Evidence map›Paper›PMID 41995316›Full record

ArticleMicrobiology spectrum2026

Identification of neutrophil-related genes associated with the severity of RSV infection.

Daiyang Zhang, Hewei Zhang, Xin Zhang, Lei Yin, Xuejun Shao, Shenghao Hua

Abstract read
In one paragraph

Article in Microbiology spectrum, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Daiyang ZhangChildren's Hospital of Soochow University, Suzhou, Jiangsu, China.
Hewei ZhangChildren's Hospital of Soochow University, Suzhou, Jiangsu, China.
Xin ZhangChildren's Hospital of Soochow University, Suzhou, Jiangsu, China.
Lei YinChildren's Hospital of Soochow University, Suzhou, Jiangsu, China.
Xuejun ShaoChildren's Hospital of Soochow University, Suzhou, Jiangsu, China.
Shenghao HuaChildren's Hospital of Soochow University, Suzhou, Jiangsu, China.ORCID 0009-0000-4422-9139

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Respiratory syncytial virus (RSV) infection is a major cause of acute respiratory illness in infants and young children, leading to significant health and economic challenges. This study aimed to identify key neutrophil-related genes associated with the severity of RSV infection and to explore their potential as biomarkers and therapeutic targets. The GSE188427 and GSE246622 data sets in the Gene Expression Omnibus (GEO) were selected to identify key neutrophil-related genes. We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to identify enriched pathways. The ROC curve was applied to evaluate the diagnostic effectiveness of key genes. Clinical samples were used to validate these genes. Finally, we constructed networks of miRNA-gene and drug-gene interactions. Integrated bioinformatics analysis revealed 10 hub genes. Further validation revealed that most of them exhibited increased expression as symptoms worsened. In addition, the expression of these 10 hub genes decreased as the symptoms improved. ROC curve analyses indicated that BPI and ELANE effectively predict hospitalization needs for outpatients, whereas ARG1 and PADI4 are associated with severe disease progression. Validation with clinical samples confirmed that the expression levels of BPI, ELANE, ARG1, and PADI4 were positively associated with RSV severity. This study identified potential therapeutic targets, paving the way for future drug development and improved clinical management of RSV-related illnesses. An enhanced understanding of these biomarkers may facilitate earlier intervention and more tailored treatment strategies for affected patients. IMPORTANCE: Given the significant burden of respiratory syncytial virus (RSV) in infants and young children, our work addresses an important aspect of respiratory disease by identifying molecular markers that correlate with disease progression and recovery. This study investigates the relationship between specific neutrophil-related genes and the severity of RSV infection, highlighting their promise as biomarkers to aid clinical assessment and management.

Indexed as

NeutrophilsRespiratory Syncytial Virus, HumanRespiratory Syncytial Virus InfectionsBiomarkersComputational BiologyGene Expression ProfilingGene OntologyHumansInfantLeukocyte ElastaseMicroRNAsProteinase Inhibitory Proteins, SecretoryROC CurveSeverity of Illness IndexBiomarkersELANE protein, humanLeukocyte ElastaseMicroRNAsProteinase Inhibitory Proteins, Secretorybiomarkersneutrophil-related genesrespiratory syncytial virus

Identifiers

PMID41995316
PMCPMC13227954

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.