2 infected individuals is vital to providing appropriate care. This exploratory study looks for a potential liquid biopsy signal for PACS using both manual and machine learning approaches. Methods: Using a high definition single cell assay (HDSCA) workflow for liquid biopsy, we analysed 100 Post-COVID patients and 19 pre-pandemic normal donor (ND) controls. Within our patient cohort, 73 had received at least 1 dose of vaccination prior to SARS-CoV-2 infection. We stratified the COVID patients into 25 asymptomatic, 22 symptomatic COVID-19 but not suspected for PACS and 53 PACS suspected. All COVID-19 patients investigated in this study were diagnosed between April 2020 and January 2022 with a median 243 days (range 16-669) from diagnosis to their blood draw. We did a histopathological examination of rare events in the peripheral blood and used a machine learning model to evaluate predictors of PACS. Findings: The manual classification found rare cellular and acellular events consistent with features of endothelial cells and platelet structures in the PACS-suspected cohort. The three categories encompassing the hypothesised events were observed at a significantly higher incidence in the PACS-suspected cohort compared to the ND (p-value < 0.05). The machine learning classifier performed well when separating the NDs from Post-COVID with an accuracy of 90.1%, but poorly when separating the patients suspected and not suspected of PACS with an accuracy of 58.7%. Interpretation: Both the manual and the machine learning model found differences in the Post-COVID cohort and the NDs, suggesting the existence of a liquid biopsy signal after active SARS-CoV-2 infection. More research is needed to stratify PACS and its subsyndromes. Funding: This work was funded in whole or in part by Fulgent Genetics, Kathy and Richard Leventhal and Vassiliadis Research Fund. This work was also supported by the National Cancer InstituteU54CA260591. |
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| MeSH term(s) | Humans ; COVID-19/diagnosis ; SARS-CoV-2 ; Endothelial Cells ; Post-Acute COVID-19 Syndrome ; Pandemics |
| Language | English |
| Publishing date | 2023-03-13 |
| Publishing country | Netherlands |
| Document type | Journal Article |
| ZDB-ID | 2851331-9 |
| ISSN | 2352-3964 |
| ISSN (online) | 2352-3964 |
| DOI | 10.1016/j.ebiom.2023.104519 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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