Abstract:
Coronary artery disease (CAD) is more likely to develop among individuals with non-alcoholic fatty liver disease (NAFLD), as compared to healthy individuals. However, there are currently limited biomarkers to detect heart disease before cardiac symptoms occur. Applying metabolomic fingerprinting and profiling to these patients might improve prediction and diagnosis of CAD. Thus, the aims of this study were to identify metabolomic pattern differences among various CAD severities and to address metabolite signatures that can become potential biomarkers.
Liquid chromatography-mass spectrometry was performed on 83 serum sample extractions from participants diagnosed with NAFLD and CAD severity levels ranging from no CAD through CAD level 4. The data underwent multivariate analysis to distinguish metabolomic patterns variation, and results showed that there is a separation between CAD stages, indicating the difference in their metabolomic fingerprints by stage. Then, Student‟s t-test with FDR correction, frequency calculation, and log2 fold change were applied to select metabolites associated with CAD. Eight candidate metabolites were chosen and were further analyzed by tandem mass spectrometry to yield metabolomic profiles. Compound identification was attempted by comparing these sample profiles with the NIST database. According to the results, one of the targeted profiles matched a drug derived metabolite, 4-hydroxyatorvastatin lactone, and it is CAD 0 stage specific. Based on patient medical history report, the use of atorvastatin was found to be higher in this stage, which confirmed the result. In conclusion, the identified metabolite can be considered as an internal standard; it verified the data processing and method of selecting metabolites in the present research. The other 7 CAD sensitive metabolites were unable to be identified using current databases of known compounds and may be investigated in future projects.
