Journal of Alzheimer’s Disease

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.

INTRODUCTION: The Diabetes Prevention Program (DPP) was a randomized clinical trial designed to prevent type 2 diabetes (T2D) in adults with prediabetes. The DPP Outcomes Study (DPPOS) is the 30-year follow-up of this cohort, focusing on T2D, prediabetes, and related complications. Cognitive assessments began in 2009 and expanded in 2022 to examine cognitive impairment, including Alzheimer's disease (AD) and AD related dementias (ADRD), in the surviving cohort. To support these aims, the National Alzheimer's Coordinating Center Uniform Data Set version 3 (NACC-UDSv3), the standardized framework used by Alzheimer's Disease Research Centers, was implemented in DPPOS in 2022 to enable data sharing with NACC. These forms were complemented by cognitive tests administered in DPPOS. We aimed to integrate the NACC-UDSv3 into the existing longitudinal DPPOS framework while maintaining fidelity to its structure and developing automated reports to streamline cognitive outcomes adjudication. METHODS: Items from the 16 NACC-UDSv3 data forms were compared with those already collected within DPPOS to integrate overlapping similar items, add missing NACC-UDSv3 items, and create a dataset harmonized with NACC-UDSv3. Forms were adapted for electronic data capture (EDC) using the MIDAS (Multimodal Integrated Data Acquisition System, George Washington University). Automated reports integrated current and prior neuropsychological scores to support adjudications. In the first wave of the DPPOS-AD/ADRD study, 1561 cognitive adjudications were successfully completed using the harmonized DPPOS and NACC-UDSv3 data implemented into MIDAS. DISCUSSION: The DPPOS-AD/ADRD project demonstrated that NACC-UDSv3 can be successfully integrated into a long-standing longitudinal cohort not originally designed for AD/ADRD research. The harmonization, electronic capture, and automated adjudication processes may provide a practical framework for other cohorts seeking to incorporate NACC-UDSv3 to align with national AD/ADRD research standards.

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.

Importance: Alzheimer's disease (AD) arises from complex interactions among genetic, clinical, and social determinants of health (SDoH) risk factors, yet their independent contributions to underlying AD pathophysiology remain elusive. Objective: To quantify the effects of risk factors across amyloid (A{beta})/tau, neurodegeneration, and cognition. Design: Cross-sectional analysis using structural equation modeling (SEM). Setting: Health and Aging Brain Study-Health Disparities (HABS-HD), a community-based cohort study. Participants: A total of 2,276 participants with demographics, genetic, clinical, and biomarker data from the baseline visit. Exposures: APOE e4 carrier status, AD polygenic risk score (AD-PRS), clinical risk score (CogDRisk), and a social determinants of health (SDoH) latent score derived using factor analysis. Main Outcomes and Measures: Latent variables representing A{beta}/tau pathology (plasma pTau181, plasma pTau217/A{beta}42, amyloid PET positivity, and global standardized uptake value ratio), neurodegeneration (plasma neurofilament light, cortical thickness, hippocampal volume), and cognition (memory, executive, and language tests) were modeled and regressed on AD latent variables using SEM adjusted for age, sex, genetic principal components, and spoken language. Results: The total analytic sample included 2,276 participants (mean age: 65.3 {+/-} 8.7; non-Hispanic White: 43.0%, non-Hispanic Black: 16.2%, and Latinx/Hispanic adults: 40.8%). APOE e4 was strongly associated with worse A{beta}/tau latent variable ({beta}=0.31; p<0.001), with smaller but significant associations with neurodegeneration ({beta}=0.085; p<0.001) and cognition ({beta}=0.083; p<0.001). Higher AD-PRS was modestly associated with worse A{beta}/tau ({beta}=0.075; p<0.01) but was not associated with neurodegeneration or cognition. A higher clinical risk score was significantly associated with worse neurodegeneration ({beta}=0.16; p<0.001) but not with A{beta}/tau or cognition. Adverse SDoH was associated with worse neurodegeneration ({beta}=0.071; p<0.05) and strongly associated with worse cognition ({beta}=0.22; p<0.001), with no associations with A{beta}/tau. Conclusion and Relevance: Genetic risks were primarily associated with A{beta} and tau pathology, clinical risks with neurodegeneration, and SDoH risks with cognition, suggesting that risk factors exert differential effects on AD pathophysiology. Future studies investigating additional risk factors and their longitudinal associations with AD pathophysiological changes are warranted.

Vascular dementia (VaD) is a complex clinical syndrome arising from cerebrovascular disease, characterized by cognitive decline and functional impairment, and is projected to double in prevalence over the next three decades. Deficiencies in one-carbon (1C) metabolism are linked to the onset of VaD. Our previous work using mouse models has demonstrated that reduced dietary folic acid intake or genetic disruptions in 1C metabolism exacerbate outcomes in a model of VaD. However, the impact of VaD on one-carbon metabolism remains poorly understood. This study aims to provide a detailed molecular portrait of 1C metabolism within the context of VaD, shedding light on potential molecular mechanisms. In post-mortem medial prefrontal cortex tissue from VaD female and male patients and controls we measured protein expression of the folate receptor (FR) and 1C enzymes including methylenetetrahydrofolate reductase (MTHFR), thymidylate synthase (TS), choline acetyltransferase (ChAT), acetylcholinesterase (AChE), cystathionine {beta}-synthase (CBS) co-localized with NeuN. There was an interaction between VaD and gender for levels of FR. Both male and female VaD had increased levels of ChAT. Female VaD patients had higher levels of MTHFR and CBS when compared to males. VaD is a complex disease; the results of this study demonstrate that VaD impacts neuronal levels of 1C enzymes. Future studies should assess 1C in other cell types of the brain, as well as measure enzyme activity levels.

Persistent racial disparities in dementia raise concerns regarding the validity and generalizability of existing prognostic models across diverse populations. We evaluated the utility of the 2024 Lancet Commission risk factors and resting heart rate (RHR) for race-specific dementia risk prediction using data from 55,004 participants in the National Alzheimer's Coordinating Center cohort. Cox proportional hazards and Random Survival Forest (RSF) models were developed separately for Black, White, Asian, and American Indian participants to predict 1-, 3-, and 5-year time to dementia. RSF consistently outperformed Cox models across all racial groups and prediction horizons, achieving 5-year AUCs of 0.88-0.91 compared with 0.69-0.81 for Cox models. Inclusion of RHR modestly and consistently improved predictive performance across racial groups. Predictor importance varied between racial groups, suggesting heterogeneity in dementia risk profiles and disease presentation. These findings support the potential utility of RHR as a complementary prognostic biomarker and highlight the importance of equitable, personalized dementia risk prediction across diverse populations.

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.

Impairment in the comprehension of morphosyntactic and transitivity information does not feature in current diagnostic guidelines for primary progressive aphasia (PPA) or Alzheimer's Disease (AD), despite research reporting delayed sensitivity or insensitivity of these clinical populations to these linguistic domains. Moreover, studies rarely compare all three PPA variants and AD within a single design, and the literature is weighted toward English, whose reduced morphology may not capture the full range of comprehension difficulties these populations experience. We developed a computer-based acceptability judgment task covering comprehension of the nominal and verbal inflection paradigm in Spanish, transitivity and word order. We recruited Spanish-speaking patients diagnosed with non-fluent/agrammatic, logopenic and semantic variants of PPA and typical AD. Psychometric evaluation confirmed good sensitivity, internal consistency and moderate correlation of task accuracy with language and neuropsychological measures. The four clinical groups retained the ability to endorse grammatical sentences but showed selective difficulty rejecting unacceptable ones. AD and the three PPA variants showed impaired comprehension of inflectional and transitivity information, whereas sensitivity to word order was comparatively preserved. Exploratory analyses revealed that short-term memory, working memory, and verbal semantics were differentially associated with sentence evaluation performance within and across groups. VBM analyses identified the left posterior temporal cortex as the main neuroanatomical correlate of grammaticality judgment performance. These findings extend prior English-language research to Spanish, demonstrating that morphosyntactic and transitivity deficits are a robust and cross-linguistically consistent feature of neurodegenerative language decline, and highlighting the importance of developing language-sensitive assessment tools for underrepresented linguistic populations.

Background: Alzheimer's Disease and Related Dementias (ADRD) is a growing global public health challenge, and caregivers experience high rates of burden, unmet needs, and system failures. These challenges vary by caregiver role and relationship to the care recipient, reflecting the heterogeneous nature of caregiving. Yet prior work has largely studied burden, unmet needs, and system failures as separate domains rather than examining how they co-occur within individual caregivers. Methods: We applied an LLM-based classification framework (Claude 3.5 Sonnet) to 7,198 posts from three ALZConnected caregiver forums (general, spouse/partner, and adult child caregivers), coding each post for burden, unmet needs, and system failures across 9, 12, and 10 categories respectively. We compared expression rates by caregiver role (primary vs. secondary) and relationship to the care recipient (spousal vs. child) and used post-level co-occurrence networks to map how categories cluster within and across domains. Results: Burden was expressed in 89.0% of posts and unmet needs in 93.3%, while system failures appeared in 34.8%. Primary caregivers reported burden more often than secondary caregivers (91.6% vs. 84.7%), while secondary caregivers reported more unmet needs (94.6% vs. 92.5%) and more system failures (37.2% vs. 33.4%). Child caregivers reported higher rates than spousal caregivers across all three domains. Co-occurrence networks showed dense within-domain clustering (density 0.61-0.65) and 84 significant cross-domain connections, with the strongest links between behavioral/safety burden and safety-management needs (21.7% of posts) and between emotional burden and emotional-support needs (20.9%). Conclusion: Burden, unmet needs, and system failures are not independent problems but form interconnected challenge ecosystems that vary by caregiver role and relationship. This suggests caregiver support should be designed around these connected patterns rather than treated as separate, single-domain interventions.

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

INTRODUCTION: Neurodegenerative research identifies biomarkers to confirm presence of disease and inform about risk for clinical symptoms. Expert guidance advises caution about disclosing individual research results (IRR), but participant interest remains high even when IRR may not inform individual prognosis. Existing studies of stakeholder attitudes emphasize Alzheimer's disease (AD) biomarkers. We explore participant attitudes toward IRR from the United States CADASIL Consortium (USCC), an observational study of Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL), the most heritable form of vascular dementia. METHODS: Since CADASIL research participant attitudes are unstudied and AD-focused guidelines for IRR may not generalize to populations with dominantly inherited conditions, we surveyed USCC participants using three 5-point Likert items and one open-ended question. Descriptive statistics were analyzed for Likert items. The distribution of responses to one item was directly compared to an AD participant survey. Open-ended responses underwent qualitative content analysis. RESULTS: We received 152 responses. The highest-rated reason to return IRR was "learn about my disease and its predicted course". The highest-rated IRR were imaging/MRI scans and cognitive testing. Hypothetical negative outcomes were rated as a little to somewhat concerning. USCC respondents rated reasons to return IRR higher than AD counterparts, with statistically significant differences for seven of eight items. In open-ended responses, the most frequent code was "IRR return will help improve my health and well-being". DISCUSSION: Most respondents expressed support for disclosure upon participant request. These findings could inform IRR guidance for CADASIL and other disorders and investigations of personal utility.

Alzheimers disease (AD) is characterized by amyloid-{beta} (A{beta}) peptide plaques and neurofibrillary tangles from hyperphosphorylated tau, though factors linking amyloid and tau pathology remain unclear. We investigated whether microRNA-181d-5p (miR-181d) associates with AD-related brain changes and regulates neprilysin and tau. Modeling miR-181d across individuals with no cognitive impairment, mild cognitive impairment, and AD revealed region- and sex-specific associations. Higher miR-181d levels associated with greater AD probability in the temporal lobe and cerebellum, and lower probability in the posterior cingulate cortex of males; miR-181c attenuated these probabilities. SNPs near MIR181 associated with altered entorhinal cortical thickness. In cellular models, miR-181 reduced neprilysin 3'-UTR activity, mRNA, protein, and enzymatic activity, while increasing tau mRNA and protein. Neprilysin diminution impairs A{beta} clearance and elevates tau, contributing to AD. RNA sequencing identified miR-181d-responsive neurodegenerative pathways. These findings identify miR-181 as a regulator of AD-relevant amyloid and tau pathways, providing novel targets. TeaserMiRNA-181 is a key regulator of Alzheimers risk through its effects on neprilysin and tau proteins, a novel potential target.

Importance. Metformin may influence risk of dementia, with prior conflicting observations of protection or harm. Objective. To determine the association of randomization to metformin vs. placebo or intensive lifestyle intervention (ILS) in the Diabetes Prevention Program (DPP) with cognitive outcomes (cognitive impairment syndromes and trajectories of cognitive test performance) during the DPP Outcomes Study (DPPOS). Design, Setting & Participants. Prospective long-term follow-up of DPP/DPPOS participants at 27 U.S. centers among adults who were at high risk for type 2 diabetes (T2D) at baseline. Exposures. Randomization to metformin, placebo, or ILS (1996-1999) for 3.2 years followed by open-label metformin in the original randomized metformin group until 2021. Main Outcomes & Measures. Cognitive impairment syndromes were adjudicated in 2022-2024 in 1,483 participants (median age 74 [IQR 68, 80]) using the National Alzheimer's Coordinating Center Uniform Dataset version 3. Cognitive performance in executive and memory domains was ascertained with repeated cognitive tests between 2009 and 2024. Multinomial logistic regression and mixed-effects models were fit to examine associations of randomization to metformin with cognitive outcomes. Results. Total metformin exposure (mean {+/-} SD) was 15.5 {+/-}7.7 years/person in the metformin group. Persons in the placebo and ILS groups received out-of-study metformin usually after developing diabetes with mean metformin total exposure of 4.5 {+/-}5.1 and 3.8 {+/-}4.8 years/person in the placebo and ILS groups, respectively. Overall, the frequency distributions of the cognitive syndromes did not differ significantly by treatment group; however, randomization to metformin was associated with a 60% (OR 0.40 [95%CI 0.17, 0.97]) and 62% (OR 0.38 [95%CI 0.16, 0.89]) lower odds of dementia compared with placebo and ILS, respectively, after adjustment for demographics, education, income, and APOE-{varepsilon}4 genotype. Randomization to metformin was also associated with significantly better memory performance over time ( {beta} =0.58; 95%CI: 0.09, 1.1; p=0.02; Cohen's d=0.1). Conclusions and Relevance. Long-term metformin treatment is associated with a reduced risk of dementia and better memory performance among persons with pre-diabetes or T2D. Estimates were imprecise due to a limited number of dementia cases. Longer follow-up with more dementia cases is needed to confirm our findings.

Insulin resistance is increasingly recognized as a metabolic factor associated with Alzheimers disease (AD); however, its relevance to hippocampal structural changes--a key pathological feature of AD--across disease stages is not fully understood. To address this issue, we investigated the relationship between insulin resistance, hippocampal gray matter volume, and cognitive performance using data from the Alzheimers Disease Neuroimaging Initiative (ADNI), a large-scale neuroimaging dataset. Insulin resistance was assessed using the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), and its relationship with brain structure and cognitive performance was evaluated across diagnostic groups. In the mild cognitive impairment (MCI) group, higher insulin resistance was associated with larger anterior hippocampal gray matter volume, whereas in the AD group this association was reversed in direction. Furthermore, in the MCI group, anterior hippocampal gray matter volume was also positively associated with higher Mini-Mental State Examination (MMSE) scores, and an exploratory mediation analysis suggested a significant indirect association linking HOMA-IR, anterior hippocampal volume, and cognitive performance through anterior hippocampal volume. These findings suggest that the relationship between insulin resistance and AD-related brain changes differs across diagnostic groups, highlighting the importance of considering metabolic alterations in relation to disease status.

Background & Methods: The multifaceted physical nature of heritable cognitive impairment in dementia presents significant challenges for traditional linear frameworks attempting to model synergistic risk. While various loci are identified as contributing to neurocognitive disparities, the emergent phenotypic expression and associated predictive value relative to standard clinical baselines require further investigation. To facilitate dimensional reduction of complex genetic data into identifiable phenotypes, Generalized Low Rank Modeling (GLRM) and K-means clustering are applied to participant data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The utility of these derived archetypes and clusters is assessed, stratifying variance for Mini-Mental State Examination (MMSE) performance. Utilizing generalized additive modeling (GAM) and partial eta squared (p2) effect size, the derived genetic features are compared with other predictors including age, educational attainment, gender, and raw, genetic variant carriage dimensions. Results & Conclusion: In accordance with the hypothesized empirical regularity, age and education persist as primary predictors of MMSE performance. The unsupervised machine learning pipeline successfully identified a composite genetic cluster that emerged as an influential predictor in terms of relative magnitude (p2). Centroid analysis of the GLRM subspace indicated that a particular sub-population (Cluster 2) - defined by a substantial weighting on the EPHA1 target - demonstrated a statistically significant association with MMSE scores, relative to cluster 3. These results suggest that data-driven genetic feature engineering provides an interpretable basis for inference regarding variance in global cognition. By discovering multivariate genetic architecture, this modeling approach captures complexity often missed by individual clinical variable modeling. Such findings implicate the utility of interpretable machine learning for translational dementia research and predictive clinical stratification.

Importance: Patients are increasingly learning Alzheimers disease (AD) genetic and biomarker results through electronic health portals. Evaluation of alternative scalable delivery models for return of AD risk information is needed to best support patient understanding and psychological well-being. Objective: To determine whether a patient-centered digital platform is comparable to clinician-mediated telehealth sessions for returning APOE and plasma pTau-217 results on outcomes of knowledge and psychological well-being. Design: The Evaluation of Self-Mediated Alternatives for Risk Testing Education and Return of Results (eSMARTER) study was a noninferiority trial of a patient-centered digital platform compared to clinician-mediated disclosure of APOE genotype and optional pTau-217 disclosure. Setting: Decentralized, fully remote trial enrolled participants in the contiguous United States (U.S.) between October 2024 and February 2025, with follow-up completed in November 2025. Participants: Eligible participants were aged 60-80 and had previously undergone APOE genotyping (without disclosure) via the GeneMatch program, passed psychological screening, had internet access, and were English-speaking. Interventions: Participants were randomized, 2:1, to the eSMARTER digital platform or clinician-mediated disclosure of APOE genotype. Following the 6-month post-APOE assessment, participants were offered optional pTau-217 disclosure via the same randomized modality. Main Outcomes and Measures: Primary outcomes at 1-7 days following APOE disclosure included changes in anxiety, disease-specific distress, and AD-related knowledge within a priori non-inferiority margins. Results: 674 persons (mean [SD] age 68 [4.7] years; 451 [67%] female; mean [SD] telephone MoCA=19 [2]) were eligible and provided demographic information. 651 participants were randomized to clinician-mediated (n=216) or digital disclosure (n=435) and completed APOE disclosure (66 [10%] APOE4 homozygotes, 377 [58%] heterozygotes, 208 [32%] non-carriers). 604 participants completed the study; 500 completed optional pTau-217 disclosure. Baseline characteristics were balanced across groups. At 1-7 days following APOE disclosure, scores on AD-related knowledge, PROMIS Anxiety, and disease-specific distress measures met non-inferiority. Conclusions and Relevance: Disclosure of APOE genotype by the eSMARTER digital platform is non-inferior to clinician-mediated telehealth disclosure. No significant between group differences were found following disclosure of pTau-217 results. Together, these results suggest that this digital platform may provide an evidence-based scalable approach for returning AD genetic and biomarker results.

Studies in humans and murine models have pointed towards a possible link between metabolic syndrome, which shows insulin resistance and metabolic dysregulation, and Alzheimer's disease (AD) pathology marked by amyloid-beta (A{beta}) accumulation and hypometabolism in the brain. Yet, the underlying biological mechanisms by which metabolic syndrome affects these pathological changes in AD brain remain unknown. We hypothesized that insulin resistance is responsible for alterations in blood-brain barrier (BBB) transport of A{beta} peptides and glucose. This hypothesis was tested by employing radiolabeled ligands (125I-A{beta}40, 125I-A{beta}42, and 18F-FDG) in high-fat diet (HFD)-fed mouse models that manifest metabolic syndrome. Further, we assessed alterations in the expression of various molecular mediators within the brain microcapillaries harvested from both low-fat diet (LFD)-fed and HFD-fed mice. Our findings show that HFD-fed mice developed peripheral insulin resistance and obesity. In addition, HFD-fed mice demonstrated an increase in the influx rate of A{beta} peptides and a reduction in 18F-FDG (a glucose surrogate) influx rate compared to LFD-fed mice. These transport changes are associated with the increase in the BBB endothelial expression of RAGE (receptor to traffic A{beta} from plasma-to-brain) and reduction of GLUT1 (glucose transporter) expression in HFD-fed mice compared to LFD-fed mice. Moreover, disruption in insulin signaling, as indicated by reduced pAKT and pERK expression, was observed in HFD-fed mice. Inhibiting AKT or ERK phosphorylation resulted in similar changes in A{beta} and glucose uptake in polarized BBB endothelial cell monolayers in vitro. These results indicate that high-fat diet induced metabolic syndrome may lead to BBB dysfunction, characterized by increased plasma-to-brain A{beta} trafficking and diminished glucose transport at the BBB, thereby aggravating the expression of AD pathological hallmarks.

Background: Epidemiological evidence links type 2 diabetes (T2D) to an increased risk of dementia, including Alzheimers disease (AD). However, previous syntheses often combined heterogeneous diabetes and dementia definitions and have not comprehensively quantified AD incidence among individuals with T2D. We aimed to estimate both the incidence of AD among individuals with T2D and the association between T2D and AD using studies with well-defined T2D and AD outcomes. Methods: We systematically searched MEDLINE, CINAHL (via EBSCO), Embase (via Ovid), and Scopus from inception to April 2026 for studies investigating the incidence of AD among individuals with T2D or the association between T2D and AD. Data were pooled using random-effects models and presented as incidence rates and adjusted relative risks (RRs) with 95% confidence intervals (CIs). Results Of the 9,430 articles identified, 40 studies involving 27,102,559 participants were included. Twenty-three studies contributed incidence data, and 26 reported adjusted relative risks (aRR). The pooled incidence of AD among individuals with T2D was 4.71 per 1,000 person-years (95% CI 3.31, 6.71). T2D was associated with an increased risk of AD (aRR 1.53, 95% CI 1.38, 1.70). Subgroup findings were generally consistent, results were robust in sensitivity analyses, and no publication bias was detected. Conclusions: This study provides a comprehensive quantification of the AD burden associated with T2D by focusing on well-defined AD and T2D outcomes and advancing the field beyond prior broad dementia syntheses. Integrating incidence and relative risk estimates clarifies both the absolute and relative burden of AD in T2D and extends previous syntheses that primarily emphasised relative risk. Individuals with T2D experienced approximately five AD cases per 1,000 person-years and a 53% higher risk of AD, supporting the rationale for integrating cognitive risk prevention into diabetes care.

Although prenatal alcohol exposure (PAE) has been proposed as an early-life risk factor for Alzheimers disease and related dementias (AD/ADRD), the mechanistic underpinnings are underexplored. Mutations in the Presenilin genes contribute to AD/ADRD, with Presenilin 1 acting as the catalytic subunit of the {gamma}-secretase complex responsible for cleaving Notch and amyloid precursor protein (APP). We hypothesized that PAE disrupts {gamma}-secretase activity during brain development, which persists and is associated with behavioral deficits later in life. Pregnant wild-type B6129 and 3xTg-AD mice were fed an ethanol-containing liquid diet during gestational days 13-15. From birth to adulthood, PAE increased APP C-terminal fragments and Notch intracellular domain (NICD) levels in cortical lysates. These changes were associated with impaired hippocampal-dependent learning and memory in wild-type mice at 3 and 6 months of age and exacerbated behavioral deficits in 4-month-old 3xTg-AD mice. Our findings provide the first mechanistic insight linking PAE to AD/ADRD vulnerability.

While loss of NMDA receptors (NMDARs) is associated with Alzheimers disease (AD) severity, the effect of sex or the relationship between regional NMDAR density and antemortem cognitive status across the AD spectrum has not been examined. We performed quantitative in vitro autoradiography of hippocampus, entorhinal cortex (EC), and parietal cortex using NMDAR and tau radioligands. Relationships between regional NMDAR density and cognitive status assessed by the Mini Mental State Exam (MMSE), and between NMDAR and tau density, were examined by bivariate correlations. In both sexes, the largest AD-related decreases in NMDAR density were observed in the CA1 field. However, there was a significant diagnosis by sex interaction driven by sex-specific changes in the mild cognitive impairment (MCI) stage, with lower NMDAR density in MCI women, but not MCI men relative to same-sex controls. Within diagnosis analyses revealed positive correlations between NMDAR density and MMSE scores and significant negative correlations between EC NMDAR and tau density, which was significant only in AD men. Our data show that changes in hippocampal NMDAR density across the AD continuum are modulated by sex and may contribute to the known sex differences in the clinical trajectory of the disease.