Exploring serological classification tree model of active pulmonary tuberculosis by magnetic beads pretreatment and MALDI-TOF MS analysis.

Pulmonary tuberculosis (TB) is an infectious disease disturbing status of public health, and accurate diagnosis of TB would effectively help control the disturbance. Our study tried to establish a classification tree model that distinguished active TB from non-TB individuals. We used matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) combined with weak cationic exchange (WCX) magnetic beads to analyse 178 serum samples containing 75 patients with active TB and 103 non-TB individuals (43 patients with common pulmonary diseases and 60 healthy controls). Samples were randomly divided into a training set and a test set. Statistical softwares were applied to construct this model. An amount of 48 differential expressed peaks (P < 0.05) were identified by the training set, and our model was set up by three of them, m/z 7626, 8561 and 8608. This model can discriminate patients with active TB from patients with non-TB with a sensitivity of 98.3% and a specificity of 84.4%. The test set was used to verify the performance, which demonstrated good sensitivity and specificity: 85.7% and 83.3%, respectively. Differential expressed peaks between smear-positive and smear-negative active TB also have been analysed. It came out that m/z 8561 and 8608 not only acted as vital factors in the pathogenesis of active TB but also played an important role in regulating different active TB status. In conclusion, MALDI-TOF MS combined with WCX magnetic beads was a powerful technology for constructing classification tree model, and the model we built could serve as a potential diagnostic tool for active TB.