Alzheimer's & Dementia: Translational Research & Clinical Interventions

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

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

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.

BackgroundThe AT(N) biological framework classifies Alzheimers disease (AD) pathology using CSF biomarkers, with the A+T+ profile defining biological AD and the A-T+ profile representing a biologically distinct entity consistent with suspected non-Alzheimers pathophysiology, such as primary age-related tauopathy. Functional assessment capable of differentiating these profiles non-invasively remains limited. This study investigates whether cognitive vergence and pupillary temporal dynamics during a visual oddball task can distinguish A-T+ from A+T+ biological profiles in individuals with mild cognitive impairment (MCI). MethodsThirty-eight participants with MCI (12 A-T+, 26 A+T+) classified by CSF biomarkers completed a visual oddball task (80% distractors, 20% targets) under continuous eye-tracking. Linear mixed-effects models examined profile x condition interactions on full time series and six trial-level temporal features. Participant-level differentiation was assessed using binomial logistic regression, adjusting for age, sex, and MMSE. ResultsBoth profiles showed comparable overall oculomotor response magnitudes but diverged markedly in temporal organization. Significant profile x condition interactions emerged for cognitive vergence global slope, time to peak, and pupillary time to peak. Logistic regression confirmed that timing features discriminated biological profiles at the participant level, with differentiation reversing direction between distractor and target conditions. A-T+ participants also maintained superior target detection accuracy (89.3% vs. 82.4%, p = 0.001). ConclusionCognitive Vergence and pupillary temporal dynamics during an oddball task provide condition-dependent functional oculomotor signatures that systematically differentiate AT(N) biological profiles in MCI, suggesting that oculomotor assessment may offer an accessible, non-invasive complement to CSF-based profile characterization.

Background: Gabapentin prescriptions have increased 123% since 2010, reaching 59 million annually and 15.5 million patients. Recent evidence indicates that concomitant use of gabapentin and dihydropyridine calcium channel blockers (DHP-CCBs) amplifies dementia risk through a dual neuronal calcium signaling blockade mechanism. Whether these cognitive effects are reversible upon discontinuation, and whether the combination accelerates decline in patients with established dementia, remains unknown. Methods: We conducted two complementary studies using the Rutgers Clinical Research Data Warehouse (CRDW; 2015-2024). Study 1: A self-controlled case series (SCCS; N=3,058) comparing cognitive event rates during concomitant gabapentin-DHP-CCB use versus after discontinuation, using strictly duration-matched observation windows. Study 2: A cohort study (N=320) of patients with established dementia initiating gabapentin, comparing outcomes between DHP-CCB, non-DHP-CCB, and no-CCB users. Findings were externally replicated in the NIH All of Us Research Program Controlled Tier (N=8,853). Results: In the CRDW self-controlled analysis, event rates were significantly higher during combination use versus after discontinuation: falls (RR 1.34, 95% CI 1.11-1.61), cognitive symptoms (RR 1.67, 95% CI 1.38-2.01), and composite cognitive endpoint (RR 1.32, 95% CI 1.09-1.59). Effects were greatest when both drugs were discontinued (cognitive symptoms RR 2.21; falls RR 1.76). Protopathic bias was ruled out by monotonically increasing RRs across 0-, 30-, and 60-day lag conditions. In the dementia acceleration cohort, DHP-CCB use tripled encephalopathy risk (HR 3.18, 95% CI 1.36-7.46), with zero events among non-DHP CCB users. External replication in All of Us confirmed all primary outcomes (falls RR 1.53, cognitive symptoms RR 1.26, composite RR 1.42; all p<0.001). A non-DHP CCB negative control in All of Us confirmed mechanistic specificity: cognitive symptom and encephalopathy reversal signals were absent with verapamil/diltiazem. CKD amplified effects in both datasets, consistent with gabapentin accumulation through impaired renal clearance. Conclusions: Cognitive effects associated with concomitant gabapentin-DHP-CCB use appear substantially reversible upon discontinuation, replicated across two independent datasets. The DHP-specific pattern, confirmed through a pharmacological negative control, supports a neuronal L-type calcium channel mechanism. Clinicians should review gabapentin-DHP-CCB combinations in patients with cognitive complaints or falls, as deprescribing - particularly of both agents - may produce meaningful improvement.

Early detection of disease progression using clinically-relevant biomarkers in animal models is important for mechanistic studies and for developing therapeutics in neurodegenerative diseases including Alzheimers disease (AD). The preclinical stage of AD, when amyloid-{beta} (A{beta}) starts to accumulate before cognitive decline, provides a critical window for disease modification. In humans, decreases in cerebrospinal fluid (CSF) A{beta}42 and the A{beta}42/A{beta}40 ratio in preclinical AD are considered to reflect the preferential sequestration of aggregation-prone A{beta}42 into {beta}-sheet-rich deposition in the brain, with corresponding changes being detectable in plasma. However, the extent to which these biomarker-pathology relationships are recapitulated in AD model mice remains incompletely defined. Here we show that CSF and plasma A{beta}42 and the A{beta}42/A{beta}40 ratio decline with age in parallel with the progression of {beta}-sheet-rich A{beta} deposition in preclinical 5XFAD mice, one of the most widely used AD mouse models, as assessed through monthly profiling of these biomarkers. Notably, the CSF A{beta}42/A{beta}40 ratio showed a negative correlation with {beta}-sheet-rich A{beta} deposition in the brain, whereas CSF A{beta}40 did not show a comparable association. In addition, the plasma A{beta}42/A{beta}40 ratio showed a positive correlation with the CSF A{beta}42/A{beta}40 ratio, suggesting that the plasma A{beta}42/A{beta}40 ratio may also reflect brain A{beta} deposition in this model. The strength of these correlations differed by sex, suggesting that sex-dependent differences in the A{beta} kinetics in this model may influence how closely fluid biomarkers reflect pathological progression. These findings support the potential utility of fluid A{beta} as a pathology-linked, translatable biomarker in preclinical 5XFAD mice. Highlights- Fluid A{beta} biomarkers are associated with early A{beta} deposition in preclinical 5XFAD mice. - The CSF A{beta}42/A{beta}40 ratio negatively correlates with {beta}-sheet-rich brain A{beta} deposition. - The plasma A{beta}42/A{beta}40 ratio positively correlates with the CSF A{beta}42/A{beta}40 ratio. - Monthly profiling defines fluid A{beta} biomarker dynamics in preclinical 5XFAD mice. - Sex differences may affect biomarker-pathology relationships in these mice.

BackgroundTraumatic brain injury with loss of consciousness (TBI-LOC) is an established risk factor for dementia, yet the pathways linking remote TBI to Alzheimers disease (AD) biology remain incompletely defined. APOE {varepsilon}4 is the strongest genetic predictor of amyloid accumulation in late-onset AD, it may moderate the long-term consequences of head injury. This study investigates whether history TBI-LOC independently contributes or synergistically interacts with APOE {varepsilon}4 to amplify late-life amyloid and tau burden. Methods429 participants completed the Ohio State University TBI screening tool and an amyloid PET scan (centiloids). A subcohort (n=352) also underwent tau PET. TBI history was classified by recency (<10 vs >10 years) and severity (no TBI, dazing/confusion [TBI-DZ], TBI-LOC). Analyses were stratified by degree of clinical impairment as assessed by Clinical Dementia Rating (CDR=0 vs CDR>0). Logistic and linear regression models examined associations between TBI and amyloid, adjusting for age, sex, education, and APOE {varepsilon}4, including an APOE*TBI-LOC status interaction term, while Fishers exact tests evaluated TBI recency and biomarker positivity. ResultsIn CDR=0 participants (n=365), 119 reported a history of TBI, comprising 56 TBI-DZ and 63 TBI-LOC. TBI-LOC but not TBI-DZ, correlated with elevated amyloid PET levels (p<0.001; [4.6-17]). Furthermore, an interaction between APOE {varepsilon}4 and TBI-LOC indicated that TBI-LOC augmented the amyloid-related risk associated with the APOE {varepsilon}4 allele (p=0.003; [4.3-21]). The interaction persisted when stratified by TBI recency with only remote TBI-LOC (occurring more than 10 years prior) associated with increased amyloid PET (p=0.003 [5.2-25]). No association between TBI and tau was identified in a subset with tau PET, and no TBI-amyloid correlations were observed among symptomatic participants (CDR>0; n=64) suggesting a ceiling effect of pathology once clinical dementia is present. ConclusionsHistory of remote TBI-LOC is linked to elevated amyloid PET levels in later life, particularly among APOE {varepsilon}4 carriers with a CDR=0. The robust findings for amyloid, contrasted with null tau results and the reduced association in symptomatic cases underscore the importance of considering TBI history when screening for preclinical AD and assessing early-stage risk.

INTRODUCTION: Herpes simplex virus-1 (HSV-1) has been implicated in Alzheimers disease (AD). METHODS: Reads from Alzheimers Disease Sequencing Project whole-genome sequencing data collected from brain (2,203 AD; 616 controls) and blood (8,908 AD; 15,768 controls) were aligned to viral genomes. Generalized linear mixed-models tested for the effect of HSV-1 DNA on AD, and we performed GWAS on HSV-1 presence and SNPxHSV-1 interaction effects on AD, adjusting for age, sex, tissue, library preparation, relatedness, and ancestry principal components. RESULTS: Across ancestry groups, HSV-1 DNA was consistently less frequent in AD cases; reads predominantly mapped to regions containing the latency-associated transcript region. DNA prevalence was lower in APOE-{epsilon}4 carriers; HSV-1 was associated with reduced AD risk in {epsilon}4 non-carriers but increased risk in carriers. GWAS identified host genetic influences on HSV-1 detection and interaction loci affecting AD risk. DISCUSSION: HSV-1 DNA showed an inverse association with AD and is affected by genetics.

BackgroundGenome-wide association studies have identified numerous variants associated with neuropsychiatric disorders. Although some significant loci can carry substantial risk, as in Alzheimers Disease, the remaining genetic variance is distributed across many small-effect loci. Polygenic risk scores (PRS) aggregate this risk but do not capture epistatic interactions, and offer limited biological interpretability and predictive accuracy. Computing gene level risk scores and integrating known or statistically validated gene-gene associations has the potential to increase interpretability and/or accuracy. Graph Neural Networks (GNNs) can leverage graph structured genetic data that models potential epistatic interactions to achieve these goals. MethodsWe developed a three-stage Graph Attention Network (GAT) classifier using individual-level GWAS data from 7,358 participants across seven Alzheimers Disease Center cohorts. Nodes were defined as genes, with risk scores from AD and 11 genetically correlated phenotypes serving as features. We evaluated two graph construction strategies: gene co-expression networks derived from hippocampal transcriptomic data and curated pathway-based graphs. Additionally, a bilinear context module was incorporated to capture global gene-gene interactions beyond the graph topology. In Stage 1, a GNN encoder was trained on the graphs; Stage 2 injected PRS for non-coding SNPs after the encoder to better capture genetic risk via transfer learning, and Stage 3 applied adversarial training with gradient reversal for ancestry debiasing. GNN predictions were ensembled with whole-genome PRS using elastic net regression. ResultsThe best-performing GNN model -- a GAT with bilinear context operating on the pathway graph -- achieved an AUROC of 0.78 (95% CI: 0.75-0.80). Ensemble models combining Stage 2 or 3 GNN logits with whole-genome PRS achieved an AUROC of 0.82 (0.79-0.84), outperforming PRS alone (0.80). GxI attribution and additional explainability analyses revealed stage-specific biological signals, some of which re-capitulated known gene-phenotype associations and others which may reflect potential new areas of inquiry. ConclusionA multi-stage GAT framework captures complementary, non-additive genetic signal that, when ensembled with PRS, improves the accuracy of AD classification. Post-hoc explainability analyses yield biologically interpretable gene networks, supporting the utility of graph-based deep learning for dissecting complex genetic architectures.

Background: Cardiovascular health factors are associated with cognitive decline and risk of dementia, including Alzheimer disease (AD); however, this has been mostly studied in late life. We investigated whether vascular and lifestyle factors are associated with AD plasma and imaging biomarkers in midlife. Methods: We investigated 1,406 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study with information on vascular and lifestyle factors framed from the American Heart Association (AHA) life's essential 8 (LE8) guidelines for cardiovascular health at early midlife (mean age 45.0 SD 3.6) and AD biomarkers in late midlife (mean age 60 SD 3.5). LE8 was calculated and categorized into poor (0-49), intermediate (50-79), and ideal (80-100) cardiovascular health, based on 8 components including smoking, diet, body mass index (BMI), sleep, fasting glucose, blood pressure, cholesterol, and physical activity. We assessed the AD plasma biomarkers phosphorylated tau 217 (ptau-217) and amyloid beta 42/40 ratio (A{beta}42/40) and the Spatial Pattern of Abnormality for Recognition of Early AD (SPARE-AD), an algorithm that characterizes AD-like brain atrophy on brain MRI. We used linear regression to examine the association between LE8 and log-transformed and standardized AD biomarker measures adjusting for age, sex, race, education, and kidney function. Results: Compared to ideal LE8, intermediate (67.9% of participants) and poor (12.6%) LE8 was associated with lower A {beta}42/40 (adjusted mean difference: -2.37, 95% CI: -2.38 to -2.36 and -2.38, 95% CI: -2.40 to -2.36, respectively). There was no association between the LE8 group and ptau-217 level. Moreover, compared to ideal LE8 participants, those with poor LE8 had higher SPARE-AD atrophy pattern (adjusted mean difference: -0.71, 95% CI: -0.81 to -0.62). Conclusion: These findings indicate that poor cardiovascular health in midlife, as defined by the AHA LE8, is linked to less favorable early AD biomarker profiles, particularly reflecting greater amyloid burden and structural brain changes.

BackgroundRNA editing is a post-transcriptional modification that alters the sequence of an RNA transcript. Two types of RNA editing were found in mammals, involving the enzymatic deamination of either adenosine to inosine (A-to-I) or cytidine to uridine (C-to-U) nucleotides in RNA. A-to-I, which is the most common form of RNA editing, is mediated by the ADAR (adenosine deaminases acting on RNA) family of enzymes, ADAR1, ADAR2, and ADAR3. The editing event alters the hydrogen bond pairing of nucleobases, and the editing site will be recorded as guanosine rather than the original adenosine. Indeed, RNA editing deregulation has been linked to several nervous and neurodegenerative diseases. In this project work is done on Alzheimers disease (AD) and the samples are from anterior cingulate cortex of human brain tissue. AD is the main dementia in the world and a neurodegenerative condition prevalent in the elderly. MethodologyA total of 20 raw RNA-sequencing data samples containing 10 controls and 10 Alzheimers disease (AD) cases were collected from NCBI using SRA Toolkit. Quality assessment was performed using FastQC and processed using Trimmomatic. Alignment was done using STAR RNA-seq aligner. RNA editing detection was performed using REDItools, detected sites were subsequently annotated against the REDIportal database. The resulting control-specific and disease-specific novel editing sites were merged into a single dataset containing exclusively novel, group-specific A-to-I editing events. This merged dataset was subsequently used for downstream feature extraction and machine learning analysis. Probability-based filtering was done to extract high-confidence disease associated sites and their gene list was used for computational level biological validation, pathway and functional enrichment analysis as well as overlap with known AD loci. ResultsRandom Forest showed the highest accuracy score (0.804) and ROC-AUC score (0.854). Most important features that differentiated control and diseased novel sites in random forest were coverage ([~]0.35), editing level ([~]0.33) and GC content ([~]0.15). The AEI mean values is higher in both male and female diseased cases ([~]0.48-0.50) but less in male and female control cases ([~]0.14-0.21). The mean values of ADAR1_CPM higher in control cases (123.65-143.30) and is less in diseased cases (88.35-97.93), ADAR2_CPM is almost equal in all cases ([~]3.7-4.7) and ADAR3_CPM is very less in all the cases ([~]0-0.02). Most candidate editing site were present in exon ([~]62-67 %) CDS regions ([~]17-21%) and relatively smaller fraction of gene ([~]15-16 %). Editing alterations preferentially affect molecular systems governing synaptic structure, neurotransmission, and central nervous system integrity. In the main set -of the 2576 high-confidence genes identified, 33 overlapped with AD GWAS loci. In the core set -of the 1367 high-confidence genes identified, 11 overlapped with AD GWAS loci. ConclusionFeature like coverage, editing level and GC content contributed most. Alu sites are negligible as compared to non-alu sites but the AEI mean values are higher in diseased cases than in control cases. The mean values of ADAR1_CPM are higher than ADAR2_CPM and ADAR3_CPM.Sex does not play a major factor. High-confidence disease-associated RNA editing sites are strongly biased toward transcript-centric regions, particularly exons, with a notable subset affecting coding sequences. Importantly, enrichment of neurodegeneration-associated pathways and cognition-related human phenotypes further supports the disease relevance of these gene networks. RNA editing events in Alzheimers cortex may represent a regulatory mechanism largely independent of inherited genetic susceptibility loci.

Background: Social determinants of health (SDOH) are increasingly recognized as contributors to Alzheimer disease (AD) risk, yet the impact of multidimensional social disadvantage early AD-related pathophysiology remains poorly understood. Methods: We studied 1,466 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) cohort with SDOH assessed in early midlife (mean age 40, SD 3.6 years) and plasma AD biomarkers measured 20 years later. A comprehensive SDOH index was constructed from 12 indicators spanning five domains (economic stability, education, neighborhood and physical environment, community and social context, and health care access). We examined associations between SDOH quartile and log-transformed, standardized plasma phosphorylated tau 217 (p-tau217), neurofilament light chain (NfL), and amyloid-lower case Greek beta42/40 (Alower case Greek beta42/40) using linear regression adjusted for age, sex, race, and estimated glomerular filtration rate. Linear trends across SDOH quartile were also evaluated. Results: Participants in the most disadvantaged SDOH quartile had higher p-tau217, higher NfL and lower Alower case Greek beta42/40 level compared with those in the least disadvantaged quartile (p-tau 217: lower case Greek beta = 0.12, 95% CI 0.03-0.21, p = 0.008; NfL: lower case Greek beta = 0.20, 95% CI 0.05-0.35, p = 0.009; lower case Greek beta42/40: lower case Greek beta = -0.15, 95% CI -0.30-0.00, p=0.05). There was also a significant trend across quartile (p-tau 217: p for trend = 0.012; NfL: p for trend= 0.001). Analyses of individual SDOH domains indicated that lower economic stability, poorer health care access, and lower education were associated with higher NfL, and poorer health care access was associated with higher p-tau217. Conclusions: Greater SDOH disadvantage in early midlife was associated with higher levels of plasma AD biomarkers reflecting AD pathology and neurodegeneration decades later. These findings suggest that social disadvantage during midlife may contribute to early AD-related biological changes and highlight potentially modifiable social factors relevant for dementia prevention.

Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSAdults with Down syndrome (DS) have a higher risk of developing Alzheimers disease (AD). As gut microbiota (GM) alterations have been reported in AD, we investigated their association with cognitive decline and plasma AD biomarkers in DS. METHODSFecal and plasma samples were collected from 58 adults with DS (21-75 years) and 30 euploid controls (CTRL; 25-83 years). GM was profiled using 16S rRNA sequencing. Major Neurocognitive Disorder (NcD) was diagnosed according to DSM-5 criteria. Plasma levels of p-Tau181, NfL, and GFAP were measured using the Simoa platform. RESULTSCompared with CTRL, DS showed significant changes in UBA1819 and Intestinibacter genera, previously reported to be associated with mild cognitive impairment. Furthermore, DS with NcD were characterized by a reduced abundance of Roseburia genus, which was also negatively associated with plasma levels of AD biomarkers. CONCLUSIONAdults with DS display AD-associated changes in GM partially resembling those previously reported in euploid AD patients

Nighttime agitation (NA) is a prevalent and challenging phenomenon affecting people with dementia (PwD), often resulting in premature institutionalization. Yet, informal caregivers' perspectives on this phenomenon remain underexplored. We conducted 15 in-depth interviews with informal caregivers to gain insight into their experiences and reactions to NA. Thematic analysis identified seven sub-themes related to carers' experience and eight sub-themes concerning their reactions. These themes emerged across three levels, namely, PwD, informal caregiver and the environment. Most phenomena occurred at a dyadic level between PwD and informal caregiver, highlighting the potential of interventions targeting dyadic coping. Informal caregivers feel insufficiently supported when sleep disturbances co-occur with NA. They primarily rely on self-initiated strategies and learn by experience. Caregivers mention the need for more advanced knowledge and skills in reacting to co-occurrence of sleep disturbances with NA or systemic support in terms of dealing with emergencies. Caregivers also reflect extensively on the impact of challenging behaviors during the night on their mental and physical well-being. Notably, no non-pharmacological interventions for NA adequately address the themes identified in this study, highlighting the urgent need for integrative approaches and recognition of caregiver wellbeing as a core outcome, not a secondary consideration in interventions.

Background: The role of biological age acceleration (BioAgeAccel) in the dynamic progression from single cardiovascular-kidney-metabolic disease (CKMD) to multimorbidity, and subsequently to dementia and mortality remains elusive. Methods: We conducted a longitudinal study with data of 433,911 UK Biobank participants. Cardiovascular-kidney-metabolic multimorbidity (CKMM) was defined as the coexistence of two or more CKMDs, including cardiovascular disease (CVD), stroke, type 2 diabetes (T2D), and chronic kidney disease. Biological aging was measured via PhenoAge and KDM-BA. Multistate models examined the association between BioAgeAccel and disease transitions, ranging from healthy to the first occurrence of CKMD (FCKMD), then progression to CKMM, dementia, and mortality. Restricted mean survival time estimated the disease transition time or life expectancy between states. Results: BioAgeAccel was significantly associated with increased risks across all disease transitions. Specifically, during CKMM progression, the hazard ratios (HRs) of the transition from healthy to FCKMD were 1.24 [95%CI 1.23-1.25] for PhenoAgeAccel and 1.16 [1.15-1.17] for KDM-BA-Accel. For subsequent transition to CKMM, the HRs were 1.20 [1.18-1.22] and 1.19 [1.17-1.21], respectively. In dementia-related transitions, PhenoAgeAccel showed the higher risk for CKMM to dementia (HR=1.13 [1.04-1.22]) than for the transition from healthy or from FCKMD to dementia. These associations were further moderated by age, physical activity, educational, and lifestyle factors. BioAgeAccel also accelerated disease progression and reduced life expectancy; for example, during CKMM progression, BioAgeAccel shortened the time between disease transitions by about 1.09 years from healthy to FCKMD, and an additional 1.75 years to CKMM. Regarding life expectancy, individuals with CKMM experienced an average reduction of about 1.36 years under PhenoAge, while those with dementia showed a decrease of about 0.77 years. Among individuals with CVD or T2D as the initial diagnosis, the impact of BioAgeAccel on progression to CKMM or dementia was stronger. Conclusions: BioAgeAccel exerts significant promotive role in the onset of CKMD and their subsequent progression to CKMM, dementia, and mortality, helping identify high-risk individuals. Implementing biological age assessments and health lifestyle interventions in middle-aged populations serves as an effective strategy for alleviating the burden of CKMDs and dementia.

BackgroundAlzheimers disease (AD) causes progressive decline in language and cognition. Automated speech analysis has emerged as a promising screening tool, yet clinical data scarcity limits progress. To address this, we generated a large-scale simulated speech dataset to model linguistic and acoustic deterioration across cognitive stages, Control, Mild Cognitive Impairment (MCI), and AD. MethodsUsing Monte Carlo simulations, we emulated the Pitt DementiaBank "Cookie Theft" narratives. Acoustic features (speech rate, pause duration, jitter, shimmer) and linguistic features (type-token ratio, unique-word count, filler usage) were synthetically sampled from real-world DementiaBank distributions. We trained an XGBoost classifier to distinguish diagnostic groups, and applied SHAP (Shapley Additive exPlanations) to assess feature importance. ResultsThe model achieved high discriminative performance (AUC {approx} 0.94; accuracy {approx} 85%). Compared to controls, simulated MCI and AD groups showed progressive declines in fluency and lexical diversity, and increases in disfluencies and voice instability. SHAP analysis revealed that key predictors included reduced type-token ratio, higher pause and filler rates, and elevated jitter/shimmer. Classification was most accurate for Control vs. AD; MCI misclassifications highlighted intermediate profiles. InterpretationOur framework, FMN (Forget Me Not), captures clinically relevant speech changes using simulated data, offering an explainable and scalable approach for cognitive screening. While not a substitute for real datasets, FMN validates a pipeline that mirrors known AD markers and can guide future real-world deployments. External validation remains a key next step for translational impact.

Objectives: To evaluate the diagnostic performance of the -synuclein seed amplification assay (SAA) and characterize the impact of -synuclein co-pathology on cognitive and biological profiles in routine clinical practice. Methods: We included 398 patients from the prospective multicenter ALZAN cohort recruited from memory clinics in Montpellier, Nimes, and Perpignan. All participants underwent CSF and blood sampling with measurement of CSF biomarkers (A{beta}42/40, tau, ptau181) and plasma biomarkers (A{beta}42/40, ptau181, ptau217, GFAP, NfL). Cognitive assessment was performed using the Mini-Mental State Examination (MMSE). Clinical diagnoses were independently confirmed by two senior neurologists. Syn status was determined by SAA (RT-QuIC). Results: Of 398 patients, 19 out of 20 patients with Lewy body dementia (LBD) (95.0%) and 32 out of 203 patients with AD (15.8%) were SAA+. SAA-positivity presented a sensitivity of 95% and a specificity of 93.5% for distinguishing LBD from patients without LBD or AD. In the entire cohort, SAA+ patients showed lower MMSE scores (p<0.01), lower CSF A{beta}42/40 ratio (p<0.01), and elevated plasma GFAP (p<0.05). Within the AD group, no significant differences in CSF or blood biomarkers were observed between SAA+ and SAA- patients. Within the AD subgroup, no significant differences in CSF or blood biomarkers were observed between SAA+ and SAA- patients, except for a lower CSF A{beta}42/40 ratio in SAA+ patients (p<0.01). Interpretation: SAA demonstrates good diagnostic capabilities for detecting LBD and confirms notable Syn co-pathology in AD. This study highlights the limitations of routine CSF and emerging blood biomarkers in capturing Syn pathology and the value of integrating SAA into routine neurodegenerative disease assessment.

Background Autosomal dominant Alzheimer's disease (ADAD) serves as a model for presymptomatic biomarker discovery. Characterising the temporal profile of plasma biomarker levels in presymptomatic individuals may enhance understanding of disease pathogenesis, inform future clinical trials, and guide clinical interpretation. Methods We evaluated 124 proteins using a NUcleic acid-Linked Immuno-Sandwich Assay (NULISA) panel in 270 plasma samples from a longitudinal cohort study of ADAD, comprising 113 individuals (73 mutation carriers and 40 non-carriers). We determined the plasma proteomic changes that distinguished mutation carriers from non-carriers. We then used predicted age at symptom onset to determine the approximate timing of presymptomatic divergence in biomarker levels in carriers relative to non-carriers. Results Nine proteins (A{beta}42, BACE1, GFAP, pTau181, pTau231, pTau217, MAPT, NfL, and AChE) robustly differed between carriers and non-carriers, cross-sectionally. Longitudinal analyses showed A{beta}42 levels were elevated in carriers at least 26 years before expected symptom onset. Carriers diverged from non-carriers in phosphorylated tau markers at 21-24 years before expected symptoms, total-tau at 19 years, GFAP and BACE1 at 14 years, and NfL at 6 years. Differences in AChE were seen in symptomatic individuals, likely reflecting cholinesterase inhibitor use. Conclusion Multiple plasma proteins are elevated in presymptomatic and symptomatic autosomal dominant AD mutation carriers relative to non-carriers. Changes in eight biomarkers occur sequentially from 26 to 6 years prior to symptom onset. Combining biomarkers may help in staging presymptomatic AD and optimise clinical trial inclusion. Further work is needed to assess how these findings generalise to non-monogenic AD.