Abstract

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), poses a global health challenge with substantial mortality and incidence rates. Sensitivity biomarkers and accurate distinction between pulmonary tuberculosis (PTB) and other progressions are vital for effective treatment and transmission prevention, yet existing diagnostic methods encounter reliability limitations, particularly in cases of malnutrition or concurrent HIV infection. This exploration investigates the potential of Neutrophil Extracellular Traps (NETs) related genes, especially IL1B, G0S2, PTAFR, and CSF3R, as biomarkers for pulmonary TB. Leveraging single-cell data from murine Mtb infection, dynamic changes in Neutrophils are observed, emphasizing their interaction with Macrophages/T-cells. NETs-related genes exhibit significant activity in neutrophils, contributing to TB severity. 31 human TB datasets (4209 samples) validate elevated expression of IL1B, G0S2, PTAFR, and CSF3R in PTB, significantly associating with demographic features, complications, and disease progression stages. A random forest model classifying healthy control (Control), subclinical infection (Subclinical), extrapulmonary tuberculosis (EPTB), PTB, and latent tuberculosis infection (LTBI), incorporating these four genes and their interaction genes as features, achieves high diagnostic accuracy. The model's lowest Area Under the Curve (AUC) is 0.871 for PTB, while its highest is 0.995 for EPTB. Furthermore, the developed diagnostic biomarker, TBSig, demonstrates reliability and sensitivity across diverse progressions of TB patients. Subtype analysis determined three PTB subtypes (C1, C2, C3) based on the focused NETs-related genes with distinct clinical characteristics and immune microenvironments. C1 exhibits heightened inflammation, while C3 shows T cell regulation dominance. Differential expression analysis reveals CLEC4D with expression dynamics align with disease progression stages. Interestingly, CLEC4D is potentially involved with early neutrophil activity and CD8+ T cell suppression. These findings provide insights into the molecular mechanisms of PTB and propose potential biomarkers for accurate diagnosis and therapeutic interventions.