Plasma phospholipids identify antecedent memory impairment in older adults

Gut microbiome and plasma lipidome analysis reveals a specific impact of Clostridioides difficile infection on intestinal bacterial communities and sterol metabolism

Clostridioides difficile infection (CDI) causes alterations in the intestinal microbiota, frequently associated with changes in the gut metabolism of bile acids and cholesterol. In addition to the impact on microbiome composition and given the metabolic changes occurring during CDI, our work focuses on the importance to know the effects at the local and systemic levels, both during the infection and its treatment, by paying particular attention to plasma lipid metabolism due to its relationship with CDI pathogenesis. Specific changes, characterized by a loss of microbial richness and diversity and related to a reduction in short-chain acid-producing bacteria and an increase in bile salt hydrolase-producing bacteria, were observed in the gut microbiota of CDI patients, especially in those suffering from recurrent CDI (RCDI). However, gut microbiota showed its ability to restore itself after treatment, resembling healthy individuals, in those patients treated by fecal microbiome transfer (FMT), in contrast with those treated with antibiotics, and displaying increased levels of Eubacterium coprostanoligenes, a cholesterol-reducing anaerobe. Interestingly, changes in plasma lipidome revealed a global depletion in circulating lipids in CDI, with the largest impact on cholesteryl esters. CDI patients also showed a specific and consistent decrease in the levels of lipid species containing linoleic acid-an essential fatty acid-which were only partially recovered after antibiotic treatment. Analysis of the plasma lipidome reflects CDI impact on the gut microbiota and its metabolism, evidencing changes in sterol and fatty acid metabolism that are possibly related to specific alterations observed in gut microbial communities of CDI patients.

IMPORTANCE

There is increasing evidence about the influence the changes in microbiota and its metabolism has on numerous diseases and infections such as Clostridioides difficile infection (CDI). The knowledge of these changes at local and systemic levels can help us manage this infection to avoid recurrences and apply the best therapies, such as fecal microbiota transfer (FMT). This study shows a better restoration of the gut in FMT-treated patients than in antibiotic-treated patients, resembling healthy controls and showing increased levels of cholesterol-reducing bacteria. Furthermore, it evidences the CDI impact on plasma lipidome. We observed in CDI patients a global depletion in circulating lipids, particularly cholesteryl esters, and a specific decrease in linoleic acid-containing lipids, an essential fatty acid. Our observations could impact CDI management because the lipid content was only partially recovered after treatment, suggesting that continued nutritional support, aiming to restore healthy lipid levels, could be essential for a full recovery.

Plasma lipidomic signatures of dementia with Lewy bodies revealed by machine learning, and compared to alzheimer's disease

BACKGROUND

Dementia with Lewy Bodies (DLB) is a complex neurodegenerative disorder that often overlaps clinically with Alzheimer's disease (AD), presenting challenges in accurate diagnosis and underscoring the need for novel biomarkers. Lipidomic emerges as a promising avenue for uncovering disease-specific metabolic alterations and potential biomarkers, particularly as the lipidomics landscape of DLB has not been previously explored. We aim to identify potential diagnostic biomarkers and elucidate the disease's pathophysiological mechanisms.

METHODS

This study conducted a lipidomic analysis of plasma samples from patients with DLB, AD, and healthy controls (HCs) at Xuanwu Hospital. Untargeted plasma lipidomic profiling was conducted via liquid chromatography coupled with mass spectrometry. Machine learning methods were employed to discern lipidomic signatures specific to DLB and to differentiate it from AD.

RESULTS

The study enrolled 159 participants, including 57 with AD, 48 with DLB, and 54 HCs. Significant differences in lipid profiles were observed between the DLB and HC groups, particularly in the classes of sphingolipids and phospholipids. A total of 55 differentially expressed lipid species were identified between DLB and HCs, and 17 between DLB and AD. Correlations were observed linking these lipidomic profiles to clinical parameters like Unified Parkinson's Disease Rating Scale III (UPDRS III) and cognitive scores. Machine learning models demonstrated to be highly effective in distinguishing DLB from both HCs and AD, achieving substantial accuracy through the utilization of specific lipidomic signatures. These include PC(15:0_18:2), PC(15:0_20:5), and SPH(d16:0) for differentiation between DLB and HCs; and a panel includes 13 lipid molecules: four PCs, two PEs, three SPHs, two Cers, and two Hex1Cers for distinguishing DLB from AD.

CONCLUSIONS

This study presents a novel and comprehensive lipidomic profile of DLB, distinguishing it from AD and HCs. Predominantly, sphingolipids (e.g., ceramides and SPHs) and phospholipids (e.g., PE and PC) were the most dysregulated lipids in relation to DLB patients. The lipidomics panels identified through machine learning may serve as effective plasma biomarkers for diagnosing DLB and differentiating it from AD dementia.

Decreased plasma nicotinamide and altered NAD+ metabolism in glial cells surrounding Aβ plaques in a mouse model of Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disease and a leading cause of senile dementia. Amyloid-β (Aβ) accumulation triggers chronic neuroinflammation, initiating AD pathogenesis. Recent clinical trials for anti-Aβ immunotherapy underscore that blood-based biomarkers have significant advantages and applicability over conventional diagnostics and are an unmet clinical need. To further advance ongoing clinical trials and identify novel therapeutic targets for AD, developing additional plasma biomarkers closely associated with pathogenic mechanisms downstream of Aβ accumulation is critically important. To identify plasma metabolites reflective of neuroinflammation caused by Aβ pathology, we performed untargeted metabolomic analyses of the plasma by capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS) and analyzed the potential roles of the identified metabolic changes in the brain neuroinflammatory response using the female App knock-in (AppNLGF) mouse model of Aβ amyloidosis. The CE-TOFMS analysis of plasma samples from female wild-type (WT) and AppNLGF mice revealed that plasma levels of nicotinamide, a nicotinamide adenine dinucleotide (NAD+) precursor, were decreased in AppNLGF mice, and altered metabolite profiles were enriched for nicotinate/nicotinamide metabolism. In AppNLGF mouse brains, NAD+ levels were unaltered, but mRNA levels of NAD+-synthesizing nicotinate phosphoribosyltransferase (Naprt) and NAD+-degrading Cd38 genes were increased. These enzymes were induced in reactive astrocytes and microglia surrounding Aβ plaques in the cortex and hippocampus of female AppNLGF mouse brains, suggesting neuroinflammation increases NAD+ metabolism. This study suggests plasma nicotinamide could be indicative of the neuroinflammatory response and that nicotinate and nicotinamide metabolism are potential therapeutic targets for AD, by targeting both neuroinflammation and neuroprotection.

Transcriptomic and metabolomic changes might predict frailty in SAMP8 mice

Frailty is a geriatric, multi-dimensional syndrome that reflects multisystem physiological change and is a transversal measure of reduced resilience to negative events. It is characterized by weakness, frequent falls, cognitive decline, increased hospitalization and dead and represents a risk factor for the development of Alzheimer's disease (AD). The fact that frailty is recognized as a reversible condition encourages the identification of earlier biomarkers to timely predict and prevent its occurrence. SAMP8 (Senescence-Accelerated Mouse Prone-8) mice represent the most appropriate preclinical model to this aim and were used in this study to carry transcriptional and metabolic analyses in the brain and plasma, respectively, upon a characterization at cognitive, motor, structural, and neuropathological level at 2.5, 6, and 9 months of age. At 2.5 months, SAMP8 mice started displaying memory deficits, muscle weakness, and motor impairment. Functional alterations were associated with a neurodevelopmental deficiency associated with reduced neuronal density and glial cell loss. Through transcriptomics, we identified specific genetic signatures well distinguishing SAMP8 mice at 6 months, whereas plasma metabolomics allowed to segregate SAMP8 mice from SAMR1 already at 2.5 months of age by detecting constitutively lower levels of acylcarnitines and lipids in SAMP8 at all ages investigated correlating with functional deficits and neuropathological signs. Our findings suggest that specific genetic alterations at central level, as well as metabolomic changes in plasma, might allow to early assess a frail condition leading to dementia development, which paves the foundation for future investigation in a clinical setting.

Unlocking choline's potential in Alzheimer's disease: A narrative review exploring the neuroprotective and neurotrophic role of phosphatidylcholine and assessing its impact on memory and learning

BACKGROUND AND AIMS

Growing evidence suggests nutritional intervention may influence the development and progression of Alzheimer's Disease (AD). Choline, an essential dietary nutrient plays a critical role in neurological development and brain function, however, its effects on AD in humans is unclear. The research aims to investigate mechanistic links between dietary choline intake and cognitive functioning, focusing on the role of phosphatidylcholine (PC) in neuroplasticity and its interaction with amyloid beta (Aβ) peptides in neuron membranes. Additionally, human evidence on the potential benefits of PC interventions on AD, cognition, and proposed mechanisms are evaluated.

METHODS

A reproducible systematic literature search was performed using a three-tranche strategy, consisting of a review, mechanism, and intervention search. Using PubMed as the main database, 1254 titles and abstracts were screened, 149 papers were read in full and 65 peer-reviewed papers were accepted, critically appraised, and analysed in a narrative review.

RESULTS

Predominantly preclinical evidence demonstrated that PC enhances neuroplasticity, a key biological substrate for cognition, by activating intracellular neuronal signalling pathways or through neuron membrane function. Molecular dynamic simulation methods provided a mechanistic understanding of the interconnection between neuronal PC content and the potential behaviour and trajectory of Aβ peptide aggregation. The results indicate that the neuronal membrane composition of PC is critical to inhibiting Aβ aggregation and neuronal damage, protecting the neuron from Aβ toxicity. This might provide a foundation for optimising cellular PC which may prove beneficial in the treatment or prevention of neurodegenerative disease. Altered PC metabolism in AD was evidenced in observational studies; however, whether this relationship represents a cause or consequence of AD remains to be determined. Human intervention studies did not produce conclusive evidence supporting its effectiveness in enhancing cognitive function. This lack of consistency primarily stems from methodological constraints within the conducted studies. Human observational research provided the most compelling evidence linking a higher dietary PC intake to a reduced risk of dementia and significant improvements in cognitive testing.

CONCLUSION

Despite the lack of randomised control trials (RCTs) assessing the efficacy of lecithin/PC to improve cognition in AD patients, there exists promising evidence supporting its neuroprotective and neurotrophic role. This review establishes an evidence-based framework through chains of mechanistic evidence, that may provide potential strategies for enhanced neuroprotection and reduced neurodegeneration caused by AD. Considering the escalating global burden of AD and the current shortcomings in effective treatments, this review together with the limitations and gaps identified in the existing research presents valuable insights that emphasise the urgency of more comprehensive research into the relationship between PC and AD.

Serum lipidome associates with neuroimaging features in patients with traumatic brain injury

Acute traumatic brain injury (TBI) is associated with substantial abnormalities in lipid biology, including changes in the structural lipids that are present in the myelin in the brain. We investigated the relationship between traumatic microstructural changes in white matter from magnetic resonance imaging (MRI) and quantitative lipidomic changes from blood serum. The study cohort included 103 patients from the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study. Diffusion tensor fitting generated fractional anisotropy (FA) and mean diffusivity (MD) maps for the MRI scans while ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry was applied to analyze the lipidome. Increasing severity of TBI was associated with higher MD and lower FA values, which scaled with different lipidomic signatures. There appears to be consistent patterns of lipid changes associating with the specific microstructure changes in the CNS white matter, but also regional specificity, suggesting that blood-based lipidomics may provide an insight into the underlying pathophysiology of TBI.

Automated preparation of plasma lipids, metabolites, and proteins for LC/MS-based analysis of a high-fat diet in mice

Blood plasma is one of the most commonly analyzed and easily accessible biological samples. Here, we describe an automated liquid-liquid extraction platform that generates accurate, precise, and reproducible samples for metabolomic, lipidomic, and proteomic analyses from a single aliquot of plasma while minimizing hands-on time and avoiding contamination from plasticware. We applied mass spectrometry to examine the metabolome, lipidome, and proteome of 90 plasma samples to determine the effects of age, time of day, and a high-fat diet in mice. From 25 μl of mouse plasma, we identified 907 lipid species from 16 different lipid classes and subclasses, 233 polar metabolites, and 344 proteins. We found that the high-fat diet induced only mild changes in the polar metabolome, upregulated apolipoproteins, and induced substantial shifts in the lipidome, including a significant increase in arachidonic acid and a decrease in eicosapentaenoic acid content across all lipid classes.

Mass Spectrometry Imaging Reveals Region-Specific Lipid Alterations in the Mouse Brain in Response to Efavirenz Treatment

Efavirenz (EFV) is a commonly used drug to treat human immunodeficiency virus infection and is known to exert adverse effects on the brain. Although it is known that EFV is associated with abnormal plasma lipid levels, the changes in the spatial localization of individual lipid molecules in brain tissue following EFV treatment are yet to be explored. In this study, we employed a matrix-assisted laser desorption/ionization mass spectrometry imaging approach to determine region-specific lipid alterations in mouse brains following EFV treatment. We detected unique spatial localization patterns of phosphatidylcholine (PC), sphingomyelin (SM), ceramide phosphoinositol (PI-Cer), and hexosylceramide (HexCer) molecules in the mouse brain. Interestingly, PC(32:0), PC(38:5), and SM(36:1;O2) showed high abundance in the hippocampus region, whereas PI-Cer(38:8) exhibited low abundance in the hippocampus region of the EFV-treated mouse brains. Additionally, we observed low abundance of PC(38:6), PC(40:6), and PI-Cer(40:3) in the thalamus region of the EFV-treated mouse brains. Furthermore, SM(40:1;O2), SM(42:2;O2), SM(42:1;O2), SM(43:2;O2), and SM(43:1;O2) exhibited their accumulation in the corpus callosum region of the EFV-treated mouse brains as compared to controls. However, HexCer(42:1;O3) exhibited depletion in the corpus callosum region in response to EFV treatment. To characterize the expression patterns of proteins, including lipid metabolizing enzymes, in response to EFV treatment, mass spectrometry-based proteomics was utilized. From these, the expression levels of 12 brain proteins were found to be significantly decreased following EFV treatment. Taken together, these multiomics data provide important insights into the effects of EFV on brain lipid metabolism.

A novel mechanism of major ginsenosides from Panax ginseng against multiple organ aging in middle-aged mice: Phosphatidylcholine-myo-inositol metabolism based on metabolomic analysis

Aging is a complex, degenerative process associated with various metabolic abnormalities. Ginsenosides (GS) is the main active components of Panax ginseng, which has anti-aging effects and improves metabolism. However, the anti-aging effect and the mechanism of GS in middle-aged mice has not been elucidated. In this study, GS after 3-month treatment significantly improved the grip strength, fatigue resistance, cognitive indices, and cardiac function of 15-month-old mice. Meanwhile, GS treatment reduced the fat content and obviously inhibited histone H2AX phosphorylation at Ser 139 (γ-H2AX), a marker of DNA damage in major organs, especially in the heart and liver. Further, the correlation analysis of serum metabolomics combined with aging phenotype suggested that myo-inositol (MI) upregulated by GS was positively correlated with left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS), the main indicators of cardiac function. More importantly, liver tissue metabolomic analysis showed that GS increased MI content by promoting the synthesis pathway from phosphatidylcholine (PC) to MI for the inhibition of liver aging. Finally, we proved that MI reduced the percentage of senescence-associated β-galactosidase staining, γ-H2AX immunofluorescence staining, p21 expression, and the production of reactive oxygen species in H2O2-induced cardiomyocytes. These results suggest that GS can enhance multiple organ functions, especially cardiac function for promoting the healthspan of aging mice, which is mediated by the conversion of PC to MI in the liver and the increase of MI level in the serum. Our study might provide new insights into the potential mechanisms of ginsenosides for prolonging the healthspan of natural aging mice.

Association of Egg Intake With Alzheimer's Dementia Risk in Older Adults: The Rush Memory and Aging Project

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disorder with increasing prevalence due to population aging. Eggs provide many nutrients important for brain health, including choline, omega-3 fatty acids, and lutein. Emerging evidence suggests that frequent egg consumption may improve cognitive performance on verbal tests, but whether consumption influences the risk of Alzheimer's dementia and AD is unknown.

OBJECTIVES

To examine the association of egg consumption with Alzheimer's dementia risk among the Rush Memory and Aging Project cohort.

METHODS

Dietary assessment was collected using a modified Harvard semiquantitative food frequency questionnaire. Participants' first food frequency questionnaire was used as the baseline measure of egg consumption. Multivariable adjusted Cox proportional hazards regression models were used to investigate the associations of baseline egg consumption amount with Alzheimer's dementia risk, adjusting for potential confounding factors. Subgroup analyses using Cox and logistic regression models were performed to investigate the associations with AD pathology in the brain. Mediation analysis was conducted to examine the mediation effect of dietary choline in the relationship between egg intake and incident Alzheimer's dementia.

RESULTS

This study included 1024 older adults {mean [±standard deviation (SD)] age = 81.38 ± 7.20 y}. Over a mean (±SD) follow-up of 6.7 ± 4.8 y, 280 participants (27.3%) were clinically diagnosed with Alzheimer's dementia. Weekly consumption of >1 egg/wk (hazard ratio [HR]: 0.53; 95% confidence interval [CI]: 0.34, 0.83) and ≥2 eggs/wk (HR: 0.53; 95% CI: 0.35, 0.81) was associated with a decreased risk of Alzheimer's dementia. Subgroup analysis of brain autopsies from 578 deceased participants showed that intakes of >1 egg/wk (HR: 0.51; 95% CI: 0.35, 0.76) and ≥2 eggs/wk (HR: 0.62; 95% CI: 0.44, 0.90) were associated with a lower risk of AD pathology in the brain. Mediation analysis showed that 39% of the total effect of egg intake on incident Alzheimer's dementia was mediated through dietary choline.

CONCLUSIONS

These findings suggest that frequent egg consumption is associated with a lower risk of Alzheimer's dementia and AD pathology, and the association with Alzheimer's dementia is partially mediated through dietary choline.

Mass spectrometry imaging highlights dynamic patterns of lipid co-expression with Aβ plaques in mouse and human brains

Lipids play crucial roles in the susceptibility and brain cellular responses to Alzheimer's disease (AD) and are increasingly considered potential soluble biomarkers in cerebrospinal fluid (CSF) and plasma. To delineate the pathological correlations of distinct lipid species, we conducted a comprehensive characterization of both spatially localized and global differences in brain lipid composition in AppNL-G-F mice with spatial and bulk mass spectrometry lipidomic profiling, using human amyloid-expressing (h-Aβ) and WT mouse brains controls. We observed age-dependent increases in lysophospholipids, bis(monoacylglycerol) phosphates, and phosphatidylglycerols around Aβ plaques in AppNL-G-F mice. Immunohistology-based co-localization identified associations between focal pro-inflammatory lipids, glial activation, and autophagic flux disruption. Likewise, in human donors with varying Braak stages, similar studies of cortical sections revealed co-expression of lysophospholipids and ceramides around Aβ plaques in AD (Braak stage V/VI) but not in earlier Braak stage controls. Our findings in mice provide evidence of temporally and spatially heterogeneous differences in lipid composition as local and global Aβ-related pathologies evolve. Observing similar lipidomic changes associated with pathological Aβ plaques in human AD tissue provides a foundation for understanding differences in CSF lipids with reported clinical stage or disease severity.

Monoclonal antibodies and aptamers: The future therapeutics for Alzheimer's disease

Alzheimer's disease (AD) is considered the most common and prevalent form of dementia of adult-onset with characteristic progressive impairment in cognition and memory. The cure for AD has not been found yet and the treatments available until recently were only symptomatic. Regardless of multidisciplinary approaches and efforts made by pharmaceutical companies, it was only in the past two years that new drugs were approved for the treatment of the disease. Amyloid beta (Aβ) immunotherapy is at the core of this therapy, which is one of the most innovative approaches looking to change the course of AD. This technology is based on synthetic peptides or monoclonal antibodies (mAb) to reduce Aβ levels in the brain and slow down the advance of neurodegeneration. Hence, this article reviews the state of the art about AD neuropathogenesis, the traditional pharmacologic treatment, as well as the modern active and passive immunization describing approved drugs, and drug prototypes currently under investigation in different clinical trials. In addition, future perspectives on immunotherapeutic strategies for AD and the rise of the aptamer technology as a non-immunogenic alternative to curb the disease progression are discussed.

Sex-specific associations between AD genotype and the microbiome of human amyloid beta knock-in (hAβ-KI) mice

INTRODUCTION

Emerging evidence links changes in the gut microbiome to late-onset Alzheimer's disease (LOAD), necessitating examination of AD mouse models with consideration of the microbiome.

METHODS

We used shotgun metagenomics and untargeted metabolomics to study the human amyloid beta knock-in (hAβ-KI) murine model for LOAD compared to both wild-type (WT) mice and a model for early-onset AD (3xTg-AD).

RESULTS

Eighteen-month female (but not male) hAβ-KI microbiomes were distinct from WT microbiomes, with AD genotype accounting for 18% of the variance by permutational multivariate analysis of variance (PERMANOVA). Metabolomic diversity differences were observed in females, however no individual metabolites were differentially abundant. hAβ-KI mice microbiomes were distinguishable from 3xTg-AD animals (81% accuracy by random forest modeling), with separation primarily driven by Romboutsia ilealis and Turicibacter species. Microbiomes were highly cage specific, with cage assignment accounting for more than 40% of the PERMANOVA variance between the groups.

DISCUSSION

These findings highlight a sex-dependent variation in the microbiomes of hAβ-KI mice and underscore the importance of considering the microbiome when designing studies that use murine models for AD.

HIGHLIGHTS

Microbial diversity and the abundance of several species differed in human amyloid beta knock-in (hAβ-KI) females but not males. Correlations to Alzheimer's disease (AD) genotype were stronger for the microbiome than the metabolome. Microbiomes from hAβ-KI mice were distinct from 3xTg-AD mice. Cage effects accounted for most of the variance in the microbiome and metabolome.

Identification of brain-enriched proteins in CSF as biomarkers of relapsing remitting multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a clinically and biologically heterogenous disease with currently unpredictable progression and relapse. After the development and success of neurofilament as a cerebrospinal fluid (CSF) biomarker, there is reinvigorated interest in identifying other markers of or contributors to disease. The objective of this study is to probe the predictive potential of a panel of brain-enriched proteins on MS disease progression and subtype.

METHODS

This study includes 40 individuals with MS and 14 headache controls. The MS cohort consists of 20 relapsing remitting (RR) and 20 primary progressive (PP) patients. The CSF of all individuals was analyzed for 63 brain enriched proteins using a method of liquid-chromatography tandem mass spectrometry. Wilcoxon rank sum test, Kruskal-Wallis one-way ANOVA, logistic regression, and Pearson correlation were used to refine the list of candidates by comparing relative protein concentrations as well as relation to known imaging and molecular biomarkers.

RESULTS

We report 30 proteins with some relevance to disease, clinical subtype, or severity. Strikingly, we observed widespread protein depletion in the disease CSF as compared to control. We identified numerous markers of relapsing disease, including KLK6 (kallikrein 6, OR = 0.367, p < 0.05), which may be driven by active disease as defined by MRI enhancing lesions. Other oligodendrocyte-enriched proteins also appeared at reduced levels in relapsing disease, namely CNDP1 (carnosine dipeptidase 1), LINGO1 (leucine rich repeat and Immunoglobin-like domain-containing protein 1), MAG (myelin associated glycoprotein), and MOG (myelin oligodendrocyte glycoprotein). Finally, we identified three proteins-CNDP1, APLP1 (amyloid beta precursor like protein 1), and OLFM1 (olfactomedin 1)-that were statistically different in relapsing vs. progressive disease raising the potential for use as an early biomarker to discriminate clinical subtype.

CONCLUSIONS

We illustrate the utility of targeted mass spectrometry in generating potential targets for future biomarker studies and highlight reductions in brain-enriched proteins as markers of the relapsing remitting disease stage.

Exploring the significance of lipids in Alzheimer's disease and the potential of extracellular vesicles

Lipids play a significant role in maintaining central nervous system (CNS) structure and function, and the dysregulation of lipid metabolism is known to occur in many neurological disorders, including Alzheimer's disease. Here we review what is currently known about lipid dyshomeostasis in Alzheimer's disease. We propose that small extracellular vesicle (sEV) lipids may provide insight into the pathophysiology and progression of Alzheimer's disease. This stems from the recognition that sEV likely contributes to disease pathogenesis, but also an understanding that sEV can serve as a source of potential biomarkers. While the protein and RNA content of sEV in the CNS diseases have been studied extensively, our understanding of the lipidome of sEV in the CNS is still in its infancy.

Pharmacokinetics of soy-derived lysophosphatidylcholine compared with that of glycerophosphocholine: a randomized controlled trial

Lysophosphatidylcholine (LPC) is present in various foods and contains a choline moiety such as in glycerophosphocholine (GPC). However, the potential of LPC as a choline source remains unclear. This study investigated the single-dose pharmacokinetics of 480 mg soy-derived LPC in 12 healthy men compared with that of either soy oil with the same lipid amount (placebo) or GPC with the same choline amount. Both LPC and GPC supplementation increased plasma choline, serum phospholipid, and serum triglyceride concentrations, but neither of them significantly elevated plasma trimethylamine N-oxide concentration. In addition, although the intake of LPC slightly increased plasma LPC16:0, LPC18:2, and total LPC concentrations, their concentrations remained within physiological ranges. No adverse events were attributed to the LPC supplementation. To the best of our knowledge, this study is the first to compare LPC and GPC pharmacokinetics in humans and shows that LPC can be a source of choline.

Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults

Alzheimer's disease is strongly linked to metabolic abnormalities. We aimed to distinguish amyloid-positive people who progressed to cognitive decline from those who remained cognitively intact. We performed untargeted metabolomics of blood samples from amyloid-positive individuals, before any sign of cognitive decline, to distinguish individuals who progressed to cognitive decline from those who remained cognitively intact. A plasma-derived metabolite signature was developed from Supercritical Fluid chromatography coupled with high-resolution mass spectrometry (SFC-HRMS) and nuclear magnetic resonance (NMR) metabolomics. The 2 metabolomics data sets were analyzed by Data Integration Analysis for Biomarker discovery using Latent approaches for Omics studies (DIABLO), to identify a minimum set of metabolites that could describe cognitive decline status. NMR or SFC-HRMS data alone cannot predict cognitive decline. However, among the 320 metabolites identified, a statistical method that integrated the 2 data sets enabled the identification of a minimal signature of 9 metabolites (3-hydroxybutyrate, citrate, succinate, acetone, methionine, glucose, serine, sphingomyelin d18:1/C26:0 and triglyceride C48:3) with a statistically significant ability to predict cognitive decline more than 3 years before decline. This metabolic fingerprint obtained during this exploratory study may help to predict amyloid-positive individuals who will develop cognitive decline. Due to the high prevalence of brain amyloid-positivity in older adults, identifying adults who will have cognitive decline will enable the development of personalized and early interventions.

Risk factors and metabolomics of mild cognitive impairment in type 2 diabetes mellitus

Objective: This study aimed to explore the risk factors, metabolic characteristics, and potential biomarkers of mild cognitive impairment in type 2 diabetes mellitus (T2DM-MCI) and to provide potential evidence for the diagnosis, prevention, and treatment of mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 103 patients with T2DM were recruited from the Endocrinology Department of The Second Affiliated Hospital of Dalian Medical University for inclusion in the study. The Montreal Cognitive Assessment (MoCA) was utilized to evaluate the cognitive functioning of all patients. Among them, 50 patients were categorized into the T2DM-MCI group (MoCA score < 26 points), while 53 subjects were classified into the T2DM without cognitive impairment (T2DM-NCI) group (MoCA score ≥ 26 points). Serum samples were collected from the subjects, and metabolomics profiling data were generated by Ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS). These groups were analyzed to investigate the differences in expression of small molecule metabolites, metabolic pathways, and potential specific biomarkers. Results: Comparison between the T2DM-MCI group and T2DM-NCI group revealed significant differences in years of education, history of insulin application, insulin resistance index, insulin-like growth factor-binding protein-3 (IGFBP-3), and creatinine levels. Further binary logistic regression analysis of the variables indicated that low educational level and low serum IGFBP-3 were independent risk factor for T2DM-MCI. Metabolomics analysis revealed that differential expression of 10 metabolites between the T2DM-MCI group and T2DM-NCI group (p < 0.05 and FDR<0.05, VIP>1.5). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis revealed that fatty acid degradation was the most significant pathway. Receiver operating characteristic (ROC) analysis shows that lysophosphatidylcholine (LPC) 18:0 exhibited greater diagnostic efficiency. Conclusion: This study revealed that a shorter duration of education and lower serum IGFBP-3 levels are independent risk factors for T2DM-MCI. Serum metabolites were found to be altered in both T2DM-MCI and T2DM-NCI groups. T2DM patients with or without MCI can be distinguished by LPC 18:0. Abnormal lipid metabolism plays a significant role in the development of MCI in T2DM patients.

Investigating a Novel Neurodegenerative Disease Toxic Mechanism Involving Lipid Binding Specificity of Amyloid Oligomers

Exploring the mechanisms underlying the toxicity of amyloid oligomers (AOs) presents a significant opportunity for discovering cures and developing treatments for neurodegenerative diseases. Recently, using a combination of ion mobility spectrometry-mass spectrometry (IMS-MS) and X-ray crystallography (XRC), we showed that the peptide KVKVLWDVIEV, which is the G95W mutant of αB-Crystallin (90-100) and abbreviated as G6W, self-assembles up to a dodecamer that structurally resembles lipid transport proteins. The glycine to tryptophan mutation promotes not only larger oligomers and enhanced cytotoxicity in brain slices than the wild type but also a narrow hydrophobic cavity suitable for fatty acid or phospholipid binding. Here, we determine the plausibility of a novel cytotoxic mechanism where the G6W's structural motif could perturb lipid homeostasis by determining its lipid binding selectivity and specificity. We show that the G6W oligomers have a strong affinity toward unsaturated phospholipids with a preference toward phospholipids containing 16-C alkyl chains. Molecular dynamics simulations demonstrate how an unsaturated, 16-C phospholipid fits tightly inside and outside G6W's hydrophobic cavity. This binding is exclusive to the G6W peptide, as other amyloid oligomers with different atomic structures, including its wildtype αB-Crystallin (90-100) and several superoxide dismutase 1 (SOD1) peptides that are known to self-assemble into amyloid oligomers (SOD1P28K and SOD1WG-GW), do not experience the same strong binding affinity. While the existing chaperone-lipid hypothesis on amyloid toxicity suggests amyloid-lipid complexes perforate cell membranes, our work provides a new outlook, indicating that soluble amyloid oligomers disrupt lipid homeostasis via selective protein-ligand interactions. The toxic mechanisms may arise from the formation of unique amyloid oligomer structures assisted by lipid ligands or impaired lipid transports.

Glucometabolic-Related Genes as Diagnostic Biomarkers and Therapeutic Targets for Alzheimer's Disease and Type 2 Diabetes Mellitus: A Bioinformatics Analysis

Background

Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are two widespread chronic disorders characterized by shared risk factors and molecular pathways. Glucose metabolism, pivotal for cellular homeostasis and energy supply, plays a critical role in these diseases. Its disturbance has been linked to the pathogenesis of both AD and T2DM. However, a comprehensive investigation into the specific roles of glucometabolic genes in the onset and progression of AD and T2DM has yet to be conducted.

Methods

By analyzing microarray datasets from the Gene Expression Omnibus (GEO) repository, we identified differentially expressed glucometabolic genes (DEGs) in AD and T2DM cohorts. A range of bioinformatics tools were employed for functional annotation, pathway enrichment, protein interaction network construction, module analysis, ROC curve assessment, correlation matrix construction, gene set enrichment analysis, and gene-drug interaction mapping of these DEGs. Key genes were further validated using quantitative real-time polymerase chain reaction (qRT-PCR) in AD and T2DM murine models.

Results

Our investigation identified 41 glucometabolic-related DEGs, with six prominent genes (G6PD, PKM, ENO3, PFKL, PGD, and TALDO1) being common in both AD and T2DM cohorts. These genes play crucial roles in metabolic pathways including glycolysis, pentose phosphate pathway, and amino sugar metabolism. Their diagnostic potential was highlighted by area under curve (AUC) values exceeding 0.6 for AD and 0.8 for T2DM. Further analysis explored the interactions, pathway enrichments, regulatory mechanisms, and potential drug interactions of these key genes. In the AD murine model, quantitative real-time polymerase chain reaction (qRT-PCR) analysis revealed significant upregulation of G6pd, Eno3, and Taldo1. Similarly, in the T2DM murine model, elevated expression levels of G6pd, Pfkl, Eno3, and Pgd were observed.

Conclusion

Our rigorous research sheds light on the molecular interconnections between AD and T2DM from a glucometabolic perspective, revealing new opportunities for pharmacological innovation and therapeutic approaches. This study appears to be the first to extensively investigate glucometabolic-associated DEGs and key genes in both AD and T2DM, utilizing multiple datasets. These insights are set to enhance our understanding of the complex pathophysiology underlying these widespread chronic diseases.

Lipid profile in breast cancer: From signaling pathways to treatment strategies

Breast cancer is the most prevalent cancer in women. Metabolic abnormalities, particularly increased lipid synthesis and uptake, impact the onset and progression of the disease. However, the influence of lipid metabolism in breast cancer varies according to the disease stage and patient's hormone status. In postmenopausal patients, obesity is associated with a higher risk and poor prognosis of luminal tumors, while in premenopausal individuals, it is correlated to BRCA mutated tumors. In fact, the tumor's lipid profile may be used to distinguish between HER2+, luminal and BRCA-mutated tumors. Moreover, drug resistance was associated with increased fatty acid synthesis and alterations in membrane composition, impacting its fluidity and spatial subdomains such as lipid rafts. Here, we discuss the subtype-specific lipid metabolism alterations found in breast cancer and the potentiality of its modulation in a clinical setting.

Comprehensive analysis of phospholipid in milk and their biological roles as nutrients and biomarkers

Phospholipids (PL) have garnered significant attention due to their physiological activities. Milk and other dairy products are important dietary sources for humans and have been extensively used to analyze the presence of PL by various analytical techniques. In this paper, the analysis techniques of PL were reviewed with the eight trigrams of phospholipidomics and a comprehensive fingerprint of 1295 PLs covering 8 subclasses in milk and other dairy products, especially. Technology is the primary productive force. Based on phospholipidomics technology, we further review the relationship between the composition of PL and factors that may be involved in processing and experimental operation, and emphasized the significance of the biological role played by PL in dietary supplements and biomarkers (production, processing and clinical research), and providing the future research directions.

Large-Scale Population-Based Studies of Blood Metabolome and Brain Health

Metabolomics technologies enable the quantification of multiple metabolomic measures simultaneously, which provides novel insights into molecular aspects of human health and disease. In large-scale, population-based studies, blood is often the preferred biospecimen. Circulating metabolome may relate to brain health either by affecting or reflecting brain metabolism. Peripheral metabolites may act at or cross the blood-brain barrier and, subsequently, influence brain metabolism, or they may reflect brain metabolism if similar pathways are engaged. Peripheral metabolites may also include those penetrating the circulation from the brain, indicating, for example, brain damage. Most brain health-related metabolomics studies have been conducted in the context of neurodegenerative disorders and cognition, but some studies have also focused on neuroimaging markers of these disorders. Moreover, several metabolomics studies of neurodevelopmental disorders have been performed. Here, we provide a brief background on the types of blood metabolites commonly assessed, and we review the literature describing the relationships between human blood metabolome (n > 50 metabolites) and brain health reported in large-scale studies (n > 500 individuals).

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

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

Postpartum Oxytocin Treatment via the Mother Reprograms Long-Term Behavioral Disorders Induced by Early Life Stress on the Plasma and Brain Metabolome in the Rat

The rat model of perinatal stress (PRS), in which exposure of pregnant dams to restraint stress reduces maternal behavior, is characterized by a metabolic profile that is reminiscent of the "metabolic syndrome". We aimed to identify plasma metabolomic signatures linked to long-term programming induced by PRS in aged male rats. This study was conducted in the plasma and frontal cortex. We also investigated the reversal effect of postpartum carbetocin (Cbt) on these signatures, along with its impact on deficits in cognitive, social, and exploratory behavior. We found that PRS induced long-lasting changes in biomarkers of secondary bile acid metabolism in the plasma and glutathione metabolism in the frontal cortex. Cbt treatment demonstrated disease-dependent effects by reversing the metabolite alterations. The metabolomic signatures of PRS were associated with long-term cognitive and emotional alterations alongside endocrinological disturbances. Our findings represent the first evidence of how early life stress may alter the metabolomic profile in aged individuals, thereby increasing vulnerability to CNS disorders. This raises the intriguing prospect that the pharmacological activation of oxytocin receptors soon after delivery through the mother may rectify these alterations.

Neuropsychiatric symptoms and ApoE genotype in older adults without dementia: a cross-sectional study

BACKGROUND

The ApoE genotype and neuropsychiatric symptoms (NPS) are known risk factors for cognitive decline in older adults. However, the interaction between these variables is still unclear. The aim of this study was to determine the association between the presence of the ApoE ε4 allele and the occurrence of NPS in older adults without dementia.

METHODS

In this cross-sectional investigation we determined the apolipoprotein E (ApoE) genotype of 74 older adults who were either cognitively normal (20.3% / Clinician Dementia Rating Scale (CDR): 0) or had mild cognitive impairment (MCI: 79.7% / CDR: 0.5). We used a comprehensive cognitive assessment protocol, and NPS were estimated by the Neuropsychiatric Inventory-Clinician Rating Scale (NPI-C), Mild Behavioural Impairment-Checklist (MBI-C), Hamilton Rating Scale for Depression (HAM-D), and Apathy Inventory.

RESULTS

ApoE ε4 carriers had higher MBI-C total scores than ApoE ε4 noncarriers. Correlations between NPS and ApoE genotype were observed for two NPI-C domains, although in opposite directions: the ApoE ε4 allele was associated with a 1.8 unit decrease in the estimated aberrant motor disturbance score and with a 1.3 unit increase in the estimated appetite/eating disorders score. All fitted models were significant, except for the one fitted for the domain delusions from the NPI-C. Among individuals with amnestic MCI, ε4 carriers presented higher depression score (HAM-D) than noncarriers; in turn, ε4 noncarriers exhibited higher aggression score (NPI-C) than ε4 carriers.

CONCLUSIONS

Our analyses showed associations between NPS and the presence of the ApoE ε4 allele in two NPI-C domains, despite the sample size. Furthermore, compared to noncarriers, the presence of the ApoE ε4 correlated positively with appetite/eating disorders and negatively with aberrant motor disturbance domain. Examination of the amnestic MCI group displayed significant, although weak, associations. Therefore, ε4 carriers exhibited higher depression scores according to the HAM-D scale compared to ε4 noncarriers. Conversely, ε4 noncarriers had higher scores in the aggression domain of the NPI-C than ε4 carriers.

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

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

Behavioral, metabolic, and lipidomic characterization of the 5xFADxTg30 mouse model of Alzheimer's disease

Alzheimer's disease (AD) is associated with both extracellular amyloid-β (Aβ) plaques and intracellular tau-containing neurofibrillary tangles (NFT). We characterized the behavioral, metabolic and lipidomic phenotype of the 5xFADxTg30 mouse model which contains overexpression of both Aβ and tau. Our results independently reproduce several phenotypic traits described previously for this model, while providing additional characterization. This model develops many aspects associated with AD including frailty, decreased survival, initiation of aspects of cognitive decline and alterations to specific lipid classes and molecular lipid species in the plasma and brain. Notably, some sex-specific differences exist in this model and motor impairment with aging in this model does compromise the utility of the model for some movement-based behavioral assessments of cognitive function. These findings provide a reference for individuals interested in using this model to understand the pathology associated with elevated Aβ and tau or for testing potential therapeutics for the treatment of AD.

Unraveling lipid and inflammation interplay in cancer, aging and infection for novel theranostic approaches

The synergistic relationships between Cancer, Aging, and Infection, here referred to as the CAIn Triangle, are significant determinants in numerous health maladies and mortality rates. The CAIn-related pathologies exhibit close correlations with each other and share two common underlying factors: persistent inflammation and anomalous lipid concentration profiles in the membranes of affected cells. This study provides a comprehensive evaluation of the most pertinent interconnections within the CAIn Triangle, in addition to examining the relationship between chronic inflammation and specific lipidic compositions in cellular membranes. To tackle the CAIn-associated diseases, a suite of complementary strategies aimed at diagnosis, prevention, and treatment is proffered. Our holistic approach is expected to augment the understanding of the fundamental mechanisms underlying these diseases and highlight the potential of shared features to facilitate the development of novel theranostic strategies.

Role of the Gut Bacteria-Derived Metabolite Phenylacetylglutamine in Health and Diseases

Over the past few decades, it has been well established that gut microbiota-derived metabolites can disrupt gut function, thus resulting in an array of diseases. Notably, phenylacetylglutamine (PAGln), a bacterial derived metabolite, has recently gained attention due to its role in the initiation and progression of cardiovascular and cerebrovascular diseases. This meta-organismal metabolite PAGln is a byproduct of amino acid acetylation of its precursor phenylacetic acid (PAA) from a range of dietary sources like egg, meat, dairy products, etc. The microbiota-dependent metabolism of phenylalanine produces PAA, which is a crucial intermediate that is catalyzed by diverse microbial catalytic pathways. PAA conjugates with glutamine and glycine in the liver and kidney to predominantly form phenylacetylglutamine in humans and phenylacetylglycine in rodents. PAGln is associated with thrombosis as it enhances platelet activation mediated through the GPCRs receptors α2A, α2B, and β2 ADRs, thereby aggravating the pathological conditions. Clinical evidence suggests that elevated levels of PAGln are associated with pathology of cardiovascular, cerebrovascular, and neurological diseases. This Review further consolidates the microbial/biochemical synthesis of PAGln and discusses its role in the above pathophysiologies.

Plasma metabolic profiles predict future dementia and dementia subtypes: a prospective analysis of 274,160 participants

BACKGROUND

Blood-based biomarkers for dementia are gaining attention due to their non-invasive nature and feasibility in regular healthcare settings. Here, we explored the associations between 249 metabolites with all-cause dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VaD) and assessed their predictive potential.

METHODS

This study included 274,160 participants from the UK Biobank. Cox proportional hazard models were employed to investigate longitudinal associations between metabolites and dementia. The importance of these metabolites was quantified using machine learning algorithms, and a metabolic risk score (MetRS) was subsequently developed for each dementia type. We further investigated how MetRS stratified the risk of dementia onset and assessed its predictive performance, both alone and in combination with demographic and cognitive predictors.

RESULTS

During a median follow-up of 14.01 years, 5274 participants developed dementia. Of the 249 metabolites examined, 143 were significantly associated with incident ACD, 130 with AD, and 140 with VaD. Among metabolites significantly associated with dementia, lipoprotein lipid concentrations, linoleic acid, sphingomyelin, glucose, and branched-chain amino acids ranked top in importance. Individuals within the top tertile of MetRS faced a significantly greater risk of developing dementia than those in the lowest tertile. When MetRS was combined with demographic and cognitive predictors, the model yielded the area under the receiver operating characteristic curve (AUC) values of 0.857 for ACD, 0.861 for AD, and 0.873 for VaD.

CONCLUSIONS

We conducted the largest metabolome investigation of dementia to date, for the first time revealed the metabolite importance ranking, and highlighted the contribution of plasma metabolites for dementia prediction.

Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review

Translational bioinformatics and data science play a crucial role in biomarker discovery as it enables translational research and helps to bridge the gap between the bench research and the bedside clinical applications. Thanks to newer and faster molecular profiling technologies and reducing costs, there are many opportunities for researchers to explore the molecular and physiological mechanisms of diseases. Biomarker discovery enables researchers to better characterize patients, enables early detection and intervention/prevention and predicts treatment responses. Due to increasing prevalence and rising treatment costs, mental health (MH) disorders have become an important venue for biomarker discovery with the goal of improved patient diagnostics, treatment and care. Exploration of underlying biological mechanisms is the key to the understanding of pathogenesis and pathophysiology of MH disorders. In an effort to better understand the underlying mechanisms of MH disorders, we reviewed the major accomplishments in the MH space from a bioinformatics and data science perspective, summarized existing knowledge derived from molecular and cellular data and described challenges and areas of opportunities in this space.

Brain areas lipidomics in female transgenic mouse model of Alzheimer's disease

Lipids are the major component of the brain with important structural and functional properties. Lipid disruption could play a relevant role in Alzheimer's disease (AD). Some brain lipidomic studies showed significant differences compared to controls, but few studies have focused on different brain areas related to AD. Furthermore, AD is more prevalent in females, but there is a lack of studies focusing on this sex. This work aims to perform a lipidomic study in selected brain areas (cerebellum, amygdala, hippocampus, entire cortex) from wild-type (WT, n = 10) and APPswe/PS1dE9 transgenic (TG, n = 10) female mice of 5 months of age, as a model of early AD, to identify alterations in lipid composition. A lipidomic mass spectrometry-based method was optimized and applied to brain tissue. As result, some lipids showed statistically significant differences between mice groups in cerebellum (n = 68), amygdala (n = 49), hippocampus (n = 48), and the cortex (n = 22). In addition, some lipids (n = 15) from the glycerolipid, phospholipid, and sphingolipid families were statistically significant in several brain areas simultaneously between WT and TG. A selection of lipid variables was made to develop a multivariate approach to assess their discriminant potential, showing high diagnostic indexes, especially in cerebellum and amygdala (sensitivity 70-100%, sensibility 80-100%).

What's New in Dementia Risk Prediction Modelling? An Updated Systematic Review

Introduction

Identifying individuals at high risk of dementia is critical to optimized clinical care, formulating effective preventative strategies, and determining eligibility for clinical trials. Since our previous systematic reviews in 2010 and 2015, there has been a surge in dementia risk prediction modelling. The aim of this study was to update our previous reviews to explore, and critically review, new developments in dementia risk modelling.

Methods

MEDLINE, Embase, Scopus, and Web of Science were searched from March 2014 to June 2022. Studies were included if they were population- or community-based cohorts (including electronic health record data), had developed a model for predicting late-life incident dementia, and included model performance indices such as discrimination, calibration, or external validation.

Results

In total, 9,209 articles were identified from the electronic search, of which 74 met the inclusion criteria. We found a substantial increase in the number of new models published from 2014 (>50 new models), including an increase in the number of models developed using machine learning. Over 450 unique predictor (component) variables have been tested. Nineteen studies (26%) undertook external validation of newly developed or existing models, with mixed results. For the first time, models have also been developed in low- and middle-income countries (LMICs) and others validated in racial and ethnic minority groups.

Conclusion

The literature on dementia risk prediction modelling is rapidly evolving with new analytical developments and testing in LMICs. However, it is still challenging to make recommendations about which one model is the most suitable for routine use in a clinical setting. There is an urgent need to develop a suitable, robust, validated risk prediction model in the general population that can be widely implemented in clinical practice to improve dementia prevention.

Alzheimer's Disease Prevention and Treatment Based on Population-Based Approaches

The development of effective prevention and treatment strategies for Alzheimer's disease (AD) and dementia is hindered by limited knowledge of the underlying biological and environmental causes. While certain genetic factors have been associated with AD, and various lifestyle and environmental factors have been linked to dementia risk, the interactions between genes and the environment are not yet fully understood. To identify new avenues for dementia prevention, coordinated global efforts are needed to utilize existing cohorts and resources effectively and efficiently. This chapter provides an overview of current research on risk and protective factors for AD and dementia and discusses the opportunities and challenges associated with population-based approaches.

Lipid metabolism and oxidative stress in patients with Alzheimer's disease and amnestic mild cognitive impairment

Lipid metabolism and oxidative stress are key mechanisms in Alzheimer's disease (AD). The link between plasma lipid metabolites and oxidative stress in AD patients is poorly understood. This study was to identify markers that distinguish AD and amnestic mild cognitive impairment (aMCI) from NC, and to reveal potential links between lipid metabolites and oxidative stress. We performed non-targeted lipid metabolism analysis of plasma from patients with AD, aMCI, and NC using LC-MS/MS. The plasma malondialdehyde (MDA), glutathione peroxidase (GSH-Px), and superoxide dismutase (SOD) levels were assessed. We found significant differences in lipid metabolism between patients with AD and aMCI compared to those in NC. AD severity is associated with lipid metabolites, especially TG (18:0_16:0_18:0) + NH4, TG (18:0_16:0_16:0) + NH4, LPC(16:1e)-CH3, and PE (20:0_20:4)-H. SPH (d16:0) + H, SPH (d18:1) + H, and SPH (d18:0) + H were high-performance markers to distinguish AD and aMCI from NC. The AUC of three SPHs combined to predict AD was 0.990, with specificity and sensitivity as 0.949 and 1, respectively; the AUC of three SPHs combined to predict aMCI was 0.934, with specificity and sensitivity as 0.900, 0.981, respectively. Plasma MDA concentrations were higher in the AD group than in the NC group (p = 0.003), whereas plasma SOD levels were lower in the AD (p < 0.001) and aMCI (p = 0.045) groups than in NC, and GSH-Px activity were higher in the AD group than in the aMCI group (p = 0.007). In addition, lipid metabolites and oxidative stress are widely associated. In conclusion, this study distinguished serum lipid metabolism in AD, aMCI, and NC subjects, highlighting that the three SPHs can distinguish AD and aMCI from NC. Additionally, AD patients showed elevated oxidative stress, and there are complex interactions between lipid metabolites and oxidative stress.

Towards a Unitary Hypothesis of Alzheimer's Disease Pathogenesis

The "amyloid cascade" hypothesis of Alzheimer's disease (AD) pathogenesis invokes the accumulation in the brain of plaques (containing the amyloid-β protein precursor [AβPP] cleavage product amyloid-β [Aβ]) and tangles (containing hyperphosphorylated tau) as drivers of pathogenesis. However, the poor track record of clinical trials based on this hypothesis suggests that the accumulation of these peptides is not the only cause of AD. Here, an alternative hypothesis is proposed in which the AβPP cleavage product C99, not Aβ, is the main culprit, via its role as a regulator of cholesterol metabolism. C99, which is a cholesterol sensor, promotes the formation of mitochondria-associated endoplasmic reticulum (ER) membranes (MAM), a cholesterol-rich lipid raft-like subdomain of the ER that communicates, both physically and biochemically, with mitochondria. We propose that in early-onset AD (EOAD), MAM-localized C99 is elevated above normal levels, resulting in increased transport of cholesterol from the plasma membrane to membranes of intracellular organelles, such as ER/endosomes, thereby upregulating MAM function and driving pathology. By the same token, late-onset AD (LOAD) is triggered by any genetic variant that increases the accumulation of intracellular cholesterol that, in turn, boosts the levels of C99 and again upregulates MAM function. Thus, the functional cause of AD is upregulated MAM function that, in turn, causes the hallmark disease phenotypes, including the plaques and tangles. Accordingly, the MAM hypothesis invokes two key interrelated elements, C99 and cholesterol, that converge at the MAM to drive AD pathogenesis. From this perspective, AD is, at bottom, a lipid disorder.

How far are we from reliable metabolomics-based biomarkers? The often-overlooked importance of addressing inter-individual variability factors

Metabolomics has proven great potential to unravel the molecular basis of diseases. However, most attempts aimed at identifying reliable metabolomics-based biomarkers for diagnosis, prediction, and prognosis of diseases have repeatedly failed because of inconsistent results and unsatisfactory replication in independent cohorts. This review article explores the possible causes behind this reproducibility crisis, with special focus on the role that inter-individual variability factors play in modulating the susceptibility to disease development. Furthermore, we provide future perspectives on the applicability of metabolomics in biomedical research and its translatability into clinical practice.

Genetic Insights into the Association and Causality Between Blood Metabolites and Alzheimer's Disease

Background

Alzheimer's disease (AD) is an increasing public health concern with the aging of the global population. Understanding the genetic correlation and potential causal relationships between blood metabolites and AD may provide important insights into the metabolic dysregulation underlying this neurodegenerative disorder.

Objective

The aim of this study was to investigate the causal relationship between blood metabolites and AD using Mendelian randomization (MR) analysis.

Methods

Association data were obtained from three large-scale genome-wide association studies of 486 blood metabolites (N = 7,824), AD (71,880 cases and 383,378 controls), early-onset AD (N = 303,760), and late-onset AD (N = 307,112). Causal associations between blood metabolites and AD were assessed using inverse variance weighting (IVW), MR-Egger, and weighted median methods. Bidirectional two-sample MR analysis was used to identify causal blood metabolites. MR-PRESSO, MR-Egger, and Cochran-Q were used to quantify instrumental variable heterogeneity and horizontal pleiotropy.

Results

Using MR and sensitivity analysis, we identified 40 blood metabolites with potential causal associations with AD. After applying false discovery rate (FDR) correction, two metabolites, gamma-glutamylphenylalanine (OR = 1.15, 95% CI: 1.06-1.24, p = 3.88×10-4, q = 0.09) and X-11317 (OR = 1.16, 95% CI: 1.08-1.26, p = 1.14×10-4, q = 0.05), retained significant associations with AD. Reverse MR analysis indicated no significant causal effect of AD on blood metabolites. No significant instrumental variable heterogeneity or horizontal pleiotropy was found.

Conclusions

This two-sample MR study provides compelling evidence for a potential causal relationship between blood metabolic dysregulation and susceptibility to AD. Further investigation of the biological relevance of the identified metabolites to AD and additional supporting evidence is warranted.

Metabolic profiling of Alzheimer's disease: Untargeted metabolomics analysis of plasma samples

Alzheimer's disease (AD) is often not recognized or is diagnosed very late, which significantly reduces the effectiveness of available pharmacological treatments. Metabolomic analyzes have great potential for improving existing knowledge about the pathogenesis and etiology of AD and represent a novel approach towards discovering biomarkers that could be used for diagnosis, prognosis, and therapy monitoring. In this study, we applied the untargeted metabolomic approach to investigate the changes in biochemical pathways related to AD pathology. We used gas chromatography and liquid chromatography coupled to mass spectrometry (GC-MS and LC-MS, respectively) to identify metabolites whose levels have changed in subjects with AD diagnosis (N = 40) compared to healthy controls (N = 40) and individuals with mild cognitive impairment (MCI, N = 40). The GC-MS identified significant differences between groups in levels of metabolites belonging to the classes of benzene and substituted derivatives, carboxylic acids and derivatives, fatty acyls, hydroxy acids and derivatives, keto acids and derivatives, and organooxygen compounds. Most of the compounds identified by the LC-MS were various fatty acyls, glycerolipids and glycerophospholipids. All of these compounds were decreased in AD patients and in subjects with MCI compared to healthy controls. The results of the study indicate disturbed metabolism of lipids and amino acids and an imbalance of metabolites involved in energy metabolism in individuals diagnosed with AD, compared to healthy controls and MCI subjects.

Biological Diagnosis of Alzheimer's Disease Based on Amyloid Status: An Illustration of Confirmation Bias in Medical Research?

Alzheimer's disease (AD) was first characterized by Dr. Alois Alzheimer in 1906 by studying a demented patient and discovering cerebral amyloid plaques and neurofibrillary tangles. Subsequent research highlighted the roles of Aβ peptides and tau proteins, which are the primary constituents of these lesions, which led to the amyloid cascade hypothesis. Technological advances, such as PET scans using Florbetapir, have made it possible to visualize amyloid plaques in living patients, thus improving AD's risk assessment. The National Institute on Aging and the Alzheimer's Association introduced biological diagnostic criteria in 2011, which underlined the amyloid deposits diagnostic value. However, potential confirmation bias may have led researchers to over-rely on amyloid markers independent of AD's symptoms, despite evidence of their limited specificity. This review provides a critical examination of the current research paradigm in AD, including, in particular, the predominant focus on amyloid and tau species in diagnostics. We discuss the potential multifaceted consequences of this approach and propose strategies to mitigate its overemphasis in the development of new biomarkers. Furthermore, our study presents comprehensive guidelines aimed at enhancing the creation of biomarkers for accurately predicting AD dementia onset. These innovations are crucial for refining patient selection processes in clinical trial enrollment and for the optimization of therapeutic strategies. Overcoming confirmation bias is essential to advance the diagnosis and treatment of AD and to move towards precision medicine by incorporating a more nuanced understanding of amyloid biomarkers.

Lipidomics profiling reveals distinct patterns of plasma sphingolipid alterations in Alzheimer's disease and vascular dementia

BACKGROUND

Alzheimer's disease (AD) and vascular dementia (VaD) are two of the commonest causes of dementia in the elderly. Of the myriad biomolecules implicated in dementia pathogenesis, sphingolipids have attracted relatively scant research attention despite their known involvement in multiple pathophysiological processes. The potential utility of peripheral sphingolipids as biomarkers in dementia cohorts with high concomitance of cerebrovascular diseases is also unclear.

METHODS

Using a lipidomics platform, we performed a case-control study of plasma sphingolipids in a prospectively assessed cohort of 526 participants (non-cognitively impaired, NCI = 93, cognitively impaired = 217, AD = 166, VaD = 50) using a lipidomics platform.

RESULTS

Distinct patterns of sphingolipid alterations were found in AD and VaD, namely an upregulation of d18:1 species in AD compared to downregulation of d16:1 species in VaD. In particular, GM3 d18:1/16:0 and GM3 d18:1/24:1 showed the strongest positive associations with AD. Furthermore, evaluation of sphingolipids panels showed specific combinations with higher sensitivity and specificity for classification of AD (Cer d16:1/24:0. Cer d18:1/16:0, GM3 d16:1/22:0, GM3 d18:1/16:0, SM d16:1/22:0, HexCer d18:1/18:0) and VAD (Cer d16:1/24:0, Cer d18:1/16:0, Hex2Cer d16:1/16:0, HexCer d18:1/18:0, SM d16:1/16:0, SM d16:1/20:0, SM d18:2/22:0) compared to NCI.

CONCLUSIONS

AD and VaD are associated with distinct changes of plasma sphingolipids, warranting further studies into underlying pathophysiological mechanisms and assessments of their potential utility as dementia biomarkers and therapeutic targets.

A Comprehensive Review of the Effects of Glycemic Carbohydrates on the Neurocognitive Functions Based on Gut Microenvironment Regulation and Glycemic Fluctuation Control

Improper glycemic carbohydrates (GCs) consumption can be a potential risk factor for metabolic diseases such as obesity and diabetes, which may lead to cognitive impairment. Although several potential mechanisms have been studied, the biological relationship between carbohydrate consumption and neurocognitive impairment is still uncertain. In this review, the main effects and mechanisms of GCs' digestive characteristics on cognitive functions are comprehensively elucidated. Additionally, healthier carbohydrate selection, a reliable research model, and future directions are discussed. Individuals in their early and late lives and patients with metabolic diseases are highly susceptible to dietary-induced cognitive impairment. It is well known that gut function is closely related to dietary patterns. Unhealthy carbohydrate diet-induced gut microenvironment disorders negatively impact cognitive functions through the gut-brain axis. Moreover, severe glycemic fluctuations, due to rapidly digestible carbohydrate consumption or metabolic diseases, can impair neurocognitive functions by disrupting glucose metabolism, dysregulating calcium homeostasis, oxidative stress, inflammatory responses, and accumulating advanced glycation end products. Unstable glycemic status can lead to more severe neurological impairment than persistent hyperglycemia. Slow-digested or resistant carbohydrates might contribute to better neurocognitive functions due to stable glycemic response and healthier gut functions than fully gelatinized starch and nutritive sugars.

The effect of lipid metabolism on age-associated cognitive decline: Lessons learned from model organisms and human

Lipids are required as integral building blocks of cells to support cellular structures and functions. The intricate mechanisms underpinning lipid homeostasis are essential for the health and maintenance of the central nervous system. Here we summarize the recent advances in dissecting the effect of lipid metabolism on cognitive function and its age-associated decline by reviewing relevant studies ranging from invertebrate model organisms to mammals including human.

Circulating metabolites and risk of incident dementia: A prospective cohort study

Identifying circulating metabolites associated with dementia, cognition, and brain volume may improve the understanding of dementia pathogenesis and provide novel insights for preventive and therapeutic interventions. This cohort study included a total of 87 885 participants (median follow-up of 9.1 years, 54% female) without dementia at baseline from the UK Biobank. A total of 249 plasma metabolites were measured using nuclear magnetic resonance spectroscopy at baseline. Cox proportional regression was used to examine the associations of each metabolite with incident dementia (cases = 1134), Alzheimer's disease (AD; cases = 488), and vascular dementia (VD; cases = 257) during follow-up. Dementia-associated metabolites were further analyzed for association with cognitive deficits (N = 87 885) and brain volume (N = 7756) using logistic regression and linear regression. We identified 26 metabolites associated with incident dementia, of which 6 were associated with incident AD and 5 were associated with incident VD. These 26 dementia-related metabolites were subfractions of intermediate-density lipoprotein, large low-density lipoprotein (L-LDL), small high-density lipoprotein (S-HDL), very-low-density lipoprotein, fatty acids, ketone bodies, citrate, glucose, and valine. Among them, the cholesterol percentage in L-LDL (L-LDL-C%) was associated with lower risk of AD (HR [95% CI] = 0.92 [0.87-0.97], p = 0.002), higher brain cortical (β = 0.047, p = 3.91 × 10-6 ), and hippocampal (β = 0.043, p = 1.93 × 10-4 ) volume. Cholesteryl ester-to-total lipid ratio in L-LDL (L-LDL-CE%) was associated with lower risk of AD (HR [95% CI] = 0.93 [0.90-0.96], p = 1.48 × 10-4 ), cognitive deficits (odds ratio = 0.98, p = 0.009), and higher hippocampal volume (β = 0.027, p = 0.009). Cholesteryl esters in S-HDL (S-HDL-CE) were associated with lower risk of VD (HR [95% CI] = 0.81 [0.71-0.93], p = 0.002), but not AD. Taken together, circulating levels of L-LDL-CE% and L-LDL-C% were robustly associated with risk of AD and AD phenotypes, but not with VD. S-HDL-CE was associated with lower risk of VD, but not with AD or AD phenotypes. These metabolites may play a role in the advancement of future intervention trials. Additional research is necessary to gain a complete comprehension of the molecular mechanisms behind these associations.

An arrayed CRISPR knockout screen identifies genetic regulators of GLUT1 expression

Glucose, a primary fuel source under homeostatic conditions, is transported into cells by membrane transporters such as glucose transporter 1 (GLUT1). Due to its essential role in maintaining energy homeostasis, dysregulation of GLUT1 expression and function can adversely affect many physiological processes in the body. This has implications in a wide range of disorders such as Alzheimer's disease (AD) and several types of cancers. However, the regulatory pathways that govern GLUT1 expression, which may be altered in these diseases, are poorly characterized. To gain insight into GLUT1 regulation, we performed an arrayed CRISPR knockout screen using Caco-2 cells as a model cell line. Using an automated high content immunostaining approach to quantify GLUT1 expression, we identified more than 300 genes whose removal led to GLUT1 downregulation. Many of these genes were enriched along signaling pathways associated with G-protein coupled receptors, particularly the rhodopsin-like family. Secondary hit validation confirmed that removal of select genes, or modulation of the activity of a corresponding protein, yielded changes in GLUT1 expression. Overall, this work provides a resource and framework for understanding GLUT1 regulation in health and disease.

Lipids and lipoproteins may play a role in the neuropathology of Alzheimer's disease

Alzheimer's disease (AD) and other classes of dementia are important public health problems with overwhelming social, physical, and financial effects for patients, society, and their families and caregivers. The pathophysiology of AD is poorly understood despite the extensive number of clinical and experimental studies. The brain's lipid-rich composition is linked to disturbances in lipid homeostasis, often associated with glucose and lipid abnormalities in various neurodegenerative diseases, including AD. Moreover, elevated low-density lipoprotein (LDL) cholesterol levels may be related to a higher probability of AD. Here, we hypothesize that lipids, and electronegative LDL (L5) in particular, may be involved in the pathophysiology of AD. Although changes in cholesterol, triglyceride, LDL, and glucose levels are seen in AD, the cause remains unknown. We believe that L5-the most electronegative subfraction of LDL-may be a crucial factor in understanding the involvement of lipids in AD pathology. LDL and L5 are internalized by cells through different receptors and mechanisms that trigger separate intracellular pathways. One of the receptors involved in L5 internalization, LOX-1, triggers apoptotic pathways. Aging is associated with dysregulation of lipid homeostasis, and it is believed that alterations in lipid metabolism contribute to the pathogenesis of AD. Proposed mechanisms of lipid dysregulation in AD include mitochondrial dysfunction, blood-brain barrier disease, neuronal signaling, inflammation, and oxidative stress, all of which lead ultimately to memory loss through deficiency of synaptic integration. Several lipid species and their receptors have essential functions in AD pathogenesis and may be potential biomarkers.

Cardiovascular Disease and Alzheimer's Disease: The Heart-Brain Axis

Cardiovascular disease (CVD) remains one of the leading causes of morbidity and mortality in aging adults across the United States. Prior studies indicate that the presence of atherosclerosis, the pathogenic basis of CVD, is linked with dementias. Alzheimer's disease (AD) and AD-related dementias are a major public health challenge in the United States. Recent studies indicate that ≈3.7 million Americans ≥65 years of age had clinical AD in 2017, with projected increases to 9.3 million by 2060. Treatment options for AD remain limited. Development of disease-modifying therapies are challenging due, in part, to the long preclinical window of AD. The preclinical incubation period of AD starts in midlife, providing a critical window for identification and optimization of AD risk factors. Studies link AD with CVD risk factors such as hypertension, inflammation, and dyslipidemia. Both AD and CVD are progressive diseases with decades-long development periods. CVD can clinically manifest several years earlier than AD, making CVD and its risk factors a potential predictor of future AD. The current review focuses on the state of literature on molecular and metabolic pathways modulating the heart-brain axis underlying the potential association of midlife CVD risk factors and their effect on AD and related dementias. Further, we explore potential CVD/dementia preventive strategies during the window of opportunity in midlife and the future of research in the field in the multiomics and novel biomarker use era.

Mass Spectrometry Based on Chemical Derivatization Has Brought Novel Discoveries to Lipidomics: A Comprehensive Review

Lipids, as one of the most important organic compounds in organisms, are important components of cells and participate in energy storage and signal transduction of living organisms. As a rapidly rising field, lipidomics research involves the identification and quantification of multiple classes of lipid molecules, as well as the structure, function, dynamics, and interactions of lipids in living organisms. Due to its inherent high selectivity and high sensitivity, mass spectrometry (MS) is the "gold standard" analysis technique for small molecules in biological samples. The combination chemical derivatization with MS detection is a unique strategy that could improve MS ionization efficiency, facilitate structure identification and quantitative analysis. Herein, this review discusses derivatization-based MS strategies for lipidomic analysis over the past decade and focuses on all the reported lipid categories, including fatty acids and modified fatty acids, glycerolipids, glycerophospholipids, sterols and saccharolipids. The functional groups of lipids mainly involved in chemical derivatization include the C=C group, carboxyl group, hydroxyl group, amino group, carbonyl group. Furthermore, representative applications of these derivatization-based lipid profiling methods were summarized. Finally, challenges and countermeasures of lipid derivatization are mentioned and highlighted to guide future studies of derivatization-based MS strategy in lipidomics.

ABCA7-Associated Clinical Features and Molecular Mechanisms in Alzheimer's Disease

Alzheimer's disease (AD) is the most common type of neurodegenerative disease and its pathogenesis is still unclear. Genetic factors are thought to account for a large proportion of the overall AD phenotypes. ATP-binding cassette transporter A7 (ABCA7) is one of the most important risk gene for AD. Multiple forms of ABCA7 variants significantly increase the risk of AD, such as single-nucleotide polymorphisms, premature termination codon variants, missense variants, variable number tandem repeat, mutations, and alternative splicing. AD patients with ABCA7 variants usually exhibit typical clinical and pathological features of traditional AD with a wide age of onset range. ABCA7 variants can alter ABCA7 protein expression levels and protein structure to affect protein functions such as abnormal lipid metabolism, amyloid precursor protein (APP) processing, and immune cell function. Specifically, ABCA7 deficiency can cause neuronal apoptosis by inducing endoplasmic reticulum stress through the PERK/eIF2α pathway. Second, ABCA7 deficiency can increase Aβ production by upregulating the SREBP2/BACE1 pathway and promoting APP endocytosis. In addition, the ability of microglia to phagocytose and degrade Aβ is destroyed by ABCA7 deficiency, leading to reduced clearance of Aβ. Finally, disturbance of lipid metabolism may also be an important method by which ABCA7 variants influence the incidence rate of AD. In the future, more attention should be given to different ABCA7 variants and ABCA7 targeted therapies for AD.