Beckett, Laurel

Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) recently celebrated its 20th anniversary, reflecting two decades of major contributions to Alzheimer's research through open data sharing and longitudinal multimodal assessments. This review synthesizes 122 high‐impact studies using ADNI data or biospecimens from 2023 to mid‐2025 to clarify mechanisms of Alzheimer's disease (AD) progression. Studies describe impairment of glymphatic clearance and the impact of cerebral small vessel disease, trajectories of amyloid beta and tau deposition, inflammation, metabolic disturbances, synaptic dysfunction, and neurodegeneration, leading to cognitive impairment and neuropsychiatric symptoms. Multifactorial contributions from genetic and epigenetic influences, co‐pathologies and comorbidities, and mechanisms of resilience modulate disease progression. Finally, heterogeneity of clinical presentation and disease course is described in the context of multiple contributing factors, highlighting the complexity of AD. By integrating imaging, fluid biomarkers, genetics, and clinical measures, ADNI provides a comprehensive research dataset for unraveling mechanisms underlying AD progression.

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 Remote neuropsychological testing can monitor brain health in individuals with or at risk of Alzheimer's disease (AD). We evaluated acceptability and validity of the Cogstate Brief Battery (CBB) for remote administration. METHODS Non‐demented adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) completed the CBB in‐clinic under supervision, then remotely every six months, with annual in‐clinic reassessments. Groups included cognitively unimpaired (CU) adults with normal amyloid (CU Aβ−) or elevated amyloid (CU Aβ+), and individuals with mild cognitive impairment with or without amyloid (MCI Aβ+, MCI Aβ−). Performance was compared across contexts and longitudinal changes were examined. RESULTS At baseline, MCI Aβ+ participants performed worse than CU Aβ−. CBB performance was similar across contexts, with consistent group differences. Over time, MCI Aβ+ participants showed greater decline on remote CBB measures than CU Aβ− adults. DISCUSSION Remote unsupervised CBB assessments are valid, reliable, and sensitive to AD‐related cognitive impairment.

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) continues to pose a major public health challenge. Since its launch in 2004, the Alzheimer's Disease Neuroimaging Initiative (ADNI) has played a pivotal role in advancing the field by providing a comprehensive, open‐access, longitudinal dataset that integrates neuroimaging, biomarker, genetic, and clinical data related to AD. We used standard literature search methods to identify ∼1830 publications from 2023 to mid‐2025 that used ADNI data or samples. This review highlights key ADNI studies with direct clinical applications. We describe how these have impacted the development and validation of plasma biomarkers, improved clinical trials, assessed AD therapies, and developed methods for diagnosis and prediction using clinical, fluid, and imaging biomarkers. These contributions are underlain by an improved understanding of biological mechanisms of disease progression in AD and highlight ADNI's central role in advancing translational research and accelerating progress toward more effective, individualized care for patients with AD.

Importance Sex differences are increasingly recognized as modifiers of Alzheimer disease and related dementias, with women exhibiting greater tau burden and faster cognitive decline than men. Even though α-synuclein copathology frequently occurs in Alzheimer disease, its contribution to sex differences in disease progression is unclear. Objective To test whether α-synuclein positivity, measured using cerebrospinal fluid seed amplification assay (SAA), is differentially associated with tau accumulation in women vs men across the Alzheimer disease continuum. Design, Setting, and Participants This cohort study used longitudinal tau positron emission tomography from the Alzheimer’s Disease Neuroimaging Initiative collected between 2015 and 2023, with a median (IQR) follow-up of 1.23 (0.00-3.84) years. Participants were stratified by cerebrospinal fluid α-synuclein seed amplification assay status and sex. Participants were cognitively unimpaired or cognitively impaired (mild cognitive impairment or dementia) at baseline. Exposure Cerebrospinal fluid α-synuclein status determined by SAA and dichotomized as SAA negative or SAA positive. Main Outcomes and Measures Tau burden was quantified as standardized uptake value ratio (SUVr) in the medial temporal composite region of interest. Linear mixed-effects models tested SAA by sex by time interactions on longitudinal tau accumulation, adjusting for baseline age, baseline cognitive status, apolipoprotein E ε4 carrier status, and site. Sample size estimates were calculated to detect 25% and 50% treatment effects with 80% power in those with cognitive impairment. Results Among 415 participants (mean [SD] age, 72.3 [7.6] years; 220 women [53%]; 69 SAA positive [17%] and 346 SAA negative [83%]), there was a significant interaction between SAA status, sex, and time on tau accumulation (β, 0.061; 95% CI, 0.030-0.093; P < .001). Women with positive SAA results exhibited the fastest tau accumulation compared with other groups (0.066 SUVr per year; 95% CI, 0.043 to 0.089 SUVr per year; P < .001). Clinical trials targeting tau pathology in cognitively impaired individuals with 18-month follow-up would require 129 SAA-positive women to detect a 25% treatment effect with 80% power, compared with 518 SAA-negative women. Conclusions and Relevance In this cohort study of participants across the Alzheimer disease continuum, α-synuclein copathology was associated with faster tau accumulation in women than men. These findings may inform sex-specific interpretation of α-synuclein biomarkers and trial design.

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.

Abstract Early-onset Alzheimer’s disease (EOAD) and Late-onset AD (LOAD) differ in clinical presentations and rates of progression. We aimed to compare baseline and longitudinal tau PET burden, and their relationship with clinical variables in amyloid-PET positive, cognitively impaired participants from the Longitudinal Early-Onset Alzheimer’s Disease Study (EOAD; n=390) and Alzheimer’s Disease Neuroimaging Initiative (LOAD; n=211). Patients with EOAD showed higher baseline tau PET retention, broader neuroanatomical involvement and faster accumulation rates over time compared to LOAD, after adjusting for amyloid load and clinical stage. Tau PET showed stronger correlations with baseline amyloid burden and clinical measures of global cognition and function in EOAD than LOAD. We conclude that earlier age of onset in AD is linked to a more aggressive tauopathy, which in turn is a primary driver of clinical decline. These findings suggest that optimal therapeutic targets and strategies may differ between EOAD and LOAD. One Sentence Summary Younger patients with Alzheimer’s disease show more aggressive tau spread, suggesting age of onset defines distinct disease pathways with key clinical implications.