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

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.

The Effects of Amyloid-β on Metabolomic Profiles of Cardiomyocytes and Coronary Endothelial Cells

BACKGROUND

An increasing number of experimental and clinical studies show a link between Alzheimer's disease and heart diseases such as heart failure, ischemic heart disease, and atrial fibrillation. However, the mechanisms underlying the potential role of amyloid-β (Aβ) in the pathogenesis of cardiac dysfunction in Alzheimer's disease remain unknown. We have recently shown the effects of Aβ 1 - 40 and Aβ 1 - 42 on cell viability and mitochondrial function in cardiomyocytes and coronary artery endothelial cells.

OBJECTIVE

In this study, we investigated the effects of Aβ 1 - 40 and Aβ 1 - 42 on the metabolism of cardiomyocytes and coronary artery endothelial cells.

METHODS

Gas chromatography-mass spectrometry was used to analyze metabolomic profiles of cardiomyocytes and coronary artery endothelial cells treated with Aβ 1 - 40 and Aβ 1 - 42. In addition, we determined mitochondrial respiration and lipid peroxidation in these cells.

RESULTS

We found that the metabolism of different amino acids was affected by Aβ 1 - 42 in each cell type, whereas the fatty acid metabolism is consistently disrupted in both types of cells. Lipid peroxidation was significantly increased, whereas mitochondrial respiration was reduced in both cell types in response to Aβ 1 - 42.

CONCLUSION

This study revealed the disruptive effects of Aβ on lipid metabolism and mitochondria function in cardiac cells.

Comparative Metagenomics and Metabolomes Reveals Abnormal Metabolism Activity Is Associated with Gut Microbiota in Alzheimer's Disease Mice

A common symptom in Alzheimer's disease (AD) is cognitive decline, of which the potential pathogenesis remains unclear. In order to understand the mechanism of gut microbiota in AD, it is necessary to clarify the relationship between gut microbiota and metabolites. Behavioral tests, pathological examination, metagenomics, and metabolomics were applied to analyze the difference of gut microbiota and metabolome between APP^swe/PS1^ΔE9 (PAP) mice with cognitive decline and age-matched controls, and their possible correlations. Our results showed that PAP mice and health mice had different structures of the bacterial communities in the gut. The abundances and diversities of the bacterial communities in health mice were higher than in PAP mice by metagenomics analysis. The abundances of Libanicoccus massiliensis, Paraprevotella clara, and Lactobacillus amylovorus were significantly increased in PAP mice, while the abundances of Turicibacter sanguinis, Dubosiella newyorkensis, and Prevotella oris were greatly reduced. Furthermore, PAP mice possessed peculiar metabolic phenotypes in stool, serum, and hippocampus relative to WT mice, as is demonstrated by alterations in neurotransmitters metabolism, lipid metabolism, aromatic amino acids metabolism, energy metabolism, vitamin digestion and absorption, and bile metabolism. Microbiota-host metabolic correlation analysis suggests that abnormal metabolism in stool, serum, and hippocampus of PAP mice may be modulated by the gut microbiota, especially T. sanguinis, D. newyorkensis, and P. oris. Therefore, abnormal metabolism activity is associated with gut microbiota in Alzheimer's disease mice. Our results imply that modifying host metabolism through targeting gut microbiota may be a novel and viable strategy for the prevention and treatment of AD in the future.

Metabolomic alterations in the blood plasma of older adults with mild cognitive impairment and Alzheimer's disease (from the Nakayama Study)

Alzheimer's disease (AD) is a progressive disease, and the number of AD patients is increasing every year as the population ages. One of the pathophysiological mechanisms of AD is thought to be the effect of metabolomic abnormalities. There have been several studies of metabolomic abnormalities of AD, and new biomarkers are being investigated. Metabolomic studies have been attracting attention, and the aim of this study was to identify metabolomic biomarkers associated with AD and mild cognitive impairment (MCI). Of the 927 participants in the Nakayama Study conducted in Iyo City, Ehime Prefecture, 106 were selected for this study as Control (n = 40), MCI (n = 26), and AD (n = 40) groups, matched by age and sex. Metabolomic comparisons were made across the three groups. Then, correlations between metabolites and clinical symptoms were examined. The blood mRNA levels of the ornithine metabolic enzymes were also measured. Of the plasma metabolites, significant differences were found in ornithine, uracil, and lysine. Ornithine was significantly decreased in the AD group compared to the Control and MCI groups (Control vs. AD: 97.2 vs. 77.4; P = 0.01, MCI vs. AD: 92.5 vs. 77.4; P = 0.02). Uracil and lysine were also significantly decreased in the AD group compared to the Control group (uracil, Control vs. AD: 272 vs. 235; P = 0.04, lysine, Control vs. AD: 208 vs. 176; P = 0.03). In the total sample, the MMSE score was significantly correlated with lysine, ornithine, thymine, and uracil. The Barthel index score was significantly correlated with lysine. The instrumental activities of daily living (IADL) score were significantly correlated with lysine, betaine, creatine, and thymine. In the ornithine metabolism pathway, the spermine synthase mRNA level was significantly decreased in AD. Ornithine was decreased, and mRNA expressions related to its metabolism were changed in the AD group compared to the Control and MCI groups, suggesting an association between abnormal ornithine metabolism and AD. Increased betaine and decreased methionine may also have the potential to serve as markers of higher IADL in elderly persons. Plasma metabolites may be useful for predicting the progression of AD.

Alzheimer's disease: a scoping review of biomarker research and development for effective disease diagnosis

INTRODUCTION

Alzheimer's disease (AD) is regarded as the foremost reason for neurodegeneration that prominently affects the geriatric population. Characterized by extracellular accumulation of amyloid-beta (Aβ), intracellular aggregation of hyperphosphorylated tau (p-tau), and neuronal degeneration that causes impairment of memory and cognition. Amyloid/tau/neurodegeneration (ATN) classification is utilized for research purposes and involves amyloid, tau, and neuronal injury staging through MRI, PET scanning, and CSF protein concentration estimations. CSF sampling is invasive, and MRI and PET scanning requires sophisticated radiological facilities which limit its widespread diagnostic use. ATN classification lacks effectiveness in preclinical AD.

AREAS COVERED

This publication intends to collate and review the existing biomarker profile and the current research and development of a new arsenal of biomarkers for AD pathology from different biological samples, microRNA (miRNA), proteomics, metabolomics, artificial intelligence, and machine learning for AD screening, diagnosis, prognosis, and monitoring of AD treatments.

EXPERT OPINION

It is an accepted observation that AD-related pathological changes occur over a long period of time before the first symptoms are observed providing ample opportunity for detection of biological alterations in various biological samples that can aid in early diagnosis and modify treatment outcomes.

Multiomics technologies: role in disease biomarker discoveries and therapeutics

 

Medical research has been revolutionized after the publication of the full human genome. This was the major landmark that paved the way for understanding the biological functions of different macro and micro molecules. With the advent of different high-throughput technologies, biomedical research was further revolutionized. These technologies constitute genomics, transcriptomics, proteomics, metabolomics, etc. Collectively, these high-throughputs are referred to as multi-omics technologies. In the biomedical field, these omics technologies act as efficient and effective tools for disease diagnosis, management, monitoring, treatment and discovery of certain novel disease biomarkers. Genotyping arrays and other transcriptomic studies have helped us to elucidate the gene expression patterns in different biological states, i.e. healthy and diseased states. Further omics technologies such as proteomics and metabolomics have an important role in predicting the role of different biological molecules in an organism. It is because of these high throughput omics technologies that we have been able to fully understand the role of different genes, proteins, metabolites and biological pathways in a diseased condition. To understand a complex biological process, it is important to apply an integrative approach that analyses the multi-omics data in order to highlight the possible interrelationships of the involved biomolecules and their functions. Furthermore, these omics technologies offer an important opportunity to understand the information that underlies disease. In the current review, we will discuss the importance of omics technologies as promising tools to understand the role of different biomolecules in diseases such as cancer, cardiovascular diseases, neurodegenerative diseases and diabetes.

SUMMARY POINTS

MoNET: an R package for multi-omic network analysis

MOTIVATION

The increasing availability of multi-omic data has enabled the discovery of disease biomarkers in different scales. Understanding the functional interaction between multi-omic biomarkers is becoming increasingly important due to its great potential for providing insights of the underlying molecular mechanism.

RESULTS

Leveraging multiple biological network databases, we integrated the relationship between single nucleotide polymorphisms (SNPs), genes/proteins and metabolites, and developed an R package Multi-omic Network Explorer Tool (MoNET) for multi-omic network analysis. This new tool enables users to not only track down the interaction of SNPs/genes with metabolome level, but also trace back for the potential risk variants/regulators given altered genes/metabolites. MoNET is expected to advance our understanding of the multi-omic findings by unveiling their transomic interactions and is likely to generate new hypotheses for further validation.

AVAILABILITY AND IMPLEMENTATION

The MoNET package is freely available on https://github.com/JW-Yan/MONET.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Development of a method for dansylation of metabolites using organic solvent-compatible buffer systems for amine/phenol submetabolome analysis

Metabolomics, which serves as a readout of biological processes and diseases monitoring, is an informative research area for disease biomarker discovery and systems biology studies. In particular, reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) has become a powerful and popular tool for metabolomics analysis, enabling the detection of most metabolites. Very polar and ionic metabolites, however, are less easily detected because of their poor retention in RP columns. Dansylation of metabolites simplifies the sub-metabolome analysis by reducing its complexity and increasing both hydrophobicity and ionization ability. However, the various metabolite concentrations in clinical samples have a wide dynamic range with highly individual variation in total metabolite amount, such as in saliva. The bicarbonate buffer typically used in dansylation labeling reactions induces solvent stratification, resulting in poor reproducibility, selective sample loss and an increase in false-determined metabolite peaks. In this study, we optimized the dansylation protocol for samples with wide concentration range of metabolites, utilizing diisopropylethylamine (DIPEA) or tri-ethylamine (TEA) in place of bicarbonate buffer, and presented the results of a systemic investigation of the influences of individual processes involved on the overall performance of the protocol. In addition to achieving high reproducibility, substitution of DIPEA or TEA buffer resulted in similar labeling efficiency of most metabolites and more efficient labeling of some metabolites with a higher pK_a. With this improvement, compounds that are only present in samples in trace amounts can be detected, and more comprehensive metabolomics profiles can be acquired for biomarker discovery or pathway analysis, making it possible to analyze clinical samples with limited amounts of metabolites.

Role of Oxidative Damage in Alzheimer's Disease and Neurodegeneration: From Pathogenic Mechanisms to Biomarker Discovery

Alzheimer’s disease (AD) is a neurodegenerative disorder accounting for over 50% of all dementia patients and representing a leading cause of death worldwide for the global ageing population. The lack of effective treatments for overt AD urges the discovery of biomarkers for early diagnosis, i.e., in subjects with mild cognitive impairment (MCI) or prodromal AD. The brain is exposed to oxidative stress as levels of reactive oxygen species (ROS) are increased, whereas cellular antioxidant defenses are decreased. Increased ROS levels can damage cellular structures or molecules, leading to protein, lipid, DNA, or RNA oxidation. Oxidative damage is involved in the molecular mechanisms which link the accumulation of amyloid-β and neurofibrillary tangles, containing hyperphosphorylated tau, to microglia response. In this scenario, microglia are thought to play a crucial role not only in the early events of AD pathogenesis but also in the progression of the disease. This review will focus on oxidative damage products as possible peripheral biomarkers in AD and in the preclinical phases of the disease. Particular attention will be paid to biological fluids such as blood, CSF, urine, and saliva, and potential future use of molecules contained in such body fluids for early differential diagnosis and monitoring the disease course. We will also review the role of oxidative damage and microglia in the pathogenesis of AD and, more broadly, in neurodegeneration.

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.

Roles and Mechanisms of Axon-Guidance Molecules in Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disease that is characterized by progressive memory decline and cognitive dysfunctions. Although the causes of AD have not yet been established, many mechanisms have been proposed. Axon-guidance molecules play the roles in the occurrence and development of AD by participating in different mechanisms. Therefore, what roles do axon-guidance molecules play in AD? This study aimed at elucidating how axon-guidance molecules Netrins, Slits, Semaphorins, and Ephrins regulate the levels of Aβ, hyperphosphorylation of tau protein, Reelin, and other ways through different signaling pathways, in order to show the roles of axon-guidance molecules in the occurrence and development of AD. And it is hoped that this study can provide a theoretical basis and new perspectives in the search for new therapeutic targets for AD.

Effects of Aerobic Exercise Training on Systemic Biomarkers and Cognition in Late Middle-Aged Adults at Risk for Alzheimer's Disease

Increasing evidence indicates that physical activity and exercise training may delay or prevent the onset of Alzheimer's disease (AD). However, systemic biomarkers that can measure exercise effects on brain function and that link to relevant metabolic responses are lacking. To begin to address this issue, we utilized blood samples of 23 asymptomatic late middle-aged adults, with familial and genetic risk for AD (mean age 65 years old, 50% female) who underwent 26 weeks of supervised treadmill training. Systemic biomarkers implicated in learning and memory, including the myokine Cathepsin B (CTSB), brain-derived neurotrophic factor (BDNF), and klotho, as well as metabolomics were evaluated. Here we show that aerobic exercise training increases plasma CTSB and that changes in CTSB, but not BDNF or klotho, correlate with cognitive performance. BDNF levels decreased with exercise training. Klotho levels were unchanged by training, but closely associated with change in VO2peak. Metabolomic analysis revealed increased levels of polyunsaturated free fatty acids (PUFAs), reductions in ceramides, sphingo- and phospholipids, as well as changes in gut microbiome metabolites and redox homeostasis, with exercise. Multiple metabolites (~30%) correlated with changes in BDNF, but not CSTB or klotho. The positive association between CTSB and cognition, and the modulation of lipid metabolites implicated in dementia, support the beneficial effects of exercise training on brain function. Overall, our analyses indicate metabolic regulation of exercise-induced plasma BDNF changes and provide evidence that CTSB is a marker of cognitive changes in late middle-aged adults at risk for dementia.

Myeloid Arginase 1 Insufficiency Exacerbates Amyloid-β Associated Neurodegenerative Pathways and Glial Signatures in a Mouse Model of Alzheimer's Disease: A Targeted Transcriptome Analysis

Brain myeloid cells, include infiltrating macrophages and resident microglia, play an essential role in responding to and inducing neurodegenerative diseases, such as Alzheimer's disease (AD). Genome-wide association studies (GWAS) implicate many AD casual and risk genes enriched in brain myeloid cells. Coordinated arginine metabolism through arginase 1 (Arg1) is critical for brain myeloid cells to perform biological functions, whereas dysregulated arginine metabolism disrupts them. Altered arginine metabolism is proposed as a new biomarker pathway for AD. We previously reported Arg1 deficiency in myeloid biased cells using lysozyme M (LysM) promoter-driven deletion worsened amyloidosis-related neuropathology and behavioral impairment. However, it remains unclear how Arg1 deficiency in these cells impacts the whole brain to promote amyloidosis. Herein, we aim to determine how Arg1 deficiency driven by LysM restriction during amyloidosis affects fundamental neurodegenerative pathways at the transcriptome level. By applying several bioinformatic tools and analyses, we found that amyloid-β (Aβ) stimulated transcriptomic signatures in autophagy-related pathways and myeloid cells' inflammatory response. At the same time, myeloid Arg1 deficiency during amyloidosis promoted gene signatures of lipid metabolism, myelination, and migration of myeloid cells. Focusing on Aβ associated glial transcriptomic signatures, we found myeloid Arg1 deficiency up-regulated glial gene transcripts that positively correlated with Aβ plaque burden. We also observed that Aβ preferentially activated disease-associated microglial signatures to increase phagocytic response, whereas myeloid Arg1 deficiency selectively promoted homeostatic microglial signature that is non-phagocytic. These transcriptomic findings suggest a critical role for proper Arg1 function during normal and pathological challenges associated with amyloidosis. Furthermore, understanding pathways that govern Arg1 metabolism may provide new therapeutic opportunities to rebalance immune function and improve microglia/macrophage fitness.

Citrulline supplementation improves spatial memory in a murine model for Alzheimer's disease

OBJECTIVES

Alzheimer's disease (AD) correlates with the dysfunction of metabolic pathways that translates into neurological symptoms. An arginine deficiency, a precursor of nitric oxide (NO), has been reported for patients with AD. We aimed to evaluate the effect of citrulline oral supplementation on cognitive decline in an AD murine model.

METHODS

Three-month citrulline or water supplementation was blindly given to male and female wild-type and 3 × Tg mice with AD trained and tested in the Morris water maze. Cerebrospinal fluid and brain tissue were collected. Ultra-performance liquid chromatography was used for arginine determinations and the Griess method for NO.

RESULTS

Eight-month-old male 3 × Tg mice with AD supplemented with citrulline performed significantly better in the Morris water maze task. Arginine levels increased in the cerebrospinal fluid although no changes were seen in brain tissue and only a tendency of increase of NO was observed.

CONCLUSIONS

Citrulline oral administration is a viable treatment for memory improvement in the early stages of AD, pointing to NO as a viable, efficient target for memory dysfunction in AD.

Arginase 1 Insufficiency Precipitates Amyloid-β Deposition and Hastens Behavioral Impairment in a Mouse Model of Amyloidosis

Alzheimer’s disease (AD) includes several hallmarks comprised of amyloid-β (Aβ) deposition, tau neuropathology, inflammation, and memory impairment. Brain metabolism becomes uncoupled due to aging and other AD risk factors, which ultimately lead to impaired protein clearance and aggregation. Increasing evidence indicates a role of arginine metabolism in AD, where arginases are key enzymes in neurons and glia capable of depleting arginine and producing ornithine and polyamines. However, currently, it remains unknown if the reduction of arginase 1 (Arg1) in myeloid cell impacts amyloidosis. Herein, we produced haploinsufficiency of Arg1 by the hemizygous deletion in myeloid cells using Arg1^fl/fl and LysMcre^Tg/+ mice crossed with APP Tg2576 mice. Our data indicated that Arg1 haploinsufficiency promoted Aβ deposition, exacerbated some behavioral impairment, and decreased components of Ragulator-Rag complex involved in mechanistic target of rapamycin complex 1 (mTORC1) signaling and autophagy. Additionally, Arg1 repression and arginine supplementation both impaired microglial phagocytosis in vitro. These data suggest that proper function of Arg1 and arginine metabolism in myeloid cells remains essential to restrict amyloidosis.

Novel biomarkers in Alzheimer's disease using high resolution proteomics and metabolomics: miRNAS, proteins and metabolites

Alzheimer's disease (AD) is the most common form of dementia. It affects approximately 6% of people over the age of 65 years. It is a clinicopathological, degenerative, chronical and progressive disease that exhibits a deterioration of memory, orientation, speech and other functions. Factors contributing to the pathogenesis of the disease are the presence of extracellular amyloid deposits, called neuritic senile plaques, and fibrillary protein deposits inside neurons, known as neurofibrillary bundles, that appear mainly in the frontal and temporal lobes. AD has a long preclinical latency and is difficult to diagnose and prevent at early stages. Despite the advent of novel high-throughput technologies, it is a great challenge to identify precise biomarkers to understand the progression of the disease and the development of new treatments. In this sense, important knowledge is emerging regarding novel molecular and biological candidates with diagnostic potential, including microRNAs that have a key role in gene repression. On the other hand, proteomic approaches offer a platform for the comprehensive analysis of the whole proteome in a certain physiological time. Proteomic technology investigates protein expression directly and reveals post-translational modifications known to be determinant for many human diseases. Clinically, there is growing evidence for the role of proteomic and metabolomic technologies in AD biomarker discovery. This review discusses the role of several miRNAs identified using genomic technologies, and the importance of novel proteomic and metabolomic approaches to identify new proteins and metabolites that may be useful as biomarkers for monitoring the progression and treatment of AD.

Circulating asymmetric dimethylarginine and cognitive decline: A 4-year follow-up study of the 1936 Aberdeen Birth Cohort

BACKGROUND

The underlying mechanisms leading to dementia and Alzheimer's disease (AD) are unclear. Asymmetric dimethylarginine (ADMA), an endogenous inhibitor of nitric oxide synthase, may be associated with cognitive decline, but population-based evidence is lacking.

METHODS

Change in cognitive performance was assessed in participants of the Aberdeen Birth Cohort of 1936 using longitudinal Raven's progressive matrices (RPM) between 2000 and 2004. Multiple linear regression was used to estimate the association between ADMA concentrations in 2000 and change in cognitive performance after adjustment for potential confounders.

RESULTS

A total of 93 participants had complete information on cognitive performance between 2000 and 2004. Mean plasma ADMA concentrations were approximately 0.4 μmol/L lower in those participants with stable or improved RPM scores over follow-up compared with participants whose cognitive performance worsened. In confounder-adjusted analysis, one SD (0.06 μmol/L) increase in ADMA at 63 years of age was associated with an average reduction in RPM of 1.26 points (95% CI 0.14-2.26) after 4 years.

CONCLUSION

Raised plasma ADMA concentrations predicted worsening cognitive performance after approximately 4 years in this cohort of adults in late-middle age. These findings have implications for future research, including presymptomatic diagnosis or novel therapeutic targets for dementia and AD.

UHPLC-QTOFMS-based metabolomic analysis of serum and urine in rats treated with musalais containing varying ethyl carbamate content

The aim of this work is to investigate the effect of the ethyl carbamate (EC) content in musalais on the metabolism of rats. Electron beam irradiation was performed to decrease the content of EC in musalais, and Sprague Dawley rats were subjected to intragastric administration of musalais with varying EC content (high, medium, and low groups). Control rats were fed normally without any treatment. Serum and urine samples were analyzed using ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry. Principal component analysis and orthogonal projections to latent structures discriminant analysis (OPLS-DA) were performed to detect changes in the metabolite profile in the serum and urine in order to identify the differential metabolites and metabolic pathways. The results demonstrated clear differences in the serum and urine metabolic patterns between control and treatment groups. Ions in treatment groups with variable importance in the projection of >1 (selected from the OPLS-DA loading plots) and Ps < 0.05 (Student t test) compared to control group were identified as candidate metabolites. Analysis of the metabolic pathways relevant to the identified differential metabolites revealed that high EC content in musalais (10 mg/kg) mainly affected rats through valine, leucine, and isoleucine biosynthesis and nicotinate and nicotinamide metabolism, which were associated with energy metabolism. In addition, this work suggests that EC can induce oxidative stress via inhibition of glycine content.

Three plasma metabolites in elderly patients differentiate mild cognitive impairment and Alzheimer's disease: a pilot study

The metabolomic profile of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) may suggest potential diagnostic biomarkers and provide information on the pathophysiology of dementia. Our aim was to quantify plasmatic metabolites of AD patients, MCI and controls. We investigated the metabolomic profile-using the AbsoluteIDQ®p180 assay-of 79 older adults with primary cognitive impairment (34 AD and 20 MCI) and 25 healthy elders (controls). A cluster analysis revealed that a combination C12-DC, C12 and PCaaC26:0 could differentiate the patients according to diagnostic. Future studies should combine metabolomic profiles with other biomarkers to identify diagnostic groups.

Utility of Animal Models to Understand Human Alzheimer's Disease, Using the Mastermind Research Approach to Avoid Unnecessary Further Sacrifices of Animals

To diagnose and treat early-stage (preclinical) Alzheimer’s disease (AD) patients, we need body-fluid-based biomarkers that reflect the processes that occur in this stage, but current knowledge on associated processes is lacking. As human studies on (possible) onset and early-stage AD would be extremely expensive and time-consuming, we investigate the potential value of animal AD models to help to fill this knowledge gap. We provide a comprehensive overview of processes associated with AD pathogenesis and biomarkers, current knowledge on AD-related biomarkers derived from on human and animal brains and body fluids, comparisons of biomarkers obtained in human AD and frequently used animal AD models, and emerging body-fluid-based biomarkers. In human studies, amyloid beta (Aβ), hyperphosphorylated tau (P-tau), total tau (T-tau), neurogranin, SNAP-25, glial fibrillary acidic protein (GFAP), YKL-40, and especially neurofilament light (NfL) are frequently measured. In animal studies, the emphasis has been mostly on Aβ. Although a direct comparison between human (familial and sporadic) AD and (mostly genetic) animal AD models cannot be made, still, in brain, cerebrospinal fluid (CSF), and blood, a majority of similar trends are observed for human AD stage and animal AD model life stage. This indicates the potential value of animal AD models in understanding of the onset and early stage of AD. Moreover, animal studies can be smartly designed to provide mechanistic information on the interrelationships between the different AD processes in a longitudinal fashion and may also include the combinations of different conditions that may reflect comorbidities in human AD, according to the Mastermind Research approach.

Retention time shift analysis and correction in chemical isotope labeling liquid chromatography/mass spectrometry for metabolome analysis

RATIONALE

In chemical isotope labeling (CIL) liquid chromatography/mass spectrometry (LC/MS) metabolome analysis, the peak pairs of the same metabolite detected from different samples are aligned according to their mass and retention time (RT). Any RT shift of a peak pair in one of the sample files that falls outside the tolerance window will result in misalignment of the pair as a different metabolite. Thus, determination and correction of any significant RT shift are important to ensure the generation of high-quality metabolome results.

METHODS

In CIL LC/MS, the heavy-isotope-labeled pooled sample is spiked into all light-isotope-labeled individual samples. As a result, in the analysis of labeled samples of the same type, many common metabolites are detectable with high intensity in all LC/MS runs. We have developed a method to select a few of these metabolites as internal RT reference markers to check the occurrence of any RT shift in an LC/MS run. If a significant shift is found, an expanded list of these markers with their RT values covering the entire LC RT window is selected to serve as internal RT calibrants to recalibrate the chromatogram to correct any RT shift.

RESULTS

We developed a software program in R to perform RT check (RTC) and recalibration (RT-calib). This program can quickly determine the occurrence of any RT shift falling outside a user-defined threshold in an LC/MS run, thereby triggering a timely intervention to correct the problem (e.g., fixing a small leak or changing a column). In the analysis of 278 dansylation LC/MS runs of human urine samples, we show that the RT values can be corrected to be within a 30-second window.

CONCLUSIONS

An RT-check method and program tailored to CIL LC/MS metabolome analysis have been developed for quick detection and correction of RT shifts during the course of running many metabolome samples.

Nicotinamide attenuates the decrease in dendritic spine density in hippocampal primary neurons from 5xFAD mice, an Alzheimer's disease animal model

Alzheimer’s disease (AD) is the most common neurodegenerative disease characterized by memory loss and the presence of amyloid plaques and neurofibrillary tangles in the patients’ brains. In this study, we investigated the alterations in metabolite profiles of the hippocampal tissues from 6, 8, and 12 month-old wild-type (WT) and 5xfamiliar AD (5xFAD) mice, an AD mouse model harboring 5 early-onset familiar AD mutations, which shows memory loss from approximately 5 months of age, by exploiting the untargeted metabolomics profiling. We found that nicotinamide and adenosine monophosphate levels have been significantly decreased while lysophosphatidylcholine (LysoPC) (16:0), LysoPC (18:0), and lysophosphatidylethanolamine (LysoPE) (16:0) levels have been significantly increased in the hippocampi from 5xFAD mice at 8 months or 12 months of age, compared to those from age-matched wild-type mice. In the present study, we focused on the role of nicotinamide and examined if replenishment of nicotinamide exerts attenuating effects on the reduction in dendritic spine density in hippocampal primary neurons from 5xFAD mice. Treatment with nicotinamide attenuated the deficits in spine density in the hippocampal primary neurons derived from 5xFAD mice, indicating a potential role of nicotinamide in the pathogenesis of AD. Taken together, these findings suggest that the decreased hippocampal nicotinamide level could be linked with AD pathogenesis and be a useful therapeutic target for AD.

Development of a cognitive function marker based on D-amino acid proportions using new chiral tandem LC-MS/MS systems

The incidence of dementia, a clinical symptom characterized by severe cognitive decline, is increasing worldwide. Predictive biomarkers are therefore required for early identification and management. D-amino acids in the brain contribute to cognitive function and are suggested as useful biomarkers for diagnosing dementia risk. To clarify their relationship with human cognitive decline, we developed an identification method of chiral metabolomics for detecting slight differences in chiral amino acid amounts. Chiral tandem liquid chromatography-tandem mass spectrometry systems were applied for sensitive and selective amino acid species along with chiral species determination based on anion and zwitterion exchange mechanisms. In a comprehensive health cohort (cross-sectional study), we measured blood chiral amino acid levels from 305 women (65–80 years old) classified into Control, Mild-cognitive-Impairment (MCI), and Dementia groups using the Mini-Mental State Examination. MCI exhibited higher D-Pro (D-Pro/(D-Pro + L-Pro)) proportion vs the Control group, suggesting this proportion as a useful biomarker for MCI. Biomarker accuracy was improved in combination with D-Ser proportion. Receiver operating characteristics analysis of the Control vs. MCI proportion obtained area under the curve (0.80) with 70% sensitivity and 84% specificity at the optimal cutoff value (0.30). Thus, dementia monitoring can be improved by including trace D-amino acids measurements.

Targeted metabolomic analysis of nitric oxide/L-arginine pathway metabolites in dementia: association with pathology, severity, and structural brain changes

L-Arginine/NO pathway is altered in Alzheimer disease (AD). Its clinical relevance and pathway status in vascular dementia (VaD) are unknown. Using targeted metabolomics (a liquid chromatography-mass spectrometry) we assessed L-arginine, L-citrulline, dimethylamine (DMA), asymmetric dimethyl arginine (ADMA) and symmetric dimethylarginine (SDMA) in AD (n = 48), mixed-type dementia (MD; n = 34), VaD (n = 40) and non-demented individuals (n = 140) and determined their clinical relevance (the association with dementia pathology, cognitive impairment, and structural brain damage). L-Arginine, ADMA, L-arginine/ADMA, and L-citrulline levels were decreased in dementia and L-arginine, L-citrulline, age and sex were its independent predictors correctly classifying 91% of cases. L-Arginine and L-arginine/ADMA were differentiating between VaD and AD with moderate accuracy. L-Arginine, L-arginine/ADMA, SDMA, and DMA reflected structural brain changes. DMA and L-citrulline were elevated in patients with strategic infarcts and SDMA, L-arginine/ADMA, and DMA were independent predictors of Hachinski ischemic score. ADMA and SDMA accumulation reflected severity of cognitive impairment. In summary, L-Arginine/NO pathway is altered in neurodegenerative and vascular dementia in association with neurodegenerative and vascular markers of brain damage and severity of cognitive impairment.