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May 6, 2026Pathogens1 citationsOpen Access

RISK6  as a Translational Host Transcriptomic Signature for Tuberculosis Diagnosis, Treatment Monitoring, and Risk Stratification 

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CMChrispian MamudiPPurnamawatiPAPanca Andana

Key Points

  • This review evaluates the RISK6 transcriptomic signature as a potential biomarker for diagnosing and monitoring tuberculosis and stratifying patient risk.
  • Clinically oriented synthesis of existing evidence on the RISK6 signature.
  • Assessment of diagnostic performance and applicability across tuberculosis disease spectrum.
  • Examination of limitations in multidrug-resistant tuberculosis populations.
  • RISK6 shows promising diagnostic performance with context-dependent variability.
  • It functions better within integrated frameworks including clinical data.
  • Limited evidence highlights its challenges as a standalone biomarker.

Abstract

Tuberculosis (TB) remains a leading cause of infectious mortality worldwide, reflecting persistent gaps in diagnosis, risk stratification, and treatment monitoring. Host RNA transcriptomic signatures have emerged as promising tools for capturing dynamic immune responses across the TB disease spectrum. Among these, the six-gene RISK6 signature has attracted attention due to its parsimonious design and potential for clinical translation. This review provides a clinically oriented synthesis of current evidence on host transcriptomic biomarkers, with a particular focus on the application of RISK6 in diagnosis, prediction of disease progression, and treatment monitoring. Available data suggest that RISK6 demonstrates promising but context-dependent diagnostic performance and represents a versatile host-response biomarker across multiple clinical applications. However, variability across populations and the limited evidence in multidrug-resistant TB remain important constraints. In practice, RISK6 is unlikely to function optimally as a standalone biomarker. Its clinical value appears greater when interpreted within integrated frameworks that combine transcriptomic, microbiological, and clinical data. Further validation in diverse populations and real-world settings will be essential to support meaningful clinical implementation.

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Cite This Study

Mamudi et al. (2026) studied this question.

synapsesocial.com/papers/69fadaab03f892aec9b1e608https://doi.org/10.3390/pathogens15050489
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