Gene expression profiling identifies candidate biomarkers for active and latent tuberculosis

Area of Science:

• Genomics
• Molecular Diagnostics
• Infectious Disease Research

Background:

• Tuberculosis (TB) remains a significant global health challenge, with current diagnostic methods lacking optimal sensitivity, efficiency, or specificity.
• Distinguishing between active TB, latent TB infection, and healthy states is critical for disease control.
• Mycobacterium tuberculosis infection presents diagnostic challenges due to asymptomatic latent phases.

Purpose of the Study:

• To identify gene expression profiles in peripheral blood mononuclear cells (PBMCs) differentiating active TB, latent TB infection, and healthy individuals.
• To discover novel biomarkers for early and accurate TB diagnosis.
• To develop a computational model for TB detection using identified gene biomarkers.

Main Methods:

• Microarray analysis of PBMCs from Taiwanese individuals with active TB, latent infection, and healthy controls.
• Bioinformatic analysis to identify differentially expressed genes.
• Reverse transcription-quantitative PCR (RT-PCR) for validating candidate biomarkers (NEMF, ASUN, DHX29, PTPRC).
• Receiver operating characteristic (ROC) analysis and Naïve Bayes classification model construction.

Main Results:

• Gene expression analysis revealed significant differences in immune response, inflammation, and cell cycle pathways.
• Four genes (NEMF, ASUN, DHX29, PTPRC) were identified as potential TB biomarkers.
• PTPRC expression distinguished active TB from healthy individuals; ASUN differentiated latent TB from healthy individuals.
• DHX29 showed potential in identifying latent TB among active TB patients or healthy individuals.
• A Naïve Bayes model using ASUN, DHX29, and PTPRC demonstrated high performance in classifying TB states.

Conclusions:

• Blood gene expression profiles can effectively identify active TB patients and differentiate latent TB infections from healthy states.
• The identified biomarkers (ASUN, DHX29, PTPRC) show promise for developing sensitive molecular diagnostic tools for TB.
• Further validation in larger cohorts is necessary to confirm biomarker reliability and advance a cost-effective TB diagnostic platform.