Advancing personalized medicine for tuberculosis through the application of immune profiling

Vo Thuy Anh Thu, Ly Da Dat, Rannissa Puspita Jayanti, Hoang Kim Tu Trinh, Tran Minh Hung, Yong Soon Cho, Nguyen Phuoc Long*, Jae Gook Shin*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

6 Scopus citations

Abstract

While early and precise diagnosis is the key to eliminating tuberculosis (TB), conventional methods using culture conversion or sputum smear microscopy have failed to meet demand. This is especially true in high-epidemic developing countries and during pandemic-associated social restrictions. Suboptimal biomarkers have restricted the improvement of TB management and eradication strategies. Therefore, the research and development of new affordable and accessible methods are required. Following the emergence of many high-throughput quantification TB studies, immunomics has the advantages of directly targeting responsive immune molecules and significantly simplifying workloads. In particular, immune profiling has been demonstrated to be a versatile tool that potentially unlocks many options for application in TB management. Herein, we review the current approaches for TB control with regard to the potentials and limitations of immunomics. Multiple directions are also proposed to hopefully unleash immunomics’ potential in TB research, not least in revealing representative immune biomarkers to correctly diagnose TB. The immune profiles of patients can be valuable covariates for model-informed precision dosing-based treatment monitoring, prediction of outcome, and the optimal dose prediction of anti-TB drugs.

Original languageEnglish
Article number1108155
JournalFrontiers in Cellular and Infection Microbiology
Volume13
DOIs
StatePublished - 10 02 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
Copyright © 2023 Thu, Dat, Jayanti, Trinh, Hung, Cho, Long and Shin.

Keywords

  • biomarkers
  • immunomics
  • model-informed precision dosing
  • multi-omics
  • personalized medicine
  • tuberculosis

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