Biomarker Identification and Treatment Monitoring in Pulmonary Tuberculosis

Pulmonary tuberculosis remains a leading cause of infectious mortality worldwide, yet progress in precision management has been hindered by the absence of reliable indicators of disease activity and treatment response. Biomarkers for tuberculosis encompass microbial measures, host immune signatures and composite indicators that correlate with bacterial burden, lung pathology and clinical recovery. Advances in molecular assays have enabled quantitative tracking of mycobacterial RNA and DNA in sputum, while multiplexed immunoassays and proteomic profiling of blood have uncovered panels of cytokines and acute-phase proteins that reflect disease severity and the trajectory of cure. Emerging work also identifies combinations of host and pathogen markers that may predict relapse risk, guide treatment duration and support individualised therapy. The global significance of these developments lies in reducing treatment failures, curbing the spread of drug-resistant strains and optimising resource allocation in settings of high disease burden. Integrating biomarker platforms into routine care demands assays that are rapid, minimally invasive, affordable and scalable, aligning with priorities for decentralised management and equitable access to diagnostics.

Research from Nature Portfolio

Recent studies have demonstrated that the quantitative output of widely used molecular platforms can serve as a surrogate for bacterial load, offering a point-of-care marker of treatment response. Analysis of cycle threshold values from automated nucleic acid amplification assays shows strong correlation with smear microscopy grade and culture time-to-positivity across diverse patient populations, including those with HIV co-infection. By establishing cycle threshold cut-offs that reliably rule out high bacillary burden, these findings support the use of real-time PCR metrics not only for diagnosis but also for monitoring therapy, potentially informing infection control decisions and shortening the interval to detect treatment failure.

Biomarker Identification and Treatment Monitoring in Pulmonary Tuberculosis publication trend

The graph below shows the total number of articles in biomarker identification and treatment monitoring in pulmonary tuberculosis across all publications each year (not limited to Nature Index journals).

Technical terms

Biomarker: A measurable indicator of biological state or response, used to assess disease activity, severity or therapy effect.

Cycle threshold (CT): The number of amplification cycles in a PCR assay required to detect target DNA above background, inversely related to pathogen load.

Molecular bacterial load assay (MBLA): A test that quantifies pathogen RNA to estimate viable bacterial count in a sample, useful for monitoring treatment clearance.

Culture conversion: The point during therapy when a patient’s sputum culture changes from positive to negative, indicating bacterial eradication.

Immunomics: The comprehensive analysis of immune molecules (such as cytokines) to understand host response and identify diagnostic or prognostic markers.

Target product profile: A document defining the desired characteristics and performance criteria for a diagnostic or therapeutic product in development.

References

1. Accuracy of the tuberculosis molecular bacterial load assay to diagnose and monitor response to anti-tuberculosis therapy: a longitudinal comparative study with standard-of-care smear microscopy, Xpert MTB/RIF Ultra, and culture in Uganda. The Lancet Microbe (2024).
2. Inflammatory immune profiles associated with disease severity in pulmonary tuberculosis patients with moderate to severe clinical TB or anemia. Frontiers in Immunology (2023).
3. Target product profiles: tests for tuberculosis treatment monitoring and optimization. Bulletin of the World Health Organization (2023).
4. Correlation of Xpert MTB/RIF with measures to assess Mycobacterium tuberculosis bacillary burden in high HIV burden areas of Southern Africa. Scientific Reports (2018).