Identification Of Biomarker And Development Of A Diagnosis Model For Active Tuberculosis Using Proteomics Techniques

Objective:To identify the biomarker and develop a diagnostic model for active tuberculosis(TB) using proteomics techniques,and to study the expression of biomarker in the sera from the patients with pulmonary TB and extrapulmonary TB.Method:The proteomic fingerprinting of 346 human sera as follow were analyzed using the surface-enhanced laser desorption ionization time of flight mass spectrometry(SELDI/TOF-MS) and protein-chip technology:129 cases with active pulmonary TB,69 cases with non-TB respiratory diseases,57 cases with tuberculous pleuritis,4 cases with non-TB pleuritis,19 cases with tuberculous meningitis,2 cases with non-TB meningitis,and 66 healthy controls. The peaks were detected and filtrated by Ciphergen Protein Chip(?) Software (version 3.1.1).Using the Biomarker Pattern 5.0 software,a diagnostic model was developed for diagnosis of active tuberculosis.The potential biomarker was separated,purified,analyzed,and identified using reverse phase-high performance liquid chromotography(RP-HPLC),Matrix assisted laser desorption ionisation time-of-flight mass spectrometry(MALDI-TOF-MS) and linear ion chromotograph mass spectrometry/mass spectrometry(LC-MS/MS).Result:(1) Fifty protein peaks in the sera were significantly different between 129 patients with active pulmonary tuberculosis and 135 controls with overlapping clinical features(P＜0.01).Five protein peaks at 4360,3311,8160, 5723,15173 m/z were chosen for the system classifier and the development of diagnosis model 1.The model differentiated the patients with active pulmonary tuberculosis from the controls with a sensitivity of 83.0%,and a specificity of 89.6%.The diagnostic accuracy was up to 86.4%.Three protein peaks at 5643, 4486,4360 m/z were chosen for the system classifier and the development of diagnosis model 2.The model differentiated the patients with active pulmonary tuberculosis from the controls with a sensitivity of 96.9%,and a specificity of 97.8%.The diagnostic accuracy was up to 97.3%.(2) The discrepant protein peak at m/z 5643 was highly expressed in 62.8%(81/129) sera from active TB patients, and lowly expressed in 71.9%(97/135) sera from other respiratory diseases and healthy controls.Therefore,protein at m/z 5643 was screened as a potential biomarker for active TB,separated,purified by RP-HPLC,identified using MALDI-TOF-MS and LC-MS/MS.The potential biomarker was comfirmed as orosomucoid,which is also named as alpha-1-acid glycoprotein.(3) Fifty-two protein peaks in the sera were significantly different between 57 patients with tuberculous pleuritis and 70 controls(P＜0.01).The protein peak at m/z 5643 was highly expressed in 47.4%(27/57) sera from the patients with tuberculous pleuritis,and lowly expressed in 4 sera from the patients with non-TB pleuritis.(4) Twenty-five protein peaks in the sera were significantly different between 19 patients with tuberculous meningitis and 68 controls(P＜0.05).The protein peak at m/z 5643 was highly expressed in 73.7%(14/19) sera from the patients with tuberculous meningitis,and lowly expressed in 2 sera from the patients with non-TB meningitis.Conclusion:(1) The mass spectrometry and protein chip technology need small quantity of samples,can detect directly serum samples.It might be used as a new method for the diagnosis of the active TB.(2) The proteomic technology can effectively screen,isolate,purified,and identified the TB-specific biomarkers.(3) The alpha-1-acid glycoprotein isoforms or the differences in the glycosylation of alpha-1-acid glycoprotein from TB might be used to diagnose the active TB.