{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Fossati A"],"funding":["NIAID NIH HHS","NHLBI NIH HHS"],"pubmed_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, and identifying novel non-sputum-based TB biomarkers to improve pediatric TB diagnosis is a global priority. We sought to develop a plasma biosignature for TB by probing the plasma proteome of 511 children stratified by TB diagnostic classification and HIV status from sites in four low- and middle-income countries, using high-throughput data-independent acquisition mass-spectrometry (DIA-PASEF-MS). We identified 47 proteins differentially regulated (BH adjusted p-values < 1%) between children with microbiologically confirmed TB and children with non-TB respiratory diseases (Unlikely TB). We further employed machine learning to derive three parsimonious biosignatures encompassing 4, 5, or 6 proteins that achieved AUCs of 0.86-0.88 all of which exceeded the minimum WHO target product profile accuracy thresholds for a TB screening test (70% specificity at 90% sensitivity, PPV 0.65-0.74, NPV 0.92-0.95). 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 detection and management of TB in children worldwide."],"journal":["medRxiv : the preprint server for health sciences"],"pagination":["2024.12.05.24318340"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11643232"],"repository":["biostudies-literature"],"pubmed_title":["Plasma proteomics for novel biomarker discovery in childhood tuberculosis."],"pmcid":["PMC11643232"],"funding_grant_id":["P30 AI168386","K23 HL153581","R01 AI152161","R01 AI175312"],"pubmed_authors":["Mohapatra A","Fossati A","McKetney J","Wobudeya E","Sigal GB","Franke MF","Mousavian Z","Segal MR","Wambi P","Cattamanchi A","Zar HJ","Castro R","Ernst JD","Nerurkar R","Kampman B","Nkereuwem E","Collins JM","Luiz J","Swaney DL","Jaganath D","Calderon R"],"additional_accession":[]},"is_claimable":false,"name":"Plasma proteomics for novel biomarker discovery in childhood tuberculosis.","description":"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, and identifying novel non-sputum-based TB biomarkers to improve pediatric TB diagnosis is a global priority. We sought to develop a plasma biosignature for TB by probing the plasma proteome of 511 children stratified by TB diagnostic classification and HIV status from sites in four low- and middle-income countries, using high-throughput data-independent acquisition mass-spectrometry (DIA-PASEF-MS). We identified 47 proteins differentially regulated (BH adjusted p-values < 1%) between children with microbiologically confirmed TB and children with non-TB respiratory diseases (Unlikely TB). We further employed machine learning to derive three parsimonious biosignatures encompassing 4, 5, or 6 proteins that achieved AUCs of 0.86-0.88 all of which exceeded the minimum WHO target product profile accuracy thresholds for a TB screening test (70% specificity at 90% sensitivity, PPV 0.65-0.74, NPV 0.92-0.95). 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 detection and management of TB in children worldwide.","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Mar","modification":"2025-08-14T03:05:07.101Z","creation":"2025-04-06T17:50:17.769Z"},"accession":"S-EPMC11643232","cross_references":{"pubmed":["39677468"],"doi":["10.1101/2024.12.05.24318340"]}}