{"title":"利用舌苔代谢组学鉴定中医湿痰型慢性胃炎的生物标记物","authors":"Zhiyuan You, Jialin Zhang, Yifeng Xu, Junhong Lu, Renling Zhang, Zhujing Zhu, Yiqin Wang, Yiming Hao","doi":"10.2147/JIR.S480307","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to establish a model for identifying chronic gastritis with the traditional Chinese medicine damp phlegm pattern by examining metabolite changes in the tongue coating of patients. It also explored the role of metabolic pathways in the pathogenesis of this condition.</p><p><strong>Methods: </strong>This cross-sectional study involved 300 patients diagnosed with chronic gastritis. Of these, 200 patients exhibited the damp phlegm pattern, while 100 did not. Metabolomic methods employing GC-TOF-MS and UHPLC-QE-MS were utilized to identify various metabolites in the tongue coating of patients. An identification model for chronic gastritis with the damp phlegm pattern was created based on ROC curves derived from differential biomarkers. Additionally, 50 samples not included in model construction were collected for external validation.</p><p><strong>Results: </strong>Comparison of the damp phlegm pattern group with the non-damp phlegm pattern group revealed a total of 116 differential metabolites. Among these, lipids and lipid-like compounds were most abundant, comprising 27 types, which included four lipid metabolites related to sphingomyelin metabolism. The ROC model, which included phenol, 2.6-diaminoheptanedioic acid, and N-hexadecanoyl pyrrolidine, demonstrated the highest accuracy, with accuracy, sensitivity, and specificity metrics of 94.0%, 91.0%, and 87.0%, respectively. Furthermore, external validation using tongue coating metabolites from 50 patients revealed accuracy, sensitivity, and specificity in the validation set of 93.9%, 90.6%, and 83.3%, respectively.</p><p><strong>Conclusion: </strong>Differential metabolites between patients with the damp phlegm pattern and those without are primarily lipids and lipid-like compounds. N-hexadecanoyl pyrrolidine, phenol, and 2.6-diaminoheptanedioic acid may serve as potential biomarkers for chronic gastritis characterized by the damp phlegm pattern.</p>","PeriodicalId":16107,"journal":{"name":"Journal of Inflammation Research","volume":"17 ","pages":"8027-8045"},"PeriodicalIF":4.2000,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11539634/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identification of the Biomarkers for Chronic Gastritis with TCM Damp Phlegm Pattern by Using Tongue Coating Metabolomics.\",\"authors\":\"Zhiyuan You, Jialin Zhang, Yifeng Xu, Junhong Lu, Renling Zhang, Zhujing Zhu, Yiqin Wang, Yiming Hao\",\"doi\":\"10.2147/JIR.S480307\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>This study aimed to establish a model for identifying chronic gastritis with the traditional Chinese medicine damp phlegm pattern by examining metabolite changes in the tongue coating of patients. It also explored the role of metabolic pathways in the pathogenesis of this condition.</p><p><strong>Methods: </strong>This cross-sectional study involved 300 patients diagnosed with chronic gastritis. Of these, 200 patients exhibited the damp phlegm pattern, while 100 did not. Metabolomic methods employing GC-TOF-MS and UHPLC-QE-MS were utilized to identify various metabolites in the tongue coating of patients. An identification model for chronic gastritis with the damp phlegm pattern was created based on ROC curves derived from differential biomarkers. Additionally, 50 samples not included in model construction were collected for external validation.</p><p><strong>Results: </strong>Comparison of the damp phlegm pattern group with the non-damp phlegm pattern group revealed a total of 116 differential metabolites. Among these, lipids and lipid-like compounds were most abundant, comprising 27 types, which included four lipid metabolites related to sphingomyelin metabolism. The ROC model, which included phenol, 2.6-diaminoheptanedioic acid, and N-hexadecanoyl pyrrolidine, demonstrated the highest accuracy, with accuracy, sensitivity, and specificity metrics of 94.0%, 91.0%, and 87.0%, respectively. Furthermore, external validation using tongue coating metabolites from 50 patients revealed accuracy, sensitivity, and specificity in the validation set of 93.9%, 90.6%, and 83.3%, respectively.</p><p><strong>Conclusion: </strong>Differential metabolites between patients with the damp phlegm pattern and those without are primarily lipids and lipid-like compounds. N-hexadecanoyl pyrrolidine, phenol, and 2.6-diaminoheptanedioic acid may serve as potential biomarkers for chronic gastritis characterized by the damp phlegm pattern.</p>\",\"PeriodicalId\":16107,\"journal\":{\"name\":\"Journal of Inflammation Research\",\"volume\":\"17 \",\"pages\":\"8027-8045\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11539634/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Inflammation Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/JIR.S480307\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Inflammation Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/JIR.S480307","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
Identification of the Biomarkers for Chronic Gastritis with TCM Damp Phlegm Pattern by Using Tongue Coating Metabolomics.
Objective: This study aimed to establish a model for identifying chronic gastritis with the traditional Chinese medicine damp phlegm pattern by examining metabolite changes in the tongue coating of patients. It also explored the role of metabolic pathways in the pathogenesis of this condition.
Methods: This cross-sectional study involved 300 patients diagnosed with chronic gastritis. Of these, 200 patients exhibited the damp phlegm pattern, while 100 did not. Metabolomic methods employing GC-TOF-MS and UHPLC-QE-MS were utilized to identify various metabolites in the tongue coating of patients. An identification model for chronic gastritis with the damp phlegm pattern was created based on ROC curves derived from differential biomarkers. Additionally, 50 samples not included in model construction were collected for external validation.
Results: Comparison of the damp phlegm pattern group with the non-damp phlegm pattern group revealed a total of 116 differential metabolites. Among these, lipids and lipid-like compounds were most abundant, comprising 27 types, which included four lipid metabolites related to sphingomyelin metabolism. The ROC model, which included phenol, 2.6-diaminoheptanedioic acid, and N-hexadecanoyl pyrrolidine, demonstrated the highest accuracy, with accuracy, sensitivity, and specificity metrics of 94.0%, 91.0%, and 87.0%, respectively. Furthermore, external validation using tongue coating metabolites from 50 patients revealed accuracy, sensitivity, and specificity in the validation set of 93.9%, 90.6%, and 83.3%, respectively.
Conclusion: Differential metabolites between patients with the damp phlegm pattern and those without are primarily lipids and lipid-like compounds. N-hexadecanoyl pyrrolidine, phenol, and 2.6-diaminoheptanedioic acid may serve as potential biomarkers for chronic gastritis characterized by the damp phlegm pattern.
期刊介绍:
An international, peer-reviewed, open access, online journal that welcomes laboratory and clinical findings on the molecular basis, cell biology and pharmacology of inflammation.