Abstract
BACKGROUND: Immune thrombocytopenia (ITP) is an autoimmune disorder characterized by immune-mediated platelet destruction, leading to an abnormally reduced platelet count. While numerous susceptibility genomic loci have been identified, the genetic mechanisms and pathways driving ITP remain poorly understood. This limits treatment options to broad immunosuppressants that increase patient vulnerability. OBJECTIVE: This study aims to uncover the functional and biological significance of ITP-associated genetic variations by integrating bioinformatics approaches. It seeks to identify functional SNPs, key immune pathways, and potential drug targets to enhance understanding of ITP pathogenesis and support the development of targeted therapies. METHODS: An integrative bioinformatics approach was employed to identify expression quantitative trait loci (eQTL) and pathogenic SNPs, reconstruct protein-protein interaction (PPI) networks, perform gene ontology analysis, and explore potential drug targets. RESULTS: The study identified 60 eQTL and 6 pathogenic SNPs associated with ITP, along with over 300 gene ontology processes. 14 hub genes in the PPI network were linked to key immune mechanisms, including T cell dysfunction (CD40, CTLA4, FOXP3, IL-10, IL-4, TBX21), cytokine dysregulation (IFNG, IL-6, IL-10, IL-4, TNF-α, TGFB1), JAK/STAT signaling (JAK2, STAT1, STAT3), and pattern-recognition (TLR4). TNF-α emerged as the top-ranked hub gene. Additionally, several platelet related genes (HPA2, MPL, PRKCA, PTPN11, and others) were implicated in the analysis. CONCLUSION: Functional SNPs and hub genes identified in this study serve as potential biomarkers for ITP diagnosis and prognosis. Cytokine pathways and T cell subsets were highlighted as central players in ITP pathogenesis. The drug-gene interaction analysis further suggests potential therapeutic avenues through drug repurposing, offering insights into novel treatment strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12959-026-00833-0.