Adaptation of the AbsoluteIDQ p180 kit to the analysis of metabolites in the human aqueous humor.

The aim of this study was to use the commercial kit AbsoluteIDQ p180 (Biocrates) for the quantification of metabolites in aqueous humor (AH), as well as to determine the optimal volume of AH that is necessary to obtain reliable and reproducible results. Different volumes of AH (10 µl, 20 µl, and 30 µl) were tested. Of the 188 metabolites measurable with the Biocrates kit, 69 were detected in AH. Depending on the volume used, 41, 51, and 63 metabolites were measured using 10 µl, 20 µl, and 30 µl of AH, respectively. The repeatability of the measurements improved with increasing AH volume. Considering only those metabolites that were obtained with a CV < 15%, 34 metabolites at 10 µl, 41 at 20 µl, and 44 at 30 µl AH were received. On this basis, it can be concluded that the tested method can be successfully applied to analyze metabolites in the human AH. To achieve the most comprehensive detection range and highest repeatability of measurements, it is recommended to use 30 µl AH.

Simultaneous Comparison of Aqueous Humor and Serum Metabolic Profiles of Diabetic and Nondiabetic Patients Undergoing Cataract Surgery-A Targeted and Quantitative Metabolomics Study.

The aim of this study was to compare the aqueous humor (AH) and serum concentrations of metabolites in diabetic (n = 36) and nondiabetic (n = 36) senior adults undergoing cataract surgery. Blood samples were collected before surgery and AH during surgery. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted metabolomic and lipidomic analyses of samples were performed using the AbsoluteIDQ® p180 kit. Out of 188 metabolites targeted by the kit, 41 and 133 were detected in >80% of AH and serum samples, respectively. Statistical analysis performed to indicate metabolites differentiating diabetic and nondiabetic patients showed 8 and 20 significant metabolites in AH and serum, respectively. Pathway analysis performed for significant metabolites revealed that galactose metabolism is mostly affected in the AH, while arginine biosynthesis is mostly affected in the serum. Among metabolites that differentiate diabetic and nondiabetic patients, arginine was the only metabolite common to both serum and AH samples, as well as the only one with a decreased concentration in both body fluids of diabetic patients. Concentrations of the rest were elevated in AH and lowered in serum. This may suggest different mechanisms of diabetes-related dysregulation of the local metabolism in the eye in comparison to systemic changes observed in the blood.

Changes in plasma endocannabinoids concentrations correlate with 18F-FDG PET/MR uptake in brown adipocytes in humans.

Introduction: Recent data suggest a possible role of endocannabinoids in the regulation of brown adipose tissue (BAT) activity. Those findings indicate potential treatment options for obesity. The aim of this study was to evaluate the relationship between plasma endocannabinoids concentrations and the presence of BAT in humans. Methods: The study group consisted of 25 subjects divided into two groups: BAT positive BAT(+), (n = 17, median age = 25 years) and BAT negative BAT(-), (n = 8, median age = 28 years). BAT was estimated using 18F-FDG PET/MR after 2 h of cold exposure. The level of plasma endocannabinoids was assessed at baseline, 60 min and 120 min of cold exposure. Results: In both groups, BAT(+) and BAT(-), during the cooling, we observed a decrease of the same endocannabinoids: arachidonoylethanolamide (AEA), eicosapentaenoyl ethanolamide (EPEA) and oleoyl ethanolamide (OEA) with a much more profound decline in BAT(+) subjects. Statistically significant fall of PEA (palmitoylethanolamide) and SEA (stearoylethanolamide) concentrations after 60 min (FC = 0.7, p = 0.007 and FC = 0.8, p = 0.03, respectively) and 120 min (FC = 0.81, p = 0.004, and FC = 0.9, p = 0.01, respectively) of cooling was observed only in individuals with BAT. Conclusion: We noticed the profound decline of endocannabinoids concentrations in subjects with increased 18F-FDG PET/MR uptake in BAT. Identification of a new molecules related to BAT activity may create a new target for obesity treatment.

A comparison of different machine-learning techniques for the selection of a panel of metabolites allowing early detection of brain tumors.

Metabolomics combined with machine learning methods (MLMs), is a powerful tool for searching novel diagnostic panels. This study was intended to use targeted plasma metabolomics and advanced MLMs to develop strategies for diagnosing brain tumors. Measurement of 188 metabolites was performed on plasma samples collected from 95 patients with gliomas (grade I-IV), 70 with meningioma, and 71 healthy individuals as a control group. Four predictive models to diagnose glioma were prepared using 10 MLMs and a conventional approach. Based on the cross-validation results of the created models, the F1-scores were calculated, then obtained values were compared. Subsequently, the best algorithm was applied to perform five comparisons involving gliomas, meningiomas, and controls. The best results were obtained using the newly developed hybrid evolutionary heterogeneous decision tree (EvoHDTree) algorithm, which was validated using Leave-One-Out Cross-Validation, resulting in an F1-score for all comparisons in the range of 0.476-0.948 and the area under the ROC curves ranging from 0.660 to 0.873. Brain tumor diagnostic panels were constructed with unique metabolites, which reduces the likelihood of misdiagnosis. This study proposes a novel interdisciplinary method for brain tumor diagnosis based on metabolomics and EvoHDTree, exhibiting significant predictive coefficients.

Extent of interocular (a)symmetry based on the metabolomic profile of human aqueous humor.

Aims: Interocular comparison of the metabolomic signature of aqueous humor (AH) was performed. The aim of the study was to quantitatively evaluate the symmetry in concentrations of various metabolites belonging to different categories. Methods: The study included AH samples from 23 patients, 74.17 ± 11.52 years old, undergoing simultaneous bilateral cataract surgery at the Ophthalmology Department of the Medical University of Bialystok, Poland. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted metabolomics and lipidomics analyses of AH samples were performed using the AbsoluteIDQ® p180 kit. Out of 188 metabolites available in the kit, 67 were measured in the majority (>70%) of the samples: 21/21 amino acids, 10/22 biogenic amines, 9/40 acylcarnitines, 0/14 lysophosphatidylcholines, 21/76 phosphatidylcholines, 5/15 sphingolipids, and 1/1sum of hexoses. Results: The comparison of both eyes revealed that the concentrations of metabolites did not differ significantly (p < 0.05) except for taurine (p = 0.037). There was moderate-to-strong positive interocular correlation (r > 0.5) between most metabolites regarding concentration. This was confirmed by the high intraclass correlation coefficient (ICC) values of different levels, which varied for the different metabolites. However, there were exceptions. Correlations were not significant for 2 acylcarnitines (tiglylcarnitine and decadienylcarnitine) and 3 glycerophospholipids (PC aa C32:3, PC aa C40:2, and PC aa C40:5). Conclusion: With a few exceptions, a single eye was found to be representative of the fellow eye in terms of the concentration of most of the analyzed metabolites. The degree of intraindividual variability in the AH of fellow eyes differs for particular metabolites/metabolite categories.

Gut Microbiome in Chronic Coronary Syndrome Patients.

Despite knowledge of classical coronary artery disease (CAD) risk factors, the morbidity and mortality associated with this disease remain high. Therefore, new factors that may affect the development of CAD, such as the gut microbiome, are extensively investigated. This study aimed to evaluate gut microbiome composition in CAD patients in relation to the control group. We examined 169 CAD patients and 166 people in the control group, without CAD, matched in terms of age and sex to the study group. Both populations underwent a detailed health assessment. The microbiome analysis was based on the V3-V4 region of the 16S rRNA gene (NGS method). Among 4074 identified taxonomic units in the whole population, 1070 differed between study groups. The most common bacterial types were Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. Furthermore, a higher Firmicutes/Bacteroidetes ratio in the CAD group compared with the control was demonstrated. Firmicutes/Bacteroidetes ratio, independent of age, sex, CAD status, LDL cholesterol concentration, and statins treatment, was related to altered phosphatidylcholine concentrations obtained in targeted metabolomics. Altered alpha-biodiversity (Kruskal-Wallis test, p = 0.001) and beta-biodiversity (Bray-Curtis metric, p < 0.001) in the CAD group were observed. Moreover, a predicted functional analysis revealed some taxonomic units, metabolic pathways, and proteins that might be characteristic of the CAD patients' microbiome, such as increased expressions of 6-phospho-ß-glucosidase and protein-N(pi)-phosphohistidine-sugar phosphotransferase and decreased expressions of DNA topoisomerase, oxaloacetate decarboxylase, and 6-beta-glucosidase. In summary, CAD is associated with altered gut microbiome composition and function.

Assessment of Ceragenins in Prevention of Damage to Voice Prostheses Caused by Candida Biofilm Formation.

This study aimed to investigate the potential application of ceragenins (CSAs) as new candidacidal agents to prevent biofilm formation on voice prostheses (VPs). The deterioration of the silicone material of VPs is caused by biofilm growth on the device which leads to frequent replacement procedures and sometimes serious complications. A significant proportion of these failures is caused by Candida species. We found that CSAs have significant candidacidal activities in vitro (MIC; MFC; MBIC), and they effectively eradicate species of yeast responsible for VP failure. Additionally, in our in vitro experimental setting, when different Candida species were subjected to CSA-13 and CSA-131 during 25 passages, no tested Candida strain showed the significant development of resistance. Using liquid chromatography-mass spectrometry (LC-MS), we found that VP immersion in an ethanol solution containing CSA-131 results in silicon impregnation with CSA-131 molecules, and in vitro testing revealed that fungal biofilm formation on such VP surfaces was inhibited by embedded ceragenins. Future in vivo studies will validate the use of ceragenin-coated VP for improvement in the life quality and safety of patients after a total laryngectomy.

A Preliminary Study Showing the Impact of Genetic and Dietary Factors on GC-MS-Based Plasma Metabolome of Patients with and without PROX1-Genetic Predisposition to T2DM up to 5 Years Prior to Prediabetes Appearance.

Risk factors for type 2 diabetes mellitus (T2DM) consist of a combination of an unhealthy, imbalanced diet and genetic factors that may interact with each other. Single nucleotide polymorphism (SNP) in the prospero homeobox 1 (PROX1) gene is a strong genetic susceptibility factor for this metabolic disorder and impaired ß-cell function. As the role of this gene in T2DM development remains unclear, novel approaches are needed to advance the understanding of the mechanisms of T2DM development. Therefore, in this study, for the first time, postprandial changes in plasma metabolites were analysed by GC-MS in nondiabetic men with different PROX1 genotypes up to 5 years prior to prediabetes appearance. Eighteen contestants (12 with high risk (HR) and 6 with low risk (LR) genotype) participated in high-carbohydrate (HC) and normo-carbohydrate (NC) meal-challenge tests. Our study concluded that both meal-challenge tests provoked changes in 15 plasma metabolites (amino acids, carbohydrates, fatty acids and others) in HR, but not LR genotype carriers. Postprandial changes in the levels of some of the detected metabolites may be a source of potential specific early disturbances possibly associated with the future development of T2DM. Thus, accurate determination of these metabolites can be important for the early diagnosis of this metabolic disease.