alitretinoin and ST-Elevation-Myocardial-Infarction

The relevant metabolite biomarkers for risk prediction of early onset of ventricular fibrillation (VF) after ST-segment elevation myocardial infarction (STEMI) remain unstudied. Here, we aimed to identify these imetabolites and the important metabolic pathways involved, and explore whether these metabolites could be used as predictors for the phenotype. Plasma samples were obtained retrospectively from a propensity-score matched cohort including 42 STEMI patients (21 consecutive VF and 21 non-VF). Ultra-performance liquid chromatography and mass spectrometry in combination with a comprehensive analysis of metabolomic data using Metaboanalyst 5.0 version were performed. As a result, the retinal metabolism pathway proved to be the most discriminative for the VF phenotype. Furthermore, 9-cis-Retinoic acid (9cRA) and dehydrophytosphingosine proved to be the most discriminative biomarkers. Biomarker analysis through receiver operating characteristic (ROC) curve showed the 2-metabolite biomarker panel yielding an area under the curve (AUC) of 0.836. The model based on Monte Carlo cross-validation found that 9cRA had the greatest probability of appearing in the predictive panel of biomarkers in the model. Validation of model efficiency based on an ROC curve showed that the combination model constructed by 9cRA and dehydrophytosphingosine had a good predictive value for early-onset VF after STEMI, and the AUC was 0.884 (95% CI 0.714-1). Conclusively, the retinol metabolism pathway was the most powerful pathway for differentiating the post-STEMI VF phenotype. 9cRA was the most important predictive biomarker of VF, and a plasma biomarker panel made up of two metabolites, may help to build a potent predictive model for VF.

Topics: Adolescent; Adult; Aged; Alitretinoin; Biomarkers; Female; Humans; Male; Middle Aged; Sphingosine; ST Elevation Myocardial Infarction; Ventricular Fibrillation

The detection of left main coronary artery disease (LMCAD) is crucial before ST-segment elevated myocardial infarction (STEMI) or sudden cardiac death. The aim of this study was to identify characteristic metabolite modifications in the LMCAD phenotype, using the metabolomics technique. Metabolic profiles were generated based on ultra-performance liquid chromatography and mass spectrometry, combined with multivariate statistical analysis. Plasma samples were collected prospectively from a propensity-score matched cohort including 44 STEMI patients (22 consecutive LMCAD and 22 non-LMCAD), and 22 healthy controls. A comprehensive metabolomics data analysis was performed with Metaboanalyst 3.0 version. The retinol metabolism pathway was shown to have the strongest discriminative power for the LMCAD phenotype. According to biomarker analysis through receiver-operating characteristic curves, 9-cis-retinoic acid (9cRA) dominated the first page of biomarkers, with area under the curve (AUC) value 0.888. Next highest were a biomarker panel consisting of 9cRA, dehydrophytosphingosine, 1H-Indole-3-carboxaldehyde, and another seven variants of lysophosphatidylcholines, exhibiting the highest AUC (0.933). These novel data propose that the retinol metabolism pathway was the strongest differential pathway for the LMCAD phenotype. 9cRA was the most critical biomarker of LMCAD, and a ten-metabolite plasma biomarker panel, in which 9cRA remained the weightiest, may help develop a potent predictive model for LMCAD in clinic.

Topics: Aged; Alitretinoin; Biomarkers; Coronary Artery Disease; Female; Humans; Male; Metabolomics; Middle Aged; ST Elevation Myocardial Infarction