Our study provides the first evidence about significant hypothalamic alterations correlating with clinical outcomes of MS, using 1H-MRS. The combination of increased Glu or mIns with reduced NAA in HYP reflects whole-brain activity of MS. In addition, excess of Glu is linked to severe disease course, depressive mood and fatigue in MS patients, suggesting superiority of Glu over other metabolites in determining MS burden.

Regular physical activity seems to have a positive effect on the microbiota composition of the elderly, but little is known about the added possible benefits of strenuous endurance training. To gain insight into the physiology of the elderly and to identify biomarkers associated with endurance training, we combined different omics approaches. We aimed to investigate the gut microbiome, plasma composition, body composition, cardiorespiratory fitness, and muscle strength of lifetime elderly endurance athletes (LA) age 63.5 (95% CI 61.4, 65.7), height 177.2 (95% CI 174.4, 180.1) cm, weight 77.8 (95% CI 75.1, 80.5) kg, VO2max 42.4 (95% CI 39.8, 45.0) ml.kg–1.min–1 (n = 13) and healthy controls age 64.9 (95% CI 62.1, 67.7), height 174.9 (95% CI 171.2, 178.6) cm, weight 83.4 (95% CI 77.1, 89.7) kg, VO2max 28.9 (95% CI 23.9, 33.9), ml.kg–1.min–1 (n = 9). Microbiome analysis was performed on collected stool samples further subjected to 16S rRNA gene analysis. NMR-spectroscopic analysis was applied to determine and compare selected blood plasma metabolites mostly linked to energy metabolism. The machine learning (ML) analysis discriminated subjects from the LA and CTRL groups using the joint predictors Bacteroides 1.8E + 00 (95% CI 1.1, 2.5)%, 3.8E + 00 (95% CI 2.7, 4.8)% (p = 0.002); Prevotella 1.3 (95% CI 0.28, 2.4)%, 0.1 (95% CI 0.07, 0.3)% (p = 0.02); Intestinimonas 1.3E-02 (95% CI 9.3E-03, 1.7E-02)%, 5.9E-03 (95% CI 3.9E-03, 7.9E-03)% (p = 0.002), Subdoligranulum 7.9E-02 (95% CI 2.5E-02, 1.3E-02)%, 3.2E-02 (95% CI 1.8E-02, 4.6E-02)% (p = 0.02); and the ratio of Bacteroides to Prevotella 133 (95% CI -86.2, 352), 732 (95% CI 385, 1079.3) (p = 0.03), leading to an ROC curve with AUC of 0.94. Further, random forest ML analysis identified VO2max, BMI, and the Bacteroides to Prevotella ratio as appropriate, joint predictors for discriminating between subjects from the LA and CTRL groups. Although lifelong endurance training does not bring any significant benefit regarding overall gut microbiota diversity, strenuous athletic training is associated with higher cardiorespiratory fitness, lower body fat, and some favorable gut microbiota composition, all factors associated with slowing the rate of biological aging.

Weight loss interventions with probiotics have favourable effects on gut microbiota composition and derived metabolites. However, little is known about whether the consumption of natural probiotics, such as Bryndza cheeses, brings similar benefits. The purpose of the study was to find the effect of short-term weight loss programs and Bryndza cheese consumption on the structure of the gut microbiota, microbiota-derived metabolites and body composition in middle-aged women. We conducted a randomised controlled intervention study. Twenty-two female participants with a body fat percentage ≥25% underwent a short weight loss program (4 weeks). Subjects were randomised to either the control or intervention group according to diet. The intervention group comprised 13 participants, whose diet contained 30 g of “Bryndza” cheese daily (WLPB). The control group comprised nine participants without the regular consumption of Bryndza cheese (WLP) in their diet. Both interventions lead to a significant and favourable change of BMI, body fat, waist circumference and muscle mass. Moreover, the relative abundance of Erysipelotrichales significantly increased in both groups. However, the relative abundance of lactic acid bacteria (Lactobacillales, Streptococcaceae, Lactococcus and Streptococcus) significantly increased only in the WLPB group. Furthermore, short-chain fatty acid producers Phascolarctobacterium and Butyricimonas increased significantly in the WLPB group. A short-term weight loss program combined with Bryndza cheese consumption improves body composition and increases the abundance of lactic acid bacteria and short-chain fatty acid producers in middle-aged women.

Cardiac arrest is one of the leading causes of death among adults in older age. Understanding mechanisms how organism responds to ischemia at global level is essential for the prevention and ischemic patient's treatment. In this study, we used a global cerebral ischemia induced by four-vessel occlusion as an established animal model for ischemic stroke to investigate metabolic changes after 24 h reperfusion, when transitions occur due to the onset of delayed neuronal death. We also focused on the endogenous phenomenon known as ischemic tolerance by the pre-ischemic treatment. The experiments were carried out on blood plasma samples as easily available and metabolically reflecting the overall changes in injured organism. Our results imply that disturbed glycolysis pathway, as a consequence of ischemic injury, leads to the increased level of ketone bodies (acetone, acetoacetate and β-hydroxybutyrate) along with increased utilization of triacylglycerols in plasma of ischemic and ischemically preconditioned rats. Complementary to, a decreased level of glycolytic intermediates (lactate, pyruvate, acetate) with increased level of glucose was found in ischemic and preconditioned animals. The protective effect of ischemic preconditioning on metabolome recovery was demonstrated by significantly increased level of creatine compared to ischemic, non-preconditioned rats. We also document that acetoacetate, pyruvate, lactate, and leucine have the best discriminatory power between ischemic and control plasma. Conclusively, our results provide evidence that NMR spectra analysis can identify specific group of metabolites present in plasma with the capability for discrimination between individual groups of animals. In addition, an excellent feasibility for the statistical discrimination among ischemic, preconditioned, and control rats can be applied regardless of native or deproteinated plasma and also regardless of noesy or cpmg NMR acquisition.

The brain tumours represent a complex tissue that has its own characteristic metabolic features and is interfaced with the whole organism. We investigated changes in basal blood plasma metabolites in the presence of primary brain tumour, their correlation with tumour grade, as well as the feasibility of statistical discrimination based on plasma metabolites. Together 60 plasma samples from patients with clinically defined glioblastoma, meningioma, oligodendrioglioma, astrocytoma, and non-specific glial tumour and plasma samples from 28 healthy volunteers without any cancer history were measured by NMR spectroscopy. In blood plasma of primary brain tumour patients, we found significantly increased levels of glycolytic metabolites glucose and pyruvate, and significantly decreased level of glutamine and also metabolites participating in tricarboxylic acid (TCA) cycle, citrate and succinate, when compared with controls. Further, plasma metabolites levels: tyrosine, phenylalanine, glucose, creatine and creatinine correlated significantly with tumour grade. In general, observed changes are parallel to the biochemistry expected for tumourous tissue and metabolic changes in plasma seem to follow the similar rules in all primary brain tumours, with very subtle variations among tumour types. Only two plasma metabolites tyrosine and phenylalanine were increased exclusively in

Several relatively recently published studies have shown changes in plasma metabolites in various viral diseases such as Zika, Dengue, RSV or SARS-CoV-1. The aim of this study was to analyze the metabolome profile of patients during acute COVID-19 approximately one month after the acute infection and to compare these results with healthy (SARS-CoV-2-negative) controls. The metabolome analysis was performed by NMR spectroscopy from the peripheral blood of patients and controls. The blood samples were collected on 3 different occasions (at admission, during hospitalization and on control visit after discharge from the hospital). When comparing sample groups (based on the date of acquisition) to controls, there is an indicative shift in metabolomics features based on the time passed after the first sample was taken towards controls. Based on the random forest algorithm, there is a strong discriminatory predictive value between controls and different sample groups (AUC equals 1 for controls versus samples taken at admission, Mathew correlation coefficient equals 1). Significant metabolomic changes persist in patients more than a month after acute SARS-CoV-2 infection. The random forest algorithm shows very strong discrimination (almost ideal) when comparing metabolite levels of patients in two various stages of disease and during the recovery period compared to SARS-CoV-2-negative controls.

Background: COVID-19 represents a severe inflammatory condition. Our work was designed to monitor the longitudinal dynamics of the metabolomic response of blood plasma and to reveal presumable discrimination in patients with positive and negative outcomes of COVID-19 respiratory symptoms. Methods: Blood plasma from patients, divided into subgroups with positive (survivors) and negative (worsening condition, non-survivors) outcomes, on Days 1, 3, and 7 after admission to hospital, was measured by NMR spectroscopy. Results: We observed changes in energy metabolism in both groups of COVID-19 patients; initial hyperglycaemia, indicating lowered glucose utilisation, was balanced with increased production of 3-hydroxybutyrate as an alternative energy source and accompanied by accelerated protein catabolism manifested by an increase in BCAA levels. These changes were normalised in patients with positive outcome by the seventh day, but still persisted one week after hospitalisation in patients with negative outcome. The initially decreased glutamine plasma level normalised faster in patients with positive outcome. Patients with negative outcome showed a more pronounced Phe/Tyr ratio, which is related to exacerbated and generalised inflammatory processes. Almost ideal discrimination from controls was proved. Conclusions: Distinct metabolomic responses to severe inflammation initiated by SARS-CoV-2 infection may serve towards complementary personalised pharmacological and nutritional support to improve patient outcomes.

Leucine is an essential, ketogenic amino acid with proteinogenic, metabolic, and signaling roles. It is readily imported from the bloodstream into the brain parenchyma. Therefore, it could serve as a putative substrate that is complementing glucose for sustaining the metabolic needs of brain tumor cells. Here, we investigated the ability of cultured human cancer cells to metabolize leucine. Indeed, cancer cells dispose of leucine from their environment and enrich their media with the metabolite 2-oxoisocaproate. The enrichment of the culture media with a high level of leucine stimulated the production of 3-hydroxybutyrate. When 13C6-leucine was offered, it led to an increased appearance of the heavier citrate isotope with a molar mass greater by two units in the culture media. The expression of 3-methylcrotonyl-CoA carboxylase (MCC), an enzyme characteristic for the irreversible part of the leucine catabolic pathway, was detected in cultured cancer cells and human tumor samples by immunoprobing methods. Our results demonstrate that these cancer cells can catabolize leucine and furnish its carbon atoms into the tricarboxylic acid (TCA) cycle. Furthermore, the release of 3-hydroxybutyrate and citrate by cancer cells suggests their capability to exchange these metabolites with their milieu and the capability to participate in their metabolism. This indicates that leucine could be an additional substrate for cancer cell metabolism in the brain parenchyma. In this way, leucine could potentially contribute to the synthesis of metabolites such as lipids, which require the withdrawal of citrate from the TCA cycle.