Ramu Adela, Siva Swapna Kasarla, Najmuddin Saquib, Sonu Kumar Gupta, Sneh Bajpai, Yashwant Kumar and Sanjay K Banerjee
{"title":"Untargeted metabolomics reveals altered branch chain amino acids, glucose and fat metabolism contributing to coronary artery disease among Indian diabetic patients†","authors":"Ramu Adela, Siva Swapna Kasarla, Najmuddin Saquib, Sonu Kumar Gupta, Sneh Bajpai, Yashwant Kumar and Sanjay K Banerjee","doi":"10.1039/D2MO00320A","DOIUrl":null,"url":null,"abstract":"<p >Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterised by increased blood glucose levels. Patients with T2DM have a high risk of developing atherosclerotic coronary artery disease (CAD). CAD with T2DM has a complex etiology and the understanding of the pathophysiology of coronary artery disease (CAD) in the presence of diabetes is poor. Here, we have used LC-MS/MS-based untargeted metabolomics to unveil the alterations of metabolites in the serum of South-Indian patients diagnosed with T2DM, CAD and T2DM along with CAD (T2DM-CAD) compared with the healthy subjects (CT). Using untargeted metabolomics and network-based approaches, a set of metabolites highly co-expressed with T2DM-CAD pathogenesis were identified. Our results revealed that these metabolites belong to essential pathways such as amino acid metabolism, fatty acid metabolism and carbohydrate metabolism. The candidate metabolites identified by metabolomics study are branch chain amino acids, <small>L</small>-arginine, linoleic acid, <small>L</small>-serine, <small>L</small>-cysteine, fructose-6-phosphate, glycerol, creatine and 3-phosphoglyceric acid, and explain the pathogenesis of T2DM-assisted CAD. The identified metabolites could be used as potential prognostic markers to predict CAD in patients diagnosed with T2DM.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"99","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2023/mo/d2mo00320a","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
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterised by increased blood glucose levels. Patients with T2DM have a high risk of developing atherosclerotic coronary artery disease (CAD). CAD with T2DM has a complex etiology and the understanding of the pathophysiology of coronary artery disease (CAD) in the presence of diabetes is poor. Here, we have used LC-MS/MS-based untargeted metabolomics to unveil the alterations of metabolites in the serum of South-Indian patients diagnosed with T2DM, CAD and T2DM along with CAD (T2DM-CAD) compared with the healthy subjects (CT). Using untargeted metabolomics and network-based approaches, a set of metabolites highly co-expressed with T2DM-CAD pathogenesis were identified. Our results revealed that these metabolites belong to essential pathways such as amino acid metabolism, fatty acid metabolism and carbohydrate metabolism. The candidate metabolites identified by metabolomics study are branch chain amino acids, L-arginine, linoleic acid, L-serine, L-cysteine, fructose-6-phosphate, glycerol, creatine and 3-phosphoglyceric acid, and explain the pathogenesis of T2DM-assisted CAD. The identified metabolites could be used as potential prognostic markers to predict CAD in patients diagnosed with T2DM.