Metabolomic Assays of Postmortem Brain Extracts: Pitfalls in Extrapolation of Concentrations of Glucose and Amino Acids to Metabolic Dysregulation In Vivo in Neurological Diseases

Mind the Metabolic Gap: Bridging Migraine and Alzheimer's disease through Brain Insulin Resistance

Brain insulin resistance has recently been described as a metabolic abnormality of brain glucose homeostasis that has been proven to downregulate insulin receptors, both in astrocytes and neurons, triggering a reduction in glucose uptake and glycogen synthesis. This condition may generate a mismatch between brain's energy reserve and expenditure, mainly during high metabolic demand, which could be involved in the chronification of migraine and, in the long run, at least in certain subsets of patients, in the prodromic phase of Alzheimer's disease, along a putative metabolic physiopathological continuum. Indeed, the persistent disruption of glucose homeostasis and energy supply to neurons may eventually impair protein folding, an energy-requiring process, promoting pathological changes in Alzheimer's disease, such as amyloid-β deposition and tau hyperphosphorylation. Hopefully, the "neuroenergetic hypothesis" presented herein will provide further insight on there being a conceivable metabolic bridge between chronic migraine and Alzheimer's disease, elucidating novel potential targets for the prophylactic treatment of both diseases.

Integrated metabolomics and proteomics analysis of plasma lipid metabolism in Parkinson's disease

INTRODUCTION

Metabolomics and proteomics are two growing fields of science which may shed light on the molecular mechanisms that contribute to neurodegenerative diseases. Studies focusing on these aspects can reveal specific metabolites and proteins that can halt or reverse the progressive neurodegenerative process leading to dopaminergic cell death in the brain.

AREAS COVERED

In this article, an overview of the current status of metabolomic and proteomic profiling in the neurodegenerative disease such as Parkinson's disease (PD) is presented. We discuss the importance of state-of-the-art metabolomics and proteomics using advanced analytical methodologies and their potential for discovering new biomarkers in PD. We critically review the research to date, highlighting how metabolomics and proteomics can have an important impact on early disease diagnosis, future therapy development and the identification of new biomarkers. Finally, we will discuss interactions between lipids and α-synuclein (SNCA) and also consider the role of SNCA in lipid metabolism.

EXPERT OPINION

Metabolomic and proteomic studies contribute to understanding the biological basis of PD pathogenesis, identifying potential biomarkers and introducing new therapeutic strategies. The complexity and multifactorial nature of this disease requires a comprehensive approach, which can be achieved by integrating just these two omic studies.

Orthogonal approaches required to measure proteasome composition and activity in mammalian brain tissue

Proteasomes are large macromolecular complexes with multiple distinct catalytic activities that are each vital to human brain health and disease. Despite their importance, standardized approaches to investigate proteasomes have not been universally adapted. Here, we describe pitfalls and define straightforward orthogonal biochemical approaches essential to measure and understand changes in proteasome composition and activity in the mammalian central nervous system. Through our experimentation in the mammalian brain, we determined an abundance of catalytically active proteasomes exist with and without a 19S cap(s), the regulatory particle essential for ubiquitin-dependent degradation. Moreover, we learned that in-cell measurements using activity-based probes (ABPs) are more sensitive in determining the available activity of the 20S proteasome without the 19S cap and in measuring individual catalytic subunit activities of each β subunit within all neuronal proteasomes. Subsequently, applying these tools to human brain samples, we were surprised to find that post-mortem tissue retained little to no 19S-capped proteasome, regardless of age, sex, or disease state. Comparing brain tissues (parahippocampal gyrus) from human Alzheimer's disease (AD) patients and unaffected subjects, available 20S proteasome activity was significantly elevated in severe cases of AD, an observation not previously noted. Taken together, our study establishes standardized approaches for comprehensive investigation of proteasomes in mammalian brain tissue, and we reveal new insight into brain proteasome biology.

Potential new roles for glycogen in epilepsy

Seizures often originate in epileptogenic foci. Between seizures (interictally), these foci and some of the surrounding tissue often show low signals with 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) in many epileptic patients, even when there are no radiologically detectable structural abnormalities. Low FDG-PET signals are thought to reflect glucose hypometabolism. Here, we review knowledge about metabolism of glucose and glycogen and oxidative stress in people with epilepsy and in acute and chronic rodent seizure models. Interictal brain glucose levels are normal and do not cause apparent glucose hypometabolism, which remains unexplained. During seizures, high amounts of fuel are needed to satisfy increased energy demands. Astrocytes consume glycogen as an additional emergency fuel to supplement glucose during high metabolic demand, such as during brain stimulation, stress, and seizures. In rodents, brain glycogen levels drop during induced seizures and increase to higher levels thereafter. Interictally, in people with epilepsy and in chronic epilepsy models, normal glucose but high glycogen levels have been found in the presumed brain areas involved in seizure generation. We present our new hypothesis that as an adaptive response to repeated episodes of high metabolic demand, high interictal glycogen levels in epileptogenic brain areas are used to support energy metabolism and potentially interictal neuronal activity. Glycogenolysis, which can be triggered by stress or oxidative stress, leads to decreased utilization of plasma glucose in epileptogenic brain areas, resulting in low FDG signals that are related to functional changes underlying seizure onset and propagation. This is (partially) reversible after successful surgery. Last, we propose that potential interictal glycogen depletion in epileptogenic and surrounding areas may cause energy shortages in astrocytes, which may impair potassium buffering and contribute to seizure generation. Based on these hypotheses, auxiliary fuels or treatments that support glycogen metabolism may be useful to treat epilepsy.

Stability of Metabolomic Content during Sample Preparation: Blood and Brain Tissues

Thermal and enzymatic reactions can significantly change the tissue metabolomic content during the sample preparation. In this work, we evaluated the stability of metabolites in human whole blood, serum, and rat brain, as well as in metabolomic extracts from these tissues. We measured the concentrations of 63 metabolites in brain and 52 metabolites in blood. We have shown that metabolites in the extracts from biological tissues are stable within 24 h at 4 °C. Serum and whole blood metabolomes are also rather stable, changes in metabolomic content of the whole blood homogenate become apparent only after 1–2 h of incubation at 4 °C, and become strong after 24 h. The most significant changes correspond to energy metabolites: the concentrations of ATP and ADP decrease fivefold, and the concentrations of NAD, NADH, and NADPH decrease below the detectable level. A statistically significant increase was observed for AMP, IMP, hypoxanthine, and nicotinamide. The brain tissue is much more metabolically active than human blood, and significant metabolomic changes occur already within the first several minutes during the brain harvest and sample homogenization. At a longer timescale (hours), noticeable changes were observed for all classes of compounds, including amino acids, organic acids, alcohols, amines, sugars, nitrogenous bases, nucleotides, and nucleosides.

High Resolution Magic Angle Spinning Proton NMR Study of Alzheimer's Disease with Mouse Models

Alzheimer's disease (AD) is a crippling condition that affects millions of elderly adults each year, yet there remains a serious need for improved methods of diagnosis. Metabolomic analysis has been proposed as a potential methodology to better investigate and understand the progression of this disease; however, studies of human brain tissue metabolomics are challenging, due to sample limitations and ethical considerations. Comprehensive comparisons of imaging measurements in animal models to identify similarities and differences between aging- and AD-associated metabolic changes should thus be tested and validated for future human non-invasive studies. In this paper, we present the results of our highresolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) studies of AD and wild-type (WT) mouse models, based on animal age, brain regions, including cortex vs. hippocampus, and disease status. Our findings suggest the ability of HRMAS NMR to differentiate between AD and WT mice using brain metabolomics, which potentially can be implemented in in vivo evaluations.

Metabolomics in degenerative brain diseases

Among the most studied diseases that affect the central nervous system are Parkinson's, Alzheimer's, and Huntington's diseases, but the lack of effective biomarkers, accurate diagnosis, and precise treatment for each of them is currently an issue. Due to the contribution of biomarkers in supporting diagnosis, many recent efforts have focused on their identification and validation at the beginning or during the progression of the mental illness. Metabolome reveals the metabolic processes that result from protein activities under the guided gene expression and environmental factors, either in healthy or pathological conditions. In this context, metabolomics has proven to be a valuable approach. Currently, magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the most commonly used bioanalytical techniques for metabolomics. MS-assisted profiling is considered the most versatile technique, and the NMR is the most reproductive. However, each one of them has its drawbacks. In this review, we summarized several alterations in metabolites that have been reported for these three classic brain diseases using MS and NMR-based research, which might suggest some possible biomarkers to support the diagnosis and/or new targets for their treatment.

Phenylalanine Metabolism is Dysregulated in Human Hippocampus with Alzheimer's Disease Related Pathological Changes

BACKGROUND

Alzheimer's disease (AD) is one of the most challenging diseases causing an increasing burden worldwide. Although the neuropathologic diagnosis of AD has been established for many years, the metabolic changes in neuropathologic diagnosed AD samples have not been fully investigated.

OBJECTIVE

To elucidate the potential metabolism dysregulation in the postmortem human brain samples assessed by AD related pathological examination.

METHODS

We performed untargeted and targeted metabolomics in 44 postmortem human brain tissues. The metabolic differences in the hippocampus between AD group and control (NC) group were compared.

RESULTS

The results show that a pervasive metabolic dysregulation including phenylalanine metabolism, valine, leucine, and isoleucine biosynthesis, biotin metabolism, and purine metabolism are associated with AD pathology. Targeted metabolomics reveal that phenylalanine, phenylpyruvic acid, and N-acetyl-L-phenylalanine are upregulated in AD samples. In addition, the enzyme IL-4I1 catalyzing transformation from phenylalanine to phenylpyruvic acid is also upregulated in AD samples.

CONCLUSION

There is a pervasive metabolic dysregulation in hippocampus with AD-related pathological changes. Our study suggests that the dysregulation of phenylalanine metabolism in hippocampus may be an important pathogenesis for AD pathology formation.

Stop the rot. Enzyme inactivation at brain harvest prevents artifacts: A guide for preservation of the in vivo concentrations of brain constituents

Post-mortem metabolism is widely recognized to cause rapid and prolonged changes in the concentrations of multiple classes of compounds in brain, that is, they are labile. Post-mortem changes from levels in living brain include components of pathways of metabolism of glucose and energy compounds, amino acids, lipids, signaling molecules, neuropeptides, phosphoproteins, and proteins. Methods that stop enzyme activity at brain harvest were developed almost 50 years ago and have been extensively used in studies of brain functions and diseases. Unfortunately, these methods are not commonly used to harvest brain tissue for mass spectrometry-based metabolomic studies or for imaging mass spectrometry studies (IMS, also called mass spectrometry imaging, MSI, or matrix-assisted laser desorption/ionization-MSI, MALDI-MSI). Instead these studies commonly kill animals, decapitate, dissect out brain and regions of interest if needed, then 'snap' freeze the tissue to stop enzymatic activity after harvest, with post-mortem intervals typically ranging from ~0.5 to 3 min. To increase awareness of the importance of stopping metabolism at harvest and preventing the unnecessary complications of not doing so, this commentary provides examples of labile metabolites and the magnitudes of their post-mortem changes in concentrations during brain harvest. Brain harvest methods that stop metabolism at harvest eliminate post-mortem enzymatic activities and can improve characterization of normal and diseased brain. In addition, metabolomic studies would be improved by reporting absolute units of concentration along with normalized peak areas or fold changes. Then reported values can be evaluated and compared with the extensive neurochemical literature to help prevent reporting of artifactual data.

Metabolomic and Imaging Mass Spectrometric Assays of Labile Brain Metabolites: Critical Importance of Brain Harvest Procedures

Metabolomic technologies including imaging mass spectrometry (IMS; also called mass spectrometry imaging, MSI, or matrix-assisted laser desorption/ionization-mass spectrometry imaging, MALDI MSI) are important methods to evaluate levels of many compounds in brain with high spatial resolution, characterize metabolic phenotypes of brain disorders, and identify disease biomarkers. ATP is central to brain energetics, and reports of its heterogeneous distribution in brain and regional differences in ATP/ADP ratios reported in IMS studies conflict with earlier studies. These discordant data were, therefore, analyzed and compared with biochemical literature that used rigorous methods to preserve labile metabolites. Unequal, very low regional ATP levels and low ATP/ADP ratios are explained by rapid metabolism during postmortem ischemia. A critical aspect of any analysis of brain components is their stability during and after tissue harvest so measured concentrations closely approximate their physiological levels in vivo. Unfortunately, the requirement for inactivation of brain enzymes by freezing or heating is not widely recognized outside the neurochemistry discipline, and procedures that do not prevent postmortem autolysis, including decapitation, brain removal/dissection, and 'snap freezing' are commonly used. Strong emphasis is placed on use of supplementary approaches to calibrate metabolite abundance in units of concentration in IMS studies and comparison of IMS results with biochemical data obtained by different methods to help identify potential artifacts.

Postmortem metabolomics: Correlating time-dependent concentration changes of xenobiotic and endogenous compounds

Postmortem redistribution (PMR) describes the artificial postmortem concentration changes of xenobiotics that may pose major challenges in forensic toxicology. Only a few studies have systematically investigated time-dependent postmortem drug concentration changes so far and the a posteriori estimation of the occurrence of PMR is not yet possible. In this context, the general concept that postmortem biochemical changes in blood might parallel drug redistribution mechanisms seems promising. Thus, the current study investigated the possible correlations between time-dependent postmortem concentration changes of xenobiotic and endogenous compounds; exemplified for authentic morphine (n = 19) and methadone (n = 11) cases. Peripheral blood samples at two time-points postmortem were analyzed for morphine and methadone concentrations and an (un)targeted postmortem metabolomics approach was utilized to combine targeted quantitative analysis of 56 endogenous analytes and untargeted screening for endogenous compounds (characterizing 1174 features); liquid and gas chromatography-mass spectrometry was used respectively. Individual statistically significant correlations between morphine/methadone and endogenous compounds/features could be determined. Hence, the general applicability of the proposed concept could successfully be confirmed. To verify the reproducibility and robustness of the correlating behavior, a larger dataset must be analyzed next. Once a marker/set of markers is found (e.g. robust correlation with specific xenobiotic or xenobiotic class), these could be used as surrogates to further study the time-dependent PMR in a broader variety of cases (e.g. independent of a xenobiotic drug present). A crucial next step will also be the attempt to create a statistical model that allows a posteriori estimation of PMR occurrence of xenobiotics to assist forensic toxicologists in postmortem case interpretation.

Analytical considerations for postmortem metabolomics using GC-high-resolution MS

Metabolomics studies that aim to qualitatively and quantitatively characterize the entirety of small endogenous biomolecules in an organism are widely conducted in the clinical setting. They also become more and more popular in the field of forensics (toxicology), e.g., to assist in postmortem investigations by objective postmortem interval estimation. However, other issues in postmortem toxicology, such as the phenomenon of (time-dependent) postmortem redistribution, have not yet been tackled by metabolomics studies. Hence, the aim of the current study was to develop an (un)targeted gas chromatography-high-resolution mass spectrometry-based method for endogenous metabolites as a tool for large-scale (un)targeted human postmortem metabolomics investigations (e.g., to objectively assess PMR) with thorough analytical evaluation of this method to ensure fitness-to-purpose in terms of reliability and robustness. This was achieved by using a targeted metabolite subset (n = 56) and a targeted processing workflow. Evaluation experiments have shown that using an artificial matrix (revised simulated body fluid (rSBF) + 5% bovine serum albumin (BSA)) for calibration purposes, all parameters lay within the scope of the method (sensitivity, selectivity, calibration model, accuracy, precision, processed sample stability, and extraction efficiency). When applying this method to large-scale studies, samples should be run in randomized order if analysis time is expected to exceed 18-24 h and potential biomarkers that are found with this method should be verified by a specialized, targeted method (e.g., by using standard addition in authentic matrix for quantification purposes). Overall, the current method can be successfully used for conduction of time-dependent postmortem metabolomics investigations. Graphical abstract.