Metabolome in progression to Alzheimer's disease

Imaging 6-Phosphogluconolactonase Activity in Brain Tumors In Vivo Using Hyperpolarized δ-[1-13C]gluconolactone

INTRODUCTION

The pentose phosphate pathway (PPP) is essential for NADPH generation and redox homeostasis in cancer, including glioblastomas. However, the precise contribution to redox and tumor proliferation of the second PPP enzyme 6-phosphogluconolactonase (PGLS), which converts 6-phospho-δ-gluconolactone to 6-phosphogluconate (6PG), remains unclear. Furthermore, non-invasive methods of assessing PGLS activity are lacking. The goal of this study was to examine the role of PGLS in glioblastomas and assess the utility of probing PGLS activity using hyperpolarized δ-[1-13C]gluconolactone for non-invasive imaging.

METHODS

To interrogate the function of PGLS in redox, PGLS expression was silenced in U87, U251 and GS2 glioblastoma cells by RNA interference and levels of NADPH and reduced glutathione (GSH) measured. Clonogenicity assays were used to assess the effect of PGLS silencing on glioblastoma proliferation. Hyperpolarized δ-[1-13C]gluconolactone metabolism to 6PG was assessed in live cells treated with the chemotherapeutic agent temozolomide (TMZ) or with vehicle control. 13C 2D echo-planar spectroscopic imaging (EPSI) studies of hyperpolarized δ-[1-13C]gluconolactone metabolism were performed on rats bearing orthotopic glioblastoma tumors or tumor-free controls on a 3T spectrometer. Longitudinal 2D EPSI studies of hyperpolarized δ-[1-13C]gluconolactone metabolism and T2-weighted magnetic resonance imaging (MRI) were performed in rats bearing orthotopic U251 tumors following treatment with TMZ to examine the ability of hyperpolarized δ-[1-13C]gluconolactone to report on treatment response.

RESULTS

PGLS knockdown downregulated NADPH and GSH, elevated oxidative stress and inhibited clonogenicity in all models. Conversely, PGLS expression and activity and steady-state NADPH and GSH were higher in tumor tissues from rats bearing orthotopic glioblastoma xenografts relative to contralateral brain and tumor-free brain. Importantly, [1-13C]6PG production from hyperpolarized δ-[1-13C]gluconolactone was observed in live glioblastoma cells and was significantly reduced by treatment with TMZ. Furthermore, hyperpolarized δ-[1-13C]gluconolactone metabolism to [1-13C]6PG could differentiate tumor from contralateral normal brain in vivo. Notably, TMZ significantly reduced 6PG production from hyperpolarized δ-[1-13C]gluconolactone at an early timepoint prior to volumetric alterations as assessed by anatomical imaging.

CONCLUSIONS

Collectively, we have, for the first time, identified a role for PGLS activity in glioblastoma proliferation and validated the utility of probing PGLS activity using hyperpolarized δ-[1-13C]gluconolactone for non-invasive in vivo imaging of glioblastomas and their response to therapy.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Mechanistic Insights into Alzheimer's Disease Unveiled through the Investigation of Disturbances in Central Metabolites and Metabolic Pathways

Hydrophilic metabolites are closely involved in multiple primary metabolic pathways and, consequently, play an essential role in the onset and progression of multifactorial human disorders, such as Alzheimer’s disease. This review article provides a comprehensive revision of the literature published on the use of mass spectrometry-based metabolomics platforms for approaching the central metabolome in Alzheimer’s disease research, including direct mass spectrometry, gas chromatography-mass spectrometry, hydrophilic interaction liquid chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Overall, mounting evidence points to profound disturbances that affect a multitude of central metabolic pathways, such as the energy-related metabolism, the urea cycle, the homeostasis of amino acids, fatty acids and nucleotides, neurotransmission, and others.

Huanglian Jiedu decoction remodels the periphery microenvironment to inhibit Alzheimer's disease progression based on the "brain-gut" axis through multiple integrated omics

BACKGROUND

In recent years, excellent results have suggested an association between the "brain-gut" axis and Alzheimer's disease (AD) progression, yet the role of the "brain-gut" axis in AD pathogenesis still remains obscure. Herein, we provided a potential link between the central and peripheral neuroinflammatory disorders in AD progression.

METHODS

The Morris water maze (MWM) test, immunohistochemistry, ELISA, ProcartaPlex Multiplex immunoassay, multiple LC-MS/MS methods, and the V3-V4 regions of 16S rRNA genes were applied to explore potential biomarkers.

RESULTS

In Tg-APP/PS1 mice, gut dysbiosis and lipid metabolism were highly associated with AD-like neuroinflammation. The combination of inflammatory factors (IL-6 and INF-γ), phosphatidylcholines (PCs) and SCFA-producing bacteria were expected to be early diagnostic biomarkers for AD. Huanglian Jiedu decoction (HLJDD) suppressed gut dysbiosis and the associated Aβ accumulation, harnessed neuroinflammation and reversed cognitive impairment.

CONCLUSION

Together, our findings highlighted the roles of neuroinflammation induced by gut dysbiosis and lipid metabolism disorder in AD progression. This integrated metabolomics approach showed its potential to understand the complex mechanisms of HLJDD in the treatment of AD.

Early signature in the blood lipidome associated with subsequent cognitive decline in the elderly: A case-control analysis nested within the Three-City cohort study

BACKGROUND

Brain lipid metabolism appears critical for cognitive aging, but whether alterations in the lipidome relate to cognitive decline remains unclear at the system level.

METHODS

We studied participants from the Three-City study, a multicentric cohort of older persons, free of dementia at time of blood sampling, and who provided repeated measures of cognition over 12 subsequent years. We measured 189 serum lipids from 13 lipid classes using shotgun lipidomics in a case-control sample on cognitive decline (matched on age, sex and level of education) nested within the Bordeaux study center (discovery, n = 418). Associations with cognitive decline were investigated using bootstrapped penalized regression, and tested for validation in the Dijon study center (validation, n = 314).

FINDINGS

Among 17 lipids identified in the discovery stage, lower levels of the triglyceride TAG50:5, and of four membrane lipids (sphingomyelin SM40:2,2, phosphatidylethanolamine PE38:5(18:1/20:4), ether-phosphatidylethanolamine PEO34:3(16:1/18:2), and ether-phosphatidylcholine PCO34:1(16:1/18:0)), and higher levels of PCO32:0(16:0/16:0), were associated with greater odds of cognitive decline, and replicated in our validation sample.

INTERPRETATION

These findings indicate that in the blood lipidome of non-demented older persons, a specific profile of lipids involved in membrane fluidity, myelination, and lipid rafts, is associated with subsequent cognitive decline.

FUNDING

The complete list of funders is available at the end of the manuscript, in the Acknowledgement section.

Rhodiola crenulata protects against Alzheimer's disease in rats: A brain lipidomics study by Fourier-transform ion cyclotron resonance mass spectrometry coupled with high-performance reversed-phase liquid chromatography and hydrophilic interaction liquid chromatography

RATIONALE

Alzheimer's disease (AD) is a chronic, severe, progressive neurodegenerative disorder associated with cognitive and memory impairment that ultimately causes death. Most approved drugs can only alleviate some of the symptoms of AD, but no interventions have been found that reverse the underlying disease mechanisms. Rhodiola crenulata extract (RCE) has been reported to alleviate AD symptoms in rats. However, its underlying mechanism of action is still unclear.

METHODS

A brain lipidomics study was conducted to investigate the protective effects of RCE against AD in rats to identify potential biomarkers of AD using Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) coupled with high-performance reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC). Differences in lipid metabolism profiles were evaluated using multivariate statistical analysis. Finally, the possible mechanism of action of RCE on AD was investigated by analysing metabolic pathways.

RESULTS

The RPLCHILIC/FT-ICR MS results showed 20 lipid components with significant differences between the control and model groups. After administration of RCE, the levels of 10 lipids in AD rats tended to shift toward reference levels. The pathway analysis revealed that the protective effect of RCE against AD might be related to regulation of glycerophospholipid metabolism.

CONCLUSIONS

This study provides a novel perspective on the potential intervention mechanism of RCE in the treatment of AD.

The Evolving Landscape of Exosomes in Neurodegenerative Diseases: Exosomes Characteristics and a Promising Role in Early Diagnosis

Neurodegenerative diseases (ND) remains to be one of the biggest burdens on healthcare systems and serves as a leading cause of disability and death. Alzheimer's disease (AD) is among the most common of such disorders, followed by Parkinson's disease (PD). The basic molecular details of disease initiation and pathology are still under research. Only recently, the role of exosomes has been linked to the initiation and progression of these neurodegenerative diseases. Exosomes are small bilipid layer enclosed extracellular vesicles, which were once considered as a cellular waste and functionless. These nano-vesicles of 30-150 nm in diameter carry specific proteins, lipids, functional mRNAs, and high amounts of non-coding RNAs (miRNAs, lncRNAs, and circRNAs). As the exosomes content is known to vary as per their originating and recipient cells, these vesicles can be utilized as a diagnostic biomarker for early disease detection. Here we review exosomes, their biogenesis, composition, and role in neurodegenerative diseases. We have also provided details for their characterization through an array of available techniques. Their updated role in neurodegenerative disease pathology is also discussed. Finally, we have shed light on a novel field of salivary exosomes as a potential candidate for early diagnosis in neurodegenerative diseases and compared the biomarkers of salivary exosomes with other blood/cerebrospinal fluid (CSF) based exosomes within these neurological ailments.

Plasma Sphingomyelins in Late-Onset Alzheimer's Disease

BACKGROUND

Altered plasma levels of sphingolipids, including sphingomyelins (SM), have been found in mouse models of Alzheimer's disease (AD) and in AD patient plasma samples.

OBJECTIVE

This study assesses fourteen plasma SM species in a late-onset AD (LOAD) patient cohort (n = 138).

METHODS

Specimens from control, preclinical, and symptomatic subjects were analyzed using targeted mass-spectrometry-based metabolomic methods.

RESULTS

Total plasma SM levels were not significantly affected by age or cognitive status. However, one metabolite that has been elevated in manifest AD in several recent studies, SM OHC14:1, was reduced significantly in pre-clinical AD and MCI relative to normal controls.

CONCLUSION

We recommend additional comprehensive plasma lipidomics in experimental and clinical biospecimens related to LOAD that might advance the utility of plasma sphingomyelin levels in molecular phenotyping and interpretations of pathobiological mechanisms.

CCL5 promotion of bioenergy metabolism is crucial for hippocampal synapse complex and memory formation

Glucoregulatory efficiency and ATP production are key regulators for neuronal plasticity and memory formation. Besides its chemotactic and neuroinflammatory functions, the CC chemokine--CCL5 displays neurotrophic activity. We found impaired learning-memory and cognition in CCL5-knockout mice at 4 months of age correlated with reduced hippocampal long-term potentiation and impaired synapse structure. Re-expressing CCL5 in knockout mouse hippocampus restored synaptic protein expression, neuronal connectivity and cognitive function. Using metabolomics coupled with FDG-PET imaging and seahorse analysis, we found that CCL5 participates in hippocampal fructose and mannose degradation, glycolysis, gluconeogenesis as well as glutamate and purine metabolism. CCL5 additionally supports mitochondrial structural integrity, purine synthesis, ATP generation, and subsequent aerobic glucose metabolism. Overexpressing CCL5 in WT mice also enhanced memory-cognition performance as well as hippocampal neuronal activity and connectivity through promotion of de novo purine and glutamate metabolism. Thus, CCL5 actions on glucose aerobic metabolism are critical for mitochondrial function which contribute to hippocampal spine and synapse formation, improving learning and memory.

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

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

Peripheral Glycolysis in Neurodegenerative Diseases

Neurodegenerative diseases are a group of nervous system conditions characterised pathologically by the abnormal deposition of protein throughout the brain and spinal cord. One common pathophysiological change seen in all neurodegenerative disease is a change to the metabolic function of nervous system and peripheral cells. Glycolysis is the conversion of glucose to pyruvate or lactate which results in the generation of ATP and has been shown to be abnormal in peripheral cells in Alzheimer's disease, Parkinson's disease, and Amyotrophic Lateral Sclerosis. Changes to the glycolytic pathway are seen early in neurodegenerative disease and highlight how in multiple neurodegenerative conditions pathology is not always confined to the nervous system. In this paper, we review the abnormalities described in glycolysis in the three most common neurodegenerative diseases. We show that in all three diseases glycolytic changes are seen in fibroblasts, and red blood cells, and that liver, kidney, muscle and white blood cells have abnormal glycolysis in certain diseases. We highlight there is potential for peripheral glycolysis to be developed into multiple types of disease biomarker, but large-scale bio sampling and deciphering how glycolysis is inherently altered in neurodegenerative disease in multiple patients' needs to be accomplished first to meet this aim.

Metabolic Dysregulation Contributes to the Progression of Alzheimer's Disease

Alzheimer's disease (AD) is an incurable neurodegenerative disease. Numerous studies have demonstrated a critical role for dysregulated glucose metabolism in its pathogenesis. In this review, we summarize metabolic alterations in aging brain and AD-related metabolic deficits associated with glucose metabolism dysregulation, glycolysis dysfunction, tricarboxylic acid (TCA) cycle, oxidative phosphorylation (OXPHOS) deficits, and pentose phosphate pathway impairment. Additionally, we discuss recent treatment strategies targeting metabolic defects in AD, including their limitations, in an effort to encourage the development of novel therapeutic strategies.

Metabolic Profiling of Cognitive Aging in Midlife

Alzheimer's dementia (AD) begins many years before its clinical symptoms. Metabolic dysfunction represents a core feature of AD and cognitive impairment, but few metabolomic studies have focused on cognitive aging in midlife. Using an untargeted metabolomics approach, we identified metabolic predictors of cognitive aging in midlife using fasting plasma sample from 30 middle-aged (mean age 57.2), male-male twin pairs enrolled in the Vietnam Era Twin Study of Aging (VETSA). For all twin pairs, one twin developed incident MCI, whereas his co-twin brother remained to be cognitively normal during an average 5.5-year follow-up. Linear mixed model was used to identify metabolites predictive of MCI conversion or cognitive change over time, adjusting for traditional risk factors. Results from twins were replicated in an independent cohort of middle-aged adults (mean age 59.1) in the Wisconsin Registry for Alzheimer's Prevention (WRAP). Results in twins showed that higher baseline levels of four plasma metabolites, including sphingomyelin (d18:1/20:1 and d18:2/20:0), sphingomyelin (d18:1/22:1, d18:2/22:0, and d16:1/24:1), DAG (18:2/20:4), and hydroxy-CMPF, were significantly associated with a slower decrease in one or more domains of cognitive function. The association of sphingomyelin (d18:1/20:1 and d18:2/20:0) was replicated in WRAP. Our results support that metabolic perturbation occurs many years before cognitive impairment and plasma metabolites may serve as early biomarkers for prediction or monitoring of cognitive aging and AD in midlife.

Contributions of Molecular and Optical Techniques to the Clinical Diagnosis of Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide. The distinctive neuropathological feature of AD is the intracerebral accumulation of two abnormally folded proteins: β-amyloid (Aβ) in the form of extracellular plaques, and tau in the form of intracellular neurofibrillary tangles. These proteins are considered disease-specific biomarkers, and the definite diagnosis of AD relies on their post-mortem identification in the brain. The clinical diagnosis of AD is challenging, especially in the early stages. The disease is highly heterogeneous in terms of clinical presentation and neuropathological features. This phenotypic variability seems to be partially due to the presence of distinct Aβ conformers, referred to as strains. With the development of an innovative technique named Real-Time Quaking-Induced Conversion (RT-QuIC), traces of Aβ strains were found in the cerebrospinal fluid of AD patients. Emerging evidence suggests that different conformers may transmit their strain signature to the RT-QuIC reaction products. In this review, we describe the current challenges for the clinical diagnosis of AD and describe how the RT-QuIC products could be analyzed by a surface-enhanced Raman spectroscopy (SERS)-based systems to reveal the presence of strain signatures, eventually leading to early diagnosis of AD with the recognition of individual disease phenotype.

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

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

Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software

Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful analytical tool for both nontargeted and targeted analyses. However, there is a need for more integrated workflows for processing and managing the resultant high-complexity datasets. End-to-end workflows for processing GC×GC data are challenging and often require multiple tools or software to process a single dataset. We describe a new approach, which uses an existing underutilized interface within commercial software to integrate free and open-source/external scripts and tools, tailoring the workflow to the needs of the individual researcher within a single software environment. To demonstrate the concept, the interface was successfully used to complete a first-pass alignment on a large-scale GC×GC metabolomics dataset. The analysis was performed by interfacing bespoke and published external algorithms within a commercial software environment to automatically correct the variation in retention times captured by a routine reference standard. Variation in ¹t_R and ²t_R was reduced on average from 8 and 16% CV prealignment to less than 1 and 2% post alignment, respectively. The interface enables automation and creation of new functions and increases the interconnectivity between chemometric tools, providing a window for integrating data-processing software with larger informatics-based data management platforms.

Integrated lipidomics and proteomics network analysis highlights lipid and immunity pathways associated with Alzheimer's disease

BACKGROUND

There is an urgent need to understand the pathways and processes underlying Alzheimer's disease (AD) for early diagnosis and development of effective treatments. This study was aimed to investigate Alzheimer's dementia using an unsupervised lipid, protein and gene multi-omics integrative approach.

METHODS

A lipidomics dataset comprising 185 AD patients, 40 mild cognitive impairment (MCI) individuals and 185 controls, and two proteomics datasets (295 AD, 159 MCI and 197 controls) were used for weighted gene co-expression network analyses (WGCNA). Correlations of modules created within each modality with clinical AD diagnosis, brain atrophy measures and disease progression, as well as their correlations with each other, were analyzed. Gene ontology enrichment analysis was employed to examine the biological processes and molecular and cellular functions of protein modules associated with AD phenotypes. Lipid species were annotated in the lipid modules associated with AD phenotypes. The associations between established AD risk loci and the lipid/protein modules that showed high correlation with AD phenotypes were also explored.

RESULTS

Five of the 20 identified lipid modules and five of the 17 identified protein modules were correlated with clinical AD diagnosis, brain atrophy measures and disease progression. The lipid modules comprising phospholipids, triglycerides, sphingolipids and cholesterol esters were correlated with AD risk loci involved in immune response and lipid metabolism. The five protein modules involved in positive regulation of cytokine production, neutrophil-mediated immunity, and humoral immune responses were correlated with AD risk loci involved in immune and complement systems and in lipid metabolism (the APOE ε4 genotype).

CONCLUSIONS

Modules of tightly regulated lipids and proteins, drivers in lipid homeostasis and innate immunity, are strongly associated with AD phenotypes.

Significance of Blood and Cerebrospinal Fluid Biomarkers for Alzheimer's Disease: Sensitivity, Specificity and Potential for Clinical Use

Alzheimer's disease (AD) is the most common type of dementia, affecting more than 5 million Americans, with steadily increasing mortality and incredible socio-economic burden. Not only have therapeutic efforts so far failed to reach significant efficacy, but the real pathogenesis of the disease is still obscure. The current theories are based on pathological findings of amyloid plaques and tau neurofibrillary tangles that accumulate in the brain parenchyma of affected patients. These findings have defined, together with the extensive neurodegeneration, the diagnostic criteria of the disease. The ability to detect changes in the levels of amyloid and tau in cerebrospinal fluid (CSF) first, and more recently in blood, has allowed us to use these biomarkers for the specific in-vivo diagnosis of AD in humans. Furthermore, other pathological elements of AD, such as the loss of neurons, inflammation and metabolic derangement, have translated to the definition of other CSF and blood biomarkers, which are not specific of the disease but, when combined with amyloid and tau, correlate with the progression from mild cognitive impairment to AD dementia, or identify patients who will develop AD pathology. In this review, we discuss the role of current and hypothetical biomarkers of Alzheimer's disease, their specificity, and the caveats of current high-sensitivity platforms for their peripheral detection.

Links between central CB1-receptor availability and peripheral endocannabinoids in patients with first episode psychosis

There is an established, link between psychosis and metabolic abnormalities, such as altered glucose metabolism and dyslipidemia, which often precede the initiation of antipsychotic treatment. It is known that obesity-associated metabolic disorders are promoted by activation of specific cannabinoid targets (endocannabinoid system (ECS)). Our recent data suggest that there is a change in the circulating lipidome at the onset of first episode psychosis (FEP). With the aim of characterizing the involvement of the central and peripheral ECSs, and their mutual associations; here, we performed a combined neuroimaging and metabolomic study in patients with FEP and healthy controls (HC). Regional brain cannabinoid receptor type 1 (CB1R) availability was quantified in two, independent samples of patients with FEP (n = 20 and n = 8) and HC (n = 20 and n = 10), by applying three-dimensional positron emission tomography, using two radiotracers, [¹¹C]MePPEP and [¹⁸F]FMPEP-d2. Ten endogenous cannabinoids or related metabolites were quantified in serum, drawn from these individuals during the same imaging session. Circulating levels of arachidonic acid and oleoylethanolamide (OEA) were reduced in FEP individuals, but not in those who were predominantly medication free. In HC, there was an inverse association between levels of circulating arachidonoyl glycerol, anandamide, OEA, and palmitoyl ethanolamide, and CB1R availability in the posterior cingulate cortex. This phenomenon was, however, not observed in FEP patients. Our data thus provide evidence of cross talk, and dysregulation between peripheral endocannabinoids and central CB1R availability in FEP.

Peripheral serum metabolomic profiles inform central cognitive impairment

The incidence of Alzheimer's disease (AD) increases with age and is becoming a significant cause of worldwide morbidity and mortality. However, the metabolic perturbation behind the onset of AD remains unclear. In this study, we performed metabolite profiling in both brain (n = 109) and matching serum samples (n = 566) to identify differentially expressed metabolites and metabolic pathways associated with neuropathology and cognitive performance and to identify individuals at high risk of developing cognitive impairment. The abundances of 6 metabolites, glycolithocholate (GLCA), petroselinic acid, linoleic acid, myristic acid, palmitic acid, palmitoleic acid and the deoxycholate/cholate (DCA/CA) ratio, along with the dysregulation scores of 3 metabolic pathways, primary bile acid biosynthesis, fatty acid biosynthesis, and biosynthesis of unsaturated fatty acids showed significant differences across both brain and serum diagnostic groups (P-value < 0.05). Significant associations were observed between the levels of differential metabolites/pathways and cognitive performance, neurofibrillary tangles, and neuritic plaque burden. Metabolites abundances and personalized metabolic pathways scores were used to derive machine learning models, respectively, that could be used to differentiate cognitively impaired persons from those without cognitive impairment (median area under the receiver operating characteristic curve (AUC) = 0.772 for the metabolite level model; median AUC = 0.731 for the pathway level model). Utilizing these two models on the entire baseline control group, we identified those who experienced cognitive decline in the later years (AUC = 0.804, sensitivity = 0.722, specificity = 0.749 for the metabolite level model; AUC = 0.778, sensitivity = 0.633, specificity = 0.825 for the pathway level model) and demonstrated their pre-AD onset prediction potentials. Our study provides a proof-of-concept that it is possible to discriminate antecedent cognitive impairment in older adults before the onset of overt clinical symptoms using metabolomics. Our findings, if validated in future studies, could enable the earlier detection and intervention of cognitive impairment that may halt its progression.

Accelerated loss of hypoxia response in zebrafish with familial Alzheimer's disease-like mutation of presenilin 1

Ageing is the major risk factor for Alzheimer's disease (AD), a condition involving brain hypoxia. The majority of early-onset familial AD (EOfAD) cases involve dominant mutations in the gene PSEN1. PSEN1 null mutations do not cause EOfAD. We exploited putative hypomorphic and EOfAD-like mutations in the zebrafish psen1 gene to explore the effects of age and genotype on brain responses to acute hypoxia. Both mutations accelerate age-dependent changes in hypoxia-sensitive gene expression supporting that ageing is necessary, but insufficient, for AD occurrence. Curiously, the responses to acute hypoxia become inverted in extremely aged fish. This is associated with an apparent inability to upregulate glycolysis. Wild-type PSEN1 allele expression is reduced in post-mortem brains of human EOfAD mutation carriers (and extremely aged fish), possibly contributing to EOfAD pathogenesis. We also observed that age-dependent loss of HIF1 stabilization under hypoxia is a phenomenon conserved across vertebrate classes.

APOE and metabolic dysfunction in Alzheimer's disease

The strongest genetic risk factor for sporadic Alzheimer's disease (AD) is carriage of the E4 allele of APOE. Metabolic dysfunction also increases risk of dementia and AD. Facing a need for effective therapies and an aging global population, studies aimed at uncovering new therapeutic targets for AD have become critical. Insight into the biology underlying the effects of E4 and metabolic impairment on the brain may lead to novel therapies to reduce AD risk. An understudied hallmark of both AD patients and E4 individuals is a common metabolic impairment-cerebral glucose hypometabolism. This is a robust and replicated finding in humans, and begins decades prior to cognitive decline. Possession of E4 also appears to alter several other aspects of cerebral glucose metabolism, fatty acid metabolism, and management of oxidative stress through the pentose phosphate pathway. A critical knowledge gap in AD is the mechanism by which APOE alters cerebral metabolism and clarification as to its relevance to AD risk. Facing a need for effective therapies, studies aimed at uncovering new therapeutic targets have become critical. One such approach is to gain a better understanding of the metabolic mechanisms that may underlie E4-associated cognitive dysfunction and AD risk.

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

INTRODUCTION

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

AREAS COVERED

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

EXPERT OPINION

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

Impaired perfusion and capillary dysfunction in prodromal Alzheimer's disease

INTRODUCTION

Cardiovascular disease increases the risk of developing Alzheimer's disease (AD), and growing evidence suggests an involvement of cerebrovascular pathology in AD. Capillary dysfunction, a condition in which capillary flow disturbances rather than arterial blood supply limit brain oxygen extraction, could represent an overlooked vascular contributor to neurodegeneration. We examined whether cortical capillary transit-time heterogeneity (CTH), an index of capillary dysfunction, is elevated in amyloid-positive patients with mild cognitive impairment (prodromal AD [pAD]).

METHODS

We performed structural and perfusion weighted MRI in 22 pAD patients and 21 healthy controls.

RESULTS

We found hypoperfusion, reduced blood volume, and elevated CTH in the parietal and frontal cortices of pAD-patients compared to controls, while only the precuneus showed focal cortical atrophy.

DISCUSSION

We propose that microvascular flow disturbances antedate cortical atrophy and may limit local tissue oxygenation in pAD. We speculate that capillary dysfunction contributes to the development of neurodegeneration in AD.

An update on blood-based biomarkers for non-Alzheimer neurodegenerative disorders

Cerebrospinal fluid analyses and neuroimaging can identify the underlying pathophysiology at the earliest stage of some neurodegenerative disorders, but do not have the scalability needed for population screening. Therefore, a blood-based marker for such pathophysiology would have greater utility in a primary care setting and in eligibility screening for clinical trials. Rapid advances in ultra-sensitive assays have enabled the levels of pathological proteins to be measured in blood samples, but research has been predominantly focused on Alzheimer disease (AD). Nonetheless, proteins that were identified as potential blood-based biomarkers for AD, for example, amyloid-β, tau, phosphorylated tau and neurofilament light chain, are likely to be relevant to other neurodegenerative disorders that involve similar pathological processes and could also be useful for the differential diagnosis of clinical symptoms. This Review outlines the neuropathological, clinical, molecular imaging and cerebrospinal fluid features of the most common neurodegenerative disorders outside the AD continuum and gives an overview of the current status of blood-based biomarkers for these disorders.

Metabolomics and incident dementia in older Chinese adults: The Shanghai Aging Study

INTRODUCTION

Metabolomics provide a promising tool to understand the pathogenesis and to identify novel biomarkers of dementia. This study aimed to determine circulating metabolites associated with incident dementia in a Chinese cohort, and whether a selected metabolite panel could predict dementia.

METHODS

Thirty-eight metabolites in baseline serum were profiled by nuclear magnetic resonance in 1440 dementia-free participants followed 5 years in the Shanghai Aging Study.

RESULTS

Higher serum levels of glutamine and O-acetyl-glycoproteins were associated with increased risk of dementia, whereas glutamate, tyrosine, acetate, glycine, and phenylalanine were negatively related to incident dementia. A panel of five metabolites selected by least absolute shrinkage and selection operator within cross-validation regression analysis could predict incident dementia with an area under the receiver-operating characteristic curve of 0.72.

DISCUSSION

We identified seven candidate serum metabolic biomarkers for dementia. These findings and the underlying biological mechanisms need to be further replicated and elucidated in future studies.

Sex and APOE ε4 genotype modify the Alzheimer's disease serum metabolome

Late-onset Alzheimer’s disease (AD) can, in part, be considered a metabolic disease. Besides age, female sex and APOE ε4 genotype represent strong risk factors for AD that also give rise to large metabolic differences. We systematically investigated group-specific metabolic alterations by conducting stratified association analyses of 139 serum metabolites in 1,517 individuals from the AD Neuroimaging Initiative with AD biomarkers. We observed substantial sex differences in effects of 15 metabolites with partially overlapping differences for APOE ε4 status groups. Several group-specific metabolic alterations were not observed in unstratified analyses using sex and APOE ε4 as covariates. Combined stratification revealed further subgroup-specific metabolic effects limited to APOE ε4+ females. The observed metabolic alterations suggest that females experience greater impairment of mitochondrial energy production than males. Dissecting metabolic heterogeneity in AD pathogenesis can therefore enable grading the biomedical relevance for specific pathways within specific subgroups, guiding the way to personalized medicine.

Sex and the APOE ε4 genotype are important risk factors for late-onset Alzheimer’s disease. In the current study, the authors investigate how sex and APOE ε4 genotype modify the association between Alzheimer’s disease biomarkers and metabolites in serum.

Lipids and Alzheimer's Disease

Lipids, as the basic component of cell membranes, play an important role in human health as well as brain function. The brain is highly enriched in lipids, and disruption of lipid homeostasis is related to neurologic disorders as well as neurodegenerative diseases such as Alzheimer’s disease (AD). Aging is associated with changes in lipid composition. Alterations of fatty acids at the level of lipid rafts and cerebral lipid peroxidation were found in the early stage of AD. Genetic and environmental factors such as apolipoprotein and lipid transporter carrying status and dietary lipid content are associated with AD. Insight into the connection between lipids and AD is crucial to unraveling the metabolic aspects of this puzzling disease. Recent advances in lipid analytical methodology have led us to gain an in-depth understanding on lipids. As a result, lipidomics have becoming a hot topic of investigation in AD, in order to find biomarkers for disease prediction, diagnosis, and prevention, with the ultimate goal of discovering novel therapeutics.

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.

Brain and blood metabolome for Alzheimer's dementia: findings from a targeted metabolomics analysis

The development of Alzheimer's dementia (AD) accompanies both central and peripheral metabolic disturbance, but the metabolic basis underlying AD and metabolic markers predictive of AD risk remain to be determined. It is also unclear whether the metabolic changes in the peripheral blood and brain are overlapping in relation to AD. The present study addresses these questions by targeted metabolomics in both antemortem blood and postmortem brain samples in 2 community-based longitudinal cohorts of aging and dementia. We found that higher serum levels of 3 acylcarnitines, including decanoylcarnitine (C10), pimelylcarnitine (C7-DC), and tetradecadienylcarnitine (C14:2), significantly predict a lower risk of incident AD (composite hazard ratio = 0.368, 95% CI [0.207, 0.653]) after an average of 4.5-year follow-up, independent of age, sex, and education. In addition, baseline serum levels of ten glycerophospholipids, one amino acid, and 5 acylcarnitines predict the longitudinal change in cognitive functions. Moreover, 28 brain metabolites were associated with AD phenotypes. Of the putative metabolites identified in the serum and brain, 4 metabolites (3 glycerophospholipids [PC aa C30:0, PC ae C34:0, PC ae C36:1] and 1 acylcarnitine [C14:2]) were present in both the postmortem brain and antemortem blood, but only one metabolite (C14:2) was associated with AD in the same direction (i.e., protective). Partial correlation and network analyses suggest a potential tissue-specific regulation of metabolism, although other alternatives exist. Together, we identified significant associations of both central and peripheral metabolites with AD phenotypes, but there seems to be little overlap between the 2 tissues.

Accelerated brain aging towards transcriptional inversion in a zebrafish model of the K115fs mutation of human PSEN2

Background

The molecular changes involved in Alzheimer’s disease (AD) progression remain unclear since we cannot easily access antemortem human brains. Some non-mammalian vertebrates such as the zebrafish preserve AD-relevant transcript isoforms of the PRESENILIN genes lost from mice and rats. One example is PS2V, the alternative transcript isoform of the PSEN2 gene. PS2V is induced by hypoxia/oxidative stress and shows increased expression in late onset, sporadic AD brains. A unique, early onset familial AD mutation of PSEN2, K115fs, mimics the PS2V coding sequence suggesting that forced, early expression of PS2V-like isoforms may contribute to AD pathogenesis. Here we use zebrafish to model the K115fs mutation to investigate the effects of forced PS2V-like expression on the transcriptomes of young adult and aged adult brains.

Methods

We edited the zebrafish genome to model the K115fs mutation. To explore its effects at the molecular level, we analysed the brain transcriptome and proteome of young (6-month-old) and aged (24-month-old) wild type and heterozygous mutant female sibling zebrafish. Finally, we used gene co-expression network analysis (WGCNA) to compare molecular changes in the brains of these fish to human AD.

Results

Young heterozygous mutant fish show transcriptional changes suggesting accelerated brain aging and increased glucocorticoid signalling. These early changes precede a transcriptional ‘inversion’ that leads to glucocorticoid resistance and other likely pathological changes in aged heterozygous mutant fish. Notably, microglia-associated immune responses regulated by the ETS transcription factor family are altered in both our zebrafish mutant model and in human AD. The molecular changes we observe in aged heterozygous mutant fish occur without obvious histopathology and possibly in the absence of Aβ.

Conclusions

Our results suggest that forced expression of a PS2V-like isoform contributes to immune and stress responses favouring AD pathogenesis. This highlights the value of our zebrafish genetic model for exploring molecular mechanisms involved in AD pathogenesis.

APOE alters glucose flux through central carbon pathways in astrocytes

The Apolipoprotein E (APOE) gene is a major genetic risk factor associated with Alzheimer's disease (AD). APOE encodes for three main isoforms in humans (E2, E3, and E4). Homozygous E4 individuals have more than a 10-fold higher risk for developing late-onset AD, while E2 carriers are protected. A hallmark of AD is a reduction in cerebral glucose metabolism, alluding to a strong metabolic component in disease onset and progression. Interestingly, E4 individuals display a similar regional pattern of cerebral glucose hypometabolism decades prior to disease onset. Mapping this metabolic landscape may help elucidate the underlying biological mechanism of APOE-associated risk for AD. Efficient metabolic coupling of neurons and glia is necessary for proper neuronal function, and disruption in glial energy distribution has been proposed to contribute to neuronal cell death and AD pathology. One important function of astrocytes - canonically the primary source of apolipoprotein E in the brain - is to provide metabolic substrates (lactate, lipids, amino acids and neurotransmitters) to neurons. Here we investigate the effects of APOE on astrocyte glucose metabolism in vitro utilizing scintillation proximity assays, stable isotope tracer metabolomics, and gene expression analyses. Glucose uptake is impaired in E4 astrocytes relative to E2 or E3 with specific alterations in central carbon metabolism. Using stable isotope labeled glucose [U-¹³C] allowed analyses of astrocyte-specific deep metabolic networks affected by APOE, and provided insight to the effects downstream of glucose uptake. Enrichment of ¹³C in early steps of glycolysis was lowest in E4 astrocytes (highest in E2), while synthesis of lactate from glucose was highest in E4 astrocytes (lowest in E2). We observed an increase in glucose flux through the pentose phosphate pathway (PPP), with downstream increases in gluconeogenesis, lipid, and de novo nucleotide biosynthesis in E4 astrocytes. There was also a marked increase in ¹³C enrichment in the TCA cycle of E4 astrocytes - whose substrates were also incorporated into biosynthetic pathways at a higher rate. Pyruvate carboxylase (PC) and pyruvate dehydrogenase (PDH) are the two main enzymes controlling pyruvate entry to the TCA cycle. PC gene expression is increased in E4 astrocytes and the activity relative to PDH was also increased, compared to E2 or E3. Decreased enrichment in the TCA cycle of E2 and E3 astrocytes is suggestive of increased oxidation and non-glucose derived anaplerosis, which could be fueling mitochondrial ATP production. Conversely, E4 astrocytes appear to increase carbon flux into the TCA cycle to fuel cataplerosis. Together, these data demonstrate clear APOE isoform-specific effects on glucose utilization in astrocytes, including E4-associated increases in lactate synthesis, PPP flux, and de novo biosynthesis pathways.

Metabolomics study to identify plasma biomarkers in alzheimer disease: ApoE genotype effect

Alzheimer Disease (AD) is the main cause of dementia, and it has a great social and economic impact worldwide. It is a complex multifactorial disease, and we still do not know enough about its causes. For this reason, omics studies could be a useful tool for the search for new biomarkers and for enhancing the knowledge of different metabolic pathways that may be altered in the initial stages of the disease. Metabolomic analysis was carried out for plasma samples from early AD patients and healthy controls. Obtained data were normalized and analyzed by volcano plot and supervised orthogonal-least-squares-discriminant analysis. Fifteen variables were selected as the most important variables for the groups' discrimination, and the different levels of 6 identified metabolites could discriminate between patients with different ApoE4 genotypes (ε4-carriers and non ε4-carriers). In conclusion, ApoE4 genotype is associated with changes in lipid metabolomics profile in AD patients, and it could be relevant for the development of AD since early stages.

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

Background

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

Methods

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

Results

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

Conclusions

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

The Differences of Serum Metabolites Between Patients With Early-Stage Alzheimer's Disease and Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is regarded as a transition phase between normal aging and Alzheimer's disease (AD). Identification of novel and non-invasive biomarkers that can distinguish AD at an early stage from MCI is warranted for therapeutic and support planning. The goal of this study was to identify the differences of serum metabolomic profiles between MCI and early-stage AD, which could be potential non-invasive biomarkers for early diagnosis of AD.

Methods: The subjects enrolled in the study were classified into two diagnostic groups: MCI (n = 40) and early-stage AD (n = 40). Targeted metabolomics analysis of serum samples was performed using the Biocrates Absolute-IDQ P180 kit. Targeted metabolic data were analyzed by TargetLynx, and MetIDQ software was applied to integrate the metabolites by automated calculation of metabolite concentrations.

Results: The datasets of targeted metabolite analysis were analyzed by the orthogonal-projection-to-latent-structure–discriminant-analysis (OPLS-DA) model. The OPLS-DA score plots demonstrated considerable separation between the MCI and early-stage AD patients. The levels of pimelylcarnitine, putrescine, SM (OH) C24:1, and SM C24:0 were significantly lower, whereas the levels of acetylornithine, methionine sulfoxide, and PC ae C44:3 were significantly higher in early-stage AD patients as compared with MCI patients. Receiver operating characteristic curve analysis of a combination of three lipid metabolites [SM (OH) C24:1, SM C24:0, and PC ae C44:3] showed an acceptable discrimination between the early-stage AD and MCI patients (area under the curve = 0.788).

Conclusions: Our results characterized the differences of serum metabolic profiles between MCI and early-stage AD patients. The positive findings from this study indicate that the minimally invasive method of blood sampling may help to identify patients with AD at an early stage from those with MCI.

Multi-omics signature of brain amyloid deposition in asymptomatic individuals at-risk for Alzheimer's disease: The INSIGHT-preAD study

BACKGROUND

One of the biggest challenge in Alzheimer's disease (AD) is to identify pathways and markers of disease prediction easily accessible, for prevention and treatment. Here we analysed blood samples from the INveStIGation of AlzHeimer's predicTors (INSIGHT-preAD) cohort of elderly asymptomatic individuals with and without brain amyloid load.

METHODS

We performed blood RNAseq, and plasma metabolomics and lipidomics using liquid chromatography-mass spectrometry on 48 individuals amyloid positive and 48 amyloid negative (SUVr cut-off of 0·7918). The three data sets were analysed separately using differential gene expression based on negative binomial distribution, non-parametric (Wilcoxon) and parametric (correlation-adjusted Student't) tests. Data integration was conducted using sparse partial least squares-discriminant and principal component analyses. Bootstrap-selected top-ten features from the three data sets were tested for their discriminant power using Receiver Operating Characteristic curve. Longitudinal metabolomic analysis was carried out on a subset of 22 subjects.

FINDINGS

Univariate analyses identified three medium chain fatty acids, 4-nitrophenol and a set of 64 transcripts enriched for inflammation and fatty acid metabolism differentially quantified in amyloid positive and negative subjects. Importantly, the amounts of the three medium chain fatty acids were correlated over time in a subset of 22 subjects (p < 0·05). Multi-omics integrative analyses showed that metabolites efficiently discriminated between subjects according to their amyloid status while lipids did not and transcripts showed trends. Finally, the ten top metabolites and transcripts represented the most discriminant omics features with 99·4% chance prediction for amyloid positivity.

INTERPRETATION

This study suggests a potential blood omics signature for prediction of amyloid positivity in asymptomatic at-risk subjects, allowing for a less invasive, more accessible, and less expensive risk assessment of AD as compared to PET studies or lumbar puncture. FUND: Institut Hospitalo-Universitaire and Institut du Cerveau et de la Moelle Epiniere (IHU-A-ICM), French Ministry of Research, Fondation Alzheimer, Pfizer, and Avid.

Metabolomics reveals a link between homocysteine and lipid metabolism and leukocyte telomere length: the ENGAGE consortium

Telomere shortening has been associated with multiple age-related diseases such as cardiovascular disease, diabetes, and dementia. However, the biological mechanisms responsible for these associations remain largely unknown. In order to gain insight into the metabolic processes driving the association of leukocyte telomere length (LTL) with age-related diseases, we investigated the association between LTL and serum metabolite levels in 7,853 individuals from seven independent cohorts. LTL was determined by quantitative polymerase chain reaction and the levels of 131 serum metabolites were measured with mass spectrometry in biological samples from the same blood draw. With partial correlation analysis, we identified six metabolites that were significantly associated with LTL after adjustment for multiple testing: lysophosphatidylcholine acyl C17:0 (lysoPC a C17:0, p-value = 7.1 × 10⁻⁶), methionine (p-value = 9.2 × 10⁻⁵), tyrosine (p-value = 2.1 × 10⁻⁴), phosphatidylcholine diacyl C32:1 (PC aa C32:1, p-value = 2.4 × 10⁻⁴), hydroxypropionylcarnitine (C3-OH, p-value = 2.6 × 10⁻⁴), and phosphatidylcholine acyl-alkyl C38:4 (PC ae C38:4, p-value = 9.0 × 10⁻⁴). Pathway analysis showed that the three phosphatidylcholines and methionine are involved in homocysteine metabolism and we found supporting evidence for an association of lipid metabolism with LTL. In conclusion, we found longer LTL associated with higher levels of lysoPC a C17:0 and PC ae C38:4, and with lower levels of methionine, tyrosine, PC aa C32:1, and C3-OH. These metabolites have been implicated in inflammation, oxidative stress, homocysteine metabolism, and in cardiovascular disease and diabetes, two major drivers of morbidity and mortality.

Comparative evaluation of the extraction and analysis of urinary phospholipids and lysophospholipids using MALDI-TOF/MS

Lipids, particularly phospholipids (PLs) and lysophospholipids (LPLs), are attracting increasing scientific interest for their biological functions in cells and their potential as disease biomarkers for Alzheimer's disease and several types of cancer. Urinary PLs and LPLs could be ideal clinical biomarkers, because urine can be collected easily and noninvasively. However, due to their very low concentrations in urine compared with the relatively large quantity of contaminants in this matrix, efficient extraction and sensitive detection are required for analyzing urinary PLs and LPLs. In this study, various methods for analyzing PLs and LPLs in urine were compared and optimized from a clinical perspective. An optimized lipid extraction method and a matrix for matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS) were established using two external ionization standards and an internal standard mix containing 13 human urinary lipids. 9-Aminoacridine (9-AA) was a useful and effective matrix for the MALDI-TOF/MS analysis of all the internal standard lipids in both positive and negative ion modes. However, it was necessary to determine the proportional lipid concentrations from the balance between the extracted lipid and the matrix. The extraction efficiency and reproducibility of the acidified Bligh and Dyer method were excellent for both positively and negatively charged lipids. Analysis of small volumes of urine was the most efficient with the 9-AA MALDI matrix at concentrations of or below 5 mM. The combined analytical procedures allowed rapid and comprehensive screening of low concentrations of PLs and LPLs in clinical samples.

Serum Metabolite Markers of Dementia Through Quantitative NMR Analysis: The Importance of Threonine-Linked Metabolic Pathways

There is a great need for diagnostic biomarkers of impending dementia. Metabolite markers in blood have been investigated in several studies, but inconclusive findings encourage further investigation, particularly in the pre-diagnostic phase. In the present study, the serum metabolomes of 110 dementia or pre-diagnostic dementia individuals and 201 healthy individuals matched for age, gender, and education were analyzed by nuclear magnetic resonance spectroscopy in combination with multivariate data analysis. 58 metabolites were quantified in each of the 311 samples. Individuals with dementia were discriminated from controls using a panel of seven metabolites, while the pre-diagnostic dementia subjects were distinguished from controls using a separate set of seven metabolites, where threonine was a common significant metabolite in both panels. Metabolite and pathway alterations specific for dementia and pre-diagnostic dementia were identified, in particular a disturbed threonine catabolism at the pre-diagnostic stage that extends to several threonine-linked pathways at the dementia stage.

Primary fatty amides in plasma associated with brain amyloid burden, hippocampal volume, and memory in the European Medical Information Framework for Alzheimer's Disease biomarker discovery cohort

Introduction:

A critical and as-yet unmet need in Alzheimer’s disease (AD) is the discovery of peripheral small molecule biomarkers. Given that brain pathology precedes clinical symptom onset, we set out to test whether metabolites in blood associated with pathology as indexed by cerebrospinal fluid (CSF) AD biomarkers.

Methods:

This study analyzed 593 plasma samples selected from the European Medical Information Framework for Alzheimer’s Disease Multimodal Biomarker Discovery study, of individuals who were cognitively healthy (n = 242), had mild cognitive impairment (n = 236), or had AD-type dementia (n = 115). Logistic regressions were carried out between plasma metabolites (n = 883) and CSF markers, magnetic resonance imaging, cognition, and clinical diagnosis.

Results:

Eight metabolites were associated with amyloid b and one with t-tau in CSF, these were primary fatty acid amides (PFAMs), lipokines, and amino acids. From these, PFAMs, glutamate, and aspartate also associated with hippocampal volume and memory.

Discussion:

PFAMs have been found increased and associated with amyloid b burden in CSF and clinical measures.

Metabolomics in the Development and Progression of Dementia: A Systematic Review

Dementia has become a major global public health challenge with a heavy economic burden. It is urgently necessary to understand dementia pathogenesis and to identify biomarkers predicting risk of dementia in the preclinical stage for prevention, monitoring, and treatment. Metabolomics provides a novel approach for the identification of biomarkers of dementia. This systematic review aimed to examine and summarize recent retrospective cohort human studies assessing circulating metabolite markers, detected using high-throughput metabolomics, in the context of disease progression to dementia, including incident mild cognitive impairment, all-cause dementia, and cognitive decline. We systematically searched the PubMed, Embase, and Cochrane databases for retrospective cohort human studies assessing associations between blood (plasma or serum) metabolomics profile and cognitive decline and risk of dementia from inception through October 15, 2018. We identified 16 studies reporting circulating metabolites and risk of dementia, and six regarding cognitive performance change. Concentrations of several blood metabolites, including lipids (higher phosphatidylcholines, sphingomyelins, and lysophophatidylcholine, and lower docosahexaenoic acid and high-density lipoprotein subfractions), amino acids (lower branched-chain amino acids, creatinine, and taurine, and higher glutamate, glutamine, and anthranilic acid), and steroids were associated with cognitive decline and the incidence or progression of dementia. Circulating metabolites appear to be associated with the risk of dementia. Metabolomics could be a promising tool in dementia biomarker discovery. However, standardization and consensus guidelines for study design and analytical techniques require future development.

Blood-based molecular biomarkers for Alzheimer's disease

A major barrier to the effective conduct of clinical trials of new drug candidates against Alzheimer’s disease (AD) and to identifying patients for receiving future disease-modifying treatments is the limited capacity of the current health system to find and diagnose patients with early AD pathology. This may be related in part to the limited capacity of the current health systems to select those people likely to have AD pathology in order to confirm the diagnosis with available cerebrospinal fluid and imaging biomarkers at memory clinics. In the current narrative review, we summarize the literature on candidate blood tests for AD that could be implemented in primary care settings and used for the effective identification of individuals at increased risk of AD pathology, who could be referred for potential inclusion in clinical trials or future approved treatments following additional testing. We give an updated account of blood-based candidate biomarkers and biomarker panels for AD-related brain changes. Our analysis centres on biomarker candidates that have been replicated in more than one study and discusses the need of further studies to achieve the goal of a primary care-based screening algorithm for AD.

Plasma lipids metabolism in mild cognitive impairment and Alzheimer's disease

OBJECTIVES

Expression of phospholipids and related molecules could provide panels of multiple biomarkers searching for the signature of Alzheimer's disease (AD). The aim of the present study was to quantify ten phospholipids and simultaneously determine phospholipase A₂ (PLA₂) activity in blood of mild cognitive impairment (MCI) and AD patients.

METHODS

Thirty-four AD, 20 MCI and 25 controls were enrolled. The phospholipids where analysed using the AbsoluteIDQ^® p180 Kit. PLA₂ activities were accessed in platelets by a radio-enzymatic assay.

RESULTS

The study failed to fix the ten phospholipids as a panel to predict AD; the levels of PCaaC36:6, PCaaC40:6 and C16:1-OH were lower in MCI than in controls (P = 0.041, P = 0.012, P = 0.044 respectively). PCaaC40:2 levels were lower in MCI than in AD (P = 0.041). The converters MCI-AD showed at baseline lower levels of PCaaC40:2 (P = 0.050) and PCaaC40:6 (P = 0.037) than controls. iPLA₂ activity was reduced in AD and MCI than in controls (P < 0.001). We found positive correlation in the control group between PCaaC38:6 and tPLA₂ (r = 0.680; P = 0.001) and sPLA₂ (r = 0.601; P = 0.004); PCaaC40:1 and iPLA₂ (r = 0.503; P = 0.020); PCaaC40:6 and tPLA₂ (r = 0.532; P = 0.013) and sPLA₂ (r = 0.523; P = 0.015).

CONCLUSIONS

Lipids metabolites in plasma might indirectly indicate changes in neuronal membrane and this deregulation can outline the transition between healthy and diseased brains.

Mass spectrometry-based metabolomics: Targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders

Metabolomics seeks to take a "snapshot" in a time of the levels, activities, regulation and interactions of all small molecule metabolites in response to a biological system with genetic or environmental changes. The emerging development in mass spectrometry technologies has shown promise in the discovery and quantitation of neuroactive small molecule metabolites associated with gut microbiota and brain. Significant progress has been made recently in the characterization of intermediate role of small molecule metabolites linked to neural development and neurodegenerative disorder, showing its potential in understanding the crosstalk between gut microbiota and the host brain. More evidence reveals that small molecule metabolites may play a critical role in mediating microbial effects on neurotransmission and disease development. Mass spectrometry-based metabolomics is uniquely suitable for obtaining the metabolic signals in bidirectional communication between gut microbiota and brain. In this review, we summarized major mass spectrometry technologies including liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and imaging mass spectrometry for metabolomics studies of neurodegenerative disorders. We also reviewed the recent advances in the identification of new metabolites by mass spectrometry and metabolic pathways involved in the connection of intestinal microbiota and brain. These metabolic pathways allowed the microbiota to impact the regular function of the brain, which can in turn affect the composition of microbiota via the neurotransmitter substances. The dysfunctional interaction of this crosstalk connects neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease and Huntington's disease. The mass spectrometry-based metabolomics analysis provides information for targeting dysfunctional pathways of small molecule metabolites in the development of the neurodegenerative diseases, which may be valuable for the investigation of underlying mechanism of therapeutic strategies.

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

Alzheimer's disease (AD) is a complex disease driven mainly by neuronal loss due to accumulation of intracellular neurofibrillary tangles and amyloid β aggregates in the brain. The diagnosis of AD currently relies on clinical symptoms while the disease can only be confirmed at autopsy. The few available biomarkers allowing for diagnosis are typically detected many years after the onset of the disease. New diagnostic approaches, particularly in easily-accessible biofluids, are essential. By providing an exhaustive information of the phenotype, metabolomics is an ideal approach for identification of new biomarkers. This review investigates the current position of metabolomics in the field of AD research, focusing on animal and human studies, and discusses the improvements carried out over the past decade.

Association of branched-chain amino acids and other circulating metabolites with risk of incident dementia and Alzheimer's disease: A prospective study in eight cohorts

INTRODUCTION

Metabolite, lipid, and lipoprotein lipid profiling can provide novel insights into mechanisms underlying incident dementia and Alzheimer's disease.

METHODS

We studied eight prospective cohorts with 22,623 participants profiled by nuclear magnetic resonance or mass spectrometry metabolomics. Four cohorts were used for discovery with replication undertaken in the other four to avoid false positives. For metabolites that survived replication, combined association results are presented.

RESULTS

Over 246,698 person-years, 995 and 745 cases of incident dementia and Alzheimer's disease were detected, respectively. Three branched-chain amino acids (isoleucine, leucine, and valine), creatinine and two very low density lipoprotein (VLDL)-specific lipoprotein lipid subclasses were associated with lower dementia risk. One high density lipoprotein (HDL; the concentration of cholesterol esters relative to total lipids in large HDL) and one VLDL (total cholesterol to total lipids ratio in very large VLDL) lipoprotein lipid subclass was associated with increased dementia risk. Branched-chain amino acids were also associated with decreased Alzheimer's disease risk and the concentration of cholesterol esters relative to total lipids in large HDL with increased Alzheimer's disease risk.

DISCUSSION

Further studies can clarify whether these molecules play a causal role in dementia pathogenesis or are merely markers of early pathology.

From correlation to causation: analysis of metabolomics data using systems biology approaches

INTRODUCTION

Metabolomics is a well-established tool in systems biology, especially in the top-down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.

OBJECTIVES

This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.

METHODS

We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.

RESULTS

We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.

CONCLUSIONS

Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.

Effects of Ectoine on Behavior and Candidate Genes Expression in ICV-STZ Rat Model of Sporadic Alzheimer's Disease

Purpose: Alzheimer's disease (AD) is pathologically defined by the presence of amyloid plaques and tangles in the brain, therefore, any drug or compound with potential effect on lowering amyloid plaques, could be noticed for AD management especially in the primary phases of the disease. Ectoine constitutes a group of small molecule chaperones (SMCs). SMCs inhibit proteins and other changeable macromolecular structures misfolding from environmental stresses. Ectoine has been reported successfully prohibit insulin amyloid formation in vitro. Methods: We selected eight genes, DAXX, NFκβ, VEGF, PSEN1, MTAP2, SYP, MAPK3 and TNFα genes which had previously showed significant differential expression in Alzheimer human brain and STZ- rat model. We considered the neuroprotective efficacy by comparing the expression of candidate genes levels in the hippocampus of rat model of Sopradic Alzheimer's disease (SAD), using qPCR in compound-treated and control groups as well as therapeutic effects at learning and memory levels by using Morris Water Maze (MWM) test. Results: Our results showed significant down-regulation of Syp, Mapk3 and Tnfα and up-regulation of Vegf in rat's hippocampus after treatment with ectoine comparing to the STZ-induced group. In MWM, there was no significant change in swimming distance and time for finding the hidden platform in treated comparing to STZ-induced group. In addition, it wasn't seen significant change in compound-treated comparing to STZ-induced and control groups in memory level. Conclusion: It seems this compound may have significant effect on expression level of some AD- related genes but not on clinical levels.