Biomarkers and Immune Repertoire Metrics Identified by Peripheral Blood Transcriptomic Sequencing Reveal the Pathogenesis of COVID-19

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global crisis; however, our current understanding of the host immune response to SARS-CoV-2 infection remains limited. Herein, we performed RNA sequencing using peri...

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Main Authors: Yang Liu, Yankang Wu, Bing Liu, Youpeng Zhang, Dan San, Yu Chen, Yu Zhou, Long Yu, Haihong Zeng, Yun Zhou, Fuxiang Zhou, Heng Yang, Lei Yin, Yafei Huang
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-08-01
Series:Frontiers in Immunology
Subjects:
IgG
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2021.677025/full
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spelling doaj-e52889fa184e4405b0310a3c1cb178e72021-08-24T06:14:29ZengFrontiers Media S.A.Frontiers in Immunology1664-32242021-08-011210.3389/fimmu.2021.677025677025Biomarkers and Immune Repertoire Metrics Identified by Peripheral Blood Transcriptomic Sequencing Reveal the Pathogenesis of COVID-19Yang Liu0Yankang Wu1Bing Liu2Youpeng Zhang3Dan San4Yu Chen5Yu Zhou6Long Yu7Haihong Zeng8Yun Zhou9Fuxiang Zhou10Heng Yang11Lei Yin12Yafei Huang13State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, ChinaState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, ChinaDepartment of Respiratory and Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, ChinaState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, ChinaState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, ChinaState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, ChinaState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, ChinaTongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaTongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaTongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Respiratory and Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, ChinaCenter for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, ChinaState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, ChinaTongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaThe coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global crisis; however, our current understanding of the host immune response to SARS-CoV-2 infection remains limited. Herein, we performed RNA sequencing using peripheral blood from acute and convalescent patients and interrogated the dynamic changes of adaptive immune response to SARS-CoV-2 infection over time. Our results revealed numerous alterations in these cohorts in terms of gene expression profiles and the features of immune repertoire. Moreover, a machine learning method was developed and resulted in the identification of five independent biomarkers and a collection of biomarkers that could accurately differentiate and predict the development of COVID-19. Interestingly, the increased expression of one of these biomarkers, UCHL1, a molecule related to nervous system damage, was associated with the clustering of severe symptoms. Importantly, analyses on immune repertoire metrics revealed the distinct kinetics of T-cell and B-cell responses to SARS-CoV-2 infection, with B-cell response plateaued in the acute phase and declined thereafter, whereas T-cell response can be maintained for up to 6 months post-infection onset and T-cell clonality was positively correlated with the serum level of anti-SARS-CoV-2 IgG. Together, the significantly altered genes or biomarkers, as well as the abnormally high levels of B-cell response in acute infection, may contribute to the pathogenesis of COVID-19 through mediating inflammation and immune responses, whereas prolonged T-cell response in the convalescents might help these patients in preventing reinfection. Thus, our findings could provide insight into the underlying molecular mechanism of host immune response to COVID-19 and facilitate the development of novel therapeutic strategies and effective vaccines.https://www.frontiersin.org/articles/10.3389/fimmu.2021.677025/fullSARS-CoV-2transcriptomic characteristicsIgGmachine learningbiomarker
collection DOAJ
language English
format Article
sources DOAJ
author Yang Liu
Yankang Wu
Bing Liu
Youpeng Zhang
Dan San
Yu Chen
Yu Zhou
Long Yu
Haihong Zeng
Yun Zhou
Fuxiang Zhou
Heng Yang
Lei Yin
Yafei Huang
spellingShingle Yang Liu
Yankang Wu
Bing Liu
Youpeng Zhang
Dan San
Yu Chen
Yu Zhou
Long Yu
Haihong Zeng
Yun Zhou
Fuxiang Zhou
Heng Yang
Lei Yin
Yafei Huang
Biomarkers and Immune Repertoire Metrics Identified by Peripheral Blood Transcriptomic Sequencing Reveal the Pathogenesis of COVID-19
Frontiers in Immunology
SARS-CoV-2
transcriptomic characteristics
IgG
machine learning
biomarker
author_facet Yang Liu
Yankang Wu
Bing Liu
Youpeng Zhang
Dan San
Yu Chen
Yu Zhou
Long Yu
Haihong Zeng
Yun Zhou
Fuxiang Zhou
Heng Yang
Lei Yin
Yafei Huang
author_sort Yang Liu
title Biomarkers and Immune Repertoire Metrics Identified by Peripheral Blood Transcriptomic Sequencing Reveal the Pathogenesis of COVID-19
title_short Biomarkers and Immune Repertoire Metrics Identified by Peripheral Blood Transcriptomic Sequencing Reveal the Pathogenesis of COVID-19
title_full Biomarkers and Immune Repertoire Metrics Identified by Peripheral Blood Transcriptomic Sequencing Reveal the Pathogenesis of COVID-19
title_fullStr Biomarkers and Immune Repertoire Metrics Identified by Peripheral Blood Transcriptomic Sequencing Reveal the Pathogenesis of COVID-19
title_full_unstemmed Biomarkers and Immune Repertoire Metrics Identified by Peripheral Blood Transcriptomic Sequencing Reveal the Pathogenesis of COVID-19
title_sort biomarkers and immune repertoire metrics identified by peripheral blood transcriptomic sequencing reveal the pathogenesis of covid-19
publisher Frontiers Media S.A.
series Frontiers in Immunology
issn 1664-3224
publishDate 2021-08-01
description The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global crisis; however, our current understanding of the host immune response to SARS-CoV-2 infection remains limited. Herein, we performed RNA sequencing using peripheral blood from acute and convalescent patients and interrogated the dynamic changes of adaptive immune response to SARS-CoV-2 infection over time. Our results revealed numerous alterations in these cohorts in terms of gene expression profiles and the features of immune repertoire. Moreover, a machine learning method was developed and resulted in the identification of five independent biomarkers and a collection of biomarkers that could accurately differentiate and predict the development of COVID-19. Interestingly, the increased expression of one of these biomarkers, UCHL1, a molecule related to nervous system damage, was associated with the clustering of severe symptoms. Importantly, analyses on immune repertoire metrics revealed the distinct kinetics of T-cell and B-cell responses to SARS-CoV-2 infection, with B-cell response plateaued in the acute phase and declined thereafter, whereas T-cell response can be maintained for up to 6 months post-infection onset and T-cell clonality was positively correlated with the serum level of anti-SARS-CoV-2 IgG. Together, the significantly altered genes or biomarkers, as well as the abnormally high levels of B-cell response in acute infection, may contribute to the pathogenesis of COVID-19 through mediating inflammation and immune responses, whereas prolonged T-cell response in the convalescents might help these patients in preventing reinfection. Thus, our findings could provide insight into the underlying molecular mechanism of host immune response to COVID-19 and facilitate the development of novel therapeutic strategies and effective vaccines.
topic SARS-CoV-2
transcriptomic characteristics
IgG
machine learning
biomarker
url https://www.frontiersin.org/articles/10.3389/fimmu.2021.677025/full
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