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Persistent Overactive Cytotoxic Immune Response in a Spanish Cohort of Individuals With Long-COVID: Identification of Diagnostic Biomarkers. | LitMetric

AI Article Synopsis

  • Long-COVID is a new syndrome marked by symptoms lingering for over four weeks after a COVID-19 infection, with potential causes still being researched.
  • A study on Spanish individuals found that those with Long-COVID had significantly higher levels of certain immune cells, indicating a strong antiviral response.
  • By analyzing clinical symptoms and demographic factors, researchers developed a Random Forest algorithm that accurately predicted Long-COVID status, suggesting that identifying specific biomarkers could enhance patient management.

Article Abstract

Long-COVID is a new emerging syndrome worldwide that is characterized by the persistence of unresolved signs and symptoms of COVID-19 more than 4 weeks after the infection and even after more than 12 weeks. The underlying mechanisms for Long-COVID are still undefined, but a sustained inflammatory response caused by the persistence of SARS-CoV-2 in organ and tissue sanctuaries or resemblance with an autoimmune disease are within the most considered hypotheses. In this study, we analyzed the usefulness of several demographic, clinical, and immunological parameters as diagnostic biomarkers of Long-COVID in one cohort of Spanish individuals who presented signs and symptoms of this syndrome after 49 weeks post-infection, in comparison with individuals who recovered completely in the first 12 weeks after the infection. We determined that individuals with Long-COVID showed significantly increased levels of functional memory cells with high antiviral cytotoxic activity such as CD8 TEMRA cells, CD8TCRγδ cells, and NK cells with CD56CD57NKG2C phenotype. The persistence of these long-lasting cytotoxic populations was supported by enhanced levels of CD4 Tregs and the expression of the exhaustion marker PD-1 on the surface of CD3 T lymphocytes. With the use of these immune parameters and significant clinical features such as lethargy, pleuritic chest pain, and dermatological injuries, as well as demographic factors such as female gender and O blood type, a Random Forest algorithm predicted the assignment of the participants in the Long-COVID group with 100% accuracy. The definition of the most accurate diagnostic biomarkers could be helpful to detect the development of Long-COVID and to improve the clinical management of these patients.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8990790PMC
http://dx.doi.org/10.3389/fimmu.2022.848886DOI Listing

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