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Article: Multi-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery

TitleMulti-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery
Authors
Issue Date2021
PublisherNature 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?
AbstractDisease 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 Identifierhttp://hdl.handle.net/10722/301122
ISSN
PubMed Central ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Y-
dc.contributor.authorHou, G-
dc.contributor.authorZhou, H-
dc.contributor.authorWang, Y-
dc.contributor.authorTun, HM-
dc.contributor.authorZhu, A-
dc.contributor.authorZhao, J-
dc.contributor.authorXiao, F-
dc.contributor.authorLin, S-
dc.contributor.authorLiu, D-
dc.contributor.authorZhou, D-
dc.contributor.authorMai, L-
dc.contributor.authorZhang, L-
dc.contributor.authorZhang, Z-
dc.contributor.authorKuang, Z-
dc.contributor.authorGuan, J-
dc.contributor.authorChen, Q-
dc.contributor.authorWen, L-
dc.contributor.authorZhang, Y-
dc.contributor.authorZhuo, J-
dc.contributor.authorLi, F-
dc.contributor.authorZhuang, Z-
dc.contributor.authorChen, Z-
dc.contributor.authorLuo, L-
dc.contributor.authorLiu, D-
dc.contributor.authorChen, C-
dc.contributor.authorGan, M-
dc.contributor.authorZhong, N-
dc.contributor.authorZhao, J-
dc.contributor.authorRen, Y-
dc.contributor.authorXu, Y-
dc.date.accessioned2021-07-27T08:06:26Z-
dc.date.available2021-07-27T08:06:26Z-
dc.date.issued2021-
dc.identifier.citationSignal Transduction and Targeted Therapy, 2021, v. 6, p. article no. 155-
dc.identifier.issn2059-3635-
dc.identifier.urihttp://hdl.handle.net/10722/301122-
dc.description.abstractDisease 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.languageeng-
dc.publisherNature Research: Fully open access journals. The Journal's web site is located at http://www.nature.com/sigtrans/-
dc.relation.ispartofSignal Transduction and Targeted Therapy-
dc.rightsSignal Transduction and Targeted Therapy. Copyright © Nature Research: Fully open access journals.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleMulti-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery-
dc.typeArticle-
dc.identifier.emailTun, HM: heinmtun@hku.hk-
dc.identifier.authorityTun, HM=rp02389-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1038/s41392-021-00508-4-
dc.identifier.pmid33859163-
dc.identifier.pmcidPMC8047575-
dc.identifier.scopuseid_2-s2.0-85104416427-
dc.identifier.hkuros323440-
dc.identifier.volume6-
dc.identifier.spagearticle no. 155-
dc.identifier.epagearticle no. 155-
dc.publisher.placeUnited States-

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