Investigation of novel metabolites potentially involved in the pathogenesis of coronary heart disease using a UHPLC-QTOF/MS-based metabolomics approach. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Li, Yiping; Zhang, Dong; He, Yuan; Chen, Changzhe; Song, Chenxi; Zhao, Yanyan; Bai, Yinxiao; Wang, Yang; Pu, Jielin; Chen, Jingzhou; Yang, Yuejin; Dou, Kefei
• Is Part Of: Scientific reports. Volume 7:Issue 1(2017)
• Page Start: 1
• Page End: 8
• Publication Date: 2017-12
• Subjects: Natural history -- Research -- Periodicals; Biology -- Research -- Periodicals; Physical sciences -- Research -- Periodicals; Earth sciences -- Research -- Periodicals; Environmental sciences -- Research -- Periodicals; 502.85
• DOI: 10.1038/s41598-017-15737-3
• Languages: English
• ISSNs: 2045-2322

Abstract

Abstract Coronary heart disease (CHD) is associated with complex metabolic disorders, but its molecular aetiology remains unclear. Using a novel nontargeted metabolomics approach, we explored the global metabolic perturbation profile for CHD. Blood samples from 150 patients with severe obstructive CHD and 150 angiographically normal controls were collected. Metabolic fingerprinting was performed by ultra-high performance liquid chromatography coupled to quadruple time-of-flight mass spectrometry (UHPLC-QTOF/MS) technique. After adjusting for CHD traditional risk factors and metabolic batch, a comprehensive list of 105 metabolites was found to be significantly altered in CHD patients. Among the metabolites identified, six metabolites were discovered to have the strongest correlation with CHD after adjusting for multiple testing: palmitic acid (β = 0.205; p < 0.0001), linoleic acid (β = 0.133; p < 0.0001), 4-pyridoxic acid (β = 0.142; p < 0.0001), phosphatidylglycerol (20:3/2:0) (β = 0.287; p < 0.0001), carnitine (14:1) (β = 0.332; p < 0.0001) and lithocholic acid (β = 0.224; p < 0.0001); of these, 4-pyridoxic acid, lithocholic acid and phosphatidylglycerol (20:3/2:0) were, to the best of our knowledge, first reported in this study. A logistic regression model further quantified their positive independent correlations with CHD. In conclusion, this study surveyed a broad panel of nontargeted metabolites in Chinese CHD populations and identified novel metabolites that are potentially involved in CHD pathogenesis.