Hui Wang , Xuemei Fan , Fuguo Han , Haiyan Hao , Xiaowen Xu , Yanli Hao , Zhiguang Sun , Zhengguang Li , Qingfei Liu
{"title":"Metabolomics study of Shenling Baizhu Powder in the treatment of multiple organ dysfunction syndrome in the elderly (MODSE) with malnutrition","authors":"Hui Wang , Xuemei Fan , Fuguo Han , Haiyan Hao , Xiaowen Xu , Yanli Hao , Zhiguang Sun , Zhengguang Li , Qingfei Liu","doi":"10.1016/j.jpba.2024.116423","DOIUrl":null,"url":null,"abstract":"<div><p>Malnutrition is an important risk factor for multiple organ dysfunction syndrome in the elderly (MODSE) and seriously affects the occurrence, progression and prognosis of MODSE. Shenling Baizhu Power (SBP), a classic formula from traditional Chinese medicine (TCM), when integrated with enteral nutrition, has been proven to be an effective clinical strategy for treating the patients of MODSE with malnutrition. This study aimed to investigate the metabolic changes during disease occurrence and SBP treatment, and to discover potential metabolic biomarkers for the diagnosis and efficacy evaluation. An untargeted metabolomics strategy based on UHPLC-Q-Orbitrap-HRMS was performed to reveal the differential serum metabolites between MODSE patients with malnutrition (n=59) and healthy controls (n=33), and those between patients treated with enteral nutrition (n=31) and SBP combined with enteral nutrition (n=28). Significantly different metabolites were identified and mapped onto the network of metabolic pathways to explore the metabolic disorders caused by the disease and the metabolic regulatory mechanism of SBP. Additionally, the area under the curve (AUC) of the potential biomarkers was investigated for predicting the disease and the efficacy of SBP. Sixty differential metabolites were identified between the disease and control groups, which were mainly related to amino acid metabolism, energy metabolism and carbohydrate metabolism. In the same way, 50 differential metabolites associated with SBP treatment were identified, which improved metabolic abnormalities in vivo mainly by regulating the above-mentioned metabolic pathways. Finally, 13 differential metabolites in common were selected as the potential biomarkers and the AUC value of each biomarker was within the range of 0.8–1.0, indicating that these biomarkers had high prediction accuracy for the diagnosis and efficacy evaluation of MODSE with malnutrition. This study demonstrates that serum metabolomics approaches based on the UHPLC-Q-Orbitrap-HRMS platform can be applied as a tool to reveal the metabolic changes induced by MODSE with malnutrition and SBP can play an important role in the clinical application.</p></div>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0731708524004631","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Malnutrition is an important risk factor for multiple organ dysfunction syndrome in the elderly (MODSE) and seriously affects the occurrence, progression and prognosis of MODSE. Shenling Baizhu Power (SBP), a classic formula from traditional Chinese medicine (TCM), when integrated with enteral nutrition, has been proven to be an effective clinical strategy for treating the patients of MODSE with malnutrition. This study aimed to investigate the metabolic changes during disease occurrence and SBP treatment, and to discover potential metabolic biomarkers for the diagnosis and efficacy evaluation. An untargeted metabolomics strategy based on UHPLC-Q-Orbitrap-HRMS was performed to reveal the differential serum metabolites between MODSE patients with malnutrition (n=59) and healthy controls (n=33), and those between patients treated with enteral nutrition (n=31) and SBP combined with enteral nutrition (n=28). Significantly different metabolites were identified and mapped onto the network of metabolic pathways to explore the metabolic disorders caused by the disease and the metabolic regulatory mechanism of SBP. Additionally, the area under the curve (AUC) of the potential biomarkers was investigated for predicting the disease and the efficacy of SBP. Sixty differential metabolites were identified between the disease and control groups, which were mainly related to amino acid metabolism, energy metabolism and carbohydrate metabolism. In the same way, 50 differential metabolites associated with SBP treatment were identified, which improved metabolic abnormalities in vivo mainly by regulating the above-mentioned metabolic pathways. Finally, 13 differential metabolites in common were selected as the potential biomarkers and the AUC value of each biomarker was within the range of 0.8–1.0, indicating that these biomarkers had high prediction accuracy for the diagnosis and efficacy evaluation of MODSE with malnutrition. This study demonstrates that serum metabolomics approaches based on the UHPLC-Q-Orbitrap-HRMS platform can be applied as a tool to reveal the metabolic changes induced by MODSE with malnutrition and SBP can play an important role in the clinical application.