Comprehensive plasma proteomic profiling reveals biomarkers for active tuberculosis
Diana J. Garay-Baquero, … , Spiros D. Garbis, Paul Elkington
Diana J. Garay-Baquero, … , Spiros D. Garbis, Paul Elkington
Published August 11, 2020
Citation Information: JCI Insight. 2020;5(18):e137427. https://doi.org/10.1172/jci.insight.137427.
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Clinical Medicine Infectious disease

Comprehensive plasma proteomic profiling reveals biomarkers for active tuberculosis

Abstract

BACKGROUND Tuberculosis (TB) kills more people than any other infection, and new diagnostic tests to identify active cases are required. We aimed to discover and verify novel markers for TB in nondepleted plasma.METHODS We applied an optimized quantitative proteomics discovery methodology based on multidimensional and orthogonal liquid chromatographic separation combined with high-resolution mass spectrometry to study nondepleted plasma of 11 patients with active TB compared with 10 healthy controls. Prioritized candidates were verified in independent UK (n = 118) and South African cohorts (n = 203).RESULTS We generated the most comprehensive TB plasma proteome to date, profiling 5022 proteins spanning 11 orders-of-magnitude concentration range with diverse biochemical and molecular properties. We analyzed the predominantly low–molecular weight subproteome, identifying 46 proteins with significantly increased and 90 with decreased abundance (peptide FDR ≤ 1%, q ≤ 0.05). Verification was performed for novel candidate biomarkers (CFHR5, ILF2) in 2 independent cohorts. Receiver operating characteristics analyses using a 5-protein panel (CFHR5, LRG1, CRP, LBP, and SAA1) exhibited discriminatory power in distinguishing TB from other respiratory diseases (AUC = 0.81).CONCLUSION We report the most comprehensive TB plasma proteome to date, identifying novel markers with verification in 2 independent cohorts, leading to a 5-protein biosignature with potential to improve TB diagnosis. With further development, these biomarkers have potential as a diagnostic triage test.FUNDING Colciencias, Medical Research Council, Innovate UK, NIHR, Academy of Medical Sciences, Program for Advanced Research Capacities for AIDS, Wellcome Centre for Infectious Diseases Research.

Authors

Diana J. Garay-Baquero, Cory H. White, Naomi F. Walker, Marc Tebruegge, Hannah F. Schiff, Cesar Ugarte-Gil, Stephen Morris-Jones, Ben G. Marshall, Antigoni Manousopoulou, John Adamson, Andres F. Vallejo, Magdalena K. Bielecka, Robert J. Wilkinson, Liku B. Tezera, Christopher H. Woelk, Spiros D. Garbis, Paul Elkington

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Figure 7

Combination of 5 protein markers discriminates patients with TB in a UK-based cohort.

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Combination of 5 protein markers discriminates patients with TB in a UK-...
ROC curves were generated using SPSS v.25, for individual proteins (CFHR5, LBP, SAA, CRP, and ILF2) and after binary logistic regression for combined analytes. AUC was estimated under nonparametric assumption. TB was set as the positive test outcome and the test direction such that larger test result indicates a more positive test. ROC curve for TB infection versus HCs shows good discrimination, with the multiplex panel most discriminatory (A), while the ROC curve for TB infection versus ORDs shows individual analytes are not differentiating, but a combined multiplex panel generates an AUC of 0.813 (B).