Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over forty million patients worldwide. Although most coronavirus disease 2019 (COVID-19) patients have a good prognosis, some develop severe illness. Markers that define disease severity or predict clinical outcome need to be urgently developed as the mortality rate in critical cases is approximately 61.5%. In the present study, we performed in-depth proteome profiling of undepleted plasma from eight COVID-19 patients. Quantitative proteomic analysis using the BoxCar method revealed that 91 out of 1222 quantified proteins were differentially expressed depending on the severity of COVID-19. Importantly, we found 76 proteins, previously not reported, which could be novel prognostic biomarker candidates. Our plasma proteome signatures captured the host response to SARS-CoV-2 infection, thereby highlighting the role of neutrophil activation, complement activation, platelet function, and T cell suppression as well as proinflammatory factors upstream and downstream of interleukin-6, interleukin-1B, and tumor necrosis factor. Consequently, this study supports the development of blood biomarkers and potential therapeutic targets to aid clinical decision-making and subsequently improve prognosis of COVID-19.
Highlights
Coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global health threat caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
We provided this in-depth proteome as a cornerstone to the communities doing research on COVID-19
To the best of our knowledge, with a total of 1639 proteins identified and 1222 proteins statistically analyzed, this is the first comprehensive study of the plasma proteome for COVID-19 patients, which provides a unique insight into the altered protein circulation based on the severity of COVID-19
Summary
Coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global health threat caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Yan et al.[2] reported that blood-borne marker panels can identify the mortality rate in individual patients more than 10 days in advance with > 90% accuracy. They suggested that tissue damage markers can be leveraged to predict COVID-19 outcomes. Mass spectrometry (MS)-based proteomics may potentially be used as an ideal technology in this situation as it can quickly deliver substantial amounts of clinical and biological information from blood plasma or serum in an untargeted manner[3,4] These MS-based proteomic workflows for biomarker discovery and profiling are well e stablished[3]. We performed in-depth proteome profiling of undepleted plasma samples using the BoxCar acquisition m ethod[8] from an exploratory cohort comprising 8 COVID-19 patients to identify candidate biomarkers for evaluating the disease severity
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