Table_2_Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection.DOCX

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.

活动性肺结核（active tuberculosis, TB）与潜伏性结核感染（latent tuberculosis infection, LTBI）缺乏有效的鉴别诊断手段，仍是结核病防控的核心阻碍之一。此外，从潜伏性结核感染进展为活动性肺结核的分子机制尚未阐明。为此，本研究采用无标记定量蛋白质组学技术，筛选可用于区分肺结核（pulmonary TB, PTB）与潜伏性结核感染的血浆生物标志物。相较于15名潜伏性结核感染者、15名健康对照（healthy controls, HCs），本研究在15名肺结核患者中鉴定出31个表达水平存在显著差异的重叠蛋白。通过蛋白质印迹（western blot）验证了8个差异表达蛋白，其结果与蛋白质组学分析完全一致。在训练集（n=240）中，采用酶联免疫吸附实验（enzyme-linked immunosorbent assay, ELISA）进一步验证：6个蛋白在肺结核组与潜伏性结核感染组、健康对照组间的表达差异具有统计学意义。本研究采用分类与回归树（classification and regression tree, CART）分析，确定了区分肺结核与潜伏性结核感染及健康对照的最优蛋白组合。最终构建了由α1-抗胰凝乳蛋白酶（alpha-1-antichymotrypsin, ACT）、α1-酸性糖蛋白1（alpha-1-acid glycoprotein 1, AGP1）与E-钙粘蛋白（E-cadherin, CDH1）组成的诊断模型。该模型在区分肺结核与潜伏性结核感染时，灵敏度为81.2%（69/85），特异度为95.2%（80/84）；在区分肺结核与健康对照时，灵敏度为81.2%（69/85），特异度为90.1%（64/81）。额外在盲法测试集（n=113）中对该诊断模型进行验证，结果显示：在肺结核vs潜伏性结核感染组中，灵敏度为75.0%（21/28），特异度为96.1%（25/26）；在肺结核vs健康对照组中，灵敏度为75.0%（21/28），特异度为92.3%（24/26）；在肺结核vs肺癌（lung cancer, LC）组中，灵敏度为75.0%（21/28），特异度为81.8%（27/33）。本研究获取了不同结核分枝杆菌感染状态下的血浆蛋白质组学特征，有助于深入理解潜伏性结核感染向活动性肺结核转化的发病机制，并为区分肺结核与潜伏性结核感染提供了新的潜在诊断生物标志物。