ArticleFrontiers in microbiology2022
Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility.
Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 10 citations in OpenAlex.
- CSsingle: a unified tool for robust decomposition of bulk and spatial transcriptomic data across diverse single-cell references.Nucleic acids research · 2026Article
- New Simplified White Blood Cells Score Improves Mortality Prediction in Severe COVID-19 Patients.Journal of clinical medicine · 2026Article
- Transcriptomic profiling reveals immune signatures associated with potential COVID-19 susceptibility and a predictive framework in a Chinese cohort.Frontiers in immunology · 2026Article
- The Neutrophil/Lymphocyte Ratio Was Identified as a Marker of Severe Influenza During the 2024-2025 Outbreak in France.Infectious disease reports · 2025Article
- The value of common blood parameters for the differential diagnosis of respiratory tract infections in children.AMB Express · 2025Article
- Harnessing Endogenous Peptide Compounds as Potential Therapeutics for Severe Influenza.The Journal of infectious diseases · 2024Article
- The blood routine test holds screening values for influenza A in 2023: a retrospective study.Translational pediatrics · 2024Article
- Leveraging baseline transcriptional features and information from single-cell data to power the prediction of influenza vaccine response.Frontiers in cellular and infection microbiology · 2024Article
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Authors and funding
4 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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