Non-targeted Metabolomics To Study The Tongue Coating And Saliva Of The Patients With Chronic Gastritis

Chronic gastritis(CG)is a chronic inflammation of the gastric mucosal,which is characterized by the infiltration of inflammatory cells and has a high incidence in China.The active period of CG is an important precancerous period of gastric cancer,which is one of the most frequently occurring cancers in the world,but the pathogenesis of CG is not clear.In terms of current clinical practice,the main method of diagnosis for CG relies on gastroscopy,biopsy and pathological examination,which are generally considered invasive,expensive and time-consuming for the patients.Therefore,it is important to find other diagnostic biomarkers that can be detected with a simple,non-invasive and convenient method and to more thoroughly clarifying the pathogenesis of CG.Metabonomics is a rapid development of technology in recent years,which has been widely used in the early diagnosis,mechanism research and treatment of diseases.Tongue diagnosis,as a diagnostic method is through the observation of changes of tongue body and tongue coating to understand the changes of physiological function and pathologies.In the TCM clinic,through the changes in the color,thickness,and moistness of tongue coating,the development of the disease can be objectively reflected.Saliva is one of the body's important body fluids.Since the saliva detection is simple,convenient and inexpensive,it is considered to have a good prospect of the clinical diagnosis.According to the theory of traditional Chinese medicine,“Zai Pi Wei Xian” means that saliva can reflect the state of the(Pi)spleen and(Wei)stomach.In this study,a UHPLC-QTOF-MS-based metabolomics analysis method was performed to search for differential metabolites in the tongue coating and saliva of patients with chronic gastritis and to further discover the molecular mechanisms of chronic gastritis and potential biomarkers that aid diagnosis of chronic gastritis.Part one Non-targeted Metabolomics to Study the Tongue Coating of the Patients with SCGObjective: To establish a UHPLC-QTOF-MS-based metabolomics analysis method to search for differential metabolites in the tongue coating of patients with SCG and to further discover the molecular mechanisms of chronic gastritis and potential biomarkers that aid diagnosis of chronic gastritis.Methods: According to the formulated selection method,thirty patients with SCG(male 13 cases,female 17 cases)and thirty healthy person(male 12 cases,female 18 cases)were selected.Appropriate amount of tongue coating was scraped and lyophilized.90% acetonitrile was added into the lyophilized powder to get the mixture which was broken to extract the endogenous components.The handled sample was analyzed by UHPLC-QTOF-MS method using ACQUITY UPLC? BEH HILIC(2.1×100 mm,1.7 ?m)column and ACQUITY UPLC? HSS T3(2.1×100 mm,1.8 ?m)column with positive and negative ion separately scanning modes.The raw data was imported into Progenesis QI to perform peak alignment,deconvolution and selection of adducts to get the handled dataset.The obtained datasets were tested by Student's T test to obtain P value and OPLS-DA model was established to obtain VIP value.Components that both satisfying P<0.05 and VIP value>1 were considered as differential compounds.Differential compounds were identifited by matching secondary spectrum with online database(HMDB,METLIN)to obtain the potential biomarkers.The Metabo Analyst 4.0 software was performed to enrich the markers and analyze the metabolic pathway of the markers.The ROC curve analysis was performed to find potential diagnostic biomarkers.Results: In the four analysis models of this study,4212,3820,3628 and 1949 peaks were obtained from the original data preprocessing.130,229,113 and 92 differential compounds associated with SCG were obtained by multivariate statistical analysis and then a total of 37 potential biomarkers were obtained by matching databases.Some of the metabolic pathways were found to be associated with SCG by using online software,including: purine metabolism,sphingolipid metabolism,energy metabolism,amino acid metabolism(valine,leucine and isoleucine metabolic pathways),aminoacyl-t RNA biosynthesis and caffeine metabolism.Inosine,oleamide,adenosine,N-acetyl-glucosamine and xanthine were found to have good accuracy in predicting chronic gastritis by ROC curve analysis whose AUC were 0.918(CI: 0.851-0.985),0.918(CI: 0.840-0.996),0.899(CI: 0.821-0.977),0.877(CI: 0.792-0.961)and 0.873(CI: 0.784-0.962)respectively.Conclusion: For the first time,a UHPLC-QTOF-MS-based non-targeted metabolomics method was established for the analysis of tongue coating samples in the healthy and the patients with SCG.Thirty-seven metabolites were finally identified as potential biomarkers related to SCG,which involved various metabolic disorders such as purine metabolism,amino acid metabolism,sphingolipid metabolism and energy metabolism and five potential diagnostic biomarkers were screened using ROC curve analysis.This study provides new ideas and methods for molecular mechanism research and clinical diagnosis of chronic gastritis.Part two Non-targeted Metabolomics to Study the Saliva of the Patients with Different Symptom Type of Chronic GastritisObjective : To establish a UHPLC-QTOF-MS-based metabolomics analysis method to search for differential metabolites in saliva of patients with different symptom type of chronic gastritis and to further discover the molecular mechanisms of chronic gastritis and potential biomarkers that aid diagnosis of chronic gastritis.Methods: According to the formulated selection method,forty-one patients with SCG(SCG group: male 18 cases,female 23 cases),thirteen patients with ZCG(ZCG group: male 8 cases,female 5 cases)and eighteen healthy person(HC group: male 10 cases,female 8 cases)were selected.100 ?L of acetonitrile was added into 50 ?L of saliva sample to get the mixture which was centrifuged to extract the endogenous components.The handled sample was analyzed by UHPLC-QTOF-MS method using ACQUITY UPLC? BEH HILIC(2.1×100 mm,1.7 ?m)column and ACQUITY UPLC? HSS T3(2.1×100 mm,1.8 ?m)column with positive and negative ion separately scanning modes.The raw data was imported into Progenesis QI to perform peak alignment,deconvolution and selection of adducts to get the handled dataset.The obtained datasets of HC group,SCG group and ZCG group were performed to establish PLS-DA model.The obtained datasets of HC group and ZCG group were tested by Student's T test to obtain P value and OPLS-DA model was established to obtain VIP value.Components that both satisfying P<0.05 and VIP>1 were considered as differential compounds.Differential compounds were identifited by matching secondary spectrum with online database(HMDB,METLIN)to obtain the potential biomarkers.The Metabo Analyst 4.0 software was performed to enrich the markers and analyze the metabolic pathway of the markers.The ROC curve analysis was performed to find potential diagnostic biomarkers.Potential biomarkers were obtained by analyzing HC and ZCG groups and the content of them in the three groups was analyzed by Graph Pad Prism 6.0.Results: In the PLS-DA model of the HC group,SCG group and ZCG group,the HC group and ZCG group can be clearly distinguished and the SCG group partially intersects with the other two groups.In the comparison between the HC group and ZCG group,2511,1134,4858 and 1216 peaks were obtained in the four analysis models of this study.79,51,305 and 44 differential compounds associated with ZCG were obtained by multivariate statistical analysis and then a total of 17 potential biomarkers were obtained by matching databases.Some of the metabolic pathways were found to be associated with ZCG by using online software,including: pyrimidine metabolism,amino acid metabolism and taurine and metataurine metabolism.cytidine,cytosine and 1,4-methylimidazolium acetate were found to have good accuracy in predicting ZCG by ROC curve analysis whose AUC were 0.949(CI: 0.878-1.000),0.957(CI: 0.891-1.000)and 0.940(CI: 0.857-1.000)respectively.Conclusion: For the first time,a UHPLC-QTOF-MS-based non-targeted metabolomics method was established for the analysis of saliva samples in the healthy and the patients with SCG and ZCG.The analysis of salivary samples provided evidence of the progressive development of Shi Re Kun Pi syndrome and Zhuo Du Nei Yun syndrome.Seventeen metabolites were finally identified as potential biomarkers related to ZCG,which involved various metabolic disorders such as pyrimidine metabolism,amino acid metabolism and taurine and metataurine metabolism and three potential diagnostic biomarkers were screened using ROC curve analysis.This study provides new ideas and methods for molecular mechanism research and clinical diagnosis of chronic gastritis by saliva samples.