Dengue virus infection remains a major global health threat, with severe dengue disease progressing to life-threatening hemorrhage and shock syndrome. While clinical manifestations are well-documented, the transcriptional landscape associated with dengue disease severity remains incompletely understood. A multi-cohort transcriptomic analysis of public datasets was performed to establish a consensus gene expression signature of dengue virus infection. Functional enrichment and protein-protein interaction networks were used to identify biological processes and highly connected nodes. In silico drug-gene interaction analysis was conducted to prioritize candidate compounds. Clinical validation was performed using an independent cohort to assess gene expression patterns across dengue disease severity groups. Differential expression analysis revealed downregulation of interferon-related genes, including STAT1-associated pathways, alongside upregulation of stress-response genes such as CDKN1A (p21), FOS, and JUNB. Network analysis identified these genes as highly connected nodes, suggesting coordinated interplay between antiviral signaling and endothelial stress responses. Candidate compounds, including Garcinol, Paclitaxel, and Romidepsin, were identified based on curated drug-gene interactions as potential modulators of this transcriptional signature. This study defines a consensus transcriptional signature associated with dengue virus infection and dengue disease severity, highlighting coordinated changes in highly connected genes involved in host response pathways. These findings provide a framework for future experimental validation and the development of host-directed therapeutic strategies.
Pestana et al. (Mon,) studied this question.