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A Non-Targeted Liquid Chromatographic-Mass Spectrometric Metabolomics Approach for Association with Coronary Artery Disease: An Identification of Biomarkers for Depiction of Underlying Biological Mechanisms

BACKGROUND: We performed non-targeted metabolomics analysis using liquid chromatography-mass spectrometry coupled technique to explore the biological mechanism of coronary artery disease (CAD) events for improved prediction. MATERIAL/METHODS: We studied the association of CAD events in 4092 individu...

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Detalles Bibliográficos
Autores principales: Zhang, Xian-Zhao, Zheng, Su-Xia, Hou, Ya-Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5301958/
https://www.ncbi.nlm.nih.gov/pubmed/28151921
http://dx.doi.org/10.12659/MSM.896298
Descripción
Sumario:BACKGROUND: We performed non-targeted metabolomics analysis using liquid chromatography-mass spectrometry coupled technique to explore the biological mechanism of coronary artery disease (CAD) events for improved prediction. MATERIAL/METHODS: We studied the association of CAD events in 4092 individuals and observed the replication of sphingomyelin (28:1), lysophosphatidylcholine (18:2), lysophosphatidylcholine (18:1), and monoglyceride (18:2), which were independent of main CAD risk factors. RESULTS: We found that these 4 metabolites were responsible for traditional risk factors and also contributed to the modifications related to reclassification and discrimination. Monoglycerides (MonoGs) were positively associated with C-reactive proteins and body mass index, while lysophosphatidylcholines (LPPCs), which had less evidence of subclinical CAD in an additional 1010 participants, yielded a reverse pattern. An association between monoGs and CAD independence of triglycerides (triGs) were also observed. On the basis of Mendelian randomization analysis, we observed a positive but weak irregular effect (odds ratio per unit increase in standard deviation in monoG=1.11, P-value=0.05) on CAD. CONCLUSIONS: Our work establishes the relationship of metabolome with coronary artery disease and explains the biological mechanism of CAD events, as we identified the above-mentioned metabolites along with the evidence supporting their clinical use.