A novel preliminary metabolomic panel for IHD diagnostics and pathogenesis.

Cardiovascular disease (CVD) represents one of the main causes of mortality worldwide and nearly a half of it is related to ischemic heart disease (IHD). The article represents a comprehensive study on the diagnostics of IHD through the targeted metabolomic profiling and machine learning techniques. A total of 112 subjects were enrolled in the study, consisting of 76 IHD patients and 36 non-CVD subjects. Metabolomic profiling was conducted, involving the quantitative analysis of 87 endogenous metabolites in plasma. A novel regression method of age-adjustment correction of metabolomics data was developed. We identified 36 significantly changed metabolites which included increased cystathionine and dimethylglycine and the decreased ADMA and arginine. Tryptophan catabolism pathways showed significant alterations with increased levels of serotonin, intermediates of the kynurenine pathway and decreased intermediates of indole pathway. Amino acid profiles indicated elevated branched-chain amino acids and increased amino acid ratios. Short-chain acylcarnitines were reduced, while long-chain acylcarnitines were elevated. Based on these metabolites data, machine learning algorithms: logistic regression, support vector machine, decision trees, random forest, and gradient boosting, were used for IHD diagnostic models. Random forest demonstrated the highest accuracy with an AUC of 0.98. The metabolites Norepinephrine; Xanthurenic acid; Anthranilic acid; Serotonin; C6-DC; C14-OH; C16; C16-OH; GSG; Phenylalanine and Methionine were found to be significant and may serve as a novel preliminary panel for IHD diagnostics. Further studies are needed to confirm these findings.

Comparative analysis of tryptophan and downstream metabolites of the kynurenine and serotonin pathways in patients with arterial hypertension and coronary artery disease.

Aim    To compare serum concentrations of tryptophane (Trp) and its metabolites in subjects with no cardiovascular disease (CVD) and patients with СVD, including arterial hypertension (AH) and ischemic heart disease (IHD).Material and methods    This study included 131 participants; 58 participants (11 of them with documented peripheral atherosclerosis) were included into the AH group, 46 participants were included into the IHD group, and 27 participants with no signs of CVD were included into the control group. Plasma concentrations of Trp and its metabolites were measured by high-performance liquid chromatography in combination with a triple quadrupole analyzer.Results    Comparison of the three study groups revealed significant differences in concentrations of Trp (р=0.029), kynurenine (p<0.001), kynurenine/Trp ratio (p<0.001), quinolinic acid (р=0.007), kynurenic acid (р=0.003), serotonin (p<0.001), and 5­hydroxyindoleacetic acid (5­HIAA) (р=0.011). When the AH group was subdivided into subgroups without and with documented peripheral atherosclerosis, the intergroup differences remained for concentrations of kynurenine, kynurenine/Trp ratio, quinolinic acid, kynurenic acid, serotonin, and 5­HIAA. Also, correlations were found between concentrations of Trp metabolites and laboratory and instrumental data, primarily inflammatory markers. Conclusion    Analysis of serum concentrations of Trp and its metabolites in CVD patients showed increases in kynurenine, kynurenine/Trp ratio, quinolinic acid, kynurenic acid, and 5­HIAA along with decreases in concentrations of Trp and serotonin in the groups of AH, AH with documented peripheral atherosclerosis, and IHD.

[Fast HPLC-MS/MS screening method for identification of illegal drugs including new psychoactive substances and their metabolites in human urine]. / Bystraya VEZhKh-MS/MS skriningovaya metodika opredeleniya v moche cheloveka zapreshchennykh narkoticheskikh sredstv, vklyuchaya novye psikhoaktivnye veshchestva, a takzhe ikh metabolity.

Aim of this study was to develop a fast screening method for identification of illegal drugs including new psychoactive substances and their metabolites in human urine by means of liquid chromatography mass-spectrometry HPLC-MS/MS screening method for identification of 138 psychoactive substances in urine was established, validated and tested. High-resolution mass-spectrometry was used for confirmation of the developed approach. The developed method was tested on 50 positive urine samples containing the target compounds, which proved reliability and accuracy of the established screening method.