Alzheimer's & Dementia: Translational Research & Clinical Interventions

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSINTRODUCTIONC_ST_ABSTreatment response in Alzheimers disease (AD) varies substantially across patients, yet no validated frameworks exist to estimate heterogeneous treatment effects (HTE) from observational data while controlling for confounding bias. METHODSWe developed a causal machine learning framework integrating expert-guided causal graphs, complementary HTE estimators, sensitivity analyses, and policy learning. We applied it to cholinesterase inhibitors (ChEIs) in MCI due to AD to patients from the NACC and ADNI cohorts. RESULTSAnalysing 4,049 patients with 12-month and 2,223 with 36-month follow-up, all estimators indicated null or negative long-term ChEI effects on cognitive and functional outcomes, notably on functional measures. ChEIs showed slightly more deleterious effects among men than women. DISCUSSIONThis framework provides a methodology for estimating HTE from observational data. It revealed no beneficial responder subgroups, highlighting the challenge of detecting treatment heterogeneity in moderately sized cohorts. This approach can inform treatment selection for other AD therapies including memantine, anti-amyloid agents, and emerging treatments.

BackgroundGabapentin prescriptions have increased 123% since 2010, reaching 15.5 million Americans annually. Recent studies suggest gabapentin-dementia associations, but whether concomitant medications modify this risk is unknown. Both gabapentin and calcium channel blockers (CCBs) affect neuronal calcium signaling through distinct mechanisms, raising the possibility of pharmacodynamic interaction. MethodsActive comparator new-user cohort study using Rutgers Clinical Research Data Warehouse (2015-2024). Adults [≥]40 years with hypertension initiating gabapentin (n=28,058) or pregabalin (n=5,733) were followed for incident dementia. Inverse probability of treatment weighted (IPTW) Cox models estimated hazard ratios stratified by baseline CCB exposure. Validation analyses tested CCB subtype specificity (dihydropyridine [DHP] vs verapamil), dementia subtypes (F03/G30/F01), frailty stratification (CKD, stroke), lag periods, falsification outcomes, and non-2{delta} anticonvulsant comparisons. ResultsAmong 33,791 patients (502 dementia events; median follow-up 1.22 years), we identified a novel drug-drug interaction: gabapentin was associated with substantially elevated dementia risk among CCB users (HR=2.22, 95% CI 1.42-3.47, p=0.0005) compared to non-users (HR=1.15, 95% CI 0.99-1.33; interaction p=0.004). A time-varying analysis confirmed this finding: among gabapentin users who initiated CCB during follow-up, CCB-exposed person-time showed 65% higher dementia incidence (Rate Ratio=1.65, 95% CI 1.19-2.29). This interaction showed striking CCB subtype specificity: DHP CCBs drove the signal (HR=3.20) while verapamil showed no interaction (insufficient events for analysis). The signal concentrated in F03 unspecified dementia (HR=1.68, p=0.004) with short latency (median 240 days), consistent with drug-induced cognitive impairment rather than neurodegeneration. Pre-index symptom balance analysis showed 6/6 symptom families balanced between groups, arguing against protopathic bias. The interaction was paradoxically weaker in frail patients (CKD ratio=0.25, stroke ratio=0.14), arguing against confounding by illness severity. Lag analyses showed strengthening over time (HR 2.22[->]3.72), falsification outcomes were largely null (4/7), and non-2{delta} anticonvulsants showed no CCB interaction. ConclusionsWe identified a novel drug-drug interaction whereby DHP CCB co-medication amplifies gabapentin-associated dementia risk, confirmed by time-varying analysis (Rate Ratio=1.65). The DHP-specific signal is biologically plausible given independent evidence that DHP CCBs may adversely affect cognition (DREAM consortium), while the absence of interaction with verapamil aligns with its potential neuroprotective properties identified in drug repurposing studies. The F03-specific pattern suggests drug-induced cognitive impairment that may be reversible. These hypothesis-generating findings identify gabapentin-DHP CCB combinations as a target for cognitive safety monitoring and warrant confirmation with concurrent exposure measurement.

ObjectiveTo examine whether menopausal women who initiate systemic menopausal hormone therapy (MHT) around menopause (45-60 years old) have a different risk of developing dementia than those not taking MHT. DesignSystematic review and meta-analysis of randomised controlled trials and longitudinal observational studies. Risk of bias was assessed using ROB-2 and ROBINS I-V2. Data sourcesMEDLINE, Web of Science, EMBASE, and Cochrane Library to 27 March 2026. Eligibility criteria for selecting studiesStudies which measured dementia or cognitive decline in women who initiated systemic MHT between ages 45-60 or within 5 years of menopause, compared with placebo or no MHT. Authors contacted for additional details if needed. Main outcome measuresDementia, Alzheimers disease (AD), cognitive decline. Results10 studies totalling 213,678 participants (189,525 in studies with the primary population). There was no significant increased risk in women with a uterus for all cause dementia (pooled hazard ratio (HR): 1.12; 95% CI 0.91-1.31, N=78,613, I2 = 96.9%), but increased AD risk (HR: 1.14; 95% CI 1.02, 1.29, N=134,865, I2 = 35.6%). Results were similar in sensitivity analyses including women with or without a uterus. Results for cognitive decline were variable. ConclusionsMHT initiated around the age of menopause should not be prescribed for cognition or dementia prevention. It is not protective against dementia and may increase risk slightly. The magnitude of risk was similar in AD and dementia, but the latter with larger confidence intervals. Studies which followed up individuals rather than on health records lost people to follow up. This may account for difference in cognitive decline outcomes between studies, as people with cognitive impairment and dementia are more likely not to attend. MHT prescribing should balance benefits against risks, including evidence of a small increased dementia risk. There are few high-quality studies, so further research would inform recommendations. Systematic review registration Prospero CRD420251010663 What is already known on this topic?O_LIMenopausal hormone therapy (MHT) is effective for alleviating vasomotor symptoms. Contemporary guidelines recommend treatment should be initiated for such symptoms under age 60 and or within 10 years of menopause onset. C_LIO_LIA large randomised trial on the topic found increased risk of dementia in women initiating MHT after the age of 65. C_LIO_LIIt is unknown whether initiating MHT around the age of menopause impacts the risk of dementia or cognitive decline. C_LI What this study addsO_LIThere was no evidence that taking MHT around the time of menopause decreases the risk of dementia or cognitive impairment. C_LIO_LIThey should not be prescribed for these indications. C_LIO_LIWe were able to find more studies which examine this question by contacting authors for additional data. C_LIO_LIInitiating MHT in women with a uterus around the age of menopause increased the risk of Alzheimers disease slightly, by over 10%, and there is a similar but not significant effect in the fewer studies of all cause dementia. Women with or without a uterus show similar results. C_LIO_LIWe found no significant difference shown in cognitive decline, possibly due to loss to follow up. This may be because most studies of cognitive decline follow up C_LI

BackgroundMild behavioural impairment (MBI), characterized by later-life emergence of persistent neuropsychiatric symptoms (NPS), is an early clinical indicator of dementia risk. MBI as a global construct has been associated with Alzheimer disease (AD) pathology; studies have also explored MBI domains. Prior work has linked MBI-apathy to cerebrospinal fluid (CSF) biomarkers of AD, but whether similar associations are detectable using plasma-based biomarkers such as phosphorylated tau (p-tau) is unknown. Establishing such relationships is critical, as plasma biomarkers are more accessible than CSF. ObjectiveTo explore cross-sectional and longitudinal associations between MBI-apathy and plasma p-tau181 using Alzheimers Disease Neuroimaging Initiative data. MethodsOlder adults with normal cognition or mild cognitive impairment were categorized as MBI-apathy (n=69), non-MBI NPS (n=112), and no-NPS (n=215) based on Neuropsychiatric Inventory scores and symptom persistence over one year. Linear regression modelled cross-sectional associations between NPS group and plasma p-tau181 levels, adjusting for age, sex, education, apolipoprotein E4 status, and Mini-Mental State Examination score. Hierarchical linear mixed-effects modelling assessed associations over two and three years, including time-by-NPS group interactions. ResultsMBI-apathy was associated with significantly higher plasma p-tau181 levels at baseline (24.05% [6.06-45.08%]; adjusted p=0.014), and over two (26.46% [7.24-49.12%]; adjusted p=0.012) and three years (29.28% [10.17-51.72%]; adjusted p=0.004) compared to no-NPS. No significant associations were observed for non-MBI NPS. ConclusionsMBI-apathy is associated with elevated plasma p-tau181 cross-sectionally and longitudinally. These findings support MBI-apathy as a potential proxy marker of tau pathology for early AD detection.

INTRODUCTIONEarly-onset Alzheimers disease (EOAD) is mostly caused by mutations in Presenilin-1,2 (PSEN1, PSEN2), and amyloid precursor protein (APP) genes. Both genetic and experimental evidence has supported the PSEN-APP amyloid hypothesis as the leading pathogenesis of AD. Thus far, 276 missense variants from PSEN1,2, and APP have been identified. Herein, we report the development of algorithm platforms for predicting the degrees of pathogenic potentials of these various missense mutations in AD. METHODSWe performed extensive pairwise correlations between 276 in vitro functional assays of missense variants from PSEN1, PSEN2, and APP and clinical data among EOAD patients against 37 variant effect predictors (VEPs). Furthermore, we used the structural models of all three proteins to refine understanding of the molecular basis of missense variants in dominant negative (DN) or loss-of-function (LoF) effects. RESULTSWe found that VEPs were consistently correlated with age of onset (AAO) among EOAD patients and the A{beta}42/A{beta}40 ratio biomarker. This study also identified discrepancies in the predictor variable leading to an increase in the A{beta}42/A{beta}40 ratio; The increased A{beta}42/A{beta}40 ratio was due to decreased A{beta}40 levels by Sun et al., (2016), while Petit et al., (2022) argued that increased A{beta}42 level was the culprit. We also identified that with increased predicted pathogenicity, there were decreased A{beta}38 levels. Conversely, this study found no direct correlations with A{beta}37 and A{beta}43. Lastly, structural studies show characteristics of either DN and LoF mechanisms, as there were numerous variants located in buried hydrophobic domains and those on charged surfaces of the proteins. DISCUSSIONCurrently, a major limitation in the field is the lack of reliable approaches for predicting the pathogenicity of variants in EOAD. We show that VEPs are promising in deciphering the effects of variants in PSEN1, PSEN2, and APP genes, especially between multiple pathogenic mutations. Our study also illuminates the need for experimental studies to identify the predictor variable causing the increased A{beta}42/A{beta}40 biomarker. Our biophysical studies also identify the need to characterize whether the mechanism of pathogenesis caused by DN or LoF effects is in scope of the presenilin hypothesis. Research in ContextO_LISystematic review: The authors reviewed experimental evidence of pathogenic PSEN1, PSEN2, and APP variants in scope of the presenilin hypothesis. To our knowledge, the pathogenesis of EOAD remains incompletely understood. There are also no predictive tools/models available for informing clinical translation. C_LIO_LIInterpretation: VEPs demonstrate strong correlations with AAO and A{beta} levels from pairwise correlations with 276 missense variants. Structurally, it appears that mutations demonstrate characteristics of dominant negative and loss-of-function effects. C_LIO_LIFuture Direction: Larger studies are necessary of VEPs for realistic clinical usage. C_LI HighlightsO_LIWe performed correlations of 37 VEPs against in vitro data of EOAD variants. C_LIO_LIVEPs demonstrate potential as diagnostic tools for early onset Alzheimers disease. C_LIO_LIPathogenic missense variants show characteristics of DN and LoF effects. C_LI

Background and ObjectivesProgression from mild cognitive impairment (MCI) to Alzheimers Disease and Related Dementias (AD/ADRD) varies widely across individuals, yet the mechanisms underlying this heterogeneity remain unclear. Identifying clinical and social determinants influencing this transition could enable earlier intervention. While cardiovascular and social risk factors are established contributors to dementia incidence, their role in progression from MCI to dementia may differ. Few studies using real world clinical data have evaluated these potential determinants of MCI progression. MethodsUsing electronic health records (EHR) from patients with incident MCI at UCSF Health (2010-2024), we evaluated cardiovascular (blood pressure [BP], body mass index [BMI], and type II diabetes) and social (marital status, language preference, race/ethnicity, and neighborhood disadvantage) risk factors for rate of progression from MCI to AD/ADRD. Covariate-adjusted Cox proportional hazards models estimated hazard ratios for incident AD/ADRD, with evaluation of interactions by sex. ResultsAmong 6,529 patients, higher systolic BP was associated with AD/ADRD incidence (HR per 10 mmHg: 1.09, 95% CI: 1.05-1.14). BMI was inversely associated with incidence in both males (HR: 0.94; 95% CI: 0.92-0.97) and females (HR:0.98; 95% CI: 0.96-0.99). Compared to married individuals, widowed patients had a higher hazard of progression (HR: 1.15; 95% CI: 1.00-1.32). Spanish-speaking (HR: 1.38; 95% CI: 1.04-1.81), Chinese-speaking (HR: 1.19; 95% CI: 1.00-1.42), and "Other non-English" speaking patients (HR:1.24; 95% CI: 1.03-1.51) had a higher hazard of progression compared to English speakers. Latinx (HR:1.22; 95% CI: 1.01-1.48) and Asian patients (HR:1.14, 95% CI: 1.00-1.30; p=0.04) also had higher hazards of progression compared to White patients. Neighborhood disadvantage was not significantly associated with disease progression. DiscussionCardiovascular and social factors independently influence dementia progression, with some sex-specific patterns. Integrating clinical and social indicators highlights the potential of EHR data to identify high-risk patients earlier in the care continuum and support equitable dementia prevention.

IntroductionAlzheimers disease (AD) disproportionately affects women, with accumulating evidence suggestion a contributary role of hormones in this disparity. Given the known influence of hormones on brain health and cognition, characterizing specific profiles in dementia is crucial. In addition, sex-stratified hormonal alterations in AD and other dementias remain poorly understood. MethodsWe quantified nine steroid hormones: 11-deoxycortisol, 17-hydroxyprogesterone, aldosterone, cortisol, dihydrotestosterone, estrone, progesterone, testosterone and estradiol. The hormones were quantified in cerebrospinal fluid (CSF) and plasma from 204 participants across five cognitive categories: no cognitive impairment (n=32), mild cognitive impairment (MCI) non-AD (n=38), MCI due to AD (n=21), AD dementia (n=81), and vascular dementia (VaD) (n=32). Participants were recruited at the Danish Dementia Research Centre, Copenhagen University Hospital, Copenhagen, Denmark. Hormone levels were measured using liquid chromatography-tandem mass spectrometry. Sex-stratified generalized linear models were adjusted for age. Overall, 50.5% of participants were women with a mean age of 69 (SD = 9.8) compared to men with a mean age of 70 (SD = 9.1). ResultsIn women with AD, CSF cortisol and 11-deoxycortisol were significantly elevated compared to women with no cognitive impairment (Fold Change (FC) (95% CI) = 1.13 (1.01-1.27), p-value = 0.04 and (FC (95% CI) = 1.01, (1.00-1.01), p-value = 0.03, respectively). Plasma progesterone was decreased (FC (95% CI) = 0.90 (0.81, 0.99), p-value = 0.04). Women with VaD exhibited reduced CSF estradiol (FC (95% CI) = 0.86 (0.74, 0.98), p-value = 0.03). In men with AD, plasma aldosterone was elevated (FC (95% CI) = 1.19 (1.06, 1.33), p-value = 2.81e-03). Correlation analyses revealed that CSF cortisol in women was significantly correlated with CSF AD pathology markers in amyloid-beta 42 (r = -0.29, p-value = 3.02e-03) and phosphorylated tau (r = 0.2, p-value = 0.04). The increase of cortisol was validated in an external cohort where t-test showed significant difference in cortisol between people with AD and cognitively healthy controls (CN), this difference was larger in women (mean AD = 0.26 vs mean CN = 0.21, p-value = 1.79e-06) than men (mean AD = 0.23 vs mean CN 0.21, p-value = 0.04) ConclusionOur findings demonstrate sex-dependent dysregulation of steroid hormone in dementia. Specifically, cortisol and aldosterone are highlighted, which are potential modifiable targets.

BackgroundGeroprotective interventions, including the mTOR inhibitor rapamycin, slow aging in preclinical models. Translation to humans remains challenging because clinical trials require endpoints detectable within feasible timeframes. Multi-modal in vivo imaging could address this limitation by enabling simultaneous assessment of age-related pathology across multiple organ systems, but its feasibility in clinical trials is uncertain. ObjectiveTo evaluate the feasibility of deploying a multi-modal, multi-organ imaging battery in a geroprotective intervention trial of rapamycin and to collect exploratory efficacy data across multiple domains of age-related pathology. MethodsIn a single-center, open-label, single-arm pilot trial, 14 participants with early-stage Alzheimers disease (MCI or mild dementia; Montreal Cognitive Assessment [≥]18; amyloid-positive) received oral rapamycin 7 mg once weekly for 26 weeks. Participants underwent baseline and end-of-treatment imaging including retinal optical coherence tomography (OCT); [18F]FDG positron emission tomography/computed tomography (PET/CT) of the head, thorax, and lower spine; dentomaxillofacial MRI; and cardiac MRI with stress perfusion and arterial pulse wave velocity. Feasibility outcomes included completion rates and technical or logistical barriers. Exploratory pre-post changes were assessed using paired t-tests. ResultsOf the 14 enrolled participants, 13 completed follow-up imaging. Among these, completion was 100% for OCT, [18F]FDG PET/CT, and dentomaxillofacial MRI. Cardiac MRI and pulse wave velocity were completed in 69% (9/13), primarily limited by scanner access during a healthcare worker strike. No imaging-related adverse events occurred. Exploratory analyses showed nominally significant pre-post increases in cardiac output (p=0.017), late diastolic (A-wave) kinetic energy (average: p=0.044; peak: p=0.024), left retinal ganglion cell layer thickness (p=0.044), and optic nerve head [18F]FDG uptake (p=0.040). Bone mineral density showed no significant pre-post changes, while muscle cross-sectional area decreased numerically but not significantly (p=0.058). In exposure-response analyses, higher rapamycin blood concentration was significantly correlated with greater skeletal muscle density (r=0.64, p=0.035) and, albeit not significantly, smaller loss of cross-sectional area (r=-0.53, p=0.097). ConclusionsA multi-modal imaging battery spanning several organ systems was successfully integrated into a clinical trial, with high completion rates for most modalities. Logistical constraints were the primary barriers affecting cardiac measures. These findings inform the design of future randomized trials of geroprotective interventions, where such imaging batteries may help detect changes in age-related pathology over relatively short timeframes.

Purpose: To systematically review population-based studies reporting the prevalence and incidence of neurodegenerative diseases among adults aged 50 and older in Russia Methods: We searched Medline, Scopus, Embase, and eLibrary from inception to January 2025. Cross-sectional and cohort studies were eligible if they reported community-based prevalence or incidence of dementia, cognitive impairment, or Parkinson's disease in adults aged 50 and older in Russia. Healthcare and institutionalised populations were excluded. Risk of bias was assessed using the RoB-PrevMH tool, and dementia prevalence from screening tools was adjusted for test sensitivity and specificity. Prevalence estimates were pooled using random- and fixed-effects meta-analysis, stratified by age group and assessment method. Results: Twenty studies met the inclusion criteria. Dementia prevalence ranged from 0.5% to 81.6%, with the lowest estimates from administrative data and the highest from Mini-Cog screening in adults aged 85 and older. Cognitive dysfunction was reported in 12 studies (prevalence 3.1-81.5%). Nine studies reported Parkinson's disease prevalence (0.017-0.31%), with the highest estimate from the only neurologist-assessed population-based study. Conclusion: Prevalence of dementia and Parkinson's disease in Russia varies widely depending on diagnostic method, age group, and study design. Most studies lacked representative sampling and used non-standardised diagnostic criteria. Population-based longitudinal research using validated tools is urgently needed to support public health planning in Russia.

Background and ObjectivesMultifactorial interventions have been reported to be effective in improving cognitive function; however, their long-term effectiveness in community settings remains to be sufficiently examined. This study aimed to investigate the effects of a socially implemented multifactorial intervention program on dementia onset, long-term care insurance certification, and post-intervention cognitive and physical functions. MethodsThis retrospective observational study collected data from three municipalities. The study population comprised individuals suspected of having mild cognitive decline based on cognitive function screening tests conducted by March 31, 2024, and who had been invited to participate in a dementia prevention class, but had not applied for long-term care insurance at the time of the invitation. Participants were classified into class participation and non-participation groups for analysis. Most participants attended the class only once (intervention duration: 4 or 6 months). ResultsData from 104, 218, and 256 individuals were collected from the three municipalities, respectively. No significant association was found between class participation and suppression of dementia onset or long-term care insurance certification in any of the municipalities. Regarding pre-post comparisons among class participants, significant improvements in cognitive function and some physical functions were observed in all the three municipalities. ConclusionsThe multifactorial interventions implemented in community settings showed no effect on dementia onset or health outcomes. However, class participation was associated with improvements in cognitive function and some physical functions. These findings suggest that implementing programs based on evidence can achieve effects similar to those observed in studies conducted under ideal conditions.

BackgroundIndividual clinical cognitive assessments (CCA) for Alzheimers disease (AD) provide broad disease stratification but are limited in sensitivity and specificity, requiring integration of multiple CCA for optimal disease staging. Recent work from our lab suggests that neuro-metabolic and vascular dysregulation (MVD) occurs early in AD, prior to clinical symptoms, and may provide higher sensitivity and specificity than CCA alone. In this study, we combined three widely accepted CCA with MVD readouts and developed a multimodal ensemble machine learning approach across the AD spectrum to predict disease stage and grade. MethodsAD subjects (N=372) across the disease spectrum with imaging (PET:18F-FDG, MRI:T1w, T2 FLAIR, ASL) and CCAs (ADAS-Cog, CDR, MoCA) data were analyzed from ADNI. Imaging data were registered to MNI152+, z-scored relative to cognitively normal controls, and processed for MVD. A clinical-set-enrichment analysis (CSEA) was developed to link regional brain changes with CCA scores, map changes to functional categories, project them into a 3D Cartesian space, and model trajectories, thus revealing at-risk and resilient regions. In addition, an ensemble machine-learning approach was utilized for disease stage classification, and a disease grading scheme across the AD spectrum was developed to further stratify within disease stages. FindingsRegional data followed an MVD pattern across AD stages stratified by CSEA scores. Females showed greater stage separation along the CCA axis within each region, indicating faster disease progression. Moreover, progression in at-risk brain regions (e.g., mid- and inf-temporal gyri, amygdala) was associated with longer disease path lengths, whereas progression in resilient brain regions (supramarginal gyrus) was not. Moreover, our classification and grading approach can predict AD stage and grade independent of amyloid-beta and tau with high precision and accuracy. InterpretationA framework was developed to evaluate MVD and CCA variations across the AD spectrum, thereby distinguishing at-risk and resilient brain regions. Distinct disease trajectories were identified, and a new data-driven grading scheme was proposed to highlight the potential for precision medicine and therapeutic evaluation. FundingNIH T32AG071444

Quercetin is an abundant dietary flavonol with interesting in vitro properties that include substrate-selective positive allosteric modulation (PAM) of the activity of the receptor type protein tyrosine phosphatase D (PTPRD) and substantial antioxidant actions. Its in vivo activities include reducing incidence of Alzheimers disease (AD) and reducing AD neurofibrillary pathology in mouse models. Structure-activity studies have identified quercetin analogs with improved in vitro and in vivo properties, including the improved PTPRD PAM 6-bromoquercetin (6BrQ). However, there is no comparison of the antioxidant properties of 6BrQ to those of quercetin. There is no systematic screening for activities of quercetin or of 6BrQ using a panel of targets for most currently-used drugs. We now report that both quercetin and 6BrQ provide equivalent results in cyclic voltammetric and biochemical antioxidant assays. We also report that neither 10-7 M quercetin nor 6BrQ provides any significant (>50%) effects on any of the 104 assays in a Eurofins off-target screening panel. At 10-5 M, both quercetin and 6BrQ exert significant effects in assays for glycogen synthase kinase 3 (GSK3{beta}) as well as those for serotonin 5HT2B receptor, adenosine transport, adenosine A2A receptors, cyclooxygenases COX1 and COX2, phosphodiesterases PDE3A and 4D2 and PPAR gamma. These data extend prior characterization of quercetins biochemical effects, provide novel results for 6BrQ and support the likelihood that both quercetin and 6BrQ can a) directly inhibit GSK3, b) reduce GSK3 activities via enhancement of its dephosphorylation by PTPRD and c) display modest numbers of off target activities at high concentrations, several of which could conceivably contribute to anti-AD activities. These results advance bioavailable glycosylated prodrugs that can be metabolized to 6BrQ as developmental candidates for AD.

BackgroundAlzheimers disease (AD) is a neurodegenerative disorder marked by cognitive decline, memory impairment, and functional deterioration. Its complex pathogenesis involves factors such as amyloid plaques, tau tangles, neuroinflammation, and synaptic dysfunction, but the precise mechanisms remain unclear, hindering effective treatment. Genetic, environmental, and lifestyle factors contribute to AD risk, yet their interactions are poorly understood. Recent advances in transcriptomics and metabolomics have shed light on the molecular underpinnings of AD, with gene expression alterations and metabolic disruptions implicated in disease progression. These multi-omics disruptions highlight the need for integrative analytical approaches to better characterize AD-relevant biology and advance biomarker discovery. ObjectivesTo integrate genetically imputed whole blood transcriptomics and plasma metabolomics to predict cognitive performance (PACC3) and to identify risk genes and metabolites contributing to prediction, thereby characterizing molecular signatures associated with cognitive performance in AD. MethodsThis study applies a machine learning algorithm to integrate genetically imputed whole blood transcriptomics and measured plasma metabolomics data to predict cognitive performance, as measured by PACC3 score, using data from the Wisconsin Registry for Alzheimers Prevention (WRAP) cohort (N = 1,046). After training a machine learning model on WRAP, the predictive performance was evaluated using an independent dataset from the Wisconsin Alzheimers Disease Research Center (ADRC) cohort (N = 85). Feature importance was assessed to identify genes and metabolites that may play a role as potential risk factors in AD. ResultsThe machine learning model achieved a normalized root mean squared error (NRMSE) of 0.743 {+/-} 0.037 and an R{superscript 2} of 0.311 {+/-} 0.016 across 5-fold holdout test folds in WRAP (p = 5.93 x 10-30), and an NRMSE of 0.915 and an R{superscript 2} of 0.061 when applied to the Wisconsin ADRC cohort. Feature importance revealed transcriptomic biomarkers such as RIPK1, IL6ST, and BIN1 whose higher imputed expression levels were associated with poorer cognitive performance whereas other potential biomarkers including UGP2, NDUFB5, and TMOD2 were associated with better cognitive performance, reflecting mitochondrial energy metabolism and molecular processes associated with cognitive resilience. Several predictive metabolites including benzoate, 3-phenylpropionate, and imidazolelactate also mapped to AD vulnerability signatures, while acyl-carnitine species such as hexanoylcarnitine (C6) and propionate-related metabolites aligned with metabolic resilience. ConclusionIntegrated analysis of transcriptomics and metabolomics demonstrated potential utility for identifying candidate biomarkers associated with cognition in AD. Genes and metabolites reflecting inflammatory signaling, mitochondrial dysregulation, and lipid metabolism emerged consistently among the most influential contributors. These findings align with well-established AD vulnerability pathways and highlight convergent biology across two omics layers. Collectively, this supports the value of multi-omics integration for improving molecular characterization of AD and advancing biomarker prioritization for future mechanistic and translational studies.

INTRODUCTIONAstrocyte reactivity may contribute to the increased risk of Alzheimers disease (AD) in women. Plasma glial fibrillary acidic protein (GFAP), a marker of astrocytic reactivity, has been associated with AD pathology and cognitive decline. Although higher GFAP levels have been reported in women, few studies have investigated sex-specific relationships with other plasma AD biomarkers and cognition. METHODSParticipants were enrolled in the Memory Education and Research Initiative, a longitudinal community-based cohort, and underwent comprehensive evaluation including blood biomarker sampling. RESULTSCognitively unimpaired women exhibited higher plasma GFAP levels than men (N=548). Higher baseline GFAP was associated with worse longitudinal episodic memory performance, exclusively in women. In addition, both higher baseline GFAP and increasing GFAP levels over time were associated with lower longitudinal plasma A{beta}42/40 ratio. DISCUSSIONThese findings suggest that astrocytic reactivity is more pronounced in women and may contribute to sex-specific vulnerability to AD-related pathology and cognitive decline. HighlightsO_LIWomen are at increased risk of developing Alzheimers disease (AD). C_LIO_LICognitively unimpaired women exhibited higher plasma GFAP levels than men. C_LIO_LIHigher GFAP levels were associated with longitudinal cognitive decline in women. C_LIO_LIHigher GFAP associated with greater amyloid and tau burden biomarkers in women. C_LIO_LIIncreased astrocyte reactivity (GFAP) may explain increased AD risk for women. C_LI Research in Context1) Systematic Review: Women account for approximately two-thirds of individuals with Alzheimers disease (AD). Longer lifespan only partially explains this higher prevalence. Astrocyte reactivity, indexed by glial fibrillary acidic protein (GFAP), has emerged as a key biological marker associated with AD risk. In preclinical and prodromal stages, higher GFAP levels are linked to cognitive decline, amyloid accumulation, tau pathology, and neurodegeneration. Few studies have investigated sex-related differences in GFAP and AD risk. 2) Interpretation: Our findings indicate that cognitively unimpaired women show higher plasma GFAP levels than men. Elevated GFAP levels in women are associated with plasma biomarkers of increased amyloid and tau burden. Higher GFAP levels are also related to longitudinal decline in global cognition and episodic memory in women. 3) Future Directions: Further studies should investigate sex-related differences in astrocyte reactivity in relation to systemic inflammation, microglial activation, brain amyloid and tau pathology, and future AD risk.

Background: Estimates from high income countries suggest that approximately 40% of dementia cases may be attributable to modifiable risk factors across the life course. However, most evidence informing these estimates originates from high income settings, and population level estimates from sub Saharan Africa remain limited. We aimed to estimate population attributable fractions (PAFs) for modifiable dementia risk factors in the Democratic Republic of the Congo (DRC). Methods: We conducted a cross sectional analysis of community dwelling adults aged 65 years and older enrolled in the Etude du Vieillissement Cognitif et de Demence en Republique Democratique du Congo (EVCD RDC). Prevalence estimates of dementia and associated exposures were derived from prior epidemiological studies in this population. Odds ratios were estimated using logistic regression, and population attributable fractions were calculated by integrating exposure prevalence with effect size estimates. To account for correlations between exposures, communality weights were applied when estimating combined PAFs across risk factors. Findings: Combined modifiable risk factors were estimated to account for 37.3% (95% CI 14.3 to 55.6) of dementia cases in this sample. Poverty had the largest weighted PAF (18.4%, 95% CI 13.3 to 22.8), followed by low educational attainment (11.3%, 95% CI 7.3 to 15.3) and depression (5.8%, 95% CI 2.8 to 8.6). Additional contributors included traumatic events (5.4%), war exposure (2.1%), diabetes (1.3%), and hypertension (1.1%). A hypothetical 15% proportional reduction in these risk factors was estimated to reduce dementia prevalence by 6.4% (95% CI 2.1 to 10.8), corresponding to approximately 10 700 cases prevented in the DRC by 2025. Interpretation: Modifiable risk factors account for a substantial proportion of dementia burden in the DRC, with structural determinants such as poverty and education contributing the largest fractions. Dementia prevention strategies in low and middle income countries may therefore require broader public health approaches that address socioeconomic and structural determinants alongside conventional clinical risk factors.

Amyloid-{beta} (A{beta}) PET imaging is a core biomarker and is considered sufficient for the biological diagnosis of Alzheimers disease (AD). However, it is typically reduced to a binary A{beta}/A{beta}+ classification. In this study, we aimed to identify subgroups along the continuum of A{beta} accumulation including subgroups within A{beta}- and A{beta}+. We used a total of 3,110 of A{beta} PET scans from Alzheimers Disease Neuroimaging Initiative (ADNI) and Anti-Amyloid Treatment in Asymptomatic Alzheimers Disease (A4) datasets to develop petVAE, a 2D variational autoencoder model. The model accurately reconstructed A{beta} PET scans without prior labeling or pre-selection based on scanner type or region of interest. Latent representations of scans extracted from the petVAE (11,648 latent features per scan) were used to visualize, analyze, and cluster the AD continuum. We identified the latent features most representative of the continuum, and clustering of PET scans using these features produced four clusters. Post-hoc characterization revealed that two clusters (A{beta}-, A{beta}-+) were predominantly A{beta} negative and two (A{beta}+, A{beta}++) were predominantly A{beta} positive. All clusters differed significantly in standardized uptake value ratio (p < 1.64x10-8) and cerebrospinal fluid (CSF) A{beta} (p < 0.02), demonstrating petVAEs ability to assign scans along the A{beta} continuum. The clusters at the extremes of the continuum (A{beta}-, A{beta}++) resembled to the conventional A{beta} negative and A{beta} positive groups and differed significantly in cognitive performance, Apolipoprotein E (APOE) {varepsilon}4 prevalence, and A{beta}, tau and phosphorylated tau CSF biomarkers (p < 3x10-6). The two intermediate clusters (A{beta}-+, A{beta}+) showed significantly higher odds of carrying at least one APOE {varepsilon}4 allele compared with the A{beta}-cluster (p < 0.026). Participants in A{beta}+ or A{beta}++ clusters exhibited a significantly faster rate of progression to AD compared to A{beta}-group (Hazard ratio = 2.42 and 9.43 for groups A{beta}+ and A{beta}++, respectively, p < 1.17x10-7). Thus, petVAE was capable of reconstructing PET scans while also extracting latent features that effectively represented the AD continuum and defined biologically meaningful clusters. By capturing subtle A{beta}-related changes in brain PET scans, petVAE-based classification enables the detection of preclinical AD stages and offers a new data-driven framework for studying disease progression.

Mild Behavioural Impairment (MBI) is defined by later-life onset of persistent behavioural changes and is recognized as a risk marker for cognitive decline and dementia. Apathy, a core MBI domain characterized by diminished interest, initiative, and emotional reactivity, can emerge before dementia and is hypothesized to be associated with structural brain changes. While previous studies have explored Alzheimer disease (AD)-related neuroanatomical substrates of apathy in the dementia clinical stage, few have investigated these associations in cognitively normal (CN) or mild cognitive impairment (MCI) individuals with persistent apathy consistent with MBI. Thus, this study explores structural brain differences between individuals with MBI-apathy and those without neuropsychiatric symptoms (no-NPS). Participants (n = 446; mean age = 69.6 years; 79.8% CN; 62.8% female) were drawn from the National Alzheimers Coordinating Center and categorized into MBI-apathy (n = 59) and no-NPS (n = 387) groups. Linear regressions were used to model associations between NPS group and regional brain measures, with adjustments for age, sex, years of education, apolipoprotein E4 carrier status, intracranial volume, and Mini-Mental State Examination score, with false discovery rate (FDR) correction for multiple comparisons. Primary outcomes included two predefined AD meta-regions-of-interest (ROIs): 1) thickness: a composite measure of mean cortical thickness across the entorhinal cortex, inferior temporal gyrus, middle temporal gyrus, inferior parietal lobule, fusiform gyrus, and precuneus; and 2) volume: a composite measure of mean cortical and subcortical grey matter volume across the hippocampus, entorhinal cortex, amygdala, middle temporal gyrus, inferior parietal lobule, and precuneus. Primary outcomes also included cortical thickness and grey matter volume among individual ROIs including the ventral striatum (VS), anterior cingulate cortex (ACC), orbitofrontal cortex (OFC), ventrolateral prefrontal cortex (vlPFC), and dorsolateral prefrontal cortex (dlPFC). MBI-apathy status was associated with significantly lower AD-meta-ROI cortical thickness (Z-score difference [95% CI]; FDR-corrected p-value, -0.43 [-0.73 - [-0.12]]; 0.025) and lower AD meta-ROI grey matter volume (-0.50 [-0.71 - [-0.30]]; <0.001). MBI-apathy was also associated with significantly lower dlPFC thickness (-0.40, [-0.70 - [-0.09]]; 0.02) and volume (-0.28 [-0.50- [-0.06]]; 0.026) and lower OFC volume (-0.32, [-0.57 - [-0.07]]; 0.026) compared to the no-NPS group. Within a non-dementia sample, MBI-apathy was more strongly associated with established AD-vulnerable regions than with regions that have been traditionally implicated in apathy in dementia. Results suggests that during CN and MCI stages, MBI-apathy may reflect early AD-related neurodegeneration, with conventional apathy-related structural changes becoming more prominent as disease progresses.

INTRODUCTIONHealthful dietary patterns may attenuate dementia risk by preserving cerebrovascular health. Prior work has focused on systemic arterial stiffness, but cerebrovascular measures may be more sensitive to neuroprotective effects of diet. We examined associations between Mediterranean diet adherence, prefrontal cortex (PFC) arterial elasticity, and cognition in older adults. METHODSParticipants were 198 older adults (58% female; mean age 65.6 years) from the Newcastle ACTIVate cohort. Mediterranean Diet (MedDiet) scores were derived from the Australian Eating Survey food frequency questionnaire. Pulse Relaxation Function (PReFx), an index of PFC arterial elasticity, was measured using pulse Diffuse Optical Tomography. Cognition was assessed with CANTAB and a cued task-switching paradigm. RESULTSHigher MedDiet was associated with higher PFC arterial elasticity. MedDiet was not associated with cognition, and PReFx did not mediate diet-cognition associations. DISCUSSIONGreater Mediterranean diet alignment was cross-sectionally associated with PFC arterial elasticity, suggesting a pathway through which diet may influence brain health in ageing.

BackgroundRecent studies revealed key immunological mechanisms within the central nervous system (CNS) that contribute to Alzheimers disease pathology. Additionally, analyses of human AD datasets have also associated viral encephalitis exposure (i.e., viral-induced neuroinflammation) with the development of AD and dementia, highlighting the need to better understand how viral encephalitis and neuroimmune mechanisms within the brain may impact AD pathologies such as A{beta} plaque deposition. Intracranial infection of susceptible mice with the neurotropic JHM strain of murine coronavirus (JHMV) results in acute encephalomyelitis characterized by viral infection of glia and a robust inflammatory response comprised of monocytes/macrophages and T cells that aid in controlling viral replication. MethodsTo determine how coronavirus-induced encephalitis may impact established A{beta} plaque deposition, we intracranially inoculated JHMV into aged 5xFAD model of amyloidosis. We utilize immunohistochemical and biochemical analysis to assess the impact on existing A{beta} pathology. We also utilize spatial transcriptomic imaging to explore how viral encephalitis affects cellular responses to plaque pathology with single-cell resolution. ResultsIn aged 5xFAD mice, JHMV-induced encephalitis at 12 days p.i. resulted in minimal changes to overall A{beta} protein within the brain. However, viral encephalitis induces CD4+ and CD8+ T cell infiltration and more Lgals3/MAC2-expressing macrophages surrounding dense-core A{beta} plaques, which appear more compacted in JHMV-infected 5xFAD brains compared to uninfected 5xFAD controls. We compared gene expression within JHMV-infected 5xFAD mice and uninfected controls to identify distinct cellular responses to A{beta} plaques that differed. Utilizing differential gene expression and pathway analysis, we found that viral encephalitis increased the proportion of myeloid cells in the 5xFAD brain, which also showed down-regulated disease-associated (DAM) pathways involving A{beta} clearance, response to lipids, and macrophage activation within the post-encephalitis 5xFAD brains. ConclusionsTogether, these findings suggest an attenuated myeloid cell response to A{beta} plaque burden in 5xFAD mice following acute viral encephalitis. Future experiments aim to further dissect inflammatory mechanisms between infiltrating myeloid cells, T cells, and the progression of A{beta} and tau pathology. Data derived from these experiments will further elucidate the viral-induced neuroimmune mechanisms that affect AD pathology and offer an opportunity to determine how these neuropathologic changes, such as subsequent neuronal damage, occur.

The Montreal Cognitive Assessment (MoCA) is widely used to screen for cognitive impairment, yet commonly applied cutoff scores have been found to perform poorly among US Latinos. Prior studies relied on small samples, combining persons with mild cognitive impairment (MCI) and dementia into a single group, or failing to account for multiple intersecting demographic factors. We identified optimal MoCA cutoffs for MCI and dementia among US Latinos while addressing these limitations. We analyzed cross-sectional data from the National Alzheimers Coordinating Center Unified Data Set. Participants included English- and Spanish-speaking Latinos who completed testing in their primary language. Research diagnostic groups consisted of cognitively unimpaired (CU), MCI, and dementia. Groups were further stratified by testing language, age, and level of education. Diagnostic accuracy and receiver operating characteristic (ROC) analyses were performed. The Youden Index was used to determine the optimal cutoff score. Of the 1,673 participants in the total sample, 46% completed the MoCA in Spanish and 54% in English, 54% were CU, and 28% had MCI and 19% had dementia. Area under the curve (AUC) values for CU vs. MCI were 0.70 for Spanish-tested participants and 0.79 for English-tested participants, while values for MCI vs. dementia were 0.85 and 0.89 for the Spanish and English tested participants, respectively. Overall AUC values were 0.76 for CU vs. MCI and 0.86 for mild cognitive impairment vs. dementia. Optimal cutoffs were consistently found to be lower among participants tested in Spanish, those older than age 75, and participants with the fewest years of education, with some optimal cutoffs shown to be substantially lower than the traditionally used standard cutoff. These findings provide cutoffs that better reflect differences amongst language and demographic groups. We also provide a scoring calculator for clinical and research use.