The Journal of Prevention of Alzheimer's Disease

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: International Classification of Diseases (ICD) codes are often used in epidemiological studies to track disease rates over time. Objective: This evaluation of ICD-code-based algorithms for electronic medical record (EMR) studies of Alzheimers disease (AD) and related dementias (ADRD) examines the impact of incorporating Centers for Medicare and Medicaid (CMS) data as an additional source of diagnostic and treatment information in Department of Veterans Affairs (VA) EMR studies. Methods: We performed a chart review of 100 VA Million Veteran Program (MVP) participants to evaluate algorithm performance. We also assessed genetic associations across algorithms in a large MVP cohort (n=396k). Results: Adding CMS data increased the number of detected cases, sensitivity, and positive predictive value, but decreased specificity and negative predictive value. Genetic analyses showed that broader (ADRD/dementia) algorithms with just VA data performed similarly to narrow (AD-focused) algorithms incorporating both VA and CMS ICD codes. Additionally, narrow AD algorithms based solely on VA data yielded the highest ORs, indicating the largest proportion of late-onset AD cases. Conclusions: We recommend using a broad (ADRD) algorithm without CMS or medication data, particularly for epidemiological studies or a strict AD algorithm including CMS and medication cases for genetic discovery of late-onset AD associations in VA EMR, and a strict AD algorithm without CMS data for applications focused solely on AD and sensitive to misspecification. Careful evaluation of algorithm performance is warranted in different EMR systems, as ICD coding practices vary by institution, as demonstrated by this comparison of VA EMR and CMS data.

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.

Background: Anti-amyloid antibody therapies have changed the clinical pathway for early Alzheimer disease (AD). Lecanemab and donanemab are now clinically available in many countries, including Japan, and their use requires biomarker confirmation, repeated magnetic resonance imaging monitoring, management of amyloid-related imaging abnormalities, infusion capacity, staff resources, and shared decision-making. In Japan, these treatments are provided under the universal public health insurance system and are regulated by the optimal use guidelines. Therefore, it is important to understand not only the number of treated patients but also how specialists perceive clinical, logistical, and policy challenges in routine practice. Objective: This paper describes the protocol for a nationwide anonymous online survey of dementia specialists in Japan. The survey aims to evaluate the real-world implementation of anti-amyloid antibody therapies, including current clinical practice, facility readiness, perceived barriers, possible policy solutions, and physician preferences assessed using a discrete choice experiment and best-worst scaling. Methods: This is a prospective, cross-sectional, anonymous online survey using Google Forms. The survey targets board-certified specialists of the Japanese Society for Dementia Research and the Japanese Psychogeriatric Society, with a main focus on physicians who have completed the official training course required for anti-amyloid antibody therapy. The questionnaire includes items on respondent and facility characteristics, perceived value of treatment, treatment experience, diagnostic and eligibility assessment, amyloid and APOE testing, MRI monitoring, infusion capacity, continued-administration facilities, blood-based biomarkers, preclinical AD, a discrete choice experiment, and best-worst scaling. Among respondents routed to the DCE section, the discrete choice experiment asks respondents to choose between hypothetical anti-amyloid antibody treatment profiles for early AD, defined by expected efficacy, risk of amyloid-related imaging abnormalities requiring treatment interruption or discontinuation, treatment duration, visit frequency, waiting time, and monthly out-of-pocket cost. Best-worst scaling evaluates the relative importance of policy and system-level solutions. Results: Data collection started on June 3, 2026, and is planned to close on June 30, 2026. This protocol was prepared before data lock and before any outcome analyses. The main results will be reported after data cleaning and analysis according to the prespecified analysis plan. Conclusions: This protocol describes a nationwide survey designed to clarify clinical, logistical, and policy challenges in the implementation of anti-amyloid antibody therapies in Japan. By publishing the survey design and analysis plan before data lock, this study aims to improve transparency and interpretability. The findings will help identify where Japanese dementia specialists perceive bottlenecks in diagnosis, biomarker testing, safety monitoring, infusion delivery, continued administration, and reimbursement. They may also inform policy discussions on APOE testing, blood-based biomarkers, regional care coordination, and service reimbursement for anti-amyloid antibody therapy.

Background: Electronic health record (EHR)-linked biorepositories provide opportunities to advance epidemiological research in Alzheimer's disease (AD) and related dementias. Objective: Evaluate the extraction, curation, and associative validity of Mini Mental State Examination (MMSE) scores from the VA EHR for participants in the VA Million Veteran Program (MVP). Methods: The sample (N = 49,555; 7.4% women) included a multiethnic cohort (European [68.3%], African [20.4%], Hispanic [9.0%]) with EHR-extracted MMSE scores; 30.7% were apolipoprotein E (APOE) {epsilon}4 carriers, and 25.8% had multiple scores. Linear regressions examined cross-sectional associations between {epsilon}4 dosage (0, 1, 2) and first and lowest MMSE scores. MMSE scores were also evaluated against MVP dementia diagnostic algorithms in participants aged [&ge;]65 years. Results: Among participants of European ancestry, there was a significant {epsilon}4 dose-response relationship (ps < .001) with MMSE scores. Homozygote carriers scored lower than heterozygote carriers (Mdiff: first = -0.5; lowest = -0.9), who scored lower than non-carriers (Mdiff: first = -0.4; lowest = -0.6). Among Veterans of African and Hispanic ancestry, no dose-response relationship was observed, although {epsilon}4 carriers had lower scores than non-carriers (ps [&le;] .04). MMSE scores corresponded strongly with dementia case/control status across phenotypes: mild impairment on the MMSE was strongly associated with AD (odds ratio [OR] = 11.48), with more severe MMSE impairment showing stronger associations (moderate OR = 17.95; severe OR = 27.83). Conclusion: This study demonstrated MMSE scores can be systematically extracted and curated from the VA EHR. Findings offer a scalable framework for future studies on risk stratification, highlighting the potential for harnessing MVP to explore genetic and clinical factors contributing to cognitive and dementia outcomes in diverse samples.

Background: The heart-brain axis links cardiovascular and neurodegenerative disease through shared vascular and inflammatory mechanisms. Although low-density lipoprotein cholesterol (LDL-C) is an established causal factor in atherosclerotic cardiovascular disease (ASCVD), its relationship with dementia remains uncertain, with midlife elevations associated with increased risk but late-life associations often appearing null or inverse. To address this cholesterol paradox, we integrated mendelian randomization (MR) with an active-comparator new-user target trial emulation. Methods: We applied a triangulated causal inference framework integrating two-sample MR with observational target trial emulation. Genetic variants associated with LDL-C were used as instrumental variables to evaluate Alzheimer disease (AD), dementia with Lewy bodies (DLB), frontotemporal dementia (FTD), and any dementia (AnyDem), with causal estimates derived using inverse-variance weighted models and sensitivity analyses for heterogeneity and pleiotropy. In parallel, an active-comparator new-user design compared statin versus ezetimibe initiation among adults aged 60 years or older using propensity score (PS) overlap weighting and Cox proportional hazards models to evaluate cardiovascular and dementia outcomes. Results: Genetically predicted LDL-C was associated with increased risk of DLB (OR 1.65, 95% CI 1.30-2.10; p<0.001), but not AD or AnyDem; FTD estimates were inconsistent. Sensitivity analyses suggested heterogeneity and possible pleiotropy for DLB. In the observational analysis (n=6,977), statin initiation was associated with higher risks of ASCVD (HR 1.26, 95% CI 1.11-1.45) and AnyDem (HR 1.66, 95% CI 1.16-2.38), although estimates attenuated after lipid adjustment and lagged analyses, suggesting residual confounding, treatment selection, and reverse causation in late-life observational associations. Conclusions: These findings suggest that LDL-C reflects accumulated vascular and metabolic risk rather than a direct causal driver of AD or overall dementia, although a subtype-specific association was observed for DLB. Late-life associations appeared influenced by timing, reverse causation, and treatment selection, warranting cautious interpretation. Keywords: Heart-brain axis, dementia, cardiovascular disease, low-density lipoprotein cholesterol, causal inference

BACKGROUND: Differences in renal function may affect Alzheimer disease (AD) blood biomarker levels independent of AD pathology. Although renal function was unaccounted for in foundational AD blood biomarker studies, there is potential to address this through quantification of estimated glomerular filtration rate (eGFR) from frozen serum and plasma samples. However, the validity of eGFR evaluation from long-term frozen blood samples is unknown. METHODS: Adults aged 50-85 with at least 2 vascular risk factors were recruited from vascular surgery or cardiology clinics in Tucson, Arizona from 2022-2025. Individuals with creatinine assessments in point-of-care whole blood (POC-WB) and frozen serum and plasma samples using the iSTAT (Abbott) were included. eGFR was calculated using the 2021 CKD-EPI creatinine equation without race. Agreement between POC-WB and frozen blood samples was assessed using Cohen's kappa with linear weights. RESULTS: 134 participants (mean [SD] age: 72.6 [7.5] years, 39.6% female, 23.1% chronic kidney disease) had POC-WB eGFR available. Frozen serum and plasma samples had strong agreement with POC-WB for eGFR (Kw= 0.90-0.95, P<0.001). Pre-analytical factors had minimal effect on eGFR differences between POC-WB and frozen blood samples. CONCLUSIONS: Renal function can be assessed from frozen blood samples with high consistency to POC-WB, which may be particularly relevant for interpretation of AD blood biomarkers in general aging and vascular populations who often have impaired renal function.

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.

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

ABSTRACT INTRODUCTION: Early identification of individuals with mild cognitive impairment (MCI) at high risk of conversion to Alzheimer's disease (AD) is essential for timely intervention. We evaluated whether routinely obtainable clinical assessments can accurately predict 24-month MC to AD conversion. METHODS: Data from 2,430 participants with MCI in the Alzheimer's Disease Neuroimaging Initiative were analyzed. XGBoost, Random Forest, and Logistic Regression models were evaluated. SHAP-based feature selection and feature ablation analyses assessed the incremental value of APOE4 genotype. RESULTS: A six-feature model incorporating age, sex, education, RAVLT Immediate Recall, MMSE, and EcogSPTotal achieved an AUC of 0.922 (95% CI, 0.911~0.933). APOE4 provided negligible additional predictive value once cognitive measures were included. The XGBoost model outperformed Clinical Dementia Rating Sum of Boxes classification. DISCUSSION: Routine cognitive assessments accurately predict 24-month MCI-to-AD progression without biomarkers, neuroimaging, or genetic testing, offering a practical, low-cost tool for clinical risk stratification.

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: Dementia, particularly Alzheimer disease (AD), is a major global health challenge, with prevalence projected to reach 150 million cases by 2050. AD is characterized by progressive cognitive decline linked to neuroinflammation and neurodegeneration. Non-steroidal anti-inflammatory drugs (NSAIDs) have been explored as potential neuroprotective agents, particularly diclofenac, which has been proposed to modulate microglial inflammasome signaling. However, prior studies investigating NSAIDs in AD have yielded inconsistent findings. We therefore reexamined the relationship between selected NSAIDs and dementia outcomes in a large longitudinal cohort from the National Alzheimer Coordinating Center (NACC). METHODS: We analyzed cross-sectional and longitudinal data from the NACC database collected between 2005 and 2022. Associations between NSAID exposure and dementia, AD, and cognitive trajectories were examined. Propensity score matching was performed to compare NSAID users with matched non-users while adjusting for demographic and clinical confounders. Longitudinal mixed-effects models were used to assess cognitive decline based on Montreal Cognitive Assessment (MoCA) scores. RESULTS: Among 47,165 participants, diclofenac and naproxen use were associated with a lower prevalence of dementia and AD compared with matched non-users, whereas etodolac showed no significant associations. Diclofenac users demonstrated reduced odds of dementia and AD. Naproxen showed similar cross-sectional associations. In longitudinal modeling, diclofenac users had a significantly slower rate of cognitive decline than non-users. DISCUSSION: These findings suggest a compound-specific association between NSAID use and AD, with diclofenac potentially modulating disease progression through anti-inflammatory mechanisms. The observed modulation of longitudinal cognitive decline supports further investigation of inflammatory pathways, including microglial and inflammasome signaling, as therapeutic targets in biomarker-defined AD populations.

Background: Growing evidence suggests that urinary {beta}-amyloid precursor protein (A{beta}PP) fragments can serve as an early screening biomarker for mild cognitive impairment and dementia. However, in reality, older adults, regardless of the presence of cognitive decline, often suffer from multiple age-related conditions and are on multiple medications. How these comorbidities and treatments affect the performance of early diagnostic biomarkers remains unclear. Methods : This study further validated the sensitivity, specificity, and clinical value of the Qankorey (R) urinary {beta}-amyloid protein detection kit in early dementia screening through a randomized community screening (n=51187) conducted in Changsha, and a multicenter case-control study conducted at Yuquan Hospital (Tsinghua University), Tiantan Hospital (Capital Medical University), Beijing Friendship Hospital, Zibo 148 Hospital (Shandong), and the Third People's Hospital of Yunnan Province. The multicenter case-control study included 898 participants, comprising 266 healthy, age-matched controls without any comorbidities, 167 patients with mild cognitive impairment/Alzheimer's disease (MCI/AD), and 465 non-AD patients with various comorbidities and age-related diseases. Results: The kit showed a significant age-dependent positive rate in both men and women in Changsha, increasing from 6.29% to 15.40%. The number of weakly positive/positive/negative individuals in the healthy group, non-AD group, and MCI/AD group were 8/12/246 (positive rate 7.52%), 41/16/409 (12.23%), and 77/44/46 (72.46%), respectively, with a Kappa value of 0.669, indicating that the method performed well in the clinical diagnosis of MCI/AD, consistent with previously published results. Among the 8 weakly positive healthy subjects, 6 were found to have brain abnormalities by MRI/CT examination. Comorbidity analysis showed that memory decline was the most significant risk factor (P=9.6 x 10^-23, Fisher's exact test), followed by dizziness (P=1.3 x 10^-14;) , hyperlipidemia (P=3.2 x 10^-12) , history of stroke (P=0.0011), and hypertension (P=0.0058). Treatment analysis showed that cardiovascular drugs and antithrombotic drugs significantly reduced the risk of dementia (P values were 0.0061 and 0.0081, respectively), followed by hypoglycemic drugs (P=0.0358). For AD patients, those receiving only memantine showed a slightly lower positive test rate (P=0.0532). Conclusion: Our findings confirm the diagnostic value of urinary {beta}-amyloid protein detection in MCI and AD-related dementia. Furthermore, this kit can be used in practical clinical applications to assess the risk of cognitive decline and treatment efficacy across various diseases.

INTRODUCTION: The biomarker-based amyloid/ tau/ neurodegeneration (A/T/N) framework has become a popular staging method for Alzheimer's disease (AD) research. Previous studies use the framework either as a rule-based or data-driven approach but typically sacrifice either adaptivity or interpretability. METHODS: We present an interpretable, hybrid method, called Neurosymodal Data Fusion, for predicting incident AD in the ADNI dataset. Specifically, we encode the A/T/N framework as a logic program, where the input biomarker features are extracted by one or more neural networks. RESULTS: Our pipeline predicted four-year incident AD with a sensitivity of up to 0.84. Additionally, our models learned scores for each A/T/N profile, denoting relative importances to model predictions. These scores also indicated that empirically-derived cut-off values for the A and T criteria might be uninformative for the ADNI data. DISCUSSION: Our pipeline provides a novel way to use the A/T/N framework that could potentially improve early AD screening years before clinical manifestations.

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.

Background: Alzheimer's disease and related dementias (ADRD) affect over 7.2 million Americans aged 65 and older, with the APOE-4 allele representing the strongest known genetic risk factor. Physical activity (PA) has been associated with reduced dementia risk, but its interaction with APOE genotype remains poorly characterized in large, genomically informed cohorts. Methods: We conducted a retrospective cohort analysis using linked genomic, survey, and longitudinal electronic health record data from the VA Million Veteran Program (MVP). Veterans aged <65 at enrollment with available APOE genotype data, at least 10 years of prior VA medical history, and a completed Lifestyle Survey were included. Individuals with a pre-existing ADRD diagnosis were excluded, yielding a final cohort of 137,593 veterans. Self-reported vigorous physical activity (PA) was ascertained from the MVP Lifestyle Survey and coded as both a four-level ordinal variable and a binary active/inactive classification. The primary composite outcome was incident ADRD or all-cause mortality. Cox proportional hazards models were fitted adjusting for age, sex, race/ethnicity, and baseline comorbidities. A multiplicative interaction term between APOE {varepsilon}4 allele count and PA level was included to formally test for effect modification. Results: Over a median follow-up of 84 months, 65,628 participants (47.7%) experienced the composite outcome. Each additional APOE-4 allele was associated with a 19% increase in risk (aHR = 1.19, 95% CI 1.17-1.21), while active individuals had a 33% lower risk compared to inactive individuals (aHR = 0.67, 95% CI 0.66-0.68). A statistically significant interaction between APOE-4 burden and PA was identified (p < 0.005). Stratified analyses demonstrated that the protective association of PA was present across all genotype groups, with homozygotes demonstrating a 22% risk reduction among active individuals. Conclusions: In this large veteran cohort, vigorous PA was independently and significantly associated with reduced risk of incident ADRD or death across all APOE genotype groups, with the greatest absolute benefit observed among individuals at highest genetic risk. These findings support the prioritization of PA as a targeted preventive strategy, particularly for APOE-4 carriers.

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.

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.

Structured AbstractO_ST_ABSBackgroundC_ST_ABSSubjective cognitive decline (SCD) is associated with increased cognitive impairment and dementia. However, limited research has explored how amyloid (A) pathology contributes to these cognitive changes over time and whether these changes differ by sex. Methods1185 cognitively normal older adults (955 A-, 230 A+; 959 SCD-, 226 SCD+) from the National Alzheimers Coordinating Center dataset were included. Linear mixed effects examined the interactions between SCD, sex, and amyloid positivity in predicting cognitive decline. ResultsSCD+ and A+ individuals exhibited increased global cognition declines (p<.05), and A+SCD+ individuals showed the steepest decline in global cognition and function status (p<.05). A+ males exhibited increased functional deficits (p<.05), while A+SCD+ females exhibited increased language deficits (p<.05). DiscussionOur findings suggest that SCD and amyloid-positivity differentially impact global cognition, functional status, and language in males versus females, with important implications for clinical trials and therapeutic interventions. Highlights- Few studies have explored the independent and joint effects of amyloid and sex in SCD - SCD is associated with increased rates of global cognitive decline - Amyloid positive females with SCD exhibit increased language declines - Amyloid positive males exhibit increased functional status declines Research in ContextO_ST_ABSSystematic reviewC_ST_ABSWe reviewed the literature using traditional sources (e.g., PsycInfo, PubMed) and found that there are limited findings exploring longitudinal cognitive trajectories in people who are amyloid positive with SCD and whether these trajectories differ by sex. InterpretationOur findings suggest that SCD and amyloid positivity jointly interact to influence global cognitive and functional declines. Females experience language deficits when they have both SCD and amyloid positivity whereas males with amyloid positivity exhibit increased functional deficits. Together these findings suggest that SCD status and amyloid positivity differentially impact females and males. Future directionsMore research is needed using grouping amyloid, tau, neurodegeneration, and vascular pathologies together to explore the joint impact on cognitive change and conversion in people with SCD.

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.