ArticleVirus genes2025
Unraveling potential gene biomarkers for dengue infection through RNA sequencing.
Article in Virus genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mechanistic constraints in dengue severity: a systematic review with evidence stratification and agent-based evaluation of logical sufficiency.Frontiers in immunology · 2026Pooled it
- Integrative Transcriptomic Analysis Reveals Distinct and Shared Host Responses in Dengue and Chikungunya Infections.International journal of molecular sciences · 2026Article
- Role of MZB1 in disease pathogenesis: current insights and future directions.Clinical and experimental medicine · 2026Review
- Hybrid Feature Selection-Based Machine Learning and Deep Learning Framework for Biomarker Prediction From RNA-seq Data During Dengue Fever to Severe Dengue Progression.Evolutionary bioinformatics online · 2026Article
- Research progress on the role of MZB1 in immune regulation.Frontiers in immunology · 2026Review
- In-silico discovery of druggable molecular signatures that drive dengue fever to severe dengue fever highlighting common pathogenesis through single-cell RNA-Seq analysis.Scientific reports · 2025Article
- Mechanistic Insights Into the Tumor-Driving and Diagnostic Roles of KCTD Family Genes in Ovarian Cancer: An Integrated In Silico and In Vitro Analysis.Cancer medicine · 2025Article
- Immune profiling in subclinical secondary dengue-infected cases reveals adaptive immune signatures correlated to protection from severe dengue.Cell host & microbe · 2025Article
- Dengue infection changes the expressions of CD154 and CD148 in human platelets.Virus research · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Dengue virus hijacks host cell mechanisms and immune responses in order to replicate efficiently. The interaction between the host and the virus affects the host's gene expression, which remains largely unexplored. This pilot study aimed to profile the host transcriptome as a potential strategy for identifying specific biomarkers for dengue prediction and detection. High-throughput RNA sequencing (RNA-seq) was employed to generate host transcriptome profiles in 16 dengue patients and 10 healthy controls. Differentially expressed genes (DEGs) were identified in patients with severe dengue and those with dengue with warning signs compared to healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to elucidate the functions of upregulated and downregulated genes. Compared to healthy controls, 6466 genes were significantly differentially expressed (p < 0.05) in the dengue with warning signs group and 3082 genes in the severe dengue group, with over half being upregulated. The major KEGG pathways implicated included transport and catabolism (14.4%-16.3%), signal transduction (6.6%-7.3%), global and overview maps (6.7%-7.1%), viral diseases (4.6%-4.8%), and the immune system (4.4%-4.6%). Several genes exhibited consistent and significant upregulation across all dengue patients, regardless of severity: Interferon alpha inducible protein 27 (IFI27), Potassium Channel Tetramerization Domain Containing 14 (KCTD14), Syndecan 1 (SDC1), DCC netrin 1 receptor (DCC), Ubiquitin C-terminal hydrolase L1 (UCHL1), Marginal zone B and B1 cell-specific protein (MZB1), Nestin (NES), C-C motif chemokine ligand 2 (CCL2), TNF receptor superfamily member 17 (TNFSF17), and TNF receptor superfamily member 13B (TNFRSF13B). Further analysis revealed potential biomarkers for severe dengue prediction, including TNF superfamily member 15 (TNFSF15), Plasminogen Activator Inhibitor-2 (SERPINB2), motif chemokine ligand 7 (CCL7), aconitate decarboxylase 1 (ACOD1), Metallothionein 1G (MT1G), and Myosin Light Chain Kinase (MYLK2), which were expressed 3.5 times, 2.9 times, 2.3 times, 2.1 times, 1.7 times, and 1.4 times greater, respectively, than dengue patients exhibiting warning signs. The identification of these host biomarkers through RNA-sequencing holds promising implications and potential to augment existing dengue detection algorithms, contributing significantly to improved diagnostic and prognostic capabilities.
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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 Socratic graph.