High-Throughput Metabolomics for Discovering Potential Biomarkers and Identifying Metabolic Mechanisms in Aging and Alzheimer's Disease

Metabolomic and Proteomic Analysis of ApoE4-Carrying H4 Neuroglioma Cells in Alzheimer's Disease Using OrbiSIMS and LC-MS/MS

Growing clinical evidence reveals that systematic molecular alterations in the brain occur 20 years before the onset of AD pathological features. Apolipoprotein E4 (ApoE4) is one of the most significant genetic risk factors for Alzheimer's disease (AD), which is not only associated with the AD pathological features such as amyloid-β deposition, phosphorylation of tau proteins, and neuroinflammation but is also involved in metabolism, neuron growth, and synaptic plasticity. Multiomics, such as metabolomics and proteomics, are applied widely in identifying key disease-related molecular alterations and disease-progression-related changes. Despite recent advances in the development of analytical technologies, screening the entire profile of metabolites remains challenging due to the numerous classes of compounds with diverse chemical properties that require different extraction processes for mass spectrometry. In this study, we utilized Orbitrap Secondary Ion Mass Spectrometry (OrbiSIMS) as a chemical filtering screening tool to examine molecular alterations in ApoE4-carried neuroglioma cells compared to wild-type H4 cells. The findings were compared using liquid chromatography (LC)-MS/MS targeted metabolomics analysis for the confirmation of specific metabolite classes. Detected alterations in peptide fragments by OrbiSIMS provided preliminary indications of protein changes. These were extensively analyzed through proteomics to explore ApoE4's impact on proteins. Our metabolomics approach, combining OrbiSIMS and LC-MS/MS, revealed disruptions in lipid metabolism, including glycerophospholipids and sphingolipids, as well as amino acid metabolism, encompassing alanine, aspartate, and glutamate metabolism; aminoacyl-tRNA biosynthesis; glutamine metabolism; and taurine and hypotaurine metabolism. Further LC-MS/MS proteomics studies confirmed the dysfunction in amino acid and tRNA aminoacylation metabolic processes, and highlighted RNA splicing alterations influenced by ApoE4.

L-arginine metabolism ameliorates age-related cognitive impairment by Amuc_1100-mediated gut homeostasis maintaining

Aging-induced cognitive impairment is associated with a loss of metabolic homeostasis and plasticity. An emerging idea is that targeting key metabolites is sufficient to impact the function of other organisms. Therefore, more metabolism-targeted therapeutic intervention is needed to improve cognitive impairment. We first conducted untargeted metabolomic analyses and 16S rRNA to identify the aging-associated metabolic adaption and intestinal microbiome change. Untargeted metabolomic analyses of plasma revealed L-arginine metabolic homeostasis was altered during the aging process. Impaired L-arginine metabolic homeostasis was associated with low abundance of intestinal Akkermansia muciniphila (AKK) colonization in mice. Long-term supplementation of AKK outer membranes protein-Amuc_1100, rescued the L-arginine level and restored cognitive impairment in aging mice. Mechanically, Amuc_1100 acted directly as a source of L-arginine and enriched the L-arginine-producing bacteria. In aged brain, Amuc_1100 promoted the superoxide dismutase to alleviated oxidation stress, and increased nitric oxide, derivatives of L-arginine, to improve synaptic plasticity. Meanwhile, L-arginine repaired lipopolysaccharide-induced intestinal barrier damage and promoted growth of colon organoid. Our findings indicated that aging-related cognitive impairment was closely associated with the disorders of L-arginine metabolism. AKK-derived Amuc_1100, as a potential postbiotic, targeting the L-arginine metabolism, might provide a promising therapeutic strategy to maintain the intestinal homeostasis and cognitive function in aging.

Bayesian functional analysis for untargeted metabolomics data with matching uncertainty and small sample sizes

Untargeted metabolomics based on liquid chromatography-mass spectrometry technology is quickly gaining widespread application, given its ability to depict the global metabolic pattern in biological samples. However, the data are noisy and plagued by the lack of clear identity of data features measured from samples. Multiple potential matchings exist between data features and known metabolites, while the truth can only be one-to-one matches. Some existing methods attempt to reduce the matching uncertainty, but are far from being able to remove the uncertainty for most features. The existence of the uncertainty causes major difficulty in downstream functional analysis. To address these issues, we develop a novel approach for Bayesian Analysis of Untargeted Metabolomics data (BAUM) to integrate previously separate tasks into a single framework, including matching uncertainty inference, metabolite selection and functional analysis. By incorporating the knowledge graph between variables and using relatively simple assumptions, BAUM can analyze datasets with small sample sizes. By allowing different confidence levels of feature-metabolite matching, the method is applicable to datasets in which feature identities are partially known. Simulation studies demonstrate that, compared with other existing methods, BAUM achieves better accuracy in selecting important metabolites that tend to be functionally consistent and assigning confidence scores to feature-metabolite matches. We analyze a COVID-19 metabolomics dataset and a mouse brain metabolomics dataset using BAUM. Even with a very small sample size of 16 mice per group, BAUM is robust and stable. It finds pathways that conform to existing knowledge, as well as novel pathways that are biologically plausible.

Can Small Molecules Provide Clues on Disease Progression in Cerebrospinal Fluid from Mild Cognitive Impairment and Alzheimer's Disease Patients?

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease, which is currently diagnosed via clinical symptoms and nonspecific biomarkers (such as Aβ1-42, t-Tau, and p-Tau) measured in cerebrospinal fluid (CSF), which alone do not provide sufficient insights into disease progression. In this pilot study, these biomarkers were complemented with small-molecule analysis using non-target high-resolution mass spectrometry coupled with liquid chromatography (LC) on the CSF of three groups: AD, mild cognitive impairment (MCI) due to AD, and a non-demented (ND) control group. An open-source cheminformatics pipeline based on MS-DIAL and patRoon was enhanced using CSF- and AD-specific suspect lists to assist in data interpretation. Chemical Similarity Enrichment Analysis revealed a significant increase of hydroxybutyrates in AD, including 3-hydroxybutanoic acid, which was found at higher levels in AD compared to MCI and ND. Furthermore, a highly sensitive target LC-MS method was used to quantify 35 bile acids (BAs) in the CSF, revealing several statistically significant differences including higher dehydrolithocholic acid levels and decreased conjugated BA levels in AD. This work provides several promising small-molecule hypotheses that could be used to help track the progression of AD in CSF samples.

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.

Chronic exposure to parabens promotes non-alcoholic fatty liver disease in association with the changes of the gut microbiota and lipid metabolism

Non-alcoholic fatty liver disease (NAFLD) has become a serious public health issue due to changing dietary patterns and composition. However, the relationship between NAFLD occurrence and food additives, such as preservatives, remains unknown. This study aimed to evaluate the toxicity of parabens, namely methylparaben (MeP) and ethylparaben (EtP), in relation to NAFLD occurrence in mice under different dietary conditions. Exposure to MeP and EtP exacerbated high-fat diet (HFD)-induced obesity, glucose intolerance, higher serum lipid concentrations, and fat accumulation by upregulating genes involved in lipid metabolism. Untargeted metabolomics revealed that arachidonic acid (AA) metabolism was the top enriched pathway upon MeP and EtP exposure in the presence of HFD. 11,12-Epoxyeicosatrienoic acid (11,12-EET) was the most abundant AA metabolite and was significantly reduced upon exposure to MeP or EtP. Moreover, an integrative analysis of differential fecal taxa at the genus level and serum AA metabolites revealed significant associations. In addition, MeP and EtP enhanced lipid accumulation in AML12 cells and HepG2 cells cultured with oleic acid. 11,12-EET supplementation could significantly alleviate lipid accumulation by suppressing the expression of lipid metabolism-related genes and proteins. The present study suggests that chronic exposure to MeP and EtP promoted NAFLD via gut microbiota-dependent AA metabolism. These results highlight the need for reducing oral exposure to synthetic preservatives to improve metabolic disturbance under HFD conditions.

Microbiota from Alzheimer's patients induce deficits in cognition and hippocampal neurogenesis

Alzheimer's disease is a complex neurodegenerative disorder leading to a decline in cognitive function and mental health. Recent research has positioned the gut microbiota as an important susceptibility factor in Alzheimer's disease by showing specific alterations in the gut microbiome composition of Alzheimer's patients and in rodent models. However, it is unknown whether gut microbiota alterations are causal in the manifestation of Alzheimer's symptoms. To understand the involvement of Alzheimer's patient gut microbiota in host physiology and behaviour, we transplanted faecal microbiota from Alzheimer's patients and age-matched healthy controls into microbiota-depleted young adult rats. We found impairments in behaviours reliant on adult hippocampal neurogenesis, an essential process for certain memory functions and mood, resulting from Alzheimer's patient transplants. Notably, the severity of impairments correlated with clinical cognitive scores in donor patients. Discrete changes in the rat caecal and hippocampal metabolome were also evident. As hippocampal neurogenesis cannot be measured in living humans but is modulated by the circulatory systemic environment, we assessed the impact of the Alzheimer's systemic environment on proxy neurogenesis readouts. Serum from Alzheimer's patients decreased neurogenesis in human cells in vitro and were associated with cognitive scores and key microbial genera. Our findings reveal for the first time, that Alzheimer's symptoms can be transferred to a healthy young organism via the gut microbiota, confirming a causal role of gut microbiota in Alzheimer's disease, and highlight hippocampal neurogenesis as a converging central cellular process regulating systemic circulatory and gut-mediated factors in Alzheimer's.

Gut microbiota links to serum ferritin and cognition

Iron is required for the replication and growth of almost all bacterial species and in the production of myelin and neurotransmitters. Increasing clinical studies evidence that the gut microbiota plays a critical role in iron metabolism and cognition. However, the understanding of the complex iron-microbiome-cognition crosstalk remains elusive. In a recent study in the Aging Imageomics cohort (n = 1,030), we identified a positive association of serum ferritin (SF) with executive function (EF) as inferred from the semantic verbal fluency (SVF,) the total digit span (TDS) and the phonemic verbal fluency tests (PVF). Here, we explored the potential mechanisms by analyzing the gut microbiome and plasma metabolome using shotgun metagenomics and HPLC-ESI-MS/MS, respectively. Different bacterial species belonging to the Proteobacteria phylum (Klebsiella pneumoniae, Klebsiella michiganensis, Unclassified Escherichia) were negatively associated both with SF and executive function. At the functional level, an enrichment of microbial pathways involved in phenylalanine, arginine, and proline metabolism was identified. Consistently, phenylacetylglutamine, a metabolite derived from microbial catabolism of phenylalanine, was negatively associated with SF, EF, and semantic memory. Other metabolites such as ureidobutyric acid and 19,20-DiHDPA, a DHA-derived oxylipin, were also consistently and negatively associated with SF, EF, and semantic memory, while plasma eicosapentaenoic acid was positively associated. The associations of SF with cognition could be mediated by the gut microbiome through microbial-derived metabolites.

Data-driven transcriptomics analysis identifies PCSK9 as a novel key regulator in liver aging

The liver, as a crucial metabolic organ, undergoes significant pathological changes during the aging process, which can have a profound impact on overall health. To gain a comprehensive understanding of these alterations, we employed data-driven approaches, along with biochemical methods, histology, and immunohistochemistry techniques, to systematically investigate the effects of aging on the liver. Our study utilized a well-established rat aging model provided by the National Institute of Aging. Systems biology approaches were used to analyze genome-wide transcriptomics data from liver samples obtained from young (4-5 months old) and aging (20-21 months old) Fischer 344 rats. Our findings revealed pathological changes occurring in various essential biological processes in aging livers. These included mitochondrial dysfunction, increased oxidative/nitrative stress, decreased NAD + content, impaired amino acid and protein synthesis, heightened inflammation, disrupted lipid metabolism, enhanced apoptosis, senescence, and fibrosis. These results were validated using independent datasets from both human and rat aging studies. Furthermore, by employing co-expression network analysis, we identified novel driver genes responsible for liver aging, confirmed our findings in human aging subjects, and pointed out the cellular localization of the driver genes using single-cell RNA-sequencing human data. Our study led to the discovery and validation of a liver-specific gene, proprotein convertase subtilisin/kexin type 9 (PCSK9), as a potential therapeutic target for mitigating the pathological processes associated with aging in the liver. This finding envisions new possibilities for developing interventions aimed to improve liver health during the aging process.

Metabolic changes in the plasma of mild Alzheimer's disease patients treated with Hachimijiogan

Background: Alzheimer's disease (AD), the most prevalent form of dementia, is a debilitating, progressive neurodegeneration. Amino acids play a wide variety of physiological and pathophysiological roles in the nervous system, and their levels and disorders related to their synthesis have been related to cognitive impairment, the core feature of AD. Our previous multicenter trial showed that hachimijiogan (HJG), a traditional Japanese herbal medicine (Kampo), has an adjuvant effect for Acetylcholine estelase inhibitors (AChEIs) and that it delays the deterioration of the cognitive dysfunction of female patients with mild AD. However, there are aspects of the molecular mechanism(s) by which HJG improves cognitive dysfunction that remain unclear. Objectives: To elucidate through metabolomic analysis the mechanism(s) of HJG for mild AD based on changes in plasma metabolites. Methods: Sixty-seven patients with mild AD were randomly assigned to either an HJG group taking HJG extract 7.5 g/day in addition to AChEI or to a control group treated only with AChEI (HJG:33, Control:34). Blood samples were collected before, 3 months, and 6 months after the first drug administration. Comprehensive metabolomic analyses of plasma samples were done by optimized LC-MS/MS and GC-MS/MS methods. The web-based software MetaboAnalyst 5.0 was used for partial least square-discriminant analysis (PLS-DA) to visualize and compare the dynamics of changes in the concentrations of the identified metabolites. Results: The VIP (Variable Importance in Projection) score of the PLS-DA analysis of female participants revealed a significantly higher increase in plasma metabolite levels after HJG administration for 6 months than was seen in the control group. In univariate analysis, the aspartic acid level of female participants showed a significantly higher increase from baseline after HJG administration for 6 months when compared with the control group. Conclusion: Aspartic acid was a major contributor to the difference between the female HJG and control group participants of this study. Several metabolites were shown to be related to the mechanism of HJG effectiveness for mild AD.

Structural-Activity Relationship of Rare Ginsenosides from Red Ginseng in the Treatment of Alzheimer's Disease

Rare ginsenosides are the major components of red ginseng. However, there has been little research into the relationship between the structure of ginsenosides and their anti-inflammatory activity. In this work, BV-2 cells induced by lipopolysaccharide (LPS) or nigericin, the anti-inflammatory activity of eight rare ginsenosides, and the target proteins expression of AD were compared. In addition, the Morris water maze test, HE staining, thioflavins staining, and urine metabonomics were used to evaluate the effect of Rh4 on AD mice. Our results showed that their configuration influences the anti-inflammatory activity of ginsenosides. Ginsenosides Rk1, Rg5, Rk3, and Rh4 have significant anti-inflammatory activity compared to ginsenosides S-Rh1, R-Rh1, S-Rg3, and R-Rg3. Ginsenosides S-Rh1 and S-Rg3 have more pronounced anti-inflammatory activity than ginsenosides R-Rh1 and R-Rg3, respectively. Furthermore, the two pairs of stereoisomeric ginsenosides can significantly reduce the level of NLRP3, caspase-1, and ASC in BV-2 cells. Interestingly, Rh4 can improve the learning ability of AD mice, improve cognitive impairment, reduce hippocampal neuronal apoptosis and Aβ deposition, and regulate AD-related pathways such as the tricarboxylic acid cycle and the sphingolipid metabolism. Our findings conclude that rare ginsenosides with a double bond have more anti-inflammatory activity than those without, and 20(S)-ginsenosides have more excellent anti-inflammatory activity than 20(R)-ginsenosides.

Proline Metabolism in Neurological and Psychiatric Disorders

Proline plays a multifaceted role in protein synthesis, redox balance, cell fate regulation, brain development, and other cellular and physiological processes. Here, we focus our review on proline metabolism in neurons, highlighting the role of dysregulated proline metabolism in neuronal dysfunction and consequently neurological and psychiatric disorders. We will discuss the association between genetic and protein function of enzymes in the proline pathway and the development of neurological and psychiatric disorders. We will conclude with a potential mechanism of proline metabolism in neuronal function and mental health.

Modulation of Small RNA Signatures by Astrocytes on Early Neurodegeneration Stages; Implications for Biomarker Discovery

Diagnosis of neurodegenerative disease (NDD) is complex, therefore simpler, less invasive, more accurate biomarkers are needed. small non-coding RNA (sncRNA) dysregulates in NDDs and sncRNA signatures have been explored for the diagnosis of NDDs, however, the performance of previous biomarkers is still better. Astrocyte dysfunction promotes neurodegeneration and thus derived scnRNA signatures could provide a more precise way to identify of changes related to NDD course and pathogenesis, and it could be useful for the dissection of mechanistic insights operating in NDD. Often sncRNA are transported outside the cell by the action of secreted particles such as extracellular vesicles (EV), which protect sncRNA from degradation. Furthermore, EV associated sncRNA can cross the BBB to be found in easier to obtain peripheral samples, EVs also inherit cell-specific surface markers that can be used for the identification of Astrocyte Derived Extracellular Vesicles (ADEVs) in a peripheral sample. By the study of the sncRNA transported in ADEVs it is possible to identify astrocyte specific sncRNA signatures that could show astrocyte dysfunction in a more simpler manner than previous methods. However, sncRNA signatures in ADEV are not a copy of intracellular transcriptome and methodological aspects such as the yield of sncRNA produced in ADEV or the variable amount of ADEV captured after separation protocols must be considered. Here we review the role as signaling molecules of ADEV derived sncRNA dysregulated in conditions associated with risk of neurodegeneration, providing an explanation of why to choose ADEV for the identification of astrocyte-specific transcriptome. Finally, we discuss possible limitations of this approach and the need to improve the detection limits of sncRNA for the use of ADEV derived sncRNA signatures.

Associations of the Lipidome with Ageing, Cognitive Decline and Exercise Behaviours

One of the most recognisable features of ageing is a decline in brain health and cognitive dysfunction, which is associated with perturbations to regular lipid homeostasis. Although ageing is the largest risk factor for several neurodegenerative diseases such as dementia, a loss in cognitive function is commonly observed in adults over the age of 65. Despite the prevalence of normal age-related cognitive decline, there is a lack of effective methods to improve the health of the ageing brain. In light of this, exercise has shown promise for positively influencing neurocognitive health and associated lipid profiles. This review summarises age-related changes in several lipid classes that are found in the brain, including fatty acyls, glycerolipids, phospholipids, sphingolipids and sterols, and explores the consequences of age-associated pathological cognitive decline on these lipid classes. Evidence of the positive effects of exercise on the affected lipid profiles are also discussed to highlight the potential for exercise to be used therapeutically to mitigate age-related changes to lipid metabolism and prevent cognitive decline in later life.

Comparative Metabolomics Analysis Reveals Key Metabolic Mechanisms and Protein Biomarkers in Alzheimer’s Disease

Alzheimer’s disease (AD) is one of the most common progressive neurodegenerative diseases, accompanied by global alterations in metabolic profiles. In the past 10 years, over hundreds of metabolomics studies have been conducted to unravel metabolic changes in AD, which provides insight into the identification of potential biomarkers for diagnosis, treatment, and prognostic assessment. However, since different species may lead to systemic abnormalities in metabolomic profiles, it is urgently needed to perform a comparative metabolomics analysis between AD animal models and human patients. In this study, we integrated 78 metabolic profiles from public literatures, including 11 metabolomics studies in different AD mouse models and 67 metabolomics studies from AD patients. Metabolites and enrichment analysis were further conducted to reveal key metabolic pathways and metabolites in AD. We totally identified 14 key metabolites and 16 pathways that are both differentially significant in AD mouse models and patients. Moreover, we built a metabolite-target network to predict potential protein markers in AD. Finally, we validated HER2 and NDF2 as key protein markers in APP/PS1 mice. Overall, this study provides a comprehensive strategy for AD metabolomics research, contributing to understanding the pathological mechanism of AD.

Acupuncture Effect Assessment in APP/PS1 Transgenic Mice: On Regulating Learning-Memory Abilities, Gut Microbiota, and Microbial Metabolites

Alzheimer's disease (AD) is a brain illness that affects learning and memory capacities over time. In recent investigations, acupuncture has been shown to be an effective alternative treatment for AD. We investigated the effect of acupuncture on learning and memory abilities using a water maze in APP/PS1 transgenic mice. The amounts of Aβ and tau protein in mice's hippocampal tissue were determined using Western blot. The levels of IL-1β, IL-10, LPS and TNF-α in mice's serum were measured using ELISA. The variations of gut microbiota in mice's feces were determined using the 16SrDNA technique, and the metabolites were examined using a untargeted metabolomics methodology. The results showed that acupuncture treatment improved mice's learning and memory abilities substantially. Acupuncture therapy regulated the Aβ and tau protein concentration as well as the levels of IL-10 and LPS. Acupuncture treatment influenced the mouse microbiota and metabolites and had been linked to six biochemical pathways. This study adds to our understanding of the effect of acupuncture on AD and opens the door to further research into the alterations of intestinal bacteria in the presence of AD.

Clinical Insights into Mitochondrial Neurodevelopmental and Neurodegenerative Disorders: Their Biosignatures from Mass Spectrometry-Based Metabolomics

Mitochondria are dynamic multitask organelles that function as hubs for many metabolic pathways. They produce most ATP via the oxidative phosphorylation pathway, a critical pathway that the brain relies on its energy need associated with its numerous functions, such as synaptic homeostasis and plasticity. Therefore, mitochondrial dysfunction is a prevalent pathological hallmark of many neurodevelopmental and neurodegenerative disorders resulting in altered neurometabolic coupling. With the advent of mass spectrometry (MS) technology, MS-based metabolomics provides an emerging mechanistic understanding of their global and dynamic metabolic signatures. In this review, we discuss the pathogenetic causes of mitochondrial metabolic disorders and the recent MS-based metabolomic advances on their metabolomic remodeling. We conclude by exploring the MS-based metabolomic functional insights into their biosignatures to improve diagnostic platforms, stratify patients, and design novel targeted therapeutic strategies.