Carrillo, María C.

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.

Importance Brain imaging biomarkers may (1) identify underlying mechanisms of intervention effects and (2) define brain characteristics of those most likely to benefit cognitively from the intervention. Objective To test whether (1) a lifestyle intervention is related to brain changes, (2) brain changes are correlated with intervention-specific cognition changes, and (3) brain imaging biomarkers provide information about who is likely to benefit from a lifestyle intervention. Design, Setting, and Participants In this randomized clinical trial, the POINTER Imaging study was an ancillary study of the 2-year, single-blind multicenter US POINTER clinical trial in which neuroimaging data were collected on eligible enrolled participants. The study was conducted from May 2019 to March 2023 (final follow-up, May 14, 2025). Participants were enrolled into the POINTER Imaging study following a standard procedure at 5 clinical sites in the US. Participant eligibility criteria included an age of 60 to 79 years, sedentary lifestyle, and suboptimal diet, plus at least 2 additional risk criteria for cognitive decline and no contraindications for neuroimaging. Interventions Participants were randomly assigned to receive the structured or self-guided intervention. Both interventions emphasized increased physical and cognitive activity, healthy nutrition, social engagement, and cardiovascular health monitoring, but they differed in intensity and accountability. Main Outcomes and Measures There were 4 primary imaging outcomes: global β-amyloid (Aβ) burden, tau burden in the entorhinal cortex (ERC), hippocampal (HC) volume, and white matter hyperintensity volume. The primary cognitive measure was a global cognitive composite. Results Among 1943 parent trial participants who were assessed for eligibility, 983 underwent at least 1 magnetic resonance imaging or positron emission tomography scanning session. The mean (SD) age was 68.4 (5.2) years; 605 participants (61.5%) were female and 378 male (38.5%). Five hundred sixteen participants received the structured intervention and 467 the self-guided intervention. There were no intervention group differences in longitudinal cognitive or imaging outcomes. Intervention group differences were not associated with or moderated by Aβ status or accumulation. There was a negative association between change in ERC tau and change in global cognition in the self-guided group that was attenuated in the structured group (difference in association: 0.289; 95% CI, 0.029 to 0.550; interaction P = .03). Lower baseline HC volume was associated with greater cognitive benefit for participants in the structured group vs the self-guided group (lower HC: 0.077 SD; 95% CI, 0.022 to 0.132; higher HC: 0.002 SD; 95% CI, −0.037 to 0.041; interaction P = .03). Conclusion and Relevance This study found that a high-intensity multidomain lifestyle intervention did not affect brain biomarker trajectories and was not associated with Aβ pathology, but older adults with specific at-risk brain characteristics, including lower baseline HC volume, showed a greater cognitive benefit of the structured intervention. Trial Registration ClinicalTrials.gov Identifier: NCT03688126

Abstract Latin America is undergoing rapid population aging alongside a rising burden of dementia. While the region holds substantial potential for dementia risk reduction, challenges remain, such as delayed diagnoses, limited access to specialized care and biomarker testing, persistent stigma, and deep‐rooted structural inequities. To address these gaps and foster regionally informed solutions, the Alzheimer's Association convened the 2025 Alzheimer's Association International Conference (AAIC) Satellite Symposium in Lima, Peru, on May 14–15, in collaboration with the Global Brain Health Institute (GBHI) and the Atlantic Fellows for Equity in Brain Health. The meeting aimed to bring core elements of the global AAIC meeting to regional Latin American settings, recognizing that national and cultural contexts demand tailored approaches to dementia prevention, risk reduction, treatment and care all aimed at promoting brain health in the region. This manuscript synthesizes the symposium's key discussions, scientific advances, and opportunities for collaboration across the region.

Abstract Advances in biomarker technology, digital cognitive assessments, and amyloid‐targeting therapies have redefined the opportunities for accurate and early diagnosis and care of Alzheimer's disease (AD). These advances also create new possibilities for intervention before the onset of cognitive impairment. This paradigm shift has increased the focus on Stages 1 and 2 of AD, in which individuals are cognitively unimpaired but exhibit biological evidence of disease. While early identification of AD offers an opportunity to intervene early to delay progression and preserve quality of life, it also presents complex challenges related to communicating diagnostic results to patients and their families, contextualizing the cost effectiveness of early diagnosis and treatment, and implementation of and equitable access to treatments. Recent, successfully enrolled, preclinical AD trials highlight the complex strategies required to identify asymptomatic, biomarker‐positive individuals on a large scale, and demonstrate critical knowledge gaps in inclusion, follow‐up, and long‐term outcome measurement. The Spring 2025 Alzheimer's Association Research Roundtable (AARR) meeting brought together academics, clinicians, industry, and regulatory leaders to exchange perspectives on current challenges, key learnings, and potential strategies for identifying and treating individuals in very early stages of AD, effectively and safely. This paper presents key takeaways from the Spring 2025 AARR meeting. Highlights New criteria for Alzheimer's disease (AD) enable early identification of AD pathology. Blood tests and digital cognitive assessment tools may facilitate early and personalized care. Plasma biomarkers may be scalable in clinical settings but need confirmation or follow‐up assessments in those individuals with equivocal results. Early therapy shows best results in people with lower initial amyloid and tau burden.

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.

Abstract INTRODUCTION The genetic basis of sporadic early‐onset Alzheimer's disease (EOAD) remains largely unknown, prompting evaluation of late‐onset Alzheimer's disease (LOAD) polygenic risk in EOAD. METHODS A LOAD polygenic score (PGS) was calculated in the Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) and Alzheimer's Disease Neuroimaging Initiative (ADNI) study and tested for associations with AD risk, cognitive performance, and imaging and fluid biomarkers. RESULTS Though PGS was elevated in LOAD and EOAD, it was not a significant predictor of EOAD adjusting for APOE ε4 carrier status and was not associated with age of EOAD onset ( p = 0.106) or with cognitive performance ( p = 0.417). In LEADS, greater LOAD PGS was associated with differences in neuroimaging and fluid biomarkers, including elevated synaptosomal‐associated protein 25 (SNAP‐25) ( p = 2.3 × 10 −5 ). DISCUSSION While LOAD polygenic risk contributed minimally to EOAD onset and cognitive dysfunction, PGS association with fluid biomarkers in LEADS suggests a role for LOAD polygenic risk in EOAD pathophysiology. Highlights LOAD PGSs were elevated in both LOAD and EOAD compared to controls; however, LOAD PGS did not significantly predict EOAD risk, age at onset, or cognitive performance independent of APOE ε4 in the LEADS. Higher LOAD PGS was associated with lower amyloid PET Centiloids (less brain amyloid deposition) as well as lower CSF biomarker Aβ42 in LEADS (proxy marker suggesting higher brain amyloid deposition) in LEADS; these contradictory findings support the need for larger studies to further investigate whether LOAD PGS is associated with increased amyloid deposition in EOAD. Higher LOAD PGS was also associated with higher levels of CSF synaptosomal‐associated protein 25 (SNAP‐25), a key component of the SNARE complex, suggesting that LOAD genetic factors may contribute to dysregulation of synaptic transmission and/or pathological protein aggregation in EOAD.

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen's kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure 1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure 1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure 2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure 2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.

Abstract Background Sex, education and race/ethnicity are all associated with risk of Alzheimer's disease dementia. Here, we assess the effects of self‐reported sex, educational attainment and race/ethnicity on amyloid‐positivity, and tau‐PET‐positivity in 12,048 (7,394 cognitively unimpaired [CU], 2,177 MCI, and 2,477 dementia) individuals from 42 cohorts worldwide. Method Logistic generalized estimating equations were used to estimate frequency of amyloid‐positivity (using cohort‐specific thresholds for amyloid‐PET [84%] or CSF) and tau‐PET‐positivity (cohort‐specific thresholds of 2SD above mean temporal uptake in amyloid‐negative controls). We assessed: i) sex and APOEε4 ( N = 10,098) associations, to complement earlier findings of a higher frequency of tau‐positivity in females, ii) effects of lower/higher education ( N = 10,970; cohort‐specific median‐split), and iii) effects of race/ethnicity (non‐Hispanic White [hereafter: White], N = 4880; Asian, N = 116; Black or African‐American [hereafter: Black], N = 353; Hispanic, N = 356, only from Northern‐American cohorts). Outcomes were frequency of amyloid‐positivity in CU individuals only, and tau‐PET‐positivity in both amyloid‐positive (AB+) CU and cognitively impaired (CI, i.e. MCI and dementia) individuals. Interaction effects on the relationship between age and amyloid/tau‐positivity were assessed and only retained in the models when significant. Result Female sex was associated with an APOEε4 ‐independent increased frequency of amyloid‐positivity (β=0.51[0.22], p = 0.02) in CU and increase of tau‐positivity in both AB+CU (β=0.27[0.08]) and AB+CI (β=0.37[0.08], both p <0.01). Remarkably, tau‐positivity frequencies of female APOEε4 non‐carriers were equivalent to male APOEε4 carriers in AB+CI (Figure 1). No significant sex* APOE interactions were observed. In CU, higher education was associated with lower amyloid‐positivity frequency (β=‐0.12[0.05], p = 0.02). In contrast, among AB+CU, there was an age*education interaction effect that indicated more pronounced age effects on tau‐positivity in individuals with higher education (age*education:β interaction =0.03[0.01], p <0.01). There were no education effects in AB+CI (Figure 2). In CU, an age*race/ethnicity interaction effect was observed across all non‐White groups compared to White (Hispanic:β interaction =‐0.05[0.01], p <0.01; Black:‐0.04[0.01], p <0.01; Asian:‐0.02[0.01], p = 0.04). This suggests that the impact of age on amyloid‐positivity was less pronounced in non‐White groups. Furthermore, in AB+CI, Hispanic ethnicity was related to higher tau‐positivity frequency than White (β=0.51[0.22], p = 0.02; Figure 3). Conclusion In this multi‐center initiative comprised of clinical and community‐based cohorts, we observed that self‐reported sex, educational attainment and race/ethnicity were related to positivity‐frequencies of Alzheimer's disease pathology.

Abstract Background The Joint Propagation Model (JPM)‐based CenTauR scale was recently introduced to harmonize tau‐PET quantification across different radiotracers. This study examined how CenTauR harmonization enhances the comparability of tau‐PET quantification across matched cohorts using different tracers. The evaluation focused on three key aspects: (1) comparing tau‐PET positivity rates as defined by CenTauR, (2) evaluating its diagnostic accuracy for symptomatic AD, and (3) analyzing longitudinal changes in tau‐PET rates over time. Method The JPM, developed by the CPAD‐led Tau PET Harmonization Working Group (Leuzy et al., Alzheimers Dement. 2024; Figure 1A), models relationships between anchor point subjects and head‐to‐head tau‐PET SUVR data onto the CenTauR scale, providing conversion equations for multiple tracers. JPM equations were applied to [ 18 F]flortaucipir SUVR (Meta‐temporal ROI) data from 561 cognitively impaired participants in the ADNI and OASIS‐3 studies. Using ROC analysis, we determined the CenTauR cut‐off for positivity (T+) that maximized the Youden index for discriminating between FDA‐approved positive/negative visual reads. Three separate cohorts, scanned using [ 18 F]flortaucipir (ADNI), [ 18 F]MK‐6240 (CPAS), and [ 18 F]RO‐948 (BioFINDER‐2), were matched 1:1 by age, MMSE, amyloid‐β, and clinical diagnosis. CenTauR‐based metrics were compared across these cohorts. Result A cut‐off of 18 CenTauRs was found to optimally classify [ 18 F]flortaucipir PET visual reads (Figure 1B). The matching procedure identified 1089 participants (363 per cohort). The frequency of T+ using the 18 CenTauRs cut‐off for the Meta‐Temporal ROI was highly comparable across tracers across groups, except for the Aβ‐positive cognitively unimpaired group, where variability was more pronounced due to a smaller sample size (Figure 2A). Similarly, tau‐PET discriminative accuracy for symptomatic AD vs controls remained similar across [ 18 F]flortaucipir and [ 18 F]MK‐6240 (Figure 2B). In a separate sample of 212 matched participants from ADNI ([ 18 F]flortaucipir) and AIBL ([ 18 F]MK‐6240) with baseline and 1‐year follow‐up tau‐PET scans, 1‐year change in CenTauRs was comparable (Figure 2C). An exploratory voxelwise transformation, utilizing the Meta‐Temporal conversion equation in a representative case scanned with both [ 18 F]flortaucipir and [ 18 F]MK‐6240, demonstrates the potential for voxelwise CenTauR harmonization (Figure 3). Conclusion These analyses suggest that CenTauR harmonization increases the comparability of tau‐PET data acquired with different tracers. Additional validation analyses with larger cohorts including other radiotracers ([ 18 F]PI‐2620) are underway.