Plasma proteomics for biomarker discovery in childhood tuberculosis

Andrea Fossati, Peter Wambi, Devan Jaganath, Roger Calderon, Robert Castro, Alexander Mohapatra, Justin McKetney, Juaneta Luiz, Rutuja Nerurkar, Esin Nkereuwem, Molly F. Franke, Zaynab Mousavian, Jeffrey M. Collins, George B. Sigal, Mark R. Segal, Beate Kampman, Eric Wobudeya, Adithya Cattamanchi, Joel D. Ernst, Heather J. Zar () and Danielle L. Swaney ()
Additional contact information
Andrea Fossati: J. David Gladstone Institutes
Peter Wambi: Kololo
Devan Jaganath: University of California San Francisco
Roger Calderon: Advanced Research and Health
Robert Castro: University of California San Francisco
Alexander Mohapatra: University of California San Francisco
Justin McKetney: J. David Gladstone Institutes
Juaneta Luiz: University of Cape Town
Rutuja Nerurkar: University of California San Francisco
Esin Nkereuwem: MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine
Molly F. Franke: Harvard Medical School
Zaynab Mousavian: Karolinska Institutet
Jeffrey M. Collins: Emory University School of Medicine
George B. Sigal: Meso Scale Diagnostics, LLC.
Mark R. Segal: University of California San Francisco
Beate Kampman: MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine
Eric Wobudeya: Kololo
Adithya Cattamanchi: University of California San Francisco
Joel D. Ernst: University of California San Francisco
Heather J. Zar: University of Cape Town
Danielle L. Swaney: J. David Gladstone Institutes

Nature Communications, 2025, vol. 16, issue 1, 1-11

Abstract: 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.

Date: 2025
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DOI: 10.1038/s41467-025-61515-5

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