The Trans-omics Landscape of COVID-19

• DOI: 10.1101/2020.07.17.20155150
• Publication Date: 2020-07-22T20:47:49Z
• Authors: Peng Wu; Dongsheng Chen; Wencheng Ding; Ping Wu; Hongyan Hou; Yong Bai; Yuwen Zhou; Kezhen Li; Shunian Xiang; Panhong Liu; Jia Ju; Ensong Guo; Jia Liu; Bin Yang; Junpeng Fan; Liang He; Ziyong Sun; Ling Feng; Jian Wang; Tangchun Wu; Hao Wang; Jin Cheng; Hui Xing; Yifan Meng; Yongsheng Li; Yuanliang Zhang; Hongbo Luo; Gang Xie; Xianmei Lan; Ye Tao; Hao Yuan; Kang Huang; Wan Sun; Xiaobo Qian; Zhichao Li; Mingxi Huang; Peiwen Ding; Haoyu Wang; Jiaying Qiu; Feiyue Wang; Shiyou Wang; Jiacheng Zhu; Xiangning Ding; Chaochao Chai; Langchao Liang; Xiaoling Wang; Lihua Luo; Yuzhe Sun; Ying Yang; Zhenkun Zhuang; Tao Li; Lei Tian; Shaoqiao Zhang; Linnan Zhu; Lei Chen; Yiquan Wu; Xiaoyan Ma; Fang Chen; Yan Ren; Xun Xu; Siqi Liu; Jian Wang; Huanming Yang; Lin Wang; Chaoyang Sun; Ding Ma; Xin Jin; Gang Chen
• Keywords: Cytokine Storm; Pathogenesis; Omics

Summary System-wide molecular characteristics of COVID-19, especially in those patients without comorbidities, have not been fully investigated. We compared extensive profiles blood samples from 231 COVID-19 patients, ranging asymptomatic to critically ill, importantly excluding with any comorbidities. Amongst the major findings, were characterized by highly activated anti-virus interferon, T/natural killer (NK) cell activation, and transcriptional upregulation inflammatory cytokine mRNAs. However, given very abundant RNA binding proteins (RBPs), these mRNAs could be effectively destabilized hence preserving normal levels. In contrast, ill storm due RBPs inhibition tryptophan metabolites accumulation contributed T/NK dysfunction. A machine-learning model was constructed which accurately stratified severities based on their multi-omics features. Overall, our analysis provides insights into pathogenesis identifies targets for intervening treatment.