Journal of Alzheimer's Disease最新文献

BackgroundTechnologies such as assistive devices and social robots show promise in supporting people with dementia and their caregivers. However, their long-term cost-effectiveness remains unclear, and existing health-economic models are limited in capturing the relevant outcomes.ObjectiveThis study aims to conceptualize a health-economic model to assess the potential impact of care technologies in dementia care on lifetime quality of life and care use.MethodsWe summarized an impact pathway of three care technologies and conceptualized a health-economic model to estimate the long-term impact on quality of life and care use, drawing on literature and multidisciplinary expert input.ResultsWe conceptualized a cohort-based Markov state-transition model simulating states of dementia severity progression (mild, moderate, severe), care setting transitions (no formal care, home care, nursing home), and mortality. Intervention effects are modeled through surrogate outcomes such as functional status and caregiver burden associated to care transitions and quality of life.ConclusionsThis model offers a framework for early health technology assessment of assistive technologies in dementia, supporting extrapolation of effects beyond limited trial data. Future work should focus on developing and operationalizing this model, applying it to establish the value of dementia care technologies.

BackgroundSoluble tau oligomers (tauO) are early, synaptotoxic drivers of dysfunction in tauopathies. While selective vulnerability is well documented at the cellular level, emerging evidence suggests that synaptic subtypes may differ in their susceptibility to tau pathology. Still, the key factors that shape synaptic vulnerability to toxic tauO, particularly in humans, remain poorly understood.ObjectiveTo define the synaptic compartments and subtypes most vulnerable to tauO and identify molecular correlates underlying this susceptibility.MethodsSynaptosomes were isolated from cognitively normal human autopsy specimens and acutely challenged with preformed recombinant tauO. Flow cytometry with multiplexed immunophenotyping resolved tauO engagement across intact pre- and postsynaptic compartments and excitatory versus inhibitory subtypes. Functional effects were assessed by microtransplanting synaptic membranes into Xenopus laevis oocytes and recording ligand-gated GABAergic and glutamatergic responses. Complementary LC-MS/MS proteomics of brain-derived tau oligomers (BDTO) from PBS-soluble hippocampal lysates of primary age-related tauopathy (PART) cases were analyzed using SynGO enrichment to identify molecular correlates.ResultsTauO preferentially engaged presynaptic compartments and showed elevated association with GABAergic synapses. Functionally, acute tauO exposure selectively enhanced GABA_AR-mediated responses, with no effect on AMPAR-mediated currents. The PART BDTO interactome was enriched for presynaptic vesicle-associated proteins involved in vesicle cycling and neurotransmitter release, consistent with a presynaptic axis of vulnerability.ConclusionsThis integrative analysis identifies a compartment- and subtype-specific vulnerability of human synapses to tauO, highlighting a presynaptic inhibitory bias as a potential driver of synaptic dysfunction and tau propagation in early-stage tauopathies.

BackgroundThe disparities in Alzheimer's disease and other dementias (ADOD) burden across global regions have been further exacerbated following the COVID-19 pandemic, necessitating urgent systematic research into its changing trends and driving factors.ObjectiveTo evaluate trends and driving factors of ADOD burden over the past 32 years and analyze changes during the COVID-19 pandemic.MethodsData were extracted from the Global Burden of Disease 2021. We used the average annual percentage change to assess ADOD burden trends from 1990 to 2021, and quantified the drivers of burden through decomposition analysis. We further utilized frontier analysis to explore the relationship between socio-demographic index (SDI) and disability-adjusted life-years (DALYs), and employed the Bayesian age-period-cohort (BAPC) model to project DALYs trends for ADOD from 2022 to 2050.ResultsFrom 1990 to 2021, global age-standardized rates (ASRs) of prevalence, incidence, years lived with disability, and DALYs for ADOD showed increasing trends, while the ASRs of death remained stable. Females consistently bore a higher burden than males. However, during the COVID-19 pandemic, global ASRs of all these indicators increased significantly. High-middle and middle SDI regions experienced marked increases across all epidemiological metrics. Decomposition analysis revealed population growth as the primary driver of ADOD burden escalation. BAPC predicted that DALYs in each age group showed varying degrees of upward trends, with the fastest increase in 85-89 years old group.ConclusionsThe COVID-19 pandemic triggered a sharp rise in ADOD burden. As global aging and population growth persist, ADOD burden is likely to escalate, necessitating urgent public health interventions.

BackgroundSubjective cognitive decline (SCD) represents the first early symptomatic stage of Alzheimer's disease (AD).ObjectiveWe aimed to investigate the relationships between features in SCD and to assess the importance of these features in the future development of dementia to inform a targeted management protocol.Methods440 SCD patients underwent neurological and neuropsychological assessments, MRI scans, APOE genotyping, and AD biomarker evaluations. Patients were followed for a median of 10 years. Relationships among features were first assessed univariately, focusing on differences across stratified subgroups. To capture multivariate associations, we applied network analysis using a Markov Random Field. Finally, baseline features were related to dementia progression using an XGboost machine learning model.ResultsWomen comprising 68.9% of the cohort, were generally younger at onset, had lower APOE ε4 prevalence, and differed in neuropsychological performance compared to men. Older patients (age >60) exhibited a higher prevalence of APOE ε4 and cerebral small vessel disease. Patients with depressive symptoms demonstrated lower cognitive performance across multiple domains. Network analysis indicated complex interconnections among gender, cognitive reserve, SCD severity, and depressive symptoms. The XGboost model achieved 74% accuracy in predicting progression to dementia, identifying age at onset, mini-mental state examination scores, and APOE genotype as the most predictive factors.ConclusionsThis study highlights the role of age, gender, APOE genotype, and depressive symptoms in the presentation and progression of cognitive decline. By identifying key predictive features, we propose a personalized management protocol aimed at optimizing care for individuals with SCD.Trial registration number: NCT05569083, registration date: 2019-05-30.

BackgroundAlzheimer's disease (AD) is the leading cause of dementia worldwide, yet long-term persistence with acetylcholinesterase inhibitors remains suboptimal in routine practice.ObjectiveTo compare real-world treatment persistence among patients with mild to moderate AD receiving oral donepezil, rivastigmine capsules, or transdermal rivastigmine patches, and to identify factors influencing discontinuation.MethodsIn this retrospective cohort study, 1062 patients aged ≥65 years with newly diagnosed AD were identified from a hospital registry between 2015 and 2019 and followed through 2021. Treatment persistence was evaluated by duration and 1-year continuation rates. Discontinuation was defined as a prescription gap exceeding 90 days. Multivariable Cox proportional hazards models were used to identify predictors of discontinuation.ResultsPatients receiving donepezil had significantly longer mean treatment duration (3.03 years) and higher 1-year continuation rates (66.2%) than those receiving rivastigmine capsules (1.81 years, 39.9%) or patches (1.43 years, 45.5%). Both rivastigmine formulations were independently associated with greater discontinuation risk (adjusted hazard ratio [aHR] 1.44 and 1.76, respectively; p < 0.001). Participation in a national dementia care program was the strongest protective factor, associated with a 69% lower discontinuation risk (aHR 0.31; p < 0.001). Higher baseline CASI scores, younger age, and milder cognitive impairment predicted greater persistence, whereas adverse events markedly increased discontinuation.ConclusionsDonepezil demonstrated superior real-world persistence compared with rivastigmine. Structured dementia care programs substantially enhanced treatment continuity, underscoring the importance of both pharmacologic choice and system-level support in sustaining long-term therapy in AD.

BackgroundAlzheimer's disease (AD) and age-related macular degeneration (AMD) are two common neurodegenerative diseases with many similar pathological features, but their shared metabolic characteristics have not been fully elucidated.ObjectiveThis study aims to explore the shared metabolic pathways between AD and AMD using an integrated multi-omics strategy.MethodsWe incorporated Mendelian randomization (MR), bulk and single-cell transcriptomics, and targeted metabolomics to investigate the metabolic links.ResultsThrough MR, we found elevated genetically inferred glutamine concentrations were correlated with a lower likelihood of AD but a higher likelihood of AMD. Using transcriptomic profiling, we detected 19 common differentially expressed genes associated with glutamine and glutamate metabolism, such as GLS. Analysis of single-cell RNA sequencing data revealed that GLS displays distinct cell-type expression patterns. Targeted metabolomic profiling in APP/PS1 mice at 5 months of age provided additional evidence for alterations in glutamine metabolism. The degree of metabolic changes in the eyes was higher than that in the cortex and hippocampus, and the prominent eyes may be an early indicator of neurodegenerative metabolic dysfunction.ConclusionsOverall, these findings suggest that glutamine metabolism disorders represent a convergent mechanism between AD and AMD. Our findings shed light on the overlapping metabolic pathways linking AD and AMD, underscoring the value of ocular biomarkers as promising tools for early disease detection.

BackgroundAlzheimer's disease (AD) exhibits substantial clinical and biological heterogeneity, complicating efforts in treatment and intervention development. While new computational methods offer insights into AD subtyping and disease staging, the reproducibility of these subtypes across datasets remains understudied, particularly concerning the robustness of subtype definitions when validated on diverse databases.ObjectiveThis study evaluates the robustness of the AD progression subtypes identified by the Subtype and Stage Inference (SuStaIn) algorithm on a larger and more diverse cohort.MethodsWe extracted T1-weighted MRI data for 5444 subjects from ANMerge, OASIS, and ADNI datasets, forming four independent cohorts. Each cohort was analyzed with SuStaIn under two conditions: one using the full cohort, including cognitively normal controls, and another excluding controls to test subtype robustness.ResultsResults confirm the three primary atrophy subtypes identified in earlier studies: Typical, Cortical, and Subcortical, as well as the emergence of rare and atypical AD variants such as posterior cortical atrophy. Notably, each subtype displayed varying robustness to the inclusion of controls, with certain subtypes, like the Subcortical subtype, more influenced by cohort composition.ConclusionsThis investigation underscores SuStaIn's reliability for defining stable AD subtypes and suggests its utility in clinical stratification for trials and diagnosis. However, our findings also highlight the need for improved dataset ethnic and demographic diversity, particularly in terms of ethnic representation, to enhance generalizability and support broader clinical application.

BackgroundEarly detection of Alzheimer's disease (AD) is critical for effective disease management and treatment. Web-based assessment tools offer advantages by enabling broader accessibility and reducing reliance on specialized clinical infrastructure.ObjectiveThis study aimed to validate a self-administered, web-based cognitive assessment tool for AD screening.MethodsA total of 106 older adults aged 55 to 84 years were recruited and clinically classified as cognitively unimpaired (CU, n = 35), amnestic mild cognitive impairment (aMCI, n = 37), or AD (n = 34). Participants completed Cogscreen, a 10-min web-based cognitive test comprising verbal cued memory and digit symbol substitution tasks.ResultsBoth the verbal cued memory and digit symbol substitution tasks showed significant score differences among CU, aMCI, and AD (p < 0.001). The Cogscreen composite score yielded area under the curve (AUC) values of 0.876 for aMCI (cut-off = 0.64, sensitivity = 0.865, specificity = 0.657) and 0.994 for AD (cut-off = -0.59, sensitivity = 0.971, specificity = 0.971), and outperformed the Mini-Mental State Examination (MMSE) in diagnosing aMCI (AUC = 0.638, p = 0.001). The composite score significantly correlated with the Consortium to Establish a Registry for Alzheimer's Disease assessment packet total score (r = 0.765, p < 0.001) and MMSE score (r = 0.722, p < 0.001).ConclusionsCogscreen is a rapid, self-administered cognitive screening tool for detecting aMCI and AD. It outperforms the MMSE in identifying early cognitive decline and holds potential for detecting even subtler cognitive changes in the future.

BackgroundRetinal amyloid-β (Aβ) accumulation has been detected in Alzheimer's disease (AD) and correlates with brain Aβ deposition, suggesting that the retina may reflect central disease processes. Impaired Aquaporin-4 (AQP4)-mediated glymphatic clearance contributes to Aβ accumulation in AD brains, but whether similar mechanisms affect the retina remains unclear.ObjectiveThis study investigated glymphatic transport and Müller glia cell (MGC) remodeling in 3-month-old female 5xFAD mice.MethodsFluorescent immunostaining of 5xFAD and wild-type (WT) retinas (n = 5 for each) of AQP4, glial fibrillary acidic protein (GFAP), and glutamine synthetase (GS) were performed to evaluate MGC function. To evaluate bulk glymphatic clearance rates along the optic nerve, intravitreal injections of fluorescent Aβ and cadaverine (interstitial fluid indicator) were performed (n = 5 for each WT, AD).Results5xFAD retinas showed upregulated AQP4 across all retina layers with increased perivascular localization, particularly in the peripheral retina. Indicators of more efficient perivascular Aβ clearance were observed in peripheral versus the central retina. Elevated GFAP in 5xFAD peripheral retinas indicated glial activation. Despite these changes, tracer-based assays showed no significant differences in bulk glymphatic flow.ConclusionsThese findings suggest that retinal Aβ accumulation at this disease stage is unlikely driven by impaired glymphatic clearance but may result from enhanced local Aβ production. While later glymphatic dysfunction cannot be excluded, our results highlight the spatiotemporal dynamics of MGC remodeling and underscore the importance of a) focusing diagnostic imaging studies on the retinal periphery, and b) longitudinal evaluation of retinal amyloid plaque formation mechanisms.

BackgroundOthers have examined heterogeneity in Alzheimer's disease (AD); however, few have used longitudinal data while accounting for variation in disease stage. We used latent classes to model heterogeneity in the trajectories of three cognitive domains (memory, language, and executive functioning) starting at AD dementia diagnosis.ObjectiveOur aim was to describe the patterns of heterogeneity in cognitive decline across cognitive domains during the course of AD and to contextualize our findings by assessing associations with demographic factors and neuropathological measures.MethodsWe used cognitive data from the Religious Orders Study, the Rush Memory and Aging Project, and the Minority Aging Research Study in a multi-dimensional joint latent class mixed model, which allowed us to estimate cognitive trajectories that varied across cognitive domains and latent classes. We accounted for the uncertainty in latent class assignment and corrected for multiple hypotheses when assessing the association of the latent classes with demographic and neuropathological variables.ResultsWe identified five latent classes differentiated by level of impairment (high to low) and rate of decline (slow to fast). Within each latent class, the pattern of decline did not differ substantially across cognitive domains. Classes were associated with APOE genotype, sex, race, education, and neuritic plaque and neurofibrillary tangle burden.ConclusionsOur results highlight global differences in the level of cognitive impairment at diagnosis and the rate of decline rather than differences between domains of cognition. Examination of patterns in the global rate of cognitive decline may improve understanding of heterogeneity in AD.