作者
Hong Wang,Cuicui Liu,Xiaowei Xie,Mingming Niu,Yingrui Wang,Xuelian Cheng,Biao Zhang,Dong Zhang,Mengyao Liu,Rui Sun,Yanying Ma,Shihui Ma,Huijun Wang,Guo‐Qing Zhu,Yang Liu,Baiming Huang,Pei Su,Xiaoyuan Chen,Jun Zhao,Hongtao Wang,Long Shen,Li Fu,Qianqian Huang,Yang Yang,Weiling He,Chunxia Wu,Weigang Ge,Chen Chen,Qianyu Huo,Qingping Wang,Ying Wang,Lanlan Geng,Yan Xie,Youhua Xie,Lijun Liu,Jianwei Qi,Huaiyong Chen,Junping Wu,Erlie Jiang,Weijia Jiang,Ximo Wang,Zhongyang Shen,Tiannan Guo,Jiaxi Zhou,Ping Zhu,Tao Cheng
摘要
Although host responses to the ancestral SARS-CoV-2 strain are well described, those to the new Omicron variants are less resolved. We profiled the clinical phenomes, transcriptomes, proteomes, metabolomes, and immune repertoires of >1,000 blood cell or plasma specimens from SARS-CoV-2 Omicron patients. Using in-depth integrated multi-omics, we dissected the host response dynamics during multiple disease phases to reveal the molecular and cellular landscapes in the blood. Specifically, we detected enhanced interferon-mediated antiviral signatures of platelets in Omicron-infected patients, and platelets preferentially formed widespread aggregates with leukocytes to modulate immune cell functions. In addition, patients who were re-tested positive for viral RNA showed marked reductions in B cell receptor clones, antibody generation, and neutralizing capacity against Omicron. Finally, we developed a machine learning model that accurately predicted the probability of re-positivity in Omicron patients. Our study may inspire a paradigm shift in studying systemic diseases and emerging public health concerns.