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10.1038/s41392-021-00508-4

http://scihub22266oqcxt.onion/10.1038/s41392-021-00508-4
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33859163!8047575!33859163
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suck abstract from ncbi


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pmid33859163      Signal+Transduct+Target+Ther 2021 ; 6 (1): 155
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  • Multi-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery #MMPMID33859163
  • Li Y; Hou G; Zhou H; Wang Y; Tun HM; Zhu A; Zhao J; Xiao F; Lin S; Liu D; Zhou D; Mai L; Zhang L; Zhang Z; Kuang L; Guan J; Chen Q; Wen L; Zhang Y; Zhuo J; Li F; Zhuang Z; Chen Z; Luo L; Liu D; Chen C; Gan M; Zhong N; Zhao J; Ren Y; Xu Y
  • Signal Transduct Target Ther 2021[Apr]; 6 (1): 155 PMID33859163show ga
  • 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.
  • |*COVID-19 Drug Treatment[MESH]
  • |*Drug Discovery[MESH]
  • |*Lipidomics[MESH]
  • |*Proteomics[MESH]
  • |Biomarkers/blood[MESH]
  • |COVID-19/*blood[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Male[MESH]


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