The Journal of Prevention of Alzheimer's Disease

Importance: Little is known about the impact of returning Alzheimer disease (AD) biomarkers to cognitively unimpaired (CU) research participants. Objective: Does return of research results (RoRR) negatively impact longitudinal symptoms of depression and cognition. Design: Randomized, noninferiority, delayed-start clinical trial, 2021-2025 Setting: AD biomarker research results offered to CU participants in a longitudinal study of aging Participants: CU participants age 65+ were offered research AD biomarker results (APOE genotype and either plasma AB42/40 or amyloid PET and MRI hippocampal volume) with an estimated 5-year risk of symptomatic AD. Intervention(s) (for clinical trials) or Exposure(s) (for observational studies): 147 participants were randomized to receive results either soon after consent (RoRR arm, N=73) or one year later (delayed-start arm, N=74). Main Outcome(s) and Measure(s): Longitudinal change in Geriatric Depression Scale (GDS), Clinical Dementia Rating sum of boxes (CDR-SB), and global cognitive composite. Outcomes were measured at annual assessments for a longitudinal study of aging. Results: 187 participants received results: 70 in RoRR arm (average age 75, 60% female), 66 in delayed-start arm (average age 73, 53% female). The observed changes in annual measures did not differ between arms in both those with elevated amyloid (AB+) and in those without elevated amyloid (AB-) for GDS (AB+ difference 0.7, 95% CI 0.0-1.3; AB- difference -0.1, 95% CI -0.7-0.5; clinically significant decline >4.0), CDR-SB (AB+ difference 0.0, 95% CI -0.1-0.1; AB difference 0.0, 95% CI 0.0-0.1; clinically significant decline >0.5), and cognitive composite (AB+ difference -0.10, 95% CI -0.25-0.06; AB- difference -0.05, 95% CI -0.17-0.07; clinically significant decline < -0.26). Secondary analyses found no evidence of association between RoRR and proximity to follow-up testing. Conclusions and Relevance: In the first randomized, delayed-start clinical trial of returning AD research results to CU older-adult participants, no effect was seen on longitudinal changes in symptoms of depression or cognition. This supports evidence that there are no harms to returning AD research results, although the results may not apply to more diverse populations not included in this study. Trial Registration: NCT04699786

Background: Alzheimers disease (AD) is a multifactorial neurodegenerative disorder in which copper dyshomeostasis, mitochondrial stress, oxidative injury and immune dysregulation may contribute to pathogenesis. Cuproptosis, a copper-triggered regulated cell death pathway, has emerged as a potential mechanistic link to AD, but its therapeutic and biomarker implications remain incompletely defined. Methods: We integrated transcriptomic, machine learning, immune infiltration, QSFR, molecular docking, docking validation and ADME analyses using GEO blood- and brain-based AD cohorts. Differentially expressed genes were intersected with curated cuproptosis-related genes, followed by pathway enrichment, construction and validation of a hybrid ensemble classifier, CIBERSORT-based immune correlation analysis, QSFR-driven target prioritization, ligand docking, consensus docking validation and SwissADME profiling. Results: The transcriptomic analyses revealed reproducible AD associated signatures enriched in neurodegenerative, oxidative stress, mitochondrial and inflammatory pathways. Across multiple machine learning models, FDX1, PDHB, PDHA1, DLAT and DLD consistently emerged as the most important cuproptosis-related genes, with the hybrid ensemble achieving the best diagnostic performance. Immune profiling suggested that these genes are linked to distinct immune infiltration patterns. QSFR and docking prioritized FDX1 as a key target and Clioquinol, PBT2 and Ebselen showed the strongest and most consistent binding behavior. Docking validation confirmed reliable pose reproduction and enrichment over decoys, while ADME analysis supported Clioquinol, PBT2 and Ebselen as the most balanced candidates for further consideration. Conclusion: This integrated workflow identifies a cuproptosis-centered mitochondrial gene module as a robust AD signature and highlights Clioquinol, PBT2 and Ebselen as promising repurposing candidates. The findings provide a prioritized computational framework for future experimental validation of copper-linked therapeutic strategies in AD.

Background The majority of family dementia caregivers in the United States (U.S.) are now young and middleaged adults. However, little research has been conducted to understand how caregiver needs and preferences for support differ depending on their phase of adulthood. This study evaluated differences in mental health, caregiving readiness, desired supports, and intervention preferences among early (<46 years), middle (46 to 60 years), and late (>60 years) adulthood dementia caregivers. Methods A cross sectional survey was conducted with 202 family dementia caregivers aged 22 to 88. Caregivers completed validated measures of burden, anxiety, depression, well being, time pressure, dementia knowledge, caregiving preparedness, and positive aspects of caregiving. Desired supports and preferences for intervention format, program type, and frequency were assessed. Analyses examined both categorical adulthood phase and continuous age associations with caregiver outcomes, with alpha thresholds of p<.05. Results Early adulthood caregivers self reported higher anxiety symptoms (relative to late adulthood caregivers) and perceived time pressure (relative to middle and late adulthood caregivers). Relative to late adulthood caregivers only, early adulthood caregivers more frequently endorsed desired support for supplemental care and safety tools for the person with dementia, as well as willingness to engage in individual counseling and automated, digital supports. Relative to both middle adulthood and late adulthood caregivers, they also more frequently expressed desired support for their own mental health. Conclusions Dementia caregiving in early adulthood is associated with distinct psychological and practical support needs, suggesting life course informed interventions may enhance relevance and engagement.

BackgroundMultiple studies suggest bidirectional links between delirium and Alzheimers Disease and Related Dementias (ADRD). Although they establish a strong association between delirium and subsequent ADRD, it has not been explored using statistical causal inference which makes the best use of observational data to minimize biases. MethodsWe conducted an emulated clinical trial to estimate the effect of experiencing delirium during hospitalization between April 2017 and September 2019 on the cumulative incidence of ADRD over two years following hospital admission in patients 65 and older. The emulated trial used observational data from individuals in the Mass General Brigham Electronic Medical Record (EMR). We carried out statistical causal survival analysis using methods that adjust for confounding, censoring, competing risks, and immortal-time bias, including inverse propensity weighting (IPW) and g-formula approaches. ResultsOf the 6029 patients hospitalized in this time frame who were 65 or older with evidence of a PCP in the EMR, 5901 were included in the analysis based on no history of dementia diagnosis or medications 12 months prior to admission. At two years post-admission, the adjusted cumulative incidence of ADRD in individuals who did not experience delirium was 7.6% (95% Confidence Interval [CI] 4.0-12.1%) while it was 20.2% (95% CI 13.2-27.9%) for those who did experience delirium when calculated using the IPW method. ConclusionsOur emulated trial results argue for a strong association between delirium during hospitalization and the risk of developing ADRD in the two years following hospital admission in individuals 65 and older. Key PointsO_ST_ABSQuestionC_ST_ABSWe sought to answer whether statistical causal inference would show the same association between delirium and the onset of dementia in the two years following hospitalization. FindingsOur emulated trial results argue for a strong association between delirium during hospitalization and the risk of developing ADRD in the two years following hospital admission in individuals 65 and older. MeaningThe implications of demonstrating this relationship underscore the importance of delirium-mitigating interventions for long-term cognitive outcomes.

IntroductionStudies of the risk and timing of symptomatic Alzheimers disease (AD) in cognitively unimpaired individuals are challenging due to the relatively small number of clinical progressors and limited clinical follow-up, which can lead to design-related associations. Clock models can be used to anchor the timing of events to biological events such as biomarker positivity. We hypothesized that estimated age at plasma %p-tau217 positivity based on clock models is less affected by design-related associations as compared to baseline age. MethodsData from the Knight Alzheimer Disease Research Center (Knight ADRC) and Alzheimers Disease Neuroimaging Initiative (ADNI) were analyzed. Age at %p-tau217 positivity was estimated using two clock model approaches, TIRA and SILA. The C-index of estimated age at plasma %p-tau217 positivity and age at the baseline plasma sample (baseline age) for ranking age of AD symptom onset was evaluated in initially cognitively unimpaired individuals, including progressors and non-progressors. In progressor sub-cohorts, baseline age and time from %p-tau217 positivity to baseline were associated with time from baseline until symptom onset; baseline age and estimated age at %p-tau217 positivity were associated with age at symptom onset. Commonality analyses partitioned the variance unique to each predictor and shared between predictors. Randomization analyses evaluated whether observed associations exceeded those expected by chance. ResultsEstimated age at %p-tau217 positivity enabled analyses of a greater number of progressors in the research cohorts, which did not have plasma %p-tau217 data from every clinical assessment. The estimated age at %p-tau217 positivity had a higher C-index than baseline age for ordering the likelihood of AD symptom onset when all follow-up was considered; when follow-up was truncated, the C-index for estimated age at %p-tau217 positivity remained stable while the C-index for baseline age became inflated. In progressors, estimated age at %p-tau217 positivity contributed unique variance beyond baseline age in associations with age at symptom onset. Randomization analyses in the larger Knight ADRC found that associations between clock-derived measures and time from baseline until symptom onset and age at symptom onset exceeded the permuted null distribution, with some mixed results in the smaller ADNI cohort. ConclusionsCompared to baseline age, the biologically-anchored estimated age at %p-tau217 positivity is less susceptible to design-related associations and incrementally improves prediction of age at symptom onset in analyses conditional on progression.

Digital health technologies (DHT) offer a promising solution to the timely identification of early Alzheimer's disease (eAD) to enable early treatment. This study evaluated the feasibility, acceptability, adherence, reliability, and preliminary clinical and content validity of the novel AD Digital Assessment Suite (AD-DAS). 123 individuals (32 healthy controls (HC), 31 amyloid-PET negative (SCDn), 30 amyloid-PET positive (SCDp) with subjective cognitive decline, and 30 early AD (eAD)) participated. AD-DAS was remotely deployed for 28 days. Remote testing was feasible (97.6% completers), acceptable (>85% ''good''), and associated with high adherence (96%). Metrics showed moderate to excellent test-retest reliability (ICC 0.53-0.91), associations with clinical comparators (adjusted R2 0.01-0.24), differentiated eAD from other known groups (absolute log odds differences 0.6-3.28), and correlated with brain atrophy in expected regions. Episodic and working memory AD-DAS metrics differentiated SCDp from SCDn participants. These preliminary findings suggest that AD-DAS may be a promising tool for detecting cognitive impairments in early AD stages.

INTRODUCTIONWhether Alzheimers disease (AD) blood biomarker-cognition associations differ across cognitive domains, analytic context, and biomarker modeling strategy in population-based cohorts is unclear. METHODSIn 1,170 older adults from the Health and Retirement Study Harmonized Cognitive Assessment Protocol, we examined cross-sectional (2016) and prospective (2016-2022) associations of blood p-tau181, glial fibrillary acidic protein (GFAP), neurofilament light (NfL), and amyloid-{beta}42/40 with memory, executive function, language, visuospatial ability, and global cognition using individual biomarker, principal components analysis-derived composite, and multibiomarker panel models. RESULTSCross-sectionally, NfL and GFAP showed the broadest associations. Prospectively, p-tau181 was independently associated with memory and global cognition, whereas GFAP was associated with executive function, memory, and global cognition. P-tau181 also showed relative memory-versus-executive selectivity. The comparatively best-fitting modeling approach differed by cognitive domain and analytic context. DISCUSSIONAD blood biomarker-cognition associations in community-dwelling older adults are domain-differentiated and context-dependent, supporting domain-specific outcomes and flexible biomarker modeling strategies.

BackgroundEpidemiological studies consistently report inverse associations between caffeinated coffee consumption and dementia risk. However, the molecular mechanisms linking coffee-derived phytochemicals to neuroprotection remain only partially understood. ObjectiveTo evaluate, through integrated in silico pharmacology, the relative contribution of adenosine receptor modulation versus direct amyloidogenic enzyme and kinase inhibition in mediating the putative neuroprotective effects of major coffee constituents. MethodsMolecular docking analyses were conducted for caffeine, paraxanthine, chlorogenic acid, trigonelline, cafestol, and kahweol against adenosine A2A and A1 receptors (A2AR, A1R), {beta}-secretase 1 (BACE1), glycogen synthase kinase-3{beta} (GSK-3{beta}), and NLRP3 inflammasome components. Docking was performed using the CB-Dock2 platform. Binding affinities, interaction patterns, and ligand efficiency metrics were assessed. Blood-brain barrier permeability and ADMET properties were predicted using pkCSM. ResultsCaffeine and paraxanthine demonstrated structurally coherent binding within the orthosteric pockets of A2AR and A1R, supported by favorable predicted blood-brain barrier penetration and high unbound fractions. Ligand efficiency analysis identified adenosine receptors as the most pharmacologically plausible targets for small xanthine derivatives. Although larger phytochemicals exhibited stronger absolute docking scores at BACE1, GSK-3{beta}, and NLRP3, predicted pharmacokinetic constraints suggest a small biological effect due to a limited central exposure. ConclusionsThese findings support an adenosine receptor-centered mechanism as the dominant molecular axis linking caffeinated coffee consumption to reduced dementia risk, favoring neuroinflammatory and signaling modulation over direct enzymatic inhibition. Experimental validation is warranted to confirm translational relevance. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=193 HEIGHT=200 SRC="FIGDIR/small/723029v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1a02629org.highwire.dtl.DTLVardef@129890dorg.highwire.dtl.DTLVardef@1e4c05corg.highwire.dtl.DTLVardef@110ec7a_HPS_FORMAT_FIGEXP M_FIG C_FIG

Alzheimer's disease is a progressive neurodegenerative disorder that poses a growing global public health challenge. Early and accurate diagnosis is critical for effective treatment, clinical trial participation, and disease management. This systematic review and meta-analysis evaluates the diagnostic performance of machine learning (ML) and deep learning (DL) algorithms for detecting Alzheimer's disease (AD) and mild cognitive impairment (MCI) using neuroimaging and clinical data. Relevant studies were identified from PubMed, IEEE Xplore, and arXiv (2015 to 2025). Random-effects models were applied to estimate pooled performance metrics (AUC, sensitivity, specificity, and F1-score), and subgroup analyses compared results by model type, imaging modality, and validation strategy. Thirty studies met inclusion criteria. The pooled AUC was 0.962, indicating high overall discriminative accuracy. However, studies relying solely on internal validation or with smaller datasets often reported inflated metrics, suggesting potential overfitting and optimism bias. ML and DL methods demonstrate strong potential for early AD detection, but standardized evaluation protocols and external validation are necessary for clinical translation.

Summary Background Although CAIDE (Cardiovascular Risk Factors, Aging, and Dementia) score estimates 20 year dementia risk, prior studies have largely focused on global or composite measures. Only a few studies investigated on cognitive functions and structural neuroimaging markers, and the available structural neuroimaging evidence has largely been derived from subsamples or highly selected small cohorts rather than full population based cohorts. We therefore not only investigated associations between CAIDE score and cognitive performance but also explored structural neuroimaging markers in middle to older aged population. Methods Of 2,864 participants who were available for structural magnetic resonance imaging (MRI) data at baseline, we excluded 230 participants who have neurological and cardiovascular disease at baseline. We also further excluded 209 participants without having exposure, covariates, and cognitive assessments data, including 2,425 participants for the final analysis. The main exposure is CAIDE score (0 to 15) were calculated from age, sex, education, systolic blood pressure, body mass index, total cholesterol, and physical activity and categorized as low risk (<6), moderate risk (6 to 7), and high risk (7<) at baseline. The main outcomes were neuropsychological assessment battery included Story recall, Visual reproductions, Verbal fluency, Trail making, Digit symbol coding, and Stroop tests. Findings Of 2,425 healthy participants (mean age of 58.5 [6.5]; men 1,189 [49.0]), higher CAIDE risk groups were associated with poorer cognitive performance. Compared with low risk group, the high risk group showed significantly lower performance across all 12 cognitive assessments (all p <.001). The moderate risk group also showed lower performance in visual reproduction (immediate and delayed recall), digit symbol oding, and Stroop (word and color) reading tests. Interpretation This large based population study showed the highest risk group were independently associated with lower cognitive performance across all domains compare to the lowest risk group, suggesting the potential importance of managing these features for preserving neurological health in middle and older aged adults.

INTRODUCTION: Knowledge about how Alzheimer's disease (AD) and AD-related dementia (AD/ADRD) plasma biomarkers relate to global and domain-specific cognitive functioning across diagnostic groups remains limited, particularly in heterogeneous, community-dwelling populations with multiple comorbidities. METHODS: We evaluated associations between baseline plasma biomarker levels (A{beta}42/40, p-tau181, p-tau217, NfL, GFAP) and cognitive performance at baseline and longitudinally (up to 7 years). Participants (n=590) enrolled in the Wake Forest Alzheimer's Disease Research Center Clinical Core (314 cognitively unimpaired [CU]; 206 mild cognitive impairment [MCI]; and 70 dementia) completed annual cognitive assessments including the Uniform Data Set (UDSv3; NACC). Domain-specific cognitive composites including memory, executive function, attention, language, visuospatial ability, and phonemic fluency, as well as a modified Preclinical Alzheimer's Cognitive Composite (PACC5), were evaluated. General linear and mixed-effects models were adjusted for demographics (age, sex, race, education), APOE-{epsilon}4 status, comorbidities (estimated glomerular filtration rate; BMI), and cardiometabolic health factors (hypertension, diabetes). Effect modification by cognitive diagnosis was evaluated. RESULTS: Baseline plasma biomarkers, particularly p-tau217, were associated with poorer baseline cognitive performance and greater longitudinal decline on the PACC5 and all cognitive domains assessed, except phonemic fluency (strongest for memory). Post-hoc analyses indicated associations between plasma biomarker levels and cognition were generally more pronounced in MCI compared with CU participants. Effect modification by baseline cognitive status was limited and attenuated when all biomarkers were modeled simultaneously. Comorbidities and cardiometabolic factors modified select associations. DISCUSSION: Plasma AD/ADRD biomarkers, particularly p-tau217, were associated with cognitive impairment and decline in a heterogenous community cohort.

Objective: To systematically evaluate pathway-informed polygenic risk score (PRS) strategies and determine which approaches most effectively leverage biological annotations for risk prediction, using brain amyloid-beta positivity as a case study. Methods: We systematically benchmarked approaches for integrating pathway information into PRS construction to predict brain A{beta} positivity. Using two cohorts, the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 969) and Australian Imaging, Biomarkers and Lifestyle (AIBL, n = 251), we compared Apolipoprotein E (APOE) genetic risk score (GRS), clumping and thresholding (C+T) PRS, pathway-guided single nucleotide polymorphism (SNP) selection PRS, and pathway-specific PRSs ensembled via machine learning. Pathways were derived from manually curated literature or from pathway databases via Functional Mapping and Annotation (FUMA). Results: In cross-validation on the ADNI cohort, pathway-informed PRS using a narrow-set of pathways to guide SNP selection (PathPRS-SNPLit without APOE locus) significantly outperformed the standard PRS model (median AUC = 0.742, p = 0.006) and the APOE locus model (median AUC = 0.736, p = 5.1 x 10-5) based on the Mann-Whitney U test, achieving a median AUC of 0.763. This model showed enhanced ability to identify subgroups within the 10% lowest- and highest-risk groups compared to the current standard of APOE locus alone (odds ratio = 0.67, 95% CI: 0.56-0.81; and OR = 13.23, 95% CI: 10.23-17.11), highlighting its clinical potential. Using a focused set of literature-curated pathways outperformed using a broader set of database-derived pathways across configurations. When contrasting strategies for aggregating information across pathways, we observed that using pathways to guide selection of SNPs and then building a single PRS performed comparably to building PRS for each pathway and using machine learning (ML) to aggregate these, though the latter enabled pathway-level interpretability. Similar trends were observed in the external AIBL validation dataset. Interpretation: Pathway-informed PRS can meaningfully improve genetic risk enrichment for A{beta} positivity beyond APOE and standard C+T approaches, provided pathway definitions are carefully curated. The choice of pathway source has the strongest impact on predictive performance, with aggregation strategies or ML model choice having far less impact. Our findings highlight the utility of literature-curated, pathway-informed PRSs for A{beta} prediction and offer practical guidance for pathway-informed PRS construction in other polygenic traits.

Background: Improvements in health technology offer opportunities for remote disease screening, diagnosis and monitoring. The Withings Sleep Analyzer (WSA), an under mattress ballistocardiograph sensor able to detect body movement, breathing, and cardiac ejection is a promising technology for the non-invasive detection and monitoring of neurodegenerative diseases. InSleep46 aims to evaluate whether the WSA is able to detect preclinical Alzheimer's disease in members of the 1946 British Birth cohort, now in their late 70s. Objectives: To assess feasibility of deployment of a remote sleep, circadian and physiological monitoring device in a population of older adults. Participants: 356 participants from the Insight 46 neuroimaging sub-study (1946 British Birth Cohort), all born in one week in March 1946. Methods: We describe remote recruitment, device installation, and troubleshooting protocols. Feasibility analysis examined participant characteristics associated with recruitment and successful device set-up using logistic regression. Troubleshooting events for device installation and maintenance were recorded over a mean 14-month follow-up period. Results: During the feasibility analysis period, 263 (74%) participants, mean (SD) age 77 years (0.47) agreed to take part, of whom 245 (93%) successfully set up the WSA. Recruitment and successful set up of the WSA were not dependent on cognitive ability, socioeconomic position, or educational attainment. 162 (62%) of recruited individuals required [&ge;]1 troubleshooting call (mean 2.3 per participant, range 0-16). 603 calls were required in total. Conclusion: Deployment of a remote sleep and physiological monitoring device in an older adult population is feasible. Most participants required individualised assistance to set up the device. For the technology to be widely implemented, the set up must be accessible, with dedicated support available.

INTRODUCTION: MethylCog is a 29-CpG blood DNA methylation (DNAm) proxy for general cognitive ability (g). Its incremental association with blood biomarkers of Alzheimer's disease and related dementias (ADRD) and prospective cognitive ability remains unclear. METHODS: In the held-out test set from the original MethylCog study, we tested whether MethylCog explained baseline g beyond four ADRD blood biomarkers, and whether it predicted six-year follow-up g beyond baseline g and biomarkers. RESULTS: MethylCog showed a stronger age-adjusted association with baseline g than individual biomarkers (r=.368 vs absolute r=.083-.162). MethylCog added 10.0% variance beyond all four biomarkers cross-sectionally (p<.001) and predicted six-year follow-up g in the biomarker-adjusted model (beta=.108, p=.002). No individual ADRD biomarker independently predicted follow-up g. DISCUSSION: MethylCog may provide cognition-related DNAm information complementary to blood-based ADRD biomarkers.

Abstract Background: Biological systems exhibit dynamic patterns over multiple temporal scales -from minutes to months- that are poorly captured by conventional cross-sectional or low-frequency longitudinal studies. These patterns, including circadian and ultradian rhythms, may be critical determinants of health, resilience, and disease risk in aging. Existing longitudinal studies in older adults lack high-frequency, multimodal measurements that integrate molecular, physiological, and digital health data streams. Objectives: The TIME Study aims to: (i) Characterize temporal patterns in molecular, physiological, and digital health measures in healthy older adults; (ii) determine how these patterns vary across biological domains and relate to each other; and (iii) assess how physiological systems respond to defined perturbations (oral glucose tolerance and maximal exercise). Methods: TIME is a single-site, observational, longitudinal study enrolling up to 150 adults aged [&ge;] 55 years. Over an 11-week main phase, participants complete seven weekly low-frequency visits, two perturbation challenge visits, and two, two-day high-frequency sampling epochs. Biospecimens, clinical measures, cognitive and physical performance tests, and continuous digital health data are collected. Follow-up visits occur at 6 and 12 months. Expected Impact: By integrating multimodal, temporally resolved data, TIME will provide a foundational dataset for understanding the role of biological rhythms in aging and inform future precision health strategies.

SUMMARY Background GLP-1 receptor agonists (GLP-1 RAs) are widely used for treatment of type 2 diabetes and obesity and have demonstrated cardiovascular benefits, but their effect on dementia risk is uncertain. We used a drug-target Mendelian randomisation (MR) framework to estimate the causal effect of GLP-1 receptor (GLP-1R) agonism on dementia risk and brain structure. Methods We used single nucleotide polymorphisms (SNPs) in GLP1R to recapitulate the effect of GLP1-RAs against circulating markers of glucose, glycated haemoglobin and outcomes of type 2 diabetes and obesity, to understand if we can reliably proxy agonism at GLP1R using gene variants. We then considered clinical outcomes, including all-cause dementia, vascular dementia, Alzheimer's disease, and neuroimaging outcomes. Analyses were conducted in UK Biobank and replicated in FinnGen and All of Us and results were combined using meta-analysis. Findings Genetically proxied GLP-1R agonism was associated with a 17% lower risk of vascular dementia, with directional consistency across the two largest cohorts. No consistent association was observed for all-cause dementia. An elevated risk of Alzheimer's disease was observed in UK Biobank but was not replicated in FinnGen or All of Us, and the pooled estimate across cohorts was null. There was no consistent evidence of an effect on neuroimaging outcomes, though higher GLP-1R agonism was associated with greater total brain volume. Interpretation Genetic evidence supports a potential protective effect of GLP-1R agonism on vascular dementia, consistent with the established cardio-metabolic benefits of this drug class. The null pooled finding for Alzheimer's disease suggests that GLP-1R agonism does not meaningfully modify neurodegenerative pathways specific to this disease, though results from ongoing clinical trials are awaited. These findings highlight the importance of distinguishing between dementia subtypes when evaluating the cognitive effects of cardiometabolic therapies.

Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSEducational attainment is a key proxy of cognitive reserve (CR), but whether its association with cognition persists after accounting for multimodal brain pathology remains unclear. METHODSData from PREVENT-AD and CIMA-Q were analyzed using cross-sectional, longitudinal, and residual-based models adjusted for multimodal pathology, including MRI-based white matter hyperintensities and atrophy measures, and plasma Alzheimers disease biomarkers. Education was examined in both cohorts. A multidimensional CR questionnaire was also examined in CIMA-Q. RESULTSHigher education was associated with better performance across multiple cognitive domains after accounting for pathology (p < 0.05). The CR composite score showed less consistent associations, and non-education subdomains showed limited added value. Longitudinally, education was more consistently associated with baseline cognitive levels than cognitive change, with executive-function trajectory differences observed in PREVENT-AD. DISCUSSIONFindings support a CR framework in which education relates to better cognition despite pathology, while effects on decline are limited and domain-specific.

INTRODUCTION: Cognitive trajectories may clarify how type 2 diabetes (T2D) and impaired fasting glucose (IFG) relate to dementia risk, but longitudinal associations remain unclear, particularly in the context of stroke. METHODS: Data from 5,631 dementia- and stroke-free older adults (mean age 75 years) from 7 international population-based cohorts were analyzed. Linear mixed-effects models estimated cognitive trajectories during stroke-free and post-stroke follow-up. Glucose status was defined by fasting glucose and prior T2D diagnosis. RESULTS: Over 6.6 years of follow-up (4.5% with incident stroke), T2D was associated with lower baseline cognitive performance compared with normal fasting glucose (-0.14 SD, 95% CI -0.21 to -0.07), but not with faster cognitive decline during stroke-free or post-stroke follow-up. IFG was not associated with lower cognitive performance or faster decline. DISCUSSION: In older adults, T2D was associated with persistently lower cognitive performance but not faster decline, suggesting adverse cognitive effects may be established before late life.

BACKGROUNDWe investigated associations of neighborhood disadvantage with Alzheimers Disease (AD)-related outcomes by biological and social factors in at-risk older adults. METHODS1,880 U.S. POINTER participants with Area Deprivation Index (ADI) and cognition (PACC) were included. 868 had amyloid, tau PET, white matter hyperintensities (WMH), and/or gray matter volumes. We conducted exploratory, linear models testing ADI interactions with sex, race and ethnicity, and APOE {varepsilon}4, adjusting for age and education. RESULTS"White/European American", "Hispanic/Latinx/Spanish" and "Others" showed lower cognitive scores with higher ADI, while "White/European American" showed the highest cognitive scores across ADI levels. APOE {varepsilon}4 carriers from high-ADI areas showed higher WMH and tau, and "Hispanic/Latinx/Spanish" from more deprived areas showed higher WMH. Females from moderate-ADI areas showed higher tau. Amyloid burden was higher in APOE {varepsilon}4 carriers from low-ADI areas. CONCLUSIONDifferential associations of ADI with AD-related outcomes across biological and social factors may reflect systemic health disparities and study design.

Objectives. Despite the body of literature on genetic risk factors for dementia, little is known on protective genetic factors associated with favourable cognitive ageing in the oldest population. In Europe, Italy has a leading position with a swelling population of centenarians, and the urban area of Genoa in the Liguria region has one of the highest prevalence of centenarians. The COOL study is a not-for-profit, multicentric study involving a cohort of centenarians (aged >99) living in the Genoa area. The ultimate aim is the identification of genomic biomarkers associated with cognition in the oldest old population. Results. Participants underwent a semi-structured interview on personal, disease and family history, and a neuropsychological assessment of the main cognitive domains. As of July 2025, we enrolled 88 centenarians (age range: 99-108, median 100.56) with and without cognitive impairment; 32 subjects were followed up. All participants were of Italian ancestry, 81% were female. The cognitive profile in assessed subjects showed a wide range of cognitive health measures (CDR 0-5; MMSE 3-30, median 24). Whole peripheral blood and DNA samples from 67 participants were stored. Conclusions. We demonstrated that the protocol is feasible, and acceptable by participants and their families. A comprehensive phenotype dataset was established, and DNA samples were stored. Centenarians exhibited a broad spectrum of cognitive profiles, from preserved cognition to severe dementia. These findings will eventually allow to interpret the profiles of genomic variants as associated with variability of cognitive performance in centenarians. The molecular underpinnings of healthy cognitive ageing could inform health policy strategies in the general population.