SARS-CoV-2 infection leads to a highly variable clinical evolution, ranging from asymptomatic to severe disease with acute respiratory distress syndrome, requiring intensive care units (ICU) admission. The optimal management of hospitalized patients has become a worldwide concern and identification of immune biomarkers predictive of the clinical outcome for hospitalized patients remains a major challenge. Immunophenotyping and transcriptomic analysis of hospitalized COVID-19 patients at admission allow identifying the two categories of patients. Inflammation, high neutrophil activation, dysfunctional monocytic response and a strongly impaired adaptive immune response was observed in patients who will experience the more severe form of the disease. This observation was validated in an independent cohort of patients. Using in silico analysis on drug signature database, we identify differential therapeutics that specifically correspond to each group of patients. From this signature, we propose a score—the SARS-Score—composed of easily quantifiable biomarkers, to classify hospitalized patients upon arrival to adapt treatment according to their immune profile.
【저자키워드】 COVID-19, immunologic profile, personalized medicine/personalized health care, score, therapeutic strategy, 【초록키워드】 Treatment, Biomarker, Biomarkers, acute respiratory distress syndrome, SARS-COV-2 infection, neutrophil, intensive care unit, Immune profile, hospitalized patients, database, immune, ICU, Clinical outcome, Immunophenotyping, intensive care units, Asymptomatic, management, Patient, transcriptomic analysis, in silico analysis, Adaptive immune response, Admission, patients, acute respiratory distress, hospitalized COVID-19 patient, severe disease, neutrophil activation, leads, Predictive, respiratory distress, observation, hospitalized COVID-19 patients, syndrome, clinical evolution, independent, identify, the disease, hospitalized patient, category, cohort of patients, 【제목키워드】 Medicine, signature,