{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,6]],"date-time":"2026-11-06T22:02:28Z","timestamp":1794002548952,"version":"4.8.0"},"reference-count":28,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T00:00:00Z","timestamp":1679616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Pharmacol."],"abstract":"<jats:p>\n                    <jats:bold>Background:<\/jats:bold>\n                    Patients with diabetes have a two-to four-fold increased incidence of cardiovascular diseases compared with non-diabetics. Currently, there is no recognized model to predict the occurrence and progression of CVDs in diabetics.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Objective:<\/jats:bold>\n                    This work aimed to develop a metabolic biomarker-assisted model, a combination of metabolic markers with clinical variables, for risk prediction of CVDs in diabetics.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Methods:<\/jats:bold>\n                    A total of 475 patients with diabetes were studied. Each patient underwent coronary angiography. Plasma samples were analyzed by liquid chromatography-quadrupole time-of-flight mass spectrometry. Ordinal logistic regression and random forest were used to screen metabolites. Receiver operating characteristic (ROC) curve, nomogram, and decision curve analysis (DCA) were employed to evaluate their prediction performances.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Results:<\/jats:bold>\n                    Ordinal logistic regression screened out 34 differential metabolites (adjusted-false discovery rate\n                    <jats:italic>p<\/jats:italic>\n                    &amp;lt; 0.05) from 2059 ion features by comparisons of diabetics with and without CVDs. Random forest identified methylglutarylcarnitine and lysoPC (18:0) as the metabolic markers (mean decrease gini &amp;gt;1.0) for non-significant CVDs (nos-CVDs)\n                    <jats:italic>versus<\/jats:italic>\n                    normal coronary artery (NCA), 1,3-Octadiene and 3-Octanone for acute coronary syndrome (ACS)\n                    <jats:italic>versus<\/jats:italic>\n                    nos-CVDs, and lysoPC (18:0) for acute coronary syndrome\n                    <jats:italic>versus<\/jats:italic>\n                    normal coronary artery. For risk prediction, the metabolic marker-assisted models provided areas under the curve of 0.962\u20130.979 by ROC (0.576\u20130.779 for the base models), and c-indices of 0.8477\u20130.9537 by nomogram analysis (0.1514\u20130.5196 for the base models). Decision curve analysis (DCA) showed that the models produced greater benefits throughout a wide range of risk probabilities compared with the base model.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Conclusion:<\/jats:bold>\n                    Metabolic biomarker-assisted model remarkably improved risk prediction of cardiovascular disease in diabetics (&amp;gt;90%).\n                  <\/jats:p>","DOI":"10.3389\/fphar.2023.1175021","type":"journal-article","created":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T09:14:00Z","timestamp":1679649240000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Metabolite-assisted models improve risk prediction of coronary heart disease in patients with diabetes"],"prefix":"10.3389","volume":"14","author":[{"given":"Min","family":"Shen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingya","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruizhe","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunjing","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pingxi","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,3,24]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1002\/sim.4780040107","article-title":"The bootstrap and identification of prognostic factors via Cox's proportional hazards regression model","volume":"4","author":"Chen","year":"1985","journal-title":"Statistics Med."},{"key":"B2","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1016\/S0140-6736(04)16895-5","article-title":"Primary prevention of cardiovascular disease with atorvastatin in type 2 diabetes in the collaborative atorvastatin diabetes study (CARDS): Multicentre randomised placebo-controlled trial","volume":"364","author":"Colhoun","year":"2004","journal-title":"Lancet"},{"key":"B3","doi-asserted-by":"publisher","first-page":"2005","DOI":"10.1016\/s0140-6736(03)13636-7","article-title":"MRC\/BHF heart protection study of cholesterol-lowering with simvastatin in 5963 people with diabetes: A randomised placebo-controlled trial","volume":"361","author":"Collins","year":"2003","journal-title":"Lancet"},{"key":"B4","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1001\/jamaneurol.2016.4491","article-title":"Association of collateral blood vessels detected by arterial spin labeling magnetic resonance imaging with neurological outcome after ischemic stroke","volume":"74","author":"de Havenon","year":"2017","journal-title":"JAMA neurol."},{"key":"B5","doi-asserted-by":"publisher","first-page":"2494","DOI":"10.1001\/jama.2010.1708","article-title":"Association of serial measures of cardiac troponin T using a sensitive assay with incident heart failure and cardiovascular mortality in older adults","volume":"304","author":"deFilippi","year":"2010","journal-title":"Jama-J Am. Med. Assoc."},{"key":"B6","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/s00726-015-2067-1","article-title":"The role of leucine and its metabolites in protein and energy metabolism","volume":"48","author":"Duan","year":"2016","journal-title":"Amino acids"},{"key":"B7","doi-asserted-by":"publisher","first-page":"1060","DOI":"10.1038\/nprot.2011.335","article-title":"Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry","volume":"6","author":"Dunn","year":"2011","journal-title":"Nat. Protoc."},{"key":"B8","doi-asserted-by":"publisher","first-page":"2215","DOI":"10.1016\/S0140-6736(10)60484-9","article-title":"Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: A collaborative meta-analysis of 102 prospective studies","volume":"375","author":"Emerging Risk Factors","year":"2010","journal-title":"Lancet"},{"key":"B9","doi-asserted-by":"publisher","first-page":"1281","DOI":"10.1016\/j.jacc.2016.06.044","article-title":"Comprehensive metabolomic characterization of coronary artery diseases","volume":"68","author":"Fan","year":"2016","journal-title":"J. Am. Coll. Cardiol."},{"key":"B10","doi-asserted-by":"publisher","first-page":"1206","DOI":"10.1016\/j.metabol.2013.04.003","article-title":"Mass spectrometry techniques in the survey of steroid metabolites as potential disease biomarkers: A review","volume":"62","author":"Gouveia","year":"2013","journal-title":"Metabolism"},{"key":"B11","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1186\/s12933-015-0296-y","article-title":"Patients with coronary artery disease and diabetes need improved management: A report from the EUROASPIRE IV survey: A registry from the EuroObservational research programme of the European society of Cardiology","volume":"14","author":"Gyberg","year":"2015","journal-title":"Cardiovasc. Diabetol."},{"key":"B12","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1056\/NEJM199807233390404","article-title":"Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction","volume":"339","author":"Haffner","year":"1998","journal-title":"N. Engl. J. Med."},{"key":"B13","doi-asserted-by":"publisher","first-page":"2543","DOI":"10.1001\/jama.1982.03320430047030","article-title":"Evaluating the yield of medical tests","volume":"247","author":"Harrell","year":"1982","journal-title":"Jama"},{"key":"B14","doi-asserted-by":"publisher","first-page":"978","DOI":"10.1056\/NEJMc1508386","article-title":"Follow-up of glycemic control and cardiovascular outcomes in type 2 diabetes","volume":"373","author":"Hayward","year":"2015","journal-title":"N. Engl. J. Med."},{"key":"B15","doi-asserted-by":"publisher","first-page":"2930","DOI":"10.1093\/eurheartj\/ehp309","article-title":"Expression of lipoprotein-associated phospholipase A(2) in carotid artery plaques predicts long-term cardiac outcome","volume":"30","author":"Herrmann","year":"2009","journal-title":"Eur. heart J."},{"key":"B16","doi-asserted-by":"publisher","first-page":"1413","DOI":"10.1016\/j.jacc.2005.01.039","article-title":"The gender-specific impact of diabetes and myocardial infarction at baseline and during follow-up on mortality from all causes and coronary heart disease","volume":"45","author":"Hu","year":"2005","journal-title":"J. Am. Coll. Cardiol."},{"key":"B17","doi-asserted-by":"publisher","first-page":"1849","DOI":"10.1016\/S0140-6736(05)67667-2","article-title":"Effects of long-term fenofibrate therapy on cardiovascular events in 9795 people with type 2 diabetes mellitus (the FIELD study): Randomised controlled trial","volume":"366","author":"Keech","year":"2005","journal-title":"Lancet"},{"key":"B18","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.jnutbio.2016.02.007","article-title":"Branched-chain amino acids are associated with cardiometabolic risk profiles found already in lean, overweight and obese young","volume":"32","author":"Mangge","year":"2016","journal-title":"J. Nutr. Biochem."},{"key":"B19","doi-asserted-by":"publisher","first-page":"4270","DOI":"10.2337\/db13-0570","article-title":"Biomarkers for type 2 diabetes and impaired fasting glucose using a nontargeted metabolomics approach","volume":"62","author":"Menni","year":"2013","journal-title":"Diabetes"},{"key":"B20","doi-asserted-by":"publisher","first-page":"819","DOI":"10.1038\/nmeth.2085","article-title":"forestSV: structural variant discovery through statistical learning","volume":"9","author":"Michaelson","year":"2012","journal-title":"Nat. Methods"},{"key":"B21","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1093\/eurheartj\/ehx018","article-title":"Coronary artery disease in diabetes","volume":"38","author":"Nicholls","year":"2017","journal-title":"Eur. heart J."},{"key":"B22","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1038\/ijo.2014.53","article-title":"Mapping of the circulating metabolome reveals alpha-ketoglutarate as a predictor of morbid obesity-associated non-alcoholic fatty liver disease","volume":"39","author":"Rodriguez-Gallego","year":"2015","journal-title":"Int. J. Obes."},{"key":"B23","doi-asserted-by":"publisher","first-page":"3024","DOI":"10.1093\/eurheartj\/ehq322","article-title":"Multiple marker approach to risk stratification in patients with stable coronary artery disease","volume":"31","author":"Schnabel","year":"2010","journal-title":"Eur. heart J."},{"key":"B24","doi-asserted-by":"publisher","first-page":"1821","DOI":"10.1161\/CIRCULATIONAHA.113.002500","article-title":"Lipidomics profiling and risk of cardiovascular disease in the prospective population-based Bruneck study","volume":"129","author":"Stegemann","year":"2014","journal-title":"Circulation"},{"key":"B25","doi-asserted-by":"publisher","first-page":"e51","DOI":"10.1093\/nar\/gkw1260","article-title":"miSTAR: miRNA target prediction through modeling quantitative and qualitative miRNA binding site information in a stacked model structure","volume":"45","author":"Van Peer","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"B26","doi-asserted-by":"publisher","first-page":"1700","DOI":"10.1161\/CIRCULATIONAHA.109.929661","article-title":"Multimarker approach for the prediction of heart failure incidence in the community","volume":"122","author":"Velagaleti","year":"2010","journal-title":"Circulation"},{"key":"B27","doi-asserted-by":"publisher","first-page":"1398","DOI":"10.1136\/hrt.2003.026104","article-title":"Cardiovascular disease incidence and mortality in older men with diabetes and in men with coronary heart disease","volume":"90","author":"Wannamethee","year":"2004","journal-title":"Heart"},{"key":"B28","doi-asserted-by":"publisher","first-page":"e38","DOI":"10.1161\/CIR.0000000000000350","article-title":"Heart disease and stroke statistics-2016 update: A report from the American heart association","volume":"133","author":"Writing Group","year":"2016","journal-title":"Circulation"}],"container-title":["Frontiers in Pharmacology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fphar.2023.1175021\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T09:14:04Z","timestamp":1679649244000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fphar.2023.1175021\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,24]]},"references-count":28,"alternative-id":["10.3389\/fphar.2023.1175021"],"URL":"https:\/\/doi.org\/10.3389\/fphar.2023.1175021","relation":{},"ISSN":["1663-9812"],"issn-type":[{"value":"1663-9812","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,24]]},"article-number":"1175021"}}