Serum metabolomic profiling in patients with Alzheimer disease and amnestic mild cognitive impairment by GC/MS

Association of genetically predicted 486 blood metabolites on the risk of Alzheimer's disease: a Mendelian randomization study

Background

Studies have reported that metabolic disturbance exhibits in patients with Alzheimer's disease (AD). Still, the presence of definitive evidence concerning the genetic effect of metabolites on AD risk remains insufficient. A systematic exploration of the genetic association between blood metabolites and AD would contribute to the identification of new targets for AD screening and prevention.

Methods

We conducted an exploratory two-sample Mendelian randomization (MR) study aiming to preliminarily identify the potential metabolites involved in AD development. A genome-wide association study (GWAS) involving 7,824 participants provided information on 486 human blood metabolites. Outcome information was obtained from a large-scale GWAS meta-analysis of AD, encompassing 21,982 cases and 41,944 controls of Europeans. The primary two-sample MR analysis utilized the inverse variance weighted (IVW) model while supplementary analyses used Weighted median (WM), MR Egger, Simple mode, and Weighted mode, followed by sensitivity analyses such as the heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis. For the further identification of metabolites, replication and meta-analysis with FinnGen data, steiger test, linkage disequilibrium score regression, confounding analysis, and were conducted for further evaluation. Multivariable MR was performed to assess the direct effect of metabolites on AD. Besides, an extra replication analysis with EADB data was conducted for final evaluation of the most promising findings.

Results

After rigorous genetic variant selection, IVW, complementary analysis, sensitivity analysis, replication and meta-analysis with the FinnGen data, five metabolites (epiandrosterone sulfate, X-12680, pyruvate, docosapentaenoate, and 1-stearoylglycerophosphocholine) were identified as being genetically associated with AD. MVMR analysis disclosed that genetically predicted these four known metabolites can directly influence AD independently of other metabolites. Only epiandrosterone sulfate and X-12680 remained suggestive significant associations with AD after replication analysis with the EADB data.

Conclusion

By integrating genomics with metabonomics, this study furnishes evidence substantiating the genetic association of epiandrosterone sulfate and X-12680 with AD. These findings hold significance for the screening, prevention, and treatment strategies for AD.

Bile acid profile associated with CSF and PET biomarkers in Alzheimer's disease

BACKGROUND

Recent studies have shown that gut microbiota can affect the development of Alzheimer's disease (AD) through various mechanisms. Bile acids (BAs), which are the final byproducts of cholesterol metabolism created through both the human body and gut microbiome, appear to be influenced by gut microbiota and may impact AD pathological characteristics such as the accumulation of tau and amyloid-β. We aimed to investigate the associations between various serum BAs and CSF biomarkers (including Aβ, total tau, and p-tau). Additionally, we sought to examine the longitudinal changes in brain Aβ and tau through PET imaging in relation to BAs profile.

METHODS

The data of 828 subjects including 491 diagnosed with mild cognitive impairment (MCI), 119 patients diagnosed with AD, and 267 cognitively normal (CN) participants were obtained from ADNI. The baseline and longitudinal [18F] florbetapir and [18F] flortaucipir PET standard uptake value ratios (SUVR) measures were obtained to assess the accumulation of tau and Aβ. Moreover, baseline levels of serum BAs and CSF Aβ1-42, tau, and p-tau were used.

RESULTS

After FDR correction we observed that five BAs level and relevant calculated ratios were associated with CSF p-tau and tau, three with CSF Aβ1-42. Furthermore, three BAs level and relevant calculated ratios were associated with the tau-PET rate of change, and two with the Aβ rate of change.

CONCLUSION

The findings from our study suggest a correlation between altered profiles of BAs and CSF and imaging biomarkers associated with AD. These results provide supporting evidence for the link between the gut microbiome and the pathological features of AD.

Investigating metabolic dysregulation in serum of triple transgenic Alzheimer's disease male mice: implications for pathogenesis and potential biomarkers

Alzheimer's disease (AD) is a multifactorial neurodegenerative disease that lacks convenient and accessible peripheral blood diagnostic markers and effective drugs. Metabolic dysfunction is one of AD risk factors, which leaded to alterations of various metabolites in the body. Pathological changes of the brain can be reflected in blood metabolites that are expected to explain the disease mechanisms or be candidate biomarkers. The aim of this study was to investigate the changes of targeted metabolites within peripheral blood of AD mouse model, with the purpose of exploring the disease mechanism and potential biomarkers. Targeted metabolomics was used to quantify 256 metabolites in serum of triple transgenic AD (3 × Tg-AD) male mice. Compared with controls, 49 differential metabolites represented dysregulation in purine, pyrimidine, tryptophan, cysteine and methionine and glycerophospholipid metabolism. Among them, adenosine, serotonin, N-acetyl-5-hydroxytryptamine, and acetylcholine play a key role in regulating neural transmitter network. The alteration of S-adenosine-L-homocysteine, S-adenosine-L-methionine, and trimethylamine-N-oxide in AD mice serum can served as indicator of AD risk. The results revealed the changes of metabolites in serum, suggesting that metabolic dysregulation in periphery in AD mice may be related to the disturbances in neuroinhibition, the serotonergic system, sleep function, the cholinergic system, and the gut microbiota. This study provides novel insights into the dysregulation of several key metabolites and metabolic pathways in AD, presenting potential avenues for future research and the development of peripheral biomarkers.

Association of metabolic dysfunction with cognitive decline and Alzheimer's disease: A review of metabolomic evidence

The discovery of new biomarkers that can distinguish Alzheimer's disease (AD) from mild cognitive impairment (MCI) in the early stages will help to provide new diagnostic and therapeutic strategies and slow the transition from MCI to AD. Patients with AD may present with a concomitant metabolic disorder, such as diabetes, obesity, and dyslipidemia, as a risk factor for AD that may be involved in the onset of both AD pathology and cognitive impairment. Therefore, metabolite profiling, or metabolomics, can be very useful in diagnosing AD, developing new therapeutic targets, and evaluating both the course of treatment and the clinical course of the disease. In addition, studying the relationship between nutritional behavior and AD requires investigation of the role of conditions such as obesity, hypertension, dyslipidemia, and elevated glucose level. Based on this literature review, nutritional recommendations, including weight loss by reducing calorie and cholesterol intake and omega-3 fatty acid supplementation can prevent cognitive decline and dementia in the elderly. The underlying metabolic causes of the pathology and cognitive decline caused by AD and MCI are not well understood. In this review article, metabolomics biomarkers for diagnosis of AD and MCI and metabolic risk factors for cognitive decline in AD were evaluated.

The comprehensive mechanism underlying Schisandra polysaccharide in AD-like symptoms of Aβ25-35-induced rats based on hippocampal metabolomics and serum lipidomics techniques

As is well documented, Alzheimer's disease (AD) is the most prevalent neurodegenerative disease. Meanwhile, Schisandra polysaccharide (SCP) has been reported to exert a protective effect on the nervous system and can regulate metabolic disorders in AD-like symptoms of amyloid β-peptide (Aβ) 25-35-induced rats. Nevertheless, the underlying mechanisms and metabolic markers for the diagnosis of AD are yet to be determined. This study aimed to explore the neuroprotective effect and potential mechanism of action of SCP in AD-like symptoms of Aβ25-35-induced rats by combining pharmacodynamics, metabolomics, and lipidomics. The pharmacodynamic results revealed that SCP significantly improved the spatial learning and long-term memory function and the morphology of neurons in the hippocampal CA1 region, alleviated inflammatory damage and oxidative stress, inhibited the activation of microglia and astrocytes, and increased the proportion of mature neurons of AD-like symptoms of Aβ25-35-induced rats. The results of hippocampal metabolomics and serum lipidomics showed 46 and 48 potential biomarkers were identified for the SCP treatment of AD, respectively. The involved pathways principally comprised lipid metabolism, amino acid metabolism, and energy metabolism. This study elucidates the neuroprotective effect of SCP in AD and its mechanism from the perspective of metabolomics and lipidomics and provides a theoretical basis for the therapeutic effect of SCP in AD.

Non-invasive biomarkers for mild cognitive impairment and Alzheimer's disease

Alzheimer's disease is the most common type of dementia in the elderly. It is a progressive degenerative disorder that may begin to develop up to 15 years before clinical symptoms appear. The identification of early biomarkers is crucial to enable a prompt diagnosis and to start effective interventions. In this work, we conducted a metabolomic study using proton Nuclear Magnetic Resonance (1H NMR) spectroscopy in serum samples from patients with neuropathologically confirmed Alzheimer's disease (AD, n = 51), mild cognitive impairment (MCI, n = 27), and cognitively healthy controls (HC, n = 50) to search for metabolites that could be used as biomarkers. Patients and controls underwent yearly clinical follow-ups for up to six years. MCI group included samples from three subgroups of subjects with different disease progression rates. The first subgroup included subjects that remained clinically stable at the MCI stage during the period of study (stable MCI, S-MCI, n = 9). The second subgroup accounted for subjects which were diagnosed with MCI at the moment of blood extraction, but progressed to clinical dementia in subsequent years (MCI-to-dementia, MCI-D, n = 14). The last subgroup was composed of subjects that had been diagnosed as dementia for the first time at the moment of sample collection (incipient dementia, Incp-D, n = 4). Partial Least Square Discriminant Analysis (PLS-DA) models were developed. Three models were obtained, one to discriminate between AD and HC samples with high sensitivity (93.75%) and specificity (94.75%), another model to discriminate between AD and MCI samples (100% sensitivity and 82.35% specificity), and a last model to discriminate HC and MCI with lower sensitivity and specificity (67% and 50%). Differences within the MCI group were further studied in an attempt to determine those MCI subjects that could develop AD-type dementia in the future. The relative concentration of metabolites, and metabolic pathways were studied. Alterations in the pathways of alanine, aspartate and glutamate metabolism, pantothenate and CoA biosynthesis, and beta-alanine metabolism, were found when HC and MCI- D patients were compared. In contrast, no pathway was found disturbed in the comparison of S-MCI with HC groups. These results highlight the potential of 1H NMR metabolomics to support the diagnosis of dementia in a less invasive way, and set a starting point for the study of potential biomarkers to identify MCI or HC subjects at risk of developing AD in the future.

An integrated neuroimaging-omics approach for the gut-brain communication pathways in Alzheimer's disease

A key role of the gut microbiota in the pathogenesis of neurodegenerative diseases, such as Alzheimer's disease (AD), has been identified over the past decades. Increasing clinical and preclinical evidence implicates that there is bidirectional communication between the gut microbiota and the central nervous system (CNS), which is also known as the microbiota-gut-brain axis. Nevertheless, current knowledge on the interplay between gut microbiota and the brain remains largely unclear. One of the primary mediating factors by which the gut microbiota interacts with the host is peripheral metabolites, including blood or gut-derived metabolites. However, mechanistic knowledge about the effect of the microbiome and metabolome signaling on the brain is limited. Neuroimaging techniques, such as multi-modal magnetic resonance imaging (MRI), and fluorodeoxyglucose-positron emission tomography (FDG-PET), have the potential to directly elucidate brain structural and functional changes corresponding with alterations of the gut microbiota and peripheral metabolites in vivo. Employing a combination of gut microbiota, metabolome, and advanced neuroimaging techniques provides a future perspective in illustrating the microbiota-gut-brain pathway and further unveiling potential therapeutic targets for AD treatments.

A blood-based, metabolite and demographic characteristic markers panel for the diagnosis of Alzheimer's disease

Aims: This work was designed to provide early diagnosis strategies for Alzheimer's disease (AD) based on the identification of blood metabolic biomarkers. Patients & methods: A total of 90 subjects aged 60 years or older were included in this study; 45 patients were assigned to the case group and control group, respectively. A total of 31 target metabolites were quantitatively analyzed by parallel reaction monitoring between the two groups. Results & conclusion: Three metabolites were screened out, including cystine, serine and alanine/sarcosine. Logistic regression and random forest analysis were used to establish AD diagnosis models, and the model combining metabolic biomarkers and demographic variables had higher detection efficiency (area under the curve = 0.869). A combination diagnostic model to provide a scientific reference for early screening and diagnosis of AD was constructed.

Plasma metabolites associated with cognitive function across race/ethnicities affirming the importance of healthy nutrition

INTRODUCTION

We studied the replication and generalization of previously identified metabolites potentially associated with global cognitive function in multiple race/ethnicities and assessed the contribution of diet to these associations.

METHODS

We tested metabolite-cognitive function associations in U.S.A. Hispanic/Latino adults (n = 2222) from the Community Health Study/ Study of Latinos (HCHS/SOL) and in European (n = 1365) and African (n = 478) Americans from the Atherosclerosis Risk In Communities (ARIC) Study. We applied Mendelian Randomization (MR) analyses to assess causal associations between the metabolites and cognitive function and between Mediterranean diet and cognitive function.

RESULTS

Six metabolites were consistently associated with lower global cognitive function across all studies. Of these, four were sugar-related (e.g., ribitol). MR analyses provided weak evidence for a potential causal effect of ribitol on cognitive function and bi-directional effects of cognitive performance on diet.

DISCUSSION

Several diet-related metabolites were associated with global cognitive function across studies with different race/ethnicities.

HIGHLIGHTS

Metabolites associated with cognitive function in Puerto Rican adults were recently identified. We demonstrate the generalizability of these associations across diverse race/ethnicities. Most identified metabolites are related to sugars. Mendelian Randomization (MR) provides weak evidence for a causal effect of ribitol on cognitive function. Beta-cryptoxanthin and other metabolites highlight the importance of a healthy diet.

Insulin resistance in Alzheimer's disease: The genetics and metabolomics links

Alzheimer's disease (AD) is a neurodegenerative disease with significant socioeconomic burden worldwide. Although genetics and environmental factors play a role, AD is highly associated with insulin resistance (IR) disorders such as metabolic syndrome (MS), obesity, and type two diabetes mellitus (T2DM). These findings highlight a shared pathogenesis. The use of metabolomics as a downstream systems' biology (omics) approach can help to identify these shared metabolic traits and assist in the early identification of at-risk groups and potentially guide therapy. Targeting the shared AD-IR metabolic trait with lifestyle interventions and pharmacological treatments may offer promising AD therapeutic approach. In this narrative review, we reviewed the literature on the AD-IR pathogenic link, the shared genetics and metabolomics biomarkers between AD and IR disorders, as well as the lifestyle interventions and pharmacological treatments which target this pathogenic link.

Analysis of serum metabolism in premature infants before and after feeding using GC-MS and the relationship with necrotizing enterocolitis

Preterm birth and enteral feeding are two main factors leading to necrotizing enterocolitis (NEC). The metabolomics of preterm infants before and after feeding can provide a basis for the prediction of NEC. Using the method of cross-sectional study, the mode was established with the serum samples of 19 premature infants at birth and after feeding as the control group. The serum was analyzed using GC-MS. Chemometric analysis includes principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis. Spectral separation of serum metabolites occurred in premature infants before and after feeding. The levels of xylose, d-talose, phosphoglycolic acid, maleimide, l-gulonolactone, maleic acid, β-hydroxypyruvate, itaconic acid, and pantothenic acid in the serum of premature infants after feeding were significant in both multidimensional and single-dimensional modes (variable importance in projection >2, P < 0.01). There was a moderate correlation between total bilirubin and l-gulonolactone and β-hydroxypyruvate (0.8 > r > 0.5). Maleimide, maleic acid, and itaconic acid have diagnostic value (area under the curve >0.9). The results indicated that serum metabolism of preterm infants changes significantly after feeding. Some metabolites have potential value in predicting NEC.

Multi-Omics, an Integrated Approach to Identify Novel Blood Biomarkers of Alzheimer's Disease

The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD/MCI pathogenesis is unclear. This study compared the metabolomic and proteomic signature of plasma from cognitively normal (CN) and dementia patients diagnosed with MCI or AD, to identify specific cellular pathways and new biomarkers altered with the progression of the disease. We analysed 80 plasma samples from individuals with MCI or AD, as well as age- and gender-matched CN individuals, by utilising mass spectrometry methods and data analyses that included combined pathway analysis and model predictions. Several proteins clearly identified AD from the MCI and CN groups and included plasma actins, mannan-binding lectin serine protease 1, serum amyloid A2, fibronectin and extracellular matrix protein 1 and Keratin 9. The integrated pathway analysis showed various metabolic pathways were affected in AD, such as the arginine, alanine, aspartate, glutamate and pyruvate metabolism pathways. Therefore, our multi-omics approach identified novel plasma biomarkers for the MCI and AD groups, identified changes in metabolic processes, and may form the basis of a biomarker panel for stratifying dementia participants in future clinical trials.

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.

Taurine and Astrocytes: A Homeostatic and Neuroprotective Relationship

Taurine is considered the most abundant free amino acid in the brain. Even though there are endogenous mechanisms for taurine production in neural cells, an exogenous supply of taurine is required to meet physiological needs. Taurine is required for optimal postnatal brain development; however, its brain concentration decreases with age. Synthesis of taurine in the central nervous system (CNS) occurs predominantly in astrocytes. A metabolic coupling between astrocytes and neurons has been reported, in which astrocytes provide neurons with hypotaurine as a substrate for taurine production. Taurine has antioxidative, osmoregulatory, and anti-inflammatory functions, among other cytoprotective properties. Astrocytes release taurine as a gliotransmitter, promoting both extracellular and intracellular effects in neurons. The extracellular effects include binding to neuronal GABAA and glycine receptors, with subsequent cellular hyperpolarization, and attenuation of N-methyl-D-aspartic acid (NMDA)-mediated glutamate excitotoxicity. Taurine intracellular effects are directed toward calcium homeostatic pathway, reducing calcium overload and thus preventing excitotoxicity, mitochondrial stress, and apoptosis. However, several physiological aspects of taurine remain unclear, such as the existence or not of a specific taurine receptor. Therefore, further research is needed not only in astrocytes and neurons, but also in other glial cells in order to fully comprehend taurine metabolism and function in the brain. Nonetheless, astrocyte’s role in taurine-induced neuroprotective functions should be considered as a promising therapeutic target of several neuroinflammatory, neurodegenerative and psychiatric diseases in the near future. This review provides an overview of the significant relationship between taurine and astrocytes, as well as its homeostatic and neuroprotective role in the nervous system.

A multi-omics analysis for the prediction of neurocognitive disorders risk among the elderly in Macao

BACKGROUND

Due to the increasing ageing population, neurocognitive disorders (NCDs) have been a global public health issue, and its prevention and early diagnosis are crucial. Our previous study demonstrated that there is a significant correlation between specific populations and NCDs, but the biological characteristics of the vulnerable group predispose to NCDs are unclear. The purpose of this study is to investigate the predictors for the vulnerable group by a multi-omics analysis.

METHODS

Multi-omics approaches, including metagenomics, metabolomic and proteomic, were used to detect gut microbiota, faecal metabolites and urine exosome of 8 normal controls and 13 vulnerable elders after a rigorous screening of 400 elders in Macao. The multi-omics data were analysed using R and Bioconductor. The two-sided Wilcoxon's rank-sum test, Kruskal-Wallis rank sum test and the linear discriminant analysis effective size were applied to investigate characterized features. Moreover, a 2-year follow-up was conducted to evaluate cognitive function change of the elderly.

RESULTS

Compared with the control elders, the metagenomics of gut microbiota showed that Ruminococcus gnavus, Lachnospira eligens, Escherichia coli and Desulfovibrio piger were increased significantly in the vulnerable group. Carboxylates, like alpha-ketoglutaric acid and d-saccharic acid, and levels of vitamins had obvious differences in the faecal metabolites. There was a distinct decrease in the expression of eukaryotic translation initiation factor 2 subunit 1 (eIF2α) and amine oxidase A (MAO-A) according to the proteomic results of the urine exosomes. Moreover, the compound annual growth rate of neurocognitive scores was notably decreased in vulnerable elders.

CONCLUSIONS

The multi-omics characteristics of disturbed glyoxylate and dicarboxylate metabolism (bacteria), vitamin digestion and absorption and tricarboxylic acid cycle in vulnerable elders can serve as predictors of NCDs risk among the elderly of Macao. Intervention with them may be effective therapeutic approaches for NCDs, and the underlying mechanisms merit further exploration.

Blood-Based Biomarkers for Alzheimer's Disease Diagnosis and Progression: An Overview

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, and no disease-modifying therapies are presently available. Fluid biomarker discovery for AD is a rapidly expanding field of research aimed at anticipating disease diagnosis and following disease progression over time. Currently, Aβ_1–42, phosphorylated tau, and total tau levels in the cerebrospinal fluid are the best-studied fluid biomarkers for AD, but the need for novel, cheap, less-invasive, easily detectable, and more-accessible markers has recently led to the search for new blood-based molecules. However, despite considerable research activity, a comprehensive and up-to-date overview of the main blood-based biomarker candidates is still lacking. In this narrative review, we discuss the role of proteins, lipids, metabolites, oxidative-stress-related molecules, and cytokines as possible disease biomarkers. Furthermore, we highlight the potential of the emerging miRNAs and long non-coding RNAs (lncRNAs) as diagnostic tools, and we briefly present the role of vitamins and gut-microbiome-related molecules as novel candidates for AD detection and monitoring, thus offering new insights into the diagnosis and progression of this devastating disease.

A Review of Bile Acid Metabolism and Signaling in Cognitive Dysfunction-Related Diseases

Bile acids are commonly known as one of the vital metabolites derived from cholesterol. The role of bile acids in glycolipid metabolism and their mechanisms in liver and cholestatic diseases have been well studied. In addition, bile acids also serve as ligands of signal molecules such as FXR, TGR5, and S1PR2 to regulate some physiological processes in vivo. Recent studies have found that bile acids signaling may also play a critical role in the central nervous system. Evidence showed that some bile acids have exhibited neuroprotective effects in experimental animal models and clinical trials of many cognitive dysfunction-related diseases. Besides, alterations in bile acid metabolisms well as the expression of different bile acid receptors have been discovered as possible biomarkers for prognosis tools in multiple cognitive dysfunction-related diseases. This review summarizes biosynthesis and regulation of bile acids, receptor classification and characteristics, receptor agonists and signaling transduction, and recent findings in cognitive dysfunction-related diseases.

Cerebrospinal Fluid Amino Acid Metabolite Signatures of Diabetic Cognitive Dysfunction Based on Targeted Mass Spectrometry

BACKGROUND

Diabetic cognitive dysfunction (DCD) is one of severe diabetic complications and might develop to irreversible dementia. Early diagnosis and detection of DCD is significant for prevention and treatment.

OBJECTIVE

The main objective of this study was to investigate the amino acid profiles of rat with DCD in the cerebrospinal fluid (CSF) to distinguish the early specific biomarkers.

METHODS

In total, rats were assigned into control and model groups. Model was induced by intraperitoneal injection of streptozotocin. The Morris water maze (MWM) method was used to evaluate learning and memory in rats on the 13th week after the model established. CSF samples were collected via cisterna magna puncture at the 0th, 5th, 9th, and 13th week, and amino acids profiling of CSF samples were performed via ultra performance liquid chromatography multiple reaction monitoring mass spectrometry (UPLC-MRM-MS). The amino acid profile was processed through multivariate analysis to identify potential biomarkers, and the related metabolic pathways were analyzed by MetaboAnalyst 5.0.

RESULTS

Compared to the control group, the escape latency of the MWM was significantly prolonged in model group rats (p <  0.05). Different amino acid profiles were obtained between two groups. L-Alanine, L-Glutamine, L-Lysine, L-Serine, and L-Threonine were identified as potential biomarkers for DCD. These biomarkers are principally involved in glycine, serine, and threonine metabolism, aminoacyl-tRNA biosynthesis, alanine, aspartate, and glutamate metabolism, and glyoxylate and dicarboxylate metabolism.

CONCLUSION

There are amino acid biomarkers in the CSF of rat with DCD. The mechanism of DCD is related to those pathways, which provide help for the early diagnosis and treatment and mechanism research.

Recent Advances in Understanding of Alzheimer's Disease Progression through Mass Spectrometry-Based Metabolomics

Alzheimer's disease (AD) is the leading cause of dementia in the aging population, but despite extensive research, there is no consensus on the biological cause of AD. While AD research is dominated by protein/peptide-centric research based on the amyloid hypothesis, a theory that designates dysfunction in beta-amyloid production, accumulation, or disposal as the primary cause of AD, many studies focus on metabolomics as a means of understanding the biological processes behind AD progression. In this review, we discuss mass spectrometry (MS)-based AD metabolomics studies, including sample type and preparation, mass spectrometry specifications, and data analysis, as well as biological insights gleaned from these studies, with the hope of informing future AD metabolomic studies.

Small phenolic and indolic gut-dependent molecules in the primate central nervous system: levels vs. bioactivity

INTRODUCTION

A rapidly growing body of data documents associations between disease of the brain and small molecules generated by gut-microbiota (GMB). While such metabolites can affect brain function through a variety of mechanisms, the most direct action would be on the central nervous system (CNS) itself.

OBJECTIVE

Identify indolic and phenolic GMB-dependent small molecules that reach bioactive concentrations in primate CNS.

METHODS

We conducted a PubMed search for metabolomic studies of the primate CNS [brain tissue or cerebrospinal fluid (CSF)] and then selected for phenolic or indolic metabolites that (i) had been quantified, (ii) were GMB-dependent. For each chemical we then conducted a search for studies of bioactivity conducted in vitro in human cells of any kind or in CNS cells from the mouse or rat.

RESULTS

36 metabolites of interests were identified in primate CNS through targeted metabolomics. Quantification was available for 31/36 and in vitro bioactivity for 23/36. The reported CNS range for 8 metabolites 2-(3-hydroxyphenyl)acetic acid, 2-(4-hydroxyphenyl)acetic acid, 3-(3-hydroxyphenyl)propanoic acid, (E)-3-(3,4-dihydroxyphenyl)prop-2-enoic acid [caffeic acid], 3-hydroxybenzoic acid, 4-hydroxybenzoic acid, 2-acetamido-3-(1H-indol-3-yl)propanoic acid [N-acetyltryptophan], 1H-indol-3-yl hydrogen sulfate [indoxyl-3-sulfate] overlapped with a bioactive concentration. However, the number and quality of relevant studies of CNS neurochemistry as well as of bioactivity were highly limited. Structural isomers, multiple metabolites and potential confounders were inadequately considered.

CONCLUSION

The potential direct bioactivity of GMB-derived indolic and phenolic molecules on primate CNS remains largely unknown. The field requires additional strategies to identify and prioritize screening of the most promising small molecules that enter the CNS.

Tilapia Head Protein Hydrolysate Attenuates Scopolamine-Induced Cognitive Impairment through the Gut-Brain Axis in Mice

The destruction of the homeostasis in the gut-brain axis can lead to cognitive impairment and memory decline. Dietary intervention with bioactive peptides from aquatic products is an innovative strategy to prevent cognitive deficits. The present study aimed to determine the neuroprotective effect of tilapia head protein hydrolysate (THPH) on scopolamine-induced cognitive impairment in mice, and to further explore its mechanism through the microbiota–gut-brain axis. The results showed that THPH administration significantly improved the cognitive behavior of mice, and normalized the cholinergic system and oxidative stress system of the mice brain. The histopathological observation showed that THPH administration significantly reduced the pathological damage of hippocampal neurons, increased the number of mature neurons marked by NeuN and delayed the activation of astrocytes in the hippocampus of mice. In addition, THPH administration maintained the stability of cholinergic system, alleviated oxidative stress and further improved the cognitive impairment by reshaping the gut microbiota structure of scopolamine-induced mice and alleviating the disorder of lipid metabolism and amino acid metabolism in serum. In conclusion, our research shows that THPH supplementation is a nutritional strategy to alleviate cognitive impairment through the gut-brain axis.

Metabolic Profiling of Neocortical Tissue Discriminates Alzheimer's Disease from Mild Cognitive Impairment, High Pathology Controls, and Normal Controls

Alzheimer's disease (AD) is the most common cause of dementia, accounting for an estimated 60-80% of cases, and is the sixth-leading cause of death in the United States. While considerable advancements have been made in the clinical care of AD, it remains a complicated disorder that can be difficult to identify definitively in its earliest stages. Recently, mass spectrometry (MS)-based metabolomics has shown significant potential for elucidation of disease mechanisms and identification of therapeutic targets as well diagnostic and prognostic markers that may be useful in resolving some of the difficulties affecting clinical AD studies, such as effective stratification. In this study, complementary gas chromatography- and liquid chromatography-MS platforms were used to detect and monitor 2080 metabolites and features in 48 postmortem tissue samples harvested from the superior frontal gyrus of male and female subjects. Samples were taken from four groups: 12 normal control (NC) patients, 12 cognitively normal subjects characterized as high pathology controls (HPC), 12 subjects with nonspecific mild cognitive impairment (MCI), and 12 subjects with AD. Multivariate statistics informed the construction and cross-validation (p < 0.01) of partial least squares-discriminant analysis (PLS-DA) models defined by a nine-metabolite panel of disease markers (lauric acid, stearic acid, myristic acid, palmitic acid, palmitoleic acid, and four unidentified mass spectral features). Receiver operating characteristic analysis showed high predictive accuracy of the resulting PLS-DA models for discrimination of NC (97%), HPC (92%), MCI (∼96%), and AD (∼96%) groups. Pathway analysis revealed significant disturbances in lysine degradation, fatty acid metabolism, and the degradation of branched-chain amino acids. Network analysis showed significant enrichment of 11 enzymes, predominantly within the mitochondria. The results expand basic knowledge of the metabolome related to AD and reveal pathways that can be targeted therapeutically. This study also provides a promising basis for the development of larger multisite projects to validate these candidate markers in readily available biospecimens such as blood to enable the effective screening, rapid diagnosis, accurate surveillance, and therapeutic monitoring of AD. All raw mass spectrometry data have been deposited to MassIVE (data set identifier MSV000087165).

Biomarkers for the Clinical Diagnosis of Alzheimer's Disease: Metabolomics Analysis of Brain Tissue and Blood

With an increase in aging populations worldwide, age-related diseases such as Alzheimer's disease (AD) have become a global concern. At present, a cure for neurodegenerative disease is lacking. There is an urgent need for a biomarker that can facilitate the diagnosis, classification, prognosis, and treatment response of AD. The recent emergence of highly sensitive mass-spectrometry platforms and high-throughput technology can be employed to discover and catalog vast datasets of small metabolites, which respond to changed status in the body. Metabolomics analysis provides hope for a better understanding of AD as well as the subsequent identification and analysis of metabolites. Here, we review the state-of-the-art emerging candidate biomarkers for AD.

Fecal Fungal Dysbiosis in Chinese Patients With Alzheimer's Disease

Gut bacterial dysbiosis plays a vital role in the development of Alzheimer’s disease (AD). However, our understanding of alterations to the gut fungal microbiota and their correlations with host immunity in AD is still limited. Samples were obtained from 88 Chinese patients with AD, and 65 age- and gender-matched, cognitively normal controls. Using these samples, we investigated the fungal microbiota targeting internal transcribed spacer 2 (ITS2) rRNA genes using MiSeq sequencing, and analyzed their associations with the host immune response. Our data demonstrated unaltered fungal diversity but altered taxonomic composition of the fecal fungal microbiota in the AD patients. The analysis of the fungal microbiota was performed using 6,585,557 high-quality reads (2,932,482 reads from the controls and 3,653,075 from the AD patients), with an average of 43,042 reads per sample. We found that several key differential fungi such as Candida tropicalis and Schizophyllum commune were enriched in the AD patients, while Rhodotorula mucilaginosa decreased significantly. Interestingly, C. tropicalis and S. commune were positively correlated with IP-10 and TNF-α levels. In contrast, C. tropicalis was negatively correlated with IL-8 and IFN-γ levels, and R. mucilaginosa was negatively correlated with TNF-α level. PiCRUSt analysis revealed that lipoic acid metabolism, starch and sucrose metabolism were significantly decreased in the AD fungal microbiota. This study is the first to demonstrate fecal fungal dysbiosis in stable AD patients at a deeper level, and to identify the key differential fungi involved in regulating host systemic immunity. The analysis of the fungal microbiota in AD performed here may provide novel insights into the etiopathogenesis of AD and pave the way for improved diagnosis and treatment of AD.

Salivaomics as a Potential Tool for Predicting Alzheimer's Disease During the Early Stages of Neurodegeneration

BACKGROUND

The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is poorly understood and the relationships between systemic abnormalities in metabolism and AD/AMCI pathogenesis are unclear.

OBJECTIVE

The aim of the study was to compare the metabolomic and proteomic signature of saliva from cognitively normal and patients diagnosed with MCI or AD, to identify specific cellular pathways altered with the progression of the disease.

METHODS

We analyzed 80 saliva samples from individuals with MCI or AD as well as age- and gender-matched healthy controls. Saliva proteomic and metabolomic analyses were conducted utilizing mass spectrometry methods and data combined using pathway analysis.

RESULTS

We found significant alterations in multiple cellular pathways, demonstrating that at the omics level, disease progression impacts numerous cellular processes. Multivariate statistics using SIMCA showed that partial least squares-data analysis could be used to provide separation of the three groups.

CONCLUSION

This study found significant changes in metabolites and proteins from multiple cellular pathways in saliva. These changes were associated with AD, demonstrating that this approach might prove useful to identify new biomarkers based upon integration of multi-omics parameters.

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.