From Exposure to Disease: Predicting Tuberculosis Progression

Abstract Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), infects nearly one-fourth of global population, with 5%–10% progressing to active TB, one of the deadliest infectious diseases worldwide. Despite advancements in identifying infected individuals, actual tools lack precision in identifying those at highest risk of active TB. Close contacts of TB cases are at particularly high risk of progression. Multinational networks, such RePORT (Regional Prospective Observational Research for TB) International—a consortium of eight country-based networks—have advanced the field through collaboration, data sharing, and large-scale studies across diverse populations. This review synthesizes current knowledge on TB transmission dynamics, biomarkers, and genetic factors influencing disease progression, predictive models for identifying high-risk individuals, and the implications for public health interventions and screening programs. By centering on findings from RePORT studies, we discuss the strengths and limitations of existing approaches, including the temporal dynamics and context dependence of host-response signatures, and consider key challenges for implementation in high-burden settings. Together, these insights highlight opportunities to refine targeted TB prevention strategies and advance progress toward TB elimination.