tetano
Editor, Senior Moderator
Front Immunol
. 2021 Aug 24;12:677025.
doi: 10.3389/fimmu.2021.677025. eCollection 2021.
Biomarkers and Immune Repertoire Metrics Identified by Peripheral Blood Transcriptomic Sequencing Reveal the Pathogenesis of COVID-19
Yang Liu[SUP] 1 [/SUP], Yankang Wu[SUP] 1 [/SUP], Bing Liu[SUP] 2 [/SUP], Youpeng Zhang[SUP] 1 [/SUP], Dan San[SUP] 1 [/SUP], Yu Chen[SUP] 1 [/SUP], Yu Zhou[SUP] 1 [/SUP], Long Yu[SUP] 3 [/SUP], Haihong Zeng[SUP] 3 [/SUP], Yun Zhou[SUP] 3 [/SUP], Fuxiang Zhou[SUP] 2 [/SUP], Heng Yang[SUP] 4 [/SUP], Lei Yin[SUP] 1 [/SUP], Yafei Huang[SUP] 3 [/SUP]
Affiliations
Abstract
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.
Keywords: IgG; SARS-CoV-2; biomarker; machine learning; transcriptomic characteristics.
. 2021 Aug 24;12:677025.
doi: 10.3389/fimmu.2021.677025. eCollection 2021.
Biomarkers and Immune Repertoire Metrics Identified by Peripheral Blood Transcriptomic Sequencing Reveal the Pathogenesis of COVID-19
Yang Liu[SUP] 1 [/SUP], Yankang Wu[SUP] 1 [/SUP], Bing Liu[SUP] 2 [/SUP], Youpeng Zhang[SUP] 1 [/SUP], Dan San[SUP] 1 [/SUP], Yu Chen[SUP] 1 [/SUP], Yu Zhou[SUP] 1 [/SUP], Long Yu[SUP] 3 [/SUP], Haihong Zeng[SUP] 3 [/SUP], Yun Zhou[SUP] 3 [/SUP], Fuxiang Zhou[SUP] 2 [/SUP], Heng Yang[SUP] 4 [/SUP], Lei Yin[SUP] 1 [/SUP], Yafei Huang[SUP] 3 [/SUP]
Affiliations
- PMID: 34504487
- PMCID: PMC8421539
- DOI: 10.3389/fimmu.2021.677025
Abstract
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.
Keywords: IgG; SARS-CoV-2; biomarker; machine learning; transcriptomic characteristics.