Citations

Abstract Introduction Remote cognitive assessments offer an accessible, scalable way to support clinical characterization and longitudinal monitoring of cognition. This study evaluates the feasibility of implementing Mayo Test Drive (MTD), a remote, self-administered digital cognitive assessment, within a specialized clinic focused on eligibility assessments for anti-amyloid therapies for Alzheimer’s disease (AD). Method Two-hundred and nine ( N =209) patients (M age =71.2, 53% female) were evaluated through the Mayo Clinic Rochester Alzheimer’s Disease Treatment Clinic (ADTC) and had the opportunity to complete MTD, either as a remote, patient-initiated session through a patient-facing healthcare portal or during an in-clinic neuropsychological evaluation. Results Clinical diagnoses included 55.2% mild cognitive impairment (MCI), 31.0% mild dementia, and 11.6% moderate dementia, in addition to 2.2% cognitively unimpaired (CU), as determined by neurology consensus at a multidisciplinary case conference. Among those who initiated MTD ( n =197/209), 97.5% completed a session (70.6% remotely, 26.9% in clinic). Completion rates were high across diagnostic groups and did not significantly differ by clinical severity ( p =.12): CU (100%), MCI (99.1%), mild dementia (97.0%), and moderate dementia (89.5%). Remote completion rates overall were high (97.9%). Among completers, administration setting (remote vs. in-clinic) did not significantly differ by clinical stage, χ²(3)=2.37, p =.49. Reasons for non-initiation included not receiving or opening portal messages and other/unknown factors. Discussion Remote digital cognitive assessment is feasible within the context of clinic eligibility evaluations for AD therapies. The high completion rates of MTD across clinical impairment levels in this setting support development of paths for broader use in cognitive characterization in AD care.

Assessing balance is crucial in neurological rehabilitation, yet while wearable sensors enable real-world monitoring, identifying reliable digital biomarkers remains challenging. This study utilized a high-fidelity instrumented walkway to determine which gait parameters best predict balance impairment, providing robust targets for future wearable applications. We analyzed 49 steady-state gait metrics from 140 individuals with diverse neurological conditions. Using statistical analysis and machine learning, we evaluated these parameters against objective force plate sway scores and clinical fall-history labels. Group analysis identified 16 parameters significantly distinguishing fallers from non-fallers, and a neural network classified fallers with an area under the curve of 0.75. Across all analytical approaches, overall gait variability, e.g., Stride Width S.D. and the Gait Variability Index, emerged as a universal predictor of balance impairment and fall risk. Furthermore, while traditional linear models emphasized spatial postural control, machine learning classification uniquely identified inter-limb asymmetry as a premier driver of fall prediction. These findings indicate that instrumented gait analysis effectively identifies digital biomarkers for balance deficits. Isolating these specific metrics provides a clear blueprint for meaningful metrics required for continuous objective monitoring and future development of personalized, adaptive rehabilitation strategies.

BACKGROUND: White matter hyperintensities (WMH) are widely used to assess cerebral small vessel disease but reflect late-stage injury. Diffusion magnetic resonance imaging (MRI) biomarkers have been proposed to capture earlier small vessel disease-related microstructural damage but their temporal progression relative to WMH and risk factors associated with progression remain unexplored. METHODS: We identified 2077 participants from the population-based cohort study of the Mayo Clinic Study of Aging in Olmsted County, Minnesota (aged 50–101 years) collected between 05/2005 and 09/2024 with longitudinal neuroimaging. Using multioutput nonlinear mixed-effects models in those with at least 2 fluid-attenuated inversion recovery-MRI and diffusion MRI scans, we characterized the temporal progression of WMH and 4 diffusion MRI biomarkers: fractional anisotropy of the genu of the corpus callosum, peak width of skeletonized mean diffusivity, free water, and Arteriolosclerosis-score, which were automatically estimated. Models incorporated participant-specific time shifts, correlations between biomarkers, and effects of risk factors (sex, education, APOE ε4 status, cardiometabolic conditions). RESULTS: The study population had a mean age of 78 years, 47% were women, 28% were APOE ε4 allele carriers, and 80% were cognitively unimpaired, with an average follow-up of 5.2 years (SD, 4.3 years) for fluid-attenuated inversion recovery-MRI and 4.3 years (SD, 3.9 years) for diffusion MRI. Arteriolosclerosis-score, fractional anisotropy of the genu of the corpus callosum, free water, and peak width of skeletonized mean diffusivity became abnormal in 50% of the study population 16, 12, 10, and 7 years before WMH become abnormal (half-width of CI <1 year), respectively. Global markers (Arteriolosclerosis-score, free water, peak width of skeletonized mean diffusivity, and WMH) were correlated, indicating shared substrates of widespread white matter injury. Fractional anisotropy of the genu of the corpus callosum, a vascular risk microstructural injury biomarker, was weakly coupled with WMH and had an earlier but more linear worsening across adulthood. Cardiometabolic conditions predicted earlier worsening of all biomarkers. Female participants showed earlier WMH, fractional anisotropy of the genu of the corpus callosum, and Arteriolosclerosis-score abnormalities, whereas male participants exhibited earlier peak width of skeletonized mean diffusivity and free water abnormalities. CONCLUSIONS: Diffusion MRI biomarkers were abnormal at least a decade before WMH become abnormal in the population, revealing a prolonged phase of early small vessel disease and highlighting their potential for small vessel disease prevention.

Objective Magnetic resonance imaging (MRI)‐visible enlarged perivascular spaces (PVS) are markers of cerebral small vessel disease (SVD) and aging, processes implicated in both neurodegenerative and cerebrovascular pathologies. However, longitudinal positron emission tomography (PET) studies examining PVS as a mechanism underlying Alzheimer's disease (AD) pathophysiological progression are lacking. Our overall objective was to investigate the associations of baseline PVS burden with white matter hyperintensity (WMH) volume, amyloid‐PET, and tau‐PET, both cross‐sectionally and longitudinally. Methods We examined 2,229 participants across the aging‐AD spectrum from the Mayo Clinic Study of Aging (MCSA) and the Mayo Alzheimer's Disease Research Center (ADRC) (mean age = 68.59 ± 12.70 and 48.94% women). PVS and WMH were quantified using a novel in‐house algorithm. Amyloid on [ 11 C]Pittsburgh Compound B (PiB)‐PET and tau on AV1451‐PET were measured. Cross‐sectional regional and global associations were examined using canonical correlation analysis (CCA). Longitudinal associations were examined using age‐ and sex‐adjusted linear mixed effect (LME) models with natural splines and subject‐wise 10‐fold cross‐validation. Result Three distinct associations were observed: (1) PVS in the basal ganglia (PVS‐BG) was associated with greater WMH volume both cross‐sectionally and longitudinally; (2) PVS‐BG covaried with higher PiB standardized uptake value ratio (SUVR) cross‐sectionally, with longitudinal trajectory associations limited to amyloid‐negative individuals; (3) PVS in the centrum semiovale (PVS‐CSO) was not associated with amyloid or tau, but was associated with occipital WMH, a pattern characteristic of CAA. Interpretation Findings lend support for PVS‐BG as an early indicator of small vessel dysfunction and WMH pathogenesis. Individuals with higher PVS‐BG burden exhibited higher WMH burden and faster WMH progression, suggesting that PVS‐BG may identify individuals at increased risk of progressive SVD. Evidence linking PVS to downstream AD biomarker progression was weaker. Findings support the relevance of PVS‐CSO to CAA, suggesting that they may reflect changes occurring early in the disease process. ANN NEUROL 2026

Abstract Background Alzheimer’s disease (AD) is clinicopathologically heterogeneous. A proportion of patients living with AD present clinically at a younger onset of cognitive symptoms before 65 years old and/or non-amnestic clinical syndromes. Neuropathologically, corticolimbic distribution of neurofibrillary tangle pathology occurs on a continuum with some cases having greater cortical tau pathology relative to limbic regions and others with relatively restricted accumulation in limbic structures. These patterns of corticolimbic tangle distribution are associated with clinical presentation and age at onset. This study sought to examine protein expression differences across the spectrum of clinicopathologic heterogeneity using the NULISA targeted proteomics platform. Methods A series of thirteen neuropathologically diagnosed AD cases from Mayo Clinic prospectively followed research studies were selected to reflect heterogeneity of clinical syndromes and corticolimbic distribution of tangle pathology. Frozen postmortem brain tissue samples were isolated from inferior parietal cortex and homogenized in RIPA buffer for analysis using Alamar Biosciences’ NULISA CNS disease 120 panel. Applying a conservative detection threshold of 75% level of detection for the novel application of NULISA in human brain, we evaluated levels of 69 of 129 protein targets across samples. We examined associations between age at onset cognitive symptoms and corticolimbic distribution of tangles (CLix) separately with individual protein targets using linear regression analysis. Results AD cases with a younger age at onset had higher measured levels of ubiquitin, while older age was associated with higher levels of total tau, CRH, and NPTX2. Investigations of corticolimbic heterogeneity revealed AD cases with lower CLix score (i.e., cortical predominant distribution of tau) had higher measured p-tau181, p-tau231, ubiquitin, and p62. AD cases with higher CLix (i.e., relative cortical sparing) had higher levels of total tau, CRH, NPTX2, MDH1, and HBA1. Brain-derived total tau consistently showed a stronger association in both models. Conclusion This work demonstrates the utility of postmortem proteomics for investigating biomarkers associated with AD clinicopathologic heterogeneity. We observed proteomic differences in synapse integrity, tau post-translational modification, and ubiquitination associated with age at symptomatic onset and corticolimbic distribution of tangle pathology.

Purpose of Research Lucidity is the transient recovery of abilities and communication that were seemingly lost among people living with dementia (PLWD). This study describes lucid episodes reported by Alzheimer’s dementia (AD) and Lewy Body Dementias (LBD) caregivers. We analyzed survey data from 212 current AD ( n = 191) and LBD caregivers who reported the frequency, duration, and characteristics of 653 lucid episodes witnessed in the past month. Major Findings Most AD caregivers (67%) and LBD caregivers (81%) witnessed a lucid episode within the past month. LBD caregivers reported lucid episodes with greater changes in awareness and communication, compared to AD caregivers. LBD caregivers reported longer lucid episodes and that the PLWD knew about their change in lucidity, compared to AD caregivers. Conclusions Findings suggest that differences in lucid episode intensity, timing, and meta-awareness between AD and LBD are possible and may inform care strategies for PLWD.

Abstract INTRODUCTION Face identification algorithms have increased the risk of study participants being identified through different neuroimaging modalities. De‐facing algorithms can de‐identify neuroimages; however, none are validated in individuals with Down syndrome (DS) – a population at high risk of Alzheimer's disease and the focus of numerous Alzheimer's disease cohort studies. METHODS Overall, 37 adults with DS were parcellated using FreeSurfer before and after de‐facing with mri_reface . A group of neurotypically developed individuals balanced on age, sex, and magnetic resonance imaging scanner manufacturer served as controls. RESULTS De‐facing produced no effect on cortical thickness or volumetrics in adults with DS compared to controls or regional discrimination based on an area under the receiver operating characteristic curve analysis after correcting for multiple comparisons. DISCUSSION FreeSurfer‐derived volumetric and cortical thickness measures changed minimally following de‐facing with mri_reface in adults with DS and are unlikely to influence study outcomes. De‐facing should be considered prior to data sharing in studies of adults with DS.

Abstract Patients with atypical variants of Alzheimer's disease (AD) often present at a younger age with predominantly non‐amnestic impairments and a more aggressive disease course. Historically, individuals with atypical presentations have not been included in large‐scale clinical trials, which typically focus on late‐onset, sporadic amnestic‐predominant AD. Consequently, treatment options and research efforts specific to atypical AD remain limited. The emergence of amyloid‐targeting therapies that slow disease progression underscores these challenges, as evidence supporting their efficacy in early‐onset amnestic and non‐amnestic AD variants is scarce. This perspective article argues that atypical AD represents an excellent disease model for clinical trials and proposes strategies to address critical gaps in clinical trial design for this population. Key considerations include optimizing participant selection approaches, establishing syndrome‐specific or surrogate biological and clinical endpoints, and fostering advocacy to enhance early and accurate diagnosis, equitable representation, and outcomes for these populations.