A T-Cell-Derived 3-Gene Signature Distinguishes SARS-CoV-2 from Common Respiratory Viruses
Yang Li,
Xinya Tao,
Sheng Ye,
Qianchen Tai,
Yu-Ang You,
Xinting Huang,
Mifang Liang,
Kai Wang,
Haiyan Wen,
Chong You,
Yan Zhang,
Xiaohua Zhou
Affiliations
Yang Li
Beijing International Center for Mathematical Research, Peking University, Beijing 100871, China
Xinya Tao
Chongqing Research Institute of Big Data, Peking University, Chongqing 400041, China
Sheng Ye
Chongqing Center for Disease Control and Prevention, Chongqing 400707, China
Qianchen Tai
Department of Probability and Statistics, School of Mathematical Sciences, Peking University, Beijing 100091, China
Yu-Ang You
Institute of Pharmaceutical Science, King’s College London, London WC2R 2LS, UK
Xinting Huang
Chongqing Research Institute of Big Data, Peking University, Chongqing 400041, China
Mifang Liang
NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
Kai Wang
Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Department of Infectious Diseases, Institute for Viral Hepatitis, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
Haiyan Wen
Chongqing International Travel Health Care Center, Chongqing 401120, China
Chong You
Beijing International Center for Mathematical Research, Peking University, Beijing 100871, China
Yan Zhang
Sports & Medicine Integration Research Center (SMIRC), Capital University of Physical Education and Sports, Beijing 100088, China
Xiaohua Zhou
Beijing International Center for Mathematical Research, Peking University, Beijing 100871, China
Research on the host responses to respiratory viruses could help develop effective interventions and therapies against the current and future pandemics from the host perspective. To explore the pathogenesis that distinguishes SARS-CoV-2 infections from other respiratory viruses, we performed a multi-cohort analysis with integrated bioinformatics and machine learning. We collected 3730 blood samples from both asymptomatic and symptomatic individuals infected with SARS-CoV-2, seasonal human coronavirus (sHCoVs), influenza virus (IFV), respiratory syncytial virus (RSV), or human rhinovirus (HRV) across 15 cohorts. First, we identified an enhanced cellular immune response but limited interferon activities in SARS-CoV-2 infection, especially in asymptomatic cases. Second, we identified a SARS-CoV-2-specific 3-gene signature (CLSPN, RBBP6, CCDC91) that was predominantly expressed by T cells, could distinguish SARS-CoV-2 infection, including Omicron, from other common respiratory viruses regardless of symptoms, and was predictive of SARS-CoV-2 infection before detectable viral RNA on RT-PCR testing in a longitude follow-up study. Thereafter, a user-friendly online tool, based on datasets collected here, was developed for querying a gene of interest across multiple viral infections. Our results not only identify a unique host response to the viral pathogenesis in SARS-CoV-2 but also provide insights into developing effective tools against viral pandemics from the host perspective.
