A Study For Potential Biomarkers Of Periodontitis Based On Metabonomics

As periodontitis is one of the most common disease of oral cavity dominated by bacteria with various factors involved in.Despite the high prevalence and negative effects on quality of life,periodontitis is usually paid attention in a later stage when patients observe severe symptoms with periodontal inflammation and destruction of supporting structures.At present,the diagnosis of periodontitis depend on clinical measurements.effective biochemical index to measure its initiation and development is still absent.Metabonomics,as a new discipline,focuses on metabolites in normal physiological processes and disease,which can explore the metabolic pathways related to diseases.Previous studies have shown that there are differences between metabolites in periodontitis and healthy people,but few studies have focused on metabolites changes in different degrees of periodontitis.In addition,few studies have explored the combined application of “omics”in periodontal disease.This study was aimed at differential metabolites of gingivitis,periodontitis and healthy people,explored potential biomarkers of periodontitis.We tried to improve the specificity and sensitivity of diagnosis through the combined application of multiple metabolites.Meanwhile,this study explored important metabolic pathways in the occurrence and development of periodontitis,and combined metabonomics with proteomics through bioinformatics analysis method,so as to provide new ideas for the identification of etiology,prediction and diagnosis of periodontitis.This study analyzed non-irritating salivary metabolites from 30 participants from healthy,mild and severe periodontitis via Liquid chromatography/mass spectrometry,followed by Multivariate regression analysis to explore the relationship of them.Metaboanalyst and cytoscape were used to explore the important metabolic pathways and the relationship of metabolites.In addition,Logistic regression and receiver operator characteristic curve(ROC)were used to assess the associations of biomarkers to explore combined value to prospecting periodontitis.Proteo Exchange,a public database of proteomics,was used to find the proteomics data of periodontal disease.The proteomics information were analyzed and linked with metabonomics through KEGG pathway.Finally,Various amino acid metabolism,Pyrimidine metabolism,Arachidonic acid metabolism and Sphingolipid metabolism participated in the progress.Arachidonic acid,Prostaglandin E2,L-Phenylalanine and5?aminoimidazole?4?carboxamide?riboside(AICAR)altered gradually in control group,mild and severe periodontitis,considered to be associated with the initiation and progression of periodontitis.L-Arginine,Uracil,L-Proline increased in periodontitis compared with healthy without significant different between mild and severe periodontitis.Increasing glucosylceramide only exhibited in severe periodontitis,which could be potential biomarker for periodontitis of later stage.In addition,Logistic regression and receiver operator characteristic curve were used to assess the associations of biomarkers to explore combined value to prospecting periodontitis.The combination of AICAR and Caprylic acid,Uracil and L-Proline,Pyrocatechol and 4-Hydroxy-L-glutamic acid,Glucosylceramide(d18:1/9Z-18:1)and Methacrylyl-Co A showed better area under curve,which could improve diagnostic accuracy for periodontitis.In addition,proteomics revealed that a variety of proteins changed in periodontal disease.Metabolic pathway analysis revealed that aldehyde dehydrogenase(ALDH),glutamic-oxaloacetic transaminase 1(GOT1),glutamic-oxaloacetic transaminase 2(GOT2),carbonyl reductase 3(CBr3)and other enzymes were involved.These enzymes plays an important role in metabolic pathways such as arginine and proline metabolism,arachidonic acid metabolism,cysteine and methionine metabolism leads to changes in downstream metabolites.In this study,we successfully applied biochemical profiling to assess the differential metabolism of saliva in periodontitis.some metabolites were found to be significant.Glucosylceramide,L-Arginine,Uracil,L-Proline,Arachidonic acid,Prostaglandin E2,L-Phenylalanine,AICAR showed possibility to predict and diagnose periodontitis.Moreover,the combination of metabolites(AICAR and Caprylic acid,Uracil and L-Proline,Pyrocatechol and 4-Hydroxy-L-glutamic acid,Glucosylceramide and Methacrylyl-Co A)could improve the sensitivity and specificity.The combined analysis of salivary metabonomics and proteomics provides a new idea for the histological study of periodontal disease.