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1.
FEBS J ; 288(17): 5190-5200, 2021 09.
Article in English | MEDLINE | ID: covidwho-887379

ABSTRACT

Up to 10-20% of patients with coronavirus disease 2019 (COVID-19) develop a severe pulmonary disease due to immune dysfunction and cytokine dysregulation. However, the extracellular proteomic characteristics in respiratory tract of these critical COVID-19 patients still remain to be investigated. In the present study, we performed a quantitative proteomic analysis of the bronchoalveolar lavage fluid (BALF) from patients with critical COVID-19 and from non-COVID-19 controls. Our study identified 358 differentially expressed BALF proteins (P < 0.05), among which 41 were significantly changed after using the Benjamini-Hochberg correction (q < 0.05). The up-regulated signaling was found to be mainly involved in inflammatory signaling and response to oxidative stress. A series of increased extracellular factors including Tenascin-C (TNC), Mucin-1 (KL-6 or MUC1), Lipocalin-2 (LCN2), periostin (POSTN), Chitinase 3-like 1 (CHI3L1 or YKL40), and S100A12, and the antigens including lymphocyte antigen 6D/E48 antigen (LY6D), CD9 antigen, CD177 antigen, and prostate stem cell antigen (PSCA) were identified, among which the proinflammatory factors TNC and KL-6 were further validated in serum of another thirty-nine COVID-19 patients and healthy controls, showing high potentials of being biomarkers or therapeutic candidates for COVID-19. This BALF proteome associated with COVID-19 would also be a valuable resource for researches on anti-inflammatory medication and understanding the molecular mechanisms of host response. DATABASE: Proteomic raw data are available in ProteomeXchange (http://proteomecentral.proteomexchange.org) under the accession number PXD022085, and in iProX (www.iprox.org) under the accession number IPX0002429000.


Subject(s)
Bronchoalveolar Lavage Fluid , COVID-19/genetics , Proteome/genetics , SARS-CoV-2/genetics , Adult , COVID-19/pathology , COVID-19/virology , Critical Illness , Female , Humans , Lung/metabolism , Lung/pathology , Male , Middle Aged , Proteomics , SARS-CoV-2/pathogenicity
2.
Immunity ; 53(5): 1108-1122.e5, 2020 11 17.
Article in English | MEDLINE | ID: covidwho-880509

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic is a global public health crisis. However, little is known about the pathogenesis and biomarkers of COVID-19. Here, we profiled host responses to COVID-19 by performing plasma proteomics of a cohort of COVID-19 patients, including non-survivors and survivors recovered from mild or severe symptoms, and uncovered numerous COVID-19-associated alterations of plasma proteins. We developed a machine-learning-based pipeline to identify 11 proteins as biomarkers and a set of biomarker combinations, which were validated by an independent cohort and accurately distinguished and predicted COVID-19 outcomes. Some of the biomarkers were further validated by enzyme-linked immunosorbent assay (ELISA) using a larger cohort. These markedly altered proteins, including the biomarkers, mediate pathophysiological pathways, such as immune or inflammatory responses, platelet degranulation and coagulation, and metabolism, that likely contribute to the pathogenesis. Our findings provide valuable knowledge about COVID-19 biomarkers and shed light on the pathogenesis and potential therapeutic targets of COVID-19.


Subject(s)
Coronavirus Infections/blood , Coronavirus Infections/pathology , Plasma/metabolism , Pneumonia, Viral/blood , Pneumonia, Viral/pathology , Adult , Aged , Aged, 80 and over , Betacoronavirus , Biomarkers/blood , Blood Proteins/metabolism , COVID-19 , Coronavirus Infections/classification , Coronavirus Infections/metabolism , Female , Humans , Machine Learning , Male , Middle Aged , Pandemics/classification , Pneumonia, Viral/classification , Pneumonia, Viral/metabolism , Proteomics , Reproducibility of Results , SARS-CoV-2
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