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Profiling of the immune repertoire in COVID-19 patients with mild, severe, convalescent, or retesting-positive status

  • Zhou, Yonggang1, 2, 3
  • Zhang, Jinhe2, 3
  • Wang, Dongyao1, 2, 3
  • Wang, Dong2, 3
  • Guan, Wuxiang4
  • Qin, Jingkun2, 3
  • Xu, Xiuxiu1, 2, 3
  • Fang, Jingwen5
  • Fu, Binqing1, 2, 3
  • Zheng, Xiaohu2, 3
  • Wang, Dongsheng1
  • Zhao, Hong6
  • Chen, Xianxiang7
  • Tian, Zhigang2, 3
  • Xu, Xiaoling1
  • Wang, Guiqiang6
  • Wei, Haiming1, 2, 3
  • 1 Respiratory and Critical Care Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China
  • 2 Technology of China, Hefei, 230027, China
  • 3 Institute of Immunology, University of Science and Technology of China, Hefei, 230027, China
  • 4 Center for Emerging Infectious Diseases, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, Hubei, 430071, China
  • 5 HanGene Biotech, Xiaoshan Innovation Polis, Hangzhou, Zhejiang, 311200, China
  • 6 Department of Infectious Diseases, Peking University First Hospital, Beijing, 100034, China
  • 7 Department of Tuberculosis, Wuhan Pulmonary Hospital, Wuhan, 430030, China
Published Article
Journal of Autoimmunity
Publication Date
Jan 14, 2021
DOI: 10.1016/j.jaut.2021.102596
PMID: 33540371
PMCID: PMC7837046
PubMed Central
  • Article


Forty-seven samples of peripheral blood mononuclear cells from four groups of coronavirus disease (COVID)-19 patients (mild, severe, convalescent, retesting-positive) and healthy controls were applied to profile the immune repertoire of COVID-19 patients in acute infection or convalescence by transcriptome sequencing and immune-receptor repertoire (IRR) sequencing. Transcriptome analyses showed that genes within principal component group 1 (PC1) were associated with infection and disease severity whereas genes within PC2 were associated with recovery from COVID-19. A “dual-injury mechanism” of COVID-19 severity was related to an increased number of proinflammatory pathways and activated hypercoagulable pathways. A machine-learning model based on the genes associated with inflammatory and hypercoagulable pathways had the potential to be employed to monitor COVID-19 severity. Signature analyses of B-cell receptors (BCRs) and T-cell receptors (TCRs) revealed the dominant selection of longer V–J pairs (e.g., IGHV3-9–IGHJ6 and IGHV3-23–IGHJ6) and continuous tyrosine motifs in BCRs and lower diversity of TCRs. These findings provide potential predictors for COVID-19 outcomes, and new potential targets for COVID-19 treatment.

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