Integrated plasma proteomics identifies tuberculosis-specific diagnostic biomarkers

Hannah F. Schiff, Naomi Walker, Cesar Ugarte-Gil, Marc Tebruegge, Antigoni Manousopoulou, Spiros D. Garbis, Salah Mansour, Pak Ho Wong, Gabrielle Rockett, Paolo Piazza, Mahesan Niranjan, Andres F. Vallejo, Christopher H. Woelk, Robert J. Wilkinson, Liku B. Tezera, Diana Garay-Baquero, Paul Elkington

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Novel biomarkers to identify infectious patients transmitting Mycobacterium tuberculosis are urgently needed to control the global tuberculosis (TB) pandemic. We hypothesized that proteins released into the plasma in active pulmonary TB are clinically useful biomarkers to distinguish TB cases from healthy individuals and patients with other respiratory infections. We applied a highly sensitive non-depletion tandem mass spectrometry discovery approach to investigate plasma protein expression in pulmonary TB cases compared to healthy controls in South African and Peruvian cohorts. Bioinformatic analysis using linear modelling and network correlation analyses identified 118 differentially expressed proteins, significant through three complementary analytical pipelines. Candidate biomarkers were subsequently analysed in two validation cohorts of differing ethnicity using antibody-based proximity extension assays. TB-specific host biomarkers were confirmed. A six-protein diagnostic panel, comprising FETUB, FCGR3B, LRG1, SELL, CD14 and ADA2, differentiated patients with pulmonary TB from healthy controls and patients with other respiratory infections with high sensitivity and specificity in both cohorts. This biomarker panel exceeds the World Health Organisation Target Product Profile specificity criteria for a triage test for TB. The new biomarkers have potential for further development as near-patient TB screening assays, thereby helping to close the case-detection gap that fuels the global pandemic.

Original languageEnglish
Article numbere173273
Pages (from-to)e173273
JournalJCI Insight
Volume9
Issue number8
Early online date21 Mar 2024
DOIs
Publication statusPublished - 21 Mar 2024

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