Abstract
The lack of effective differential diagnostic methods for active tuberculosis (TB) and latent infection (LTBI) is still an obstacle for TB control. Furthermore, the molecular mechanism behind the progression from LTBI to active TB has been not elucidated. Therefore, we performed label-free quantitative proteomics to identify plasma biomarkers for discriminating pulmonary TB (PTB) from LTBI. A total of 31 overlapping proteins with significant difference in expression level were identified in PTB patients (n = 15), compared with LTBI individuals (n = 15) and healthy controls (HCs, n = 15). Eight differentially expressed proteins were verified using western blot analysis, which was 100% consistent with the proteomics results. Statistically significant differences of six proteins were further validated in the PTB group compared with the LTBI and HC groups in the training set (n = 240), using ELISA. Classification and regression tree (CART) analysis was employed to determine the ideal protein combination for discriminating PTB from LTBI and HC. A diagnostic model consisting of alpha-1-antichymotrypsin (ACT), alpha-1-acid glycoprotein 1 (AGP1), and E-cadherin (CDH1) was established and presented a sensitivity of 81.2% (69/85) and a specificity of 95.2% (80/84) in discriminating PTB from LTBI, and a sensitivity of 81.2% (69/85) and a specificity of 90.1% (64/81) in discriminating PTB from HCs. Additional validation was performed by evaluating the diagnostic model in blind testing set (n = 113), which yielded a sensitivity of 75.0% (21/28) and specificity of 96.1% (25/26) in PTB vs. LTBI, 75.0% (21/28) and 92.3% (24/26) in PTB vs. HCs, and 75.0% (21/28) and 81.8% (27/33) in PTB vs. lung cancer (LC), respectively. This study obtained the plasma proteomic profiles of different M.TB infection statuses, which contribute to a better understanding of the pathogenesis involved in the transition from latent infection to TB activation and provide new potential diagnostic biomarkers for distinguishing PTB and LTBI.
Highlights
Tuberculosis (TB) is a major global infectious disease causing high mortality and morbidity, with 1.7 million deaths and 10.4 million new cases worldwide in 2016
A total of 398 participants were enrolled in this study, including 128 pulmonary TB (PTB) patients, 125 latent tuberculosis infection (LTBI) individuals, 112 healthy controls (HCs), and 33 lung cancer (LC) patients
An additional 85 PTB patients, 84 LTBI individuals, and 71 HCs were included in the training set for candidate biomarker validation and diagnostic model construction, while the remaining 28 PTB patients, 26 LTBI individuals, 26 HCs, and 33 LC patients were included in the blind testing set for diagnostic model validation
Summary
Tuberculosis (TB) is a major global infectious disease causing high mortality and morbidity, with 1.7 million deaths and 10.4 million new cases worldwide in 2016. Besides the active TB patients, about one-third of the world’s population is infected with M.TB, but remains asymptomatic, which is known as LTBI. M.TB culture is the gold standard method for TB diagnosis but require 4–8 weeks for results (Brodie and Schluger, 2005). The interferon gamma release assays (IGRAs) are a promising method to diagnose M.TB infection but cannot distinguish active TB from LTBI, especially in the suspected TB patients with clinical respiratory symptoms (Sester et al, 2011). Aforementioned methods do not satisfy the requirement to definitively diagnose patients with early-stage active pulmonary TB. A panel of measured biomarkers with high diagnostic accuracy is of paramount importance for global TB control
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