Citations

Abstract In response to a Cochrane review (published in April 2026) on the clinical trials of monoclonal antibodies targeting beta amyloid, this perspective outlines a number of critiques. The scientists, methodologists, subject‐matter experts, and clinicians on this perspective strongly recommend that the Cochrane editorial board consider a call for editorial response, correction of press materials, or commissioned reply to this review for four overarching reasons: (1) decision to pool antibodies that do and do not clear beta amyloid, (2) decision to include studies from a time when biomarkers of Alzheimer's disease were not available, (3) analytical and methodological limitations of the approach used, (4) conflating the distinct roles and methodological processes of systematic review and guideline methodologies, (5) contextualizing the present critique within the existing evidence‐synthesis literature, and (6) mechanistic inference beyond the scope of the presented analyses. Conclusions that may not accurately reflect treatment‐specific effects could cause significant downstream clinical and psychosocial harm to those currently undergoing treatment and their family members as well as individuals considering participation in Alzheimer's clinical trials.

Abstract INTRODUCTION Although cerebrospinal fluid (CSF) biomarkers reflect neurodegeneration in Alzheimer's disease (AD), it remains unclear whether these biomarkers track neurodegeneration in early‐onset Alzheimer's disease (EOAD). METHODS In 80 EOAD patients, we examined correlations between eight CSF biomarker levels and cortical thickness decreases within the EOAD cortical atrophy signature. Significant correlations were then entered into a multiple regression analysis. We also examined contributions of EOAD atrophy and CSF biomarkers to cognitive impairment. RESULTS The levels of four CSF biomarkers correlated to EOAD signature atrophy. Stepwise regression analyses revealed that CSF neurofilament light chain (NfL) levels best predicted EOAD signature atrophy. Multiple regression showed EOAD signature atrophy combined with CSF NfL levels explained more variance in cognitive impairment than either factor alone. DISCUSSION Within EOAD patients, CSF NfL levels relate to the magnitude of cortical atrophy, and a combination of EOAD signature atrophy and CSF NfL levels most robustly predict cognitive impairment.

Importance Multidomain lifestyle interventions slow cognitive decline in at-risk older adults, but effects on cerebrovascular injury and whether any effect differs by age or across magnetic resonance imaging (MRI) markers remain unclear. Objectives To test whether a structured multidomain lifestyle intervention, vs a self-guided program, alters trajectories of cerebrovascular MRI markers and whether baseline diffusion MRI estimates subsequent vascular injury. Design, Setting, and Participants POINTER Imaging was a prespecified secondary imaging analysis of the US POINTER (US Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk) randomized clinical trial conducted at multiple US sites. Starting August 1, 2020, and continuing until March 1, 2023, all newly enrolled US POINTER trial participants who met criteria, including being 60 to 79 years of age and at increased risk for cognitive decline, were given the opportunity to enroll in POINTER Imaging. Annual MRIs were performed at baseline and up to 2 follow-up visits at 12 and 24 months. The imaging study ended May 14, 2025. Interventions Structured multidomain lifestyle arm (supervised exercise, dietary counseling, cognitive and social engagement, and health coaching) vs self-guided educational arm. Main Outcomes and Measures Primary outcomes were cerebrovascular MRI markers of global white matter free water (FW), fractional anisotropy (FA), peak width of skeletonized mean diffusivity (PSMD), analysis along the perivascular space (ALPS) index, white matter hyperintensity (WMH) volume, and incident cerebral microbleeds (CMBs). Age-group analyses (<70 vs ≥70 years) were prespecified. Linear mixed-effects models tested time, intervention arm, age group, and interactions for continuous outcomes; logistic regression evaluated incident CMBs. All analyses were adjusted for sex, hypertension, diabetes, and smoking and were conducted for the evaluable population. Data were analyzed September 5 to December 11, 2025. Results For 959 participants included in the analysis, the mean (SD) age was 68 (5) years, and 594 (61.9%) were female. A significant time × arm × age group interaction was observed for FW (β = 0.050; SE = 0.018; P = .006). In participants younger than 70 years, the structured intervention, compared with the self-guided intervention, attenuated the FW increase over time (β = −0.031; SE = 0.012; P = .009); no intervention arm difference was observed in participants aged 70 years or older (β = 0.019; SE = 0.014; P = .18). No intervention-related interactions were detected (eg, time × intervention arm interaction) for WMH (β = 0.002; SE = 0.016; P = .90), FA (β = 0.016; SE = 0.016; P = .30), PSMD (β = −0.011; SE = 0.021; P = .60), or ALPS (β = 0.006; SE = 0.021; P = .79). Overall, greater odds of incident CMBs were associated with higher baseline FW (odds ratio, 1.63 [95% CI, 1.24-2.14]; P < .001) and PSMD (odds ratio, 1.40 [95% CI, 1.08-1.81]; P < .001). Greater WMH progression was associated with higher baseline FW (β = 0.014; SE = 0.006; P = .02) and lower baseline FA (β = −0.018; SE = 0.006; P = .004). Conclusions and Relevance In this secondary imaging analysis of a randomized clinical trial, FW was the cerebrovascular MRI marker most responsive to lifestyle intervention in adults 60 to 70 years of age, showing attenuated small-vessel disease–related injury. Findings suggested greater microvascular benefit when intensive lifestyle intervention is implemented earlier in late life. Trial Registration ClinicalTrials.gov Identifier: NCT03688126

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 In 2011, a workgroup of the Alzheimer's Association Research Roundtable introduced recommendations for detecting and monitoring amyloid‐related imaging abnormalities (ARIA) in Alzheimer's disease (AD) clinical trials. Since then, anti‐amyloid immunotherapies have received regulatory approval for AD treatment and are beginning to enter clinical practice, underscoring the importance of informing healthcare providers, researchers, and patients about ARIA's implications in real‐world settings. In response, the Alzheimer's Association convened a new workgroup to review current knowledge of ARIA, including underlying mechanisms, clinical presentations, associated risk factors, mitigation strategies, radiologic detection methods, patients’ perspectives in treatment decision‐making, and outstanding challenges. Here, we outline key insights from this workgroup, highlighting that effective ARIA detection and monitoring in clinical practice requires adherence to robust protocols to mitigate risks and enhance patient safety. Limited availability of clinical and pathologic data on predictors of symptomatic and severe ARIA underscores the importance of continued real‐world data collection.

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.

Abstract INTRODUCTION Tau species lacking truncation of the N‐terminal region, including plasma N‐terminal tau fragment 1 (NT1), have been previously associated with cognitive decline, neurodegeneration, and tau pathology in late‐onset sporadic Alzheimer's disease (AD). METHODS Here, we examined cross‐sectional and longitudinal plasma NT1 as a possible predictor of cognitive, clinical, and core AD biomarker trajectories in autosomal dominant AD (ADAD). RESULTS NT1 levels in ADAD mutation carriers (MC; n = 132) increased across the disease continuum, compared to non‐carriers (NC; n = 75), becoming elevated about a decade prior to estimated symptom onset. Cross‐sectional and longitudinal NT1 levels in MC were associated with clinical, cognitive, and biomarker changes. NT1 increases continued in symptomatic phases of disease, a distinct trajectory from that seen with CSF p‐tau217 and other phospho‐tau species. DISCUSSION Together, our results suggest that plasma NT1—alone or combined with other tau measures—may be useful in studying AD‐related clinical, cognitive, and biomarker outcomes. Highlights Leveraging a deeply phenotyped cohort of individuals carrying a pathogenic variant for autosomal dominant Alzheimer's disease (ADAD) and their non‐carrier family members, our results suggest that plasma N‐terminal tau fragment 1 (NT1) levels mirrored changes in clinical, cognitive, and neurodegenerative measures in ADAD, particularly in late asymptomatic and early symptomatic phases of disease. NT1 levels correlated with cerebrospinal fluid (CSF) measures of tau pathology but less so with CSF or imaging measures of β‐amyloid pathology. Together with previous supportive findings in preclinical and symptomatic sporadic AD, these results suggest that plasma NT1—alone or combined with other tau measures—may be useful in studying AD‐related tau pathology and neurodegeneration across a wide spectrum of disease.