Metabolite profiling of Alzheimer's disease cerebrospinal fluid

Advancing personalized medicine: Integrating statistical algorithms with omics and nano-omics for enhanced diagnostic accuracy and treatment efficacy

Medical laboratory services enable precise measurement of thousands of biomolecules and have become an inseparable part of high-quality healthcare services, exerting a profound influence on global health outcomes. The integration of omics technologies into laboratory medicine has transformed healthcare, enabling personalized treatments and interventions based on individuals' distinct genetic and metabolic profiles. Interpreting laboratory data relies on reliable reference values. Presently, population-derived references are used for individuals, risking misinterpretation due to population heterogeneity, and leading to medical errors. Thus, personalized references are crucial for precise interpretation of individual laboratory results, and the interpretation of omics data should be based on individualized reference values. We reviewed recent advancements in personalized laboratory medicine, focusing on personalized omics, and discussed strategies for implementing personalized statistical approaches in omics technologies to improve global health and concluded that personalized statistical algorithms for interpretation of omics data have great potential to enhance global health. Finally, we demonstrated that the convergence of nanotechnology and omics sciences is transforming personalized laboratory medicine by providing unparalleled diagnostic precision and innovative therapeutic strategies.

CSF amino acid profiles in ICV-streptozotocin-induced sporadic Alzheimer's disease in male Wistar rat: a metabolomics and systems biology perspective

Alzheimer's disease (AD) is an increasingly important public health concern due to the increasing proportion of older individuals within the general population. The impairment of processes responsible for adequate brain energy supply primarily determines the early features of the aging process. Restricting brain energy supply results in brain hypometabolism prior to clinical symptoms and is anatomically and functionally associated with cognitive impairment. The present study investigated changes in metabolic profiles induced by intracerebroventricular-streptozotocin (ICV-STZ) in an AD-like animal model. To this end, male Wistar rats received a single injection of STZ (3 mg·kg-1) by ICV (2.5 μL into each ventricle for 5 min on each side). In the second week after receiving ICV-STZ, rats were tested for cognitive performance using the Morris Water Maze test and subsequently prepared for positron emission tomography (PET) to confirm AD-like symptoms. Tandem Mass Spectrometry (MS/MS) analysis was used to detect amino acid changes in cerebrospinal fluid (CFS) samples. Our metabolomics study revealed a reduction in the concentrations of various amino acids (alanine, arginine, aspartic acid, glutamic acid, glycine, isoleucine, methionine, phenylalanine, proline, serine, threonine, tryptophane, tyrosine, and valine) in CSF of ICV-STZ-treated animals as compared to controls rats. The results of the current study indicate amino acid levels could potentially be considered targets of nutritional and/or pharmacological interventions to interfere with AD progression.

How should we be using biomarkers in trials of disease modification in Parkinson's disease?

The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson's disease has formed the backbone for a proposed staging system for incorporation in Parkinson's disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson's disease patients into trials (as distinct from patients with non-Parkinson's disease parkinsonism or non-Parkinson's disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson's disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer's disease-like pathology (detectable through CSF levels of amyloid-β42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline in Parkinson's disease even in its later stages. The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson's disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson's disease.

Establishment of a consensus protocol to explore the brain pathobiome in patients with mild cognitive impairment and Alzheimer's disease: Research outline and call for collaboration

Microbial infections of the brain can lead to dementia, and for many decades microbial infections have been implicated in Alzheimer's disease (AD) pathology. However, a causal role for infection in AD remains contentious, and the lack of standardized detection methodologies has led to inconsistent detection/identification of microbes in AD brains. There is a need for a consensus methodology; the Alzheimer's Pathobiome Initiative aims to perform comparative molecular analyses of microbes in post mortem brains versus cerebrospinal fluid, blood, olfactory neuroepithelium, oral/nasopharyngeal tissue, bronchoalveolar, urinary, and gut/stool samples. Diverse extraction methodologies, polymerase chain reaction and sequencing techniques, and bioinformatic tools will be evaluated, in addition to direct microbial culture and metabolomic techniques. The goal is to provide a roadmap for detecting infectious agents in patients with mild cognitive impairment or AD. Positive findings would then prompt tailoring of antimicrobial treatments that might attenuate or remit mounting clinical deficits in a subset of patients.

Cerebrospinal Fluid Metabolomics: Pilot Study of Using Metabolomics to Assess Diet and Metabolic Interventions in Alzheimer's Disease and Mild Cognitive Impairment

Brain glucose hypometabolism is an early sign of Alzheimer's disease (AD), and interventions which offset this deficit, such as ketogenic diets, show promise as AD therapeutics. Conversely, high-fat feeding may exacerbate AD risk. We analyzed the metabolomic profile of cerebrospinal fluid (CSF) in a pilot study of older adults who underwent saline and triglyceride (TG) infusions. Older adults (12 cognitively normal (CN), age 65.3 ± 8.1, and 9 with cognitive impairment (CI), age 70.9 ± 8.6) underwent a 5 h TG or saline infusion on different days using a random crossover design; CSF was collected at the end of infusion. Aqueous metabolites were measured using a targeted mass spectroscopy (MS) platform focusing on 215 metabolites from over 35 different metabolic pathways. Data were analyzed using MetaboAnalyst 4.0 and SAS. Of the 215 targeted metabolites, 99 were detectable in CSF. Only one metabolite significantly differed by treatment: the ketone body 3-hydroxybutyrate (HBA). Post hoc analyses showed that HBA levels were associated with age and markers of metabolic syndrome and demonstrated different correlation patterns for the two treatments. When analyzed by cognitive diagnosis group, TG-induced increases in HBA were over 3 times higher for those with cognitive impairment (change score CN +9.8 uM ± 8.3, CI +32.4 ± 7.4, p = 0.0191). Interestingly, individuals with cognitive impairment had higher HBA levels after TG infusion than those with normal cognition. These results suggest that interventions that increase plasma ketones may lead to higher brain ketones in groups at risk for AD and should be confirmed in larger intervention studies.

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.

Biomarkers of diagnosis, prognosis, pathogenesis, response to therapy: Convergence or divergence? Lessons from Alzheimer's disease and synucleinopathies

Alzheimer's disease (AD) is the most common disorder associated with cognitive impairment. Recent observations emphasize the pathogenic role of multiple factors inside and outside the central nervous system, supporting the notion that AD is a syndrome of many etiologies rather than a "heterogeneous" but ultimately unifying disease entity. Moreover, the defining pathology of amyloid and tau coexists with many others, such as α-synuclein, TDP-43, and others, as a rule, not an exception. Thus, an effort to shift our AD paradigm as an amyloidopathy must be reconsidered. Along with amyloid accumulation in its insoluble state, β-amyloid is becoming depleted in its soluble, normal states, as a result of biological, toxic, and infectious triggers, requiring a shift from convergence to divergence in our approach to neurodegeneration. These aspects are reflected-in vivo-by biomarkers, which have become increasingly strategic in dementia. Similarly, synucleinopathies are primarily characterized by abnormal deposition of misfolded α-synuclein in neurons and glial cells and, in the process, depleting the levels of the normal, soluble α-synuclein that the brain needs for many physiological functions. The soluble to insoluble conversion also affects other normal brain proteins, such as TDP-43 and tau, accumulating in their insoluble states in both AD and dementia with Lewy bodies (DLB). The two diseases have been distinguished by the differential burden and distribution of insoluble proteins, with neocortical phosphorylated tau deposition more typical of AD and neocortical α-synuclein deposition peculiar to DLB. We propose a reappraisal of the diagnostic approach to cognitive impairment from convergence (based on clinicopathologic criteria) to divergence (based on what differs across individuals affected) as a necessary step for the launch of precision medicine.

Global metabolic profiles in a non-human primate model of maternal immune activation: implications for neurodevelopmental disorders

Epidemiological evidence implicates severe maternal infections as risk factors for neurodevelopmental disorders, such as ASD and schizophrenia. Accordingly, animal models mimicking infection during pregnancy, including the maternal immune activation (MIA) model, result in offspring with neurobiological, behavioral, and metabolic phenotypes relevant to human neurodevelopmental disorders. Most of these studies have been performed in rodents. We sought to better understand the molecular signatures characterizing the MIA model in an organism more closely related to humans, rhesus monkeys (Macaca mulatta), by evaluating changes in global metabolic profiles in MIA-exposed offspring. Herein, we present the global metabolome in six peripheral tissues (plasma, cerebrospinal fluid, three regions of intestinal mucosa scrapings, and feces) from 13 MIA and 10 control offspring that were confirmed to display atypical neurodevelopment, elevated immune profiles, and neuropathology. Differences in lipid, amino acid, and nucleotide metabolism discriminated these MIA and control samples, with correlations of specific metabolites to behavior scores as well as to cytokine levels in plasma, intestinal, and brain tissues. We also observed modest changes in fecal and intestinal microbial profiles, and identify differential metabolomic profiles within males and females. These findings support a connection between maternal immune activation and the metabolism, microbiota, and behavioral traits of offspring, and may further the translational applications of the MIA model and the advancement of biomarkers for neurodevelopmental disorders such as ASD or schizophrenia.

Microbe-bridged disease-metabolite associations identification by heterogeneous graph fusion

MOTIVATION

Metabolomics has developed rapidly in recent years, and metabolism-related databases are also gradually constructed. Nowadays, more and more studies are being carried out on diverse microbes, metabolites and diseases. However, the logics of various associations among microbes, metabolites and diseases are limited understanding in the biomedicine of gut microbial system. The collection and analysis of relevant microbial bioinformation play an important role in the revelation of microbe-metabolite-disease associations. Therefore, the dataset that integrates multiple relationships and the method based on complex heterogeneous graphs need to be developed.

RESULTS

In this study, we integrated some databases and extracted a variety of associations data among microbes, metabolites and diseases. After obtaining the three interconnected bilateral association data (microbe-metabolite, metabolite-disease and disease-microbe), we considered building a heterogeneous graph to describe the association data. In our model, microbes were used as a bridge between diseases and metabolites. In order to fuse the information of disease-microbe-metabolite graph, we used the bipartite graph attention network on the disease-microbe and metabolite-microbe bipartite graph. The experimental results show that our model has good performance in the prediction of various disease-metabolite associations. Through the case study of type 2 diabetes mellitus, Parkinson's disease, inflammatory bowel disease and liver cirrhosis, it is noted that our proposed methodology are valuable for the mining of other associations and the prediction of biomarkers for different human diseases.Availability and implementation: https://github.com/Selenefreeze/DiMiMe.git.

Cerebrospinal Fluid Cortisol and Dehydroepiandrosterone Sulfate, Alzheimer’s Disease Pathology, and Cognitive Decline

Introduction

Elevated cortisol levels have been reported in Alzheimer’s disease (AD) and may accelerate the development of brain pathology and cognitive decline. Dehydroepiandrosterone sulfate (DHEAS) has anti-glucocorticoid effects and it may be involved in the AD pathophysiology.

Objectives

To investigate associations of cerebrospinal fluid (CSF) cortisol and DHEAS levels with (1) cognitive performance at baseline; (2) CSF biomarkers of amyloid pathology (as assessed by CSF Aβ levels), neuronal injury (as assessed by CSF tau), and tau hyperphosphorylation (as assessed by CSF p-tau); (3) regional brain volumes; and (4) clinical disease progression.

Materials and Methods

Individuals between 49 and 88 years (n = 145) with mild cognitive impairment or dementia or with normal cognition were included. Clinical scores, AD biomarkers, brain MRI volumetry along with CSF cortisol and DHEAS were obtained at baseline. Cognitive and functional performance was re-assessed at 18 and 36 months from baseline. We also assessed the following covariates: apolipoprotein E (APOE) genotype, BMI, and education. We used linear regression and mixed models to address associations of interest.

Results

Higher CSF cortisol was associated with poorer global cognitive performance and higher disease severity at baseline. Cortisol and cortisol/DHEAS ratio were positively associated with tau and p-tau CSF levels, and negatively associated with the amygdala and insula volumes at baseline. Higher CSF cortisol predicted more pronounced cognitive decline and clinical disease progression over 36 months. Higher CSF DHEAS predicted more pronounced disease progression over 36 months.

Conclusion

Increased cortisol in the CNS is associated with tau pathology and neurodegeneration, and with decreased insula and amygdala volume. Both CSF cortisol and DHEAS levels predict faster clinical disease progression. These results have implications for the identification of patients at risk of rapid decline as well as for the development of interventions targeting both neurodegeneration and clinical manifestations of AD.

Cross-species metabolomic analysis of tau- and DDT-related toxicity

Exposure to the pesticide dichlorodiphenyltrichloroethane (DDT) has been associated with increased risk of Alzheimer's disease (AD), a disease also associated with hyperphosphorylated tau (p-tau) protein aggregation. We investigated whether exposure to DDT can exacerbate tau protein toxicity in Caenorhabditiselegans using a transgenic strain that expresses human tau protein prone to aggregation by measuring changes in size, swim behavior, respiration, lifespan, learning, and metabolism. In addition, we examined the association between cerebrospinal fluid (CSF) p-tau protein-as a marker of postmortem tau burden-and global metabolism in both a human population study and in C. elegans, using the same p-tau transgenic strain. From the human population study, plasma and CSF-derived metabolic features associated with p-tau levels were related to drug, amino acid, fatty acid, and mitochondrial metabolism pathways. A total of five metabolites overlapped between plasma and C. elegans, and four between CSF and C. elegans. DDT exacerbated the inhibitory effect of p-tau protein on growth and basal respiration. In the presence of p-tau protein, DDT induced more curling and was associated with reduced levels of amino acids but increased levels of uric acid and adenosylselenohomocysteine. Our findings in C. elegans indicate that DDT exposure and p-tau aggregation both inhibit mitochondrial function and DDT exposure can exacerbate the mitochondrial inhibitory effects of p-tau aggregation. Further, biological pathways associated with exposure to DDT and p-tau protein appear to be conserved between species.

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.

Intact circadian rhythm despite cortisol hypersecretion in Alzheimer's disease: A meta-analysis

Hypersecretion of the glucocorticoid steroid hormone cortisol by individuals with Alzheimer's disease (AD) has been suspected for several decades, during which time dozens of examinations of this phenomenon have been conducted and published. The goals of this investigation were to summarize this sizeable body of literature, test whether participant and methodological characteristics modify the magnitude of the AD-associated basal cortisol hypersecretion, and examine whether cortisol circadian rhythmicity is maintained among individuals with AD. To this end, the present meta-analysis and systematic review examined over 300 comparisons of indices of basal HPA-axis functioning between individuals with AD and cognitively normal older adults. AD was associated with basal cortisol elevations (g = 0.45) but the magnitude of the effect was not systematically impacted by any of the participant characteristics considered or the time-of-day of the cortisol sampling. Further, there was no evidence of group differences among direct indices of circadian rhythmicity such as the cortisol awakening response or the diurnal cortisol slope. These results suggest that basal hypersecretion of cortisol, but not circadian dysrhythmia, is characteristic of individuals with AD. Mechanistically, the observed hypersecretion is consistent with the theorized AD-driven deterioration of the hippocampus and subsequent reduction in hypothalamic-pituitary-adrenal axis inhibition. Further investigation is warranted to elucidate the role and timing of cortisol elevations in the progression of AD.

Challenges in LC-MS-based metabolomics for Alzheimer's disease early detection: targeted approaches versus untargeted approaches

BACKGROUND

Alzheimer's disease (AD) is one of the most common causes of dementia in old people. Neuronal deficits such as loss of memory, language and problem-solving are severely compromised in affected patients. The molecular features of AD are Aβ deposits in plaques or in oligomeric structures and neurofibrillary tau tangles in brain. However, the challenge is that Aβ is only one piece of the puzzle, and recent findings continue to support the hypothesis that their presence is not sufficient to predict decline along the AD outcome. In this regard, metabolomic-based techniques are acquiring a growing interest for either the early diagnosis of diseases or the therapy monitoring. Mass spectrometry is one the most common analytical platforms used for detection, quantification, and characterization of metabolic biomarkers. In the past years, both targeted and untargeted strategies have been applied to identify possible interesting compounds.

AIM OF REVIEW

The overall goal of this review is to guide the reader through the most recent studies in which LC-MS-based metabolomics has been proposed as a powerful tool for the identification of new diagnostic biomarkers in AD. To this aim, herein studies spanning the period 2009-2020 have been reported. Advantages and disadvantages of targeted vs untargeted metabolomic approaches have been outlined and critically discussed.

Longitudinal Analysis of Multiple Neurotransmitter Metabolites in Cerebrospinal Fluid in Early Parkinson's Disease

BACKGROUND

Cerebrospinal fluid (CSF) levels of monoamine metabolites may represent biomarkers of Parkinson's disease (PD).

OBJECTIVE

The aim of this study was quantification of multiple metabolites in CSF from PD versus healthy control subjects (HCs), including longitudinal analysis.

METHODS

Absolute levels of multiple monoamine metabolites in CSF were quantified by liquid chromatography coupled with tandem mass spectrometry from 161 individuals with early PD and 115 HCs from the Parkinson's Progression Marker Initiative and de novo PD (DeNoPA) studies.

RESULTS

Baseline levels of homovanillic acid (HVA) and 3,4-dihydroxyphenylacetic acid (DOPAC) were lower in individuals with PD compared with HCs. HVA levels correlated with Movement Disorder Society Unified Parkinson's Disease Rating Scale total scores (P < 0.01). Both HVA/dopamine and DOPAC/dopamine levels correlated with caudate nucleus and raw DOPAC with putamen dopamine transporter single-photon emission computed tomography uptake ratios (P < 0.01). No metabolite changed over 2 years in drug-naive individuals, but some changed on starting levodopa treatment.

CONCLUSIONS

HVA and DOPAC CSF levels mirrored nigrostriatal pathway damage, confirming the central role of dopaminergic degeneration in early PD. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Potential Neuroregenerative and Neuroprotective Effects of Uridine/Choline-Enriched Multinutrient Dietary Intervention for Mild Cognitive Impairment: A Narrative Review

In mild cognitive impairment (MCI) due to Alzheimer disease (AD), also known as prodromal AD, there is evidence for a pathologic shortage of uridine, choline, and docosahexaenoic acid [DHA]), which are key nutrients needed by the brain. Preclinical and clinical evidence shows the importance of nutrient bioavailability to support the development and maintenance of brain structure and function in MCI and AD. Availability of key nutrients is limited in MCI, creating a distinct nutritional need for uridine, choline, and DHA. Evidence suggests that metabolic derangements associated with ageing and disease-related pathology can affect the body's ability to generate and utilize nutrients. This is reflected in lower levels of nutrients measured in the plasma and brains of individuals with MCI and AD dementia, and progressive loss of cognitive performance. The uridine shortage cannot be corrected by normal diet, making uridine a conditionally essential nutrient in affected individuals. It is also challenging to correct the choline shortfall through diet alone, because brain uptake from the plasma significantly decreases with ageing. There is no strong evidence to support the use of single-agent supplements in the management of MCI due to AD. As uridine and choline work synergistically with DHA to increase phosphatidylcholine formation, there is a compelling rationale to combine these nutrients. A multinutrient enriched with uridine, choline, and DHA developed to support brain function has been evaluated in randomized controlled trials covering a spectrum of dementia from MCI to moderate AD. A randomized controlled trial in subjects with prodromal AD showed that multinutrient intervention slowed brain atrophy and improved some measures of cognition. Based on the available clinical evidence, nutritional intervention should be considered as a part of the approach to the management of individuals with MCI due to AD, including adherence to a healthy, balanced diet, and consideration of evidence-based multinutrient supplements.

CircRNA-ceRNA Network Revealing the Potential Regulatory Roles of CircRNA in Alzheimer's Disease Involved the cGMP-PKG Signal Pathway

Background: Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease. The characteristic pathologies include extracellular senile plaques formed by β-amyloid protein deposition, neurofibrillary tangles formed by hyperphosphorylation of tau protein, and neuronal loss with glial cell hyperplasia. Circular RNAs (circRNAs) are rich in miRNA-binding sites (miRNA response elements, MREs), which serve as miRNA sponges or competitive endogenous RNAs (ceRNAs). Although several research groups have identified dysregulated circRNAs in the cerebral cortex of SAMP8 mice or APP/PS1 mice using deep RNA-seq analysis, we need to further explore circRNA expression patterns, targets, functions and the signaling pathways involved in the pathogenesis of AD and in particular the hippocampal circRNA expression profiles in AD.

Methods: We used deep RNA sequencing to investigate circRNA-ceRNA network patterns in the hippocampus of APP/PS1 mice.

Results: In our study, 70 dysregulated circRNAs, 39 dysregulated miRNAs and 121 dysregulated mRNAs were identified between the APP/PS1 group and the wild-type group at 8 months in the hippocampus of the mice. Through correlation analysis, we identified 11 dysregulated circRNAs, 7 dysregulated miRNAs and 8 dysregulated mRNAs forming 16 relationships in the circRNA-miRNA-mRNA regulatory network. Gene ontology (GO) analysis indicated that the dysregulated circRNAs were most enriched in biological metabolic processes. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the dysregulation of circRNAs was enriched in the cGMP-PKG signaling pathway, cAMP signaling pathway, Hippo signaling pathway, platelet activation, long-term potentiation and axon guidance. In addition, our findings preliminarily verified that the novel_circ_0003012/mmu-miR-298-3p/Smoc2 signaling axis may regulate the pathophysiology of AD by affecting the cGMP-PKG signaling pathway.

Conclusions: These newly identified circRNAs in networks and signaling pathways reveal potential diagnostic or therapeutic targets for AD.

Omics Data and Their Integrative Analysis to Support Stratified Medicine in Neurodegenerative Diseases

Molecular and clinical heterogeneity is increasingly recognized as a common characteristic of neurodegenerative diseases (NDs), such as Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis. This heterogeneity makes difficult the development of early diagnosis and effective treatment approaches, as well as the design and testing of new drugs. As such, the stratification of patients into meaningful disease subgroups, with clinical and biological relevance, may improve disease management and the development of effective treatments. To this end, omics technologies-such as genomics, transcriptomics, proteomics and metabolomics-are contributing to offer a more comprehensive view of molecular pathways underlying the development of NDs, helping to differentiate subtypes of patients based on their specific molecular signatures. In this article, we discuss how omics technologies and their integration have provided new insights into the molecular heterogeneity underlying the most prevalent NDs, aiding to define early diagnosis and progression markers as well as therapeutic targets that can translate into stratified treatment approaches, bringing us closer to the goal of personalized medicine in neurology.

An integrative multi-omics approach reveals new central nervous system pathway alterations in Alzheimer's disease

BACKGROUND

Multiple pathophysiological processes have been described in Alzheimer's disease (AD). Their inter-individual variations, complex interrelations, and relevance for clinical manifestation and disease progression remain poorly understood. We hypothesize that specific molecular patterns indicating both known and yet unidentified pathway alterations are associated with distinct aspects of AD pathology.

METHODS

We performed multi-level cerebrospinal fluid (CSF) omics in a well-characterized cohort of older adults with normal cognition, mild cognitive impairment, and mild dementia. Proteomics, metabolomics, lipidomics, one-carbon metabolism, and neuroinflammation related molecules were analyzed at single-omic level with correlation and regression approaches. Multi-omics factor analysis was used to integrate all biological levels. Identified analytes were used to construct best predictive models of the presence of AD pathology and of cognitive decline with multifactorial regression analysis. Pathway enrichment analysis identified pathway alterations in AD.

RESULTS

Multi-omics integration identified five major dimensions of heterogeneity explaining the variance within the cohort and differentially associated with AD. Further analysis exposed multiple interactions between single 'omics modalities and distinct multi-omics molecular signatures differentially related to amyloid pathology, neuronal injury, and tau hyperphosphorylation. Enrichment pathway analysis revealed overrepresentation of the hemostasis, immune response, and extracellular matrix signaling pathways in association with AD. Finally, combinations of four molecules improved prediction of both AD (protein 14-3-3 zeta/delta, clusterin, interleukin-15, and transgelin-2) and cognitive decline (protein 14-3-3 zeta/delta, clusterin, cholesteryl ester 27:1 16:0 and monocyte chemoattractant protein-1).

CONCLUSIONS

Applying an integrative multi-omics approach we report novel molecular and pathways alterations associated with AD pathology. These findings are relevant for the development of personalized diagnosis and treatment approaches in 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.

Cerebrospinal Fluid Biomarkers of Alzheimer's Disease: Current Evidence and Future Perspectives

Alzheimer's disease is a progressive, clinically heterogeneous, and particularly complex neurodegenerative disease characterized by a decline in cognition. Over the last two decades, there has been significant growth in the investigation of cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease. This review presents current evidence from many clinical neurochemical studies, with findings that attest to the efficacy of existing core CSF biomarkers such as total tau, phosphorylated tau, and amyloid-β (Aβ42), which diagnose Alzheimer's disease in the early and dementia stages of the disorder. The heterogeneity of the pathophysiology of the late-onset disease warrants the growth of the Alzheimer's disease CSF biomarker toolbox; more biomarkers showing other aspects of the disease mechanism are needed. This review focuses on new biomarkers that track Alzheimer's disease pathology, such as those that assess neuronal injury (VILIP-1 and neurofilament light), neuroinflammation (sTREM2, YKL-40, osteopontin, GFAP, progranulin, and MCP-1), synaptic dysfunction (SNAP-25 and GAP-43), vascular dysregulation (hFABP), as well as CSF α-synuclein levels and TDP-43 pathology. Some of these biomarkers are promising candidates as they are specific and predict future rates of cognitive decline. Findings from the combinations of subclasses of new Alzheimer's disease biomarkers that improve their diagnostic efficacy in detecting associated pathological changes are also presented.

Effects of Transcranial Direct Current Stimulation Treatment for Anorexia Nervosa

Background: Anorexia nervosa (AN) is a life-threatening illness with poor treatment outcomes. Although transcranial direct current stimulation (tDCS) is a promising non-invasive brain stimulation method, its effect in patients with AN remains unclear. Objective: This study investigated changes in maladaptive eating behavior, body mass index (BMI), and depression after 10 sessions of anodal tDCS over the left dorsolateral prefrontal cortex (DLPFC). Methods: In this double-blind, randomized controlled trial, 43 inpatients with AN were divided to receive either active (n = 22) or sham (n = 21) tDCS over the left DLPFC (anode F3/cathode Fp2, 2 mA for 30 min). All patients filled the Eating Disorder Examination Questionnaire (EDE-Q) and Zung Self-Rating Depression Scale (ZUNG), and their BMI was measured. These values were obtained repeatedly in four stages: (1) before tDCS treatment, (2) after tDCS treatment, (3) in the follow-up after 2 weeks, and (4) in the follow-up after 4 weeks. Results: Primary outcomes (EDE-Q) based on the ANOVA results do not show any between-group differences either after the active part of the study or in the follow-up. Secondary analysis reveals a reduction in some items of EDE-Q. Compared with sham tDCS, active tDCS significantly improved self-evaluation based on body shape (p < 0.05) and significantly decreased the need of excessive control over calorie intake (p < 0.05) in the 4-week follow-up. However, the results do not survive multiple comparison correction. In both sham and active groups, the BMI values improved, albeit not significantly. Conclusion: We did not observe a significant effect of tDCS over the left DLPFC on complex psychopathology and weight recovery in patients with AN. tDCS reduced the need to follow specific dietary rules and improved body image evaluation in patients with AN. Tests with a larger sample and different positions of electrodes are needed. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03273205.

LDL cholesterol and uridine levels in blood are potential nutritional biomarkers for clinical progression in Alzheimer's disease: The NUDAD project

INTRODUCTION

We examined associations between nutritional biomarkers and clinical progression in individuals with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's disease (AD)-type dementia.

METHODS

We included 528 individuals (64 ± 8 years, 46% F, follow-up 2.1 ± 0.87 years) with SCD (n = 204), MCI (n = 130), and AD (n = 194). Baseline levels of cholesterol, triglycerides, glucose, homocysteine, folate, vitamin A, B12, E and uridine were measured in blood and S-adenosylmethionine and S-adenosylhomocysteine in cerebrospinal fluid. We determined associations between nutritional biomarkers and clinical progression using Cox proportional hazard models.

RESULTS

Twenty-two (11%) patients with SCD, 45 (35%) patients with MCI, and 100 (52%) patients with AD showed clinical progression. In SCD, higher levels of low-density lipoprotein (LDL) cholesterol were associated with progression (hazard ratio [HR] [95% confidence interval (CI)] 1.88 [1.04 to 3.41]). In AD, lower uridine levels were associated with progression (0.79 [0.63 to 0.99]).

DISCUSSION

Our findings suggest that LDL cholesterol and uridine play a-stage-dependent-role in the clinical progression of AD.

Serum Metabolomics Profiling of Commercially Mixed Functional Foods—Effects in Beta-Amyloid Induced Rats Measured Using 1H NMR Spectroscopy

Functional foods such as pomegranate, dates and honey were shown by various previous studies to individually have a neuroprotective effect, especially in neurodegenerative disease such as Alzheimer’s disease (AD). In this novel and original study, an ¹H NMR spectroscopy tool was used to identify the metabolic neuroprotective mechanism of commercially mixed functional foods (MFF) consisting of pomegranate, dates and honey, in rats injected with amyloid-beta 1-42 (Aβ-42). Forty-five male albino Wistar rats were randomly divided into five groups: NC (0.9% normal saline treatment + phosphate buffer solution (PBS) solution injection), Abeta (0.9% normal saline treatment + 0.2 µg/µL Aβ-42 injection), MFF (4 mL/kg MFF treatment + PBS solution injection), Abeta–MFF (4 mL/kg MFF treatment + 0.2 µg/µL Aβ-42 injection) and Abeta–NAC (150 mg/kg N-acetylcysteine + 0.2 µg/µL Aβ-42 injection). Based on the results, the MFF and NAC treatment improved the spatial memory and learning using Y-maze. In the metabolic analysis, a total of 12 metabolites were identified, for which levels changed significantly among the treatment groups. Systematic metabolic pathway analysis found that the MFF and NAC treatments provided a neuroprotective effect in Aβ-42 injected rats by improving the acid amino and energy metabolisms. Overall, this finding showed that MFF might serve as a potential neuroprotective functional food for the prevention of AD.

Gas-phase basicity and proton affinity measurements of Alzheimer's disease drugs by the extended kinetic method and a theoretical investigation

This study has been carried out to obtain the thermochemical parameters of drugs used for Alzheimer's disease. The measurement of gas-phase basicity (GB) and proton affinity (PA) values of four important and commercially available drugs for Alzheimer's disease namely, rivastigmine, galantamine, memantine, and tacrine, is attempted for the first time. This study also includes the measurement of GB and PA values for the proposed drug curcumin, a natural product. We calculated the GB and PA values for all these drugs by applying electrospray ionization tandem mass spectrometry (ESI-MS/MS) with the extended kinetic method. Since, all these drugs possessing amino groups (basic nature), the PA values for all these drugs are high i.e., the PA values range from 923.6 to 979.7 kJ/mol and the GB values range from 886.2 to 943.3 kJ/mol. The GB and PA values obtained from the mass spectrometric experiments are well supported with the theoretical calculations. A high-level theoretical B3LYP/6-311 + G(d,p) method is used for the PA and GB calculation and the deviations are in the acceptable range.

Targeted metabolomics study of early pathological features in hippocampus of triple transgenic Alzheimer's disease male mice

Alzheimer's disease (AD) is a serious neurodegenerative disease in people of age 65 or above. The detailed etiology and pathogenesis of AD have not been elucidated yet. In this study, the hippocampi of 2- and 6-month-old triple transgenic Alzheimer's disease male mice and age-sex-matched wild-type (WT) mice were analyzed by using targeted metabolomics approach. Compared with WT mice, 24 and 60 metabolites were found with significant differences in 2- and 6-month-old AD mice. Among these, 14 metabolites were found common while 10 metabolites showed consistent variable trends in both groups. These differential metabolites are found associated with amino acid, lipid, vitamin, nucleotide-related base, neurotransmitter and energy metabolisms, and oxidative stress. The results suggest that these differential metabolites might play a critical role in AD pathophysiology, and may serve as potential biomarkers for AD. Moreover, the results highlight the involvement of abnormal purine, pyrimidine, arginine, and proline metabolism, along with glycerophospholipid metabolism in early pathology of AD. For the first time, several differential metabolites are found to be associated with AD in this study. Targeted metabolomics can be used for rapid and accurate quantitative analysis of specific target metabolites associated with AD.

Determination of neurosteroids in human cerebrospinal fluid in the 21st century: A review

Determination of steroid hormones synthesized by the human body plays an important role in various fields of endocrinology. Neurosteroids (NS) are steroids that are synthesized in the central (CNS) or peripheral nervous system (PNS), which is not only a source but also a target for neurosteroids. They are discussed as possible biomarkers in various cognitive disorders and research interest in this topic raises continuously. Nevertheless, knowledge on functions and metabolism is still limited, although the concept of neurosteroids was already introduced in the 1980s. Until today, the analysis of neurosteroids is truly challenging. The only accessible matrix for investigations of brain metabolism in living human beings is cerebrospinal fluid (CSF), which therefore becomes a very interesting specimen for analysis. However, neurosteroid concentrations are expected to be very low and the available amount of cerebrospinal fluid is limited. Further, high structural similarities of endogenous neurosteroids challenges analysis. Therefore, comprehensive methods, highly selective and sensitive for a large range of concentrations for different steroids in one aliquot are required and under continuous development. Although research has been increasingly intensified, still only few data are available on reference levels of neurosteroids in human cerebrospinal fluid. In this review, published literature of the last twenty years, as a period with relatively contemporary analytical methods, was systematically investigated. Considerations on human cerebrospinal fluid, different analytical approaches, and available data on levels of in analogy to periphery conceivable occurring neurosteroids, including (pro-) gestagens, androgens, corticoids, estrogens, and steroid conjugates, and their interpretation are intensively discussed.

Shared perturbations in the metallome and metabolome of Alzheimer's, Parkinson's, Huntington's, and dementia with Lewy bodies: A systematic review

Despite differences in presentation, age-related dementing diseases such as Alzheimer's (AD), Parkinson's (PD), and Huntington's diseases (HD), and dementia with Lewy bodies (DLB) may share pathogenic processes. This review aims to systematically assemble and compare findings in various biochemical pathways across these four dementias. PubMed and Google Scholar were screened for articles reporting on brain and biofluid measurements of metals and/or metabolites in AD, PD, HD, or DLB. Articles were assessed using specific a priori-defined inclusion and exclusion criteria. Of 284 papers identified, 198 met criteria for inclusion. Although varying coverage levels of metals and metabolites across diseases and tissues made comparison of many analytes impossible, several common findings were identified: elevated glucose in both brain tissue and biofluids of AD, PD, and HD cases; increased iron and decreased copper in AD, PD and HD brain tissue; and decreased uric acid in biofluids of AD and PD cases. Other analytes were found to differ between diseases or were otherwise not covered across all conditions. These findings indicate that disturbances in glucose and purine pathways may be common to AD, PD, and HD. However, standardisation of methodologies and better coverage in some areas - notably of DLB - are necessary to validate and extend these findings.

Metabolomics markers in Neurology: current knowledge and future perspectives for therapeutic targeting

INTRODUCTION

Metabolomics is an emerging approach providing new insights into the metabolic changes and underlying mechanisms involved in the pathogenesis of neurological disorders.

AREAS COVERED

Here, the authors present an overview of the current knowledge of metabolic profiling (metabolomics) to provide critical insight on the role of biochemical markers and metabolic alterations in neurological diseases.

EXPERT OPINION

Elucidation of characteristic metabolic alterations in neurological disorders is crucial for a better understanding of their pathogenesis, and for identifying potential biomarkers and drug targets. Nevertheless, discrepancies in diagnostic criteria, sample handling protocols, and analytical methods still affect the generalizability of current study results.

A multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap

Aetiological and clinical heterogeneity is increasingly recognized as a common characteristic of Alzheimer's disease and related dementias. This heterogeneity complicates diagnosis, treatment, and the design and testing of new drugs. An important line of research is discovery of multimodal biomarkers that will facilitate the targeting of subpopulations with homogeneous pathophysiological signatures. High-throughput 'omics' are unbiased data-driven techniques that probe the complex aetiology of Alzheimer's disease from multiple levels (e.g. network, cellular, and molecular) and thereby account for pathophysiological heterogeneity in clinical populations. This review focuses on data reduction analyses that identify complementary disease-relevant perturbations for three omics techniques: neuroimaging-based subtypes, metabolomics-derived metabolite panels, and genomics-related polygenic risk scores. Neuroimaging can track accrued neurodegeneration and other sources of network impairments, metabolomics provides a global small-molecule snapshot that is sensitive to ongoing pathological processes, and genomics characterizes relatively invariant genetic risk factors representing key pathways associated with Alzheimer's disease. Following this focused review, we present a roadmap for assembling these multiomics measurements into a diagnostic tool highly predictive of individual clinical trajectories, to further the goal of personalized medicine in Alzheimer's disease.

Fingerprinting Alzheimer's Disease by 1H Nuclear Magnetic Resonance Spectroscopy of Cerebrospinal Fluid

In this study, we sought for a cerebrospinal fluid (CSF) metabolomic fingerprint in Alzheimer's disease (AD) patients characterized, according to the clinical picture and CSF AD core biomarkers (Aβ₄₂, p-tau, and t-tau), both at pre-dementia (mild cognitive impairment due to AD, MCI-AD) and dementia stages (ADdem) and in a group of patients with a normal CSF biomarker profile (non-AD) using untargeted ¹H nuclear magnetic resonance (NMR) spectroscopy-based metabolomics. This is a retrospective study based on two independent cohorts: a Dutch cohort, which comprises 20 ADdem, 20 MCI-AD, and 20 non-AD patients, and an Italian cohort, constituted by 14 ADdem and 12 non-AD patients. ¹H NMR CSF spectra were analyzed using OPLS-DA. Metabolomic fingerprinting in the Dutch cohort provides a significant discrimination (86.1% accuracy) between ADdem and non-AD. MCI-AD patients show a good discrimination with respect to ADdem (70.0% accuracy) but only slight differences when compared with non-AD (59.6% accuracy). Acetate, valine, and 3-hydroxyisovalerate result to be altered in ADdem patients. Valine correlates with cognitive decline at follow-up (R = 0.53, P = 0.0011). The discrimination between ADdem and non-AD was confirmed in the Italian cohort. The CSF metabolomic fingerprinting shows a signature characteristic of ADdem patients with respect to MCI-AD and non-AD patients.

High-resolution metabolomic profiling of Alzheimer's disease in plasma

Background

Alzheimer’s disease (AD) is a complex neurological disorder with contributions from genetic and environmental factors. High‐resolution metabolomics (HRM) has the potential to identify novel endogenous and environmental factors involved in AD. Previous metabolomics studies have identified circulating metabolites linked to AD, but lack of replication and inconsistent diagnostic algorithms have hindered the generalizability of these findings. Here we applied HRM to identify plasma metabolic and environmental factors associated with AD in two study samples, with cerebrospinal fluid (CSF) biomarkers of AD incorporated to achieve high diagnostic accuracy.

Methods

Liquid chromatography‐mass spectrometry (LC–MS)‐based HRM was used to identify plasma and CSF metabolites associated with AD diagnosis and CSF AD biomarkers in two studies of prevalent AD (Study 1: 43 AD cases, 45 mild cognitive impairment [MCI] cases, 41 controls; Study 2: 50 AD cases, 18 controls). AD‐associated metabolites were identified using a metabolome‐wide association study (MWAS) framework.

Results

An MWAS meta‐analysis identified three non‐medication AD‐associated metabolites in plasma, including elevated levels of glutamine and an unknown halogenated compound and lower levels of piperine, a dietary alkaloid. The non‐medication metabolites were correlated with CSF AD biomarkers, and glutamine and the unknown halogenated compound were also detected in CSF. Furthermore, in Study 1, the unknown compound and piperine were altered in MCI patients in the same direction as AD dementia.

Conclusions

In plasma, AD was reproducibly associated with elevated levels of glutamine and a halogen‐containing compound and reduced levels of piperine. These findings provide further evidence that exposures and behavior may modify AD risks.

Prediction of disease-related metabolites using bi-random walks

Metabolites play a significant role in various complex human disease. The exploration of the relationship between metabolites and diseases can help us to better understand the underlying pathogenesis. Several network-based methods have been used to predict the association between metabolite and disease. However, some methods ignored hierarchical differences in disease network and failed to work in the absence of known metabolite-disease associations. This paper presents a bi-random walks based method for disease-related metabolites prediction, called MDBIRW. First of all, we reconstruct the disease similarity network and metabolite functional similarity network by integrating Gaussian Interaction Profile (GIP) kernel similarity of diseases and GIP kernel similarity of metabolites, respectively. Then, the bi-random walks algorithm is executed on the reconstructed disease similarity network and metabolite functional similarity network to predict potential disease-metabolite associations. At last, MDBIRW achieves reliable performance in leave-one-out cross validation (AUC of 0.910) and 5-fold cross validation (AUC of 0.924). The experimental results show that our method outperforms other existing methods for predicting disease-related metabolites.

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.

Integrated Non-targeted and Targeted Metabolomics Uncovers Dynamic Metabolic Effects during Short-Term Abstinence in Methamphetamine Self-Administering Rats

Persistent neurochemical disturbances by repeating drug reward and withdrawal lead to addiction. Particularly, drug withdrawal, usually starting within hours of the last dose, is considered as a critical step in the transition to addiction and a treatment clue. The aim of this study was to uncover metabolic effects associated with methamphetamine (MA) short-term abstinence using both non-targeted and targeted metabolomics. Metabolic alterations were investigated in rat plasma collected immediately after 16 days of MA self-administration and after 12 and 24 h of abstinence. Principal component analysis revealed that the highest level of separation occurred between the 24 h and saline (control) groups based on the significantly changed ion features, 257/320/333 and 331/409/388, in the SA/12 h/24 h groups in positive and negative modes of UPLC-QTOF-ESI-MS, respectively. Targeted metabolomics revealed dynamic changes in the biosynthesis/metabolism of amino acids, including the phenylalanine, tyrosine, and tryptophan biosynthesis and the valine, leucine, and isoleucine biosynthesis. Integrating non-targeted and targeted metabolomics data uncovered rapid and distinct changes in the metabolic pathways involved in energy metabolism, the nervous system, and membrane lipid metabolism. These findings provide essential knowledge of the dynamic metabolic effects associated with short-term MA abstinence and may help identify early warning signs of MA dependence.

Brain pyrimidine nucleotide synthesis and Alzheimer disease

Many patients suffering late-onset Alzheimer disease show a deficit in respiratory complex IV activity. The de novo pyrimidine biosynthesis pathway connects with the mitochondrial respiratory chain upstream from respiratory complex IV. We hypothesized that these patients would have decreased pyrimidine nucleotide levels. Then, different cell processes for which these compounds are essential, such as neuronal membrane generation and maintenance and synapses production, would be compromised. Using a cell model, we show that inhibiting oxidative phosphorylation function reduces neuronal differentiation. Linking these processes to pyrimidine nucleotides, uridine treatment recovers neuronal differentiation. To unmask the importance of these pathways in Alzheimer disease, we firstly confirm the existence of the de novo pyrimidine biosynthesis pathway in adult human brain. Then, we report altered mRNA levels for genes from both de novo pyrimidine biosynthesis and pyrimidine salvage pathways in brain from patients with Alzheimer disease. Thus, uridine supplementation might be used as a therapy for those Alzheimer disease patients with low respiratory complex IV activity.

Novel serum metabolites associate with cognition phenotypes among Bogalusa Heart Study participants

BACKGROUND

Metabolomics study provides an opportunity to identify novel molecular determinants of altered cognitive function.

METHODS

During 2013 to 2016 Bogalusa Heart Study (BHS) visit, 1,177 participants underwent untargeted, ultrahigh performance liquid chromatography-tandem mass spectroscopy metabolomics profiling. Global cognition and five cognition domains were also assessed. The cross-sectional associations of single metabolites with cognition were tested using multiple linear regression models. Weighted correlation network analysis was used to examine the covariable-adjusted correlations of modules of co-abundant metabolites with cognition. Analyses were conducted in the overall sample and according to both ethnicity and sex.

RESULTS

Five known metabolites and two metabolite modules robustly associated with cognition across overall and stratified analyses. Two metabolites were from lipid sub-pathways including fatty acid metabolism [9-hydroxystearate; minimum P-value (min-P)=1.11×10-5], and primary bile acid metabolism (glyco-alpha-muricholate; min-P=4.10×10-5). One metabolite from the glycogen metabolism sub-pathway (maltose; min-P=9.77×10-6), one from the polyamine metabolism sub-pathway (N-acetyl-isoputreanine; min-P=1.03×10-5), and one from the purine metabolism sub-pathway (7-methylguanine; min-P=1.19×10-5) were also identified. Two metabolite modules reflecting bile acid metabolism and androgenic steroids correlated with cognition (min-P=5.00×10-4 and 3.00×10-3, respectively).

CONCLUSION

The novel associations of 5 known metabolites and 2 metabolite modules with cognition provide insights into the physiological mechanisms regulating cognitive function.

Combined proteomic and metabolomic analyses of cerebrospinal fluid from mice with ischemic stroke reveals the effects of a Buyang Huanwu decoction in neurodegenerative disease

Ischemic stroke is one of the most common causes of death worldwide and is a major cause of acquired disability in adults. However, there is still a need for an effective drug for its treatment. Buyang Huanwu decoction (BHD), a traditional Chinese medicine (TCM) prescription, has long been used clinically to aid neurological recovery after stroke. To establish potential clinical indicators of BHD efficacy in stroke treatment and prognosis, we conducted a combined proteomic and metabolomic analysis of cerebrospinal fluid (CSF) samples in a mouse stroke model. CSF samples were obtained from male mice with acute ischemic stroke induced by middle cerebral ischemic/reperfusion (CI/R) injury, some of which were then treated with BHD. Label-free quantitative proteomics was conducted using nano-LC-MS/MS on an LTQ Orbitrap mass and metabolomic analysis was performed using nanoprobe NMR and UHPLC-QTOF-MS. The results showed that several proteins and metabolites were present at significantly different concentrations in the CSF samples from mice with CI/R alone and those treated with BHD. These belonged to pathways related to energy demand, inflammatory signaling, cytoskeletal regulation, Wnt signaling, and neuroprotection against neurodegenerative diseases. In conclusion, our in silico data suggest that BHD treatment is not only protective but can also ameliorate defects in pathways affected by neurological disorders. These data shed light on the mechanism whereby BHD may be effective in the treatment and prevention of stroke-related neurodegenerative disease.

Tissue-Specific Metabolomics Analysis Identifies the Liver as a Major Organ of Metabolic Disorders in Amyloid Precursor Protein/Presenilin 1 Mice of Alzheimer's Disease

Alzheimer's disease (AD) is regarded as a metabolic disorder, and more attention has been paid to brain metabolism. However, AD may also affect metabolism in the peripheral organs beyond the brain. In this study, therefore, we investigated metabolic changes in the liver, kidney, and heart of amyloid precursor protein/presenilin 1 (APP/PS1) mice at 1, 5, and 10 months of age by using ¹H NMR-based metabolomics and chemometrics. Metabolomic results reveal that the liver was the earliest affected organ in APP/PS1 mice during amyloid pathology progression, followed by the kidney and heart. Moreover, a hypometabolic state was found in the liver of APP/PS1 mice at 5 months of age, and the disturbed metabolites were mainly involved in energy metabolism, amino acid metabolism, nucleic acid metabolism, as well as ketone and fatty acid metabolism. In conclusion, our results suggest that AD is a systemic metabolic dysfunction, and hepatic metabolic abnormality may reflect amyloid pathology progression.

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.

Mass spectrometry is a multifaceted weapon to be used in the battle against Alzheimer's disease: Amyloid beta peptides and beyond

Amyloid-β peptide (Aβ) accumulation and aggregation have been considered for many years the main cause of Alzheimer's disease (AD), and therefore have been the principal target of investigation as well as of the proposed therapeutic approaches (Grasso [2011] Mass Spectrom Rev. 30: 347-365). However, the amyloid cascade hypothesis, which considers Aβ accumulation the only causative agent of the disease, has proven to be incomplete if not wrong. In recent years, actors such as metal ions, oxidative stress, and other cofactors have been proposed as possible co-agents or, in some cases, main causative factors of AD. In this scenario, MS investigation has proven to be fundamental to design possible diagnostic strategies of this elusive disease, as well as to understand the biomolecular mechanisms involved, in the attempt to find a possible therapeutic solution. We review the current applications of MS in the search for possible Aβ biomarkers of AD to help the diagnosis of the disease. Recent examples of the important contributions that MS has given to prove or build theories on the molecular pathways involved with such terrible disease are also reviewed.

Complex noradrenergic dysfunction in Alzheimer's disease: Low norepinephrine input is not always to blame

The locus coeruleus-noradrenergic (LC-NA) system supplies the cerebral cortex with norepinephrine, a key modulator of cognition. Neurodegeneration of the LC is an early hallmark of Alzheimer's disease (AD). In this article, we analyze current literature to understand whether NA degeneration in AD simply leads to a loss of norepinephrine input to the cortex. With reported adaptive changes in the LC-NA system at the anatomical, cellular, and molecular levels in AD, existing evidence support a seemingly sustained level of extracellular NE in the cortex, at least at early stages of the long course of AD. We postulate that loss of the integrity of the NA system, rather than mere loss of NE input, is a key contributor to AD pathogenesis. A thorough understanding of NA dysfunction in AD has a large impact on both our comprehension and treatment of this devastating 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.

The potential of metabolic profiling for vaccine development

Recent technological advances have provided deeper insights into the role of small molecules in biological processes. Metabolic profiling has thus entered the arena of -omics studies and rapidly proven its value both as stand-alone and as complement to other more advanced approaches, notably transcriptomics. Here we describe the potential of metabolic profiling for vaccinology embedded in the context of infection and immunity. This discussion is preceded by a description of the relevant technical and analytical tools for biological interpretation of metabolic data. Although not as widely applied as other -omics technologies, we believe that metabolic profiling can make important contributions to the better understanding of mechanisms underlying vaccine-induced responses and their effects on the prevention of infection or disease.

Disease-related metabolites affect protein-nanoparticle interactions

Once in biological fluids, the surface of nanoparticles (NPs) is rapidly covered with a layer of biomolecules (i.e., the "protein corona") whose composition strongly determines their biological identity, regulates interactions with biological entities including cells and the immune system, and consequently directs the biological fate and pharmacokinetics of nanoparticles. We recently introduced the concept of a "personalized protein corona" which refers to the formation of different biological identities of the exact same type of NP after being exposed to extract plasmas from individuals who have various types of diseases. As different diseases have distinct metabolomic profiles and metabolites can interact with proteins, it is legitimate to hypothesize that metabolomic profiles in plasma may have the capacity to, at least partially, drive the formation of a personalized protein corona. To test this hypothesis, we employed a multi-scale approach composed of coarse-grained (CG) and all atom (AA) molecular dynamics (MD) simulations to probe the role of glucose and cholesterol (model metabolites in diabetes and hypercholesterolemia patients) in the interaction of fibrinogen protein and polystyrene NPs. Our results revealed that glucose and cholesterol had the capacity to induce substantial changes in the binding site of fibrinogen to the surface of NPs. More specifically, the simulation results demonstrated that increasing the metabolite amount could change the profiles of fibrinogen adsorption and replacement, what is known as the Vroman effect, on the NP surface. In addition, we also found out that metabolites can substantially determine the immune triggering potency of the fibrinogen-NP complex. Our proof-of-concept outcomes further emphasize the need for the development of patient-specific NPs in a disease type-specific manner for high yielding and safe clinical applications.

Synaptic Membrane Synthesis in Rats Depends on Dietary Sufficiency of Vitamin C, Vitamin E, and Selenium: Relevance for Alzheimer's Disease

Chronic consumption of a diet enriched with nutritional precursors of phospholipids, including uridine and the polyunsaturated fatty acids, docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), was shown previously to enhance levels of brain phospholipids and synaptic proteins in rodents. Vitamin C, vitamin E, and selenium may directly affect the breakdown or synthesis of membrane phospholipids. The present study investigated the necessity of antioxidants for the effectiveness of supplementation with uridine plus DHA and EPA (as fish oil) in rats. Rats were randomized to four treatment groups and received, for 6 weeks, one of four experimental diets, i.e., a diet low in antioxidants, a diet high in antioxidants, a diet low in antioxidants supplemented with DHA+EPA+uridine, or a diet high in antioxidants supplemented with DHA+EPA+uridine. On completion of dietary treatment, rats were sacrificed, and brain levels of phospholipids, synaptic proteins, and two enzymes involved in phospholipid synthesis (choline-phosphate cytidylyltransferase, PCYT1A, and choline/ethanolamine phosphotransferase, CEPT1) were analyzed. Levels of phospholipids, the pre- and post-synaptic proteins Synapsin-1 and PSD95, and the enzymes PCYT1A and CEPT1 were significantly enhanced by combined supplementation of DHA+EPA+uridine and antioxidants and not enhanced by supplementation of DHA+EPA+uridine with insufficient antioxidant levels. Our data suggest that dietary vitamin C, vitamin E, and selenium are essential for the phospholipid precursors' effects on increasing levels of membrane phospholipids and synaptic proteins, the indirect indicators of synaptogenesis. Their concomitant supply may be relevant in Alzheimer's disease patients, because the disease is characterized by synapse loss and lower plasma and brain levels of phospholipid precursors and antioxidants.