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Urine Proteome of COVID-19 Patients
Open accessPreprint — published as 10.1016/j.urine.2021.02.001
Abstract
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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Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566
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Research works printed but not linked: 39
- 10.1038/s41586-020-2012-7 · DOI · Paper page
- 10.1056/NEJMoa2001017 · DOI · Paper page
- 10.1038/s41586-020-2008-3 · DOI · Paper page
- 2020, The architecture of SARS-CoV-2 transcriptome, Bioinformatics, 29, 15
- Cinatl, J. , et al., SARS-CoV-2 infected host cell proteomics reveal potential therapy targets. Preprint available at Research Square, 2020.
- Davidson, A.D. , et al., Characterisation of the transcriptome and proteome of SARS-CoV-2 using direct RNA sequencing and tandem mass spectrometry reveals evidence for a cell passage induced in-frame deletion in the spike glycoprotein that removes the furin-like cleavage site. bioRxiv, 2020. · DOI
- 2020, First known person-to-person transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the USA, The Lancet, 395, 1137, 10.1016/S0140-6736(20)30607-3 · DOI
- 10.1001/jama.2020.1585 · DOI · Paper page
- 2020, Liver injury in COVID-19: management and challenges, The Lancet Gastroenterology & Hepatology, 5, 428, 10.1016/S2468-1253(20)30057-1 · DOI
- 10.1136/jclinpath-2020-206522 · DOI
- Forster, P. , et al., Phylogenetic network analysis of SARS-CoV-2 genomes. Proc Natl Acad Sci U S A, 2020. · DOI
- 2020, Care for Critically Ill Patients With COVID-19, JAMA, 323, 1499, 10.1001/jama.2020.3633 · DOI
- 10.1001/jama.2020.2648 · DOI · Paper page
- 10.1016/s01406736(20)30211-7 · DOI
- 10.1002/emmm.201201494 · DOI
- 10.1038/s41598-017-03226-6 · DOI
- Shen, B. , et al., Proteomic and Metabolomic Characterization of COVID-19 Patient Sera. medRxiv, 2020. · DOI · Paper page
- 2018, Urine proteome profiling predicts lung cancer from control cases and other tumors, EBioMedicine, 30, 120, 10.1016/j.ebiom.2018.03.009 · DOI
- 10.1016/j.bbi.2018.02.013 · DOI · Paper page
- 2017, Why Batch Effects Matter in Omics Data, and How to Avoid Them, Trends Biotechnol, 35, 498, 10.1016/j.tibtech.2017.02.012 · DOI
- 10.6026/97320630002005 · DOI
- 2006, The effect of hypoxia on the expression of 150 kDa oxygen-regulated protein (ORP 150) in HeLa cells, Cell Physiol Biochem, 17, 89, 10.1159/000091467 · DOI
- 10.1074/mcp.M500324-MCP200 · DOI
- Negri, E.M. , et al., Heparin therapy improving hypoxia in COVID-19 patients - a case series. medRxiv, 2020: p. 2020.04.15.20067017. · DOI
- 10.1016/j.yexmp.2009.09.003 · DOI
- 2009, Heparin cofactor II as a novel vascular protective factor against atherosclerosis, J Atheroscler Thromb, 16, 523, 10.5551/jat.1552 · DOI
- 10.1002/hep.22439 · DOI
- Wei, C. , et al., Cholesterol Metabolism--Impact for SARS-CoV-2 Infection Prognosis, Entry, and Antiviral Therapies. medRxiv, 2020: p. 2020.04.16.20068528.
- Wang, D. , et al., Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA, 2020. · DOI · Paper page
- 2015, Exosomal proteins as potential diagnostic markers in advanced non-small cell lung carcinoma, J Extracell Vesicles, 4, 26659, 10.3402/jev.v4.26659 · DOI
- 10.1111/j.1440-1797.2005.00387.x · DOI
- 10.1503/cmaj.061590 · DOI
- Shao, C. , et al., A tool for biomarker discovery in the urinary proteome: a manually curated human and animal urine protein biomarker database. MCP, 2011. 10(11). · DOI
- 10.1002/pmic.201200591 · DOI
- Li, Y , et al., A rapid and easy protein N-terminal profiling strategy using (N-Succinimidyloxycarbonylmethyl)tris(2,4,6-trimethoxyphenyl)phosphonium bromide (TMPP) labeling and Stage Tip. Proteomics, 2017. 17(13-14). · DOI
- 10.1038/nbt.1511 · DOI · Paper page
- 10.1038/nprot.2016.136 · DOI
- 2016, The Perseus computational platform for comprehensive analysis of (prote) omics data, Nature methods, 13, 731, 10.1038/nmeth.3901 · DOI · Paper page
- 10.1093/nar/gky869 · DOI
Metadata
- Authors
- Li, Y., Wang, Y., Liu, H., Sun, W., Ding, B., Zhao, Y., Chen, P., Zhu, L., Li, Z., Li, N., Chang, L., Wang, H., Bai, C., & Xu, P.
- Affiliations
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Chinese PLA General Hospital (CN)
- University of Connecticut (US)
- Guizhou University (CN)
- Corresponding author
- Wang, Hengliang
- Bai, Changqing
- Xu, Ping
- ORCID
- Venue
- URINE
- Publisher
- openRxiv
- Published
- 2020-05-06
- Volume
- 2
- Pages
- 1-8
- ISSN
- 2590-2806 (ISSN-L)
- PMC
- PMC7933783
- OpenAlex
- W3133560788
- Cited by
- 68
- References
- 1
- Citations by year
- 2025: 5 · 2024: 8 · 2023: 19 · 2022: 15 · 2021: 15 · 2020: 6
- FWCI
- 1.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- URINE (publishedVersion, cc-by-nc-nd)
- medRxiv (acceptedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (AWS17J008, 31870824, 91839302, 2018ZX10732202, 2017YFA0505002, 2020YFE0202200, 16CXZ027, 31700723, K201901, 31670834, 31901037)
- Chinese Academy of Medical Sciences (2019RU006)
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- COVID-19 pandemic, SARS-CoV-2, urinary proteome, urinary biomarkers, disease severity prediction, complement activation, platelet secretion, lipoprotein metabolism, hypoxia response, comorbidities, early diagnosis
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