Plasma proteomics for biomarker discovery in childhood tuberculosis

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.

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Publication Details

Journal
Nature Communications
Published
2025-07-19
DOI
https://doi.org/10.1038/s41467-025-61515-5
Citations
9
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
7.25

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article

Plasma proteomics for biomarker discovery in childhood tuberculosis

Jeffrey Michael Collins, Andrea Fossati, Mark R. Segal, Esin Nkereuwem et al.
9 citations
Nature Communications
vaccines and immunoinformatics approaches
7.25
article

Plasma proteomics for biomarker discovery in childhood tuberculosis

Jeffrey Michael Collins, Andrea Fossati, Mark R. Segal, Esin Nkereuwem, Zaynab Mousavian, Juaneta Luiz, Devan Jaganath, Justin McKetney, Peter Wambi, Beate Kampmann, Robert Castro, Adithya Cattamanchi, George B. Sigal, Róger Calderón, Molly Forrest Franke, Heather Joy Zar, Danielle L. Swaney, Eric Wobudeya, J. Ernst, Rutuja Nerurkar, Alexander Mohapatra
article en
9 citations

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.

Nature CommunicationsVol. 16(1)
QB3 (US), South African Medical Research Council (ZA), Gladstone Institutes (US), Harvard University (US), Emory University (US), University of California, San Francisco (US), University of California, Irvine (US), Dora Nginza Hospital (ZA), University of California System (US), Karolinska Institutet (SE), Malaria Consortium (UG), Quantitative BioSciences (US), MRC Unit the Gambia (GM), Global Brain Health Institute (US), Harvard Global Health Institute (US), Meso Scale Discovery (United States) (US), Charité - Universitätsmedizin Berlin (DE)
UK Research and Innovation, South African Medical Research Council, National Institutes of Health, Medical Research Council
Good health and well-being
Openalex Percentile: Top 2%
vaccines and immunoinformatics approaches
7.25
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