Investigation of liquid biopsy analytes in peripheral blood of individuals after SARS-CoV-2 infectionResearch in context

Elizabeth Qi; George Courcoubetis; Emmett Liljegren; Ergueen Herrera; Nathalie Nguyen; Maimoona Nadri; Sara Ghandehari; Elham Kazemian; Karen L. Reckamp; Noah M. Merin; Akil Merchant; Jeremy Mason; Jane C. Figueiredo; Stephanie N. Shishido; Peter Kuhn

EBioMedicine (Apr 2023)

Investigation of liquid biopsy analytes in peripheral blood of individuals after SARS-CoV-2 infectionResearch in context

Elizabeth Qi,
George Courcoubetis,
Emmett Liljegren,
Ergueen Herrera,
Nathalie Nguyen,
Maimoona Nadri,
Sara Ghandehari,
Elham Kazemian,
Karen L. Reckamp,
Noah M. Merin,
Akil Merchant,
Jeremy Mason,
Jane C. Figueiredo,
Stephanie N. Shishido,
Peter Kuhn

Affiliations

Elizabeth Qi: Convergent Science Institute in Cancer, Michelson Center for Convergent Bioscience, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA 90089, USA
George Courcoubetis: Convergent Science Institute in Cancer, Michelson Center for Convergent Bioscience, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA 90089, USA
Emmett Liljegren: Convergent Science Institute in Cancer, Michelson Center for Convergent Bioscience, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA 90089, USA
Ergueen Herrera: Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, 8700 Beverly Blvd Suite AC1072, Los Angeles, CA 90048, USA
Nathalie Nguyen: Division of Medical Oncology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
Maimoona Nadri: Division of Medical Oncology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
Sara Ghandehari: Cedars-Sinai Medical Center, Pulmonary Rehabilitation in the Women's Guild Lung Institute, Los Angeles, CA 90048, USA
Elham Kazemian: Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, 8700 Beverly Blvd Suite AC1072, Los Angeles, CA 90048, USA
Karen L. Reckamp: Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, 8700 Beverly Blvd Suite AC1072, Los Angeles, CA 90048, USA
Noah M. Merin: Division of Hematology and Cellular Therapy, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
Akil Merchant: Division of Hematology and Cellular Therapy, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
Jeremy Mason: Convergent Science Institute in Cancer, Michelson Center for Convergent Bioscience, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA 90089, USA; Catherine & Joseph Aresty Department of Urology, Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
Jane C. Figueiredo: Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, 8700 Beverly Blvd Suite AC1072, Los Angeles, CA 90048, USA
Stephanie N. Shishido: Convergent Science Institute in Cancer, Michelson Center for Convergent Bioscience, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA 90089, USA
Peter Kuhn: Convergent Science Institute in Cancer, Michelson Center for Convergent Bioscience, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA 90089, USA; Catherine & Joseph Aresty Department of Urology, Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA; Department of Aerospace and Mechanical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA; Department of Biological Sciences, Dornsife College of Letters, Arts, and Sciences, University of Southern California, Los Angeles, CA 90089, USA; Corresponding author. University of Southern California, 1002 Childs Way, MCB 220M, Los Angeles, CA 90089, USA.

Journal volume & issue: Vol. 90
p. 104519

Abstract

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Summary: 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 Institute U54CA260591.

Published in EBioMedicine

ISSN: 2352-3964 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Medicine: Medicine (General)
Website: http://www.journals.elsevier.com/ebiomedicine/

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