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- Publisher Website: 10.1038/s41392-021-00508-4
- Scopus: eid_2-s2.0-85104416427
- PMID: 33859163
- WOS: WOS:000640543400001
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Article: Multi-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery
Title | Multi-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery |
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Authors | |
Issue Date | 2021 |
Publisher | Nature Research: Fully open access journals. The Journal's web site is located at http://www.nature.com/sigtrans/ |
Citation | Signal Transduction and Targeted Therapy, 2021, v. 6, p. article no. 155 How to Cite? |
Abstract | 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. |
Persistent Identifier | http://hdl.handle.net/10722/301122 |
ISSN | 2023 Impact Factor: 40.8 2023 SCImago Journal Rankings: 8.737 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Y | - |
dc.contributor.author | Hou, G | - |
dc.contributor.author | Zhou, H | - |
dc.contributor.author | Wang, Y | - |
dc.contributor.author | Tun, HM | - |
dc.contributor.author | Zhu, A | - |
dc.contributor.author | Zhao, J | - |
dc.contributor.author | Xiao, F | - |
dc.contributor.author | Lin, S | - |
dc.contributor.author | Liu, D | - |
dc.contributor.author | Zhou, D | - |
dc.contributor.author | Mai, L | - |
dc.contributor.author | Zhang, L | - |
dc.contributor.author | Zhang, Z | - |
dc.contributor.author | Kuang, Z | - |
dc.contributor.author | Guan, J | - |
dc.contributor.author | Chen, Q | - |
dc.contributor.author | Wen, L | - |
dc.contributor.author | Zhang, Y | - |
dc.contributor.author | Zhuo, J | - |
dc.contributor.author | Li, F | - |
dc.contributor.author | Zhuang, Z | - |
dc.contributor.author | Chen, Z | - |
dc.contributor.author | Luo, L | - |
dc.contributor.author | Liu, D | - |
dc.contributor.author | Chen, C | - |
dc.contributor.author | Gan, M | - |
dc.contributor.author | Zhong, N | - |
dc.contributor.author | Zhao, J | - |
dc.contributor.author | Ren, Y | - |
dc.contributor.author | Xu, Y | - |
dc.date.accessioned | 2021-07-27T08:06:26Z | - |
dc.date.available | 2021-07-27T08:06:26Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Signal Transduction and Targeted Therapy, 2021, v. 6, p. article no. 155 | - |
dc.identifier.issn | 2059-3635 | - |
dc.identifier.uri | http://hdl.handle.net/10722/301122 | - |
dc.description.abstract | 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. | - |
dc.language | eng | - |
dc.publisher | Nature Research: Fully open access journals. The Journal's web site is located at http://www.nature.com/sigtrans/ | - |
dc.relation.ispartof | Signal Transduction and Targeted Therapy | - |
dc.rights | Signal Transduction and Targeted Therapy. Copyright © Nature Research: Fully open access journals. | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.title | Multi-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery | - |
dc.type | Article | - |
dc.identifier.email | Tun, HM: heinmtun@hku.hk | - |
dc.identifier.authority | Tun, HM=rp02389 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1038/s41392-021-00508-4 | - |
dc.identifier.pmid | 33859163 | - |
dc.identifier.pmcid | PMC8047575 | - |
dc.identifier.scopus | eid_2-s2.0-85104416427 | - |
dc.identifier.hkuros | 323440 | - |
dc.identifier.volume | 6 | - |
dc.identifier.spage | article no. 155 | - |
dc.identifier.epage | article no. 155 | - |
dc.identifier.isi | WOS:000640543400001 | - |
dc.publisher.place | United States | - |