The Study Of Exhaled Breath With Liver Failure Disease By Extractive Electrospray Ionization Mass Spectrometry

In recent years, exhaled breath detection with its characteristic of nondestructive, fast, convenient sampling, and the advantages of reflect the correlation of biological markers between diseases(such as lung cancer, breast cancer), metabolism and the condition of organ, which has gradually become a hotspot in clinical medicine research and analysis tests. Extractive electrospray ionization(EESI), as a new type of ambient ionization technique, has the advantages of simple operation, stable signal and tolerates extremely complex matrices. This paper brifly introduces the application of exhaled breath detection in various diseases, and emphatically discusses the application of EESI-MS in exhaled breath analysis of patients with liver failure.(1) Analysis of liver failure patients’ exhaled breath by EESI and high-resolution mass spectrometry.A novel platform of detection exhaled breath was constructed by a homemade EESI source coupling LTQ-Orbitrap-XL mass spectrometer. The exhaled breath data of liver failure patients and healthy volunteers were obtained and then analyzed by principal component analysis(PCA) to find the large differences biomarker. Elementary compositions(molecular formula) of target compounds was investigated by orbitrap mass spectrometer. Based on this method, the breath of liver failure patients was analyzed. Coupling PCA, the fingerprints can be differentiated the patient from the control group and validated by clustering analysis. We found the potential biomarkers associated with liver failure through the clinical and pathological finding.(2) EESI-MS detection and statistical analysis of multi-batch of exhaled breath metabolomics data of liver failure patients.In metabolomics studies, the number of samples should be enough to guarantee the reliability of data statistical analysis. The effective storage time of exhaled breath is short, and it is difficult to collect and detect a large number of breath samples in a short time. Combining multi batches of samples may obtain a large data, but usually there is a large variance between batches induced by ambient air varying. In this paper, the exhaled breath data of liver failure patients and healthy volunteers were obtained by high resolution extractive electrospray ionization mass spectrometry(EESI-MS) and then analyzed by multi-block partial least square(MB-PLS). The result were compared with traditional PLS method and showed its strength of removing the variance of batches for modeling. In addition, based on the variable importance in the projection(VIP) of MB-PLS to screening the data, the model cross-validation classification accuracy rate from 0.84 ± 0.06 increased to 0.96 ± 0.04, using the model can effectively distinguish liver failure patients and healthy volunteers.(3) Analysis of different stages of liver failure patients’ exhaled breath by enclosed EESI source.Patients with liver disease are mostly weak, especially the severe hepatitis patients, using active expiratory acquisition tend to increase the burden to the patient’s body, and even cause discomfort. Therefore it produced a passive exhalation device to suitable for different stages of liver disease. Meanwhile, because of the exhaled breath are easily influenced by the environment, we use an enclosed extractive electrospray ionization source to detection exhaled breath.By the partial least squares(PLS) analysis, we found that chronic hepatitis b patients and chronic severe hepatitis b patients also have a good distinction with healthy volunteers. Through the model variables VIP values selected 11 and 18 variable respectively, which are the biggest differences. Indicating that with the aggravation of liver disease, the patient exhaled breath composition becomes complicated, which is consistent with changes in the course of the patient. The light and heavy liver disease could also achieve better distinction through PLS analysis. This method is not only to provide a new method for the diagnosis and treatment evaluation of rehabilitation of patients with liver disease, but also provides a new way for the development of personalized medicine.