Comprehensive plasma proteomic profiling reveals biomarkers for active tuberculosis

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

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.

Additional Information

© 2020, Garay-Baquero et al. This is an open access article published under the terms of the Creative Commons Attribution 4.0 International License. Submitted: February 27, 2020; Accepted: July 31, 2020; Published: September 17, 2020. This work was supported by Colciencias Scholarship 6171, Government of Colombia, Medical Research Council Global Challenges Research Fund MR/P023754/1, Confidence in Concept MC_PC16059 and MR/R001065/1, and the Global Network for Anti-Microbial Resistance and Infection Prevention funding program. NFW was supported by Wellcome Trust (094000) NIHR, Starter Grant for Clinical Lecturers (Academy of Medical Sciences UK, Wellcome, Medical Research Council UK, British Heart Foundation, Arthritis Research UK, Royal College of Physicians, and Diabetes UK), and British Infection Association. CUG received support from the Program for Advanced Research Capacities for AIDS in Peru at Universidad Peruana Cayetano Heredia (D43TW00976301) from Fogarty International Center at the US NIH. We are grateful to the Wellcome Centre for Infectious Diseases Research in Africa clinical research team and to the participants, staff, and patients of Ubuntu Clinic and the Western Cape Government Department of Health. PE is grateful for the support of the Southampton NIHR Biomedical Research Centre. The MIMIC study, MT, and SMJ were supported by a grant from the UK Technology Strategy Board/Innovate UK (grant 101556). MT was also supported by a Clinical Lectureship by the NIHR UK. Author Contributions: DJGB was involved in the study design, performed the optimization of the proteomic method and conducted the plasma proteome profiling, analyzed and integrated the data and the verification experiments, and wrote the majority of the manuscript. CH White wrote the R scripts used to normalize raw peptide intensities, calculate protein expressions, and perform limma analysis. NFW recruited the South African cohort and provided clinical annotation. MT recruited the MIMIC cohort and provided clinical annotation. HFS was involved in the experiments of verification using ELISA and Luminex. CUG recruited the Peruvian clinical cohort and provided clinical annotation. AM and JA provided expertise in the plasma proteomic protocol. AFV provided expert insight on the bioinformatic analysis and the R scripts for WGCNA and ComBat. MKB was involved in the validation experiments. RJW, SMJ, and BGM assisted with recruitment of patients to the cohorts. LBT assisted in the Luminex analysis. CH Woelk was involved in the study design and provided expertise on the bioinformatic pipeline design. SDG was involved in the study design, provided expertise and advice on the plasma proteomics method, and contributed to the manuscript writing process. PE was involved with the study design, secured funding, and contributed to manuscript writing and editing. The authors have declared that no conflict of interest exists.

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