Circulating metabolites and general cognitive ability and dementia: Evidence from 11 cohort studies

Integration of Metabolomic and Brain Imaging Data Highlights Pleiotropy Among Posttraumatic Stress Disorder, Glycoprotein Acetyls, and Pallidum Structure

Background

The development of posttraumatic stress disorder (PTSD) is attributable to the interplay between exposure to severe traumatic events, environmental factors, and biological characteristics. Blood and brain imaging markers have been associated with PTSD. However, to our knowledge, no study has systematically investigated the genetic relationship between PTSD, metabolic biomarkers, and brainwide imaging.

Methods

We integrated genome-wide data informative of PTSD, 233 metabolic biomarkers, and 3935 brain imaging-derived phenotypes (IDPs). Pleiotropy was assessed by applying global and local genetic correlation, colocalization, and genetically inferred causality.

Results

We observed significant genetic overlap between PTSD and glycoprotein acetyls (GlycA) (a stable inflammatory biomarker) in 2 independent cohorts (discovery r g = 0.26, p = 1.00 × 10-4; replication r g = 0.23, p = 5.99 × 10-19). Interestingly, there was no genetic correlation between anxiety and GlycA (p = .33). PTSD and GlycA were both genetically correlated with median T2∗ in the left pallidum (IDP-1444: r g = 0.14, p = 1.39 × 10-5; r g = -0.38, p = 2.50 × 10-3, respectively). Local genetic correlation between PTSD and GlycA was observed in 7 genetic regions (p < 2.0 × 10-5), mapping genes related to immune and stress response, inflammation, and metabolic processes. Furthermore, we identified 1 variant, rs12048743, with evidence of horizontal pleiotropy linking GlycA and IDP-1444 (z IDP-1444 = 17.14, z GlycA = -6.07, theta p = 2.06 × 10-8). Regional colocalization was observed among GlycA, IDP-1444, and tissue-specific transcriptomic regulation for brain frontal cortex and testis (rs12048743-chr1q32.1; posterior probability > 0.8). While we also tested causality between PTSD, metabolomic biomarkers, and brain IDPs, these were not consistent across different genetically informed causal inference methods.

Conclusions

Our findings highlight a new putative pleiotropic mechanism that links systemic inflammation and pallidum structure to PTSD.

Causal cardiovascular risk factors for dementia: insights from observational and genetic studies

The escalating prevalence of dementia worldwide necessitates preventive strategies to mitigate its extensive health, psychological, and social impacts. As the prevalence of dementia continues to rise, gaining insights into its risk factors and causes becomes paramount, given the absence of a definitive cure. Cardiovascular disease has emerged as a prominent player in the complex landscape of dementia. Preventing dyslipidaemia, unhealthy western-type diets, hypertension, diabetes, being overweight, physical inactivity, smoking, and high alcohol intake have the potential to diminish not only cardiovascular disease but also dementia. The purpose of this review is to present our current understanding of cardiovascular risk factors for Alzheimer's disease and vascular dementia (VaD) by using clinical human data from observational, genetic studies and clinical trials, while elaborating on potential mechanisms. Hypertension and Type 2 diabetes surface as significant causal risk factors for both Alzheimer's disease and VaD, as consistently illustrated in observational and Mendelian randomization studies. Anti-hypertensive drugs and physical activity have been shown to improve cognitive function in clinical trials. Important to note is that robust genome-wide association studies are lacking for VaD, and indeed more and prolonged clinical trials are needed to establish these findings and investigate other risk factors. Trials should strategically target individuals at the highest dementia risk, identified using risk charts incorporating genetic markers, biomarkers, and cardiovascular risk factors. Understanding causal risk factors for dementia will optimize preventive measures, and the implementation of well-known therapeutics can halt or alleviate dementia symptoms if started early. Needless to mention is that future health policies should prioritize primordial prevention from early childhood to prevent risk factors from even occurring in the first place. Together, understanding the role of cardiovascular risk factors in dementia, improving genome-wide association studies for VaD, and advancing clinical trials are crucial steps in addressing this significant public health challenge.

Providing lysophosphatidylcholine-bound omega-3 fatty acids increased eicosapentaenoic acid, but not docosahexaenoic acid, in the cortex of mice with the apolipoprotein E3 or E4 allele

BACKGROUND

Several mechanisms have been proposed for the brain uptake of omega-3 fatty acids (n-3), including passive diffusion of the unesterified form and the use of Mfsd2a transporter for the lysophosphatidylcholine (LPC) form. We hypothesize that the accumulation of LPC n-3 in the brain is lower in mice carrying the apolipoprotein E ε4 allele (APOE4), a major genetic risk factor for developing sporadic Alzheimer's disease in humans.

OBJECTIVE

Determine whether two or four months of supplementation with LPC n-3 increases the levels of docosahexaenoic acids (DHA) and eicosapentaenoic acids (EPA) in the frontal cortex of APOE3 and APOE4 mice.

METHODS

APOE3 and APOE4 mice were administered LPC n-3 (9.6 mg DHA + 18.3 mg EPA) or sunflower oil (control) by oral gavage for two or four months (n = 5-8 per genotype, per treatment, and per treatment duration). At the end of the treatment period, frontal cortices were collected, and their FA profiles analyzed by gas chromatography with flame ionization detection.

RESULTS

After two months of gavage with LPC n-3, APOE3 mice showed increased levels of EPA in their cortex, but not DHA. In APOE4 mice, neither EPA nor DHA levels were significantly affected. After four months of LPC n-3, both APOE3 and APOE4 mice exhibited higher EPA levels, while changes in DHA levels were not statistically significant.

CONCLUSION

LPC n-3 supplementation increased EPA, but not DHA, levels in the frontal cortex of mice in a duration- and APOE genotype-dependent manner. Further research is needed to explore the implications for brain health.

Increased 1H-NMR metabolomics-based health score associates with declined cognitive performance and functional independence in older adults at risk of cardiovascular disease

The 1-HMR metabolomics-based MetaboHealth score, comprised of 14 serum metabolic markers, associates with disease-specific mortality, but it is unclear whether the score also reflects cognitive changes and functional impairment. We aimed to assess the associations between the MetaboHealth score with cognitive function and functional decline in older adults at increased cardiovascular risk. A total of 5292 older adults free of dementia at baseline with mean age 75.3 years (SD = 3.4) from the Prospective Study of Pravastatin in the Elderly (PROSPER). MetaboHealth score were measured at baseline, and cognitive function and functional independence were measured at baseline and every 3 months during up to 2.5 years follow-up. Cognitive function was assessed using the Stroop test (selective attention), the Letter Digit Coding test (LDCT) (processing speed), and the two versions of the Picture Learning test (delayed and immediate; memory). Two tests of functional independence were used: Barthel Index (BI) and instrumental activities at daily living (IADL). A higher MetaboHealth score was associated with worse cognitive function (in all domains) and with worse functional independence. For example, after full adjustments, a 1-SD higher MetaboHealth score was associated with 9.02 s (95%CI 7.29, 10.75) slower performance on the Stroop test and 2.79 (2.21, 3.26) less digits coded on the LDCT. During follow-up, 1-SD higher MetaboHealth score was associated with an additional decline of 0.53 s (0.23, 0.83) on the Stroop test and - 0.08 (- 0.11, - 0.06) points on the IADL. Metabolic disturbance, as reflected by an increased metabolomics-based health score, may mark future cognitive and functional decline.

Global burden of young-onset dementia, from 1990 to 2021: an age-period-cohort analysis from the global burden of disease study 2021

This study aims to assess the burden of young-onset dementia worldwide, regionally, and nationally during 1990-2021. Prevalence, incidence, mortality, and disability adjusted life years (DALYs) rates were used to estimate burden of the young-onset dementia. The average annual percentage was utilized to evaluate the trends during 1990-2021. Decomposition analysis was performed to explore driving factors behind changes. Age-period-cohort modeling was used to estimate local drift, age, period and cohort effects. Global age standardized prevalence and incidence of dementia among people under 65 years increased from 93.39 and 16.24 per 100,000 persons in 1990 to 96.09 and 17.16 per 100,000 persons in 2021; mortality increased from 0.89 per 100,000 population to 0.91 per 100,000 population; and age standardized DALYs increased from 45.60 per 100,000 persons to 46.78 per 100,000 persons. Countries with a high, high-middle, and middle SDI experienced an upward trend of prevalence and incidence, and the mortality and DALYs of young-onset dementia in countries with a low-middle and low sociodemographic index was a higher level. Smoking, high body-mass index and high fasting plasma glucose levels were main risk factors. Population growth was the largest factor for the increasing young-onset dementia in all regions. Globally, prevalence, incidence, and DALYs rate of young-onset dementia increased with age, period effects showing a decreasing risk and then an increasing risk. Cohort effects of prevalence and DALYs began to decline after the 1950s. Young-onset dementia presents a growing global health challenge in the age, period and cohort across SDI regions, countries.

Alterations of amino acids in older adults with Alzheimer's Disease and Vascular Dementia

Metabolomics provide a promising tool for understanding dementia pathogenesis and identifying novel biomarkers. This study aimed to identify amino acid biomarkers for Alzheimer's Disease (AD) and Vascular Dementia (VD). By amino acid metabolomics, the concentrations of amino acids were determined in the serum of AD and VD patients as well as age-matched healthy controls. Several differences in the concentration of amino acids were observed in AD patients compared to both healthy controls and VD patients. However, no significant distinction was found between healthy controls and VD patients. Considering comorbidities, cystine levels were higher in AD than in VD among non-diabetic patients, but not in those with diabetes. Notably, creatine, spermidine, cystine, and tyrosine demonstrated favorable results in decision curve analyses and good discriminative performances, suggesting their potential for clinical application. These fundings give novel perspectives of serum amino acids for predicting metabolic pathways in AD and VD pathogenesis.

Metabolomics profiling of Type D personality traits

OBJECTIVE

Type D (Distressed) personality combines negative affectivity (NA) and social inhibition (SI) and is associated with an increased risk of cardiometabolic diseases. Here, we examined the association of Type D traits with 230 (predominantly) lipid metabolites and metabolite ratios.

METHODS

Four Dutch cohorts were included, comprising 10,834 individuals. Type D personality traits were measured by self-report questionnaires. A proton nuclear magnetic resonance (NMR) metabolomics platform provided 149 absolute measures (98 belonging to lipoprotein subclasses) and 81 derived ratios. For all, linear regression analyses were performed within each cohort, followed by random-effects meta-analyses. A per-measure FDR q-value<0.05 was set as a study-wise significant association.

RESULTS

SI was significantly associated with a lower omega-3 fatty acids to total fatty acids (FAw3.FA%) ratio, and a lower free cholesterol to total lipids ratio in very small VLDL (XS.VLDL.FC%). FAw3.FA% was also associated to NA (no study-wise significance though). NA showed a suggestive replication (p-value<.05) of the previous reported associations with depression for 5 out of 18 metabolites from the same metabolomics platform: triglycerides in HDL, serum total triglycerides, VLDL cholesterol, mean diameter for VLDL particles and VLDL triglycerides.

CONCLUSIONS

In this large meta-analysis, SI was associated with omega-3 fatty acids to total fatty acids ratio, which is suggestive of lower omega-3 fatty acid intake. Only some metabolite biomarkers showed tentative links to Type D and NA. In sum, it seems that there are no major alterations in lipid metabolism associated with Type D traits.

Brain maps of general cognitive function and spatial correlations with neurobiological cortical profiles

In this paper, we attempt to answer two questions: 1) which regions of the human brain, in terms of morphometry, are most strongly related to individual differences in domain-general cognitive functioning (g)? and 2) what are the underlying neurobiological properties of those regions? We meta-analyse vertex-wise g-cortical morphometry (volume, surface area, thickness, curvature and sulcal depth) associations using data from 3 cohorts: the UK Biobank (UKB), Generation Scotland (GenScot), and the Lothian Birth Cohort 1936 (LBC1936), with the meta-analytic N = 38,379 (age range = 44 to 84 years old). These g-morphometry associations vary in magnitude and direction across the cortex (|β| range = -0.12 to 0.17 across morphometry measures) and show good cross-cohort agreement (mean spatial correlation r = 0.57, SD = 0.18). Then, to address (2), we bring together existing - and derive new - cortical maps of 33 neurobiological characteristics from multiple modalities (including neurotransmitter receptor densities, gene expression, functional connectivity, metabolism, and cytoarchitectural similarity). We discover that these 33 profiles spatially covary along four major dimensions of cortical organisation (accounting for 65.9% of the variance) and denote aspects of neurobiological scaffolding that underpin the spatial patterning of MRI-cognitive associations we observe (significant |r| range = 0.21 to 0.56). Alongside the cortical maps from these analyses, which we make openly accessible, we provide a compendium of cortex-wide and within-region spatial correlations among general and specific facets of brain cortical organisation and higher order cognitive functioning, which we hope will serve as a framework for analysing other aspects of behaviour-brain MRI associations.

The blood metabolome of cognitive function and brain health in middle-aged adults - influences of genes, gut microbiome, and exposome

Increasing evidence suggests the involvement of metabolic alterations in neurological disorders, including Alzheimer's disease (AD), and highlights the significance of the peripheral metabolome, influenced by genetic factors and modifiable environmental exposures, for brain health. In this study, we examined 1,387 metabolites in plasma samples from 1,082 dementia-free middle-aged participants of the population-based Rotterdam Study. We assessed the relation of metabolites with general cognition (G-factor) and magnetic resonance imaging (MRI) markers using linear regression and estimated the variance of these metabolites explained by genes, gut microbiome, lifestyle factors, common clinical comorbidities, and medication using gradient boosting decision tree analysis. Twenty-one metabolites and one metabolite were significantly associated with total brain volume and total white matter lesions, respectively. Fourteen metabolites showed significant associations with G-factor, with ergothioneine exhibiting the largest effect (adjusted mean difference = 0.122, P = 4.65×10-7). Associations for nine of the 14 metabolites were replicated in an independent, older cohort. The metabolite signature of incident AD in the replication cohort resembled that of cognition in the discovery cohort, emphasizing the potential relevance of the identified metabolites to disease pathogenesis. Lifestyle, clinical variables, and medication were most important in determining these metabolites' blood levels, with lifestyle, explaining up to 28.6% of the variance. Smoking was associated with ten metabolites linked to G-factor, while diabetes and antidiabetic medication were associated with 13 metabolites linked to MRI markers, including N-lactoyltyrosine. Antacid medication strongly affected ergothioneine levels. Mediation analysis revealed that lower ergothioneine levels may partially mediate negative effects of antacids on cognition (31.5%). Gut microbial factors were more important for the blood levels of metabolites that were more strongly associated with cognition and incident AD in the older replication cohort (beta-cryptoxanthin, imidazole propionate), suggesting they may be involved later in the disease process. The detailed results on how multiple modifiable factors affect blood levels of cognition- and brain imaging-related metabolites in dementia-free participants may help identify new AD prevention strategies.

Vascular cognitive impairment: Advances in clinical research and management

ABSTRACT

Vascular cognitive impairment (VCI) encompasses a wide spectrum of cognitive disorders, ranging from mild cognitive impairment to vascular dementia. Its diagnosis relies on thorough clinical evaluations and neuroimaging. VCI predominately arises from vascular risk factors (VRFs) and cerebrovascular disease, either independently or in conjunction with neurodegeneration. Growing evidence underscores the prevalence of VRFs, highlighting their potential for early prediction of cognitive impairment and dementia in later life. The precise mechanisms linking vascular pathologies to cognitive deficits remain elusive. Chronic cerebrovascular pathology is the most common neuropathological feature of VCI, often interacting synergistically with neurodegenerative processes. Current research efforts are focused on developing and validating reliable biomarkers to unravel the etiology of vascular brain changes in VCI. The collaborative integration of these biomarkers into clinical practice, alongside routine incorporation into neuropathological assessments, presents a promising strategy for predicting and stratifying VCI. The cornerstone of VCI prevention remains the control of VRFs, which includes multi-domain lifestyle modifications. Identifying appropriate pharmacological approaches is also of paramount importance. In this review, we synthesize recent advancements in the field of VCI, including its definition, determinants of vascular risk, pathophysiology, neuroimaging and fluid-correlated biomarkers, predictive methodologies, and current intervention strategies. Increasingly evident is the notion that more rigorous research for VCI, which arises from a complex interplay of physiological events, is still needed to pave the way for better clinical outcomes and enhanced quality of life for affected individuals.

Biofluid biomarkers for Alzheimer's disease: past, present, and future

Alzheimer's disease (AD) is a gradually progressive neurodegenerative disease with tremendous social and economic burden. Therefore, early and accurate diagnosis is imperative for effective treatment or prevention of the disease. Cerebrospinal fluid and blood biomarkers emerge as favorable diagnostic tools due to their relative accessibility and potential for widespread clinical use. This review focuses on the AT(N) biomarker system, which includes biomarkers reflecting AD core pathologies, amyloid deposition, and pathological tau, as well as neurodegeneration. Novel biomarkers associated with inflammation/immunity, synaptic dysfunction, vascular pathology, and α-synucleinopathy, which might contribute to either the pathogenesis or the clinical progression of AD, have also been discussed. Other emerging candidates including non-coding RNAs, metabolites, and extracellular vesicle-based markers have also enriched the biofluid biomarker landscape for AD. Moreover, the review discusses the current challenges of biofluid biomarkers in AD diagnosis and offers insights into the prospective future development.

Prenatal PM2.5 Exposure Associated with Neonatal Gut Bacterial Colonization and Early Children's Cognitive Development

Previous research indicated that fine particulate matter (PM2.5) exposure affected both offspring neurodevelopment and the colonization of gut microbiota (GM), while the underlying mechanism remained unclear. Our study aimed to evaluate the impacts of prenatal PM2.5 exposure on child cognitive development and investigate the role of neonatal GM colonization in the association. Based on the Shanghai Maternal-Child Pairs Cohort, 361 maternal-child pairs were recruited. Prenatal PM2.5 exposure concentrations were estimated using a high-spatial-resolution prediction model, and child neurodevelopment was assessed by the Ages and Stages Questionnaire. Multivariable linear regression models, logistic regression models, linear discriminant analysis effect size, and random forest model were applied to explore the associations among PM2.5 exposure, GM colonization, and children's neurodevelopment. The present study revealed a negative correlation between PM2.5 exposure throughout pregnancy and child neurodevelopment. Prenatal PM2.5 exposure was associated with an increased risk of suspected developmental delay (SDD) (OR = 1.683, 95% CI: 1.138, 2.489) in infants aged 2 months. Additionally, potential operational taxonomic unit markers were identified for PM2.5-related neurotoxicity, demonstrating promising classification potential for early SDD screening (AUC = 71.27%). Prenatal PM2.5 exposure might disrupt the composition, richness, and evenness of meconium GM, thereby influencing cognitive development and the occurrence of SDD in offspring. Seven PM2.5-related genera, Ruminococcus gnavus group, Romboutsia, Burkholderiaceae Caballeronia Paraburkholderia, Blautia, Alistipes, Parabacteroides, and Bacteroides, were validated as correlated with prenatal PM2.5 exposure and the occurrence of SDD. Moreover, alterations of GM related to PM2.5 exposure and SDD might be accompanied by changes in functional pathways of amino acid, lipid, and vitamin metabolism as indicated by differentially enriched species in the Kyoto Encyclopedia of Genes and Genomes.

Circulating metabolome in relation to cognitive impairment: a community-based cohort of older adults

The role of circulating metabolome in cognitive impairment is inconclusive, and whether the associations are in the severity-dependent manner remains unclear. We aimed to identify plasma metabolites associated with cognitive impairment and evaluate the added predictive capacity of metabolite biomarkers on incident cognitive impairment beyond traditional risk factors. In the Rugao Longevity and Ageing Study (RuLAS), plasma metabolome was profiled by nuclear magnetic resonance spectroscopy. Participants were classified into the cognitively normal, moderately impaired, and severely impaired groups according to their performance in two objective cognitive tests. A two-step strategy of cross-sectional discovery followed by prospective validation was applied. In the discovery stage, we included 1643 participants (age: 78.9 ± 4.5 years) and conducted multinomial logistic regression. In the validation stage, we matched 68 incident cases of cognitive impairment (moderately-to-severely impaired) during the 2-year follow-up with 204 cognitively normal controls by age and sex at a 1:3 ratio, and conducted conditional logistic regression. We identified 28 out of 78 metabolites cross-sectionally related to severely impaired cognition, among which IDL particle number, ApoB in IDL, leucine, and valine were prospectively associated with 28%, 28%, 29%, and 33% lower risk of developing cognitive impairment, respectively. Incorporating 13 metabolite biomarkers selected through Lasso regression into the traditional risk factors-based prediction model substantially improved the ability to predict incident cognitive impairment (AUROC: 0.839 vs. 0.703, P < 0.001; AUPRC: 0.705 vs. 0.405, P < 0.001). This study identified specific plasma metabolites related to cognitive impairment. Incorporation of specific metabolites substantially improved the prediction performance for cognitive impairment.

Association between metabolomics-based biomarker scores and 10-year cognitive decline in men and women. The Doetinchem Cohort Study

BACKGROUND

Metabolomic scores based on age (MetaboAge) and mortality (MetaboHealth) are considered indicators of overall health, but their association with cognition in the general population is unknown. Therefore, the association between MetaboAge/MetaboHealth and level and decline in cognition was studied, as were differences between men and women.

METHODS

Data of 2821 participants (50% women, age range 45-75) from the Doetinchem Cohort Study was used. MetaboAge and MetaboHealth were calculated from 1H-NMR metabolomics data at baseline. Cognitive domain scores (memory, flexibility and processing speed) and global cognitive functioning were available over a 10-year period. The association between MetaboAge/MetaboHealth and level of cognitive functioning was studied using linear regressions while for the association between MetaboAge/MetaboHealth and cognitive decline longitudinal linear mixed models were used. Analyses were adjusted for demographics and lifestyle factors.

RESULTS

Higher MetaboAge, indicating poorer metabolomic ageing, was only associated with lower levels of processing speed in men. Higher MetaboHealth, indicating poorer immune-metabolic health, was associated with lower levels of cognitive functioning for all three domains and global cognitive functioning in both men and women. Only in men, MetaboHealth was also associated with 10-year decline in flexibility, processing speed and global cognition. Metabolites that contributed to the observed associations were in men mainly markers of protein metabolism, and in women mainly markers of lipid metabolism and inflammatory metabolites.

CONCLUSIONS

MetaboHealth, not MetaboAge, was associated with cognitive functioning independent of conventional risk factors. Individual metabolites affect cognitive functioning differently in men and women, suggesting sex-specific pathophysiological pathways underlying cognitive functioning.

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.

Clinical trajectories preceding incident dementia up to 15 years before diagnosis: a large prospective cohort study

BACKGROUND

Dementia has a long prodromal stage with various pathophysiological manifestations; however, the progression of pre-diagnostic changes remains unclear. We aimed to determine the evolutional trajectories of multiple-domain clinical assessments and health conditions up to 15 years before the diagnosis of dementia.

METHODS

Data was extracted from the UK-Biobank, a longitudinal cohort that recruited over 500,000 participants from March 2006 to October 2010. Each demented subject was matched with 10 healthy controls. We performed logistic regressions on 400 predictors covering a comprehensive range of clinical assessments or health conditions. Their evolutional trajectories were quantified using adjusted odds ratios (ORs) and FDR-corrected p-values under consecutive timeframes preceding the diagnosis of dementia.

FINDINGS

During a median follow-up of 13.7 [Interquartile range, IQR 12.9-14.2] years until July 2022, 7620 subjects were diagnosed with dementia. In general, upon approaching the diagnosis, demented subjects witnessed worse functional assessments and a higher prevalence of health conditions. Associations up to 15 years preceding the diagnosis comprised declined physical strength (hand grip strength, OR 0.65 [0.63-0.67]), lung dysfunction (peak expiratory flow, OR 0.78 [0.76-0.81]) and kidney dysfunction (cystatin C, OR 1.13 [1.11-1.16]), comorbidities of coronary heart disease (OR 1.78 [1.67-1.91]), stroke (OR 2.34 [2.1-1.37]), diabetes (OR 2.03 [1.89-2.18]) and a series of mental disorders. Cognitive functions in multiple tests also demonstrate decline over a decade before the diagnosis. Inadequate activity (3-5 year, overall time of activity, OR 0.82 [0.73-0.92]), drowsiness (3-5 year, sleep duration, OR 1.13 [1.04-1.24]) and weight loss (0-5 year, weight, OR 0.9 [0.83-0.98]) only exhibited associations within five years before the diagnosis. In addition, serum biomarkers of enriched endocrine, dysregulations of ketones, deficiency of brand-chain amino acids and polyunsaturated fatty acids were found in a similar prodromal time window and can be witnessed as the last pre-symptomatic conditions before the diagnosis.

INTERPRETATION

Our findings present a comprehensive temporal-diagnostic landscape preceding incident dementia, which could improve selection for preventive and early disease-modifying treatment trials.

Causal association between plasma metabolites and neurodegenerative diseases

BACKGROUND

Establishing causal relationships between metabolic biomarkers and neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) is a challenge faced by observational studies. In this study, our aim was to investigate the causal associations between plasma metabolites and neurodegenerative diseases using Mendelian Randomization (MR) methods.

METHODS

We utilized genetic associations with 1400 plasma metabolic traits as exposures. We used large-scale genome-wide association study (GWAS) summary statistics for AD and PD as our discovery datasets. For validation, we performed repeated analyses using different GWAS datasets. The main statistical method employed was inverse variance-weighted (IVW). We also conducted enrichment pathway analysis for IVW-identified metabolites.

RESULTS

In the discovered dataset, there are a total of 69 metabolites (36 negatively, 33 positively) potentially associated with AD, and 47 metabolites (24 negatively， 23 positively) potentially associated with PD. Among these, 4 significant metabolites overlap with significant metabolites (PIVW < 0.05)in the validation dataset for AD, and 1 metabolite overlaps with significant metabolites in the validation dataset for PD. Three metabolites serve as common potential metabolic markers for both AD and PD, including Tryptophan betaine, Palmitoleoylcarnitine (C16:1), and X-23655 levels. Further pathway enrichment analysis suggests that the SLC-mediated transmembrane transport pathway, involving tryptophan betaine and carnitine metabolites, may represent potential intervention targets for treating AD and PD.

CONCLUSION

This study offers novel insights into the causal effects of plasma metabolites on degenerative diseases through the integration of genomics and metabolomics. The identification of metabolites and metabolic pathways linked to AD and PD enhances our comprehension of the underlying biological mechanisms and presents promising targets for future therapeutic interventions in AD and PD.

Causal Association between Circulating Metabolites and Dementia: A Mendelian Randomization Study

The causal association of circulating metabolites with dementia remains uncertain. We assessed the causal association of circulating metabolites with dementia utilizing Mendelian randomization (MR) methods. We performed univariable MR analysis to evaluate the associations of 486 metabolites with dementia, Alzheimer's disease (AD), and vascular dementia (VaD) risk. For secondary validation, we replicated the analyses using an additional dataset with 123 metabolites. We observed 118 metabolites relevant to the risk of dementia, 59 of which were lipids, supporting the crucial role of lipids in dementia pathogenesis. After Bonferroni adjustment, we identified nine traits of HDL particles as potential causal mediators of dementia. Regarding dementia subtypes, protective effects were observed for epiandrosterone sulfate on AD (OR = 0.60, 95% CI: 0.48-0.75) and glycoproteins on VaD (OR = 0.89, 95% CI: 0.83-0.95). Bayesian model averaging MR (MR-BMA) analysis was further conducted to prioritize the predominant metabolites for dementia risk, which highlighted the mean diameter of HDL particles and the concentration of very large HDL particles as the predominant protective factors against dementia. Moreover, pathway analysis identified 17 significant and 2 shared metabolic pathways. These findings provide support for the identification of promising predictive biomarkers and therapeutic targets for dementia.

Resistance and Resilience to Alzheimer's Disease

Dementia is a significant public health crisis; the most common underlying cause of age-related cognitive decline and dementia is Alzheimer's disease neuropathologic change (ADNC). As such, there is an urgent need to identify novel therapeutic targets for the treatment and prevention of the underlying pathologic processes that contribute to the development of AD dementia. Although age is the top risk factor for dementia in general and AD specifically, these are not inevitable consequences of advanced age. Some individuals are able to live to advanced age without accumulating significant pathology (resistance to ADNC), whereas others are able to maintain cognitive function despite the presence of significant pathology (resilience to ADNC). Understanding mechanisms of resistance and resilience will inform therapeutic strategies to promote these processes to prevent or delay AD dementia. This article will highlight what is currently known about resistance and resilience to AD, including our current understanding of possible underlying mechanisms that may lead to candidate preventive and treatment interventions for this devastating neurodegenerative disease.

Unraveling the link between neuropathy target esterase NTE/SWS, lysosomal storage diseases, inflammation, abnormal fatty acid metabolism, and leaky brain barrier

Mutations in Drosophila Swiss cheese (SWS) gene or its vertebrate orthologue neuropathy target esterase (NTE) lead to progressive neuronal degeneration in flies and humans. Despite its enzymatic function as a phospholipase is well established, the molecular mechanism responsible for maintaining nervous system integrity remains unclear. In this study, we found that NTE/SWS is present in surface glia that forms the blood-brain barrier (BBB) and that NTE/SWS is important to maintain its structure and permeability. Importantly, BBB glia-specific expression of Drosophila NTE/SWS or human NTE in the sws mutant background fully rescues surface glial organization and partially restores BBB integrity, suggesting a conserved function of NTE/SWS. Interestingly, sws mutant glia showed abnormal organization of plasma membrane domains and tight junction rafts accompanied by the accumulation of lipid droplets, lysosomes, and multilamellar bodies. Since the observed cellular phenotypes closely resemble the characteristics described in a group of metabolic disorders known as lysosomal storage diseases (LSDs), our data established a novel connection between NTE/SWS and these conditions. We found that mutants with defective BBB exhibit elevated levels of fatty acids, which are precursors of eicosanoids and are involved in the inflammatory response. Also, as a consequence of a permeable BBB, several innate immunity factors are upregulated in an age-dependent manner, while BBB glia-specific expression of NTE/SWS normalizes inflammatory response. Treatment with anti-inflammatory agents prevents the abnormal architecture of the BBB, suggesting that inflammation contributes to the maintenance of a healthy brain barrier. Considering the link between a malfunctioning BBB and various neurodegenerative diseases, gaining a deeper understanding of the molecular mechanisms causing inflammation due to a defective BBB could help to promote the use of anti-inflammatory therapies for age-related neurodegeneration.

Identification of blood metabolites associated with risk of Alzheimer's disease by integrating genomics and metabolomics data

Specific metabolites have been reported to be potentially associated with Alzheimer's disease (AD) risk. However, the comprehensive understanding of roles of metabolite biomarkers in AD etiology remains elusive. We performed a large AD metabolome-wide association study (MWAS) by developing blood metabolite genetic prediction models. We evaluated associations between genetically predicted levels of metabolites and AD risk in 39,106 clinically diagnosed AD cases, 46,828 proxy AD and related dementia (proxy-ADD) cases, and 401,577 controls. We further conducted analyses to determine microbiome features associated with the detected metabolites and characterize associations between predicted microbiome feature levels and AD risk. We identified fourteen metabolites showing an association with AD risk. Five microbiome features were further identified to be potentially related to associations of five of the metabolites. Our study provides new insights into the etiology of AD that involves blood metabolites and gut microbiome, which warrants further investigation.

Metabolomics and Risk of Dementia: A Systematic Review of Prospective Studies

BACKGROUND

The projected increase in the prevalence of dementia has sparked interest in understanding the pathophysiology and underlying causal factors in its development and progression. Identifying novel biomarkers in the preclinical or prodromal phase of dementia may be important for predicting early disease risk. Applying metabolomic techniques to prediagnostic samples in prospective studies provides the opportunity to identify potential disease biomarkers.

OBJECTIVE

The objective of this systematic review was to summarize the evidence on the associations between metabolite markers and risk of dementia and related dementia subtypes in human studies with a prospective design.

DESIGN

We searched PubMed, PsycINFO, and Web of Science databases from inception through December 8, 2023. Thirteen studies (mean/median follow-up years: 2.1-21.0 y) were included in the review.

RESULTS

Several metabolites detected in biological samples, including amino acids, fatty acids, acylcarnitines, lipid and lipoprotein variations, hormones, and other related metabolites, were associated with risk of developing dementia. Our systematic review summarized the adjusted associations between metabolites and dementia risk; however, our findings should be interpreted with caution because of the heterogeneity across the included studies and potential sources of bias. Further studies are warranted with well-designed prospective cohort studies that have defined study populations, longer follow-up durations, the inclusion of additional diverse biological samples, standardization of techniques in metabolomics and ascertainment methods for diagnosing dementia, and inclusion of other related dementia subtypes.

CONCLUSIONS

This study contributes to the limited systematic reviews on metabolomics and dementia by summarizing the prospective associations between metabolites in prediagnostic biological samples with dementia risk. Our review discovered additional metabolite markers associated with the onset of developing dementia and may help aid in the understanding of dementia etiology. The protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (https://www.crd.york.ac.uk/prospero/; registration ID: CRD42022357521).

Association Between Improved Serum Fatty Acid Profiles and Cognitive Function During a Dietary Intervention Trial in Relapsing-Remitting Multiple Sclerosis

BACKGROUND

Cognitive impairment is a common multiple sclerosis (MS)-related symptom that impacts quality of life (QOL). Diet interventions are shown to be beneficial in managing QOL, and the intake of essential fatty acids is linked with improved cognitive function. However, the effect of diets on serum fatty acid profiles and cognitive function is unknown.

METHODS

A previous randomized, parallel-arm trial recruited participants with relapsing-remitting MS (N = 77). Study visits included 4 time points: run-in, baseline, 12 weeks, and 24 weeks. During the run-in phase, participants followed their usual diet and were then randomly assigned to either a modified paleolithic (Wahls) or a low saturated fat (Swank) diet at baseline. Assessments at study visits included cognitive function assessed by Symbol Digit Modalities Test-Oral (SDMT-O) and Perceived Deficits Questionnaire (PDQ), and serum fatty acids, including eicosapentaenoic (EPA), docosahexaenoic (DHA), and arachidonic (ARA) acids.

RESULTS

Both groups had significant improvements in all serum fatty acids (P < .01), except for ARA, as well as SDMT-O at 24-weeks (P < .05), total PDQ at 12 and 24 weeks (P < .01) compared with baseline values. The 12-week changes in ω-3 (EPA + DHA) index and EPA serum fatty acids were associated with SDMT-O changes (P ≤ .05); however, the changes in fatty acid levels did not mediate the effect of the diets on SDMT-O or PDQ (P > .05).

CONCLUSIONS

Both diets led to improvements in serum fatty acid profiles and cognitive function, with associations between the 12-week ω-3 (EPA + DHA) index and EPA changes with SDMT-O.

Investigating metabolic dysregulation in serum of triple transgenic Alzheimer's disease male mice: implications for pathogenesis and potential biomarkers

Alzheimer's disease (AD) is a multifactorial neurodegenerative disease that lacks convenient and accessible peripheral blood diagnostic markers and effective drugs. Metabolic dysfunction is one of AD risk factors, which leaded to alterations of various metabolites in the body. Pathological changes of the brain can be reflected in blood metabolites that are expected to explain the disease mechanisms or be candidate biomarkers. The aim of this study was to investigate the changes of targeted metabolites within peripheral blood of AD mouse model, with the purpose of exploring the disease mechanism and potential biomarkers. Targeted metabolomics was used to quantify 256 metabolites in serum of triple transgenic AD (3 × Tg-AD) male mice. Compared with controls, 49 differential metabolites represented dysregulation in purine, pyrimidine, tryptophan, cysteine and methionine and glycerophospholipid metabolism. Among them, adenosine, serotonin, N-acetyl-5-hydroxytryptamine, and acetylcholine play a key role in regulating neural transmitter network. The alteration of S-adenosine-L-homocysteine, S-adenosine-L-methionine, and trimethylamine-N-oxide in AD mice serum can served as indicator of AD risk. The results revealed the changes of metabolites in serum, suggesting that metabolic dysregulation in periphery in AD mice may be related to the disturbances in neuroinhibition, the serotonergic system, sleep function, the cholinergic system, and the gut microbiota. This study provides novel insights into the dysregulation of several key metabolites and metabolic pathways in AD, presenting potential avenues for future research and the development of peripheral biomarkers.

Circulating Lipoproteins Mediate the Association Between Cardiovascular Risk Factors and Cognitive Decline: A Community-Based Cohort Study

Cardiovascular health metrics are now widely recognized as modifiable risk factors for cognitive decline and dementia. Metabolic perturbations might play roles in the linkage of cardiovascular diseases and dementia. Circulating metabolites profiling by metabolomics may improve understanding of the potential mechanism by which cardiovascular risk factors contribute to cognitive decline. In a prospective community-based cohort in China (n = 725), 312 serum metabolic phenotypes were quantified, and cardiovascular health score was calculated including smoking, exercise, sleep, diet, body mass index, blood pressure, and blood glucose. Cognitive function assessments were conducted in baseline and follow-up visits to identify longitudinal cognitive decline. A better cardiovascular health was significantly associated with lower risk of concentration decline and orientation decline (hazard ratio (HR): 0.84-0.90; p < 0.05). Apolipoprotein-A1, high-density lipoprotein (HDL) cholesterol, cholesterol ester, and phospholipid concentrations were significantly associated with a lower risk of longitudinal memory and orientation decline (p < 0.05 and adjusted-p < 0.20). Mediation analysis suggested that the negative association between health status and the risk of orientation decline was partly mediated by cholesterol ester and total lipids in HDL-2 and -3 (proportion of mediation: 7.68-8.21%, both p < 0.05). Cardiovascular risk factors were associated with greater risks of cognitive decline, which were found to be mediated by circulating lipoproteins, particularly the medium-size HDL components. These findings underscore the potential of utilizing lipoproteins as targets for early stage dementia screening and intervention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00120-2.

NMR analysis seeking for cognitive decline and dementia metabolic markers in plasma from aged individuals

BACKGROUND

Blood biomarkers can improve the ability to diagnose dementia, providing new information to better understand the pathophysiology and causes of the disease. Some studies with patients have already shown changes in metabolic profiles among patients with pathological cognitive decline or Alzheimer's disease, when compared to individuals with normal cognition.

METHODS

To search for new metabolic biomarkers of dementia, we analyzed serum levels of several metabolites, measured by nuclear magnetic resonance spectroscopy, in elderly individuals, a group with normal cognitive decline (control), and three other groups with cognitive decline. pathological (low, moderate, and severe).

RESULTS

Decreased plasma levels of tyrosine, glutamate, valine, leucine, and isoleucine are associated with worsening of pathological cognitive decline. However, the area under analysis of receptor operating characteristics suggests that tyrosine and glutamate have low specificity and sensitivity. Valine, leucine, and isoleucine are influenced by blood glucose or diabetes, but these conditions do not seem to be of great influence in the differences observed. Isobutyrate, histidine, acetone and unknown-1 metabolite also decrease their plasma levels with increasing CD. Isobutyrate ad histidine could have neuroprotective and antioxidant actions, respectively. To elucidate the role of decreased unknown metabolite-1 as a CD biomarker, it will be necessary to previously investigate its identity. To define and elucidate the role of acetone in pathological CD, additional laboratory and clinical studies must be performed. All these metabolites together may constitute a set of biomarkers with capability to identify pathological CD or dementia.

SIGNIFICANCE AND NOVELTY

Decrease of glutamate, tyrosine, valine, leucine, isoleucine, histidine, isobutyrate, acetone and unknown-1 metabolite together are a set of biomarkers able to identify pathological CD or dementia. Histidine, isobutyrate, acetone and unknown-1 metabolite are more specific biomarkers of CD.

Plasma metabolites distinguish dementia with Lewy bodies from Alzheimer's disease: a cross-sectional metabolomic analysis

Background

In multifactorial diseases, alterations in the concentration of metabolites can identify novel pathological mechanisms at the intersection between genetic and environmental influences. This study aimed to profile the plasma metabolome of patients with dementia with Lewy bodies (DLB) and Alzheimer's disease (AD), two neurodegenerative disorders for which our understanding of the pathophysiology is incomplete. In the clinical setting, DLB is often mistaken for AD, highlighting a need for accurate diagnostic biomarkers. We therefore also aimed to determine the overlapping and differentiating metabolite patterns associated with each and establish whether identification of these patterns could be leveraged as biomarkers to support clinical diagnosis.

Methods

A panel of 630 metabolites (Biocrates MxP Quant 500) and a further 232 metabolism indicators (biologically informative sums and ratios calculated from measured metabolites, each indicative for a specific pathway or synthesis; MetaboINDICATOR) were analyzed in plasma from patients with probable DLB (n = 15; age 77.6 ± 8.2 years), probable AD (n = 15; 76.1 ± 6.4 years), and age-matched cognitively healthy controls (HC; n = 15; 75.2 ± 6.9 years). Metabolites were quantified using a reversed-phase ultra-performance liquid chromatography column and triple-quadrupole mass spectrometer in multiple reaction monitoring (MRM) mode, or by using flow injection analysis in MRM mode. Data underwent multivariate (PCA analysis), univariate and receiving operator characteristic (ROC) analysis. Metabolite data were also correlated (Spearman r) with the collected clinical neuroimaging and protein biomarker data.

Results

The PCA plot separated DLB, AD and HC groups (R2 = 0.518, Q2 = 0.348). Significant alterations in 17 detected metabolite parameters were identified (q ≤ 0.05), including neurotransmitters, amino acids and glycerophospholipids. Glutamine (Glu; q = 0.045) concentrations and indicators of sphingomyelin hydroxylation (q = 0.039) distinguished AD and DLB, and these significantly correlated with semi-quantitative measurement of cardiac sympathetic denervation. The most promising biomarker differentiating AD from DLB was Glu:lysophosphatidylcholine (lysoPC a 24:0) ratio (AUC = 0.92; 95%CI 0.809-0.996; sensitivity = 0.90; specificity = 0.90).

Discussion

Several plasma metabolomic aberrations are shared by both DLB and AD, but a rise in plasma glutamine was specific to DLB. When measured against plasma lysoPC a C24:0, glutamine could differentiate DLB from AD, and the reproducibility of this biomarker should be investigated in larger cohorts.

High-Fat Diets in Animal Models of Alzheimer's Disease: How Can Eating Too Much Fat Increase Alzheimer's Disease Risk?

High dietary intake of saturated fatty acids is a suspected risk factor for neurodegenerative diseases, including Alzheimer's disease (AD). To decipher the causal link behind these associations, high-fat diets (HFD) have been repeatedly investigated in animal models. Preclinical studies allow full control over dietary composition, avoiding ethical concerns in clinical trials. The goal of the present article is to provide a narrative review of reports on HFD in animal models of AD. Eligibility criteria included mouse models of AD fed a HFD defined as > 35% of fat/weight and western diets containing > 1% cholesterol or > 15% sugar. MEDLINE and Embase databases were searched from 1946 to August 2022, and 32 preclinical studies were included in the review. HFD-induced obesity and metabolic disturbances such as insulin resistance and glucose intolerance have been replicated in most studies, but with methodological variability. Most studies have found an aggravating effect of HFD on brain Aβ pathology, whereas tau pathology has been much less studied, and results are more equivocal. While most reports show HFD-induced impairment on cognitive behavior, confounding factors may blur their interpretation. In summary, despite conflicting results, exposing rodents to diets highly enriched in saturated fat induces not only metabolic defects, but also cognitive impairment often accompanied by aggravated neuropathological markers, most notably Aβ burden. Although there are important variations between methods, particularly the lack of diet characterization, these studies collectively suggest that excessive intake of saturated fat should be avoided in order to lower the incidence of AD.

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).

Gut microbiota-driven metabolic alterations reveal gut-brain communication in Alzheimer's disease model mice

The gut microbiota (GM) and its metabolites affect the host nervous system and are involved in the pathogeneses of various neurological diseases. However, the specific GM alterations under pathogenetic pressure and their contributions to the "microbiota - metabolite - brain axis" in Alzheimer's disease (AD) remain unclear. Here, we investigated the GM and the fecal, serum, cortical metabolomes in APP/PS1 and wild-type (WT) mice, revealing distinct hub bacteria in AD mice within scale-free GM networks shared by both groups. Moreover, we identified diverse peripheral - central metabolic landscapes between AD and WT mice that featured bile acids (e.g. deoxycholic and isodeoxycholic acid) and unsaturated fatty acids (e.g. 11Z-eicosenoic and palmitoleic acid). Machine-learning models revealed the relationships between the differential/hub bacteria and these metabolic signatures from the periphery to the brain. Notably, AD-enriched Dubosiella affected AD occurrence via cortical palmitoleic acid and vice versa. Considering the transgenic background of the AD mice, we propose that Dubosiella enrichment impedes AD progression via the synthesis of palmitoleic acid, which has protective properties against inflammation and metabolic disorders. We identified another association involving fecal deoxycholic acid-mediated interactions between the AD hub bacteria Erysipelatoclostridium and AD occurrence, which was corroborated by the correlation between deoxycholate levels and cognitive scores in humans. Overall, this study elucidated the GM network alterations, contributions of the GM to peripheral - central metabolic landscapes, and mediatory roles of metabolites between the GM and AD occurrence, thus revealing the critical roles of bacteria in AD pathogenesis and gut - brain communications under pathogenetic pressure.

Mendelian Randomization of Blood Metabolites Suggests Circulating Glutamine Protects Against Late-Onset Alzheimer's Disease

Background

Late-onset Alzheimer's disease (LOAD) represents a growing health burden. Previous studies suggest that blood metabolite levels influence risk of LOAD.

Objective

We used a genetics-based study design which may overcome limitations of other epidemiological studies to assess the influence of metabolite levels on LOAD risk.

Methods

We applied Mendelian randomization (MR) to evaluate bi-directional causal effects using summary statistics from the largest genome-wide association studies (GWAS) of 249 blood metabolites (n = 115,082) and GWAS of LOAD (ncase = 21,982, ncontrol = 41,944).

Results

MR analysis of metabolites as exposures revealed a negative association of genetically-predicted glutamine levels with LOAD (Odds Ratio (OR) = 0.83, 95% CI = 0.73, 0.92) that was consistent in multiple sensitivity analyses. We also identified a positive association of genetically-predicted free cholesterol levels in small LDL (OR = 1.79, 95% CI = 1.36, 2.22) on LOAD. Using genetically-predicted LOAD as the exposure, we identified associations with phospholipids to total lipids ratio in large LDL (OR = 0.96, 95% CI = 0.94, 0.98), but not with glutamine, suggesting that the relationship between glutamine and LOAD is unidirectional.

Conclusions

Our findings support previous evidence that higher circulating levels of glutamine may be a target for protection against LOAD.

Metabolites and Cognitive Decline in a Puerto Rican Cohort

Background

Recent studies have identified plasma metabolites associated with cognitive decline and Alzheimer's disease; however, little research on this topic has been conducted in Latinos, especially Puerto Ricans.

Objective

This study aims to add to the growing body of metabolomics research in Latinos to better understand and improve the health of this population.

Methods

We assessed the association between plasma metabolites and global cognition over 12 years of follow-up in 736 participants of the Boston Puerto Rican Health Study (BPRHS). Metabolites were measured with untargeted metabolomic profiling (Metabolon, Inc) at baseline. We used covariable adjusted linear mixed models (LMM) with a metabolite * time interaction term to identify metabolites (of 621 measured) associated with ∼12 years cognitive trajectory.

Results

We observed strong inverse associations between medium-chain fatty acids, caproic acid, and the dicarboxylic acids, azelaic and sebacic acid, and global cognition. N-formylphenylalanine, a tyrosine pathway metabolite, was associated with improvement in cognitive trajectory.

Conclusions

The metabolites identified in this study are generally consistent with prior literature and highlight a role medium chain fatty acid and tyrosine metabolism in cognitive decline.

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.

Cerebrospinal and Blood Biomarkers in Alzheimer's Disease: Did Mild Cognitive Impairment Definition Affect Their Clinical Usefulness?

Despite Alzheimer's Disease (AD) being known from the times of Alois Alzheimer, who lived more than one century ago, many aspects of the disease are still obscure, including the pathogenesis, the clinical spectrum definition, and the therapeutic approach. Well-established biomarkers for AD come from the histopathological hallmarks of the disease, which are Aβ and phosphorylated Tau protein aggregates. Consistently, cerebrospinal fluid (CSF) Amyloid β (Aβ) and phosphorylated Tau level measurements are currently used to detect AD presence. However, two central biases affect these biomarkers. Firstly, incomplete knowledge of the pathogenesis of diseases legitimates the search for novel molecules that, reasonably, could be expressed by neurons and microglia and could be detected in blood simpler and earlier than the classical markers and in a higher amount. Further, studies have been performed to evaluate whether CSF biomarkers can predict AD onset in Mild Cognitive Impairment (MCI) patients. However, the MCI definition has changed over time. Hence, the studies on MCI patients seem to be biased at the beginning due to the imprecise enrollment and heterogeneous composition of the miscellaneous MCI subgroup. Plasma biomarkers and novel candidate molecules, such as microglia biomarkers, have been tentatively investigated and could represent valuable targets for diagnosing and monitoring AD. Also, novel AD markers are urgently needed to identify molecular targets for treatment strategies. This review article summarizes the main CSF and blood AD biomarkers, underpins their advantages and flaws, and mentions novel molecules that can be used as potential biomarkers for AD.

Assessing the Biological Mechanisms Linking Smoking Behavior and Cognitive Function: A Mediation Analysis of Untargeted Metabolomics

(1) Smoking is the most significant preventable health hazard in the modern world. It increases the risk of vascular problems, which are also risk factors for dementia. In addition, toxins in cigarettes increase oxidative stress and inflammation, which have both been linked to the development of Alzheimer's disease and related dementias (ADRD). This study identified potential mechanisms of the smoking-cognitive function relationship using metabolomics data from the longitudinal Wisconsin Registry for Alzheimer's Prevention (WRAP). (2) 1266 WRAP participants were included to assess the association between smoking status and four cognitive composite scores. Next, untargeted metabolomic data were used to assess the relationships between smoking and metabolites. Metabolites significantly associated with smoking were then tested for association with cognitive composite scores. Total effect models and mediation models were used to explore the role of metabolites in smoking-cognitive function pathways. (3) Plasma N-acetylneuraminate was associated with smoking status Preclinical Alzheimer Cognitive Composite 3 (PACC3) and Immediate Learning (IMM). N-acetylneuraminate mediated 12% of the smoking-PACC3 relationship and 13% of the smoking-IMM relationship. (4) These findings provide links between previous studies that can enhance our understanding of potential biological pathways between smoking and cognitive function.

Development of a diagnostic and risk prediction model for Alzheimer's disease through integration of single-cell and bulk transcriptomic analysis of glutamine metabolism

Background

In this study, we present a novel system for quantifying glutamine metabolism (GM) to enhance the effectiveness of Alzheimer's disease (AD) diagnosis and risk prediction.

Methods

Single-cell RNA sequencing (scRNA-seq) analysis was utilized to comprehensively assess the expression patterns of GM. The WGCNA algorithm was applied to investigate the most significant genes related to GM. Subsequently, three machine learning algorithms (Boruta, LASSO, and SVM-RFE) were employed to identify GM-associated characteristic genes and develop a risk model. Patients were divided into high- and low-risk groups based on this model. Moreover, we explored biological properties, distinct signaling pathways, and immunological characteristics of AD patients at different risk levels. Finally, in vitro and in vivo models of AD were constructed to validate the characteristics of the feature genes.

Results

Both scRNA-seq and bulk transcriptomic analyses revealed increased GM activity in AD patients, specifically in certain cell subsets (pDC, Tem/Effector helper T cells (LTB), and plasma cells). Cells with higher GM scores demonstrated more significant numbers and strengths of interactions with other cell types. The WGCNA algorithm identified 360 genes related to GM, and a risk score was constructed based on nine characteristic genes (ATP13A4, PIK3C2A, CD164, PHF1, CES2, PDGFB, LCOR, TMEM30A, and PLXNA1) identified through multiple machine learning algorithms displayed reliable diagnostic efficacy for AD onset. Nomograms, calibration curves, and decision curve analysis (DCA) based on these characteristic genes provided significant clinical benefits for AD patients. High-risk AD patients exhibited higher levels of immune-related functions and pathways, increased immune cell infiltration, and elevated expressions of immune modulators. RT-qPCR analysis revealed that the majority of the nine characteristic genes were differentially expressed in AD-induced rat neurons. Knocking down PHF1 could protect against neurite loss and alleviate cell injury in AD neurons. In vivo, down-regulation of PHF1 in AD models decreases GM metabolism levels and modulates the immunoinflammatory response in the brain.

Conclusion

This comprehensive identification of gene expression patterns contributes to a deeper understanding of the underlying pathological mechanisms driving AD pathogenesis. Furthermore, the risk model based on the nine-gene signature offers a promising theoretical foundation for developing individualized treatments for AD patients.

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.

Association of Baseline Metabolomic Profiles With Incident Stroke and Dementia and With Imaging Markers of Cerebral Small Vessel Disease

BACKGROUND AND OBJECTIVES

Cerebral small vessel disease is a major cause of stroke and dementia. Metabolomics can help identify novel risk factors to better understand pathogenesis and predict disease progression and severity.

METHODS

We analyzed baseline metabolomic profiles from 118,021 UK Biobank participants. We examined cross-sectional associations of 325 metabolites with MRI markers of small vessel disease, evaluated longitudinal associations with incident stroke and dementia, and ascertained causal relationships using Mendelian randomization.

RESULTS

In cross-sectional analyses, lower levels of apolipoproteins, free cholesterol, cholesteryl esters, fatty acids, lipoprotein particle concentrations, phospholipids, and triglycerides were associated with increased white matter microstructural damage on diffusion tensor MRI. In longitudinal analyses, lipoprotein subclasses of very large high-density lipoprotein cholesterol (HDL) were associated with an increased risk of stroke, and acetate and 3-hydroxybutyrate were associated with an increased risk of dementia. Mendelian randomization analyses identified strong evidence supporting causal relationships for many findings. A few metabolites had consistent associations across multiple analysis types. Increased total lipids in very large HDL and increased HDL particle size were associated with increased white matter damage (lower fractional anisotropy: OR: 1.44, 95% CI 1.07-1.95, and OR: 1.19, 95% CI 1.06-1.34, respectively; mean diffusivity: OR: 1.49, 95% CI 1.11-2.01, and OR: 1.24, 95% CI 1.11-1.40, respectively) and an increased risk of incident all stroke (HR: 4.04, 95% CI 2.13-7.64, and HR: 1.54, 95% CI 1.20-1.98, respectively) and ischemic stroke (HR: 3.12, 95% CI 1.53-6.38; HR: 1.37, 95% CI 1.04-1.81). Valine was associated with decreased mean diffusivity (OR: 0.51, 95% CI 0.30-0.88) and had a protective association with all-cause dementia (HR: 0.008, 95% CI 0.002-0.035). Increased levels of cholesterol in small HDL were associated with a decreased risk of incident all stroke (HR: 0.17, 95% CI 0.08-0.39) and ischemic stroke (HR: 0.19, 95% CI 0.08-0.46) and were supported by evidence of a causal association with MRI-confirmed lacunar stroke (OR: 0.96, 95% CI 0.93-0.99).

DISCUSSION

In this large-scale metabolomics study, we found multiple metabolites associated with stroke, dementia, and MRI markers of small vessel disease. Further studies may help inform the development of personalized prediction models and provide insights into mechanistic pathways and future treatment approaches.

Association between inflammation and cognition: Triangulation of evidence using a population-based cohort and Mendelian randomization analyses

BACKGROUND

Inflammation is associated with cognitive functioning and dementia in older adults, but whether inflammation is related to cognitive functioning in youth and whether these associations are causal remains unclear.

METHODS

In a population-based cohort (Avon Longitudinal Study of Parents and Children; ALSPAC), we investigated cross-sectional associations of inflammatory markers (C-reactive protein [CRP], Interleukin-6 [IL-6] and Glycoprotein acetyls [GlycA]) with measures of cold (working memory, response inhibition) and hot (emotion recognition) cognition at age 24 (N = 3,305 in multiple imputation models). Furthermore, we conducted one-sample and two-sample bidirectional Mendelian randomization (MR) analyses to examine potential causal effects of genetically-proxied inflammatory markers (CRP, GlycA, IL-6, IL-6 receptor, soluble IL-6 receptor) on cognitive measures (above) and on general cognitive ability.

RESULTS

In the ALSPAC cohort, there was limited evidence of an association between standardised inflammatory markers and standardised cognitive measures at age 24 after adjusting for potential confounders (N = 3,305; beta range, -0.02 [95 % confidence interval (CI) -0.06 to 0.02, p = 0.27] to 0.02 [95 % CI -0.02 to 0.05, p = 0.33]). Similarly, we found limited evidence of potential effects of 1-unit increase in genetically-proxied inflammatory markers on standardised working memory, emotion recognition or response inhibition in one-sample MR using ALSPAC data (beta range, -0.73 [95 % CI -2.47 to 1.01, p = 0.41] to 0.21 [95 % CI -1.42 to 1.84, p = 0.80]; or on standardised general cognitive ability in two-sample MR using the latest Genome-Wide Association Study (GWAS) datasets (inverse-variance weighted beta range, -0.02 [95 % CI -0.05 to 0.01, p = 0.12] to 0.03 [95 % CI -0.01 to 0.07, p = 0.19]).

CONCLUSIONS

Our MR findings do not provide strong evidence of a potential causal effect of inflammatory markers (CRP, IL-6, IL-6 receptor, GlycA) on the cognitive functions examined here. Given the large confidence intervals in the one-sample MR, larger GWAS of specific cognitive measures are needed to enable well-powered MR analyses to investigate whether inflammation causally influences specific cognitive domains.

Circulating polyunsaturated fatty acids, fish oil supplementation, and risk of incident dementia: a prospective cohort study of 440,750 participants

Cohort studies report inconsistent associations between omega-3 polyunsaturated fatty acids (n-3 PUFA) or fish oil and dementia risk. Furthermore, evidence relating omega-6 polyunsaturated fatty acids (n-6 PUFA) with dementia is scarce. Here, we included 440,750 dementia-free participants from UK Biobank to comprehensively investigate the associations between plasma levels of different types of PUFA, fish oil supplementation, and dementia risk. During a median follow-up of 9.25 years, 7768 incident dementia events occurred. Higher plasma levels of five PUFA measures showed consistent associations with lower dementia risk (hazard ratios [95% confidence intervals] for per standard deviation increment of plasma concentrations 0.85 [0.81-0.89] for total PUFAs; 0.90 [0.86-0.95] for omega-3 PUFAs; 0.92 [0.87-0.96] for docosahexaenoic acid (DHA); 0.86 [0.82-0.90] for omega-6 PUFAs; 0.86 [0.82-0.90] for linoleic acid (LA); all p < 0.001). Compared with non-users, fish oil supplement users had a 7% decreased risk of developing all-cause dementia (0.93 [0.89-0.97], p = 0.002), and the relationship was partially mediated by plasma n-3 PUFA levels (omega-3 PUFAs: proportion of mediation = 57.99%; DHA: proportion of mediation = 56.95%). Furthermore, we observed significant associations of plasma n-3 PUFA levels and fish oil supplementation with peripheral immune markers that were related to dementia risk, as well as the positive associations of plasma PUFA levels with brain gray matter volumes and white matter microstructural integrity, suggesting they may affect dementia risk by affecting peripheral immunity and brain structure. Taken together, higher plasma PUFA levels and fish oil supplementation were associated with lower risk of incident dementia. This study may support the value of interventions to target PUFAs (specifically n-3 PUFAs) to prevent dementia.

Plasma metabolites associated with cognitive function across race/ethnicities affirming the importance of healthy nutrition

INTRODUCTION

We studied the replication and generalization of previously identified metabolites potentially associated with global cognitive function in multiple race/ethnicities and assessed the contribution of diet to these associations.

METHODS

We tested metabolite-cognitive function associations in U.S.A. Hispanic/Latino adults (n = 2222) from the Community Health Study/ Study of Latinos (HCHS/SOL) and in European (n = 1365) and African (n = 478) Americans from the Atherosclerosis Risk In Communities (ARIC) Study. We applied Mendelian Randomization (MR) analyses to assess causal associations between the metabolites and cognitive function and between Mediterranean diet and cognitive function.

RESULTS

Six metabolites were consistently associated with lower global cognitive function across all studies. Of these, four were sugar-related (e.g., ribitol). MR analyses provided weak evidence for a potential causal effect of ribitol on cognitive function and bi-directional effects of cognitive performance on diet.

DISCUSSION

Several diet-related metabolites were associated with global cognitive function across studies with different race/ethnicities.

HIGHLIGHTS

Metabolites associated with cognitive function in Puerto Rican adults were recently identified. We demonstrate the generalizability of these associations across diverse race/ethnicities. Most identified metabolites are related to sugars. Mendelian Randomization (MR) provides weak evidence for a causal effect of ribitol on cognitive function. Beta-cryptoxanthin and other metabolites highlight the importance of a healthy diet.

Glial Glutamine Homeostasis in Health and Disease

Glutamine is an essential cerebral metabolite. Several critical brain processes are directly linked to glutamine, including ammonia homeostasis, energy metabolism and neurotransmitter recycling. Astrocytes synthesize and release large quantities of glutamine, which is taken up by neurons to replenish the glutamate and GABA neurotransmitter pools. Astrocyte glutamine hereby sustains the glutamate/GABA-glutamine cycle, synaptic transmission and general brain function. Cerebral glutamine homeostasis is linked to the metabolic coupling of neurons and astrocytes, and relies on multiple cellular processes, including TCA cycle function, synaptic transmission and neurotransmitter uptake. Dysregulations of processes related to glutamine homeostasis are associated with several neurological diseases and may mediate excitotoxicity and neurodegeneration. In particular, diminished astrocyte glutamine synthesis is a common neuropathological component, depriving neurons of an essential metabolic substrate and precursor for neurotransmitter synthesis, hereby leading to synaptic dysfunction. While astrocyte glutamine synthesis is quantitatively dominant in the brain, oligodendrocyte-derived glutamine may serve important functions in white matter structures. In this review, the crucial roles of glial glutamine homeostasis in the healthy and diseased brain are discussed. First, we provide an overview of cellular recycling, transport, synthesis and metabolism of glutamine in the brain. These cellular aspects are subsequently discussed in relation to pathological glutamine homeostasis of hepatic encephalopathy, epilepsy, Alzheimer's disease, Huntington's disease and amyotrophic lateral sclerosis. Further studies on the multifaceted roles of cerebral glutamine will not only increase our understanding of the metabolic collaboration between brain cells, but may also aid to reveal much needed therapeutic targets of several neurological pathologies.

Metabolomic analysis of vascular cognitive impairment due to hepatocellular carcinoma

Introduction

Screening for metabolically relevant differentially expressed genes (DEGs) shared by hepatocellular carcinoma (HCC) and vascular cognitive impairment (VCI) to explore the possible mechanisms of HCC-induced VCI.

Methods

Based on metabolomic and gene expression data for HCC and VCI, 14 genes were identified as being associated with changes in HCC metabolites, and 71 genes were associated with changes in VCI metabolites. Multi-omics analysis was used to screen 360 DEGs associated with HCC metabolism and 63 DEGs associated with VCI metabolism.

Results

According to the Cancer Genome Atlas (TCGA) database, 882 HCC-associated DEGs were identified and 343 VCI-associated DEGs were identified. Eight genes were found at the intersection of these two gene sets: NNMT, PHGDH, NR1I2, CYP2J2, PON1, APOC2, CCL2, and SOCS3. The HCC metabolomics prognostic model was constructed and proved to have a good prognostic effect. The HCC metabolomics prognostic model was constructed and proved to have a good prognostic effect. Following principal component analyses (PCA), functional enrichment analyses, immune function analyses, and TMB analyses, these eight DEGs were identified as possibly affecting HCC-induced VCI and the immune microenvironment. As well as gene expression and gene set enrichment analyses (GSEA), a potential drug screen was conducted to investigate the possible mechanisms involved in HCC-induced VCI. The drug screening revealed the potential clinical efficacy of A-443654, A-770041, AP-24534, BI-2536, BMS- 509744, CGP-60474, and CGP-082996.

Conclusion

HCC-associated metabolic DEGs may influence the development of VCI in HCC patients.

Association Between Triglycerides and Incident Cognitive Impairment in Black and White Adults in the Reasons for Geographic and Racial Differences in Stroke Study

Background Elevated nonfasting triglycerides were associated with non-Alzheimer dementia in a recent study. However, this study neither evaluated the association of fasting triglycerides with incident cognitive impairment (ICI) nor adjusted for high-density lipoprotein cholesterol or hs-CRP (high-sensitivity C-reactive protein), known risk markers for ICI and dementia. Methods and Results We examined the association between fasting triglycerides and ICI among 16 170 participants in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study without cognitive impairment or a history of stroke at baseline in 2003 to 2007 and who had no stroke events during follow-up through September 2018. Overall, 1151 participants developed ICI during the median follow-up of 9.6 years. The relative risk for ICI associated with fasting triglycerides of ≥150 mg/dL versus <100 mg/dL including adjustment for age and geographic region of residence was 1.59 (95% CI, 1.20-2.11) among White women and 1.27 (95% CI, 1.00-1.62) among Black women. After multivariable adjustment, including adjustment for high-density lipoprotein cholesterol and hs-CRP, the relative risk for ICI associated with fasting triglycerides ≥150 mg/dL versus <100 mg/dL was 1.50 (95% CI, 1.09-2.06) among White women and 1.21 (95% CI, 0.93-1.57) among Black women. There was no evidence of an association between triglycerides and ICI among White or Black men. Conclusions Elevated fasting triglycerides were associated with ICI in White women after full adjustment including high-density lipoprotein cholesterol and hs-CRP. The current results suggest that the association between triglycerides and ICI is stronger in women than men.

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Alzheimer's disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

Ferulic acid alleviates high fat diet-induced cognitive impairment by inhibiting oxidative stress and apoptosis

Cognitive impairment has become a major public health problem. Growing evidence suggests that high-fat diet (HFD) can cause cognitive dysfunction and increase the risk of dementia. However, effective treatment for cognitive impairment is not available. Ferulic acid (FA) is a single phenolic compound with anti-inflammatory and antioxidant properties. Nevertheless, its role in regulating learning and memory in HFD-fed mice and the underlying mechanism remains unclear. In this study, we aimed to identify the neuroprotective mechanisms of FA in HFD induced cognitive impairment. We found that FA improved the survival rate of HT22 cells treated with palmitic acid (PA), inhibited cell apoptosis, and reduced oxidative stress via the IRS1/PI3K/AKT/GSK3β signaling pathway; Furthermore, FA treatment for 24 weeks improved the learning and memory of HFD-fed mice and decreased hyperlipidemia. Moreover, the expression of Nrf2 and Gpx4 proteins were decreased in HFD-fed mice. After FA treatment, the decline of these proteins was reversed. Our study showed that the neuroprotective effect of FA on cognitive impairment was related to the inhibition of oxidative stress and apoptosis and regulation of glucose and lipid metabolism. These findings suggested that FA can be developed as a potential agent for the treatment of HFD-induced cognitive impairment.

Investigating the plasma-liver-brain axis of omega-3 fatty acid metabolism in mouse knock-in for the human apolipoprotein E epsilon 4 allele

The metabolism of docosahexaenoic acid (DHA), an omega-3 fatty acid, is different in carriers of APOE4, the main genetic risk factor for late-onset Alzheimer's disease. The brain relies on the plasma DHA pool for its need, but the plasma-liver-brain axis in relation to cognition remains obscure. We hypothesized that this relationship is compromised in APOE4 mice considering the differences in fatty acid metabolism between APOE3 and APOE4 mice. Male and female APOE3 and APOE4 mice were fed either a diet enriched with DHA (0.7 g DHA/100 g diet) or a control diet for 8 months. There was a significant genotype × diet interaction for DHA concentration in the liver and adipose tissue. In the cortex, a genotype effect was found where APOE4 mice had a higher concentration of DHA than APOE3 mice fed the control diet. There was a significant genotype × diet interaction for the liver and hippocampal arachidonic acid (AA). APOE4 mice had 20-30% lower plasma DHA and AA concentrations than APOE3 mice, independent of diet. Plasma and liver DHA levels were significantly correlated in APOE3 and APOE4 mice. In APOE4 mice, there was a significant correlation between plasma, adipose tissues, cortex DHA and the Barnes maze and/or with a better recognition index. Moreover, higher AA levels in the liver and the hippocampus of APOE4 mice were correlated with lower cognitive performance. Our results suggest that there is a plasma-liver-brain axis of DHA that is modified in APOE4 mice. Moreover, our data support that APOE4 mice rely more on plasma DHA than APOE3 mice, especially in cognitive performance. Any disturbance in plasma DHA metabolism might have a greater impact on cognition in APOE4 carriers.

Does ethnicity influence dementia, stroke and mortality risk? Evidence from the UK Biobank

Introduction

The number of people with dementia and stroke is increasing worldwide. There is increasing evidence that there are clinically relevant genetic differences across ethnicities. This study aims to quantify risk factors of dementia, stroke, and mortality in Asian and black participants compared to whites.

Methods

272,660 participants from the UK Biobank were included in the final analysis, among whom the vast majority are white (n = 266,671, 97.80%), followed by Asian (n = 3,790, 1.35%), and black (n = 2,358, 0.84%) participants. Cumulative incidence risk was calculated based on all incident cases occurring during the follow-up of the individuals without dementia and stroke at baseline. We compared the allele frequency of variants in Asian and black participants with the referent ethnicity, whites, by chi-square test. Hierarchical cluster analysis was used in the clustering analysis. Significance level corrected for the false discovery rate was considered.

Results

After adjusting for risk factors, black participants have an increased risk of dementia and stroke compared to white participants, while Asians has similar odds to the white. The risk of mortality is not different in blacks and white participants but Asians have a decreased risk.

Discussion

The study provides important insights into the potential differences in the risk of dementia and stroke among different ethnic groups. Specifically, the study found that black individuals had a higher incidence of dementia and stroke compared to white individuals living in the UK. These findings are particularly significant as they suggest that there may be underlying factors that contribute to these differences, including genetic, environmental, and social factors. By identifying these differences, the study helps to inform interventions and policies aimed at reducing the risk of dementia and stroke, particularly among high-risk populations.

Association of Red Blood Cell Omega-3 Fatty Acids With MRI Markers and Cognitive Function in Midlife: The Framingham Heart Study

BACKGROUND AND OBJECTIVES

Diet may be a key contributor to brain health in midlife. In particular, omega-3 fatty acids have been related to better neurologic outcomes in older adults. However, studies focusing on midlife are lacking. We investigated the cross-sectional association of red blood cell (RBC) omega-3 fatty acid concentrations with MRI and cognitive markers of brain aging in a community-based sample of predominantly middle-aged adults and further explore effect modification by APOE genotype.

METHODS

We included participants from the Third-Generation and Omni 2 cohorts of the Framingham Heart Study attending their second examination. Docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) concentrations were measured from RBC using gas chromatography, and the Omega-3 index was calculated as EPA + DHA. We used linear regression models to relate omega-3 fatty acid concentrations to brain MRI measures (i.e., total brain, total gray matter, hippocampal, and white matter hyperintensity volumes) and cognitive function (i.e., episodic memory, processing speed, executive function, and abstract reasoning) adjusting for potential confounders. We further tested for interactions between omega-3 fatty acid levels and APOE genotype (e4 carrier vs noncarrier) on MRI and cognitive outcomes.

RESULTS

We included 2,183 dementia-free and stroke-free participants (mean age of 46 years, 53% women, 22% APOE-e4 carriers). In multivariable models, higher Omega-3 index was associated with larger hippocampal volumes (standard deviation unit beta ±standard error; 0.003 ± 0.001, p = 0.013) and better abstract reasoning (0.17 ± 0.07, p = 0.013). Similar results were obtained for DHA or EPA concentrations individually. Stratification by APOE-e4 status showed associations between higher DHA concentrations or Omega-3 index and larger hippocampal volumes in APOE-e4 noncarriers, whereas higher EPA concentrations were related to better abstract reasoning in APOE-e4 carriers. Finally, higher levels of all omega-3 predictors were related to lower white matter hyperintensity burden but only in APOE-e4 carriers.

DISCUSSION

Our results, albeit exploratory, suggest that higher omega-3 fatty acid concentrations are related to better brain structure and cognitive function in a predominantly middle-aged cohort free of clinical dementia. These associations differed by APOE genotype, suggesting potentially different metabolic patterns by APOE status. Additional studies in middle-aged populations are warranted to confirm these findings.

Metabolomic profiles predict individual multidisease outcomes

Risk stratification is critical for the early identification of high-risk individuals and disease prevention. Here we explored the potential of nuclear magnetic resonance (NMR) spectroscopy-derived metabolomic profiles to inform on multidisease risk beyond conventional clinical predictors for the onset of 24 common conditions, including metabolic, vascular, respiratory, musculoskeletal and neurological diseases and cancers. Specifically, we trained a neural network to learn disease-specific metabolomic states from 168 circulating metabolic markers measured in 117,981 participants with ~1.4 million person-years of follow-up from the UK Biobank and validated the model in four independent cohorts. We found metabolomic states to be associated with incident event rates in all the investigated conditions, except breast cancer. For 10-year outcome prediction for 15 endpoints, with and without established metabolic contribution, a combination of age and sex and the metabolomic state equaled or outperformed established predictors. Moreover, metabolomic state added predictive information over comprehensive clinical variables for eight common diseases, including type 2 diabetes, dementia and heart failure. Decision curve analyses showed that predictive improvements translated into clinical utility for a wide range of potential decision thresholds. Taken together, our study demonstrates both the potential and limitations of NMR-derived metabolomic profiles as a multidisease assay to inform on the risk of many common diseases simultaneously.