IMMUNOLOGICAL CHARACTERISTICS OF LATENT TUBERCULOSIS INFECTION

Tuberculosis (TB) continues to be one of the top 10 causes of death worldwide, caused by Mycobacterium tuberculosis. According to WHO, in 2021, 1.4 million HIV-negative and 187,000 HIV-positive TB deaths were reported worldwide. Latent tuberculosis infection (LTBI) is an immune response against M. tuberculosis without clinical manifestations or radiological evidence of active TB. Current diagnostic methods are insufficient to differentiate between healthy and latently infected populations. Here, we used a machine learning approach to analyze publicly available proteomic data from saliva and serum in Ethiopia's healthy, latent TB (LTBI) and active TB (ATBI) people. Our analysis discovered a profile of six proteins, Mast Cell Expressed Membrane Protein-1, Hemopexin, Lamin A/C, Small Proline Rich Protein 2F, Immunoglobulin Kappa Variable 4-1, and Voltage Dependent Anion Channel 2 that can precisely differentiate between the healthy and latently infected populations. This data suggests that a combination of six host proteins can serve as accurate biomarkers to diagnose latent infection. This is important for populations living in high-risk areas as it may help in the surveillance and prevention of severe disease.