Journal of Alzheimer’s Disease

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

Early identification of Alzheimer's disease and related dementias (ADRD) remains challenging despite its importance for timely intervention, management of modifiable risk factors, and care planning. We developed and evaluated ADRD onset prediction models using longitudinal electronic health records (EHRs) from the All of Us Research Program at clinically meaningful lead times of 6, 12, 24, and 36 months before diagnosis, benchmarking interpretable count-based representations against four publicly available pretrained clinical foundation models (CLMBR-T, GPT-style, LLaMA-style, and Mamba) across multiple ADRD phenotype definitions. Count-based models consistently achieved the highest discrimination and calibration across all cohorts and prediction horizons. Predictive performance declined with increasing lead time for all approaches; however, the performance gap between count-based and pretrained representations progressively narrowed, with foundation models achieving comparable AUROC of 0.719 (compared to the AUROC of 0.738 of count-based model) at the 36-month horizon while providing higher sensitivity and F1 scores under a fixed operating threshold. External validation with zero-shot evaluation on UChicago EHRs exhibited limited generalizability for count-based and pretrained clinical foundation model based representations. These findings demonstrate that transparent count-based EHR representations remain the strongest overall approach for ADRD onset prediction, while pretrained clinical foundation models provide complementary advantages for long-term risk identification and establish a benchmark for evaluating transferable clinical representations in temporal ADRD risk prediction.

Despite extensive knowledge of the progressive sequence of cognitive and functional deficits in Alzheimer's Disease (AD), the impact of neurodegeneration on the conscious experience of patients remains largely unexplored. Understanding how the content of consciousness, particularly perceptual awareness, changes with the progression of AD is crucial to enable meaningful person-centred care. This is especially important in severe AD when impairments in language and other cognitive domains mean people are unable to report their experiences. We investigated whether electrophysiological (EEG) and fMRI signatures of perceptual awareness described in healthy older people are present in people with mild-moderate and severe AD using two "no-report" paradigms. Firstly, a visual masking paradigm examined visual awareness negativity (VAN) and late positive (LP) electrophysiological responses and activation in visual cortex and fronto-parietal regions that are characteristically associated with conscious perception of faces; and second, a complex audio-visual (movie) task examined activation in fronto-parietal networks previously associated with perceptual awareness. In healthy older controls we found cortical responses characteristic of awareness in both EEG and fMRI modalities, with VAN and LP markers and widespread occipital, fusiform face area and fronto-parietal activation. In people with mild-moderate AD, there were significant reductions in VAN and LP markers and reduced fronto-parietal activation. In participants with severe AD, who were behaviourally minimally responsive, there was only limited evidence of presence of frontoparietal markers of perceptual awareness, however this may reflect attentional and task insensitivity in people with advanced dementia. These results demonstrate that the brain mechanisms associated with perceptual awareness become increasingly impaired with progression of AD. Specifically, involvement of frontoparietal networks is reduced in AD, which may reflect reduced higher-level awareness. This suggests AD should be considered a disorder of consciousness and should motivate further investigation into the dimensions of awareness affected by the disorder with implications for treatment and management of people with dementia.

Mitochondria are central hubs for cellular metabolism and mitochondrial dysfunction is a hallmark of many chronic diseases. Consequently, changes in mitochondrial DNA copy number (mtDNA-CN), the number of mtDNA genomes per cell or tissue sample, are associated with diseases ranging from cancer and obesity to psoriasis and all-cause mortality. MtDNA-CN especially holds promise as a biomarker for neurodegenerative diseases, but whether and how mtDNA-CN changes with neurodegeneration is controversial. Here, we performed a systematic review and meta-analysis of 76 studies including 156 comparisons of mtDNA-CN in populations with or without a neurodegenerative disease to identify overall trends and potential moderators that explain variation among studies. Overall, mtDNA-CN was not statistically different with neurodegeneration, but heterogeneity among studies was extreme (I2 = 99.5%). The diagnosed disease explained the most variation. For example, Alzheimer's patients showed a 21% decrease in mtDNA-CN, but there was no change in mtDNA-CN with Parkinson's disease. Decreases in mtDNA-CN during neurodegeneration were also more extreme at older ages. Surprisingly, the tissue sampled for mtDNA-CN was not particularly influential, except for certain diseases. Studies published in earlier years also showed more extreme decreases in mtDNA-CN with neurodegeneration. Excessive heterogeneity persisted even after accounting for all moderators and their interactions (I2 = 85.7%). We conclude that the general perception of decreased mtDNA-CN with neurodegeneration is a vast oversimplification that may stem from legacy effects of early studies. However, mtDNA levels offer great promise as biomarkers for neurodegeneration, other diseases, and general health metrics, assuming appropriate complications can be considered.

Introduction Guatemala is the most populous country in Central America and a setting with unique opportunities for aging research. Approximately 40% of Guatemala's population is Indigenous Maya, who together speak 22 Mayan languages. Currently, there is no population-based aging study in Guatemala and few aging studies in Latin America among Indigenous populations. The Longitudinal Study of Aging in Guatemala (ELEGUA) aims to address these gaps by developing a nationally representative, population-based, longitudinal aging study modeled on the Health and Retirement Study and the Harmonized Cognitive Assessment Protocol, adapted to the cultural and linguistic context of Guatemala. The objective of this protocol is to describe the rationale and design of the ELEGUA pilot survey. Methods and analysis The ELEGUA pilot was a cross-sectional household survey of adults aged 40 years or older in Tecpan, Guatemala. Tecpan was chosen because its diverse population facilitated testing of study procedures in both Spanish and Kaqchikel, a common Mayan language. The survey included up to 600 households sampled using a multistage stratified cluster design. Within each household, one individual aged 40 years or older was selected, with oversampling of adults aged 55 years or older. This respondent completed a comprehensive questionnaire, including detailed cognitive tests, and provided physical measurements and a venous blood sample. Household respondents provided information on household economics and family structure, and an informant reported on the individual respondent's cognitive function. Data were collected using a computer-assisted personal interviewing system. Planned analyses include survey-weighted descriptive statistics and psychometric evaluation of the cognitive assessments. Ethics and dissemination Ethics approval was obtained from the ethics committees of the Institute of Nutrition of Central America and Panama, Maya Health Alliance, and the University of Michigan. Results will be disseminated through publications in peer-reviewed journals and presentations to local, national, and international audiences.

Background Fluid biomarkers enable the demonstration of the biological effects of novel therapies in Alzheimers disease (AD). However, longitudinal biomarker data are sparse and sample size calculations for fluid biomarkers are often lacking. Here, we provided longitudinal CSF and plasma AD biomarkers measured in samples collected in a placebo arm in a 1.5-year phase 2b trial, allowing us to study natural trajectories, required sample sizes and heterogeneity in early AD clinical trials. Methods We studied individuals from the placebo group (MCI due to AD (n=65) and AD dementia (n=41)) of the T-817MA trial (NCT04191486) with positive CSF AD biomarkers (mean age=69(7) years, Female=63%). Longitudinal biomarker changes in CSF (A{beta}42, A{beta}40, A{beta}42/40, pTau181, pTau217, NFL, tTau, YKL40, NRGN, ABL1, CHIT1, CLEC5A, ITGB2, MMP10, SDC4, SPON2, THBD) and plasma biomarkers (A{beta}42, A{beta}40, A{beta}42/40, pTau181, pTau217, NFL, GFAP) were analyzed with linear mixed-effect models. Required sample size estimates for predefined treatment effects were generated. Lastly, we investigated the influence of between person variability in biomarker change by simulating a randomized clinical trial (1:1) 10000 times, and assessed the group differences at 1.5 years. Findings Fourteen biomarkers changed over time, with the largest annual changes observed for plasma pTau217 (+9.8%), CSF MMP10 (+7.1%), and CSF NFL (+6.9%), and CSF A{beta}40 by (-4.0%), CSF pTau217 (-3.0%), and CSF NRGN (-2.5%). To show a 30% change, similar to biomarker effects of approved AD drugs, almost all markers required less than 45 patients per trial arm. To reach normalized levels, established CSF markers required lower sample sizes than plasma markers. The effects of heterogeneity over time were approximately twice as large in plasma compared to CSF. Interpretation These findings offer insights into the biomarker trajectories and power in early AD, supporting more informed endpoint selection and forming a frame of reference for the interpretation of treatment effects in clinical trials.

Children and adolescents with hearing loss frequently encounter reduced auditory access and delayed language development, factors that may influence the maturation of executive functions. This study examined developmental differences in planning, a core executive function, in 98 children and adolescents with hearing loss or normal hearing aged 7 to18 years using the Tower of London task. Compared to normal hearing peers, participants with hearing loss made more unnecessary moves and rule violations and initiated problem-solving more rapidly, suggesting reduced preplanning efficiency and increased impulsivity. These group differences were most pronounced in adolescents, who showed faster initiation and greater movement inefficiency than age-matched normal hearing participants. Within the hearing loss group, adolescents displayed higher accuracy and longer initiation times than children, reflecting developmental improvements despite persistent gaps relative to hearing peers. Language development age did not alter the main effects. Findings indicate that reduced early auditory and language access may contribute to differences in planning development, highlighting the need for targeted executive functions support in educational and clinical settings for youth with hearing loss.

BACKGROUND People with type 2 diabetes mellitus (T2DM) are at higher risk of cerebral small vessel disease and left ventricular hypertrophy (LVH), potentially contributing to cognitive decline and dementia. We aimed to describe brain volume and cognitive trajectories over 2 years in a cohort of people with T2DM and to determine whether LVH causes increased brain atrophy and cognitive decline. METHODS Diabetes and Dementia (D2) study is a multicentre observational cohort study in Melbourne, Australia. Participants aged >50 years were recruited via 2 hospital outpatient clinics, 3 private clinics, and study advertisements. Participants with pre-existing cognitive impairment, life-limiting medical illness, and severe chronic renal impairment were excluded. Participants attended study visits for brain MRI, transthoracic echocardiography (TTE), and cognitive testing at baseline and 2 years. The exposure was LVH determined on baseline TTE. Pre-specified outcomes were total brain volume (TBV) change and cognitive decline (z-score change?-1 in any cognitive domain) over 2 years. Regression analyses examined associations between baseline variables and outcomes. A causal inference approach was utilized using inverse probability of treatment weighting to standardize for confounding covariates, excluding participants for non-positivity on age and baseline TBV. RESULTS Participants were recruited 20May2016 to 20March2020: 2378 screened, 702 eligible, 196 consented, 150 baseline and 123 2-year assessments with complete MRI, TTE, and cognitive data (17.4% attrition). At baseline, LVH was associated with female sex, older age, lower educational attainment, lower mood, hypertension, obesity, beta-blocker use, and smaller TBV. Participants with baseline cognitive impairment exhibited greater brain atrophy. Lower educational attainment, hypertension, and lower baseline cognitive scores were associated with cognitive decline. Causal inference analysis included 62 participants with no LVH (20(32%) women; mean [SD]=66.9[5.9] years), and 31 with LVH (17(55%) women, 67.4[5.4] years). LVH caused lower TBV change: standardized mean difference (95% CI) 6.3 (0.1, 12.5) cm3, P=.048. LVH had no effect on cognitive decline. CONCLUSIONS Brain atrophy and cognitive decline were associated with baseline cognitive impairment. LVH caused less brain atrophy and cognitive decline in people with T2DM. We conclude that guideline-directed LVH therapies such as beta-blockers have both cardioprotective (remodelling) and neuroprotective effects. TRIAL REGISTRATION ACTRN12616000546459 UTN: U1111-1181-6659

Background: Plasma phosphorylated tau at threonine 217 (p-Tau217) is a leading blood-based biomarker for Alzheimer's disease (AD). Robust analytical characterization on high-throughput platforms is essential for research use and clinical translation. Objective: To evaluate the analytical performance of an automated plasma p-Tau217 immunoassay and characterize its discrimination of PET-defined amyloid status. Methods: We performed analytical validation of the Access Research Use Only (RUO) plasma p-Tau217 immunoassay on the Beckman Coulter DxI 9000 Access Immunoassay Analyzer and evaluated biomarker discrimination of PET-defined amyloid pathology in a subset of the Bio-Hermes-001 cohort spanning the symptomatic cognitive continuum (mild cognitive impairment or mild AD dementia; cognitively unimpaired participants excluded; n = 449). Analytical precision, sensitivity, linearity, specificity, interference, and sample stability were assessed per Clinical and Laboratory Standards Institute guidelines. Discrimination of PET-defined amyloid status was evaluated using receiver operating characteristic curve and indeterminate zone analyses. Results: The assay demonstrated high precision (within-laboratory CV </=7.1%), excellent sensitivity (limit of detection 0.018-0.021 pg/mL), linearity across the analytical measuring range (R-squared > 0.99), strong epitope specificity (</=1.0% cross-reactivity with other tau phosphoisoforms), and minimal interference from over 60 endogenous and exogenous substances. In 449 research participants plasma p-Tau217 showed strong discrimination between amyloid-positive and amyloid-negative groups (AUC 0.881; 95% CI 0.846-0.915). Application of indeterminate zones systematically improved classification metrics at the cost of fewer definitive classifications. Conclusions: These findings support the Access p-Tau217 (RUO) assay as a robust, high-throughput assay for plasma biomarker-based discrimination of PET-defined amyloid pathology in AD applications.

Bayesian borrowing of external information can improve trial efficiency, particularly in pediatric and rare disease settings where patient populations are limited, but may introduce bias and inflate the Type~I error rate when the trial differs from external studies. Recent U.S. Food and Drug Administration (FDA) draft Bayesian guidance emphasizes careful evaluation of external information, prior specification, and assessment of operating characteristics. This paper compares three meta-analytic-predictive (MAP)-based methods for Bayesian borrowing: the MAP prior, robust MAP (RMAP) prior, and self-adapting mixture (SAM) prior. An adaptive platform trial design in Rett syndrome is used as a case study. Simulation studies evaluate frequentist operating characteristics under varying prior--data conflict, between-study heterogeneity, treatment effects, and clinically significant differences (CSDs) for the SAM prior. The MAP prior achieved the greatest efficiency when external and current data were compatible but exhibited the largest bias under substantial prior--data conflict. The RMAP priors improved robustness through fixed robust-component weights, whereas the SAM prior adaptively adjusted borrowing and was less sensitive to prior--data conflict while retaining efficiency gains when the data were compatible. Although the CSD influenced the degree of adaptive borrowing, as reflected by effective sample size, it had only a modest impact on frequentist operating characteristics. Sensitivity analyses using a skeptical robust component yielded similar qualitative conclusions, while accentuating the differences between the MAP and RMAP priors. These findings provide guidance for evaluating and selecting MAP-based borrowing strategies before trial implementation, particularly in rare disease settings, consistent with current FDA recommendations.

We propose two new tests to detect drug effects (DE) in trials of one to very few patients followed during two periods (before and after initiation of a treatment). Both methods use longitudinal natural history data to inform the estimation of each patient's DE. The first method uses a non linear mixed effect model (NLMEM) reflecting an expected natural history with a hypothetical drug effect, to estimate the Conditional Distribution of the Drug Effect (CDDE). The second method trains a Pareto Depth Analysis (PDA) algorithm, a machine learning based approach based on outlier detection, that we implement using data simulated under the NLMEM. We evaluated the two tests with a simulation study. We used data from the PROSPAX study in Autosomal Recessive Cerebellar Ataxias (ARCAs, to derive a NLMEM for the Scale for the Assessment and Rating of Ataxia score. The CDDE method provided controlled type I error and, in some scenarios, adequate corrected power, though sensitivity analyses showed vulnerability to misspecification. The PDA method demonstrated lower statistical power except with high score precision. These results highlight different strategies for quantifying treatment effects in ultra rare, patient' specific trials. They can inform methodological design for future ARCA precision therapies.

Parkinsons disease (PD) arises through disruption of multiple interconnected cellular processes, but the genetic contributions to these processes may differ across ancestries. We investigated functional convergence among genes harboring pathogenic or likely pathogenic (P/LP) variants and variants of uncertain significance (VUS) in a multicenter Indian cohort recruited through the Genetics of Parkinsons Disease in India Young Onset Parkinsons Disease project (GOPI YOPD). The cohort included 668 participants (463 males 69.3%) with a mean age at motor onset of 39.4+/-8.8 years. P/LP variants and VUS identified through previously reported whole-exome or whole genome sequencing were retained as separate evidential categories. The P/LP-associated gene set comprised 11 unique genes and the VUS associated set comprised 40 unique genes. Separate STRING functional-enrichment analyses evaluated Gene Ontology Biological Process, Molecular Function and Cellular Component terms, KEGG pathways, WikiPathways and STRING local network clusters. Terms meeting a Benjamini Hochberg false discovery rate threshold of <0.05 were organized into eight non-mutually-exclusive ontology/pathway categories. Gene to pathway mappings were subsequently projected to individual participants to estimate pathway representation and examine clinical associations. At least one reportable P/LP variant or VUS was identified in 336/668 participants (50.3%): 35 had a P/LP variant alone, 282 had VUS alone and 19 had a P/LP variant together with VUS in one or more additional genes. The most frequently represented categories were mitochondrial organization (247/336, 73.5%), autophagy related processes (228/336, 67.9%) and regulation of synaptic vesicle transport (201/336, 59.8%). PRKN was the most frequent P/LP-associated gene, occurring in 29/54 P/LP carriers, followed by PLA2G6 and PINK1. Lysosomal transport was represented exclusively by VUS-associated genes, particularly GBA1, VPS13C and LRRK2. Among P/LP carriers, additional VUS in distinct genes were not associated with age at onset (P = 0.81) or family history (52.6% versus 31.4%; P = 0.15). No pathway phenotype association remained significant after correction for multiple testing. Genetic findings in this Indian cohort converged across an interconnected mitochondrial autophagic lysosomal vesicular network, with different contributions from P/LP-associated and VUS associated gene sets. This study provides the first pathway resolved South Asian genetic profile and a framework for comparative studies across populations.

Objective: Cognitive impairment is a common comorbidity among people with epilepsy (PWE) and is associated with disability and reduced quality of life. We characterized the burden of cognitive impairment and identified factors associated with cognitive performance in a large, population-based cohort of PWE living in Northern Peru, a region highly endemic for Taenia solium where neurocysticercosis (NCC) is a common cause of acquired epilepsy. Methods: PWE enrolled in a population-based cohort in Northern Peru between 2007 and 2020 completed the Mini-Mental State Examination (MMSE) at enrollment. Cognitive impairment was defined as an MMSE score <24. Demographic and clinical data, including epilepsy characteristics and NCC status, were collected. Negative binomial regression was used to identify factors associated with the number of MMSE errors. Results: Among 764 participants, the mean MMSE score was 26.4 (SD 4.2), and 16.4% met criteria for cognitive impairment. Memory and attention were the most affected domains. In multivariable analysis, older age and lower educational attainment were independently associated with poorer cognitive performance. Conclusion: In this large, community-based cohort from Northern Peru, approximately 1 in 6 PWE had abnormal global cognition on the MMSE, with memory and attention most affected. These findings underscore the importance of incorporating cognitive evaluation and management into comprehensive epilepsy care, particularly in resource-limited settings where cognitive morbidity may be underrecognized. Given the potential for cognitive difficulties to compound disability and adversely affect quality of life, identifying and addressing cognitive morbidity may be especially important in populations already facing substantial barriers to epilepsy care.

Background and Objectives: Deep sequencing of brain tissue in the research setting has established that mosaic variants are a major cause of malformations of cortical development (MCDs) and epilepsy. However, genetic testing in the clinical setting primarily detects germline variants using clinically accessible samples. We aimed to determine the diagnostic yield and clinical utility of deep sequencing in the clinical setting to identify pathogenic mosaic variants for this population. Methods: We performed a retrospective cohort analysis of individuals at Boston Children's Hospital with MCDs with or without epilepsy who received clinical deep sequencing between September 2017 and February 2026. Demographic, clinical, and genetic testing data were abstracted from the medical record. For individuals without systemic features, we classified brain tissue as an affected tissue sample. For individuals with systemic features, we classified brain or relevant non-brain tissue as affected. The primary outcome was the diagnostic yield of clinical deep sequencing performed using affected vs unaffected tissue samples. The secondary outcome was the clinical utility of genetic diagnoses. Results: Our cohort included 37 individuals (19/37 (51%) female, 18/37 (49%) male) with MCDs, of whom 35/37 (95%) had epilepsy (25 with brain tissue samples available from epilepsy surgery) and 8/37 (22%) had systemic features. Most (35/37 (95%)) had dysplasia phenotypes on MRI and 12/27 (44%) with pathology available had Focal Cortical Dysplasia Type I or II. The diagnostic yield was 53% (17/32; 16 mosaic and 1 germline variant) when clinical deep sequencing was performed using an affected tissue sample vs 0% (0/6) using an unaffected tissue sample (p=0.016). Of the diagnosed cases, 13/17 (76%) had testing performed on brain tissue (1 with systemic features) and 4/17 (24%) on non-brain tissue (3 buccal and 1 duodenal tissue, all with systemic features). All but one diagnosis involved the mTOR pathway. All diagnoses had clinical utility. Discussion: Clinical deep sequencing, when performed using an affected tissue sample, has high diagnostic yield and clinical utility for individuals with MCDs, especially dysplasia phenotypes, and epilepsy. Our findings support implementation of clinical deep sequencing for this population, especially as the genetic diagnoses have implications for emerging precision therapies.

Background: Cardiovascular disease (CVD) disproportionately burdens underserved communities, where social determinants of health (SDOH) perpetuate persistent disparities. Family-based interventions leveraging social support represent a promising yet understudied approach. We describe the rationale, design, and methods of the Skills-based Educational strategies for the Reduction of Vascular Events in Orange County (SERVE OC) RCT and present baseline characteristics of enrolled families. Methods: SERVE OC is a 2-arm RCT of 190 Latino and Vietnamese families (486 individuals) randomized to the family-based intervention or individual self-management. The intervention was grounded in social network theory while employing community engaged strategies. Primary outcomes include achieving ideal cardiovascular health (CVH) defined by AHA Life's Essential 8 (LE8) and systolic blood pressure reduction at 12, 24, and 36 months. Baseline assessments include demographics, LE8, psychosocial factors, food security, and SDOH. Descriptive statistics and regression analyses examined cohort characteristics and associations between SDOH, food security, and LE8. Results: Over 83% of participants had suboptimal LE8 scores. Average adult total LE8 scores were 66.61 {plus minus}11.96, with physical activity as the weakest domain, compared to an average of 76.52{plus minus}10.15 in children. Greater SDOH burden and food security were associated with significantly lower odds of ideal CVH and lower LE8 scores respectively. Conclusions: SERVE OC demonstrates the feasibility of enrolling families in community-engaged RCT targeting CVD disparities in underserved population. Baseline findings confirm substantial CVD risk and SDOH burden underscoring the need for multi-level, culturally tailored interventions. Trials results will inform scalable, family-focused strategies for CVD prevention across the life course. Clinical Trial Registration: URL: https://www.clinicaltrials.gov/; Unique Identifier: NCT05641519.

Objective. To determine the publication rate of abstracts presented at the American Diabetes Association Scientific Sessions and to evaluate the association between statistical significance of study results and subsequent publication. Research Design and Methods. We conducted a retrospective cohort study of abstracts presented at the 2018 American Diabetes Association Scientific Sessions. The primary exposure was study result category (statistically significant vs. non-statistically significant findings), and the primary outcome was publication in an indexed journal within 5 years after conference presentation. Publication status was determined through PubMed/MEDLINE and Scopus searches. Adjusted relative risks (RRs) and 95% CIs were estimated using generalized linear models with Poisson distribution and robust variance. Results. Among 541 included abstracts, 321 (59.3%) were subsequently published in indexed journals. Abstracts reporting statistically significant findings had a higher publication rate than those reporting non-statistically significant findings (61.9% vs. 42.3%; p=0.002). In the adjusted analysis, abstracts with non-statistically significant findings had a lower likelihood of publication compared with those reporting statistically significant findings (adjusted RR 0.71 [95% CI 0.55-0.93]; p=0.013). Conclusions. Approximately four in ten abstracts presented at the ADA Scientific Sessions were not published within 5 years. Abstracts reporting non-statistically significant findings had a lower likelihood of subsequent publication, suggesting persistent publication bias in diabetology research. Future initiatives promoting the interpretation of effect estimates, confidence intervals and clinical relevance, rather than statistical significance alone, may help reduce selective dissemination of evidence

This study aimed to quantify the longitudinal tracking and cross-sectional construct validity of a single-item questionnaire measuring recreational physical activity frequency (RPAF) in the Womens Healthy Ageing Project. At baseline, 474 participants aged 45-55 reported RPAF from 1993 to 2014. Longitudinal tracking of the RPAF item was assessed as a consecutive-wave and baseline-referenced measure using linear weighted kappa (LWK), Spearman correlations, exact agreement and within-one-category agreement. Construct validity in the form of convergent and known-group validity was assessed using the International Physical Activity Questionnaire (IPAQ) leisure activity domains, Short Form 36 physical function (SF-36-PF) subscale, Timed Up and Go (TUG), hand grip strength (HGS) and waist-to-height ratio (WHtR). 474 participants provided baseline RPAF data. Pairwise longitudinal samples ranged from 176 to 459 across the study. Consecutive-wave LWK ranged from 0.38 to 0.49, and Spearman correlations ranged from 0.44 to 0.57. Exact and within-category agreement ranged from 41.4%-50.8% and 72.0%-79.0%. Baseline-referenced LWK ranged from 0.22 to 0.47, with Spearman correlations of 0.29 to 0.56. RPAF correlated with total IPAQ leisure score (rs = 0.60), IPAQ walking score (rs = 0.58), SF-36-PF (rs = 0.33) and TUG score (rs = -0.25). No significant correlation was identified between RPAF, HGS or WhTR. RPAF discriminated known groups for WHO guideline-sufficient activity, SF-36-PF, and TUG fall risk. The RPAF item demonstrated fair-to-moderate agreement in consecutive waves, with weaker baseline-referenced tracking. Cross-sectional validity was highest with total IPAQ leisure activity. The item may provide a pragmatic measure for RPAF in womens cohort studies.

Background: The Boston Criteria v2.0 represent the gold standard for diagnosing Cerebral Amyloid Angiopathy (CAA), but their application is currently precluded in mixed small vessel disease (SVD), where deep and lobar hemorrhages coexist. The aims of this study are: (i) to determine which cerebrospinal fluid (CSF) biomarker (A{beta}42, A{beta}40, A{beta}42/40 ratio) is the best candidate to support the CAA diagnosis; (ii) to define a data-driven cut-off, and (iii) to explore if a biomarker-integrated classification significantly improves the phenotypical concordance with the suspected predominant SVD (CAA vs. arteriosclerosis). Methods: We analyzed data from a retrospective multicenter cohort of patients with suspected CAA, defined as probable CAA (Boston criteria v2.0) but allowing deep hemorrhagic lesions, and with available CSF biomarkers. We visually quantified MRI-visible SVD markers (e.g., cerebral microbleeds [CMB], cortical superficial siderosis [cSS], lacunes) and their association with MRI-visible SVD features. We employed a Gaussian Mixture Model (GMM) to identify a data-driven threshold for amyloid positivity (A+). Then, we compared the prevalence of MRI-visible manifestations of SVD between subgroups applying different frameworks, namely the current MRI-based classification (probable CAA vs. mixed SVD) and a CSF biomarker-integrated classification (A+ vs. A-). Results: We enrolled 121 patients (age: 72 [66-77] years; 60% probable CAA, 40% mixed SVD with suspected CAA). The CSF A{beta}42/40 ratio showed a bimodal distribution and consistent associations with all CAA-specific radiological features. The CSF biomarker-integrated reclassification, particularly using the GMM cut-off, significantly improved the distinction between subgroups regarding CAA- and arteriosclerosis-related MRI features (e.g., cSS presence: probable CAA vs. mixed SVD: aOR=2.84 [95%CI 1.27-6.39], p=0.011; A+ vs. A-: aOR=12.68 [95%CI 4.31-37.32], p<0.001; deep lacunes presence: probable CAA vs. mixed SVD: aOR=0.20 [95%CI 0.08-0.50], p<0.001; A+ vs. A-: aOR=0.04 [95%CI 0.01-0.11], p<0.001). Notably, patients classified as A+ never demonstrated more than four deep CMBs. Discussion: A CSF biomarker-integrated classification may improve the classification of CAA compared with the current MRI-based framework. These findings are cohort-specific and would benefit from further validation, especially with a neuropathological reference. Still, these results support a future transition toward an integrated biological-radiological framework, which may refine in vivo CAA diagnosis, particularly in mixed SVD.

Background: The primary neuroanatomical site of Huntington-s disease (HD) pathology resides in the striatum and its atrophy identifies important disease progression from HD-ISS Stage 0 to Stage 1. Immune-associated proteins may capture variation in HD that is incompletely represented by markers of neuroaxonal injury. Objectives: To determine whether cerebrospinal-fluid myeloperoxidase contributes information about striatal volume loss beyond genetic disease burden and neurofilament light. Methods: Cross-sectional data from 88 persons with HD were analyzed. Cerebrospinal-fluid myeloperoxidase and neurofilament light were measured with a nucleic acid-linked immunosandwich assay. Normalized putamen volume was derived from structural magnetic resonance imaging. Linear regression adjusted for genetic disease burden and sex. Results: Higher neurofilament light was associated with smaller normalized putamen volume (standardized {beta} = -0.322, (P=.0066)). Higher myeloperoxidase was associated with larger normalized putamen volume after adjustment for genetic disease burden, sex, and neurofilament light (standardized {beta} = 0.183, (P=.0386)). Adding myeloperoxidase increased explained variance in striatal loss. Conclusions: Cerebrospinal fluid myeloperoxidase contributed modest incremental information about striatal volume in this cross-sectional sample. Independent longitudinal studies are needed to determine its biological source, temporal behavior, and potential biomarker value. Findings advance efforts to characterize multicomponent biological markers of HD.

Service members with traumatic brain injury are at approximately two- to four-fold higher risk of Alzheimer's disease or related dementias than those without such an injury, with risk increasing with injury severity. The amyloid/tau/neurodegeneration biomarker framework treats amyloid, tau, and neurodegeneration as independent axes but omits astroglial injury, despite evidence that reactive astrogliosis (indexed by glial fibrillary acidic protein, GFAP) must be elevated for cognitive decline to occur in amyloid-positive individuals. Total GFAP immunoassays aggregate intact protein with multiple calpain- and caspase-cleaved proteoforms, blurring the biological signal. We compared a calpain-cleaved GFAP neoepitope, the glial fibrillary acidic protein neoepitope (neoGFAP), against total GFAP across the full traumatic brain injury--mild cognitive impairment--Alzheimer's disease continuum in Veterans using a two-stage plasma-to-cerebrospinal-fluid biomarker approach. A plasma triage gate combining phosphorylated tau 217 and amyloid beta 42 was applied to 367 unique subjects; a cerebrospinal-fluid benchmarking cohort of 57 subjects (controls, chronic blast traumatic brain injury, mild cognitive impairment, and Alzheimer's disease) received head-to-head neoGFAP and total GFAP measurement. In the whole benchmarking cohort, neoGFAP discriminated mild cognitive impairment plus Alzheimer's disease from non-Alzheimer subjects with an area under the receiver-operating-characteristic curve of 0.81 versus 0.73 for total GFAP, a trend-level advantage that did not reach nominal significance. Within the gate-positive, amyloid-committed subset of 23 subjects, neoGFAP dominance became significant by McNemar's exact test (six discordant subjects favored neoGFAP, none the reverse). Across diagnostic contrasts, neoGFAP outperformed total GFAP for Alzheimer's disease versus control and, importantly for Veterans, for mild cognitive impairment versus chronic blast-exposed Veterans without cognitive impairment. In chronic blast injury, neoGFAP was paradoxically depleted relative to controls, consistent with tissue sequestration of aggregated proteoform fragments. Unbiased proteomic profiling confirmed coordinated elevation across astrocytic, neuronal, mitochondrial, and microglial compartments. An exploratory subject-level reclassification improved accuracy from 71.1 percent using plasma alone to 79.5 percent with added cerebrospinal-fluid markers and age. In a same-cohort ProQuantum replication (n=57), CSF neoGFAP preserved its discrimination advantage over total GFAP for MCI+AD versus non-AD (AUROC 0.76 vs 0.72; cross-platform Spearman {rho}=0.84), while plasma neoGFAP achieved AUROC 0.90, comparable to pTau217 (0.92) and exceeding A{beta}42/40 (0.84). In this small sample, neoGFAP is a superior proteoform-resolved diagnostic and prognostic biomarker across the continuum and supports adding an astroglial-proteoform axis to amyloid/tau/neurodegeneration biomarker frameworks in high-risk populations.