摘要
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.
基金
This work is supported by the grants from The National Key Research and Development Program of China(2018YFC1200100 to JC2L)
National Science and Technology Major Project(2018ZX10301403 to JCZ.)
the emergency grants for prevention and control of SARS-CoV-2 of Ministry of Science and Technology of Guangdong province(2020A111128008,2020B111112003,2018B020207013,2020B111108001 and 2020B1111320003 to JCZ,2020B1111330001 to NZ.)
The National Program on Key Basic Research Project(2017YFC0906702 to Y.W.)
National Key Technology R&D Program(2018YFC1311900 to N2.)
Guangdong Science and Technology Foundation(2019B030316028,2020A1515010911 to NZ.)
Guangzhou Medical University High-level University Innovation Team Training Program(Guangzhou Medical University released[2017]No.159 to JCZ and JX2.)
111 project(D18010 to JCZI ).We thank the patients who took part in this study.
作者简介
Correspondence:Jincun Zhao,zhaojincun@gird.cn;Correspondence:Yan Ren,reny@genomics.cn;Correspondence:Yonghao Xu,dryonghao@163.com;contributed equally:Yuming Li;contributed equally:Guixue Hou;contributed equally:Haibo Zhou;contributed equally:Yanqun Wang;contributed equally:Hein Min Tun.
