Integrated metabolomic and transcriptomic analysis reveals novel plasma biomarkers and metabolic pathway dysregulation in latent tuberculosis infection.

Tuberculosis (TB) remains a global health threat, and latent TB infection (LTBI) serves as a significant reservoir for new cases. Current diagnostic methods have limitations in accuracy and specificity. This study aimed to identify novel plasma biomarkers for LTBI by integrating metabolomics and transcriptomics. Plasma samples from healthy controls (HC) and LTBI patients were analyzed using liquid chromatography-mass spectrometry (LC-MS)/MS. We identified distinct metabolic signatures characterizing LTBI, and a diagnostic model based on five key metabolites-margaroylglycine, N-palmitoyl tryptophan, oleamide, myristic acid, and pentadecanoic acid-was established, demonstrating discriminatory potential. Multi-omics integration revealed that these metabolites are significantly associated with perturbations in glycerophospholipid and tryptophan metabolism pathways. Validation via qPCR confirmed significant dysregulation of associated genes ( IMPORTANCE: Latent tuberculosis (TB) infection (LTBI) acts as a silent reservoir for the global tuberculosis epidemic, yet current diagnostic tools often lack the specificity to fully capture the host's biological response. This study addresses this critical gap by using a multi-omics approach to decode the hidden metabolic changes in the blood. We discovered a unique "chemical fingerprint" consisting of five specific metabolites that can accurately distinguish latent infection from healthy states. Beyond providing a highly accurate diagnostic model, our findings reveal how the infection subtly reprograms host lipid and immune pathways. This work is significant because it offers a promising new tool for clinical screening and deepens our understanding of the metabolic interplay between the host and the pathogen, paving the way for better disease control strategies.