Development of a diagnosis model for active pulmonary tuberculosis using mass spectrometry and pro-tein chip / 中华微生物学和免疫学杂志

ABSTRACT

Objective To develop a diagnosis model for active pulmonary tuberculosis. Methods The proteomic fingerprinting of 264 sera from active tuberculosis patients and controls were analyzed using the surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) and protein-chip technology. The peaks were detected and filtrated by Ciphergen PrnteinChip(R) Software (version 3.1.1). Using the Biomarker Pattern 5.0 software, a diagnostic model was developed for diagnosis of active tuberculosis. Re-sults Fifty protein peaks were significantly different between the patients with active pulmonary tuberculosis and the 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 differenti-ated the patients with active pulmonary tuberculosis from the controls with a sensitivity of 83.0%, and a speci-ficity 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 pa-tients 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%. Conclusion It might be a new diagnostic test for the de-tection of sera from the patients with active pulmonary tuberculosis using SELDI-TOF-MS and protein chip.