medRxiv · 2020 · 20 citations · 37 references
Life SciencesBiochemistryInfectious DiseasesImmunopathologyInflammationProteomicsClinical ProteomicsMass Spectrometry Data AnalysisMass Spectrometry-based ProteomicsProteomic BiomarkersProteomic ProfilingClustering AnalysisComplement Activation PathwaysDisease ProteomicsPlatelet DegranulationProtein Analysis In Body FluidsProtein Expression ProfilingProteome-wide ProfilingProteomic Data Analysis
SUMMARY The atypical pneumonia (COVID-19) caused by SARS-CoV-2 is an ongoing pandemic and a serious threat to global public health. The COVID-19 patients with severe symptoms account for a majority of mortality of this disease. However, early detection and effective prediction of patients with mild to severe symptoms remains challenging. In this study, we performed proteomic profiling of urine samples from 32 healthy control individuals and 6 COVID-19 positive patients (3 mild and 3 severe). We found that urine proteome samples from the mild and severe COVID-19 patients with comorbidities can be clearly differentiated from healthy proteome samples based on the clustering analysis. Multiple pathways have been compromised after the COVID-19 infection, including the dysregulation of immune response, complement activation, platelet degranulation, lipoprotein metabolic process and response to hypoxia. We further validated our finding by directly comparing the same patients’ urine proteome after recovery. This study demonstrates the COVID-19 pathophysiology related molecular alterations could be detected in the urine and the potential application of urinary proteome in auxiliary diagnosis, severity determination and therapy development of COVID-19.
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Clinical Characteristics of Coronavirus Disease 2019 in China
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Veterinary Medicine, Infectious Diseases, Internal Medicine +10
A Novel Coronavirus from Patients with Pneumonia in China, 2019
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