Untargeted metabolomics reveal dysregulations in sugar, methionine, and tyrosine pathways in the prodromal state of AD

Whole-body metabolic modelling reveals microbiome and genomic interactions on reduced urine formate levels in Alzheimer's disease

In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilised whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalised whole-body metabolic models. Notably, AD individuals displayed diminished formate microbial secretion in these models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.

Therapeutic potential to target sialylation and SIGLECs in neurodegenerative and psychiatric diseases

Sialic acids, commonly found as the terminal carbohydrate on the glycocalyx of mammalian cells, are pivotal checkpoint inhibitors of the innate immune system, particularly within the central nervous system (CNS). Sialic acid-binding immunoglobulin-like lectins (SIGLECs) expressed on microglia are key players in maintaining microglial homeostasis by recognizing intact sialylation. The finely balanced sialic acid-SIGLEC system ensures the prevention of excessive and detrimental immune responses in the CNS. However, loss of sialylation and SIGLEC receptor dysfunctions contribute to several chronic CNS diseases. Genetic variants of SIGLEC3/CD33, SIGLEC11, and SIGLEC14 have been associated with neurodegenerative diseases such as Alzheimer's disease, while sialyltransferase ST8SIA2 and SIGLEC4/MAG have been linked to psychiatric diseases such as schizophrenia, bipolar disorders, and autism spectrum disorders. Consequently, immune-modulatory functions of polysialic acids and SIGLEC binding antibodies have been exploited experimentally in animal models of Alzheimer's disease and inflammation-induced CNS tissue damage, including retinal damage. While the potential of these therapeutic approaches is evident, only a few therapies to target either sialylation or SIGLEC receptors have been tested in patient clinical trials. Here, we provide an overview of the critical role played by the sialic acid-SIGLEC axis in shaping microglial activation and function within the context of neurodegeneration and synaptopathies and discuss the current landscape of therapies that target sialylation or SIGLECs.

Integrative brain omics approach reveals key role for sn-1 lysophosphatidylethanolamine in Alzheimer's dementia

The biology of individual lipid species and their relevance in Alzheimer's disease (AD) remains incompletely understood. We utilized non-targeted mass spectrometry to examine brain lipids variations across 316 post-mortem brains from participants in the Religious Orders Study (ROS) or Rush Memory and Aging Project (MAP) cohorts classified as either control, asymptomatic AD (AAD), or symptomatic AD (SAD) and integrated the lipidomics data with untargeted proteomic characterization on the same individuals. Lipid enrichment analysis and analysis of variance identified significantly lower abundance of lysophosphatidylethanolamine (LPE) and lysophosphatidylcholine (LPC) species in SAD than controls or AAD. Lipid-protein co-expression network analyses revealed that lipid modules consisting of LPE and LPC exhibited a significant association to protein modules associated with MAPK/metabolism, post-synaptic density, and Cell-ECM interaction pathways and were associated with better antemortem cognition and with neuropathological changes seen in AD. Particularly, LPE 22:6 [sn-1] levels are significantly decreased across AD cases (SAD) and show the most influence on protein changes compared to other lysophospholipid species. LPE 22:6 may be a lipid signature for AD and could be leveraged as potential therapeutic or dietary targets for AD.

Identifying Hair Biomarker Candidates for Alzheimer's Disease Using Three High Resolution Mass Spectrometry-Based Untargeted Metabolomics Strategies

High-resolution mass spectrometry (HRMS)-based untargeted metabolomics strategies have emerged as an effective tool for discovering biomarkers of Alzheimer's disease (AD). There are various HRMS-based untargeted metabolomics strategies for biomarker discovery, including the data-dependent acquisition (DDA) method, the combination of full scan and target MS/MS, and the all ion fragmentation (AIF) method. Hair has emerged as a potential biospecimen for biomarker discovery in clinical research since it might reflect the circulating metabolic profiles over several months, while the analytical performances of the different data acquisition methods for hair biomarker discovery have been rarely investigated. Here, the analytical performances of three data acquisition methods in HRMS-based untargeted metabolomics for hair biomarker discovery were evaluated. The human hair samples from AD patients (N = 23) and cognitively normal individuals (N = 23) were used as an example. The most significant number of discriminatory features was acquired using the full scan (407), which is approximately 10-fold higher than that using the DDA strategy (41) and 11% higher than that using the AIF strategy (366). Only 66% of discriminatory chemicals discovered in the DDA strategy were discriminatory features in the full scan dataset. Moreover, compared to the deconvoluted MS/MS spectra with coeluted and background ions from the AIF method, the MS/MS spectrum obtained from the targeted MS/MS approach is cleaner and purer. Therefore, an untargeted metabolomics strategy combining the full scan with the targeted MS/MS method could obtain most discriminatory features along with a high quality MS/MS spectrum for discovering the AD biomarkers.

Increased α-2,6 sialic acid on microglia in amyloid pathology is resistant to oseltamivir

Terminal sialic acid residues are present on most glycoproteins and glycolipids, but levels of sialylation are known to change in the brain throughout the lifespan as well as during disease. Sialic acids are important for numerous cellular processes including cell adhesion, neurodevelopment, and immune regulation as well as pathogen invasion into host cells. Neuraminidase enzymes, also known as sialidases, are responsible for removal of terminal sialic acids in a process known as desialylation. Neuraminidase 1 (Neu1) cleaves the α-2,6 bond of terminal sialic acids. Aging individuals with dementia are often treated with the antiviral medication oseltamivir, which is associated with induction of adverse neuropsychiatric side effects; this drug inhibits both viral and mammalian Neu1. The present study tested whether a clinically relevant antiviral dosing regimen of oseltamivir would disrupt behavior in the 5XFAD mouse model of Alzheimer's disease amyloid pathology or wild-type littermates. While oseltamivir treatment did not impact mouse behavior or modify amyloid plaque size or morphology, a novel spatial distribution of α-2,6 sialic acid residues was discovered in 5XFAD mice that was not present in wild-type littermates. Further analyses revealed that α-2,6 sialic acid residues were not localized the amyloid plaques but instead localized to plaque-associated microglia. Notably, treatment with oseltamivir did not alter α-2,6 sialic acid distribution on plaque-associated microglia in 5XFAD mice which may be due to downregulation of Neu1 transcript levels in 5XFAD mice. Overall, this study suggests that plaque-associated microglia are highly sialylated and are resistant to change with oseltamivir, thus interfering with microglia immune recognition of and response to amyloid pathology.

Identification of region-specific amino acid signatures for doxorubicin-induced chemo brain

Doxorubicin (DOX) is a cornerstone of chemotherapy for solid tumors and leukemias. DOX-induced cognitive impairment, termed chemo brain, has been reported in cancer survivors, whereas its mechanism remains poorly understood. Here we initially evaluated the cognitive impairments of mice treated with clinically relevant, long-term, low-dosage of DOX. Using HILIC-MS/MS-based targeted metabolomics, we presented the changes of 21 amino acids across six anatomical brain regions of mice with DOX-induced chemo brain. By mapping the altered amino acids to the human metabolic network, we constructed an amino acid-based network module for each brain region. We identified phenylalanine, tyrosine, methionine, and γ-aminobutyric acid as putative signatures of three regions (hippocampus, prefrontal cortex, and neocortex) highly associated with cognition. Relying on the reported mouse brain metabolome atlas, we found that DOX might perturb the amino acid homeostasis in multiple brain regions, similar to the changes in the aging brain. Correlation analysis suggested the possible indirect neurotoxicity of DOX that altered the brain levels of phenylalanine, tyrosine, and methionine by causing metabolic disorders in the liver and kidney. In summary, we revealed the region-specific amino acid signatures as actionable targets for DOX-induced chemo brain, which might provide safer treatment and improve the quality of life among cancer survivors.

Is There a Connection between the Metabolism of Copper, Sulfur, and Molybdenum in Alzheimer’s Disease? New Insights on Disease Etiology

Alzheimer’s disease (AD) and other forms of dementia was ranked 3rd in both the Americas and Europe in 2019 in a World Health Organization (WHO) publication listing the leading causes of death and disability worldwide. Copper (Cu) imbalance has been reported in AD and increasing evidence suggests metal imbalance, including molybdenum (Mo), as a potential link with AD occurrence.We conducted an extensive literature review of the last 60 years of research on AD and its relationship with Cu, sulfur (S), and Mo at out of range levels.Weanalyzed the interactions among metallic elements’ metabolisms;Cu and Mo are biological antagonists, Mo is a sulfite oxidase and xanthine oxidase co-factor, and their low activities impair S metabolism and reduce uric acid, respectively. We found significant evidence in the literature of a new potential mechanism linking Cu imbalance to Mo and S abnormalities in AD etiology: under certain circumstances, the accumulation of Cu not bound to ceruloplasmin might affect the transport of Mo outside the blood vessels, causing a mild Mo deficiency that might lowerthe activity of Mo and S enzymes essential for neuronal activity. The current review provides an updated discussion of the plausible mechanisms combining Cu, S, and Mo alterations in AD.

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.

Multiomics Analysis of Structural Magnetic Resonance Imaging of the Brain and Cerebrospinal Fluid Metabolomics in Cognitively Normal and Impaired Adults

INTRODUCTION

Integrating brain imaging with large scale omics data may identify novel mechanisms of mild cognitive impairment (MCI) and early Alzheimer's disease (AD). We integrated and analyzed brain magnetic resonance imaging (MRI) with cerebrospinal fluid (CSF) metabolomics to elucidate metabolic mechanisms and create a "metabolic map" of the brain in prodromal AD.

METHODS

In 145 subjects (85 cognitively normal controls and 60 with MCI), we derived voxel-wise gray matter volume via whole-brain structural MRI and conducted high-resolution untargeted metabolomics on CSF. Using a data-driven approach consisting of partial least squares discriminant analysis, a multiomics network clustering algorithm, and metabolic pathway analysis, we described dysregulated metabolic pathways in CSF mapped to brain regions associated with MCI in our cohort.

RESULTS

The multiomics network algorithm clustered metabolites with contiguous imaging voxels into seven distinct communities corresponding to the following brain regions: hippocampus/parahippocampal gyrus (three distinct clusters), thalamus, posterior thalamus, parietal cortex, and occipital lobe. Metabolic pathway analysis indicated dysregulated metabolic activity in the urea cycle, and many amino acids (arginine, histidine, lysine, glycine, tryptophan, methionine, valine, glutamate, beta-alanine, and purine) was significantly associated with those regions (P < 0.05).

CONCLUSION

By integrating CSF metabolomics data with structural MRI data, we linked specific AD-susceptible brain regions to disrupted metabolic pathways involving nitrogen excretion and amino acid metabolism critical for cognitive function. Our findings and analytical approach may extend drug and biomarker research toward more multiomics approaches.

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.

Sialometabolism in Brain Health and Alzheimer's Disease

Sialic acids refer to a unique family of acidic sugars with a 9-carbon backbone that are mostly found as terminal residues in glycan structures of glycoconjugates including both glycoproteins and glycolipids. The highest levels of sialic acids are expressed in the brain where they regulate neuronal sprouting and plasticity, axon myelination and myelin stability, as well as remodeling of mature neuronal connections. Moreover, sialic acids are the sole ligands for microglial Siglecs (sialic acid-binding immunoglobulin-type lectins), and sialic acid-Siglec interactions have been indicated to play a critical role in the regulation of microglial homeostasis in a healthy brain. The recent discovery of CD33, a microglial Siglec, as a novel genetic risk factor for late-onset Alzheimer's disease (AD), highlights the potential role of sialic acids in the development of microglial dysfunction and neuroinflammation in AD. Apart from microglia, sialic acids have been found to be involved in several other major changes associated with AD. Elevated levels of serum sialic acids have been reported in AD patients. Alterations in ganglioside (major sialic acid carrier) metabolism have been demonstrated as an aggravating factor in the formation of amyloid pathology in AD. Polysialic acids are linear homopolymers of sialic acids and have been implicated to be an important regulator of neurogenesis that contributes to neuronal repair and recovery from neurodegeneration such as in AD. In summary, this article reviews current understanding of neural functions of sialic acids and alterations of sialometabolism in aging and AD brains. Furthermore, we discuss the possibility of looking at sialic acids as a promising novel therapeutic target for AD intervention.

Sialylation acts as a checkpoint for innate immune responses in the central nervous system

Sialic acids are monosaccharides that normally terminate the glycan chains of cell surface glyco-proteins and -lipids in mammals, and are highly enriched in the central nervous tissue. Sialic acids are conjugated to proteins and lipids (termed "sialylation") by specific sialyltransferases, and are removed ("desialylation") by neuraminidases. Cell surface sialic acids are sensed by complement factor H (FH) to inhibit complement activation or by sialic acid-binding immunoglobulin-like lectin (SIGLEC) receptors to inhibit microglial activation, phagocytosis, and oxidative burst. In contrast, desialylation of cells enables binding of the opsonins C1, calreticulin, galectin-3, and collectins, stimulating phagocytosis of such cells. Hypersialylation is used by bacteria and cancers as camouflage to escape immune recognition, while polysialylation of neurons protects synapses and neurogenesis. Insufficient lysosomal cleavage of sialylated molecules can lead to lysosomal accumulation of lipids and aggregated proteins, which if excessive may be expelled into the extracellular space. On the other hand, desialylation of immune receptors can activate them or trigger removal of proteins. Loss of inhibitory SIGLECs or FH triggers reduced clearance of aggregates, oxidative brain damage and complement-mediated retinal damage. Thus, cell surface sialylation recognized by FH, SIGLEC, and other immune-related receptors acts as a major checkpoint inhibitor of innate immune responses in the central nervous system, while excessive cleavage of sialic acid residues and consequently removing this checkpoint inhibitor may trigger lipid accumulation, protein aggregation, inflammation, and neurodegeneration.