Gupta A, Kumar S, Kashyap S, Kumar D, Kapoor A. Nuclear Magnetic Resonance-Based Metabolomics of Human Filtered Serum: A Great White Hope in Appraisal of Chronic Stable Angina and Myocardial Infarction.
J Appl Lab Med 2016;
1:280-293. [PMID:
33626845 DOI:
10.1373/jalm.2016.020776]
[Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Accepted: 08/17/2016] [Indexed: 11/06/2022]
Abstract
BACKGROUND
Biochemical detection of chronic stable angina (CSA) and myocardial infarction (MI) are challenging. To address the shortcomings of the conventional biochemical approach for detection of MI, we applied serum lacking proteins and lipoprotein-based metabolomics in an approach using proton nuclear magnetic resonance (1H NMR) spectroscopy for screening of coronary artery disease (CAD) and especially MI. Our aim was to discover differential biomarkers among subjects with normal coronary (NC), CSA, and MI.
METHODS
The study comprised serum samples from nondiabetic angiographically proven CAD [CSA (n = 88), MI (n = 90)] and NC (n = 55). 1H NMR spectroscopy was used to acquire metabolomics data. Clinical variables such as troponin I (TI), lactate dehydrogenase (LD), creatine kinase (CK, CK-MB, CK-MM), serum creatinine, and lipid profiles were also measured in all subjects. Metabolomic data and clinical measures were appraised separately using a chemometric approach and ROC analysis.
RESULTS
The screening outcomes revealed that the pattern of methylguanidine, lactate, creatinine, threonine, aspartate, and trimethylamine (TMA), and TI, LD, CK, and serum creatinine were changed in CAD compared to NC. Statistical analysis demonstrated high precision (93.6% by NMR and 67.4% by clinical measures) to distinguish CAD from NC. Further analysis indicated that methylguanidine, arginine, and threonine, and TI, LD, and serum creatinine were significantly changed in CSA compared to MI. Statistical analysis demonstrated high accuracy (88.2% by NMR and 92.1% by clinical measures) to discriminate CSA from MI.
CONCLUSIONS
In contrast to other laboratory methods, 1H NMR-based metabolomics of filtered sera appears to be a robust, rapid, and minimally invasive approach to probe CSA and MI.
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