In Vivo Targeted Metabolomic Profiling of Prostanit, a Novel Anti-PAD NO-Donating Alprostadil-Based Drug.

Prostanit is a novel drug developed for the treatment of peripheral arterial diseases. It consists of a prostaglandin E1 (PGE1) moiety with two nitric oxide (NO) donor fragments, which provide a combined vasodilation effect on smooth muscles and vascular spastic reaction. Prostanit pharmacokinetics, however, remains poorly investigated. Thus, the object of this study was to investigate the pharmacokinetics of Prostanit-related and -affected metabolites in rabbit plasma using the liquid chromatography-mass spectrometry (LC-MS) approach. Besides, NO generation from Prostanit in isolated rat aorta and human smooth muscle cells was studied using the Griess method. In plasma, Prostanit was rapidly metabolized to 1,3-dinitroglycerol (1,3-DNG), PGE1, and 13,14-dihydro-15-keto-PGE1. Simultaneously, the constant growth of amino acid (proline, 4-hydroxyproline, alanine, phenylalanine, etc.), steroid (androsterone and corticosterone), and purine (adenosine, adenosine-5 monophosphate, and guanosine) levels was observed. Glycine, aspartate, cortisol, and testosterone levels were decreased. Ex vivo Prostanit induced both NO synthase-dependent and -independent NO generation. The observed pharmacokinetic properties suggested some novel beneficial activities (i.e., effect prolongation and anti-inflammation). These properties may provide a basis for future research of the effectiveness and safety of Prostanit, as well as for its characterization from a clinical perspective.

Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults.

Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors in patients diagnosed with arterial hypertension (HTA) (n = 61), coronary artery disease (CAD) (n = 48), and non-cardiovascular disease (CVD) individuals (n = 27). In total, almost all significantly different acylcarnitines, amino acids, methylarginines, and intermediates of the kynurenic and indolic tryptophan conversion pathways presented increased (p < 0.05) in concentration levels during the progression of CVD, indicating an association of inflammation, mitochondrial imbalance, and oxidative stress with early stages of CVD. Additionally, the random forest algorithm was found to have the highest prediction power in multiclass and binary classification patients with CAD, HTA, and non-CVD individuals and globally between CVD and non-CVD individuals (accuracy equal to 0.80 and 0.91, respectively). Thus, the present study provided a complex approach for the risk stratification of patients with CAD, patients with HTA, and non-CVD individuals using targeted metabolomics profiling.

Pharmacokinetic Properties of the Novel Synthetic Cannabinoid 5F-APINAC and Its Influence on Metabolites Associated with Neurotransmission in Rabbit Plasma.

The strong psychoactive effects of synthetic cannabinoids raise the need for the deeper studying of their neurometabolic effects. The pharmacokinetic properties of 5F-APINAC and its influence on metabolomics profiles associated with neurotransmission were investigated in rabbit plasma. Twelve rabbits divided into three groups received 1-mL 5F-APINAC at 0.1, 1 and 2 mg/kg. The intervention groups were compared with the controls. Sampling was performed at nine time points (0-24 h). Ultra-high-performance liquid chromatography-tandem mass spectrometry was used. The pharmacokinetics were dose-dependent (higher curve at a higher dose) with a rapid biotransformation, followed by gradual elimination within 24 h. The tryptophan concentrations abruptly decreased (p < 0.05) in all tested groups, returning to the basal levels after 6 h. 5-hydroxylindole acetic acid increased (p < 0.05) in the controls, but this trend was absent in the treated groups. The aspartic acid concentrations were elevated (p < 0.001) in the treated groups. L-kynurenine was elevated (p < 0.01) in the intervention groups receiving 1 mg/kg to 2 mg/kg. Dose-dependent elevations (p < 0.01) were found for kynurenic acid, xanthurenic acid and quinolinic acid (p < 0.01), whereas the anthranilic acid trends were decreased (p < 0.01). The indole-3-propionic acid and indole-3-carboxaldehyde trends were elevated (p < 0.05), whereas the indole-3-lactic acid trajectories were decreased (p < 0.01) in the intervention groups. 5F-APINAC administration had a rapid biotransformation and gradual elimination. The metabolites related to the kynurenine and serotonergic system/serotonin pathways, aspartic acid innervation system and microbial tryptophan catabolism were altered.

Relationship between the plasma acylcarnitine profile and cardiometabolic risk factors in adults diagnosed with cardiovascular diseases.

The development of cardiovascular diseases (CVDs) is often asymptomatic. Identification of initial indicators of cardiometabolic disruption may assist in its early detection. The objective was to determine the relationships between plasma acylcarnitines (ACs) and cardiometabolic risk factors in adults with and without CVDs. The AC profile in human plasma of healthy controls [non-CVD group, n = 13)] and individuals diagnosed with CVDs (CVD group, n = 34) were compared. A targeted analysis of 29 ACs was performed using flow injection analysis-tandem mass spectrometry. There were significant direct correlations (p < 0.05) between ACs and cardiometabolic risk factors. Comparing the groups after adjustment for covariates, showed that the ACs that were best differentiated (p < 0.05) between the two groups and that presented "good" diagnostic accuracy were carnitine [30.7 (25.5-37.7) vs. 37.7 (32.3-45.0) µM], the short-chain ACs: acetylcarnitine [8.9 (7.4-10.2) vs. 11.9 (9.2-14.4) µM] and isovalerylcarnitine [0.10 (0.06-0.13) vs. 0.13 (0.10-0.16) µM], and the medium-chain ACs: hexanoylcarnitine [0.04 (0.03-0.05) vs. 0.06 (0.05-0.07) µM] and decenoylcarnitine [0.18 (0.12-0.22) vs. 0.22 (0.17-0.32) µM]. This assessment contributes to the identification of the unique metabolic features exhibited in association with cardiometabolic risk in adults diagnosed with CVD. The altered metabolites have the potential to be used as biomarkers for early detection of CVD.