Identification of eight-protein biosignature for diagnosis of tuberculosis. Issue 7 (22nd March 2020)

• Record Type: Journal Article
• Authors: Yang, Qianting; Chen, Qi; Zhang, Mingxia; Cai, Yi; Yang, Fan; Zhang, Jieyun; Deng, Guofang; Ye, Taosheng; Deng, Qunyi; Li, Guobao; Zhang, Huihua; Yi, Yuhua; Huang, Ruo-Pan; Chen, Xinchun
• Is Part Of: Thorax. Volume 75:Issue 7(2020)
• Page Start: 576
• Page End: 583
• Publication Date: 2020-03-22
• Subjects: Mycobacterium tuberculosis -- antibody array -- protein array -- diagnosis -- biomarker; Chest -- Diseases -- Periodicals; Thorax; Chest -- Diseases; Periodicals; Periodicals; 617.54
• DOI: 10.1136/thoraxjnl-2018-213021
• Languages: English
• ISSNs: 0040-6376

Abstract

Abstract : Background: Biomarker-based tests for diagnosing TB currently rely on detecting Mycobacterium tuberculosis (Mtb) antigen-specific cellular responses. While this approach can detect Mtb infection, it is not efficient in diagnosing TB, especially for patients who lack aetiological evidence of the disease. Methods: We prospectively enrolled three cohorts for our study for a total of 630 subjects, including 160 individuals to screen protein biomarkers of TB, 368 individuals to establish and test the predictive model and 102 individuals for biomarker validation. Whole blood cultures were stimulated with pooled Mtb-peptides or mitogen, and 640 proteins within the culture supernatant were analysed simultaneously using an antibody-based array. Sixteen candidate biomarkers of TB identified during screening were then developed into a custom multiplexed antibody array for biomarker validation. Results: A two-round screening strategy identified eight-protein biomarkers of TB: I-TAC, I-309, MIG, Granulysin, FAP, MEP1B, Furin and LYVE-1. The sensitivity and specificity of the eight-protein biosignature in diagnosing TB were determined for the training (n=276), test (n=92) and prediction (n=102) cohorts. The training cohort had a 100% specificity (95% CI 98% to 100%) and 100% sensitivity (95% CI 96% to 100%) using a random forest algorithm approach by cross-validation. In the test cohort, the specificity and sensitivity were 83% (95% CI 71% to 91%) and 76% (95% CI 56% to 90%), respectively. In the prediction cohort, the specificity was 84% (95% CI 74% to 92%) and the sensitivity was 75% (95% CI 57% to 89%). Conclusions: An eight-protein biosignature to diagnose TB in a high-burden TB clinical setting was identified.