Citations

Abstract Travelling waves are a prominent feature of hippocampal activity, but the mechanisms determining their propagation and influence on the cerebral cortex remain unclear. Using a biophysically-grounded model of neural activity evolving across hippocampal and cortical surfaces, we show that spatial gradients in external in-put or neural excitability are a sufficient mechanism for the emergence of travelling waves along the long axis of the hippocampus. These waves emerge only above a critical gradient threshold, propagate with biologically-plausible velocities and exhibit frequency-dependent reversals in direction across slow and fast theta regimes. When coupled to the cerebral cortex, anterior-to-posterior hippocampal waves selectively reorganise globally synchronous cortical activity into metastable travelling waves, whereas posterior-to-anterior hippocampal waves do not, revealing a directional asymmetry in hippocampal–cortical communication. Conversely, cortical waves aligned with large-scale functional gradients induce structured hippocampal waves, revealing complementary direction specific effects across the two systems. These analyses identify structured excitability gradients as a principle governing wave propagation in the hippocampus and suggest how wave-to-wave interactions may coordinate complex cortical and hippocampal interactions during mnemonic and perceptual processes.

Abstract INTRODUCTION Research into cognitive dispersion – a cognitive process score measuring the intra‐individual variability (IIV) across a single testing session – suggests utility in neurodegenerative populations. Given widespread deficits observed in sporadic early‐onset Alzheimer's disease (EOAD), however, it is unclear if examining cognitive dispersion shows benefit in this condition. METHODS A total of 309 participants (188 amyloid‐positive EOAD, 43 amyloid‐negative early‐onset dementia [EOnonAD], 78 cognitively normal [CN]) completed neuropsychological testing twice over 12 months. Dispersion‐related differences among groups were assessed, as was cognitive dispersion's capacity to predict domain‐specific cognitive trajectories, and its convergence with imaging biomarkers. RESULTS EOAD participants displayed higher cognitive dispersion than EOnonAD participants, and associations with EOAD‐specific biomarkers. Additionally, cognitive dispersion was associated with 12‐month reliable change across several cognitive domains. DISCUSSION These preliminary results examine cognitive dispersion in sporadic EOAD. When used with baseline cognitive performance, cognitive dispersion measures may enrich future clinical trials in EOAD by enhancing treatment monitoring over time.

Abstract The growing availability of large-scale biomarker datasets has allowed data-driven methods to characterize Alzheimer’s disease biological heterogeneity. However, most prior studies have focused on cohorts of late-onset amnestic cases, leaving early-onset Alzheimer’s disease underexplored. We aimed to characterize tau-PET-based subtypes through a robust data-driven approach in the Longitudinal Early-Onset Alzheimer’s Disease Study. Baseline [18F]Flortaucipir PET scans from 365 amyloid-PET-positive participants with sporadic early-onset Alzheimer’s disease were quantified in the left and right medial temporal, lateral temporal, occipital, parietal, and frontal cortices. Tau PET values were z-scored against 85 amyloid-PET-negative cognitively normal age-matched participants and fitted into Subtype and Stage Inference (SuStaIn)—an unsupervised clustering algorithm that simultaneously models subtypes and progression from cross-sectional data. The derived subtypes were subsequently characterized by baseline and longitudinal clinical, cognitive, MRI, tau and amyloid PET features. We identified three tau-PET-based subtypes: on average, Subtype 1/Typical (n = 144, 40%) showed a predominant bilateral temporoparietal pattern typical of Alzheimer’s disease. Subtype 2/Left temporal (n = 111, 31%) showed predominant left temporal binding. Subtype 3/Posterior (n = 104, 29%) showed early and permeating occipitoparietal involvement. Subtypes did not differ in demographics or global amyloid burden, but were relatively more enriched for specific clinical presentations: S1/Typical for amnestic presentations, S2/Left Temporal for primary progressive aphasia, and S3/Posterior for posterior cortical atrophy. Baseline tau PET subtypes aligned with cortical atrophy patterns and domain-specific cognitive impairment. When follow-up tau PET scans were fitted to SuStaIn trained on baseline data, 85.6% (n = 172/201) of participants retained the same subtype classification, indicating subtype temporal stability, and progressed within subtypes by 0.56 ± 0.70 SuStaIn stage/year. Longitudinal voxel-wise linear mixed-effects modelling revealed tau accumulation patterns for each subtype in regions relatively spared at baseline: occipital lobe accumulation predominated in S1/Typical, bilateral frontal and right temporal in S2/Left Temporal, and bilateral frontotemporal lobes in S3/Posterior. All subtypes showed longitudinal increases in Clinical Dementia Rating-Sum of Boxes, but with slower worsening in S3/Posterior compared with the other subtypes. Our findings reveal robust subtypes in sporadic early-onset Alzheimer’s disease characterized by distinct spatiotemporal tau patterns that parallel differences in clinical presentations and trajectories of neurodegeneration. These subtypes extend beyond traditional clinical syndromes and support a more nuanced framework for individualized prognosis and care. Incorporating tau PET subtyping into clinical trial design could enable more targeted therapeutic approaches for this younger population.

Abstract INTRODUCTION : Despite expanding use of plasma biomarkers for Alzheimer's disease (AD), minimal examination has been undertaken in early‐onset AD (EOAD). Prior analyses assessed criterion and convergent validity of common plasma biomarkers in a well‐characterized sample with sporadic EOAD. METHODS : Plasma amyloid beta (Aβ) 42/40, tau phosphorylated at threonine 231 (p‐tau231), glial fibrillary acidic protein (GFAP), and neurofilament light change (NfL) levels were obtained for 189 EOAD, 52 early‐onset non‐AD (EOnonAD), and 83 cognitively normal (CN) participants. Diagnostic group differences, convergence with imaging biomarkers, and the capacity to predict specific cognitive domains were investigated. RESULTS : After controlling for cognitive status, EOAD participants exhibited more pathologic levels of Aβ42/40, p‐tau231, and GFAP relative to EOnonAD participants. However, NfL displayed the greatest sensitivity to non‐amnestic cognitive impairment across the sample. DISCUSSION : These results establish criterion and convergent validity of plasma biomarkers in sporadic EOAD and highlight complementary roles that AD‐specific and non‐specific plasma markers may play across the course of AD care.

Abstract Alzheimer’s disease (AD) emerges from multi-scale interactions between molecular pathology and disruptions in large-scale brain network dynamics. Understanding how these processes co-evolve and relate to disease stages is essential for advancing complex systems models of aging and AD, and for developing system-informed interventions. However, progress has been limited by a lack of large-scale longitudinal data. To address this, we examined the longitudinal relationship between subsystems of the default mode network (DMN) (posterior DMN, ventral DMN, anterior dorsal DMN) using task-free functional MRI (fMRI) and amyloid positron emission tomography (PET) imaging in a large longitudinal cohort spanning the clinico-biological spectrum of AD (n = 1,451; 2,763 time points) using mixed-effect models. We also assessed whether patterns of DMN connectivity predicted conversion to amyloid positivity, mild cognitive impairment (MCI), and dementia using Cox proportional hazards models. Our findings reveal a dynamic interplay between amyloid accumulation and connectivity within and between DMN subsystems, with both hyper- and hypoconnectivity emerging across DMN subsystems in association with increasing amyloid burden. Importantly, survival models showed that DMN connectivity patterns predicted conversion to critical stages of the disease, including not only conversion to MCI and dementia, but also conversion to amyloid positivity in otherwise clinically unimpaired individuals who were amyloid negative at baseline. These associations were independent of age, APOE4 status, sex, education, and in-scanner motion. These results support a model in which breakdowns in tightly regulated feedback loops governing DMN physiology represent a core systems-level pathophysiology of AD. Notably, this functional dyshomeostasis precedes detectable amyloidosis on imaging. Future studies should focus on the development of robust biomarkers of brain function that can be applied at the individual level, which could in turn help support the development of therapeutic approaches targeting system-level pathophysiology.

Abstract Purpose: Knowledge of prognostic factors and long-term survival in patients with diffuse hemispheric glioma, H3 G34–mutant (DHG, H3 G34), remains limited in this tumor with a poor prognosis. Experimental Design: This retrospective, multi-institutional study investigated prognostic variables for patients with DHG, H3 G34, and their association with progression-free survival (PFS) and overall survival (OS). Uni- and multivariable Cox proportional hazard models were applied with multiple imputed datasets. Results: A total of 153 patients (142 G34R, 9 G34V, 2 via DNA methylation) were included. The median age at diagnosis was 17 years (range, 2–45). Initial gross/near total resection (GTR/NTR) was achieved in 43% of patients. Radiation was given in 91% (85% focal irradiation), and initial chemotherapy was given in 87% [70% temozolomide-based (TMZ), 25% TMZ/lomustine, 5% non-TMZ]. Median OS was 24 months [interquartile range (IQR), 22–28] with a median PFS of 14 months (IQR, 12–19). Twelve patients (8%) were found to be long-term survivors (≥5 years). Exploratory multivariable analysis showed that adjuvant radiotherapy [HR, 0.076; 95% confidence interval (CI), 0.033–0.17] and achieving GTR/NTR compared with < NTR (HR, 0.51; 95% CI, 0.33–0.78) were associated with improved PFS. Multivariable analysis showed improved OS with increasing age at diagnosis (HR, 0.70; 95% CI, 0.57–0.87), initial radiotherapy (HR, 0.38; 95% CI, 0.15–0.96), and initial GTR/NTR compared with < NTR (HR, 0.60; 95% CI, 0.37–0.97). Conclusions: This cohort highlights prognostic factors for patients with DHG, H3 G34, and describes relapse patterns and therapy approaches. Clinical trials and prospective registries are needed to improve outcomes.

Abstract INTRODUCTION The tau positron emission tomography (PET) overlap index (OI) has shown promise in maximizing signal‐to‐noise for longitudinal tau PET imaging, particularly for early tau pathology, but requires validation against neuropathology. METHODS Fifty‐seven participants who underwent serial tau PET imaging (flortaucipir) and subsequent autopsy were included. Tau PET OI and standardized uptake value ratios (SUVRs) were compared across neuropathological diagnoses. RESULTS Tau PET OI showed greater concordance with neurofibrillary tangle (NFT) severity in the entorhinal cortex (a key region for Alzheimer's disease [AD] tauopathy) than SUVR, particularly in early Braak tangle stages (positivity: 52.2% for OI vs. 13.0% for SUVR). OI detected overlapping tau voxels that exhibited spatial correspondence with immunohistochemical and autoradiography measures of tau deposition across both AD and non‐AD tauopathies. DISCUSSION These findings demonstrate the enhanced capacity of OI in serial tau PET to robustly detect early and spatially localized tau pathology, supporting its application as a sensitive imaging metric in AD and select non‐AD tauopathies.

BACKGROUND AND OBJECTIVES: Ventriculoperitoneal shunt (VPS) placement is a common treatment for idiopathic normal pressure hydrocephalus (iNPH), but patients may require VPS revision. This study aims to evaluate the effectiveness of a standardized VPS placement protocol by comparing indications and rates of shunt revision compared with a historical institutional cohort. METHODS: All patients treated with VPS for “suspected” iNPH at a tertiary care center between January 2000 and January 2023 were retrospectively reviewed and divided into temporally distinct historical (before 2017) and standardized (after 2017) cohorts. Cumulative incidence and timing of VPS revision were compared using competing risks analyses. RESULTS: A total of 561 patients (median age 75.0 years) were identified with 324 (57.8%) in the historical and 237 (42.2%) in the standardized cohorts. Significant variations in surgical technique and shunt hardware were noted between the cohorts. With a median follow-up of 11.4 months for historical and 12.4 months for standardized cohort, shunt revisions occurred in 19.4% and 8.4% of patients in the historical and standardized cohorts, respectively ( P < .001). Revision indications also varied significantly with lower rates of overdrainage ( P < .001), infection ( P < .001), and proximal malfunction ( P = .042) but higher rate of distal malfunction ( P = .03) in the standardized cohort. Notably, no infections were noted in the standardized cohort. CONCLUSION: Risk of shunt revision among iNPH patients may be associated with modifiable factors related to surgical technique and shunt hardware selection. Importantly, no short-term complications such as hemorrhage, infection, or catheter malposition were observed with the standardized protocol. Development and refinement of standardized shunt protocols for iNPH patients should be commonplace to facilitate tracking, identification, and modification of modifiable technical risk factors.

INTRODUCTION Recent work has identified unique cognitive profiles for early‐onset Alzheimer's disease (EOAD) relative to late‐onset Alzheimer's disease (LOAD), however, examination has been limited in determining whether the association between age and cognitive severity at presentation also differs across conditions. METHODS A series of linear spline regression models was conducted across baseline cognitive data from 325 EOAD and 314 LOAD participants, after accounting for education, sex, and apolipoprotein ε4 status. RESULTS Significant differences existed in the relationship between baseline age and cognitive performance between EOAD and LOAD samples for Processing Speed/Attention, Executive Functioning, and Episodic Immediate Memory. Younger participants from both EOAD and LOAD groups performed disproportionately worse on non‐amnestic cognitive domains, with this occurring to a greater extent in EOAD than LOAD. DISCUSSION In the age of disease‐modifying treatments, results highlight the importance of assessing for cognitive declines in individuals starting much earlier than age 65. Highlights Early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) participants each displayed cognitive impairments relative to same‐aged peers across most domains. Both groups displayed positive relationships between impairment among non‐amnestic cognitive domains and baseline age. This relationship displayed a significantly greater effect in EOAD than LOAD, with domains of Processing Speed/Attention and Executive Functioning skills being the most pronounced. Of those participants developing AD, age displayed a disproportionate impact on their symptom onset.