Dengue fever is a major global health concern, particularly in regions where it co-occurs with comorbid conditions such as hepatitis, diabetes, coronary heart disease (CHD), chronic kidney disease (CKD), and chronic obstructive pulmonary disease (COPD). To develop targeted interventions, understanding the molecular basis of these comorbidities is essential. This study employs a systems biology approach using publicly available gene expression microarray datasets to identify genetic signatures shared between dengue and its major comorbidities. Using the Limma package in R with strict thresholds ( \(|\log _2 \text {FC}| \ge 1\) and adjusted p-value \(\le 0.01\) via the Benjamini–Hochberg correction), we identified differentially expressed genes (DEGs). We found overlapping DEGs between dengue and diabetes (46), CHD (18), hepatitis (242), COPD (14), and CKD (45), further classified as up- or downregulated. Gene–disease networks (GDNs) were constructed to highlight molecular interactions. Functional enrichment analysis—including gene ontology (GO) and pathway analysis—was performed using Enrichr. A multilayer GDN was visualized via Cytoscape, and major findings were validated using benchmark databases such as OMIM and dbGaP. These results suggest that shared immune dysregulation and metabolic dysfunction may underlie severe outcomes in dengue patients with comorbidities, potentially guiding future biomarker discovery and personalized treatment strategies.