title: Identification of metabolic biomarkers in patients with type 2 diabetic coronary heart diseases based on metabolomic approach.
abstract: Type 2 diabetic coronary heart disease (T2DM-CHD) is a kind of serious and complex disease. Great attention has been paid to exploring its mechanism; however, the detailed understanding of T2DM-CHD is still limited. Plasma samples from 15 healthy controls, 13 coronary heart disease (CHD) patients, 15 type 2 diabetes mellitus (T2DM) patients and 28 T2DM-CHD patients were analyzed in this research. The potential biomarkers of CHD and T2DM were detected and screened out by (1)H NMR-based plasma metabolic profiling and multivariate data analysis. About 11 and 12 representative metabolites of CHD and T2DM were identified respectively, mainly including alanine, arginine, proline, glutamine, creatinine and acetate. Then the diagnostic model was further constructed based on the previous metabolites of CHD and T2DM to detect T2DM-CHD with satisfying sensitivity of 92.9%, specificity of 93.3% and accuracy of 93.2%, validating the robustness of (1)H NMR-based plasma metabolic profiling to diagnostic strategy. The results demonstrated that the NMR-based metabolomics approach processed good performance to identify diagnostic plasma biomarkers and most identified metabolites related to T2DM and CHD could be considered as predictors of T2DM-CHD as well as the therapeutic targets for prevention, which provided new insight into diagnosing and forecasting of complex diseases.
authors.affiliation: Department of Chemistry, Capital Normal University, Beijing 100048, China.
authors.forename: Xinfeng
authors.initials: X
authors.lastname: Liu
authors.affiliation: Beijing University of Chinese Medicine, Beijing 100029, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Gao
authors.affiliation: Beijing University of Chinese Medicine, Beijing 100029, China.
authors.forename: Jianxin
authors.initials: J
authors.lastname: Chen
authors.affiliation: Beijing University of Chinese Medicine, Beijing 100029, China.
authors.forename: Zhiyong
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Beijing University of Chinese Medicine, Beijing 100029, China.
authors.forename: Qi
authors.initials: Q
authors.lastname: Shi
authors.affiliation: Department of Chemistry, Capital Normal University, Beijing 100048, China.
authors.forename: Hongxue
authors.initials: H
authors.lastname: Man
authors.affiliation: Beijing University of Chinese Medicine, Beijing 100029, China.
authors.forename: Shuzhen
authors.initials: S
authors.lastname: Guo
authors.affiliation: Department of Chemistry, Capital Normal University, Beijing 100048, China.
authors.forename: Yingfeng
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Chemistry, Capital Normal University, Beijing 100048, China.|Beijing University of Chinese Medicine, Beijing 100029, China.
authors.forename: Zhongfeng
authors.initials: Z
authors.lastname: Li
authors.affiliation: Beijing University of Chinese Medicine, Beijing 100029, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood*; D016022:Case-Control Studies; D003327:Coronary Disease / Q000097:blood / Q000175:diagnosis*; D003924:Diabetes Mellitus, Type 2 / Q000150:complications* / Q000378:metabolism; D005260:Female; D006801:Humans; D008297:Male; D055432:Metabolomics / Q000379:methods*; D008875:Middle Aged; D066244:Proton Magnetic Resonance Spectroscopy; D012680:Sensitivity and Specificity
chemical_list: D015415:Biomarkers