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Updated: Sep 14, 2025
Preparation of Mycobacterium Tuberculosis Culture Filtrate to Understand TB Pathogenesis
Published on: March 28, 2025
Plasma proteomics for biomarker discovery in childhood tuberculosis
Andrea Fossati1,2,3, Peter Wambi4, Devan Jaganath5,6
1J. David Gladstone Institutes, San Francisco, CA, USA.
Insights
Diagnosing pediatric tuberculosis (TB) is challenging. This study identified a novel blood protein signature to accurately detect TB in children, improving early diagnosis and treatment.
Area of Science:
- Biochemistry
- Immunology
- Pediatrics
Background:
- Tuberculosis (TB) remains a leading cause of childhood mortality, largely due to diagnostic delays.
- Current diagnostic methods for pediatric TB exhibit limited accuracy, necessitating new approaches.
- Identifying non-sputum biomarkers is crucial for improving pediatric TB diagnosis.
Purpose of the Study:
- To discover novel plasma protein biosignatures for diagnosing TB in children.
- To evaluate the diagnostic performance of these biosignatures against established accuracy thresholds.
- To understand the host response in pediatric TB using proteomic analysis.
Main Methods:
- High-throughput proteomics was used to analyze plasma samples from 511 children across four countries.
- Machine learning algorithms were employed to identify protein panels distinguishing TB status.
- Children with and without HIV were included to account for co-infection.
Main Results:
- Four distinct biosignatures, each comprising 3-6 proteins, were identified.
- These biosignatures achieved high diagnostic accuracy, with AUCs ranging from 0.87 to 0.88.
- All derived biosignatures met the World Health Organization's target product profile for TB screening tests.
Conclusions:
- A novel, non-sputum-based protein biosignature can accurately detect TB in children.
- This finding offers a promising tool to expedite TB diagnosis and improve patient outcomes.
- The study provides valuable insights into the proteomic landscape of pediatric TB.
Abstract:
Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of TB as a leading cause of death in children. Current TB diagnostic assays have poor performance in children, thus a global priority is the identification of novel non-sputum-based TB biomarkers. Here we use high-throughput proteomics to measure the plasma proteome for 511 children, with and without HIV, and across 4 countries, to distinguish TB status using standardized definitions. By employing a machine learning approach, we derive four parsimonious biosignatures encompassing 3 to 6 proteins that achieve AUCs of 0.87-0.88 and which all reach the minimum WHO target product profile accuracy thresholds for a TB screening test. This work provides insights into the unique host response in pediatric TB disease, as well as a non-sputum biosignature that could reduce delays in TB diagnosis and improve the detection and management of TB in children worldwide.
