期刊
SIGNAL TRANSDUCTION AND TARGETED THERAPY
卷 6, 期 1, 页码 -出版社
SPRINGERNATURE
DOI: 10.1038/s41392-021-00508-4
关键词
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资金
- National Key Research and Development Program of China [2018YFC1200100]
- National Science and Technology Major Project [2018ZX10301403]
- emergency grants for prevention and control of SARS-CoV-2 of Ministry of Science and Technology of Guangdong province [2020A111128008, 2020B111112003, 2018B020207013, 2020B111108001, 2020B1111320003, 2020B1111330001]
- National Program on Key Basic Research Project [2017YFC0906702]
- National Key Technology RD Program [2018YFC1311900]
- Guangdong Science and Technology Foundation [2019B030316028, 2020A1515010911]
- Guangzhou Medical University High-level University Innovation Team Training Program (Guangzhou Medical University released [2017]) [159]
- 111 project [D18010]
This study identified potential therapeutic targets and biomarkers for predicting disease severity in COVID-19 patients through multi-platform omics analysis, with validation of predictive power.
Disease progression prediction and therapeutic drug target discovery for Coronavirus disease 2019 (COVID-19) are particularly important, as there is still no effective strategy for severe COVID-19 patient treatment. Herein, we performed multi-platform omics analysis of serial plasma and urine samples collected from patients during the course of COVID-19. Integrative analyses of these omics data revealed several potential therapeutic targets, such as ANXA1 and CLEC3B. Molecular changes in plasma indicated dysregulation of macrophage and suppression of T cell functions in severe patients compared to those in non-severe patients. Further, we chose 25 important molecular signatures as potential biomarkers for the prediction of disease severity. The prediction power was validated using corresponding urine samples and plasma samples from new COVID-19 patient cohort, with AUC reached to 0.904 and 0.988, respectively. In conclusion, our omics data proposed not only potential therapeutic targets, but also biomarkers for understanding the pathogenesis of severe COVID-19.
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