Search

Sex disparities in serum bile acid (BA) levels and Alzheimer's disease (AD) prevalence have been established. However, the precise link between changes in serum BAs and AD development remains elusive. Here, authors quantitatively determined 33 serum BAs and 58 BA features in 4 219 samples collected from 1 180 participants from the Alzheimer's Disease Neuroimaging Initiative. The findings revealed that these BA features exhibited significant correlations with clinical stages, encompassing cognitively normal (CN), early and late mild cognitive impairment, and AD, as well as cognitive performance. Importantly, these associations are more pronounced in men than women. Among participants with progressive disease stages (n = 660), BAs underwent early changes in men, occurring before AD. By incorporating BA features into diagnostic and predictive models, positive enhancements are achieved for all models. The area under the receiver operating characteristic curve improved from 0.78 to 0.91 for men and from 0.76 to 0.83 for women for the differentiation of CN and AD. Additionally, the key findings are validated in a subset of participants (n = 578) with cerebrospinal fluid amyloid-beta and tau levels. These findings underscore the role of BAs in AD progression, offering potential improvements in the accuracy of AD prediction.

BackgroundDeep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics.MethodsThe c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification.FindingsThe application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6).InterpretationOur results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.FundingThe specific funding of this article is provided in the acknowledgements section.

Dysregulation of sphingomyelin and ceramide metabolism have been implicated in Alzheimer's disease. Genome-wide and transcriptome-wide association studies have identified various genes and genetic variants in lipid metabolism that are associated with Alzheimer's disease. However, the molecular mechanisms of sphingomyelin and ceramide disruption remain to be determined. We focus on the sphingolipid pathway and carry out multi-omics analyses to identify central and peripheral metabolic changes in Alzheimer's patients, correlating them to imaging features. Our multi-omics approach is based on (a) 2114 human post-mortem brain transcriptomics to identify differentially expressed genes; (b) in silico metabolic flux analysis on context-specific metabolic networks identified differential reaction fluxes; (c) multimodal neuroimaging analysis on 1576 participants to associate genetic variants in sphingomyelin pathway with Alzheimer's disease pathogenesis; (d) plasma metabolomic and lipidomic analysis to identify associations of lipid species with dysregulation in Alzheimer's; and (e) metabolite genome-wide association studies to define receptors within the pathway as a potential drug target. We validate our hypothesis in amyloidogenic APP/PS1 mice and show prolonged exposure to fingolimod alleviated synaptic plasticity and cognitive impairment in mice. Our integrative multi-omics approach identifies potential targets in the sphingomyelin pathway and suggests modulators of S1P metabolism as possible candidates for Alzheimer's disease treatment.

Increasing evidence suggests Alzheimer's disease (AD) pathophysiology is influenced by primary and secondary bile acids, the end product of cholesterol metabolism. We analyze 2,114 post-mortem brain transcriptomes and identify genes in the alternative bile acid synthesis pathway to be expressed in the brain. A targeted metabolomic analysis of primary and secondary bile acids measured from post-mortem brain samples of 111 individuals supports these results. Our metabolic network analysis suggests that taurine transport, bile acid synthesis, and cholesterol metabolism differ in AD and cognitively normal individuals. We also identify putative transcription factors regulating metabolic genes and influencing altered metabolism in AD. Intriguingly, some bile acids measured in brain tissue cannot be explained by the presence of enzymes responsible for their synthesis, suggesting that they may originate from the gut microbiome and are transported to the brain. These findings motivate further research into bile acid metabolism in AD to elucidate their possible connection to cognitive decline.

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

IntroductionBile acids (BAs) are the end products of cholesterol metabolism produced by human and gut microbiome co-metabolism. Recent evidence suggests gut microbiota influence pathological features of Alzheimer's disease (AD) including neuroinflammation and amyloid-β deposition.MethodSerum levels of 20 primary and secondary BA metabolites from the AD Neuroimaging Initiative (n = 1562) were measured using targeted metabolomic profiling. We assessed the association of BAs with the "A/T/N" (amyloid, tau, and neurodegeneration) biomarkers for AD: cerebrospinal fluid (CSF) biomarkers, atrophy (magnetic resonance imaging), and brain glucose metabolism ([18F]FDG PET).ResultsOf 23 BAs and relevant calculated ratios after quality control procedures, three BA signatures were associated with CSF Aβ1-42 ("A") and three with CSF p-tau181 ("T") (corrected P

IntroductionIncreasing evidence suggests a role for the gut microbiome in central nervous system disorders and a specific role for the gut-brain axis in neurodegeneration. Bile acids (BAs), products of cholesterol metabolism and clearance, are produced in the liver and are further metabolized by gut bacteria. They have major regulatory and signaling functions and seem dysregulated in Alzheimer's disease (AD).MethodsSerum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1464 subjects including 370 cognitively normal older adults, 284 with early mild cognitive impairment, 505 with late mild cognitive impairment, and 305 AD cases enrolled in the AD Neuroimaging Initiative. We assessed associations of BA profiles including selected ratios with diagnosis, cognition, and AD-related genetic variants, adjusting for confounders and multiple testing.ResultsIn AD compared to cognitively normal older adults, we observed significantly lower serum concentrations of a primary BA (cholic acid [CA]) and increased levels of the bacterially produced, secondary BA, deoxycholic acid, and its glycine and taurine conjugated forms. An increased ratio of deoxycholic acid:CA, which reflects 7α-dehydroxylation of CA by gut bacteria, strongly associated with cognitive decline, a finding replicated in serum and brain samples in the Rush Religious Orders and Memory and Aging Project. Several genetic variants in immune response-related genes implicated in AD showed associations with BA profiles.DiscussionWe report for the first time an association between altered BA profile, genetic variants implicated in AD, and cognitive changes in disease using a large multicenter study. These findings warrant further investigation of gut dysbiosis and possible role of gut-liver-brain axis in the pathogenesis of AD.

Introduction: Late‐onset Alzheimer's disease (LOAD) is a complex neurodegenerative disease characterized by multiple progressive stages, glucose metabolic dysregulation, Alzheimer's disease (AD) pathology, and inexorable cognitive decline. Discovery of metabolic profiles unique to sex, apolipoprotein E (APOE) genotype, and stage of disease progression could provide critical insights for personalized LOAD medicine. Methods: Sex‐ and APOE‐specific metabolic networks were constructed based on changes in 127 metabolites of 656 serum samples from the Alzheimer's Disease Neuroimaging Initiative cohort. Results: Application of an advanced analytical platform identified metabolic drivers and signatures clustered with sex and/or APOE ɛ4, establishing patient‐specific biomarkers predictive of disease state that significantly associated with cognitive function. Presence of the APOE ɛ4 shifts metabolic signatures to a phosphatidylcholine‐focused profile overriding sex‐specific differences in serum metabolites of AD patients. Discussion: These findings provide an initial but critical step in developing a diagnostic platform for personalized medicine by integrating metabolomic profiling and cognitive assessments to identify targeted precision therapeutics for AD patient subgroups through computational network modeling. [ABSTRACT FROM AUTHOR]

Introduction: Altered lipid metabolism is implicated in Alzheimer's disease (AD), but the mechanisms remain obscure. Aging‐related declines in circulating plasmalogens containing omega‐3 fatty acids may increase AD risk by reducing plasmalogen availability. Methods: We measured four ethanolamine plasmalogens (PlsEtns) and four closely related phosphatidylethanolamines (PtdEtns) from the Alzheimer's Disease Neuroimaging Initiative (ADNI; n = 1547 serum) and University of Pennsylvania (UPenn; n = 112 plasma) cohorts, and derived indices reflecting PlsEtn and PtdEtn metabolism: PL‐PX (PlsEtns), PL/PE (PlsEtn/PtdEtn ratios), and PBV (plasmalogen biosynthesis value; a composite index). We tested associations with baseline diagnosis, cognition, and cerebrospinal fluid (CSF) AD biomarkers. Results: Results revealed statistically significant negative relationships in ADNI between AD versus CN with PL‐PX (P = 0.007) and PBV (P = 0.005), late mild cognitive impairment (LMCI) versus cognitively normal (CN) with PL‐PX (P = 2.89 × 10−5) and PBV (P = 1.99 × 10−4), and AD versus LMCI with PL/PE (P = 1.85 × 10−4). In the UPenn cohort, AD versus CN diagnosis associated negatively with PL/PE (P = 0.0191) and PBV (P = 0.0296). In ADNI, cognition was negatively associated with plasmalogen indices, including Alzheimer's Disease Assessment Scale 13‐item cognitive subscale (ADAS‐Cog13; PL‐PX: P = 3.24 × 10−6; PBV: P = 6.92 × 10−5) and Mini‐Mental State Examination (MMSE; PL‐PX: P = 1.28 × 10−9; PBV: P = 6.50 × 10−9). In the UPenn cohort, there was a trend toward a similar relationship of MMSE with PL/PE (P = 0.0949). In ADNI, CSF total‐tau was negatively associated with PL‐PX (P = 5.55 × 10−6) and PBV (P = 7.77 × 10−6). Additionally, CSF t‐tau/Aβ1‐42 ratio was negatively associated with these same indices (PL‐PX, P = 2.73 × 10−6; PBV, P = 4.39 × 10−6). In the UPenn cohort, PL/PE was negatively associated with CSF total‐tau (P = 0.031) and t‐tau/Aβ1‐42 (P = 0.021). CSF Aβ1‐42 was not significantly associated with any of these indices in either cohort. Discussion: These data extend previous studies by showing an association of decreased plasmalogen indices with AD, mild cognitive impairment (MCI), cognition, and CSF tau. Future studies are needed to better define mechanistic relationships, and to test the effects of interventions designed to replete serum plasmalogens. [ABSTRACT FROM AUTHOR]

The Mini-Mental State Examination (MMSE) is one of the most widely used cognitive screening tests in the world. However, its administration and content differs by country and region, precluding direct comparison of scores across different versions. Our objective was to compare 2 methods of deriving comparable scores across versions of the MMSE. Between 1981 and 2012, investigators in the International Neuropsychological Normative Database Initiative collected MMSE scores on 122,512 persons from 47 studies conducted in 35 countries. We used MMSE data from 80,559 adults aged 41–99 years from 22 studies that provided item-level response data. We first equated 14-point, 15-point, 18-point, 19-point, and 23-point versions of the MMSE to the original 30-point version using coarse equipercentile equating methods that preserved differences across continents, age groups, and durations (years) of education. We then derived more precise item response theory–based scores using item-level responses to MMSE component items. We compared the 2 score-equating approaches using correlation and Bland-Altman plots. Both test-equating approaches were highly correlated with each other (r  = 0.73) and with raw MMSE point totals. Bland-Altman plots revealed minimal evidence of systematic differences between the approaches. Our findings support the use of equipercentile equating when item-level data are unavailable to facilitate development of international test norms. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence suggests that Alzheimer's disease (AD) patients display metabolic dysfunction. Metabolomics is a powerful tool for studying metabolic pathways by mapping biochemical changes in AD, yet little is known about the association between circulating metabolites in blood and the "A/T/N" (amyloid‐β, tau, neurodegeneration) biomarkers for AD. Method: Serum‐based targeted metabolite levels were measured in the Alzheimer's Disease Neuroimaging Initiative (ADNI; n = 1,531; 370 cognitively normal controls (CN), 95 significant memory concern (SMC), 271 early mild cognitive impairment (EMCI), 491 late MCI (LMCI), and 304 AD). The quality control process resulted in 139 metabolites for further analysis. We performed association analyses of circulating serum metabolites with the "A/T/N" biomarkers for AD. Biomarkers of "A" are CSF Aβ1‐42 and cortical amyloid‐β accumulation measured by Florbetapir PET, biomarkers of "T" are CSF phosphorylated tau (p‐tau), and biomarkers of "N" are atrophy on MRI and glucose metabolism on FDG PET. FDR‐based multiple comparison adjustment with the Benjamini‐Hochberg procedure was used. Result: We found significant associations of multiple metabolites with biomarkers of amyloid‐β ("A") and neurodegeneration ("N") including brain amyloid deposition, glucose metabolism, and structural atrophy measured from multimodal neuroimaging scans (MRI, PET) after multiple testing adjustment. We did not observe any significant associations between metabolites and biomarkers of fibrillary tau ("T") (Figure 1). In particular, higher levels of phosphatidylcholines (PC) were associated with greater amyloid deposition ("A") and decreased brain glucose metabolism ("N"). Higher levels of propionyl‐L‐carnitine (C3) were associated with less amyloid deposition and increased brain glucose metabolism. Higher levels of two amino acids, two PCs, and three sphingomyelins were associated with less brain atrophy ("N"). Conclusion: This is the first study to show serum circulating metabolites are significantly associated with neuroimaging biomarkers for AD. Perturbations in PC and acylcarnitine metabolism may play a role in features intrinsic to AD including amyloid‐β deposition and neurodegeneration, but not fibrillary tau suggesting that acylcarnitines and PCs are associated with earlier stages of AD as tau spreading is more closely related to AD progression. [ABSTRACT FROM AUTHOR]

Background: L‐carnitine is present in the mammalian cells as free carnitine (FC) and acylcarnitine and the adult human brain contains almost 10% of long chain acylcarnitine. Acylcarnitines are functionally involved in β‐oxidation of fatty acids and are also known for their role in neuroprotection. Levels of plasma acylcarnitines are known to decreased on aging. It is important to understand the association of acylcarnitines with cognitive impairment in Alzheimer's disease (AD). Method: We integrated the transcriptome data from 1000 post‐mortem brain samples from ROS/MAP, Mayo clinic and Mount Sinai Brain bank cohort with the brain region‐specific metabolic networks. We calculated the metabolic fluxes for the reactions in the model and identified those that showed differential fluxes in AD samples. We filtered the reactions that are involved in acylcarnitine synthesis and transport namely carnitine transport, fatty acid oxidation, citric acid cycle, and glutathione metabolism. Result: We found differences in metabolic fluxes for reactions involved in the acetylcarnitine transport to mitochondria (ACRNtm), carnitine palmitoyl transferase 1 and 2 (CPT1 and CPT2) as well as acyl‐CoA dehydrogenase short and medium chain (ACADS, ACADM) located in mitochondria in AD samples. Using gene‐based association analysis in participants of the AD Neuroimaging Initiative (ADNI) phases 1, GO and 2, we identified genetic variants linked to CPT1, CPT2, ACADM and ACADS genes suggested from the metabolic flux analysis. Conclusion: Our findings suggest that acylcarnitine synthesis and transport is altered in AD. Altered metabolism of short and medium chain acylcarnitines can be used as metabolic features of AD. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the most common cause of dementia. The mechanism of disease development and progression is not well understood, but increasing evidence suggests multifactorial etiology, with a number of genetic, environmental, and aging-related factors. There is a growing body of evidence that metabolic defects may contribute to this complex disease. To interrogate the relationship between system level metabolites and disease susceptibility and progression, the AD Metabolomics Consortium (ADMC) in partnership with AD Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for patients in the ADNI1 cohort. We used the Biocrates Bile Acids platform to evaluate the association of metabolic levels with disease risk and progression. We detail the quantitative metabolomics data generated on the baseline samples from ADNI1 and ADNIGO/2 (370 cognitively normal, 887 mild cognitive impairment, and 305 AD). Similar to our previous reports on ADNI1, we present the tools for data quality control and initial analysis. This data descriptor represents the third in a series of comprehensive metabolomics datasets from the ADMC on the ADNI. Measurement(s) bile acid • Medication Technology Type(s) ultra high performance liquid chromatography with mass spectrometer • Resource Informatics Factor Type(s) age • biological sex • cognitive state Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9724652 [ABSTRACT FROM AUTHOR]

Introduction: Late-onset Alzheimer's disease (LOAD) is a complex neurodegenerative disease characterized by multiple progressive stages, glucose metabolic dysregulation, Alzheimer's disease (AD) pathology, and inexorable cognitive decline. Discovery of metabolic profiles unique to sex, apolipoprotein E (APOE) genotype, and stage of disease progression could provide critical insights for personalized LOAD medicine., Methods: Sex- and APOE-specific metabolic networks were constructed based on changes in 127 metabolites of 656 serum samples from the Alzheimer's Disease Neuroimaging Initiative cohort., Results: Application of an advanced analytical platform identified metabolic drivers and signatures clustered with sex and/or APOE ɛ4, establishing patient-specific biomarkers predictive of disease state that significantly associated with cognitive function. Presence of the APOE ɛ4 shifts metabolic signatures to a phosphatidylcholine-focused profile overriding sex-specific differences in serum metabolites of AD patients., Discussion: These findings provide an initial but critical step in developing a diagnostic platform for personalized medicine by integrating metabolomic profiling and cognitive assessments to identify targeted precision therapeutics for AD patient subgroups through computational network modeling., (© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Metabolomics in the Alzheimer's Disease Neuroimaging Initiative cohort provides a powerful tool for mapping biochemical changes in Alzheimer's disease, and a unique opportunity to learn about the association between circulating blood metabolites and brain amyloid-β deposition in Alzheimer's disease. We examined 140 serum metabolites and their associations with brain amyloid-β deposition, cognition and conversion from mild cognitive impairment to Alzheimer's disease in the Alzheimer's Disease Neuroimaging Initiative. Processed [ 18 F] Florbetapir PET images were used to perform a voxel-wise statistical analysis of the effect of metabolite levels on amyloid-β accumulation across the whole brain. We performed a multivariable regression analysis using age, sex, body mass index, apolipoprotein E ε4 status and study phase as covariates. We identified nine metabolites as significantly associated with amyloid-β deposition after multiple comparison correction. Higher levels of one acylcarnitine (C3; propionylcarnitine) and one biogenic amine (kynurenine) were associated with decreased amyloid-β accumulation and higher memory scores. However, higher levels of seven phosphatidylcholines (lysoPC a C18:2, PC aa C42:0, PC ae C42:3, PC ae C44:3, PC ae C44:4, PC ae C44:5 and PC ae C44:6) were associated with increased brain amyloid-β deposition. In addition, higher levels of PC ae C44:4 were significantly associated with lower memory and executive function scores and conversion from mild cognitive impairment to Alzheimer's disease dementia. Our findings suggest that dysregulation of peripheral phosphatidylcholine metabolism is associated with earlier pathological changes noted in Alzheimer's disease as measured by brain amyloid-β deposition as well as later clinical features including changes in memory and executive functioning. Perturbations in phosphatidylcholine metabolism may point to issues with membrane restructuring leading to the accumulation of amyloid-β in the brain. Additional studies are needed to explore whether these metabolites play a causal role in the pathogenesis of Alzheimer's disease or if they are biomarkers for systemic changes during preclinical phases of the disease., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Introduction: Altered lipid metabolism is implicated in Alzheimer's disease (AD), but the mechanisms remain obscure. Aging-related declines in circulating plasmalogens containing omega-3 fatty acids may increase AD risk by reducing plasmalogen availability., Methods: We measured four ethanolamine plasmalogens (PlsEtns) and four closely related phosphatidylethanolamines (PtdEtns) from the Alzheimer's Disease Neuroimaging Initiative (ADNI; n = 1547 serum) and University of Pennsylvania (UPenn; n = 112 plasma) cohorts, and derived indices reflecting PlsEtn and PtdEtn metabolism: PL-PX (PlsEtns), PL/PE (PlsEtn/PtdEtn ratios), and PBV (plasmalogen biosynthesis value; a composite index). We tested associations with baseline diagnosis, cognition, and cerebrospinal fluid (CSF) AD biomarkers., Results: Results revealed statistically significant negative relationships in ADNI between AD versus CN with PL-PX (P = 0.007) and PBV (P = 0.005), late mild cognitive impairment (LMCI) versus cognitively normal (CN) with PL-PX (P = 2.89 × 10 -5 ) and PBV (P = 1.99 × 10 -4 ), and AD versus LMCI with PL/PE (P = 1.85 × 10 -4 ). In the UPenn cohort, AD versus CN diagnosis associated negatively with PL/PE (P = 0.0191) and PBV (P = 0.0296). In ADNI, cognition was negatively associated with plasmalogen indices, including Alzheimer's Disease Assessment Scale 13-item cognitive subscale (ADAS-Cog13; PL-PX: P = 3.24 × 10 -6 ; PBV: P = 6.92 × 10 -5 ) and Mini-Mental State Examination (MMSE; PL-PX: P = 1.28 × 10 -9 ; PBV: P = 6.50 × 10 -9 ). In the UPenn cohort, there was a trend toward a similar relationship of MMSE with PL/PE (P = 0.0949). In ADNI, CSF total-tau was negatively associated with PL-PX (P = 5.55 × 10 -6 ) and PBV (P = 7.77 × 10 -6 ). Additionally, CSF t-tau/Aβ 1-42 ratio was negatively associated with these same indices (PL-PX, P = 2.73 × 10 -6 ; PBV, P = 4.39 × 10 -6 ). In the UPenn cohort, PL/PE was negatively associated with CSF total-tau (P = 0.031) and t-tau/Aβ 1-42 (P = 0.021). CSF Aβ 1-42 was not significantly associated with any of these indices in either cohort., Discussion: These data extend previous studies by showing an association of decreased plasmalogen indices with AD, mild cognitive impairment (MCI), cognition, and CSF tau. Future studies are needed to better define mechanistic relationships, and to test the effects of interventions designed to replete serum plasmalogens., (© 2020 the Alzheimer's Association.)