Alzheimer's & Dementia: Translational Research & Clinical Interventions

Background: Low-dose levetiracetam is under investigation as a potential treatment for slowing Alzheimer's Disease progression. This study tests whether levetiracetam enhances executive function in mid-age adults, and whether drug effects differ by Apolipoprotein e4 (APOE4+) genetic risk status. Methods: Fifty-eight adults (aged 45-65 years; 27 APOE33; 31 APOE4+) participated in a double-blind, placebo-controlled study of low-dose levetiracetam (125mg bidaily for two-weeks). At the end of each treatment phase, participants completed a switch-inhibition task. Results: Mid-age APOE4+ carriers were significantly slower and showed a greater cost of increasing executive demand than APOE33 individuals. Response times were quicker under levetiracetam, with increased benefits reported in APOE33 individuals, at younger ages, and in individuals with reduced levels of plasma-based biomarkers. Levetiracetam selectively benefitted accuracy in APOE33 individuals. Conclusion: Low-dose levetiracetam enhances executive function in midlife, particularly in individuals at lower risk of Alzheimer's Disease based on age, APOE4 genotype, and proxies of neuropathology.

Objective: Alzheimer's disease (AD) is a leading cause of death and disability, and treatment options for Alzheimer's disease and related dementias (ADRD) remain limited. We applied a data-driven, mechanism-agnostic Medication-Wide Association Study Plus (MWAS+) framework to identify candidate medications associated with ADRD using longitudinal electronic health record data and explainable artificial intelligence (AI). Methods: We used Veterans Health Administration electronic health record data from January 1999 to May 2022. The initial study population comprised 8,424,715 Veterans aged 65 years or older. Cases were defined by ADRD-related diagnosis codes or ADRD-related medication prescriptions, and controls were free of ADRD diagnosis and ADRD-related medication use. After exclusions and matching on sex, race, age at first encounter, and duration of follow-up, the primary analytic cohort included 505,817 matched case-control pairs (1:1; 1,011,634 Veterans). Longitudinal features were extracted from historical data up to 1 year before the index date and aggregated into 1-year intervals. We developed an upgraded Hybrid Value-Aware Transformer (HVAT 2.0) to jointly learn from longitudinal and nonlongitudinal clinical data while incorporating numerical values associated with clinical concepts, including cumulative medication dose. To enhance interpretability, we applied a medication-specific impact score method to estimate model-derived associations between medication exposure and ADRD risk. Findings: The model demonstrated stable performance across data partitions, with area under the receiver operating characteristic curve values of 0.791 in the training set, 0.772 in the validation set, and 0.775 in the testing set. Metolazone and varenicline were identified as the top 2 candidate medications with negative impact scores, suggesting potentially protective associations with new-onset ADRD. The impact score was -0.196 per unit of cumulative dose for metolazone (1800 mg) and -0.134 per unit for varenicline (280 mg). Although individual-level impact scores varied, most exposed patients had negative scores, including 12,020 of 12,480 metolazone users (96%) and 8,341 of 8,786 varenicline users (95%). Implications: This study demonstrates the feasibility of combining a medication-wide association framework, longitudinal dose-aware modeling, and explainable AI to identify candidate medications for ADRD from real-world electronic health record data. The findings should be interpreted as signals for hypothesis generation rather than evidence of causality. This framework may support prioritization of repurposing candidates for expert review, follow-up cohort validation, and future clinical investigation.

Clinical Dementia Rating (CDR) scores are used to classify the cognitive state of patients and are provided within neuroimaging datasets. This is achieved through a standardized clinical assessment that evaluates participants cognitive and functional abilities in everyday life, after which they are given a score ranging from 0 to 3. Where 0 represents no signs of dementia and three represents severe dementia1. These scores are then used to track the progression of dementia over time2. This study explored if these CDR labels within the OASIS-1 dataset produced consistent volumetric separation across the hippocampus, amygdala, and cortex.

STRUCTURED ABSTRACTO_ST_ABSINTRODUCTIONC_ST_ABSA higher incidence of dementia, including Alzheimer s-like pathology, is observed in aged people living with HIV-1. However, mechanisms linking HIV-1 to Alzheimers disease (AD) pathology remain unclear, due to the lack of animal models that allow for concurrent study. METHODSWe created a novel APP knock-in (KI) AD mouse, NOG/APPKM670,671NL/IL-34 (hNAIL) that permits study of progressive brain HIV-1 replication. The mice harbor human microglia-like cells. Four-month-old CD34+ human cell reconstituted mice infected with the HIV-1ADA strain facilitated studies of HIV-1 replication on AD pathologies. RESULTSHIV-1 replication increased A{beta} levels and reduced synaptic and neuronal integrity. Spatial transcriptomics demonstrated distinct A{beta} and HIV-1 transcriptional patterns, whereas dual diseased combinations amplified AD pathology. Neurons showed highest transcriptional change, with genes linked to neuroinflammation, protein trafficking, and synaptic dysfunction. DISCUSSIONThe hNAIL mice enable interrogation of HIV-AD comorbidities, with a future potential for the development of novel therapeutic interventions.

Objectives: To investigate the association between pulse pressure and dementia incidence, independent of other blood pressure measurements and established risk factors, and to assess whether this association differs across dementia subtypes. Design: Prospective population-based study. Setting: UK Biobank. Participants: Of the 502,211 participants in the UK Biobank, 470,986 completed at least one blood pressure measurement and were included in the analysis. These participants were recruited between March 2006 and July 2010 and were followed for up to four assessments through to February 2024. Main outcome measures: Incidence of dementia, identified through linked health records using ICD-9 and ICD-10 diagnosis codes, self-reported diagnoses or records of dementia-specific medication use. The association between pulse pressure and risk of dementia was investigated using Cox proportional hazard models. Models were adjusted for age, sex, education, hearing problems, lipid levels, depression, traumatic brain injury, physical activity, diabetes, smoking, hypertension, body mass index, alcohol consumption and mean arterial pressure. Dementia subtype-specific associations were examined using competing risk models, with cause-specific Cox analyses included as supplementary sensitivity analyses. Results: During a median follow-up of 13 years, 9,028 persons developed dementia (Alzheimer's disease: 3,011; Vascular dementia: 1,270; Dementia with Lewy bodies: 234; Frontotemporal dementia: 191; Other/Mixed dementia: 4,322). Each 10mm Hg increase in pulse pressure was associated with a 5.4% higher risk of dementia (95% confidence interval on hazard ratio: 1.036 to 1.071), even after adjustment for age, mean arterial pressure and other established dementia risk factors. The effects were disproportionately stronger for Alzheimer's disease and vascular dementia, with no clear evidence for increased risk for dementia with Lewy bodies or frontotemporal dementia. Results were robust across sensitivity analyses including alternative blood pressure metrics, complete-case models, and alternative dementia classifications. Conclusions: Pulse pressure is independently associated with incidence of dementia beyond conventional blood pressure measures.

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.

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.

BACKGROUND: Neuropsychiatric symptoms (NPS) are prevalent and debilitating in Alzheimer's disease (AD). Existing pharmacologic treatments are often ineffective and associated with serious adverse events. Identifying modifiable risk factors (MRFs) is critical for prevention and treatment. METHODS: Capitalizing on data from 14,497 individuals with AD from the National Alzheimer's Coordinating Center (NACC) database, we examined longitudinal associations between modifiable risk factors, APOE genotype and NPI-Q-assessed NPS using Cox proportional hazards models adjusted for demographics. RESULTS: Diabetes, alcohol consumption, smoking, and TBI were associated with an increased risk of specific NPS in AD. APOE{varepsilon}4 carrier status was linked to multiple NPS, showing a dose-response relationship. Education, LDL-C, and corrective lenses were protective; hypertension showed no associations. CONCLUSION: These findings strongly suggest that individual MRFs are associated with specific NPS in line with a complex etiology underlying these symptoms. Early detection and management of vascular, lifestyle and sensory factors could reduce NPS.

INTRODUCTION: Postmenopausal estrogen decline may contribute to Alzheimer's disease (AD) risk, but longitudinal evidence linking circulating estrogens to cerebrospinal fluid (CSF) biomarkers is lacking. METHODS: We analyzed 866 female participants from the European Prevention of AD Longitudinal Cohort Study with baseline serum estradiol and estrone measured by liquid chromatography tandem mass spectrometry and repeated CSF measurements of amyloid-beta (A{beta})42, phosphorylated (p) Tau181, and total (t) Tau. RESULTS: Neither estradiol nor estrone was associated with longitudinal A{beta}42. Higher estradiol was associated with lower baseline tau and slower tau increases over time. Baseline estradiol-tau associations were stronger in apolipoprotein E (APOE) {epsilon}4 carriers, though APOE{epsilon}4 did not modify longitudinal associations. Amyloid positivity did not moderate hormone-tau associations but was associated with steeper tau increases over time. Estrone showed no significant associations. DISCUSSION: These findings suggest a more consistent relationship between estradiol and tau-related rather than amyloid-related pathology.

Background: A recent Lancet Commission estimated that up to 45% of Alzheimers Disease and Related Dementias (ADRD) cases could be prevented by addressing modifiable lifestyle risk factors. Meanwhile, genome wide association studies (GWAS) have shown that common genetic variants also account for substantial ADRD risk. Whether a favorable lifestyle can offset risk in genetically predisposed individuals remains unclear. Methods: We conducted a retrospective cohort study of 105,886 participants from the All of Us Research Program enrolled between 2018 and 2023. Participants were over age 49, assigned male or female at birth, of European ancestry, and without ADRD at baseline. ADRD diagnoses were identified via electronic health records (EHR). Fourteen potentially modifiable risk factors for ADRD were assessed using surveys, EHR records, and wearable data. Genetic risk was quantified as a polygenic risk score (PRS) based on 81 independent GWAS loci and APOE E4 genotype. Results: Overall, 967 incident ADRD events occurred over a median follow-up of 3.7 years. Ten out of 13 modifiable risk factors were significantly associated with ADRD. When grouped into risk factor profiles, intermediate and unfavorable modifiable risk factor scores were associated with substantially higher ADRD risk (HR 3.07, 95% CI 2.47, 3.83; HR 8.01, 95% CI 6.39, 10.05, respectively) compared to a favorable lifestyle; APOE E4 dosage and polygenic risk score were also independently associated with ADRD risk. Among individuals in the highest polygenic risk group, a favorable lifestyle reduced ADRD risk from HR 18.63 (95% CI 10.25, 33.86) to 1.90 (95% CI 0.94, 3.81), whereas APOE E4 homozygotes remained at elevated risk even with a favorable lifestyle (HR 6.52, 95% CI 2.97, 14.33). Conclusions: Our data suggest ADRD risk is driven more by modifiable risk factors and APOE genotype than polygenic risk score. Future genomic informed risk assessments for ADRD should calibrate their findings to accurately identify high risk individuals.

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.

4-Methylumbelliferone (4-MU) inhibits hyaluronic acid (HA) synthesis and is currently approved in Europe for biliary spasm. 4-MU administration reduces perineuronal nets (PNNs), and enzymatic degradation of PNNs in mouse models of Alzheimers disease (AD) attenuates memory impairment. Although 4-MU has therapeutic efficacy in rodent models of fibrosis and cancer, it has not been examined in an Alzheimers model. Here, we evaluated the impact of long-term 4-MU treatment in the APP/PS1 amyloid mouse model. From three months of age, mice were on either a vehicle or 4-MU-supplemented diet for 70 days or 52 weeks. Short and long-term 4-MU treatment decreased the soluble parenchymal A{beta}1-42/A{beta}1-40 ratio. Reductions in insoluble amyloid plaque were observed following 52 weeks of treatment. Extended 4-MU administration also reduced PNN intensity and ameliorated spatial memory deficits in APP/PS1 mice. These findings provide support for targeting brain extracellular matrix (ECM) as a therapeutic strategy for AD.

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.

BackgroundIn preclinical Alzheimers disease (pAD), regional patterns of amyloid-{beta} (A{beta}) deposition are well characterized but it is unclear how this process varies across functional networks. ObjectiveDetermine how A{beta} accumulation in functional networks ("network-amyloid burden" [NAB]) varies by age, network type (cognitive vs. non-cognitive), and A{beta} status (A{beta}+/A{beta}-), and relates to cognition. Methods157 cognitively unimpaired adults (45-84 years; n=28 A{beta}+ per neuroradiological read) underwent brain MRI, amyloid PET (18F-florbetapir), and neuropsychological testing. NAB was calculated as the mean standard uptake value ratio within 7 networks categorized as cognitive (fronto-parietal, default mode, ventral and dorsal attention, limbic) or non-cognitive (somato-motor, visual). Linear mixed models tested how NAB varies across age, networks (by type and each separately), A{beta} status, and their interactions, and relationships between NAB and cognition. ResultsNAB increased with age, most prominently in fronto-parietal and default mode networks. NAB was higher in cognitive than non-cognitive networks, and this difference was more pronounced in A{beta}+ individuals. NAB was not significantly associated with cognition. ConclusionsCognitive brain networks are more vulnerable to amyloid accumulation with aging and in pAD than non-cognitive networks. Cognitive NAB may be useful for early detection and as a target for intervention in pAD.

Background: People affected by dementia experience intersecting care inequalities. We explored relationships between ethnicity and health and social care resource use among people with dementia in an ethnically diverse urban region. Methods: We conducted a retrospective observational cohort study using Discover-NOW, including patients with dementia between 1.4.2015 and 1.4.2025. We calculated ethnic density as the percentage of the Middle Layer Super Output Area (SOA) population self-identifying with the same ethnic group. Regression models, clustered by Local SOA, tested whether ethnic density moderated relationships between ethnicity and primary care, outpatient, inpatient, emergency and social care service use, controlling for sociodemographic characteristics, deprivation, comorbidities and time of diagnosis. Findings: We included 30,704 people with dementia. People from Black and Mixed ethnic groups used more primary care, and those from Asian ethnic groups less primary and secondary care, than White ethnic groups. Rates of local authority social care packages were similar across ethnic groups. High ethnic density predicted fewer GP consultations in Black ethnic groups, but more in South Asian groups. Interpretation: Among Black ethnic groups, primary care use was relatively high, especially in areas of low ethnic density, perhaps reflecting greater needs among communities at risk of racism and isolation. The trend towards increased primary care use among South Asian people in areas of higher ethnic density may reflect communities mitigating help-seeking hesitancy related to cultural and language barriers. Greater care integration could reduce care inequalities among minority ethnic communities who may experience fewer barriers to social relative to health care.

Background: In clinical practice, 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) evaluation of neurodegenerative diseases relies primarily on visual interpretation, which is inherently subjective. Although current international guidelines recommend incorporating quantitative tools to support visual reading, the magnitude of the incremental diagnostic benefit and the clinical contexts in which it is most pronounced have not been formally synthesized in a systematic meta-analytic framework. Methods: Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses for Diagnostic Test Accuracy (PRISMA-DTA) guidelines, we searched PubMed, EMBASE, Cochrane Library, and KoreaMed from inception to August 2025 for studies comparing visual-only versus visual-plus-quantitative FDG-PET interpretation within identical patient cohorts. Pooled sensitivity and specificity were estimated using random-effects models. Relative diagnostic performance was summarized as odds ratios (ORs), obtained by exponentiation posterior contrasts between visual analysis combined with quantitative analysis, and visual analysis. Subgroup analyses were conducted based on the clinical experience of the readers. Results: Ten studies met the inclusion criteria. In the overall analysis (k = 9), visual analysis alone yielded a pooled sensitivity of 0.85 and specificity of 0.78 , versus a sensitivity of 0.87 and specificity of 0.88 for the combined approach. The most pronounced gain was observed in differentiating Alzheimers disease (AD) from healthy controls, with specificity increasing from 0.69 to 0.94 (Bayesian OR 4.29). Quantitative augmentation conferred a larger sensitivity gain among beginner readers (increasing from 0.75 to 0.87; Bayesian OR 2.39) than among expert readers, narrowing the performance gap between experience levels. Conclusion: Adding quantitative analysis to visual FDG-PET interpretation yields modest overall improvements in diagnostic accuracy, with the largest gains observed in distinguishing AD from cognitively normal individuals and among less experienced readers. These findings are consistent with current international guidelines that position quantitative assessment as a complementary aid to visual interpretation rather than a replacement, with particular utility for less experienced practitioners and for specific differential-diagnostic scenarios.

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.

Aims. The risk of cognitive decline after losing a spouse remained mixed. This study aims to investigate the association between spousal loss and risk of cognitive decline, assess whether this association varies by sex and age, and identify modifiable factors. Methods. We conducted a prospective cohort study using harmonized data from six population-based aging surveys: the US Health and Retirement Study and its sister surveys in England, Mexico, China, India, and South Africa, incorporating their respective Harmonized Cognitive Assessment Protocol (HCAP) sub-studies. Spousal loss (yes vs no) was the exposure. Cognitive outcomes (i.e., orientation, memory, executive function, and language), were assessed using HCAP neuropsychological batteries. We conducted parallel analyses in six cohorts. Associations between spousal loss and cognitive outcomes were estimated using generalized linear models, and summarised estimates were derived via random-effects meta-analyses. Sex stratification and restricted cubic spines were used to examine how these associations vary by sex and age, respectively. Results. The analytical cohort consisted of 18,551 individuals aged 61.22 (SD 6.30) to 71.37 (SD 7.33) years. Widowhood prevalence ranged from 14.1% in CHARLS to 53.9% in HAALSI and was consistently higher in women. Spousal loss was associated with poorer memory (multivariable-adjusted {beta} = -0.07, 95% CI -0.12 to -0.01) and executive function (multivariable-adjusted {beta} = -0.08, 95% CI -0.13 to -0.03) in the meta-analysis, with no significant associations for orientation or language. While results were generally consistent in five cohorts, the ELSA showed divergent patterns (orientation: {beta} = 0.10, 95% CI 0.06 to 0.13; memory: {beta} = 0.05, 95% CI 0.02 to 0.08; language: {beta} = 0.16, 95% CI 0.12 to 0.19). Sex-stratified analyses indicated poorer executive function among men (multivariable-adjusted {beta} = -0.14, 95% CI -0.19 to -0.08) and poorer memory among women (multivariable-adjusted {beta} = -0.07, 95% CI -0.14 to -0.01) following widowhood. Nonlinear age-related effects on cognition were observed in ELSA, LASI, and HAALSI. Higher education, internet use, and BMI were negatively associated with the risk of cognitive decline among widowed participants. Conclusions. Spousal loss is associated with domain- and sex-specific differences in cognitive performance, with substantial heterogeneity across study populations. Future research should integrate biopsychosocial markers to develop context-sensitive interventions for widowed older adults.

Diabetes mellitus (DM) is a major risk factor contributing to the development of Alzheimers disease-related dementias (ADRD). While one of the early symptoms of both Alzheimers disease (AD) and DM-related ADRD is a reduction in cerebral blood flow, the underlying biological mechanisms driving this decline remain to be fully elucidated. Genome-wide association studies have linked AD/ADRD to single-nucleotide polymorphisms in the gene encoding soluble epoxide hydrolase (sEH), an enzyme we previously reported to be upregulated in the brains of an AD rat model. Our previous work also demonstrated that chronic inhibition of sEH with 1-trifluoromethoxyphenyl-3-(1-propionylpiperidin-4-yl) urea (TPPU) preserves hippocampal-dependent spatial learning and memory and improves cerebral hemodynamics in both AD and DM-ADRD models. In the present study, we found that chronic TPPU treatment (1 mg/kg/day for 9 weeks) reduced brain sEH expression, improved cortical-based long-term non-spatial recognition memory involving both cortical and hippocampal networks, and reduced anxiety in DM-ADRD rats. TPPU improved brain perfusion and normalized impaired whisker-evoked functional hyperemia, an effect linked to upregulation of Kir2.1 expression in cerebral capillaries. Furthermore, TPPU restored tight junction proteins (ZO-1 and OCLN), mitigated capillary rarefaction, and suppressed astrocyte and microglial activation. At the cellular level, TPPU attenuated hippocampal neurodegeneration, restored the expression of synaptic proteins (PSD95 and SY38), and reduced levels of key pro-inflammatory chemokines, including MCP-1, RANTES, and MIP-1, in DM-ADRD. In conclusion, TPPU preserves cognitive function in DM-ADRD by mitigating cerebrovascular dysfunction, neuroinflammation, and gliosis while protecting synaptic integrity and neuronal survival, representing a promising therapeutic strategy for DM-ADRD.

Spousal caregivers of individuals with Alzheimers disease and related dementias frequently experience elevated perceived stress, caregiver burden, and loneliness, which are associated with adverse health outcomes. Early identification is therefore critical for timely intervention. Existing approaches commonly rely on wearable sensor data and standardized psychological questionnaires, while recent multimodal methods aim to improve prediction by integrating behavioral and linguistic information. In this study, we explored three modality configurations, wearable-derived features, interview-based text, and their combination, to classify caregiver psychological risk using the Perceived Stress Scale (PSS), Zarit Burden Interview, and UCLA Loneliness Scale. We compared traditional machine learning models and large language models (LLMs) (Gemini 2.0, Llama 4, and GPT-4o) under psychometrician-centered and caregiver-centered prompting strategies. Traditional machine learning models performed better under multimodal settings, while LLMs achieved stronger performance with Interview-Only input. We further demonstrate that PSS was the most predictable construct and prompting strategies substantially influenced LLM performance.