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COVIDpro: Database for Mining Protein Dysregulation in Patients with COVID-19
Fangfei Zhang1,2,3,4, Augustin Luna5,6, Tingting Tan2,3,4
1Fudan University, 220 Handan Road, Shanghai 200433, China.
Abstract:
The ongoing pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 still has limited treatment options. Our understanding of the molecular dysregulations that occur in response to infection remains incomplete. We developed a web application COVIDpro (https://www.guomics.com/covidPro/) that includes proteomics data obtained from 41 original studies conducted in 32 hospitals worldwide, involving 3077 patients and covering 19 types of clinical specimens, predominantly plasma and serum. The data set encompasses 53 protein expression matrices, comprising a total of 5434 samples and 14,403 unique proteins. We identified a panel of proteins that exhibit significant dysregulation, enabling the classification of COVID-19 patients into severe and non-severe disease categories. The proteomic signatures achieved promising results in distinguishing severe cases, with a mean area under the curve of 0.87 and accuracy of 0.80 across five independent test sets. COVIDpro serves as a valuable resource for testing hypotheses and exploring potential targets for novel treatments in COVID-19 patients.
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