Abstract INTRODUCTION White matter lesions on fluid‐attenuated inversion recovery magnetic resonance imaging (FLAIR‐MRI) reflect small vessel disease (SVD) and aid in identifying vascular contributions to impairment and dementia (VCID). Emerging diffusion MRI (dMRI) biomarkers are sensitive to early SVD but the lack of validated approaches for defining dMRI abnormality has limited their clinical utility. METHODS In 3934 participants (8749 observations) from a population‐based sample, we classified 9% as vascular cognitive impairment versus not (VCI+/VCI−) using abnormal FLAIR‐MRI and cognitive testing. We evaluated four distinct dMRI positivity criteria and assessed performance in an independent clinical sample. RESULTS The young referent criterion performed best and yielded an estimated prevalence of dMRI positivity aligned with pathology literature. About 40% of the population were dMRI positive, and these individuals had lower baseline cognition and faster longitudinal decline. Cutpoints were validated in an independent clinical sample. DISCUSSION The proposed dMRI abnormality framework can detect VCID and aid in identification of individuals at risk of VCI.
Mild Behavioral Impairment is Associated with Postmortem Alzheimer’s Disease (AD) Neuropathology (P7-13.003)
Rural populations are underrepresented in cognitive impairment research and have limited resources for education about brain and cognitive health, Alzheimer's disease and related dementias, or caregiving. As our Outreach, Recruitment, and Engagement team aimed to expand activities into more rural communities, we also wanted to better understand the characteristics of the communities surrounding our center and gain insight into the social exposome of the areas. The goal of the manuscript is to reflect on our experience and share measures that were useful in this effort, which can be further enriched and adjusted by other outreach teams.
Variability in Clinical Performance of the FDA-Cleared Lumipulse P-Tau217/β-Amyloid 1-42 Plasma Ratio
This cross-sectional study evaluates the performance of the US Food and Drug Administration–cleared phosphorylated tau 217 (p-tau217) to β-amyloid 42 ratio cut points used to detect amyloid pathology associated with Alzheimer disease.
Reliability of remote self‐administered Web‐based digital cognitive measures and comparison to in‐person neuropsychological tests: Stricker Learning Span, Symbols Test, and the Mayo Test Drive Screening Battery Composite
Abstract INTRODUCTION We describe the reliability of remote self‐administered digital cognitive measures completed via the Mayo Test Drive (MTD) web‐based platform. METHODS A total of 1846 participants (mean age = 70, SD = 12, range 31–101; 48% male; 96% White; 99% non‐Hispanic; 97% cognitively unimpaired) with two to four complete MTD sessions at ∼7.5‐month intervals were included. Test‐retest reliability was assessed using single‐rating, absolute‐agreement, and two‐way mixed intraclass correlation coefficients (ICCs) with 95% confidence intervals. ICCs for in‐person‐administered traditional neuropsychological measures were compared to MTD for a subset of 244 participants. Analyses also compared reliability across demographic, residential, and session context subgroups. RESULTS Reliability was good for the MTD Composite (total ICC = 0.79 [0.77, 0.80]), and moderate‐to‐good for the primary outcome variables for each MTD subtest (total ICCs 0.70–0.83 for Stricker Learning Span and Symbols). The reliability of the remote self‐administered MTD was similar to in‐person‐administered cognitive measures. DISCUSSION MTD showed moderate‐to‐good reliability, supporting its use in longitudinal monitoring.
0284 Association Between Overnight Sleep Features and Morning Brain Metabolism in Older Adults
Abstract Introduction The relationship between sleep and brain metabolism remains unclear. This study aimed to examine whether overnight sleep features, using a home sleep apnea system based on peripheral arterial tonometry, are associated with regional FDG-PET changes in older adults. Methods We analyzed cognitively unimpaired adults (≥60 years) from the Mayo Clinic Study of Aging (MCSA) cohort who were not receiving sleep apnea treatment. Participants underwent overnight sleep assessment with the WatchPAT system, followed by FDG-PET imaging the next morning. FDG-PET data were co-registered to 3T MRI and automatically segmented into 122 anatomical regions. PET signal was referenced to the pons (SUVR). We computed voxel-weighted median FDG signal across 47 bilateral cortical and subcortical regions of interest (ROIs), excluding brainstem and cerebellum. Associations between sleep architecture and sleep apnea/hypoxemia burden and regional metabolism were assessed using partial Spearman’s rank correlation, adjusting for age. Results Thirty-seven participants were included (70.3% female; median [IQR] age: 72.0 [68.0–78.0] years). Wake after sleep onset (WASO) showed widespread negative associations with FDG uptake in cortical regions (p< 0.05), particularly the ventromedial/ventrolateral (rs=–0.47 to –0.33) prefrontal cortex, lateral temporal (rs=–0.38 to –0.33), and occipital (rs=–0.47 to –0.37) cortices. Total sleep time (TST) was positively associated with medial structures (p< 0.05), including the posterior cingulate (rs=0.39), retrosplenial cortex (rs=0.48), hippocampus/parahippocampal (rs=0.34 to 0.36), calcarine cortex (ρ=0.38), thalamus (rs=0.37), and caudate (rs=0.43). Hypoxic burden was positively associated with medial occipital regions (rs=0.35 to 0.39) and AHI-4% with cuneus (rs=0.33). Regional gray matter volume did not mediate these associations. WASO correlated with Insomnia Severity Index (rs=0.43, p=0.008) and self-reported refreshing sleep (rs=0.046). Conclusion Overnight sleep macrostructure features (WASO and TST) and hypoxic burden are significantly associated with brain metabolism, potentially underlying symptoms of sleep disturbance and cognitive aging. Support (if any) Mayo Clinic Alzheimer’s Disease Research Center Development Award (P30 AG062677), R01 AG056366, U01 AG006786, R01 AG056366, R01 AG034676, R37 AG011378, R01 AG041851, R01 NS097495, R01 AG068206, P30 AG062677, R01 HL065176. CLARA project work with funding from the European Union’s HORIZON EUROPE research and innovation programme (No 101136607).
Abnormal amyloid PET usually represents intermediate/high Alzheimer's disease neuropathologic change
Abstract INTRODUCTION Alzheimer's disease neuropathologic change (ADNC) classification identifies not/low and intermediate/high levels of neuropathology. Our goal was to assess how frequently a positive amyloid positron emission tomography (PET) scan indicates not/low ADNC and whether this autopsy finding can occur >10 years after a positive amyloid PET. METHODS Participants with positive amyloid PET scans were categorized by levels of ADNC at autopsy, grouped by time from initial positive amyloid PET to time of death (<5 years, 5 to <10 years, or 10+ years). RESULTS Among those with a positive amyloid PET scan, the majority had intermediate/high ADNC at autopsy (234/259, 90%). In the group with 10+ years between a positive amyloid PET and death ( n = 39) not/low ADNC occurred in 3/39 (8%). DISCUSSION Not/low ADNC is uncommon among those with positive amyloid PET scans. After 10+ years, it is possible but rare for a positive amyloid PET scan to represent an indolent state of neuropathology.
Default mode network failure across the Alzheimer’s disease spectrum
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.