Identification of Serum Prognostic Biomarkers of Severe COVID-19 by Multi-Layered Quantitative Proteomic Approach

The COVID-19 is an unprecedented threat to humanity provoking global health concerns. Since the etio-pathogenesis of this illness is not fully characterized, the prognostic factors enabling treatment decisions have not been well documented. An accurate prediction of the disease progression can aid in appropriate patient categorization to determine the best treatment option. Here, we introduced an innovative approach utilizing data-independent acquisition (DIA) mass spectrometry to identify the serum proteins closely associated with the COVID-19 severity. We observed 23 proteins to be differentially expressed between the cohorts of critically ill COVID-19 patients with adverse and favorable prognosis. Myoglobin (MB), CHI3L1 and IGFALS were found to have a high sensitivity and specificity for their possible use as independent biomarkers to provide information on the disease prognosis. Our findings can help in formulating a diagnostic approach for accurately discriminating severe COVID-19 patients and provide appropriate treatment based on their predicted prognosis.Funding: This work was in part supported by grants from the Japan Agency for Medical Research and Development (JP19fk0108169 to YK and JP19fk0108110/JP20he0522001 to AR).Conflict of Interest: The authors declare no competing interests.Ethical Approval: This research plan and protocol was approved by the Clinical Ethics Committee of Yokohama City University Hospital (B2002000048). This study was also performed with the approval of the Clinical Ethics Committee in each of the medical facilities. Informed consent was obtained from all patients and/or their guardians before serum samples collection.