Journal of Alzheimer's Disease

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.

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.

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: The Centiloid (CL) scale standardizes global amyloid PET quantification and is widely used to define amyloid positivity. As a global summary measure, however, CL may not fully reflect the regional distribution of amyloid deposition, which can carry additional prognostic information about the rate of cognitive decline. Objective: To develop and externally validate a fixed, regional amyloid PET composite score that complements CL for predicting cognitive decline in Alzheimer's disease. Methods: The Regional Amyloid PET Score (RAPS) was derived from 82 FreeSurfer regions using machine learning with bootstrap stability selection to predict the rate of change in CDR-Sum of Boxes (CDR-SB) in 433 amyloid-positive ADNI [18F]florbetapir participants. The fixed nine-region weights were applied without retraining in a cross-tracer ADNI [18F]florbetaben subset (N = 71; largely overlapping the discovery participants) and two external validation cohorts, NACC SCAN (N = 1531; four tracers) and OASIS-3 (N = 428). Results: RAPS comprised nine regions. In ADNI, RAPS correlated more strongly with CDR-SB slope than CL and showed higher discrimination of rapid decliners (AUC 0.813 vs 0.713). Performance was directionally consistent across validation cohorts; in NACC SCAN, RAPS and CL independently predicted clinical progression. Cross-cohort meta-analysis of the three independent cohorts supported incremental discrimination beyond CL (pooled {Delta}AUC +0.066; I2 = 0%). Conclusions: RAPS, a fixed regional amyloid PET-derived score, may complement CL for prognostic stratification in Alzheimer's disease research.

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.

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.

Background Understanding the mechanisms underlying brain aging and age-related pathological changes is essential for advancing brain health research. Our group previously developed a mechanistic mathematical model of healthy brain, Chamberland et al. (2024) that integrates key biological processes involved in normal aging, from which Alzheimer's disease (AD) related changes may emerge naturally. Objectives To characterize and validate this brain model by evaluating its sensitivity, calibrating its parameters, and assessing generalizability in independent populations. Methods The model represents the evolution of key biological processes associated with brain aging, including amyloid beta (A{beta}), tau pathologies, neuroinflammation, and neuronal death. After identifying the 30 most influential parameters, we calibrated the model using cognitively normal (CN) participants from the AD Neuroimaging Initiative (ADNI) database (n = 211) by minimizing a loss function composed of three outcomes (AB) plaques, tau tangles, and neuronal density). The calibrated model was then applied to the UK Biobank cohort (n = 35,899) of normal controls (aged 44-82 years). The effects of sex and APOE were evaluated using stratified simulations. Results Parameter calibration significantly reduced the prediction errors for A{beta} and tau. Neuronal density predictions showed strong agreement in the UK Biobank cohort. The variance decomposition identified APOE status as a major contributor to variability in A{beta}. Conclusion Our validated brain health model links mechanistic pathways with population data and reproduces neuronal density patterns in an independent cohort. These findings support its use as a framework for studying brain aging and investigating how Alzheimer's disease related pathological changes may emerge with aging.

Background The time trend in long-term survival after a stroke is to some extent unknow due to (relatively) short follow up periods in available data. The objective of this study is to identify and quantify differences in long-term stroke survival in Sweden between men and women and patients with different attained educational levels, comparing two time-periods, 2000-2009 and 2010-2022. Methods This study employs total population Swedish register data pertaining to hospital-based care and mortality due to stroke for the period 2000-2022 in order to estimate survival (all-cause mortality) after ischaemic and haemorrhagic stroke, respectively, and pertaining to attained educational level. Kaplan-Meier survival functions are estimated stratifying for time-period, sex and educational level. Cox regressions are employed to quantify mortality hazard ratios between the strata. Age is taken into account in complementary analyses (supplement). Results Taking only time-period (2000-2009 vs 2010-2022) into account resulted in significantly higher survival in the second period for ischaemic stroke patients (HR: 0.84; 95% CI: 0.83-0.84), while no significant difference could be detected for haemorrhagic stroke. Stratifying for sex showed that men gained more than women in terms of reduced mortality hazard rate between the periods. Further stratifying by educational level and estimating survival separately for men and women showed that, for both men and women, patients with the lowest education were relatively worse off (compared to patients with higher education) in the second period. Further analyses, taking age into account, reversed the relative hazard ratio between men and women, but corroborated the result that low education is associated with poorer outcome than high education. Conclusions The results suggest that there are considerable differences in expected long-term survival after stroke between the sexes, but that this may be due to differences in age between the sexes at the time of stroke. Moreover, lower educational level is significantly associated with lower long-time survival.

INTRODUCTION: Biomarkers for monitoring disease activity and treatment response in peripheral neuropathies remain limited. Big tau, a high-molecular-weight isoform of tau, is predominantly expressed in the peripheral nervous system (PNS). We investigated serum levels of big tau, brain-derived tau (BD-tau), and neurofilament light chain (NfL) in peripheral neuropathies, multiple sclerosis (MS), Alzheimer disease (AD), and healthy controls (HC). METHODS: Ultra-sensitive blood-based assays run on an HD-X Single Molecule Array analyser (Quanterix) were used to measure big tau and BD-tau in serum from patients with Guillain-Barr&eacute syndrome (GBS, n=81), Miller Fisher syndrome (MFS, n=20), Charcot-Marie-Tooth disease (CMT, n=102), chronic inflammatory demyelinating polyneuropathy (CIDP, n=43), MS (n=159), AD (n=20), and HC (n=41). NfL was measured in patients with neuropathies using an SR-X Single Molecule Array analyser (Quanterix). RESULTS: Serum big tau levels were higher in GBS than in AD (11.4 vs 2.4 pg/mL, p<0.0001) and MS (11.4 vs 9.0 pg/mL, p=0.01), and similar to CIDP and CMT. Contrarily, serum BD-tau levels in GBS were higher than in CIDP (3.0 vs 2.3 pg/mL, p=0.006) and MS (3.0 vs 1.7 pg/mL, p<0.0001), but similar to CMT, and lower than in AD (3.0 vs 9.8 pg/mL, p<0.0001). Serum NfL levels were higher in GBS than in CIDP (32.5 vs 13.0 pg/mL, p=0.0002), CMT (32.5 vs 12.3 pg/mL, p<0.0001), and HC (32.5 vs 7.6 pg/mL, p<0.0001). Compared with GBS, MFS patients showed higher BD-tau (12.7 vs 3.0 pg/mL, p=0.003), lower big tau (5.4 vs 11.4 pg/mL, p=0.002), and higher NfL levels, although the latter did not reach statistical significance (118.3 vs 32.5 pg/mL, p=0.16). The NfL/big tau ratio was significantly higher in MFS than in GBS, CIDP, and CMT. In GBS, BD-tau correlated with early clinical severity (MRC at 1 week; I-RODS at 4 weeks; maximum GBS-DS and GBS-DS at 4 weeks), whereas neither tau biomarker showed long-term clinical correlations. Higher BD-tau and big tau levels were associated with the need for mechanical ventilation (BD-tau: 8.6 vs 2.9 pg/mL, p=0.019; big tau: 19.7 vs 10.7 pg/mL, p=0.007), while higher BD-tau levels were associated with mortality (10.9 vs 2.9 pg/mL, p=0.003). CONCLUSIONS: Higher big tau levels in peripheral neuropathies than in CNS diseases support its role as a PNS-specific biomarker. In MFS, increased serum BD-tau, reduced big tau, and an elevated NfL/big tau ratio suggest CNS involvement with relative preservation of the PNS.

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.

Abstract: Objective: Post-traumatic epilepsy (PTE) is a common sequela of traumatic brain injury (TBI). Research indicates that individuals with PTE tend to experience greater cognitive difficulties compared to those with TBI alone. However, it is plausible that a distinct cognitive profile exists that distinguishes between TBI cases with and without PTE. We aimed to identify longitudinal changes in cognitive measures among TBI patients to better assess the changes associated with developing PTE. Setting: Outpatient. Participants: Prospective subjects who had suffered TBI within 6 months post-injury (TBI-6M, n=32), retrospective subjects with pre-existing PTE diagnoses (PTE, n=20), and healthy control subjects (HC, n=41). Design: We examined cognitive performance for TBI patients within 6 months post-injury, then again within 12 months (TBI-12M, n=26), and within 18-months (TBI-18M, n=25), and compared this with cognitive performance among HC and PTE. Main Measures: Cognitive tests administered yielded 15 test components for analysis. We utilized linear mixed effects modeling to examine cohort-level differences cognitive function. Results: 11/15 tests showed a significant performance deficit in the PTE subjects compared to HC. TBI-6M was not significantly different from the PTE subjects; with time, 9/15 tests showed some degree of recovery in TBI subjects. Tests for information processing speed/working memory and executive function showed strong recovery (TBI-6M vs. TBI-18M, SDMT written: p<0.0001, SDMT oral and COWAT: p<0.001). Tests for visual attention/working memory also showed a smaller but significant recovery (TBI-18M vs. PTE, p<0.05). By contrast, tests for verbal memory [HVLT-R Delayed Recall] showed chronic impairment in TBI (TBI-18M vs HC, p<0.0001). TBI subjects generally trend towards recovery in cognitive performance post-TBI. Conclusions: Information processing speed/working memory are strong indicators for TBI recovery, while auditory learning/memory shows chronic impairment. The stagnation of recovery in cognitive domains typically characterized by robust recovery may correlate with an elevated risk of developing PTE.

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.

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.

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.

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.

Background Phenotypic age acceleration (PhenoAgeAccel), derived from PhenoAge, and MetaboHealth are composite exposures of biological ageing and metabolic health associated with dementia-related outcomes. Whether these associations are causal and reflect the exposures, constituent biomarkers, or both remains unclear. Methods This study included UK Biobank participants of White British genetic ancestry. MetaboHealth was derived from nuclear magnetic resonance (NMR) metabolomics and PhenoAgeAccel from clinical biomarkers and chronological age. Genome-wide association studies (GWAS) were conducted for MetaboHealth (n=272,568) and PhenoAgeAccel (n=274,077). Independent genome-wide significant variants were used as genetic instruments in two-sample Mendelian randomisation (MR) with FinnGen all-cause dementia summary statistics. Inverse-variance weighting was the primary MR method. Causal network analysis estimated relationships among constituent biomarkers and dementia. Findings GWAS identified 126 and 141 independent genome-wide significant variants for MetaboHealth and PhenoAgeAccel, of which 109 and 141 were retained as genetic instruments. MR found no evidence of a causal effect of genetically predicted MetaboHealth (per unit: OR 0.83, 95% CI 0.49-1.42; p=0.51) or PhenoAgeAccel (per year: OR 0.99, 95% CI 0.95-1.02; p=0.44) on all-cause dementia, with consistent findings across sensitivity analyses and robust MR methods. Lower lymphocyte percentage and higher NMR-derived glucose had direct relationships with dementia in the joint constituent-biomarker network. Interpretation MR provided no evidence that either composite exposure causally influenced dementia. The network prioritised lymphocyte percentage and NMR-derived glucose, supporting examination of composite exposures alongside their constituent biomarkers. Funding NIHR, UKRI, MRC, UK Dementia Research Institute, Innovate UK, and European Union. Full funding details are provided in the acknowledgements.

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: Evidence regarding delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH) remains sparse. We aimed to identify its predictors and occurrence and evaluate its role in ischemic stroke and functional outcome under treatment with interventional rescue therapy (IRT). Methods: This retrospective single-center study included 628 adults with aSAH from 2014?2023. The primary endpoint was occurrence of refractory DCI (= refractory despite induced hypertension) treated with at least one IRT. Multivariable models evaluated refractory DCI, new ischemic stroke, and poor functional outcome (mRS 3?6) at 6?12 months. Results: Among 628 included patients, 61 who died within 3 days were excluded from DCI analysis; 166/567 (29%) developed refractory DCI. Younger age (OR = 0.98; P<0.001), female sex (OR = 0.57; P=0.007), and higher WFNS grade (OR = 1.18; P=0.011) were independently associated with refractory DCI. Earlier first IRT was associated with longer DCI duration (IRR = 0.88; P<0.001) and more required IRTs (IRR = 0.91; P<0.001). IRT was performed later than day 14 in 29/166 patients (17.5%); none was older than 70 years. Refractory DCI was associated with new ischemic stroke (OR = 4.68; P<0.001) and poor functional outcome (OR = 2.37; P<0.001); earlier first IRT was associated with poor outcome within the refractory DCI subgroup (OR = 0.86; P=0.03). Outcomes after 1?2 IRTs did not differ from those without refractory DCI (P=0.4), whereas ?3 IRTs were associated with poor outcome (P=0.04). Conclusions: Refractory DCI affected 29% of aSAH patients, predominantly younger women and patients with poorer initial neurological status, and extended beyond day 14 in nearly 20% of affected patients, none of whom was older than 70 years. Refractory DCI and earlier onset were associated with poorer radiological and functional outcomes. The absence of a detected outcome difference after 1?2 IRTs suggests that favorable outcomes may remain achievable despite refractory DCI.

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: Hippocampal sclerosis (HS) is a common cause of drug-resistant focal epilepsy (DRFE) and amenable to neurosurgical treatment. Detection relies on MRI but can be challenging. 7 Tesla (T) ultra-high field MRI and automated MRI post-processing tools have independently been shown to improve radiological diagnosis of HS. However, combining these approaches remains underexplored. This study evaluated whether AID-HS, a tool for HS detection developed using 3T MRI, generalises to 7T MRI data. Methods: We collated a dataset of paired 3T and 7T T1-weighted MRI from four epilepsy centres, including 23 patients with HS, 39 healthy controls, and 23 individuals with focal cortical dysplasia as disease controls. Histopathology served as the gold standard for defining HS where available (n=7), otherwise radiological findings (n=16). AID-HS was applied to images acquired at both field strengths, and sensitivity and specificity for detection and lateralisation of HS were compared. Additionally, agreement of hippocampal features across 3T and 7T was evaluated. Results: We found no evidence of a difference in performance of AID-HS between 3T and 7T. Sensitivity for detection of unilateral HS was 63% (12/19) at 3T and 68% (13/19) at 7T (McNemar's exact test p=1.0). Specificity in controls was 97% (60/62) at 3T and 100% (62/62) at 7T (p=0.5). Bilateral HS was correctly flagged in 3 of 4 cases using feature-based criteria, with high specificity in controls. Quantitative hippocampal features showed moderate to good agreement across field strengths (ICC 0.70 to 0.98), with small differences observed for volume and thickness estimates. Conclusion: AID-HS provides robust detection and lateralisation of HS across multiple 7T MRI centres, highlighting its potential to enhance lesion detection. Future work is needed to investigate whether models trained on 7T data can leverage the improved image quality for further gains in HS detection performance.