Immune-Inflammatory Hub Genes Intersecting with a Ferroptosis-Associated Gene Set in Active Tuberculosis: A Multi-Dataset Bioinformatics Study.

The progression of tuberculosis (TB) from a latent infection to an active disease involves intricate modifications in host immune, inflammatory, oxidative, and metabolic pathways. Ferroptosis represents a distinct form of regulated cell death that requires iron and is associated with excessive lipid peroxidation and has been associated with tissue damage in TB; however, its connection with host transcriptional changes during active TB is not fully understood. This study sought to identify and externally validate immune-inflammatory hub genes among differentially expressed genes (DEGs) in active TB that overlap with a ferroptosis-associated gene set derived from FerrDb, employing an integrated transcriptomic and systems-biology methodology. Differential expression analysis of GSE37250 revealed 1015 DEGs in active TB compared to latent TB, comprising 585 upregulated and 430 downregulated genes, and 93 DEGs in active TB compared to healthy controls, including 65 upregulated and 28 downregulated genes. Intersection analysis identified 94 DEGs common to the active TB versus latent TB comparison and the ferroptosis-associated gene set, and eight DEGs common to the active tuberculosis versus healthy-control comparison and the same gene set, with no genes shared across all three sets. Functional enrichment of the 94 intersection genes underscored immune response, defense response, stress response, Toll-like receptor signaling, NOD-like receptor signaling, IL-17 signaling, TNF signaling, glutathione metabolism, neutrophil degranulation, cytokine signaling, and antimicrobial metal sequestration. Protein-protein interaction analysis followed by cytoHubba prioritization identified 10 hub genes: IL1B, TLR4, CXCL10, MMP9, CYBB, MPO, CD36, LCN2, S100A8, and LTF. Subsequent to outcome-independent probe selection, external validation in GSE28623 demonstrated significant positive differential expression of LCN2, S100A8, and LTF, while GSE62525 showed significant positive differential expression of IL1B, TLR4, MMP9, MPO, LCN2, and LTF. LCN2 and LTF were significantly upregulated in both validation datasets, indicating the strongest cross-dataset reproducibility. These results identify an immune-inflammatory transcriptional network intersecting with ferroptosis-associated genes in active TB. Notably, the transcriptomic findings do not confirm ferroptotic cell death but suggest candidate genes and biological processes for future experimental exploration.