Predicting which people with latent Mycobacterium tuberculosis infection will progress to active disease is central to targeted prevention. Biomarkers under study fall into blood transcriptional profiles, cellular activation markers, soluble inflammatory proteins, and imaging features. Evidence from clinical cohorts and translational laboratories has established that combinations of these signals carry predictive value even though no single test yet suffices for routine clinical use.
Blood transcriptional signatures
Their positive predictive value is higher in high-incidence settings and among recently exposed contacts, and lower in low-burden populations.
Cellular and soluble immune markers
Imaging and integrated approaches
Imaging with PET-CT performed by teams including Mark Hatherill at the South African Tuberculosis Vaccine Initiative, University of Cape Town, reveals metabolically active pulmonary lesions in some asymptomatic individuals; those radiologic abnormalities predict progression more strongly than immune assays alone. Combining molecular, cellular, and imaging biomarkers improves discrimination and supports a move toward multilayer risk scores that can guide preventive treatment.
Relevance, causes, and consequences converge on public health: identifying high-risk individuals enables targeted preventive therapy, reduces transmission, and can be particularly impactful in resource-limited and high-burden regions where access, stigma, and health system capacity shape outcomes. However, practical deployment faces challenges of cost, laboratory capacity, and variable predictive performance across populations, underscoring the need for further prospective validation and equitable implementation.