Metabolic network failures in Alzheimer's disease: A biochemical road map

Gut-derived metabolites mediating cognitive development in 5-year-old children: Early-life transplant in mice has lasting effects throughout adulthood

The gut microbiota has been causally linked to cognitive development. We aimed to identify metabolites mediating its effect on cognitive development, and foods or nutrients related to most promising metabolites. Faeces from 5-year-old children (DORIAN-PISAC cohort, including 90 general population families with infants, 42/48 females/males, born in 2011-2014) were transplanted (FMT) into C57BL/6 germ-free mice. Children and recipient mice were stratified by cognitive phenotype, or based on protective metabolites. Food frequency questionnaires were obtained in children. Cognitive measurements in mice included five Y-maze tests until 23 weeks post-FMT, and (at 23 weeks) PET-CT for brain metabolism and radiodensity, and ultrasound-based carotid vascular indices. Children (faeces, urine) and mice (faeces, plasma) metabolome was measured by 1H NMR spectroscopy, and the faecal microbiota was profiled in mice by 16S rRNA amplicon sequencing. Cognitive scores of children and recipient mice were correlated. FMT-dependent modifications of brain metabolism were observed. Mice receiving FMT from high-cognitive or protective metabolite-enriched children developed superior cognitive-behavioural performance. A panel of metabolites, namely xanthine, hypoxanthine, formate, mannose, tyrosine, phenylalanine, glutamine, was found to mediate the gut-cognitive axis in donor children and recipient mice. Vascular indices partially explained the metabolite-to-phenotype relationships. Children's consumption of legumes, whole-milk yogurt and eggs, and intake of iron, zinc and vitamin D appeared to support protective gut metabolites. Overall, metabolites involved in inflammation, purine metabolism and neurotransmitter synthesis mediate the gut-cognitive axis, and holds promise for screening. The related dietary and nutritional findings offer leads to microbiota-targeted interventions for cognitive protection, with long-lasting effects.

Cerebral venous congestion alters brain metabolite profiles, impairing cognitive function

Vascular cognitive impairment (VCI) represents the second most common cause of dementia after Alzheimer's disease, and pathological changes in cerebral vascular structure and function are pivotal causes of VCI. Cognitive impairment caused by arterial ischemia has been extensively studied the whole time; the influence of cerebral venous congestion on cognitive impairment draws doctors' attention in recent clinical practice, but the underlying neuropathophysiological alterations are not completely understood. This study elucidated the specific pathogenetic role of cerebral venous congestion in cognitive-behavioral deterioration and possible electrophysiological mechanisms. Using cerebral venous congestion rat models, we found these rats exhibited decreased long-term potentiation (LTP) in the hippocampal dentate gyrus and impaired spatial learning and memory. Based on untargeted metabolomics, N-acetyl-L-cysteine (NAC) deficiency was detected in cerebral venous congestion rats; supplementation with NAC appeared to ameliorate synaptic deficits, rescue impaired LTP, and mitigate cognitive impairment. In a cohort of cerebral venous congestion patients, NAC levels were decreased; NAC concentration was negatively correlated with subjective cognitive decline (SCD) score but positively correlated with mini-mental state examination (MMSE) score. These findings provide a new perspective on cognitive impairment and support further exploration of NAC as a therapeutic target for the prevention and treatment of VCI.

Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

BACKGROUND

Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics.

METHODS

The c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification.

FINDINGS

The application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6).

INTERPRETATION

Our results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.

FUNDING

The specific funding of this article is provided in the acknowledgements section.

Alteration of Metabolic Profiles during the Progression of Alzheimer's Disease

(1) Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that threatens the population health of older adults. However, the mechanisms of the altered metabolism involved in AD pathology are poorly understood. The aim of the study was to identify the potential biomarkers of AD and discover the metabolomic changes produced during the progression of the disease. (2) Methods: Gas chromatography-mass spectrometry (GC-MS) was used to measure the concentrations of the serum metabolites in a cohort of subjects with AD (n = 88) and a cognitively normal control (CN) group (n = 85). The patients were classified as very mild (n = 25), mild (n = 27), moderate (n = 25), and severe (n = 11). The serum metabolic profiles were analyzed using multivariate and univariate approaches. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied to identify the potential biomarkers of AD. Biofunctional enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. (3) Results: Our results revealed considerable separation between the AD and CN groups. Six metabolites were identified as potential biomarkers of AD (AUC > 0.85), and the diagnostic model of three metabolites could predict the risk of AD with high accuracy (AUC = 0.984). The metabolic enrichment analysis revealed that carbohydrate metabolism deficiency and the disturbance of amino acid, fatty acid, and lipid metabolism were involved in AD progression. Especially, the pathway analysis highlighted that l-glutamate participated in four crucial nervous system pathways (including the GABAergic synapse, the glutamatergic synapse, retrograde endocannabinoid signaling, and the synaptic vesicle cycle). (4) Conclusions: Carbohydrate metabolism deficiency and amino acid dysregulation, fatty acid, and lipid metabolism disorders were pivotal events in AD progression. Our study may provide novel insights into the role of metabolic disorders in AD pathogenesis and identify new markers for AD diagnosis.

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

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

Metabolomic epidemiology offers insights into disease aetiology

Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.

Changes in Plasma Neutral and Ether-Linked Lipids Are Associated with The Pathology and Progression of Alzheimer's Disease

Aberrant lipid metabolism has been strongly linked to Alzheimer's disease (AD) pathogenesis. However, the role of lipids in the pathophysiological processes of AD and their clinical progression is unclear. We hypothesized that plasma lipids are associated with the pathological hallmarks of AD, progression from mild cognitive impairment (MCI) to AD, and the rate of cognitive decline in MCI patients. To evaluate our hypotheses, we analysed the plasma lipidome profile by liquid chromatography coupled to mass spectrometry in an LC-ESI-QTOF-MS/MS platform for 213 subjects recruited consecutively: 104 AD, 89 MCI, and 20 control subjects. Forty-seven (52.8%) MCI patients progressed to AD during follow-up (58 ± 12.5 months). We found that higher plasma levels of sphingomyelin SM(36:0) and diglyceride DG(44:3) were associated with an increased risk of amyloid beta 42 (Aβ42) positivity in CSF, while levels of SM(40:1) were associated with a reduced risk. Higher plasma levels of ether-linked triglyceride TG(O-60:10) were negatively associated with pathological levels of phosphorylated tau in CSF. Plasma levels of fatty acid ester of hydroxy fatty acid FAHFA(34:0) and ether-linked phosphatidylcholine PC(O-36:1) were positively associated with pathological levels of total tau in CSF. Regarding the plasma lipids most associated with progression from MCI to AD, our analysis detected phosphatidyl-ethanolamine plasmalogen PE(P-36:4), TG(59:12), TG(46:0), and TG(O-62:7). Furthermore, TG(O-62:7) was the lipid that was most strongly associated with the rate of progression. In conclusion, our results indicate that neutral and ether-linked lipids are involved in the pathophysiological processes of AD and the progression from MCI to AD dementia, suggesting the involvement of lipid-mediated antioxidant mechanisms in AD.

Nutrition in Alzheimer's disease: a review of an underappreciated pathophysiological mechanism

Alzheimer's disease (AD) is the leading cause of dementia in older individuals and is an escalating challenge to global public health. Pharmacy therapy of AD is one of the well-funded areas; however, little progress has been made due to the complex pathogenesis. Recent evidence has demonstrated that modifying risk factors and lifestyle may prevent or delay the incidence of AD by 40%, which suggests that the management should pivot from single pharmacotherapy toward a multipronged approach because AD is a complex and multifaceted disease. Recently, the gut-microbiota-brain axis has gained tremendous traction in the pathogenesis of AD through bidirectional communication with multiple neural, immune, and metabolic pathways, providing new insights into novel therapeutic strategies. Dietary nutrition is an important and profound environmental factor that influences the composition and function of the microbiota. The Nutrition for Dementia Prevention Working Group recently found that dietary nutrition can affect cognition in AD-related dementia directly or indirectly through complex interactions of behavioral, genetic, systemic, and brain factors. Thus, considering the multiple etiologies of AD, nutrition represents a multidimensional factor that has a profound effect on AD onset and development. However, mechanistically, the effect of nutrition on AD is uncertain; therefore, optimal strategies or the timing of nutritional intervention to prevent or treat AD has not been established.Thus, this review summarizes the current state of knowledge concerning nutritional disorders, AD patient and caregiver burden, and the roles of nutrition in the pathophysiology of AD. We aim to emphasize knowledge gaps to provide direction for future research and to establish optimal nutrition-based intervention strategies for AD.

Metabolomic Signatures of Alzheimer's Disease Indicate Brain Region-Specific Neurodegenerative Progression

Pathological mechanisms contributing to Alzheimer's disease (AD) are still elusive. Here, we identified the metabolic signatures of AD in human post-mortem brains. Using 1H NMR spectroscopy and an untargeted metabolomics approach, we identified (1) metabolomic profiles of AD and age-matched healthy subjects in post-mortem brain tissue, and (2) region-common and region-unique metabolome alterations and biochemical pathways across eight brain regions revealed that BA9 was the most affected. Phenylalanine and phosphorylcholine were mainly downregulated, suggesting altered neurotransmitter synthesis. N-acetylaspartate and GABA were upregulated in most regions, suggesting higher inhibitory activity in neural circuits. Other region-common metabolic pathways indicated impaired mitochondrial function and energy metabolism, while region-unique pathways indicated oxidative stress and altered immune responses. Importantly, AD caused metabolic changes in brain regions with less well-documented pathological alterations that suggest degenerative progression. The findings provide a new understanding of the biochemical mechanisms of AD and guide biomarker discovery for personalized risk prediction and diagnosis.

Mitochondrial regulator PGC-1a in neuronal metabolism and brain aging

The brain is a high energy tissue, and the cell types of which it is comprised are distinct in function and in metabolic requirements. The transcriptional co-activator PGC-1a is a master regulator of mitochondrial function and is highly expressed in the brain; however, its cell-type specific role in regulating metabolism has not been well established. Here, we show that PGC-1a is responsive to aging and that expression of the neuron specific PGC-1a isoform allows for specialization in metabolic adaptation. Transcriptional profiles of the cortex from male mice show an impact of age on immune, inflammatory, and neuronal functional pathways and a highly integrated metabolic response that is associated with decreased expression of PGC-1a. Proteomic analysis confirms age-related changes in metabolism and further shows changes in ribosomal and RNA splicing pathways. We show that neurons express a specialized PGC-1a isoform that becomes active during differentiation from stem cells and is further induced during the maturation of isolated neurons. Neuronal but not astrocyte PGC-1a responds robustly to inhibition of the growth sensitive kinase GSK3b, where the brain specific promoter driven dominant isoform is repressed. The GSK3b inhibitor lithium broadly reprograms metabolism and growth signaling, including significantly lower expression of mitochondrial and ribosomal pathway genes and suppression of growth signaling, which are linked to changes in mitochondrial function and neuronal outgrowth. In vivo, lithium treatment significantly changes the expression of genes involved in cortical growth, endocrine, and circadian pathways. These data place the GSK3b/PGC-1a axis centrally in a growth and metabolism network that is directly relevant to brain aging.

Hepatic soluble epoxide hydrolase activity regulates cerebral Aβ metabolism and the pathogenesis of Alzheimer's disease in mice

Alzheimer's disease (AD) is caused by a complex interaction between genetic and environmental factors. However, how the role of peripheral organ changes in response to environmental stimuli during aging in AD pathogenesis remains unknown. Hepatic soluble epoxide hydrolase (sEH) activity increases with age. Hepatic sEH manipulation bidirectionally attenuates brain amyloid-β (Aβ) burden, tauopathy, and cognitive deficits in AD mouse models. Moreover, hepatic sEH manipulation bidirectionally regulates the plasma level of 14,15-epoxyeicosatrienoic acid (-EET), which rapidly crosses the blood-brain barrier and modulates brain Aβ metabolism through multiple pathways. A balance between the brain levels of 14,15-EET and Aβ is essential for preventing Aβ deposition. In AD models, 14,15-EET infusion mimicked the neuroprotective effects of hepatic sEH ablation at biological and behavioral levels. These results highlight the liver's key role in AD pathology, and targeting the liver-brain axis in response to environmental stimuli may constitute a promising therapeutic approach for AD prevention.

Whole-body 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 utilized 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 personalized 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.

Advances in peripheral blood biomarkers of patients with Alzheimer's disease: Moving closer to personalized therapies

Recently, measurable peripheral biomarkers in the plasma of patients with Alzheimer's disease (AD) have gained considerable clinical interest. Several studies have identified one or more blood signatures that may facilitate the development of novel diagnostic and therapeutic strategies. For instance, changes in peripheral amyloid β42 (Aβ42) levels have been largely investigated in patients with AD and correlated with the progression of the pathology, although with controversial results. In addition, tumor necrosis factor α (TNFα) has been identified as an inflammatory biomarker strongly associated with AD, and several studies have consistently suggested the pharmacological targeting of TNFα to reduce systemic inflammation and prevent neurotoxicity in AD. Moreover, alterations in plasma metabolite levels appear to predict the progression of systemic processes relevant to brain functions. In this study, we analyzed the changes in the levels of Aβ42, TNFα, and plasma metabolites in subjects with AD and compared the results with those in healthy elderly (HE) subjects. Differences in plasma metabolites of patients with AD were analyzed with respect to Aβ42, TNFα, and the Mini-Mental State Examination (MMSE) score, searching for plasma signatures that changed simultaneously. In addition, the phosphorylation levels of the Tyr682 residue of the amyloid precursor protein (APP), which we previously proposed as a biomarker of AD, were measured in five HE and five AD patients, in whom the levels of Aβ42, TNFα, and two plasma lipid metabolites increased simultaneously. Overall, this study highlights the potential of combining different plasma signatures to define specific clinical phenotypes of patient subgroups, thus paving the way for the stratification of patients with AD and development of personalized approaches.

Lysophosphatidylcholines are associated with P-tau181 levels in early stages of Alzheimer's Disease

Background

We investigated systemic biochemical changes in Alzheimer's disease (AD) by investigating the relationship between circulating plasma metabolites and both clinical and biomarker-assisted diagnosis of AD.

Methods

We used an untargeted approach with liquid chromatography coupled to high-resolution mass spectrometry to measure exogenous and endogenous small molecule metabolites in plasma from 150 individuals clinically diagnosed with AD and 567 age-matched elderly without dementia of Caribbean Hispanic ancestry. Plasma biomarkers of AD were also measured including P-tau181, Aβ40, Aβ42, total tau, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP). Association of individual and co-expressed modules of metabolites were tested with the clinical diagnosis of AD, as well as biologically-defined AD pathological process based on P-tau181 and other biomarker levels.

Results

Over 4000 metabolomic features were measured with high accuracy. First principal component (PC) of lysophosphatidylcholines (lysoPC) that bind to or interact with docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA) and arachidonic acid (AHA) was associated with decreased risk of AD (OR=0.91 [0.89-0.96], p=2e-04). Restricted to individuals without an APOE ε4 allele (OR=0.89 [0.84-0.94], p= 8.7e-05), the association remained. Among individuals carrying at least one APOE ε4 allele, PC4 of lysoPCs moderately increased risk of AD (OR=1.37 [1.16-1.6], p=1e-04). Essential amino acids including tyrosine metabolism pathways were enriched among metabolites associated with P-tau181 levels and heparan and keratan sulfate degradation pathways were associated with Aβ42/Aβ40 ratio reflecting different pathways enriched in early and middle stages of disease.

Conclusions

Our findings indicate that unbiased metabolic profiling can identify critical metabolites and pathways associated with β-amyloid and phosphotau pathology. We also observed an APOE ε4 dependent association of lysoPCs with AD and that biologically-based diagnostic criteria may aid in the identification of unique pathogenic mechanisms.

Integration of plasma and CSF metabolomics with CSF proteomic reveals novel associations between lipid mediators and central nervous system vascular and energy metabolism

Integration of the omics data, including metabolomics and proteomics, provides a unique opportunity to search for new associations within metabolic disorders, including Alzheimer's disease. Using metabolomics, we have previously profiled oxylipins, endocannabinoids, bile acids, and steroids in 293 CSF and 202 matched plasma samples from AD cases and healthy controls and identified both central and peripheral markers of AD pathology within inflammation-regulating cytochrome p450/soluble epoxide hydrolase pathway. Additionally, using proteomics, we have identified five cerebrospinal fluid protein panels, involved in the regulation of energy metabolism, vasculature, myelin/oligodendrocyte, glia/inflammation, and synapses/neurons, affected in AD, and reflective of AD-related changes in the brain. In the current manuscript, using metabolomics-proteomics data integration, we describe new associations between peripheral and central lipid mediators, with the above-described CSF protein panels. Particularly strong associations were observed between cytochrome p450/soluble epoxide hydrolase metabolites, bile acids, and proteins involved in glycolysis, blood coagulation, and vascular inflammation and the regulators of extracellular matrix. Those metabolic associations were not observed at the gene-co-expression level in the central nervous system. In summary, this manuscript provides new information regarding Alzheimer's disease, linking both central and peripheral metabolism, and illustrates the necessity for the "omics" data integration to uncover associations beyond gene co-expression.

Plasma lipidomics reveals potential lipid markers for the prediction of delayed neurocognitive recovery after cardiac surgery with cardiopulmonary bypass

BACKGROUND

Delayed neurocognitive recovery (DNR) is a cognitive change that affects patients after anesthesia and surgery, with a high incidence, severely impairing their quality of life. We identified relevant metabolic pathways to determine predictive lipid markers and understand the pathogenesis of DNR.

METHODS

A non-targeted lipidomic strategy using Waters Acquity I Class UPLC-Xevo G2-S QTOF UPLC-MS was employed to identify different lipids in the 24 h postoperative plasma of patients whose cognitive function was assessed 7-14 days after surgery. Principal component analysis, orthogonal partial least squares discriminant analysis, and receiver operating characteristic (ROC) curves were used to identify potential biomarkers for predicting DNR. Metabolic pathway analysis was performed using the online platform MetaboAnalyst 5.0.

RESULTS

Pre-operative hemoglobin was identified as an independent risk factor for DNR. The individual areas under the ROC curves (AUC) of the 5 representative lipids were all > 0.6, and the AUC of the combined predictor was 0.912. Glycerophospholipid metabolic pathway was dysregulated in patients with subsequent DNR.

CONCLUSION

This study identified a series of potential predictive biomarkers for DNR. These data suggested that glycerophospholipid metabolism may be the mechanism underlying the occurrence and progression of DNR.

Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.

siRNA drug delivery across the blood-brain barrier in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disease with a few FDA-approved drugs that provide modest symptomatic benefits and only two FDA-approved disease-modifying treatments for AD. The advancements in understanding the causative genes and non-coding sequences at the molecular level of the pathophysiology of AD have resulted in several exciting research papers that employed small interfering RNA (siRNA)-based therapy. Although siRNA is being sought by academia and biopharma industries, several challenges still need to be addressed. We comprehensively report the latest advances in AD pathophysiology, druggable targets, ongoing clinical trials, and the siRNA-based approaches across the blood-brain barrier for addressing AD. This review describes the latest delivery systems employed to address this barrier. Critical insights and future perspectives on siRNA therapy for AD are also provided.

Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information, with its application to neuroscience termed neuroinformatics. Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms, which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases. Importantly, integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile. In this review, we first summarize data mining studies utilizing datasets from the individual type of omics analysis, including epigenetics/epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and spatial omics, pertaining to Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We then discuss multi-omics integration approaches, including independent biological integration and unsupervised integration methods, for more intuitive and informative interpretation of the biological data obtained across different omics layers. We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks. Finally, we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery, therapeutic development, and elucidation of disease mechanisms. We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.

High preoperative blood oxaloacetate and 2-aminoadipic acid levels are associated with postoperative delayed neurocognitive recovery

Introduction

This study aimed to identify preoperative blood biomarkers related to development of delayed neurocognitive recovery (dNCR) following surgery.

Methods

A total of 67 patients (≥65 years old) who underwent head and neck tumor resection under general anesthesia were assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Preoperative serum metabolomics were determined using widely targeted metabolomics technology.

Results

Of the 67 patients, 25 developed dNCR and were matched to 25 randomly selected patients from the remaining 42 without dNCR. Differential metabolites were selected using the criteria of variable importance in projection > 1.0 in orthogonal partial least squares discrimination analysis, false discovery rate <0.05, and fold-change >1.2 or <0.83 to minimize false positives. Preoperative serum levels of oxaloacetate (OR: 1.054, 95% CI: 1.027-1.095, P = 0.001) and 2-aminoadipic acid (2-AAA) (OR: 1.181, 95% CI: 1.087-1.334, P = 0.001) were associated with postoperative dNCR after adjusting for anesthesia duration, education, and age. Areas under the curve for oxaloacetate and 2-AAA were 0.86 (sensitivity: 0.84, specificity: 0.88) and 0.86 (sensitivity: 0.84, specificity: 0.84), respectively. High levels of preoperative oxaloacetate and 2-AAA also were associated with postoperative decreased MoCA (β: 0.022, 95% CI: 0.005-0.04, P = 0.013 for oxaloacetate; β: 0.077, 95%CI: 0.016-0.137, P = 0.014 for 2-AAA) and MMSE (β: 0.024, 95% CI: 0.009-0.039, P = 0.002 for oxaloacetate; β: 0.083, 95% CI: 0.032-0.135, P = 0.002 for 2-AAA) scores after adjusting for age, education level, and operation time.

Conclusion

High preoperative blood levels of oxaloacetate and 2-AAA were associated with increased risk of postoperative dNCR.

Clinical trial registration

https://classic.clinicaltrials.gov/ct2/show/NCT05105451, identifier NCT05105451.

Comparative brain metabolomics reveals shared and distinct metabolic alterations in Alzheimer's disease and progressive supranuclear palsy

Metabolic dysregulation is a hallmark of neurodegenerative diseases, including Alzheimer's disease (AD) and progressive supranuclear palsy (PSP). While metabolic dysregulation is a common link between these two tauopathies, a comprehensive brain metabolic comparison of the diseases has not yet been performed. We analyzed 342 postmortem brain samples from the Mayo Clinic Brain Bank and examined 658 metabolites in the cerebellar cortex and the temporal cortex between the two tauopathies. Our findings indicate that both diseases display oxidative stress associated with lipid metabolism, mitochondrial dysfunction linked to lysine metabolism, and an indication of tau-induced polyamine stress response. However, specific to AD, we detected glutathione-related neuroinflammation, deregulations of enzymes tied to purines, and cognitive deficits associated with vitamin B. Taken together, our findings underscore vast alterations in the brain's metabolome, illuminating shared neurodegenerative pathways and disease-specific traits in AD and PSP.

Modeling of mitochondrial genetic polymorphisms reveals induction of heteroplasmy by pleiotropic disease locus 10398A>G

Mitochondrial (MT) dysfunction has been associated with several neurodegenerative diseases including Alzheimer's disease (AD). While MT-copy number differences have been implicated in AD, the effect of MT heteroplasmy on AD has not been well characterized. Here, we analyzed over 1800 whole genome sequencing data from four AD cohorts in seven different tissue types to determine the extent of MT heteroplasmy present. While MT heteroplasmy was present throughout the entire MT genome for blood samples, we detected MT heteroplasmy only within the MT control region for brain samples. We observed that an MT variant 10398A>G (rs2853826) was significantly associated with overall MT heteroplasmy in brain tissue while also being linked with the largest number of distinct disease phenotypes of all annotated MT variants in MitoMap. Using gene-expression data from our brain samples, our modeling discovered several gene networks involved in mitochondrial respiratory chain and Complex I function associated with 10398A>G. The variant was also found to be an expression quantitative trait loci (eQTL) for the gene MT-ND3. We further characterized the effect of 10398A>G by phenotyping a population of lymphoblastoid cell-lines (LCLs) with and without the variant allele. Examination of RNA sequence data from these LCLs reveal that 10398A>G was an eQTL for MT-ND4. We also observed in LCLs that 10398A>G was significantly associated with overall MT heteroplasmy within the MT control region, confirming the initial findings observed in post-mortem brain tissue. These results provide novel evidence linking MT SNPs with MT heteroplasmy and open novel avenues for the investigation of pathomechanisms that are driven by this pleiotropic disease associated loci.

Circulating lipid profiles are associated with cross-sectional and longitudinal changes of central biomarkers for Alzheimer's disease

Investigating the association of lipidome profiles with central Alzheimer's disease (AD) biomarkers, including amyloid/tau/neurodegeneration (A/T/N), can provide a holistic view between the lipidome and AD. We performed cross-sectional and longitudinal association analysis of serum lipidome profiles with AD biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort (N=1,395). We identified lipid species, classes, and network modules that were significantly associated with cross-sectional and longitudinal changes of A/T/N biomarkers for AD. Notably, we identified the lysoalkylphosphatidylcholine (LPC(O)) as associated with "A/N" biomarkers at baseline at lipid species, class, and module levels. Also, GM3 ganglioside showed significant association with baseline levels and longitudinal changes of the "N" biomarkers at species and class levels. Our study of circulating lipids and central AD biomarkers enabled identification of lipids that play potential roles in the cascade of AD pathogenesis. Our results suggest dysregulation of lipid metabolic pathways as precursors to AD development and progression.

A Targeted Mass Spectrometry Approach to Identify Peripheral Changes in Metabolic Pathways of Patients with Alzheimer's Disease

Alzheimer's disease (AD), a neurodegenerative disorder, is the most common cause of dementia in the elderly population. Since its original description, there has been intense debate regarding the factors that trigger its pathology. It is becoming apparent that AD is more than a brain disease and harms the whole-body metabolism. We analyzed 630 polar and apolar metabolites in the blood of 20 patients with AD and 20 healthy individuals, to determine whether the composition of plasma metabolites could offer additional indicators to evaluate any alterations in the metabolic pathways related to the illness. Multivariate statistical analysis showed that there were at least 25 significantly dysregulated metabolites in patients with AD compared with the controls. Two membrane lipid components, glycerophospholipids and ceramide, were upregulated, whereas glutamic acid, other phospholipids, and sphingolipids were downregulated. The data were analyzed using metabolite set enrichment analysis and pathway analysis using the KEGG library. The results showed that at least five pathways involved in the metabolism of polar compounds were dysregulated in patients with AD. Conversely, the lipid pathways did not show significant alterations. These results support the possibility of using metabolome analysis to understand alterations in the metabolic pathways related to AD pathophysiology.

Gut Microbiota is an Impact Factor based on the Brain-Gut Axis to Alzheimer's Disease: A Systematic Review

Alzheimer's disease (AD) is a degenerative disease of the central nervous system. The pathogenesis of AD has been explained using cholinergic, β-amyloid toxicity, tau protein hyperphosphorylation, and oxidative stress theories. However, an effective treatment method has not been developed. In recent years, with the discovery of the brain-gut axis (BGA) and breakthroughs made in Parkinson's disease, depression, autism, and other diseases, BGA has become a hotspot in AD research. Several studies have shown that gut microbiota can affect the brain and behavior of patients with AD, especially their cognitive function. Animal models, fecal microbiota transplantation, and probiotic intervention also provide evidence regarding the correlation between gut microbiota and AD. This article discusses the relationship and related mechanisms between gut microbiota and AD based on BGA to provide possible strategies for preventing or alleviating AD symptoms by regulating gut microbiota.

Cross-Platform Synaptic Network Analysis of Human Entorhinal Cortex Identifies TWF2 as a Modulator of Dendritic Spine Length

Proteomic studies using postmortem human brain tissue samples have yielded robust assessments of the aging and neurodegenerative disease(s) proteomes. While these analyses provide lists of molecular alterations in human conditions, like Alzheimer's disease (AD), identifying individual proteins that affect biological processes remains a challenge. To complicate matters, protein targets may be highly understudied and have limited information on their function. To address these hurdles, we sought to establish a blueprint to aid selection and functional validation of targets from proteomic datasets. A cross-platform pipeline was engineered to focus on synaptic processes in the entorhinal cortex (EC) of human patients, including controls, preclinical AD, and AD cases. Label-free quantification mass spectrometry (MS) data (n = 2260 proteins) was generated on synaptosome fractionated tissue from Brodmann area 28 (BA28; n = 58 samples). In parallel, dendritic spine density and morphology was measured in the same individuals. Weighted gene co-expression network analysis was used to construct a network of protein co-expression modules that were correlated with dendritic spine metrics. Module-trait correlations were used to guide unbiased selection of Twinfilin-2 (TWF2), which was the top hub protein of a module that positively correlated with thin spine length. Using CRISPR-dCas9 activation strategies, we demonstrated that boosting endogenous TWF2 protein levels in primary hippocampal neurons increased thin spine length, thus providing experimental validation for the human network analysis. Collectively, this study describes alterations in dendritic spine density and morphology as well as synaptic proteins and phosphorylated tau from the entorhinal cortex of preclinical and advanced stage AD patients.SIGNIFICANCE STATEMENT Proteomic studies can yield vast lists of molecules that are altered under various experimental or disease conditions. Here, we provide a blueprint to facilitate mechanistic validation of protein targets from human brain proteomic datasets. We conducted a proteomic analysis of human entorhinal cortex (EC) samples spanning cognitively normal and Alzheimer's disease (AD) cases with a comparison of dendritic spine morphology in the same samples. Network integration of proteomics with dendritic spine measurements allowed for unbiased discovery of Twinfilin-2 (TWF2) as a regulator of dendritic spine length. A proof-of-concept experiment in cultured neurons demonstrated that altering Twinfilin-2 protein level induced corresponding changes in dendritic spine length, thus providing experimental validation for the computational framework.

Using stable isotope tracing to unravel the metabolic components of neurodegeneration: Focus on neuron-glia metabolic interactions

Disrupted brain metabolism is a critical component of several neurodegenerative diseases. Energy metabolism of both neurons and astrocytes is closely connected to neurotransmitter recycling via the glutamate/GABA-glutamine cycle. Neurons and astrocytes hereby work in close metabolic collaboration which is essential to sustain neurotransmission. Elucidating the mechanistic involvement of altered brain metabolism in disease progression has been aided by the advance of techniques to monitor cellular metabolism, in particular by mapping metabolism of substrates containing stable isotopes, a technique known as isotope tracing. Here we review key aspects of isotope tracing including advantages, drawbacks and applications to different cerebral preparations. In addition, we narrate how isotope tracing has facilitated the discovery of central metabolic features in neurodegeneration with a focus on the metabolic cooperation between neurons and astrocytes.

Exercise Alleviates Behavioral Disorders but Shapes Brain Metabolism of APP/PS1 Mice in a Region- and Exercise-Specific Manner

Exercise plays a beneficial role in the management of Alzheimer's disease (AD), but its effects on brain metabolism are still far from being understood. Here, we examined behavioral changes of APP/PS1 mice after high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) and analyzed metabolomics profiles in the hippocampus, cortex, and hypothalamus by using nuclear magnetic resonance spectroscopy to explore potential metabolic mechanisms. The results demonstrate that both HIIT and MICT alleviated anxiety/depressive-like behaviors as well as learning and memory impairments of AD mice. Metabolomics analysis reveals that energy metabolism, neurotransmitter metabolism, and membrane metabolism were significantly altered in all three brain regions after both types of exercises. Amino acid metabolism was detected to be affected in the cortex and hypothalamus after HIIT and in the hippocampus and hypothalamus after MICT. However, only HIIT significantly altered astrocyte-neuron metabolism in the hippocampus and hypothalamus of AD mice. Therefore, our study suggests that exercise can shape brain metabolism of AD mice in a region- and exercise-specific manner, indicating that the precise modification of brain metabolism by a specific type of exercise might be a novel perspective for the prevention and treatment of AD.

Metabolomic and lipidomic signatures in autosomal dominant and late-onset Alzheimer's disease brains

INTRODUCTION

The identification of multiple genetic risk factors for Alzheimer's disease (AD) suggests that many pathways contribute to AD onset and progression. However, the metabolomic and lipidomic profiles in carriers of distinct genetic risk factors are not fully understood. The metabolome can provide a direct image of dysregulated pathways in the brain.

METHODS

We interrogated metabolomic signatures in the AD brain, including carriers of pathogenic variants in APP, PSEN1, and PSEN2 (autosomal dominant AD; ADAD), APOE ɛ4, and TREM2 risk variant carriers, and sporadic AD (sAD).

RESULTS

We identified 133 unique and shared metabolites associated with ADAD, TREM2, and sAD. We identified a signature of 16 metabolites significantly altered between groups and associated with AD duration.

DISCUSSION

AD genetic variants show distinct metabolic perturbations. Investigation of these metabolites may provide greater insight into the etiology of AD and its impact on clinical presentation.

HIGHLIGHTS

APP/PSEN1/PSEN2 and TREM2 variant carriers show distinct metabolic changes. A total of 133 metabolites were differentially abundant in AD genetic groups. β-citrylglutamate is differentially abundant in autosomal dominant, TREM2, and sporadic AD. A 16-metabolite profile shows differences between Alzheimer's disease (AD) genetic groups. The identified metabolic profile is associated with duration of disease.

Insulin Resistance and Impaired Branched-Chain Amino Acid Metabolism in Alzheimer's Disease

The pathogenesis of Alzheimer's disease (AD) is complicated and involves multiple contributing factors. Mounting evidence supports the concept that AD is an age-related metabolic neurodegenerative disease mediated in part by brain insulin resistance, and sharing similar metabolic dysfunctions and brain pathological characteristics that occur in type 2 diabetes mellitus (T2DM) and other insulin resistance disorders. Brain insulin signal pathway is a major regulator of branched-chain amino acid (BCAA) metabolism. In the past several years, impaired BCAA metabolism has been described in several insulin resistant states such as obesity, T2DM and cardiovascular disease. Disrupted BCAA metabolism leading to elevation in circulating BCAAs and related metabolites is an early metabolic phenotype of insulin resistance and correlated with future onset of T2DM. Brain is a major site for BCAA metabolism. BCAAs play pivotal roles in normal brain function, especially in signal transduction, nitrogen homeostasis, and neurotransmitter cycling. Evidence from animal models and patients support the involvement of BCAA dysmetabolism in neurodegenerative diseases including Huntington's disease, Parkinson's disease, and maple syrup urine disease. More recently, growing studies have revealed altered BCAA metabolism in AD, but the relationship between them is poorly understood. This review is focused on the recent findings regarding BCAA metabolism and its role in AD. Moreover, we will explore how impaired BCAA metabolism influences brain function and participates in the pathogenesis of AD.

Quantitative Lipidomic Analysis of Serum Phospholipids Reveals Dissociable Markers of Alzheimer's Disease and Subcortical Cerebrovascular Disease

BACKGROUND

Circulating phospholipid species have been shown to predict Alzheimer's disease (AD) prognosis but the link between phospholipid disturbances and subcortical small vessel cerebrovascular disease (CeVD) common in AD patients is not known.

OBJECTIVE

This study used quantitative lipidomics to measure serum diacyl, alkenyl (ether), alkyl, and lyso phospholipid species in individuals with extensive CeVD (n = 29), AD with minimal CeVD (n = 16), and AD with extensive CeVD (n = 14), and compared them to age-matched controls (n = 27). Memory was assessed using the California Verbal Learning Test. 3.0T MRI was used to assess hippocampal volume, atrophy, and white matter hyperintensity (WMH) volumes as manifestations of CeVD.

RESULTS

AD was associated with significantly higher concentrations of choline plasmalogen 18:0_18:1 and alkyl-phosphocholine 18:1. CeVD was associated with significantly lower lysophospholipids containing 16:0. Phospholipids containing arachidonic acid (AA) were associated with poorer memory in controls, whereas docosahexaenoic acid (DHA)-containing phospholipids were associated with better memory in individuals with AD+CeVD. In controls, DHA-containing phospholipids were associated with more atrophy and phospholipids containing linoleic acid and AA were associated with less atrophy. Lysophospholipids containing 16:0, 18:0, and 18:1 were correlated with less atrophy in controls, and of these, alkyl-phosphocholine 18:1 was correlated with smaller WMH volumes. Conversely, 16:0_18:1 choline plasmalogen was correlated with greater WMH volumes in controls.

CONCLUSION

This study demonstrates discernable differences in circulating phospholipids in individuals with AD and CeVD, as well as new associations between phospholipid species with memory and brain structure that were specific to contexts of commonly comorbid vascular and neurodegenerative pathologies.

Quality Control of Targeted Plasma Lipids in a Large-Scale Cohort Study Using Liquid Chromatography-Tandem Mass Spectrometry

High-throughput metabolomics has enabled the development of large-scale cohort studies. Long-term studies require multiple batch-based measurements, which require sophisticated quality control (QC) to eliminate unexpected bias to obtain biologically meaningful quantified metabolomic profiles. Liquid chromatography-mass spectrometry was used to analyze 10,833 samples in 279 batch measurements. The quantified profile included 147 lipids including acylcarnitine, fatty acids, glucosylceramide, lactosylceramide, lysophosphatidic acid, and progesterone. Each batch included 40 samples, and 5 QC samples were measured for 10 samples of each. The quantified data from the QC samples were used to normalize the quantified profiles of the sample data. The intra- and inter-batch median coefficients of variation (CV) among the 147 lipids were 44.3% and 20.8%, respectively. After normalization, the CV values decreased by 42.0% and 14.7%, respectively. The effect of this normalization on the subsequent analyses was also evaluated. The demonstrated analyses will contribute to obtaining unbiased, quantified data for large-scale metabolomics.

Multi-omic integration via similarity network fusion to detect molecular subtypes of ageing

Molecular subtyping of brain tissue provides insights into the heterogeneity of common neurodegenerative conditions, such as Alzheimer's disease. However, existing subtyping studies have mostly focused on single data modalities and only those individuals with severe cognitive impairment. To address these gaps, we applied similarity network fusion, a method capable of integrating multiple high-dimensional multi-omic data modalities simultaneously, to an elderly sample spanning the full spectrum of cognitive ageing trajectories. We analyzed human frontal cortex brain samples characterized by five omic modalities: bulk RNA sequencing (18 629 genes), DNA methylation (53 932 CpG sites), histone acetylation (26 384 peaks), proteomics (7737 proteins) and metabolomics (654 metabolites). Similarity network fusion followed by spectral clustering was used for subtype detection, and subtype numbers were determined by Eigen-gap and rotation cost statistics. Normalized mutual information determined the relative contribution of each modality to the fused network. Subtypes were characterized by associations with 13 age-related neuropathologies and cognitive decline. Fusion of all five data modalities (n = 111) yielded two subtypes (n S1 = 53, n S2 = 58), which were nominally associated with diffuse amyloid plaques; however, this effect was not significant after correction for multiple testing. Histone acetylation (normalized mutual information = 0.38), DNA methylation (normalized mutual information = 0.18) and RNA abundance (normalized mutual information = 0.15) contributed most strongly to this network. Secondary analysis integrating only these three modalities in a larger subsample (n = 513) indicated support for both three- and five-subtype solutions, which had significant overlap, but showed varying degrees of internal stability and external validity. One subtype showed marked cognitive decline, which remained significant even after correcting for tests across both three- and five-subtype solutions (p Bonf = 5.9 × 10-3). Comparison to single-modality subtypes demonstrated that the three-modal subtypes were able to uniquely capture cognitive variability. Comprehensive sensitivity analyses explored influences of sample size and cluster number parameters. We identified highly integrative molecular subtypes of ageing derived from multiple high dimensional, multi-omic data modalities simultaneously. Fusing RNA abundance, DNA methylation, and histone acetylation measures generated subtypes that were associated with cognitive decline. This work highlights the potential value and challenges of multi-omic integration in unsupervised subtyping of post-mortem brain.

Functional Magnetic Resonance Spectroscopy of Lactate in Alzheimer Disease: A Comprehensive Review of Alzheimer Disease Pathology and the Role of Lactate

ABSTRACT

Functional 1H magnetic resonance spectroscopy (fMRS) is a derivative of dynamic MRS imaging. This modality links physiologic metabolic responses with available activity and measures absolute or relative concentrations of various metabolites. According to clinical evidence, the mitochondrial glycolysis pathway is disrupted in many nervous system disorders, especially Alzheimer disease, resulting in the activation of anaerobic glycolysis and an increased rate of lactate production. Our study evaluates fMRS with J-editing as a cutting-edge technique to detect lactate in Alzheimer disease. In this modality, functional activation is highlighted by signal subtractions of lipids and macromolecules, which yields a much higher signal-to-noise ratio and enables better detection of trace levels of lactate compared with other modalities. However, until now, clinical evidence is not conclusive regarding the widespread use of this diagnostic method. The complex machinery of cellular and noncellular modulators in lactate metabolism has obscured the potential roles fMRS imaging can have in dementia diagnosis. Recent developments in MRI imaging such as the advent of 7 Tesla machines and new image reconstruction methods, coupled with a renewed interest in the molecular and cellular basis of Alzheimer disease, have reinvigorated the drive to establish new clinical options for the early detection of Alzheimer disease. Based on the latter, lactate has the potential to be investigated as a novel diagnostic and prognostic marker for Alzheimer disease.

Investigating the causal association between branched-chain amino acids and Alzheimer's disease: A bidirectional Mendelian randomized study

Background

There are many metabolic pathway abnormalities in Alzheimer's disease (AD). Several studies have linked branched-chain amino acid (BCAA) metabolism disorders with AD but have not obtained consistent results. The purpose of this study is to explore the causal association between BCAA concentration and the risk of AD.

Methods

A bidirectional Mendelian randomized (MR) study was applied to explore the causal effect between BCAA level and the risk of AD. Genetic instrumental variables from the genome-wide association study (GWAS) of serum BCAA levels [total BCAAs (115,047 participants), valine (115,048 participants), leucine (115,074 participants), and isoleucine (115,075 participants)] from the UK Biobank and AD (21,982 AD cases and 41,944 controls) from the International Genomics of Alzheimer's Project were applied to explore the causal effect through the inverse variance-weighted (IVW) method, MR-Egger, and weighted median, accompanied by multiple pluripotency and heterogeneity tests.

Results

The forward MR analysis showed that there was no causal effect of total BCAAs (OR: 1.067, 95% CI: 0.838–1.358; p = 0.838), valine (OR: 1.106, 95% CI: 0.917–1.333; p = 0.292), leucine (OR: 1.096, 95% CI: 0.861–1.396; p = 0.659), and isoleucine (OR: 1.457, 95% CI: 1.024–2.742; p = 0.037) levels on the risk of AD. The reverse analysis showed that AD was related to reduced levels of total BCAAs (OR: 0.979, 95% CI: 0.989–0.990; p &lt; 0.001), valine (OR: 0.977, 95% CI: 0.963–0.991; p = 0.001), leucine (OR: 0.983, 95% CI: 0.973–0.994; p = 0.002), and isoleucine (OR: 0.982, 95% CI: 0.971–0.992; p = 0.001).

Conclusion

We provide robust evidence that AD was associated with a decreased level of BCAAs, which can serve as a marker for early diagnosis of AD.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Astrocytes display ultrastructural alterations and heterogeneity in the hippocampus of aged APP-PS1 mice and human post-mortem brain samples

The past decade has witnessed increasing evidence for a crucial role played by glial cells, notably astrocytes, in Alzheimer's disease (AD). To provide novel insights into the roles of astrocytes in the pathophysiology of AD, we performed a quantitative ultrastructural characterization of their intracellular contents and parenchymal interactions in an aged mouse model of AD pathology, as aging is considered the main risk factor for developing AD. We compared 20-month-old APP-PS1 and age-matched C57BL/6J male mice, among the ventral hippocampus CA1 strata lacunosum-moleculare and radiatum, two hippocampal layers severely affected by AD pathology. Astrocytes in both layers interacted more with synaptic elements and displayed more ultrastructural markers of increased phagolysosomal activity in APP-PS1 versus C57BL6/J mice. In addition, we investigated the ultrastructural heterogeneity of astrocytes, describing in the two examined layers a dark astrocytic state that we characterized in terms of distribution, interactions with AD hallmarks, and intracellular contents. This electron-dense astrocytic state, termed dark astrocytes, was observed throughout the hippocampal parenchyma, closely associated with the vasculature, and possessed several ultrastructural markers of cellular stress. A case study exploring the hippocampal head of an aged human post-mortem brain sample also revealed the presence of a similar electron-dense, dark astrocytic state. Overall, our study provides the first ultrastructural quantitative analysis of astrocytes among the hippocampus in aged AD pathology, as well as a thorough characterization of a dark astrocytic state conserved from mouse to human.

Nutritional metabolism and cerebral bioenergetics in Alzheimer's disease and related dementias

Disturbances in the brain's capacity to meet its energy demand increase the risk of synaptic loss, neurodegeneration, and cognitive decline. Nutritional and metabolic interventions that target metabolic pathways combined with diagnostics to identify deficits in cerebral bioenergetics may therefore offer novel therapeutic potential for Alzheimer's disease (AD) prevention and management. Many diet-derived natural bioactive components can govern cellular energy metabolism but their effects on brain aging are not clear. This review examines how nutritional metabolism can regulate brain bioenergetics and mitigate AD risk. We focus on leading mechanisms of cerebral bioenergetic breakdown in the aging brain at the cellular level, as well as the putative causes and consequences of disturbed bioenergetics, particularly at the blood-brain barrier with implications for nutrient brain delivery and nutritional interventions. Novel therapeutic nutrition approaches including diet patterns are provided, integrating studies of the gut microbiome, neuroimaging, and other biomarkers to guide future personalized nutritional interventions.

Metabolomic Footprint of Disrupted Energetics and Amino Acid Metabolism in Neurodegenerative Diseases: Perspectives for Early Diagnosis and Monitoring of Therapy

The prevalence of neurodegenerative diseases (NDs) is increasing due to the aging population and improved longevity. They are characterized by a range of pathological hallmarks, including protein aggregation, mitochondrial dysfunction, and oxidative stress. The aim of this review is to summarize the alterations in brain energy and amino acid metabolism in Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD). Based on our findings, we proposed a group of selected metabolites related to disturbed energy or mitochondrial metabolism as potential indicators or predictors of disease. We also discussed the hidden challenges of metabolomics studies in NDs and proposed future directions in this field. We concluded that biochemical parameters of brain energy metabolism disruption (obtained with metabolomics) may have potential application as a diagnostic tool for the diagnosis, prediction, and monitoring of the effectiveness of therapies for NDs. However, more studies are needed to determine the sensitivity of the proposed candidates. We suggested that the most valuable biomarkers for NDs studies could be groups of metabolites combined with other neuroimaging or molecular techniques. To attain clinically applicable results, the integration of metabolomics with other “omic” techniques might be required.

The landscape of metabolic brain alterations in Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is accompanied by metabolic alterations both in the periphery and the central nervous system. However, so far, a global view of AD-associated metabolic changes in the brain has been missing.

METHODS

We metabolically profiled 500 samples from the dorsolateral prefrontal cortex. Metabolite levels were correlated with eight clinical parameters, covering both late-life cognitive performance and AD neuropathology measures.

RESULTS

We observed widespread metabolic dysregulation associated with AD, spanning 298 metabolites from various AD-relevant pathways. These included alterations to bioenergetics, cholesterol metabolism, neuroinflammation, and metabolic consequences of neurotransmitter ratio imbalances. Our findings further suggest impaired osmoregulation as a potential pathomechanism in AD. Finally, inspecting the interplay of proteinopathies provided evidence that metabolic associations were largely driven by tau pathology rather than amyloid beta pathology.

DISCUSSION

This work provides a comprehensive reference map of metabolic brain changes in AD that lays the foundation for future mechanistic follow-up studies.

Metabolic Syndrome as a Risk Factor for Alzheimer's Disease: A Focus on Insulin Resistance

Alzheimer's disease (AD) is the main type of dementia and is a disease with a profound socioeconomic burden due to the lack of effective treatment. In addition to genetics and environmental factors, AD is highly associated with metabolic syndrome, defined as the combination of hypertension, hyperlipidemia, obesity and type 2 diabetes mellitus (T2DM). Among these risk factors, the connection between AD and T2DM has been deeply studied. It has been suggested that the mechanism linking both conditions is insulin resistance. Insulin is an important hormone that regulates not only peripheral energy homeostasis but also brain functions, such as cognition. Insulin desensitization, therefore, could impact normal brain function increasing the risk of developing neurodegenerative disorders in later life. Paradoxically, it has been demonstrated that decreased neuronal insulin signalling can also have a protective role in aging and protein-aggregation-associated diseases, as is the case in AD. This controversy is fed by studies focused on neuronal insulin signalling. However, the role of insulin action on other brain cell types, such as astrocytes, is still unexplored. Therefore, it is worthwhile exploring the involvement of the astrocytic insulin receptor in cognition, as well as in the onset and/or development of AD.

Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer's disease

BACKGROUND

Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD).

METHODS

Following quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (p_FDR < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (p_FDR < 0.05) with an imaging outcome (N = 1638).

RESULTS

In the fully adjusted model, three lipid modules were associated with a brain volume measure (p_FDR < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß =  - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß =  - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (p_FDR < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction.

CONCLUSIONS

Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality.

Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer's disease

INTRODUCTION

Late-onset Alzheimer's disease (LOAD) is a complex neurodegenerative disease characterized by multiple progressive stages, glucose metabolic dysregulation, Alzheimer's disease (AD) pathology, and inexorable cognitive decline. Discovery of metabolic profiles unique to sex, apolipoprotein E (APOE) genotype, and stage of disease progression could provide critical insights for personalized LOAD medicine.

METHODS

Sex- and APOE-specific metabolic networks were constructed based on changes in 127 metabolites of 656 serum samples from the Alzheimer's Disease Neuroimaging Initiative cohort.

RESULTS

Application of an advanced analytical platform identified metabolic drivers and signatures clustered with sex and/or APOE ɛ4, establishing patient-specific biomarkers predictive of disease state that significantly associated with cognitive function. Presence of the APOE ɛ4 shifts metabolic signatures to a phosphatidylcholine-focused profile overriding sex-specific differences in serum metabolites of AD patients.

DISCUSSION

These findings provide an initial but critical step in developing a diagnostic platform for personalized medicine by integrating metabolomic profiling and cognitive assessments to identify targeted precision therapeutics for AD patient subgroups through computational network modeling.

Ether Lipid-Mediated Antioxidant Defense in Alzheimer's Disease

One of the richest tissues in lipid content and diversity of the human body is the brain. The human brain is constitutively highly vulnerable to oxidative stress. This oxidative stress is a determinant in brain aging, as well as in the onset and progression of sporadic (late-onset) Alzheimer's disease (sAD). Glycerophospholipids are the main lipid category widely distributed in neural cell membranes, with a very significant presence for the ether lipid subclass. Ether lipids have played a key role in the evolution of the human brain compositional specificity and functionality. Ether lipids determine the neural membrane structural and functional properties, membrane trafficking, cell signaling and antioxidant defense mechanisms. Here, we explore the idea that ether lipids actively participate in the pathogenesis of sAD. Firstly, we evaluate the quantitative relevance of ether lipids in the human brain composition, as well as their role in the human brain evolution. Then, we analyze the implications of ether lipids in neural cell physiology, highlighting their inherent antioxidant properties. Finally, we discuss changes in ether lipid content associated with sAD and their physiopathological implications, and propose a mechanism that, as a vicious cycle, explains the potential significance of ether lipids in sAD.

Combined metabolic activators improve cognitive functions in Alzheimer's disease patients: a randomised, double-blinded, placebo-controlled phase-II trial

BACKGROUND

Alzheimer's disease (AD) is associated with metabolic abnormalities linked to critical elements of neurodegeneration. We recently administered combined metabolic activators (CMA) to the AD rat model and observed that CMA improves the AD-associated histological parameters in the animals. CMA promotes mitochondrial fatty acid uptake from the cytosol, facilitates fatty acid oxidation in the mitochondria, and alleviates oxidative stress.

METHODS

Here, we designed a randomised, double-blinded, placebo-controlled phase-II clinical trial and studied the effect of CMA administration on the global metabolism of AD patients. One-dose CMA included 12.35 g L-serine (61.75%), 1 g nicotinamide riboside (5%), 2.55 g N-acetyl-L-cysteine (12.75%), and 3.73 g L-carnitine tartrate (18.65%). AD patients received one dose of CMA or placebo daily during the first 28 days and twice daily between day 28 and day 84. The primary endpoint was the difference in the cognitive function and daily living activity scores between the placebo and the treatment arms. The secondary aim of this study was to evaluate the safety and tolerability of CMA. A comprehensive plasma metabolome and proteome analysis was also performed to evaluate the efficacy of the CMA in AD patients.

RESULTS

We showed a significant decrease of AD Assessment Scale-cognitive subscale (ADAS-Cog) score on day 84 vs day 0 (P = 0.00001, 29% improvement) in the CMA group. Moreover, there was a significant decline (P = 0.0073) in ADAS-Cog scores (improvement of cognitive functions) in the CMA compared to the placebo group in patients with higher ADAS-Cog scores. Improved cognitive functions in AD patients were supported by the relevant alterations in the hippocampal volumes and cortical thickness based on imaging analysis. Moreover, the plasma levels of proteins and metabolites associated with NAD + and glutathione metabolism were significantly improved after CMA treatment.

CONCLUSION

Our results indicate that treatment of AD patients with CMA can lead to enhanced cognitive functions and improved clinical parameters associated with phenomics, metabolomics, proteomics and imaging analysis. Trial registration ClinicalTrials.gov NCT04044131 Registered 17 July 2019, https://clinicaltrials.gov/ct2/show/NCT04044131.

Magnoflorine-Loaded Chitosan Collagen Nanocapsules Ameliorate Cognitive Deficit in Scopolamine-Induced Alzheimer's Disease-like Conditions in a Rat Model by Downregulating IL-1β, IL-6, TNF-α, and Oxidative Stress and Upregulating Brain-Derived Neurotrophic Factor and DCX Expressions

Dementia or the loss of cognitive functioning is one of the major health issues in elderly people. Alzheimer's disease (AD) is one of the common forms of dementia. Treatment chiefly involves the use of acetylcholinesterase (AChE) inhibitors in AD. However, oxidative stress has also been found to be involved in the proliferation of the disease. Magnoflorine is one of the active compounds of Coptidis Rhizoma and has high anti-oxidative properties. Active principle-loaded nanoparticles have shown increased efficiency for neurodegenerative diseases due to their ability to cross the blood-brain barrier more easily. An in vitro study involving magnoflorine-loaded chitosan collagen nanocapsules (MF-CCNc) has shown them to possess inhibitory effects against oxidative stress and to some extent on AChE as well. In the current study, both nootropic and anti-amnesic effects of magnoflorine and MF-CCNc on scopolamine-induced amnesia in rats were evaluated. The treatment was done intraperitoneally (i.p.) once daily for 17 consecutive days with MF-CCNc (0.25, 0.5, and 1 mg), magnoflorine (1 mg), and donepezil (1 mg). To induce amnesia, hence, cognitive deficit rats were induced with scopolamine (1 mg/kg) daily for the last 9 days. Novel object recognition (NOR) and elevated plus maze (EPM) behavioral analysis were done to assess memory functioning. Hippocampal tissues were extracted to study the effect on biochemicals (AChE, MDA, SOD, and CAT), pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α), and immunohistochemistry (brain-derived neurotrophic factor (BDNF) and DCX). MF-CCNc showed memory-enhancing effects in nootropic as well as chronic scopolamine-treated rats in NOR and an increase in inflexion ratio in EPM. MF-CCNc reduced the levels of AChE and MDA while increasing SOD and CAT levels in the hippocampus. MF-CCNc further lowered the levels of pro-inflammatory cytokines IL-1β, IL-6, and TNF-α. These nanocapsules further increased the expression of BDNF and DCX that are necessary for adult neurogenesis. From the research findings, it can be concluded that MF-CCNc has high anti-amnesic properties and could be a promising candidate for the treatment of AD.

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

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