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Fossati A, Wambi P, Jaganath D, Calderon R, Castro R, Mohapatra A, McKetney J, Luiz J, Nerurkar R, Nkereuwem E, Franke MF, Mousavian Z, Collins JM, Sigal GB, Segal MR, Kampman B, Wobudeya E, Cattamanchi A, Ernst JD, Zar HJ, Swaney DL, COMBO Study Consortium
Nat Commun 16 (1) 6657 [2025-07-19; online 2025-07-19]
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.
PubMed 40683862
DOI 10.1038/s41467-025-61515-5
Crossref 10.1038/s41467-025-61515-5
pmc: PMC12276249
pii: 10.1038/s41467-025-61515-5