Investigating the relationship of circulating lipidome profiles with cross-sectional and longitudinal changes of central Alzheimer's disease (AD) biomarkers, including amyloid/tau/neurodegeneration (A/T/N), can provide a holistic view between the lipidome and AD pathophysiology. In this study, we quantified a total of 749 plasma lipid species at baseline using liquid chromatography-mass spectrometry and performed cross-sectional and longitudinal association analysis of plasma lipidome profiles with longitudinal A/T/N biomarkers for AD in the Alzheimer's Disease Neuroimaging Initiative cohort (N = 1395). We identified several lipid species, classes, and network modules of correlated lipids that were significantly associated with cross-sectional and longitudinal changes of A/T/N biomarkers. Notably, we identified lysoalkylphosphatidylcholine (LPC(O)) as associated with cross-sectional "A/N" biomarkers at the lipid species, class, and module levels. Also, Phosphatidylethanolamine (PE) ethers were associated with A/T/N biomarkers in the species level and with "N" biomarkers in the class and module levels. GM3 ganglioside showed association with cross-sectional and longitudinal changes of "N" biomarkers at the species and class levels. Furthermore, 20 lipid species, out of all 57 species identified as associated with "less severe" AD biomarkers, contained docosahexaenoic acid (DHA), indicating that the previously reported beneficial effects of DHA on AD were significant at the central biomarker level. In conclusion, our approach linking peripheral metabolic changes with brain metabolic, structural, and functional states strengthens evidence from previous studies that were performed using only clinical AD diagnosis. Importantly, our study also enabled identification of novel lipids that play potential roles in progression of AD pathophysiology, suggesting dysregulation of lipid metabolic pathways as precursors to AD development and progression.

Biological age scores capture ageing heterogeneity beyond chronological age but are often dominated by lifestyle and environmental exposures, limiting clinical interpretability. We developed an environmentally adjusted metabolic age score (EAmAge) to isolate intrinsic ageing biology relevant to neurodegeneration and chronic disease. Major environmental influences were statistically removed from plasma lipidomic profiles before constructing an age-prediction model using ridge regression. EAmAge was derived in the AusDiab cohort (n = 10,339) and validated across three independent cohorts (BHS, ADNI and ASPREE; total n = 9,835). Compared with an unadjusted lipidomic age model (mAge_orig), EAmAge showed stronger and more consistent associations with incident Alzheimer’s disease-related dementia, cardiovascular events and all-cause mortality. EAmAge was also associated with Alzheimer’s disease-related biomarkers, including amyloid burden, reduced glucose metabolism and hippocampal atrophy. These findings establish EAmAge as a robust and partially modifiable biomarker that improves risk stratification by disentangling intrinsic metabolic ageing from environmental confounding.

Cognitive impairment is increasing with global aging, yet mechanisms linking diet, the gut microbiome, and metabolism to cognitive function remain unclear. To investigate a diet-microbiome-metabolome axis associated with cognition, we integrated fecal metagenomics, diet, and multi-platform plasma metabolomics in 505 older adults from four ADRCs. Several microbes broadly associated with circulating metabolites were also linked to multiple measures of cognitive performance. These taxa exhibited coordinated metabolic signatures, with cognition-positive microbes associated with antioxidant, lipid, and microbial-host co-metabolites, and microbes negatively associated with cognition were linked to inflammatory and aromatic amino acid-derived metabolites. Dietary patterns, particularly the Healthy Eating Index Greens and Beans component, were associated with microbial composition and metabolomic structure. Mediation analyses supported a diet-microbe-metabolite-cognition pathway, while metabolites remained associated with cognition after accounting for microbial features. These findings highlight the metabolome as a central integrator of diet, microbial activity, and cognitive function.

Mounting evidence implicates inflammation as a key factor in Alzheimer’s disease (AD) development. We previously identified pro-inflammatory soluble epoxide hydrolase (sEH) metabolites to be elevated in plasma and CSF of AD participants and to be associated with lower cognition in non-AD subjects. Soluble epoxide hydrolase is a key enzyme converting anti-inflammatory epoxy fatty acids to pro-inflammatory diols, reported to be elevated in multiple cardiometabolic disorders. Here we analyzed over 700 fasting plasma samples from the baseline of Alzheimer’s Disease Neuroimaging Initiative (ADNI) 2/GO study. We applied targeted mass spectrometry method to provide absolute quantifications of over 150 metabolites from oxylipin and endocannabinoids pathway, interrogating the role for inflammation/immune dysregulation and the key enzyme soluble epoxide hydrolase in AD. We provide further insights into the regulation of this pathway in different disease stages, APOE genotypes and between sexes. Additionally, we investigated in mild cognitive impaired (MCI) participants, metabolic signatures that inform about resilience to progression and conversion to AD. Key findings include I) confirmed disruption in this key central pathway of inflammation and pointed to dysregulation of sEH in AD with sex and disease stage differences; II) identified markers of disease progression and cognitive resilience using sex and ApoE genotype stratified analysis highlighting an important role for bile acids, lipid peroxidation and stress response hormone cortisol. In conclusion, we provide molecular insights into a central pathway of inflammation and links to cognitive dysfunction, suggesting novel therapeutic approaches that are based on targeting inflammation tailored for subgroups of individuals based on their sex, APOE genotype and their metabolic profile.

The exposome factors, such as diet, lifestyle, microbiome, chemical exposures and social exposome, shapes human health beyond genetic influences, but the mechanisms remain only partially understood. Leveraging the Area Deprivation Index (ADI) of Neighborhood Atlas, a validated measure of the US social exposome, we derive molecular insights on how adverse social exposome (ASE) may impact cardiometabolic and brain health. Using complementary metabolomics platforms, we measured blood metabolome as readouts on net influences of exposome factors. Participants from six Alzheimer's disease research centers (n=449) were studied with generalizability confirmed in the UK Biobank using its harmonizable metric for ASE (n=380,943). Our results suggest that participants living in ASE have metabolic features often shown to predispose individuals to higher risks for cardiovascular diseases and cognitive decline, with impaired mitochondrial energetics, amino acid and lipid metabolism. Diet, microbiome and chemical exposures may contribute to these metabolic features. Molecular insights from metabolic signatures for ASE allows us to map potential modifiable risk factors that can impact and sustain health including brain health.

INTRODUCTION:Mounting evidence support exposome influences on brain function and health, complementing genome influences. Understanding the molecular imprint of exposome on brain metabolism and the biochemical communication between the body and brain can impact our fundamental understanding and treatment of neuropsychiatric diseases. METHODS:Leveraging two complementary metabolomics platforms, we classified 1400 features in 514 brains from the ROSMAP collection. We evaluated the origin of these compounds using literature and databases. We correlated those metabolites with cognitive function using linear models. RESULTS:We identified over 230 non-endogenous compounds in the brain, including 103 drugs and metabolites, 120 dietary and microbial products and possibly 15 compounds from environmental exposures. Over 20 dietary and gut microbial compounds showed associations with cognition. DISCUSSION:Comprehensive profiling of chemicals in the brain and the link to cognitive function provides foundational work to connect body and brain in the study of AD and related dementias.

The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet has been associated with cognitive benefits and reduced risk of Alzheimer's disease. Adherence is typically assessed using comprehensive but time-consuming food frequency questionnaires (FFQs). We examined concurrent validity between a brief MIND diet screener and a more extensive FFQ. 94 participants (51 cognitively normal (CN), 31 subjective cognitive decline (SCD), 12 mild cognitive impairment (MCI)) from the Indiana Alzheimer's Disease Research Center (IADRC) who participated in the Alzheimer's Gut Microbiome Project (AGMP) completed both the self-reported 15-item MIND screener and computerized Vioscreen FFQ. For both measures, we used the same cutoff criteria to assign values of 0, 0.5, or 1 corresponding to low, medium, and high intake for the ‘healthy’ food groups and reverse correspondence for the ‘unhealthy’ food groups, which were then summed to generate a total MIND diet score (0-15) with higher scores indicating greater adherence. Agreement between the two methods was assessed using Pearson correlation, intraclass correlation coefficient (ICC) for absolute agreement and consistency, and a tertile-based cross-classification. ANOVA was used to test differences in MIND scores between diagnostic groups, adjusting for age, sex, and education. The mean MIND diet score from the FFQ was 7.49 (range: 2.5-11), and from the screener was 10.05 (range: 5-13.5), with a mean 2.56-point difference showing consistently higher scores on the screener (Figure 1). The screener demonstrated moderate correlation with the FFQ score ( r  = 0.63, p  <0.001, R2=0.40). Absolute agreement was low (ICC=0.34), while consistency was moderate (ICC=0.64) (Figure 2). In cross-classification, 19.15% of individuals were classified into disparate tertiles. A significant difference was observed between CN and MCI groups using both methods, but only the screener-derived score remained marginally significant after adjustments ( p  = 0.05) (Figure 3). The MIND screener shows moderate correlation and consistency with the FFQ, with participants systematically reporting higher scores on the screener, indicating overestimation of their MIND diet score. While the screener does not capture detailed or food item specific dietary variations assessed by the FFQ, it is a valid tool for rapid estimation of MIND diet score and may be useful in research and clinical practice.

BACKGROUND:Comprehensive lipidomic studies have demonstrated strong cross-sectional associations between the blood lipidome and late-onset Alzheimer's disease (AD) dementia and its risk factors, yet the longitudinal relationship between lipidome changes and AD progression remains unclear. METHODS:We employed longitudinal lipidomic profiling on 4730 plasma samples from 1517 participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort to investigate the temporal evolution of lipidomes among diagnostic groups. At baseline (n = 1393), participants were classified as stable diagnosis status including stable AD (n = 243), stable cognitive normal (CN; n = 337), and stable mild cognitive impairment (MCI; n = 413), or converters (AD converters: n = 329; MCI converters: n = 71). We developed a dementia risk classification model to stratify the non-converting MCI group into dementia-like and non-dementia-like MCI based on their baseline lipidomic profiles, aiming to identify early metabolic signatures predictive of dementia progression. FINDINGS:Longitudinal analysis identified significant associations between the change in ether lipid species (including alkylphosphatidylcholine, alkenylphosphatidylcholine, lysoalkylphosphatidylcholine, and lysoalkenylphosphatidylcholine) and AD dementia conversion. Specifically, AD dementia converters show a 3-4.8% reduction in these ether lipid species compared to the non-converting CN and MCI groups, suggesting metabolic dysregulation as a key feature of AD progression. Further, The Dementia Risk Model effectively distinguished MCI from AD dementia converters (AUC = 0.70; 95% CI: 0.66-0.74). Within the MCI group, the model identified a high-risk subgroup with a twofold higher likelihood of conversion to AD dementia compared to the low-risk group. External validation in the ASPREE cohort confirmed its predictive utility, with the Dementia Risk Score discriminating incident dementia from cognitively normal individuals (C-index = 0.75, 95% CI: 0.73-0.78), improving prediction by 2% over the combination of traditional risk factors and APOE genetic risk factor. Additionally, the Dementia Risk Score was significantly associated with reduced temporal lobar fludeoxyglucose uptake (β = -0.286, p = 1.34 × 10-4), higher amyloid PET levels (β = 0.308, p = 4.03 × 10-4), and elevated p-tau levels (β = 0.167, p = 2.37 × 10-2), reinforcing its pathophysiological relevance in tracking neurodegeneration, amyloid burden, and tau pathology. INTERPRETATION:These findings highlight lipidomic profiling as a potential blood-based biomarker for identifying individuals at high risk of AD progression, offering a scalable, non-invasive approach for early detection, risk stratification, and targeted interventions in AD. FUNDING:The National Health and Medical Research Council of Australia (#1101320 and #1157607); NHMRC Investigator grant (#GNT1197190); Victorian Government's Operational Infrastructure Support Program; National Heart Foundation of Australia, Future Leader Fellowship (#102604), and National Health and Medical Research Council Investigator Grant (#2026325); Investigator grant (#2009965) from the National Health and Medical Research Council of Australia; a National Health and Medical Research Council of Australia Senior Research Fellowship (#1042095); National Institutes of Health grants: P30AG010133, P30AG072976, R01AG019771, R01AG057739, U19AG024904, R01LM013463, R01AG068193, T32AG071444, U01AG068057, U01AG072177, U19AG074879, R01AG069901, R01AG046171, RF1AG051550, RF1AG057452; National Institutes of Health/National Institute on Aging grants RF1AG058942, RF1AG059093, U01AG061359, U19AG063744, and R01AG081322, NIH/NLM R01LM012535; FNIH: DAOU16AMPA.

Alzheimer’s disease (AD) is a major neurodegenerative disorder with significant environmental factors, including diet and lifestyle, influencing its onset and progression. Although previous studies have suggested that certain diets may reduce the incidence of AD, the underlying mechanisms remain unclear. In this post-hoc analysis of a randomized crossover study of 20 elderly adults, we investigated the effects of a modified Mediterranean ketogenic diet (MMKD) on the plasma lipidome in the context of AD biomarkers, analyzing 784 lipid species across 47 classes using a targeted lipidomics platform. Here we identified substantial changes in response to MMKD intervention, aside from metabolic changes associated with a ketogenic diet, we identified a a global elevation across all plasmanyl and plasmenyl ether lipid species, with many changes linked to clinical and biochemical markers of AD. We further validated our findings by leveraging our prior clinical studies into lipid related changeswith AD (n = 1912), and found that the lipidomic signature with MMKD was inversely associated with the lipidomic signature of prevalent and incident AD. Intervention with a MMKD was able to alter the plasma lipidome in ways that contrast with AD-associated patterns. Given its low risk and cost, MMKD could be a promising approach for prevention or early symptomatic treatment of AD. Previous research has suggested that different diets might alter the risk of a person developing Alzheimer’s disease. We compared the blood of 20 older adults, some with memory impairment, following a change in diet. The two diets we compared were the Modified Mediterranean Ketogenic and American Heart Association Diets. The changes that were seen following consumption of the Mediterranean-ketogenic diet were the opposite to those typically seen in people with Alzheimer’s disease or those likely to develop it. These data suggest adopting this diet could potentially be a promising approach to slow down or prevent the development of Alzheimer’s disease. Aligning these results with previous larger clinical studies looking at lipids, we identified that these changes were opposite to what was typically seen in people with Alzheimer’s disease or those likely to develop it. As this diet was generally safe and inexpensive, this intervention could be a promising approach to mitigate some risk Alzheimer’s disease and help with early symptoms. Neth, Huynh et al. evaluate whether consuming a modified Mediterranean ketogenic diet alters parts of the plasma lipidome associated with development of Alzheimer’s disease (AD). Consuming the ketogenic diet alters the plasma lipidome, with changes inversely linked to Alzheimer’s disease (AD) biomarkers and lipidomic signatures.

This study investigated the relationship between gut microbiota and neuropsychiatric disorders (NPDs), specifically anxiety disorder (ANXD) and/or major depressive disorder (MDD), as defined by Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV or V criteria. The study also examined the influence of medication use, particularly antidepressants and/or anxiolytics, classified through the Anatomical Therapeutic Chemical (ATC) Classification System, on the gut microbiota. Both 16S rRNA gene amplicon sequencing (16S) and shallow shotgun sequencing (WGS) were performed on DNA extracted from 666 fecal samples from the Tulsa-1000 and Neurocomputational Mechanisms of Affiliation and Personality Study Center for Biomedical Research Excellence (NeuroMAP CoBRE) cohorts. The results highlight the significant influence of medication use; antidepressant use is associated with significant differences in gut microbiota beta diversity and has a larger effect size than NPD diagnosis. Next, specific microbes were associated with ANXD and MDD, highlighting their potential for non-pharmacological intervention. Finally, the study demonstrated the capability of Random Forest classifiers to predict diagnoses of NPD and medication use from microbial profiles, suggesting a promising direction for the use of gut microbiota as biomarkers for NPD. Though the effect sizes were larger in females than males, similar trends emerged for both sexes. These findings encourage future research on the gut microbiota’s role in NPD and its interactions with pharmacological treatments.

Metabolic dysregulation is a hallmark of Alzheimer's disease (AD), yet the temporal nature of metabolite-phenotype associations remains poorly understood. We systematically evaluated 506 serum metabolites across 4,063 longitudinal samples from 1,430 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI), applying cross-sectional single-timepoint analyses, multi-timepoint meta-analysis, and time-interaction analysis. Across 15 AD-related phenotypes, we identified 311 metabolites to be significantly associated with disease. Of those, 281 emerged from the multi-timepoint meta-analysis, 243 (216 overlapping/27 additional) from cross-sectional analyses, and 19 (16 overlapping/3 additional) metabolites that showed a significant evolution of their association with AD over time. In total, 128 metabolites (41%) showed persistent associations over time, providing evidence for chronic and systemic metabolic dysregulation in the disease. This, together with the comparably small number of metabolites showing evolving changes, suggests that many metabolic alterations in AD do not change substantially anymore once they manifested. Our findings confirm impaired fatty acid and energy metabolism, disrupted neurotransmitter systems, and oxidative stress as key metabolic features of AD. We demonstrate broad replication of the reported metabolite associations in prior studies and an independent lipidomics dataset in ADNI. In summary, this work expands previous metabolomics studies in AD and provides novel leads regarding timing and persistence of metabolic alterations across the disease trajectory.

The human gut microbiome has been linked to metabolic disturbances in Alzheimer's disease (AD). However, the mechanisms by which gut microbes might influence metabolic dysfunction in AD remain poorly understood. Previously, we used constraint-based metabolic modelling to associate an increased risk of AD with altered production of microbiome-derived metabolites. In this study, we investigated whether these previous results can also be identified in AD patients. Therefore, we created personalised whole-body metabolic models from gut metagenomics samples from 34 AD dementia patients, 51 individuals with mild cognitive impairments, and 298 healthy controls. These in silico models were profiled to predict the metabolic influences of gut microbiomes on blood metabolites with previously reported alterations in AD. We found an increased capacity of AD host-microbiome co-metabolism to produce S-adenosyl-L-methionine, L-arginine, creatine, taurine, and formate in the blood of AD dementia patients and patients with mild cognitive impairments. The metabolic predictions were then mechanistically linked to gut microbial changes in AD. This analysis identified that increased relative abundances of Bacteroides uniformis and Bacteroides thetaiotamicron were key factors driving the predicted metabolic changes. Furthermore, the predicted altered microbial influences on blood metabolites were also associated with allelic variations in the APOE risk gene in healthy individuals, which confirmed our previous findings. In conclusion, we identified blood metabolites whose perturbations in AD may be influenced by gut microbiota and predicted the key microbial drivers for these metabolic influences. These findings may facilitate the development of microbiome-informed treatments of AD.

Our Alzheimer Disease Metabolomics Consortium (ADMC), part of the Accelerating Medicines Partnership for AD (AMP-AD) and in partnership with AD Neuroimaging Initiative (ADNI), applied state-of-the-art metabolomics and lipidomics technologies combined with genomic and imaging data to map metabolic failures across the trajectory of the disease. Our studies confirmed that peripheral metabolic changes influenced by the exposome inform about cognitive changes, brain imaging changes, and ATN markers for disease confirming that peripheral and central changes are connected, in part through the metabolome. To map the biochemical changes in AD, we used various targeted and untargeted metabolic platforms to profile ∼800 postmortem brain tissue, and ∼ 5000 blood samples. Recently, we built a comprehensive reference map of extensive AD-related metabolic changes in brain, spanning multiple AD-related traits, including neuropathological b-amyloid and tau tangle burden, as well as late-life cognitive performance. Using this resource, we extracted novel metabolic including bioenergetic pathways, cholesterol metabolism, neuroinflammation, broad impairment of osmoregulation, an imbalance between excitatory/inhibitory neurotransmitter ratios and identification of tau load as a potential driver of metabolic dysfunction in the AD brain, with minimal contributions from b-amyloid load. As AD and progressive supranuclear palsy (PSP) share the pathological feature of tauopathy and metabolic alterations, we compared their metabolomic profiles to identify shared biological pathways that could be targeted for therapeutic interventions. Our findings indicate that both diseases display oxidative stress, mitochondrial dysfunction, and tau-induced polyamine stress response. Overall, through our studies, (1) We identified biochemical processes altered in AD, with findings supported across both metabolomic and proteomic data, indicating multimodal deregulation. (2) Our research pinpointed widespread AD-related biochemical changes across various brain regions with differing levels of neuropathology. While there are many overlapping changes across the brain regions, each region also has its distinct metabolic alterations. (3) We identified biochemical processes disrupted by AD, with parallel findings in other neurodegenerative diseases, hinting at broader implications in neurodegenerative research. Currently, we are working on mapping widespread connections of the brain metabolome with various determinants of AD namely genome, gut microbiome, exposome, and linking with peripheral metabolic alterations in AD.

Alzheimer’s disease (AD) is a neurodegenerative disorder with significant environmental factors, including diet, that influence its onset and progression. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored the KD’s molecular impact for markers of AD therapeutic potential. The BEAM diet study simultaneously profiled the KD’s effect on the lipidome, blood and cerebrospinal metabolome, and microbiome of both cognitively impaired and cognitively normal individuals. The findings summarized here assess the biological impact of a Modified Mediterranean KD in the context of Alzheimer’s disease treatment and prevention. BEAM involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean-ketogenic diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed HPLC-MS/MS lipidomics profiling in plasma, nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF, and metagenomics profiling on fecal samples before and after each diet to assess dietary-induced changes. The MMKD led to significant alterations in the blood, CSF, and microbiome. These changes included a global elevation across all plasmanyl and plasmenyl ether lipid species, improved modifiable risk factors, like increased HDL-C and reduced BMI, the reversal of serum metabolic disturbances linked to AD such as an increase in valine levels, and a reduction in systemic inflammation. Leveraging prior clinical studies on AD (n = 1,912), we found that MMKD was inversely associated with the peripheral lipidomic signature of prevalent and incident AD. In the CSF, the MMKD was linked to modified amino acid levels and the breakdown of branched-chain amino acids (BCAAs). Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. In addition, participants with MCI on the MMKD had lower levels of GABA-producing microbes and GABA, and higher levels of GABA-regulating microbes. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier. Funding : Alzheimer’s Gut Microbiome Project, NIA U19AG063744

INTRODUCTION:Higher adherence to the Mediterranean-DASH (Dietary Approaches to Stop Hypertension) Intervention for Neurodegenerative Delay (MIND) diet has been associated with reduced Alzheimer's disease (AD) risk. This study assessed the validity of a brief 15-item MIND diet screener compared to a comprehensive food frequency questionnaire (FFQ). METHODS:The validity of an adapted MIND diet screener relative to the VioScreen FFQ was evaluated in 92 older adults from the Indiana Alzheimer's Disease Research Center (IADRC). Correlation coefficients and tertile-based classification statistics were used, and FFQ nutrient profiles were examined across screener-based MIND diet tertiles. RESULTS:MIND diet scores from the screener showed strong positive correlation (r = 0.71, ρ = 0.70, p < 0.001) and comparable ranking ability (63% correctly classified, 1% grossly misclassified, kw = 0.67) compared to those from the FFQ, as well as significant associations with nutrient profiles. CONCLUSION:The MIND diet screener is an acceptable, time-efficient tool for estimating MIND diet scores in older adults. HIGHLIGHTS:The MIND diet screener effectively differentiated participants by diet quality. Agreement between instrument scores was consistent across diagnostic groups. Reliability of the screener over approximately 1 year was comparable to the FFQ. The MIND diet screener is an acceptable tool for use in time-constrained settings. Future studies should confirm validity using objective biomarkers.

BACKGROUND:The gut microbiome is a potentially modifiable risk factor for Alzheimer's disease (AD); however, understanding of its composition and function regarding AD pathology is limited. METHODS:Shallow-shotgun metagenomics was used to analyze the fecal microbiome of participants in the Wisconsin Microbiome in Alzheimer's Risk Study, leveraging clinical data and cerebrospinal fluid (CSF) biomarkers. Differential abundance and ordinary least squares regression analyses were performed to find differentially abundant gut microbiome features and their associations with CSF biomarkers of AD and related pathologies. RESULTS:Gut microbiome composition and function differed between individuals with and without AD dementia. The compositional difference was replicated in an independent cohort. Differentially abundant gut microbiome features were associated with CSF biomarkers of AD and related pathologies. DISCUSSION:These findings enhance our understanding of alterations in gut microbial composition and function in AD, and suggest that gut microbes and their pathways are linked to AD pathology. HIGHLIGHTS:Gut microbiome composition and function differ between people with Alzheimer's disease (AD) dementia and cognitively unimpaired (CU) individuals. Co-occurring gut microbes show differential abundance across AD-related groups (AD vs CU, amyloid status+ vs amyloid status-, and apolipoprotein E (APOE) ε4 status+ vs APOE ε4 status-). Gut microbiome composition also differs between people with AD dementia and CU individuals in a larger validation cohort. Differentially abundant gut microbiome composition and function between AD and CU groups are correlated with cerebrospinal fluid biomarkers for AD and related pathologies.

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

Alzheimer's disease (AD) is influenced by a variety of modifiable risk factors, including a person's dietary habits. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored KD's metabolic impact, especially on blood and cerebrospinal fluid (CSF). Our study involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean Ketogenic Diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF and metagenomics profiling on fecal samples. While the AHAD induced no notable metabolic changes, MMKD led to significant alterations in both serum and CSF. These changes included improved modifiable risk factors, like increased HDL-C and reduced BMI, reversed serum metabolic disturbances linked to AD such as a microbiome-mediated increase in valine levels, and a reduction in systemic inflammation. Additionally, the MMKD was linked to increased amino acid levels in the CSF, a breakdown of branched-chain amino acids (BCAAs), and decreased valine levels. Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier.

Alzheimer's disease (AD) is influenced by a variety of modifiable risk factors, including a person's dietary habits. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored KD's metabolic impact, especially on blood and cerebrospinal fluid (CSF). Our study involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean-ketogenic diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF and metagenomics profiling on fecal samples. While the AHAD induced no notable metabolic changes, MMKD led to significant alterations in both serum and CSF. These changes included improved modifiable risk factors, like increased HDL-C and reduced BMI, reversed serum metabolic disturbances linked to AD such as a microbiome-mediated increase in valine levels, and a reduction in systemic inflammation. Additionally, the MMKD was linked to increased amino acid levels in the CSF, a breakdown of branched-chain amino acids (BCAAs), and decreased valine levels. Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier.