biostudies-literatureUnknown6Wang WBicuspid aortic valve (BAV) is the most common congenital heart disease. The current study aims to construct a diagnostic model based on metabolic profiling as a non-invasive tool for BAV screening. Blood serum samples were prepared from an estimation group and a validation group, each consisting of 30 BAV patients and 20 healthy individuals, and analyzed by liquid chromatography-mass spectrometry (LC-MS). In total, 2213 metabolites were detected and 41 were considered different. A model for predicting BAV in the estimation group was constructed using the concentration levels of monoglyceride (MG) (18:2) and glycerophospho-N-oleoyl ethanolamine (GNOE). A novel model named Zhongshan (ZS) was developed to amplify the association between BAV and the two metabolites. The area under curve (AUC)Scientific reports37023https://www.ebi.ac.uk/biostudies/studies/S-EPMC5109472biostudies-literatureAnalysis of Serum Metabolites to Diagnose Bicuspid Aortic Valve.PMC5109472Kong BXia LLiu MWang CTao HWang WZhang LMaimaiti AZhao YWei LNian HfalseAnalysis of Serum Metabolites to Diagnose Bicuspid Aortic Valve.Bicuspid aortic valve (BAV) is the most common congenital heart disease. The current study aims to construct a diagnostic model based on metabolic profiling as a non-invasive tool for BAV screening. Blood serum samples were prepared from an estimation group and a validation group, each consisting of 30 BAV patients and 20 healthy individuals, and analyzed by liquid chromatography-mass spectrometry (LC-MS). In total, 2213 metabolites were detected and 41 were considered different. A model for predicting BAV in the estimation group was constructed using the concentration levels of monoglyceride (MG) (18:2) and glycerophospho-N-oleoyl ethanolamine (GNOE). A novel model named Zhongshan (ZS) was developed to amplify the association between BAV and the two metabolites. The area under curve (AUC)2016-01-01T00:00:00Z2016 Nov2026-04-30T01:30:15.927Z2019-03-27T02:28:59ZS-EPMC51094722784543310.1038/srep37023