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Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility

BACKGROUND: Human population exposed to influenza viruses exhibited wide variation in susceptibility. The ratio of neutrophils to lymphocytes (NLR) has been examined to be a marker of systemic inflammation. We sought to investigate the relationship between influenza susceptibility and the NLR taken...

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Autores principales: Wang, Guoyun, Lv, Cheng, Liu, Cheng, Shen, Wenjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583527/
https://www.ncbi.nlm.nih.gov/pubmed/36274727
http://dx.doi.org/10.3389/fmicb.2022.1003380
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author Wang, Guoyun
Lv, Cheng
Liu, Cheng
Shen, Wenjun
author_facet Wang, Guoyun
Lv, Cheng
Liu, Cheng
Shen, Wenjun
author_sort Wang, Guoyun
collection PubMed
description BACKGROUND: Human population exposed to influenza viruses exhibited wide variation in susceptibility. The ratio of neutrophils to lymphocytes (NLR) has been examined to be a marker of systemic inflammation. We sought to investigate the relationship between influenza susceptibility and the NLR taken before influenza virus infection. METHODS: We investigated blood samples from five independent influenza challenge cohorts prior to influenza inoculation at the cellular level by using digital cytometry. We used multi-cohort gene expression analysis to compare the NLR between the symptomatic infected (SI) and asymptomatic uninfected (AU) subjects. We then used a network analysis approach to identify host factors associated with NLR and influenza susceptibility. RESULTS: The baseline NLR was significantly higher in the SI group in both discovery and validation cohorts. The NLR achieved an AUC of 0.724 on the H3N2 data, and 0.736 on the H1N1 data in predicting influenza susceptibility. We identified four key modules that were not only significantly correlated with the baseline NLR, but also differentially expressed between the SI and AU groups. Genes within these four modules were enriched in pathways involved in B cell-mediated immune responses, cellular metabolism, cell cycle, and signal transduction, respectively. CONCLUSIONS: This study identified the NLR as a potential biomarker for predicting disease susceptibility to symptomatic influenza. An elevated NLR was detected in susceptible hosts, who may have defects in B cell-mediated immunity or impaired function in cellular metabolism, cell cycle or signal transduction. Our work can serve as a comparative model to provide insights into the COVID-19 susceptibility.
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spelling pubmed-95835272022-10-21 Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility Wang, Guoyun Lv, Cheng Liu, Cheng Shen, Wenjun Front Microbiol Microbiology BACKGROUND: Human population exposed to influenza viruses exhibited wide variation in susceptibility. The ratio of neutrophils to lymphocytes (NLR) has been examined to be a marker of systemic inflammation. We sought to investigate the relationship between influenza susceptibility and the NLR taken before influenza virus infection. METHODS: We investigated blood samples from five independent influenza challenge cohorts prior to influenza inoculation at the cellular level by using digital cytometry. We used multi-cohort gene expression analysis to compare the NLR between the symptomatic infected (SI) and asymptomatic uninfected (AU) subjects. We then used a network analysis approach to identify host factors associated with NLR and influenza susceptibility. RESULTS: The baseline NLR was significantly higher in the SI group in both discovery and validation cohorts. The NLR achieved an AUC of 0.724 on the H3N2 data, and 0.736 on the H1N1 data in predicting influenza susceptibility. We identified four key modules that were not only significantly correlated with the baseline NLR, but also differentially expressed between the SI and AU groups. Genes within these four modules were enriched in pathways involved in B cell-mediated immune responses, cellular metabolism, cell cycle, and signal transduction, respectively. CONCLUSIONS: This study identified the NLR as a potential biomarker for predicting disease susceptibility to symptomatic influenza. An elevated NLR was detected in susceptible hosts, who may have defects in B cell-mediated immunity or impaired function in cellular metabolism, cell cycle or signal transduction. Our work can serve as a comparative model to provide insights into the COVID-19 susceptibility. Frontiers Media S.A. 2022-10-06 /pmc/articles/PMC9583527/ /pubmed/36274727 http://dx.doi.org/10.3389/fmicb.2022.1003380 Text en Copyright © 2022 Wang, Lv, Liu and Shen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Wang, Guoyun
Lv, Cheng
Liu, Cheng
Shen, Wenjun
Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility
title Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility
title_full Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility
title_fullStr Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility
title_full_unstemmed Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility
title_short Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility
title_sort neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583527/
https://www.ncbi.nlm.nih.gov/pubmed/36274727
http://dx.doi.org/10.3389/fmicb.2022.1003380
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