Citations

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.

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.

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 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.

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).

Abstract Introduction Sleep-disordered breathing (SDB) is a potentially modifiable risk factor for the prevention of dementia, of which Alzheimer’s disease (AD) is the most common cause. However, there is a lack of longitudinal evidence relating SDB to AD pathology >20 years later. We examined the association between late-midlife SDB and late-life brain β-amyloid (Aβ) deposition—a hallmark of AD—assessed approximately 23 years later. Methods The Atherosclerosis Risk in Communities (ARIC) Study is an ongoing prospective cohort study initiated in 1987. Participants at two ARIC sites (Washington County, Maryland; Minneapolis, Minnesota) with primarily White participants also completed polysomnography (PSG) in the Sleep Heart Health Study (SHHS) in 1995-98. SDB measures included apnea-hypopnea index (AHI; number of apneas + hypopneas with ≥3% oxygen desaturation/hour of sleep), arousal index, and percentage of total sleep time in apnea, in hypopnea, and with oxygen saturation < 90%. A subset of participants completed florbetapir positron emission tomography (PET) scans through several ARIC ancillary studies (2011-2025 including the ARIC Sleep-PET study). We defined Aβ deposition as a global standardized uptake value ratio (SUVR) >1.2 (vs. SUVR ≤1.2). We used Poisson regression with robust standard errors to estimate relative risk (RR) of Aβ deposition by SDB, adjusting for demographics and vascular risk factors, and applied inverse probability attrition weighting to account for selective drop-out. Results Among 186 dementia-free participants (mean age=59 years at PSG and 82 years at PET scan, 58% female, 98% White), every 10% increase in total sleep time in hypopnea was associated with higher risk of Aβ deposition (RR=1.40, 95% confidence interval [CI]: 1.03, 1.91). When compared to no SDB (AHI < 5), moderate to severe SDB (AHI ≥15) was associated with elevated Aβ deposition (RR=2.36, 95% CI: 1.22, 4.57); mild SDB (AHI 5 to < 15) was not (RR=1.05, 95% CI: 0.53, 2.07). Conclusion SDB in late midlife was associated with greater risk of Aβ deposition approximately 23 years later. SDB may play a role in the early stages of AD pathogenesis. Future longitudinal studies are needed to optimize strategies for screening and treating SDB for dementia prevention. Support (if any) Supported in part by RF1AG050745.

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.

Abstract INTRODUCTION Prospective studies of blood‐based biomarkers reflecting pathogenic processes, other than Alzheimer‐specific pathologies, that contribute to dementia in diverse cohorts are lacking. METHODS We jointly fitted linear mixed‐effect models and proportional hazards models to examine associations of midlife glial fibrillary acidic protein (GFAP), chitinase‐3‐like protein 1 (YKL‐40), soluble cluster of differentiation‐14 (sCD14), neurofilament light chain (NfL), total tau (t‐tau), and ubiquitin C‐terminal hydrolase L1 (UCHL1) levels in serum (collected in 1993 to 1995) with cognitive decline and incident dementia (ascertained over 29 years through 2022) in the community‐based Atherosclerosis Risk in Communities Study. sCD14 and YKL‐40 were measured in 3082 participants and the other four biomarkers in 1766 participants. RESULTS Higher serum GFAP, YKL‐40, sCD14, and NfL were associated with faster cognitive decline and elevated dementia rate (e.g., 1 standard deviation [SD] higher log‐base2 YKL‐40 was associated with −0.11SD faster 25‐year cognitive decline (95% confidence interval [CI]: −0.15,−0.07) and 45% higher dementia hazard (hazard ratio [HR]: 1.45 [95% CI: 1.25, 1.68]). Higher t‐tau and UCHL1 were also associated with faster cognitive decline. DISCUSSION Midlife blood biomarkers reflecting glial and neuronal dysfunction and neuroinflammation are associated with early cognitive impairment.