Determining T cell exhaustion markers to predict COVID-19 disease progression?
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to take an unprecedented toll on the world’s healthcare systems and economy. Although most infected individuals are asymptomatic or mildly symptomatic, up to 20% require hospitalization, and this rate increases dramatically in the elderly (>65 years). An increased risk in the elderly may be associated with a decreased antigen-specific T cell activation due to age. We used a CyTOF workflow to investigate lymphocytes specific for a SARS-CoV-2 peptide pool in PBMCs from COVID-19 patients of different ages and disease progression: (1) younger COVID-19 patients (≤ 60 years) and (2) older COVID-19 patients (> 65 years) (a) without or (b) with intensive care treatment. Our analysis focused on the identification and changes of markers for the prediction of disease progression such as exhaustion markers or phosphatases involved in negative signaling pathways reported to impact immune cell function during aging.
Selina currently is a Junior group leader at the Translational Cancer Center (TranslaTUM) at the Klinikum rechts der Isar in Munich. The Keppler lab is especially interested in the crosstalk of B cells with specialized inflammatory niches during autoimmunity, such as the gut or the kidney. In order to understand the complexity of autoimmune processes we combine 3D imaging approaches with high-parametric flow cytometry, mass cytometry (CyTOF) and in vitro culture systems to define drivers of inflammation during homeostatic and inflammatory conditions. In addition to leading her research group, Selina is responsible for the training of users of the Core Facility of Cell Analysis in theory of flow cytometry, handling of the BDCanto and BDFortessa flow cytometers as well as multi-parametric panel design.
MRI, Technical University Munich, Institute for Clinical Chemistry and Pathobiochemistry, Munich, Germany,
TranslaTUM, Center for Translational Cancer Research, Technische Universität München, 81675 München, Germany