Application of metabolomics based on direct mass spectrometry analysis for the elucidation of altered metabolic pathways in serum from the APP/PS1 transgenic model of Alzheimer's disease

Metabolomics profiling reveals distinct, sex-specific signatures in serum and brain metabolomes in mouse models of Alzheimer's disease

INTRODUCTION

Increasing evidence suggests that metabolic impairments contribute to early Alzheimer's disease (AD) mechanisms and subsequent dementia. Signals in metabolic pathways conserved across species can facilitate translation.

METHODS

We investigated differences in serum and brain metabolites between the early-onset 5XFAD and late-onset LOAD1 (APOE4.Trem2*R47H) mouse models of AD to C57BL/6J controls at 6 months of age.

RESULTS

We identified sex differences for several classes of metabolites, such as glycerophospholipids, sphingolipids, and amino acids. Metabolic signatures were notably different between brain and serum in both mouse models. The 5XFAD mice exhibited stronger differences in brain metabolites, whereas LOAD1 mice showed more pronounced differences in serum.

DISCUSSION

Several of our findings were consistent with results in humans, showing glycerophospholipids reduction in serum of apolipoprotein E (apoE) ε4 carriers and replicating the serum metabolic imprint of the APOE ε4 genotype. Our work thus represents a significant step toward translating metabolic dysregulation from model organisms to human AD.

HIGHLIGHTS

This was a metabolomic assessment of two mouse models relevant to Alzheimer's disease. Mouse models exhibit broad sex-specific metabolic differences, similar to human study cohorts. The early-onset 5XFAD mouse model primarily alters brain metabolites while the late-onset LOAD1 model primarily changes serum metabolites. Apolipoprotein E (apoE) ε4 mice recapitulate glycerophospolipid signatures of human APOE ε4 carriers in both brain and serum.

Mass Spectrometry-Based Metabolomics Multi-platform for Alzheimer's Disease Research

The integration of complementary analytical platforms is nowadays the most common strategy for comprehensive metabolomics analysis of complex biological systems. In this chapter, we describe methods and tips for the application of a mass spectrometry multi-platform in Alzheimer's disease research, based on the combination of direct mass spectrometry and orthogonal hyphenated approaches, namely, reversed-phase ultrahigh-performance liquid chromatography and gas chromatography. These procedures have been optimized for the analysis of multiple biological samples from human patients and transgenic animal models, including blood serum, various brain regions (e.g., hippocampus, cortex, cerebellum, striatum, olfactory bulbs), and other peripheral organs (e.g., liver, kidney, spleen, thymus).

How far are we from reliable metabolomics-based biomarkers? The often-overlooked importance of addressing inter-individual variability factors

Metabolomics has proven great potential to unravel the molecular basis of diseases. However, most attempts aimed at identifying reliable metabolomics-based biomarkers for diagnosis, prediction, and prognosis of diseases have repeatedly failed because of inconsistent results and unsatisfactory replication in independent cohorts. This review article explores the possible causes behind this reproducibility crisis, with special focus on the role that inter-individual variability factors play in modulating the susceptibility to disease development. Furthermore, we provide future perspectives on the applicability of metabolomics in biomedical research and its translatability into clinical practice.

Metabolomics profiling reveals distinct, sex-specific signatures in the serum and brain metabolomes in the mouse models of Alzheimer's disease

INTRODUCTION

Increasing evidence suggests that metabolic impairments contribute to early Alzheimer's disease (AD) mechanisms and subsequent dementia. Signals in metabolic pathways conserved across species provides a promising entry point for translation. METHODS: We investigated differences of serum and brain metabolites between the early-onset 5XFAD and late-onset LOAD1 (APOE4.Trem2*R47H) mouse models of AD to C57BL/6J controls at six months of age.

RESULTS

We identified sex differences for several classes of metabolites, such as glycerophospholipids, sphingolipids, and amino acids. Metabolic signatures were notably different between brain and serum in both mouse models. The 5XFAD mice exhibited stronger differences in brain metabolites, whereas LOAD1 mice showed more pronounced differences in serum.

DISCUSSION

Several of our findings were consistent with results in humans, showing glycerophospholipids reduction in serum of APOE4 carriers and replicating the serum metabolic imprint of the APOE4 genotype. Our work thus represents a significant step towards translating metabolic dysregulation from model organisms to human AD.

Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.

Systematic review of brain and blood lipidomics in Alzheimer's disease mouse models

Alzheimer's disease (AD) diagnosis is based on invasive and expensive biomarkers. Regarding AD pathophysiological mechanisms, there is evidence of a link between AD and aberrant lipid homeostasis. Alterations in lipid composition have been observed in blood and brain samples, and transgenic mouse models represent a promising approach. Nevertheless, there is great variability among studies in mice for the determination of different types of lipids in targeted and untargeted methods. It could be explained by the different variables (model, age, sex, analytical technique), and experimental conditions used. The aim of this work is to review the studies on lipid alteration in brain tissue and blood samples from AD mouse models, focusing on different experimental parameters. As result, great disparity has been observed among the reviewed studies. Brain studies showed an increase in gangliosides, sphingomyelins, lysophospholipids and monounsaturated fatty acids and a decrease in sulfatides. In contrast, blood studies showed an increase in phosphoglycerides, sterols, diacylglycerols, triacylglycerols and polyunsaturated fatty acids, and a decrease in phospholipids, lysophospholipids and monounsaturated fatty acids. Thus, lipids are closely related to AD, and a consensus on lipidomics studies could be used as a diagnostic tool and providing insight into the mechanisms involved in AD.

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Alzheimer's disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

Chronic treatment with baicalein alleviates behavioural disorders and improves cerebral blood flow via reverting metabolic abnormalities in a J20 transgenic mouse model of Alzheimer's disease

Baicalein (BE) has both antioxidant and anti-inflammatory effects. It has also been reported able to improve cerebral blood circulation in brain ischemic injury. However, its chronic efficacy and metabolomics in Alzheimer's disease (AD) remain unknown. In this study, BE at 80 mg/kg was administrated through the oral route in J20 AD transgenic mice aged from aged 4 months to aged 10 months. Metabolic- and neurobehavioural phenotyping was done before and after 6 months' treatment to evaluate the drug efficacy and the relevant mechanisms. Meanwhile, molecular docking was used to study the binding affinity of BE and poly (ADP-ribose) polymerase-1 (PARP-1) which is related to neuronal injury. The open field test showed that BE could suppress hyperactivity in J20 mice and increase the frequency of the target quadrant crossing in the Morris Water Maze test. More importantly, BE restored cerebral blood flow back to the normal level after the chronic treatment. A ¹H NMR-based metabolomics study showed that BE treatment could restore the tricarboxylic acid cycle in plasma. And such a treatment could suppress oxidative stress, inhibit neuroinflammation, alleviate mitochondrial dysfunction, improve neurotransmission, and restore amino homeostasis via starch and sucrose metabolism and glycolipid metabolism in the cortex and hippocampus, which could affect the behavioural and cerebral blood flow. These findings showed that BE is a potential therapeutic agent for AD.

Molecular insights into sex-specific metabolic alterations in Alzheimer's mouse brain using multi-omics approach

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is characterized by altered cellular metabolism in the brain. Several of these alterations have been found to be exacerbated in females, known to be disproportionately affected by AD. We aimed to unravel metabolic alterations in AD at the metabolic pathway level and evaluate whether they are sex-specific through integrative metabolomic, lipidomic, and proteomic analysis of mouse brain tissue.

METHODS

We analyzed male and female triple-transgenic mouse whole brain tissue by untargeted mass spectrometry-based methods to obtain a molecular signature consisting of polar metabolite, complex lipid, and protein data. These data were analyzed using multi-omics factor analysis. Pathway-level alterations were identified through joint pathway enrichment analysis or by separately evaluating lipid ontology and known proteins related to lipid metabolism.

RESULTS

Our analysis revealed significant AD-associated and in part sex-specific alterations across the molecular signature. Sex-dependent alterations were identified in GABA synthesis, arginine biosynthesis, and in alanine, aspartate, and glutamate metabolism. AD-associated alterations involving lipids were also found in the fatty acid elongation pathway and lysophospholipid metabolism, with a significant sex-specific effect for the latter.

CONCLUSIONS

Through multi-omics analysis, we report AD-associated and sex-specific metabolic alterations in the AD brain involving lysophospholipid and amino acid metabolism. These findings contribute to the characterization of the AD phenotype at the molecular level while considering the effect of sex, an overlooked yet determinant metabolic variable.

Inosine in Neurodegenerative Diseases: From the Bench to the Bedside

Neurodegenerative diseases, such as Alzheimer′s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS), currently represent major unmet medical needs. Therefore, novel therapeutic strategies are needed in order to improve patients’ quality of life and prognosis. Since oxidative stress can be strongly involved in neurodegenerative diseases, the potential use of inosine, known for its antioxidant properties, in this context deserves particular attention. The protective action of inosine treatment could be mediated by its metabolite urate. Here, we review the current preclinical and clinical studies investigating the use of inosine in AD, PD, ALS, and MS. The most important properties of inosine seem to be its antioxidant action and its ability to raise urate levels and to increase energetic resources by improving ATP availability. Inosine appears to be generally safe and well tolerated; however, the possible formation of kidney stones should be monitored, and data on its effectiveness should be further explored since, so far, they have been controversial. Overall, inosine could be a promising potential strategy in the management of neurodegenerative diseases, and additional studies are needed in order to further investigate its safety and efficacy and its use as a complementary therapy along with other approved drugs.

Omics sciences for systems biology in Alzheimer's disease: State-of-the-art of the evidence

Alzheimer's disease (AD) is characterized by non-linear, genetic-driven pathophysiological dynamics with high heterogeneity in biological alterations and disease spatial-temporal progression. Human in-vivo and post-mortem studies point out a failure of multi-level biological networks underlying AD pathophysiology, including proteostasis (amyloid-β and tau), synaptic homeostasis, inflammatory and immune responses, lipid and energy metabolism, oxidative stress. Therefore, a holistic, systems-level approach is needed to fully capture AD multi-faceted pathophysiology. Omics sciences - genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics - embedded in the systems biology (SB) theoretical and computational framework can generate explainable readouts describing the entire biological continuum of a disease. Such path in Neurology is encouraged by the promising results of omics sciences and SB approaches in Oncology, where stage-driven pathway-based therapies have been developed in line with the precision medicine paradigm. Multi-omics data integrated in SB network approaches will help detect and chart AD upstream pathomechanistic alterations and downstream molecular effects occurring in preclinical stages. Finally, integrating omics and neuroimaging data - i.e., neuroimaging-omics - will identify multi-dimensional biological signatures essential to track the clinical-biological trajectories, at the subpopulation or even individual level.

An elaborative NMR based plasma metabolomics study revealed metabolic derangements in patients with mild cognitive impairment: a study on north Indian population

Mild cognitive impairment (MCI) is transition phase between cognitive decline and dementia. The current study aims to investigate altered metabolic pattern in plasma of MCI for potential biomarkers. MCI (N = 50) and healthy controls (HC, N = 50) age group 55-75 years were screened based on Mini Mental State Examination Test (MMSE) and diffusion tensor imaging (DTI imaging). The MMSE score of MCI was significantly lower (25.74 ± 1.83) compared to healthy control subjects (29 ± 1). The MCI patients exhibit significant changes in white matter integrity in the right frontal lobe, right temporal lobe, left frontal lobe, forcep major, fornix, corpus callosum. Further, the plasma samples of twenty seven MCI patients (N = 27) and twenty HC subjects (N = 20; having no significant differences in any demographics) were analyzed using ¹H NMR based metabolomics approach. Consistent with many previous reports, the levels of several plasma metabolites were found to be elevated in MCI patients compared to healthy controls. Further univariate and multivariate ROC curve analyses provided three plasma metabolites as a diagnostic panel of biomarker for MCI; which are lysine, glycine, and glutamine. Overall, the results of this study will help to improve the diagnostic and prognostic strategies of MCI in addition to improving our understanding about disease pathogenesis. We believe that the over-nutritional metabolic phenotype of MCI needs to be targeted for developing future dietary interventions so that the progression of MCI can be limited. Metabolic derangements associated with Mild Cognitive Impairment.

Brain Lipid Dynamics in Amyloid Precursor Protein/Presenilin 1 Mouse Model of Early Alzheimer's Disease by Desorption Electrospray Ionization and Matrix Assisted Laser Desorption Ionization-Mass Spectrometry Imaging Techniques

Alzheimer's disease (AD) is closely associated with lipid metabolism dysfunction. However, space distribution and metabolism of aberrant lipids in the brain of early-stage AD mouse remain unclear. In our current work, a novel lipidomics method based on mass spectrometry imaging was developed to visually disclose molecular perturbation and characterize space distribution in the brain of double transgenic amyloid precursor protein/presenilin 1 mouse (2 and 3 months old). Significant changes were detected, including phosphatidylethanolamines, phosphatidylcholines, fatty acids, lysophospholipids, and glycerides in AD mouse brain. The results in this study suggest that these significantly altered lipid metabolic pathways (glycerophospholipid metabolism) may be implicated in early-stage AD. Our work deepens the understanding of the physio-pathologic mechanism of early-stage AD.

Mechanistic Insights into Alzheimer's Disease Unveiled through the Investigation of Disturbances in Central Metabolites and Metabolic Pathways

Hydrophilic metabolites are closely involved in multiple primary metabolic pathways and, consequently, play an essential role in the onset and progression of multifactorial human disorders, such as Alzheimer’s disease. This review article provides a comprehensive revision of the literature published on the use of mass spectrometry-based metabolomics platforms for approaching the central metabolome in Alzheimer’s disease research, including direct mass spectrometry, gas chromatography-mass spectrometry, hydrophilic interaction liquid chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Overall, mounting evidence points to profound disturbances that affect a multitude of central metabolic pathways, such as the energy-related metabolism, the urea cycle, the homeostasis of amino acids, fatty acids and nucleotides, neurotransmission, and others.

Amino Acid Levels as Potential Biomarker of Elderly Patients with Dementia

Dementia is a clinical syndrome characterized by cognitive impairment, in which there is disturbance of multiple higher cortical functions. The primary risk factor of dementia is old age, and due to significant changes in the worldwide demographic structure, the prevalence of cognitive impairment is increasing dramatically with aging populations in most countries. Alzheimer's disease is the predominant and leading cause of dementia. The aim of this study was to evaluate the modifications of amino acids that characterize the initial stages of dementia to help our understanding of the complex and multifactorial pathogenesis of neurodegenerative disorders. A total of 123 participants were divided into two groups: healthy elderly subjects and patients with mild or moderate dementia. The results of this study indicate that the serum levels of three amino acids were changed significantly in patients with dementia, in relation to the subjects without dementia. In particular, we observed differences in concentrations for serine, arginine and isoleucine (all of them were significantly increased in patients with dementia, compared with the control group). Our results suggest that the metabolisms of some amino acids seem be changed in patients with dementia. We conclude that amino acid profiling might be helpful for the better understanding of biochemical and metabolic changes related to the pathogenesis and progression of dementia. However, considering the multifactorial, heterogenous and complex nature of this disease, validation with a greater study sample in further research is required.

A Urinary Metabolomics Analysis Based on UPLC-MS and Effects of Moxibustion in APP/PS1 Mice

OBJECTIVE

Alzheimer's disease (AD) is a common neurodegenerative disorder with the symptoms of cognitive impairment and decreased learning and memory abilities. Metabolomics can reflect the related functional status and physiological and pathological changes in the process of AD. Moxibustion is a unique method in traditional Chinese medicine, which has been used in the treatment and prevention of diseases for thousands of years.

METHODS

A total of 32 APP/PS1 mice were randomly divided into the model group, moxibustion group, moxa smoke group and smoke-free moxibustion group (n=8/group), using the random number table method, while eight C57BL/6 mice were used as the control group. The five groups were measured for 20 min/day, 6 days/week, for 4 weeks. After 4 weeks' experiment, all the mice were placed in metabolic cages to collect urine continuously for 24 hours, for UPLC-MS analysis.

RESULTS

Principal component analysis (PCA) was used to identify the different metabolites among the five groups, and partial least squares discriminant analysis (PLS-DA) was performed to reveal the effects on the metabolic variance. Sixteen potential biomarkers were identified among the five groups, primarily related to amino acid metabolism, starch metabolism, sucrose metabolism, interconversion of pentose and glucuronate, and aminoacyl biosynthesis. There were 17 differences in the potential metabolites between the control and model groups, involving the metabolism of amino acid, purine, pyrimidine, nicotinic acid and nicotinamide, and biosynthesis of pantothenate and coenzyme A. Fifteen potential biomarkers were identified between the model and moxibustion groups, related to starch metabolism, sucrose metabolism, interconversion of pentose and glucuronate, glyoxylate, dicarboxylate anions and some amino acid metabolism.

CONCLUSION

Moxibustion can regulate the metabolism of substance and energy by improving the synthesis and decomposition of carbohydrates and amino acids in APP/PS1 transgenic AD model mice.

Untargeted lipidomics reveals progression of early Alzheimer's disease in APP/PS1 transgenic mice

Alzheimer's Disease (AD) is closely connected to aberrant lipid metabolism. However, how early AD-like pathology synchronously influences brain and plasma lipidome in AD mice remains unclear. The study of dynamic change of lipidome in early-stage AD mice could be of great interest for the discovery of lipid biomarkers for diagnosis and monitoring of early-stage AD. For the purpose, an untargeted lipidomic strategy was developed for the characterization of lipids (≤ 1,200 Da) perturbation occurring in plasma and brain in early-stage AD mice (2, 3 and 7 months) by ultra-high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry. Significant changes were detected in the levels of several lipid species including lysophospholipids, phosphatidylcholines (PCs), phosphatidylethanolamines (PEs) and Ceramides (Cers), as well as other related lipid compounds such as fatty acids (FAs), diacylglycerols (DGs) and triacylglycerols (TGs) in AD mice. In this sense, disorders of lipid metabolism appear to involve in multiple factors including overactivation of phospholipases and diacylglycerol lipases, decreased anabolism of lysophospholipids in plasma and PEs in plasma and brain, and imbalances in the levels of PCs, FAs and glycerides at different ages. We revealed the changing panels of potential lipid biomarkers with the development of early AD. The study raises the possibility of developing lipid biomarkers for diagnosis of early-stage AD.

Divergence in the metabolome between natural aging and Alzheimer's disease

Alzheimer's disease (AD) is a progressive and debilitating neurodegenerative disorder and one of the leading causes of death in the United States. Although amyloid plaques and fibrillary tangles are hallmarks of AD, research suggests that pathology associated with AD often begins 20 or more years before symptoms appear. Therefore, it is essential to identify early-stage biomarkers in those at risk for AD and age-related cognitive decline (ARCD) in order to develop preventative treatments. Here, we used an untargeted metabolomics analysis to define system-level alterations following cognitive decline in aged and APP/PS1 (AD) mice. At 6, 12, and 24 months of age, both control (Ctrl) and AD mice were tested in a 3-shock contextual fear conditioning (CFC) paradigm to assess memory decline. AD mice exhibited memory deficits across age and these memory deficits were also seen in naturally aged mice. Prefrontal cortex (PFC), hippocampus (HPC), and spleen were then collected and analyzed for metabolomic alterations. A number of significant pathways were altered between Ctrl and AD mice and naturally aged mice. By identifying systems-level alterations following ARCD and AD, these data could provide insights into disease mechanisms and advance the development of biomarker panels.

Altered Brain Metabolome Is Associated with Memory Impairment in the rTg4510 Mouse Model of Tauopathy

Alzheimer’s disease (AD) is characterized, amongst other features, by the pathologic accumulation of abnormally phosphorylated tau filaments in neurons that lead to neurofibrillary tangles. However, the molecular mechanisms by which the abnormal processing of tau leads to neurodegeneration and cognitive impairment remain unknown. Metabolomic techniques can comprehensively assess disturbances in metabolic pathways that reflect changes downstream from genomic, transcriptomic and proteomic systems. In the present study, we undertook a targeted metabolomic approach to determine a total of 187 prenominated metabolites in brain cortex tissue from wild type and rTg4510 animals (a mice model of tauopathy), in order to establish the association of metabolic pathways with cognitive impairment. This targeted metabolomic approach revealed significant differences in metabolite concentrations of transgenic mice. Brain glutamine, serotonin and sphingomyelin C18:0 were found to be predictors of memory impairment. These findings provide informative data for future research on AD, since some of them agree with pathological alterations observed in diseased humans.

Plasma alterations in cholinergic and serotonergic systems in early Alzheimer Disease: Diagnosis utility

BACKGROUND

Alzheimer Disease (AD) is the most common cause of dementia and it involves a high social and economic cost worldwide, and the health system still does not count with an effective treatment. This may be explained by the lack of a reliable early diagnosis and the complex physiological mechanisms involved in the disease development. In this sense, the cholinergic and serotonergic systems may be altered in the disease course.

METHODS

In this study, metabolites from these pathways were determined in order to develop a non-invasive and early diagnosis model, as well as to advance in the knowledge of the physiopathological mechanisms of the disease. For this, plasma samples from mild cognitive impairment due to AD patients (MCI-AD, n = 25) and healthy controls (n = 25) were analysed.

RESULTS

choline and tryptophan pathways were deregulated in MCI-AD. Therefore, a model based on betaine, cytidine, uridine, choline, acetylcholine, serotonin and tryptophan was developed, showing an AUC-ROC of 0.862, and sensitivity and specificity of 96% and 72%, respectively.

CONCLUSION

Alterations in metabolites from these pathways are related to cognitive impairment and neurodegeneration, and they could be useful in AD diagnosis. Nevertheless, further research is required in order to validate this diagnosis model.

Medium-chain triglycerides improved cognition and lipid metabolomics in mild to moderate Alzheimer's disease patients with APOE4-/-: A double-blind, randomized, placebo-controlled crossover trial

BACKGROUND

Previous clinical and animal studies suggested that medium-chain triglycerides (MCT) might be an alternative energy substrate for the brain and might benefit patients with Alzheimer's disease (AD), but the clinical evidence is not substantial or totally convincing.

OBJECTIVE

To investigate the effects of MCT on cognitive ability in patients with mild to moderate AD and explore the changes in peripheral blood metabolomics.

METHODS

A double-blind, randomized, placebo-controlled crossover study was undertaken in 53 mild to moderate AD patients. Participants were randomized between two sequences (placebo followed by MCT or MCT followed by placebo) and took MCT jelly or placebo jelly (canola oil) by mouth three times daily (total daily fat dose: 17.3 g MCT, or 19.7 g canola oil) for 30 days per phase. The primary outcome was cognition as measured by the Alzheimer's Disease Assessment Scale-Cognitive Subscale, Chinese version (ADAS-Cog-C). The secondary outcome was self-care as measured by the activities of daily living scale (ADL) and changes in plasma metabolites.

RESULTS

This study showed a significant (p < 0.01) reduction in ADAS-Cog-C scores between the MCT (2.62 points below baseline) and placebo interventions (2.57 points above baseline). Data from 46 (86.8%) APOE4^-/- subjects who completed the entire study were analyzed. Changes in ADL scores were not significantly different between the MCT and placebo interventions (p > 0.05). The concentrations of TC, HDL-C, β-hydroxybutyrate and acetoacetate were significantly higher in the MCT group than in the placebo group (p < 0.05). Lysophosphatidylcholine 16:0 (LysoPC (16:0)), LysoPC (P-18:0), LysoPC (P-18:1(9Z)), LysoPC (20:2(11Z,14Z)), and LysoPC (22:5(4Z,7Z,10Z,13Z,16Z)) were significantly increased after MCT intervention, and the concentrations of LysoPC (18:0), palmitic acid, linoleic acid, oleic acid, and 7,12-dimethylbenz[a]anthracene were significantly decreased (p < 0.05), whereas no significant changes appeared after the placebo intervention. Androstenedione concentration increased after placebo intervention. Furthermore, a significant negative correlation was observed between changes in LysoPC (P-18:1(9Z)) and ADAS-Cog-C scores after MCT intervention (r = -0.1472, p < 0.05).

CONCLUSIONS

MCT had positive effects on cognitive ability in mild to moderate AD patients with APOE4^-/-. These effects of MCT might be related to the metabolism of LysoPC, oleic acid, linoleic acid and palmitic acid, in addition to the ketogenic effect.

STUDY ID NUMBER

ChiCTR-IOR-16009737.

REGISTRY WEBSITE

WHO ICTRP Search Portal - http://apps.who.int/trialsearch/Default.aspx.

Interplay between Alzheimer's disease and global glucose metabolism revealed by the metabolic profile alterations of pancreatic tissue and serum in APP/PS1 transgenic mice

Increasing evidence suggests that there is a correlation between type 2 diabetes mellitus (T2D) and Alzheimer's disease (AD). Increased Aβ polypeptide production in AD patients would promote metabolic abnormalities, insulin signaling dysfunction and perturbations in glucose utilization, thus leading to the onset of T2D. However, the metabolic mechanisms underlying the interplay between AD and its diabetes-promoting effects are not fully elucidated. Particularly, systematic metabolomics analysis has not been performed for the pancreas tissues of AD subjects, which play key roles in the glucose metabolism of living systems. In the current study, we characterized the dynamic metabolic profile alterations of the serum and the pancreas of APP/PS1 double-transgenic mice (an AD mouse model) using the untargeted metabolomics approaches. Serum and pancreatic tissues of APP/PS1 transgenic mice and wild-type mice were extracted and subjected to NMR analysis to evaluate the functional state of pancreas in the progress of AD. Multivariate analysis of principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted to define the global and the local (pancreas) metabolic features associated with the possible initiation of T2D in the progress of AD. Our results showed the onset of AD-induced global glucose metabolism disorders in AD mice. Hyperglycemia and its accompanying metabolic disorders including energy metabolism down-regulation and oxidative stress were observed in the serum of AD mice. Meanwhile, global disturbance of branched-chain amino acid (BCAA) metabolism was detected, and the change of BCAA (leucine) was positively correlated to the alteration of glucose. Moreover, increased level of glucose and enhanced energy metabolism were observed in the pancreas of AD mice. The results suggest that the diabetes-promoting effects accompanying the progress of AD are achieved by down-regulating the global utilization of glucose and interfering with the metabolic function of pancreas. Since T2D is a risk factor for the pathogenesis of AD, our findings suggest that targeting the glucose metabolism dysfunctions might serve as a supplementary therapeutic strategy for Alzheimer's disease.

Reverting Metabolic Dysfunction in Cortex and Cerebellum of APP/PS1 Mice, a Model for Alzheimer's Disease by Pioglitazone, a Peroxisome Proliferator-Activated Receptor Gamma (PPARγ) Agonist

Identification of molecular mechanisms underlying early-stage Alzheimer's disease (AD) is important for the development of new therapies against and diagnosis of AD. In this study, gas chromatography time-of-flight mass spectrometry (GC-TOF-MS)-based metabolomics approach was employed to investigate the metabolic profiles in plasma and brain tissues harvested from 5-month-old APP/PS1 transgenic mice and their wildtype counterparts. Since different brain regions were expected to have their own distinct metabolic signals, four different brain regions, namely cortex, hippocampus, midbrain and cerebellum tissues, were dissected and had their metabolic profiles studied separately. Biochemical assays were also performed on plasma and brain cortex tissue of transgenic mice and wildtype mice, with a focus on mitochondrial health. Amyloid precursor protein and amyloid-β levels in plasma, brain cortex tissue and mitochondria fractions isolated from brain cortex were measured to assess the amyloid pathology. Our findings include the observation of extensive metabolic alterations in cortex and cerebellum of APP/PS1 mice, but not in their hippocampus, midbrain and plasma. The major pathways affected in cortex and cerebellum of APP/PS1 mice were closely related to impaired energy metabolism and perturbation of amino acid metabolism in these mice. APP/PS1 mice also exhibited higher amyloid-β40 and amyloid-β42 in their cortex, accumulation of mitochondria APP in their cortex, and presented an altered oxidative state in their brain. Treatment with the peroxisome proliferator-activated receptor gamma (PPARγ) agonist pioglitazone (PIO) successfully restored the energy metabolism, lowered amyloid-β levels and afforded the APP/PS1 mice a better antioxidative capacity in their cortex.

Plasma metabolomics in early Alzheimer's disease patients diagnosed with amyloid biomarker

An untargeted metabolomics study has been carried out using plasma samples from patients with Mild Cognitive Impairment due to Alzheimer's disease patients (MCI-AD, n = 29) and healthy people (n = 29)). They have been classified following the National Institute on Aging and Alzheimer's Association (NIA-AA) recommendations and cerebrospinal fluid biomarkers. The analytical method was based on liquid chromatography coupled to high resolution mass spectrometry. The data process from the corresponding metabolic profiles retained 1158 molecular features in positive and 424 in negative ionization mode. Differences between metabolomic profiles from MCI-AD patients and healthy participants were investigated using a penalized logistic regression analysis (ElasticNet), and being able to select automatically the most informative variables (53 molecular features). From the molecular features selected for the elastic net models, 16 variables were preliminarily identified by The Human Metabolome Database (amino acids, lipids…). However, only 4 of these variables were tentatively identified by MS/MS and all ions fragmentation modes, being choline the only confirmed metabolite. Regarding their metabolic pathways, they could be involved in cholinergic system, energy metabolism, amino acids and lipids pathways. To conclude, this is a reliable approach to early AD mechanisms, and choline has been identified as a promising AD diagnosis metabolite. SIGNIFICANCE: The untargeted analysis carried out in human plasma samples from early Alzheimer's disease patients and healthy individuals, and the use of sophisticated statistical tools, identified some metabolic pathways and plasma biomarkers. Preliminarily, cholinergic system, energy metabolism, and aminoacids and lipids pathways may be involved in early Alzheimer's disease development.

Mass spectrometry-based metabolomics: Targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders

Metabolomics seeks to take a "snapshot" in a time of the levels, activities, regulation and interactions of all small molecule metabolites in response to a biological system with genetic or environmental changes. The emerging development in mass spectrometry technologies has shown promise in the discovery and quantitation of neuroactive small molecule metabolites associated with gut microbiota and brain. Significant progress has been made recently in the characterization of intermediate role of small molecule metabolites linked to neural development and neurodegenerative disorder, showing its potential in understanding the crosstalk between gut microbiota and the host brain. More evidence reveals that small molecule metabolites may play a critical role in mediating microbial effects on neurotransmission and disease development. Mass spectrometry-based metabolomics is uniquely suitable for obtaining the metabolic signals in bidirectional communication between gut microbiota and brain. In this review, we summarized major mass spectrometry technologies including liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and imaging mass spectrometry for metabolomics studies of neurodegenerative disorders. We also reviewed the recent advances in the identification of new metabolites by mass spectrometry and metabolic pathways involved in the connection of intestinal microbiota and brain. These metabolic pathways allowed the microbiota to impact the regular function of the brain, which can in turn affect the composition of microbiota via the neurotransmitter substances. The dysfunctional interaction of this crosstalk connects neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease and Huntington's disease. The mass spectrometry-based metabolomics analysis provides information for targeting dysfunctional pathways of small molecule metabolites in the development of the neurodegenerative diseases, which may be valuable for the investigation of underlying mechanism of therapeutic strategies.

High-Throughput Metabolomics Based on Direct Mass Spectrometry Analysis in Biomedical Research

Metabolomics based on direct mass spectrometry analysis shows a great potential in biomedical research because of its high-throughput screening capability and wide metabolome coverage. This chapter contains detailed protocols to perform comprehensive metabolomic fingerprinting of multiple biological samples (serum, plasma, urine, brain, liver, spleen, thymus) by using complementary analytical platforms. The most important issues to be considered are discussed, including sample treatment, metabolomic analysis, raw data preprocessing, and data analysis.

High-Throughput Direct Mass Spectrometry-Based Metabolomics to Characterize Metabolite Fingerprints Associated with Alzheimer's Disease Pathogenesis

Direct mass spectrometry-based metabolomics has been widely employed in recent years to characterize the metabolic alterations underlying Alzheimer's disease development and progression. This high-throughput approach presents great potential for fast and simultaneous fingerprinting of a vast number of metabolites, which can be applied to multiple biological matrices including serum/plasma, urine, cerebrospinal fluid and tissues. In this review article, we present the main advantages and drawbacks of metabolomics based on direct mass spectrometry compared with conventional analytical techniques, and provide a comprehensive revision of the literature on the use of these tools in the investigation of Alzheimer's disease.

Next-generation biomarker discovery in Alzheimer's disease using metabolomics - from animal to human studies

Alzheimer's disease (AD) is a complex disease driven mainly by neuronal loss due to accumulation of intracellular neurofibrillary tangles and amyloid β aggregates in the brain. The diagnosis of AD currently relies on clinical symptoms while the disease can only be confirmed at autopsy. The few available biomarkers allowing for diagnosis are typically detected many years after the onset of the disease. New diagnostic approaches, particularly in easily-accessible biofluids, are essential. By providing an exhaustive information of the phenotype, metabolomics is an ideal approach for identification of new biomarkers. This review investigates the current position of metabolomics in the field of AD research, focusing on animal and human studies, and discusses the improvements carried out over the past decade.

Altered plasma arginine metabolome precedes behavioural and brain arginine metabolomic profile changes in the APPswe/PS1ΔE9 mouse model of Alzheimer's disease

While amyloid-beta (Aβ) peptides play a central role in the development of Alzheimer's disease (AD), recent evidence also implicates altered metabolism of L-arginine in the pathogenesis of AD. The present study systematically investigated how behavioural function and the brain and plasma arginine metabolic profiles changed in a chronic Aβ accumulation model using male APPswe/PS1ΔE9 transgenic (Tg) mice at 7 and 13 months of age. As compared to their wild-type (WT) littermates, Tg mice displayed age-related deficits in spatial water maze tasks and alterations in brain arginine metabolism. Interestingly, the plasma arginine metabolic profile was markedly altered in 7-month Tg mice prior to major behavioural impairment. Receiver operating characteristic curve analysis revealed that plasma putrescine and spermine significantly differentiated between Tg and WT mice. These results demonstrate the parallel development of altered brain arginine metabolism and behavioural deficits in Tg mice. The altered plasma arginine metabolic profile that preceded the behavioural and brain profile changes suggests that there may be merit in an arginine-centric set of ante-mortem biomarkers for AD.

Application of Metabolomics in Alzheimer's Disease

Progress toward the development of efficacious therapies for Alzheimer’s disease (AD) is halted by a lack of understanding early underlying pathological mechanisms. Systems biology encompasses several techniques including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Metabolomics is the newest omics platform that offers great potential for the diagnosis and prognosis of neurodegenerative diseases as an individual’s metabolome reflects alterations in genetic, transcript, and protein profiles and influences from the environment. Advancements in the field of metabolomics have demonstrated the complexity of dynamic changes associated with AD progression underscoring challenges with the development of efficacious therapeutic interventions. Defining systems-level alterations in AD could provide insights into disease mechanisms, reveal sex-specific changes, advance the development of biomarker panels, and aid in monitoring therapeutic efficacy, which should advance individualized medicine. Since metabolic pathways are largely conserved between species, metabolomics could improve the translation of preclinical research conducted in animal models of AD into humans. A summary of recent developments in the application of metabolomics to advance the AD field is provided below.

Mass Spectrometry-Based Metabolomic Multiplatform for Alzheimer's Disease Research

The integration of complementary analytical platforms has emerged as a suitable strategy to perform a comprehensive metabolomic characterization of complex biological systems. In this work, we describe the most important issues to be considered for the application of a mass spectrometry multiplatform in Alzheimer's disease research, which combines direct analysis with electrospray and atmospheric pressure photoionization sources, as well as orthogonal hyphenated approaches based on reversed-phase ultrahigh-performance liquid chromatography and gas chromatography. These procedures have been optimized for the analysis of multiple biological samples from human patients and transgenic animal models, including blood serum, various brain regions (e.g., hippocampus, cortex, cerebellum, striatum, olfactory bulbs), and other peripheral organs (e.g., liver, kidney, spleen, thymus). It is noteworthy that the metabolomic pipeline here detailed has demonstrated a great potential for the investigation of metabolic perturbations underlying Alzheimer's disease pathogenesis.

Metabolic profiling of the effects of ginsenoside Re in an Alzheimer's disease mouse model

Alzheimer's disease (AD) is one of the major neurological diseases among the elderly, and there are presently no approved treatments that can slow its progression. It has been reported that ginsenoside Re (G-Re), an active pharmacological component of ginseng, can ameliorate the symptoms of AD, but the underlying mechanisms are not clear. The current study was designed to test the effects of G-Re by investigating the metabolite profiles of AD mice. An AD animal model was induced by intracerebroventricular injection of β-amyloid in Kunming mice. Model mice were administered G-Re intragastrically (4mg/kg/day as a high dose and 1mg/kg/day as a low dose) for 30days. Cognitive function of the mice was tested using a Morris water maze, and pathological changes in the brain tissue were assessed by immunohistochemistry. Global metabolite profiling using ultra performance liquid chromatography-mass spectrometry was carried out to identify the metabolites that were differentially expressed in the plasma of mice. A total of 10 potential biomarkers were identified in AD mice. The peak intensities of tryptophan, hexadecasphinganine, phytosphingosine, and various lysophosphatidylcholines were lower whereas that of phenylalanine was higher in the AD mice than in the control mice. G-Re treatment (4mg/kg) affected all of these metabolic pathways. This is the first metabonomics study to biochemically profile the plasma metabolic pathways of AD animals affected by G-Re. These outcomes provide reliable evidence that illuminates the biochemical mechanisms of AD and facilitates investigation of the therapeutic benefits of G-Re in AD treatment.

Serum Amino Acid Profiles in Normal Subjects and in Patients with or at Risk of Alzheimer Dementia

Background/Aims

Abnormalities in the plasma amino acid profile have been reported in Alzheimer disease (AD), but no data exist for the prodromal phase characterized by subjective memory complaint (SMC). It was our aim to understand if serum amino acid levels change along the continuum from normal to AD, and to identify possible diagnostic biomarkers.

Methods

Serum levels of 15 amino acids and 2 organic acids were determined in 4 groups of participants – 29 with probable AD, 18 with mild cognitive impairment (MCI), 24 with SMC, and 46 cognitively healthy subjects (HS) – by electrospray tandem mass spectrometry.

Results

Glutamate, aspartate, and phenylalanine progressively decreased, while citrulline, argi­ninosuccinate, and homocitrulline progressively increased, from HS over SMC and MCI to AD. The panel including these 6 amino acids and 4 ratios (glutamate/citrulline, citrulline/phenylalanine, leucine plus isoleucine/phenylalanine, and arginine/phenylalanine) discriminated AD from HS with about 96% accuracy. Other panels including 20 biomarkers discriminated SMC or MCI from AD or HS with an accuracy ranging from 88 to 75%.

Conclusion

Amino acids contribute to a characteristic metabotype during the progression of AD along the continuum from health to frank dementia, and their monitoring in elderly individuals might help to detect at-risk subjects.

Amelioration of cognitive impairments in APPswe/PS1dE9 mice is associated with metabolites alteration induced by total salvianolic acid

Purpose

Total salvianolic acid (TSA) is extracted from salvia miltiorrhiza; however, to date, there has been limited characterization of its effects on metabolites in Alzheimer’s disease model-APPswe/PS1dE9 mice. The main objective of this study was to investigate the metabolic changes in 7-month-old APPswe/PS1dE9 mice treated with TSA, which protects against learning and memory impairment.

Methods

APPswe/PS1dE9 mice were treated with TSA (30 mg/kg·d and 60 mg/kg·d, i.p.) and saline (i.p.) daily from 3.5 months old for 14 weeks; saline-treated (i.p.) WT mice were included as the controls. The effects of TSA on learning and memory were assessed by a series of behavioral tests, including the NOR, MWM and step-through tasks. The FBG and plasma lipid levels were subsequently assessed using the GOPOD and enzymatic color methods, respectively. Finally, the concentrations of Aβ42, Aβ40 and metabolites in the hippocampus of the mice were detected via ELISA and GC-TOF-MS, respectively.

Results

At 7 months of age, the APPswe/PS1dE9 mice treated with TSA exhibited an improvement in the preference index (PI) one hour after the acquisition phase in the NOR and the preservation of spatial learning and memory in the MWM. Treatment with TSA substantially decreased the LDL-C level, and 60 mg/kg TSA decreased the CHOL level compared with the plasma level of the APPswe/PS1dE9 group. The Aβ42 and Aβ40 levels in the hippocampus were decreased in the TSA-treated group compared with the saline-treated APPswe/PS1dE9 group. The regulation of metabolic pathways relevant to TSA predominantly included carbohydrate metabolism, such as sorbitol, glucose-6-phosphate, sucrose-6-phosphate and galactose, vitamin metabolism involved in cholecalciferol and ascorbate in the hippocampus.

Conclusions

TSA induced a remarkable amelioration of learning and memory impairments in APPswe/PS1dE9 mice through the regulation of Aβ42, Aβ40, carbohydrate and vitamin metabolites in the hippocampus and LDL-C and CHOL in the plasma.

Amino Acid Catabolism in Alzheimer's Disease Brain: Friend or Foe?

There is a dire need to discover new targets for Alzheimer's disease (AD) drug development. Decreased neuronal glucose metabolism that occurs in AD brain could play a central role in disease progression. Little is known about the compensatory neuronal changes that occur to attempt to maintain energy homeostasis. In this review using the PubMed literature database, we summarize evidence that amino acid oxidation can temporarily compensate for the decreased glucose metabolism, but eventually altered amino acid and amino acid catabolite levels likely lead to toxicities contributing to AD progression. Because amino acids are involved in so many cellular metabolic and signaling pathways, the effects of altered amino acid metabolism in AD brain are far-reaching. Possible pathological results from changes in the levels of several important amino acids are discussed. Urea cycle function may be induced in endothelial cells of AD patient brains, possibly to remove excess ammonia produced from increased amino acid catabolism. Studying AD from a metabolic perspective provides new insights into AD pathogenesis and may lead to the discovery of dietary metabolite supplements that can partially compensate for alterations of enzymatic function to delay AD or alleviate some of the suffering caused by the disease.

Direct infusion mass spectrometry for metabolomic phenotyping of diseases

Metabolomics based on direct mass spectrometry (MS) analysis, either by direct infusion or flow injection of crude sample extracts, shows a great potential for metabolic fingerprinting because of its high-throughput screening capability, wide metabolite coverage and reduced time of analysis. Considering that numerous metabolic pathways are significantly perturbed during the initiation and progression of diseases, these metabolomic tools can be used to get a deeper understanding about disease pathogenesis and discover potential biomarkers for early diagnosis. In this work, we describe the most common metabolomic platforms used in biomedical research, with special focus on strategies based on direct MS analysis. Then, a comprehensive review on the application of direct MS fingerprinting in clinical issues is provided.

Metabolomic Analysis in Brain Research: Opportunities and Challenges

Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s). Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results.

Metabolomic investigation of systemic manifestations associated with Alzheimer's disease in the APP/PS1 transgenic mouse model

There is growing evidence that Alzheimer's disease may be a widespread systemic disorder, so peripheral organs could be affected by pathological mechanisms occurring in this neurodegenerative disease. For this reason, a double metabolomic platform based on the combination of gas chromatography-mass spectrometry and ultra-high performance liquid chromatography-mass spectrometry was used for the first time to investigate metabolic changes in liver and kidney from the transgenic mice APP/PS1 against wild-type controls. Multivariate statistics showed significant differences in levels of numerous metabolites including phospholipids, sphingolipids, acylcarnitines, steroids, amino acids and other compounds, which denotes that multiple pathways might be associated with systemic pathogenesis of Alzheimer's in this mouse model, such as bioenergetic failures, oxidative stress, altered metabolism of membrane lipids, hyperammonemia or impaired homeostasis of steroids. Furthermore, it is noteworthy that some novel pathological mechanisms were found, such as impaired gluconeogenesis, polyol pathway or metabolism of branched chain amino acids, not previously described for Alzheimer's disease. Therefore, these findings clearly support the hypothesis that Alzheimer's disease may be considered as a systemic disorder.