Day, Gregory S

Abstract INTRODUCTION Preclinical Alzheimer's disease (AD) can be described relative to biomarker positivity onset time. METHODS We estimated time from amyloid positivity (A+) using sampled iterative local approximation (SILA) in a longitudinal autosomal dominant AD (ADAD) sample ( N = 379) with amyloid positron emission tomography. We compared (1) predicted age at A+ to imputed age, (2) estimated age at A+ to estimated age at symptom onset, and (3) variance in cognitive performance explained. RESULTS Mean error between imputed and SILA‐estimated age at A+ ( N = 26) was 1.15 years. Age at A+ explained 39% of estimated years to symptom onset (EYO) variance. Time from A+ explained 19% of cognitive composite variance and 14% of Clinical Dementia Rating Sum of Boxes CDR‐SB variance; EYO explained 43% and 57%, respectively. DISCUSSION SILA estimates A+ age in ADAD with reasonably good accuracy. SILA‐estimated time from A+ describes the start of pathology, but the time from A+ onset to symptoms is variable in ADAD and better described by EYO. Highlights Amyloid chronicity predicts a 14‐year preclinical AD phase in ADAD. SILA accurately estimates age at A+ (MAE < 2 years). EYO outperforms chronicity in predicting symptom onset. APP mutation carriers show atypical amyloid accumulation. Chronicity models help reveal AD heterogeneity in preclinical stages.

Abstract BACKGROUND Tau‐derived cerebrospinal fluid (CSF) biomarkers correlate with amyloid‐beta (Aβ) plaques or tau tangles in Alzheimer's disease (AD). This study assessed the effects of long‐term anti‐Aβ antibodies on amyloid plaques, tau tangles, and CSF tau species to determine the relationships between them. METHODS A post‐hoc analysis of the DIAN‐TU‐001 trial (NCT01760005) examined 142 participants at risk for dominantly inherited AD randomized to solanezumab ( n = 50), gantenerumab ( n = 52), or placebo ( n = 40). High‐resolution mass spectrometry quantified CSF tau species over four years. RESULTS Phosphorylated tau (p‐tau) species (153, 181, 217, 231) increased early in preclinical AD but were reduced with gantenerumab‐mediated Aβ plaque reduction. Nearly a decade later, MTBR‐tau243 and p‐tau205 increased, showing no association with Aβ reduction, aligning with tau tangle pathology progression. DISCUSSION Initially changing soluble p‐tau species track Aβ plaque reduction, while ptau205 and MTBR‐243 reflect tau tangle pathology, informing different pathways of therapeutic strategies. Highlights p‐tau217 and p‐tau231 correlate with Aβ‐PET and respond to Aβ‐plaque lowering therapies. Aβ immunotherapy trials support a direct link between p‐tau changes and Aβ plaques Gantenerumab reduces Aβ plaques but does not affect tau NFT‐related biomarkers. Blood‐based p‐tau217 assays may provide a non‐invasive tool to monitor Aβ therapies. MTBR‐tau243 strongly correlates with tau PET and tracks NFT pathology progression. Further studies are needed to validate tau biomarkers for tracking NFT‐targeting therapies.

Objectives Directly compare the brain glucose patterns seen with [F‐18] fluorodeoxyglucose (FDG) positron emission tomography (PET) between 2 genetically determined forms of Alzheimer's disease: Down syndrome (DS) and autosomal dominant Alzheimer's disease (ADAD). Methods Cross‐sectional analyses of FDG were performed in individuals with DS (n = 76) from the Alzheimer Biomarker Consortium‐Down Syndrome (ABC‐DS), ADAD (n = 297), and neurotypical familial controls (n = 188) from the Dominantly Inherited Alzheimer Network (DIAN). Within‐group linear regression models and generalized additive models were performed for select regional FDG uptake measures (isthmus cingulate and inferior parietal, precuneus, middle temporal gyrus, and precentral gyrus). Age, sex, apolipoprotein (APOE) ε4 carrier status, and cortical amyloid burden were included within these analyses. Results Even 20 years before expected onset of clinical symptoms, FDG uptake was lower for DS compared to neurotypical familial controls ( p < 0.01). ADAD baseline FDG was similar to neurotypical familial controls until 7 years before expected symptom onset. Both symptomatic individuals with DS and ADAD had lower FDG compared to neurotypical familial controls ( p < 0.01). A higher amyloid burden was associated with lower FDG for both genetic forms, with similar rates of decline in FDG uptake for DS and ADAD who were amyloid positive. Interpretation Brain glucose metabolism is substantially lower for people with DS, even in individuals who are cognitively stable. The patterns of FDG decline are distinct in these 2 genetically determined forms of AD. The diagnostic utility of FDG‐PET is specific to the genetic form of AD. ANN NEUROL 2025;98:1237–1248

Objective To establish a framework for validating candidate biomarkers of cerebral small vessel diseases (SVD) associated with cognitive impairment and characterize individuals enrolled by the MarkVCID2 consortium under this framework. Methods Participants age 60 to 90 years were enrolled across 17 MarkVCID2 sites. Recruitment was targeted to enrich in cognitive symptoms (mild dementia, mild cognitive impairment, subjective cognitive decline), defined risk factors (diabetes mellitus, advanced hypertension), and Black/African American, White, and Hispanic/Latino subgroups. Enrolled participants underwent baseline visits that included cognitive testing, multimodal magnetic resonance imaging (MRI), and biofluid collection. Provisional risk for SVD‐related cognitive decline was estimated primarily by baseline cognitive symptoms plus SVD risk factors. Adjudicated risk status was estimated by cognitive symptoms plus presence of moderate‐to‐severe white matter hyperintensities, microbleeds, or lacunes on baseline MRI. Results MarkVCID2 enrolled 1883 individuals age 73.4 ± 7.5 years, 65.0% female, 24.2% Hispanic, and 27.1% non‐Hispanic Black. Among enrollees, 44.8% were provisionally designated high‐risk. After baseline MRI, 48.5% were categorized as adjudicated high‐risk status, with substantial recategorization both from low‐ to high‐risk (primarily because of MRI lesions without SVD risk factors) and high‐ to low‐risk (primarily suspected cognitive impairment at screening not confirmed by baseline testing). Interpretation MarkVCID2 baseline data indicate successful enrollment of diverse individuals enriched in factors associated with SVD‐related cognitive decline. Changes over 3 years of longitudinal follow‐up will be analyzed to validate the candidate biomarkers for 2 projected contexts of use: subject selection (identifying likelihood of future SVD progression) and study outcome (efficiently measuring SVD progression). ANN NEUROL 2026;99:449–458

Abstract Objective This study aims to better characterize the long‐term neurological quality of life (QOL) outcomes (using the Neuro‐QOL scale) in survivors of new onset refractory status epilepticus (NORSE), including its subtype febrile infection‐related epilepsy syndrome (FIRES), and provide guidance for psychological and social support strategies. Methods Utilizing data from a multicenter prospective study of NORSE/FIRES led by Yale University, we enrolled patients who completed the validated, patient‐reported Neuro‐QOL scale at least once at 3–6 months ( n = 37), 12 months ( n = 29), 24 months ( n = 23), or ≥36 months ( n = 9) following discharge. The Neuro‐QOL scale assesses physical, mental, and social health in patients with neurological disorders. QOL impairment (QOL‐I) scores were calculated, with higher scores indicating greater impairment. T ‐scores enabled comparisons with reference populations. Results In adults, median QOL‐I improved from 44.1% at 3–6 months to 37.6% at 36+ months. Paired analysis showed significant improvement in QOL‐I between 3–6 and 24 months ( p = .016), with specific improvements in communication, satisfaction with social roles, fatigue, and mobility. Greater improvement was also observed for participation in social roles (5.5‐point T ‐score gain) compared to the reference population, suggesting meaningful change. A gradual improvement in overall QOL‐I scores was also observed in pediatric participants, despite a modest sample size ( n = 5 with data at 3–6 and 12 months). Measures of fatigue and anxiety persisted in adults, and cognitive difficulties persisted in both adults and children. In adults, longer status epilepticus duration and intensive care unit stay were associated with poorer QOL. Additionally, a higher number of antiseizure medications was associated with more depression, cognitive impairments, and perceived stigma. Significance These findings highlight the potential for recovery following an acute episode of NORSE, although many patients continue to face challenges requiring ongoing support, and the clinical meaning of the reported QOL improvement remains unclear. Furthermore, the findings underscore the importance of strategic multidisciplinary support systems in the years following discharge.

ABSTRACT Objectives To investigate the value of cytokine, chemokine, and neurofilament light chain (NfL) concentrations in predicting relapse risk, chronic epilepsy, and functional impairment in LGI1 autoimmune encephalitis (AE). Methods Cytokines/chemokines (IL‐1‐beta, IL‐2, IL‐4, IL‐5, IL‐6, IL‐8/CXCL8, IL‐10, IL‐12p70, IL‐13, IL‐17A, GM‐CSF, TNF‐alpha, IFN‐gamma, CXCL9, CXCL10, CXCL13, BAFF) and NfL concentrations were measured in CSF and paired serum from LGI1‐AE patients evaluated at Mayo Clinic (01/2015–02/2024), using a multiplex immunoassay system (ELLA, Bio‐Techne) and correlated with clinical outcomes. A laboratory‐based cohort of LGI1‐IgG‐positive patients and control cohorts, including patients with mixed non‐inflammatory disorders (MNID), Alzheimer's disease (AD), and temporal lobe epilepsy (TLE) were analyzed. Results Forty‐four patients with LGI1‐AE were included; 29 (66%) were male, with a median age of 68.5 years (range, 8–85). Median time from symptom onset to CSF sampling was eight months (IQR, 3–17); 19/42 (45%) experienced a clinical relapse and 27% developed chronic epilepsy. Serum IL‐6, serum and CSF IL‐8/CXCL8, and IL‐17A were higher in LGI1‐IgG positive patients than MNID ( p < 0.05). TLE cytokine/chemokine profiles were similar to LGI1 AE; AD patients had lower serum IL‐6 and CSF IL‐8/CXCL8 ( p = 0.04; p = 0.01), and higher serum IL‐17A and GM‐CSF ( p = 0.004; p = 0.01) than LGI1‐AE. Higher CSF IL‐6 and IL‐8/CXCL8 in LGI1‐AE associated with clinical relapse ( p < 0.05) and higher CSF NfL associated with chronic epilepsy ( p = 0.01). Conclusion Elevations in IL‐6, IL‐8/CXCL8, and IL‐17A were identified in this LGI1‐AE cohort. CSF IL‐6, IL‐8/CXCL8, and NfL levels are potential prognostic biomarkers for risk of relapse and chronic epilepsy in LGI1‐AE.

Abstract The link between regional tau load and clinical manifestation of Alzheimer’s disease (AD) highlights the importance of characterizing spatial tau distribution across disease variants. In typical (memory-predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicentres. However, given the limited spatial heterogeneity of tau in typical AD, atypical (non-amnestic-predominant) AD variants with distinct tau patterns provide a key opportunity to investigate the universality of connectivity as a scaffold for tau progression. In this large-scale, multicentre study across 14 international sites, we included cross-sectional tau-PET data from 320 individuals with atypical AD (n = 139 posterior cortical atrophy/PCA-AD; n = 103 logopenic variant primary progressive aphasia/lvPPA-AD; n = 35 behavioural variant AD/bvAD; n = 43 corticobasal syndrome/CBS-AD), with a subset of individuals (n = 78) having longitudinal tau-PET data. Additionally, as an independent sample, we included regional post-mortem tau stainings from 93 atypical AD patients from two sites (n = 19 PCA-AD, n = 32 lvPPA-AD, n = 23 bvAD, n = 19 CBS-AD). Gaussian mixture modelling was used to harmonize different tau-PET tracers by transforming tau-PET standardized uptake value ratios to tau positivity probabilities (a uniform scale ranging from 0% to 100%). Using linear regression, we assessed whether brain regions with stronger resting-state functional MRI-based functional connectivity, derived from healthy elderly controls in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), showed greater covariance in cross-sectional and longitudinal tau-PET and post-mortem tau pathology. Furthermore, we examined whether functional connectivity of tau-PET epicentres (i.e. the top 5% of regions with the highest baseline tau load) and tau-PET accumulation epicentres (i.e. the top 5% of regions with the highest tau accumulation rates) was associated with cross-sectional and longitudinal tau patterns. Our findings show that tau-PET epicentres aligned with clinical variants, e.g. a visual network predominant pattern in PCA-AD (‘visual AD’) and left-hemispheric temporal predominance, particularly within the language network, in lvPPA-AD (‘language AD’). Moreover, more strongly functionally connected regions showed correlated concurrent tau-PET levels (confirmed with post-mortem data) and tau-PET accumulation rates. The functional connectivity profile of tau-PET epicentres and accumulation epicentres corresponded to tau-PET progression patterns, with higher tau-PET levels and accumulation rates in functionally close regions, and lower tau-PET levels and accumulation rates in functionally distant regions. Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicentres, across all AD clinical variants. Since tau proteinopathy is a major driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant-specific end points in clinical trials.

Abstract INTRODUCTION African American (AA) individuals are underrepresented in biomarker studies for Alzheimer's disease (AD). Biomarkers that reflect the heterogeneity of AD and achieve the greatest accuracy across populations are sorely needed. METHODS Untargeted proteome measurements were obtained using the SomaScan 7k platform to identify novel plasma biomarkers for AD in AA participants with clinical diagnoses of AD dementia ( n = 181) and cognitively unimpaired (CU, n = 142). Machine learning was used to identify a set of plasma proteins that yielded the best classification accuracy. RESULTS A set of 36 proteins achieved an area under the curve (AUC) of 0.94 to classify AD dementia versus CU, a 16% improvement over age, sex, and apolipoprotein E ( APOE) . This finding was replicated in multiple plasma and brain datasets (AUCs 0.73–0.97). Our findings underscore the importance of matrisome and cerebrovascular dysfunction in AD pathophysiology. DISCUSSION This study demonstrates the potential of biomarker discovery through untargeted plasma proteomics and machine learning. Highlights Conducted large‐scale plasma proteomics in Alzheimer's disease (AD) versus cognitively unimpaired controls. Machine learning biomarker discovery was replicated in an independent cohort. Novel set of proteins distinguishes AD versus controls with high accuracy (area under the curve [AUC] = 0.94). Achieved reproducibility across multiple replication cohorts (AUC = 0.73–0.97). Network analyses implicates matrisome biology and cerebrovascular dysfunction.