Dengue, the most prevalent mosquito-borne disease worldwide, poses a significant health burden. This study integrates clinical data and transcriptomic datasets from different phases of dengue to investigate distinctive and shared cellular and molecular features. Clinical data from 29 dengue patients were collected and analyzed alongside a public transcriptomic data set (GSE28405) to perform differential gene expression analysis, functional enrichment, immune landscape assessment, and development of machine learning model. Neutropenia was observed in 54.79% of dengue patients, particularly during the defervescence phase (65.79%) in clinical cohorts. Bioinformatics analyses corroborated a significant reduction in neutrophil immune infiltration in dengue patients. Receiver operating characteristic curve analysis demonstrated that dynamic changes in neutrophil infiltration levels could predict disease progression, especially during the defervescence phase, with the area under the curve of 0.96. Three neutrophil-associated biomarkers-DHRS12, Transforming growth factor alpha, and ZDHHC19-were identified as promising for diagnosing and predicting dengue progression. In addition, the activation of neutrophil extracellular traps was significantly enhanced and linked to FcγR-mediated signaling pathways and Toll-like receptor signaling pathways. Neutrophil activation and depletion play a critical role in dengue's immune response. The identified biomarkers and their associated pathways offer potential for improved diagnosis and understanding of dengue pathogenesis and progression.
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http://dx.doi.org/10.1002/jmv.29729 | DOI Listing |
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