Impairment of astrocytic glutaminolysis in glutaric aciduria type I

Cerebral White Matter Alterations Associated With Oligodendrocyte Vulnerability in Organic Acidurias: Insights in Glutaric Aciduria Type I

The white matter is an important constituent of the central nervous system, containing axons, oligodendrocytes, and its progenitor cells, astrocytes, and microglial cells. Oligodendrocytes are central for myelin synthesis, the insulating envelope that protects axons and allows normal neural conduction. Both, oligodendrocytes and myelin, are highly vulnerable to toxic factors in many neurodevelopmental and neurodegenerative disorders associated with disturbances of myelination. Here we review the main alterations in oligodendrocytes and myelin observed in some organic acidurias/acidemias, which correspond to inherited neurometabolic disorders biochemically characterized by accumulation of potentially neurotoxic organic acids and their derivatives. The yet incompletely understood mechanisms underlying the high vulnerability of OLs and/or myelin in glutaric acidemia type I, the most prototypical cerebral organic aciduria, are particularly discussed.

Integrative metabolomics dictate distinctive signature profiles in patients with Tetralogy of Fallot

BACKGROUND

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease (CCHD) with multifactorial etiology. We aimed to investigate the metabolic profiles of CCHD and their independent contributions to TOF.

METHODS

A cohort comprising 42 individuals with TOF and atrial septal defect (ASD) was enrolled. Targeted ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) was employed to systematically analyze metabolite levels and identify TOF-associated metabolic profiles.

RESULTS

Of 370 identified metabolites in tissue and 284 in plasma, over one-third of metabolites showed an association with microbiome. Differential metabolic pathways including amino acids biosynthesis, ABC (ATP-binding cassette) transporters, carbon metabolism, and fatty acid biosynthesis, shed light on TOF biological phenotypes. Additionally, ROC curves identified potential biomarkers, such as erythronic acid with an AUC of 0.868 in plasma, and 3-β-hydroxy-bisnor-5-cholenic acid, isocitric acid, glutaric acid, ortho-Hydroxyphenylacetic acid, picolinic acid with AUC close to 1 in tissue, whereas the discriminative performance of those substances significantly improved when combined with clinical phenotypes.

CONCLUSIONS

Distinct metabolic profiles exhibited robust discriminatory capabilities, effectively distinguishing TOF from ASD patients. These metabolites may serve as biomarkers or key molecular players in the intricate metabolic pathways involved in CCHD development.

IMPACT

Distinct metabolic profiles exhibited robust discriminatory capabilities, effectively distinguishing Tetralogy of Fallot from atrial septal defect patients. Similar profiling but inconsistent differential pathways between plasma and tissue. More than one-third metabolites in plasma and tissue are associated with the microbiome. The discovery of biomarkers is instrumental in facilitating early detection and diagnosis of Tetralogy of Fallot. Disturbed metabolism offers insights into interpretation of pathogenesis of Tetralogy of Fallot.

Novel Approaches to the Establishment of Local Microenvironment from Resorbable Biomaterials in the Brain In Vitro Models

The development of brain in vitro models requires the application of novel biocompatible materials and biopolymers as scaffolds for controllable and effective cell growth and functioning. The "ideal" brain in vitro model should demonstrate the principal features of brain plasticity like synaptic transmission and remodeling, neurogenesis and angiogenesis, and changes in the metabolism associated with the establishment of new intercellular connections. Therefore, the extracellular scaffolds that are helpful in the establishment and maintenance of local microenvironments supporting brain plasticity mechanisms are of critical importance. In this review, we will focus on some carbohydrate metabolites-lactate, pyruvate, oxaloacetate, malate-that greatly contribute to the regulation of cell-to-cell communications and metabolic plasticity of brain cells and on some resorbable biopolymers that may reproduce the local microenvironment enriched in particular cell metabolites.

Identification of Biomarkers for Methamphetamine Exposure Time Prediction in Mice Using Metabolomics and Machine Learning Approaches

Methamphetamine (METH) abuse has become a global public health and safety problem. More information is needed to identify the time of drug abuse. In this study, methamphetamine was administered to male C57BL/6J mice with increasing doses from 5 to 30 mg kg^-1 (once a day, i.p.) for 20 days. Serum and urine samples were collected for metabolomics studies using gas chromatography-mass spectrometry (GC-MS). Six machine learning models were used to infer the time of drug abuse and the best model was selected to predict administration time preliminarily. The metabolic changes caused by methamphetamine were explored. As results, the metabolic patterns of methamphetamine exposure mice were quite different from the control group and changed over time. Specifically, serum metabolomics showed enhanced amino acid metabolism and increased fatty acid consumption, while urine metabolomics showed slowed metabolism of the tricarboxylic acid (TCA) cycle, increased organic acid excretion, and abnormal purine metabolism. Phenylalanine in serum and glutamine in urine increased, while palmitic acid, 5-HT, and monopalmitin in serum and gamma-aminobutyric acid in urine decreased significantly. Among the six machine learning models, the random forest model was the best to predict the exposure time (serum: MAE = 1.482, RMSE = 1.69, R squared = 0.981; urine: MAE = 2.369, RMSE = 1.926, R squared = 0.946). The potential biomarker set containing four metabolites in the serum (palmitic acid, 5-hydroxytryptamine, monopalmitin, and phenylalanine) facilitated the identification of methamphetamine exposure. The random forest model helped predict the methamphetamine exposure time based on these potential biomarkers.

Aging-related markers in rat urine revealed by dynamic metabolic profiling using machine learning

The process of aging and metabolism is intimately intertwined; thus, developing biomarkers related to metabolism is critical for delaying aging. However, few studies have identified reliable markers that reflect aging trajectories based on machine learning. We generated metabolomic profiles from rat urine using ultra-performance liquid chromatography/mass spectrometry. This was dynamically collected at four stages of the rat's age (20, 50, 75, and 100 weeks) for both the training and test groups. Partial least squares-discriminant analysis score plots revealed a perfect separation trajectory in one direction with increasing age in the training and test groups. We further screened 25 aging-related biomarkers through the combination of four algorithms (VIP, time-series, LASSO, and SVM-RFE) in the training group. They were validated in the test group with an area under the curve of 1. Finally, six metabolites, known or novel aging-related markers, were identified, including epinephrine, glutarylcarnitine, L-kynurenine, taurine, 3-hydroxydodecanedioic acid, and N-acetylcitrulline. We also found that, except for N-acetylcitrulline (p < 0.05), the identified aging-related metabolites did not differ between tumor-free and tumor-bearing rats at 100 weeks (p > 0.05). Our findings reveal the metabolic trajectories of aging and provide novel biomarkers as potential therapeutic antiaging targets.

Organic acidurias: Major gaps, new challenges, and a yet unfulfilled promise

Organic acidurias (OADs) comprise a biochemically defined group of inherited metabolic diseases. Increasing awareness, reliable diagnostic work-up, newborn screening programs for some OADs, optimized neonatal and intensive care, and the development of evidence-based recommendations have improved neonatal survival and short-term outcome of affected individuals. However, chronic progression of organ dysfunction in an aging patient population cannot be reliably prevented with traditional therapeutic measures. Evidence is increasing that disease progression might be best explained by mitochondrial dysfunction. Previous studies have demonstrated that some toxic metabolites target mitochondrial proteins inducing synergistic bioenergetic impairment. Although these potentially reversible mechanisms help to understand the development of acute metabolic decompensations during catabolic state, they currently cannot completely explain disease progression with age. Recent studies identified unbalanced autophagy as a novel mechanism in the renal pathology of methylmalonic aciduria, resulting in impaired quality control of organelles, mitochondrial aging and, subsequently, progressive organ dysfunction. In addition, the discovery of post-translational short-chain lysine acylation of histones and mitochondrial enzymes helps to understand how intracellular key metabolites modulate gene expression and enzyme function. While acylation is considered an important mechanism for metabolic adaptation, the chronic accumulation of potential substrates of short-chain lysine acylation in inherited metabolic diseases might exert the opposite effect, in the long run. Recently, changed glutarylation patterns of mitochondrial proteins have been demonstrated in glutaric aciduria type 1. These new insights might bridge the gap between natural history and pathophysiology in OADs, and their exploitation for the development of targeted therapies seems promising.

Fungal Enzyme l-Lysine α-Oxidase Affects the Amino Acid Metabolism in the Brain and Decreases the Polyamine Level

The fungal glycoprotein l-lysine α-oxidase (LO) catalyzes the oxidative deamination of l-lysine (l-lys). LO may be internalized in the intestine and shows antitumor, antibacterial, and antiviral effects in vivo. The main mechanisms of its effects have been shown to be depletion of the essential amino acid l-lys and action of reactive oxidative species produced by the reaction. Here, we report that LO penetrates into the brain and is retained there for up to 48 h after intravenous injection, which might be explained by specific pharmacokinetics. LO actively intervenes in amino acid metabolism in the brain. The most significant impact of LO was towards amino acids, which are directly exposed to its action (l-lys, l-orn, l-arg). In addition, the enzyme significantly affected the redistribution of amino acids directly associated with the tricarboxylic acid (TCA) cycle (l-asp and l-glu). We discovered that the depletion of l-orn, the precursor of polyamines (PA), led to a significant and long-term decrease in the concentration of polyamines, which are responsible for regulation of many processes including cell proliferation. Thus, LO may be used to reduce levels of l-lys and PA in the brain.

Malignant brain tumors in patients with glutaric aciduria type I

Three young patients with glutaric aciduria type I (age 6-23 years) of different ethnic origins, treated for their metabolic disease since early childhood, presented with malignant central nervous system tumors. We recommend continuing clinical follow-up, including monitoring of neurological manifestations and neuroradiological findings, in all patients with glutaric aciduria type I beyond early childhood, especially if adherence to diet is poor or the treatment was not started neonatally.