Citations

Abstract Background Neighborhood social and built environment characteristics may promote physical activity, a modifiable factor for dementia risk, which may in turn promote cognitive and brain health. We explored the associations of the U.S. National Walkability Index ‐ a nationwide geographic data resource that ranks block groups according to their relative walkability – with cognitive function, gray matter (GM) and white matter hyperintensities (WMH), neighborhood disadvantage, sedentary behavior and frequency of physical activity in cognitively unimpaired older adults at increased Alzheimer's disease (AD) risk. Method We included baseline data from 1398 older adults (68.3 ± 5.17 years, 68.3% females, 30.5% APOE4 carriers) from the U.S. POINTER trial. Walkability was classified as: least, below average, above average and most walkable. Neighborhood disadvantage (low, moderate and high) was assessed using Area Deprivation Index (ADI) ( N = 1384). Physical inactivity was assessed using the Sedentary Behavior Questionnaire (SBQ, hours sitting/week, N = 1106), and physical activity was measured with a composite score from the Community Health Activities Model Program for Seniors (CHAMPS) questionnaire. Linear and logistic regressions examined associations between walkability and (1) physical activity and sedentary behavior; and (2) cognition assessed with the Preclinical Alzheimer's Cognitive Composite (PACC‐5), GM volume and WMHs, Additionally, associations between neighborhood disadvantage and physical activity and sedentary behavior were explored. Models were adjusted for age, sex, race, APOE4 and total intracranial volume. Result More deprived areas were generally less walkable (β = ‐0.008, p < 0.001) (Figure 1). Higher walkability (Above average: β = 0.192, p = 0.011 and most walkable: β = 0.183, p = 0.032) was associated with higher PACC‐5 (Figure 2A) scores but not with more preserved GM or lower WMH. Walkability scores were not associated with physical activity and sedentary measurements, while greater neighborhood disadvantage was linked to sedentary behavior (β = 0.126, p < 0.001) (Figure 2B). Conclusion These results suggest that physical inactivity in more deprived areas is associated with neighborhood socioeconomic disadvantages rather than built environment. Additionally, walkability scores were not associated with any measure of physical activity or brain health, suggesting the need to further investigate other health effects of neighborhood disadvantage and walkability.

Abstract Background In aging and dementia research, the relationships between modifiable risk factors and biomarkers often vary across cohorts. We aim to evaluate the consistency and generalizability of the association between the area deprivation index (ADI) ‐ an indicator of socioeconomic/resource disadvantage within a specific area ‐ and cognition and Alzheimer's disease (AD) biomarkers across three distinct research cohorts, two from the U.S. (U.S. POINTER Imaging, ADNI) and one from Spain (UBRAIN). Method We included a total of 3091 participants without dementia, 1879 from U.S. POINTER Imaging, 282 from ADNI and 930 from UBRAIN (Table 1). The ADI was calculated using validated indices from the US and Spain, with neighborhood deprivation ranked as Low, Moderate, and High in the US, and Low and High in Spain. Outcomes of interest included (1) the preclinical Alzheimer's cognitive composite (PACC‐5), (2) MRI‐derived gray matter volumes in AD‐vulnerable regions and (3) PET or CSF‐derived amyloid status (+/‐). We ran logistic regression models with ADI level as predictor adjusted by sex, age, and APOE4 and considered education and race or ethnicity (only US cohorts) in our analyses. Result Participants in more deprived areas had lower education across cohorts and were more likely to be female (U.S. POINTER) and African American (U.S. POINTER and ADNI, Table 1). Independent of age, sex and APOE4 status, higher ADI was associated with lower PACC in U.S. POINTER (Moderate: β=‐0.165, p <0.001; High β=‐0.412, p <0.001) and UBRAIN (ADI: High β=‐0.096, p = 0.022) but not in ADNI (Figure 1). After controlling for education, this association remained significant in U.S. POINTER (Moderate: β=‐0.166, p = 0.002; High: β=‐0.248, p = 0.007) but not in UBRAIN (β=‐0.021, p = 0.66). In U.S. POINTER, there was a trend towards an association of higher ADI with lower GM volume in AD‐vulnerable regions (β=‐0.126, p = 0.089) that was not observed in ADNI or UBRAIN (Figure 2). No associations between ADI and amyloid status were found across cohorts. Conclusion We observed differing associations in neighborhood deprivation and cognition across US cohorts, as well as between the US and Spain cohorts. Country‐specific factors and sample representativeness must be considered when investigating the pathophysiologic mechanisms underlying social determinants and disparities in AD.

Abstract Background The first three talks focused on three important aspects on including diversity in Resilience Research ‐ engagement and inclusion of historically underserved communities, including sex, gender, and social determinants of health (SDH) in our analyses, and methodological challenges and recommendations for inclusion of diverse populations. Objective While important knowledge gaps were identified and recommendations made for diversity inclusion, discussion of these topics in the context of clinical importance and applied potential will enhance knowledge mobilization and translation of research findings which will be discussed as part of this talk. Methods Clinical importance for knowledge mobilization focuses on direct impact on patient diagnosis/treatment to ensure research improves health outcomes. Whereas, applied potential focuses on public health and outreach activities to ensure that research reaches underserved communities and subgroups of populations. Results Guided by the aspects discussed in the first three talks, we will discuss specific examples from emerging research across diverse populations on 1) how inclusion of diversity in resilience research can aid in improvements in patient care, screening, and management; and 2) how better data collection and targeting awareness of research in underserved communities along with improving instruments of recruitment and retention can provide us with data for deeper evaluation of mechanisms of prevention across different sub‐populations. Conclusion While creating a roadmap for inclusion of diversity in resilience research for aging and dementia is the important first step, focus should be placed on effective translation of the emerging research findings to reach broader aspects of patient care.

Abstract The Atherosclerosis Risk in Communities (ARIC) study started in 1987‐1989 (visit 1), when participants from four U.S. communities were 45‐64yo. Participants have been seen at up to 10 additional in‐person visits with annual/semi‐annual telephone calls to ascertain clinical events, hospitalizations, and other health outcomes. In 2011‐2013, at ARIC visit 5, the ARIC Neurocognitive Study (ARIC‐NCS) was initiated for surviving participants, incorporating neuropsychological assessments at multiple in‐person visits and informant interviews to support cognitive adjudication. A subset of participants have undergone brain MRI with measurement of brain volumes, cortical thickness, arterial disease and vascular lesions, with a smaller subset having brain florbetapir PET. Blood‐based Alzheimer's disease (AD) biomarkers are available at multiple visits along with extensive measurement of vascular risk factors, vascular markers, and ‐omic (e.g.genomic and proteomic) data. This presentation will focus on the available data in ARIC, the methods underlying its collection and subsequent analysis, and some of the primary contributions of this study to the field. With 37 years of follow‐up, a great strength of ARIC is the ability to evaluate risk factors in midlife; ARIC studies have supported an association of midlife hypertension, diabetes, physical inactivity, and other vascular risk factors with reduced dementia risk, even among those with increased genetic risk for dementia. ARIC studies have demonstrated associations between stroke and dementia, and have linked vascular risk factors with blood‐based and imaging biomarkers of AD‐related dementias. ARIC has demonstrated the importance of hearing loss in dementia risk, and a subset of ARIC participants were recruited into (and were those who most benefited from the intervention of) the ACHIEVE study of hearing aid use for reduction of dementia. Proteomic studies have identified markers of dementia risk when evaluated in midlife. Recently, ARIC data informed updated estimates on lifetime risk of dementia, where it was estimated that among individuals surviving beyond age 55, 42% would develop dementia over their lifetime through age 95. ARIC studies continue to focus on risk factors for dementia, particularly now in the oldest old, and on contributors to cognitive reserve and resilience. ARIC follows a model of data sharing and broad collaboration.

Abstract Background Tau‐PET imaging enables in vivo detection of tau pathology in Alzheimer’s disease (AD), with early detection being critical for tracking disease progression. Here, we compare [ 18 F]FTP and [ 18 F]MK6240 in individuals with low tau burden. Method 450 individuals from the HEAD study (22 cognitively unimpaired (CU) young (CUY), 242 CU old and 186 cognitively impaired (CI)) underwent [ 18 F]FTP and [ 18 F]MK6240 tau‐PET and amyloid‐PET scans. Scans were processed using identical pipelines with inferior cerebellar gray matter as the reference region. Individuals were categorized as low tau if both [ 18 F]FTP and [ 18 F]MK6240 meta‐temporal SUVR were lower than 1.5. For comparison, [ 18 F]MK6240 and [ 18 F]FTP were transformed into one another using linear and non‐linear models; additionally, images were also z‐scored relative to the CUYs. Result Despite cognitive status and amyloid burden, several individuals showed elevated [ 18 F]FTP retention in temporal regions relative to [ 18 F]MK6240. As an example, Figure 1 shows [ 18 F]FTP and [ 18 F]MK6240 in 16 participants (4 per cognitive and amyloid status). Across most subjects with SUVRs<1.5, [ 18 F]FTP presented higher retention in meta‐temporal region as compared to [ 18 F]MK6240, though [ 18 F]MK6240 increased sharply above this threshold (Figure 2). In Figure 3, group‐average images and their transformed counterparts are shown for each group by amyloid and cognitive status, the subset of low‐tau participants in Aβ+ groups are also shown. In low tau groups, [ 18 F]FTP meta‐temporal retention is high in comparison to [ 18 F]MK6240. Additionally, z‐scored [ 18 F]FTP images show broader spread into temporal regions than [ 18 F]MK6240, reinforcing differences in retention. Conclusion [ 18 F]FTP shows meta‐temporal retention not seen with [ 18 F]MK6240 in low tau individuals. This discrepancy persists across transformed and z‐scored images, suggesting that there is a difference in early tracer retention between [ 18 F]FTP and [ 18 F]MK6240. It is unclear if the early [ 18 F]FTP retention is related to early maturity levels of tau or off‐target signal. These findings have important implications for basic understanding of early tau retention, early diagnosis, and biomarker harmonization efforts.

Abstract Background Cognitive impairment often goes undetected by clinicians due to time constraints, limited expertise, and lack of standardized tools. Structured cognitive assessments improve detection accuracy compared to unstructured clinical judgment. In 2013, the Alzheimer’s Association published recommendations to help primary care clinicians incorporate cognitive assessments into the Medicare Annual Wellness Visit. Since then, advances in cognitive assessment tools, availability of disease‐modifying therapies, and shifting expectations around early diagnosis have highlighted the need for updated guidance. In response, the Alzheimer’s Association is developing an evidence‐based clinical practice guideline for cognitive testing in primary care, using the GRADE approach, informed by a systematic review of the best available evidence. Method A multidisciplinary panel formulated a clinical question to inform the development of this guideline. A systematic review was conducted (search range: 1999‐2024) to evaluate the diagnostic accuracy of ten cognitive tests (5‐Cog, AD8, GPCOG, IQCODE, Mini‐Cog, MIS, MoCA, QDRS, RUDAS, and SLUMS) for the early detection of cognitive impairment (including MCI and dementia), in adults aged 55+ in ambulatory settings. The panel also narratively summarized data on emerging digital tools. Result Forty‐one studies meeting eligibility criteria were included in the systematic review. Results were analyzed separately by test (including short‐IQCODE and short‐MoCA) and for primary care and for ambulatory clinic settings (e.g., neurology, memory disorder clinics), as well as for English and Spanish language, resulting in 21 separate analyses. Only three analyses, all related to MoCA, allowed for meta‐analysis. The panel will use the evidence to inform conditional recommendations for or against each specific test. Conclusion By evaluating the diagnostic performance of selected tests, this guideline aims to support healthcare professionals in primary care settings in effective triaging of individuals who may benefit from further cognitive evaluation. To enhance real‐world applicability, considerations such as administration time, ease of scoring, and diagnostic accuracy ‐ along with appropriate cut‐offs by race/ethnicity, education, and language ‐ should be prioritized. This guideline will be regularly updated over time to reflect emerging evidence and the needs of diverse populations.

Abstract Background In recent years, blood‐based biomarkers (BBMs) have transformed the diagnostic landscape of Alzheimer’s disease (AD), with some now approaching readiness for clinical implementation. This progress aligns with the growing importance of accurate early diagnostics and availability of anti‐Aβ therapies for the treatment of early symptomatic AD, reinforcing the need for more rapid and early diagnostic capabilities. To address this need, the Alzheimer’s Association convened a multidisciplinary panel of clinical experts, subject‐matter specialists, and guideline methodologists to conduct a systematic review and develop evidence‐based recommendations for the use of BBMs in the diagnostic evaluation of AD. The scope of this guideline is focused on individuals with cognitive impairment ‐ either MCI or dementia ‐ who are undergoing diagnostic assessment in secondary or tertiary care settings. Method The panel conducted a systematic review to assess BBMs' diagnostic test accuracy in detecting amyloid pathology for triaging (≥90% sensitivity, ≥75% specificity) and confirmatory (≥90% sensitivity and specificity) diagnostic workup. The BBMs of interest included plasma p ‐tau and Aβ tests measuring the following analytes: p ‐tau217, % p ‐tau217, p ‐tau181, p ‐tau231, and Aβ42/Aβ40 ratio. The reference standard tests included CSF, amyloid PET, or neuropathology examination. The panel applied the GRADE approach to assess the certainty of the evidence and the GRADE Evidence‐to‐Decision Framework to develop its recommendations. Result Across 49 observational studies meeting eligibility criteria, 31 different BBM tests were evaluated. Using predefined decision thresholds, the panel determined whether each test has 1) sufficient diagnostic test accuracy to be used as a triaging test where a positive test is to be confirmed by PET or CSF, 2) sufficient diagnostic test accuracy as a confirmatory test to replace PET or CSF, or 3) insufficient diagnostic test accuracy to recommend current use in clinical practice. Recommendations will be provided in case any BBMs met a priori DTA thresholds. Conclusion BBMs can improve early AD diagnosis and expand access to disease‐modifying therapies. Evidence‐based guidelines are key to standardizing their use and will be updated as new evidence and applications emerge.

Abstract Background Mitophagy constitutes a crucial cellular pathway in mitochondrial quality control, in which the enzymatic pair PINK1 and PRKN selectively decorates damaged mitochondria with phosphorylated‐ubiquitin (pS65‐Ub), facilitating their autophagic‐lysosomal removal. We previously demonstrated significant accumulation of pS65‐Ub labeled damaged mitochondria in Lewy body and Alzheimer’s disease autopsy brain. This mitophagy alteration was strongly associated with pre‐tangle tau pathology in neurons. The effects of distinct tau species on mitophagy across different cell types however remain largely unknown. We therefore expanded our analyses to primary tauopathies, exploring how specific tau forms and their aggregation influence mitophagy in selectively vulnerable brain regions and cell types. Method This study included 92 control and tauopathy cases with primary age‐related tauopathy (PART), Pick’s disease (PiD), progressive supranuclear palsy (PSP), or corticobasal degeneration (CBD). Immunohistochemistry for the mitophagy marker pS65‐Ub and phospho‐tau was performed in vulnerable brain regions (hippocampus for PART and PiD, primary motor cortex for PSP and CBD). A deep learning‐based image identification model was used to identify and quantify distinct tau inclusions. pS65‐Ub‐positive cells were manually counted and grouped based on signal intensity and morphology. Immunofluorescence co‐staining of pS65‐Ub and phospho‐tau was conducted to study their spatial relationship at single‐cell level. Result We observed marked increases in pS65‐Ub‐positive cells in the hippocampus of PART and PiD cases compared to controls. Although less prominent, significant increases were also found in the primary motor cortex of PSP, whereas only minor changes were observed in CBD. Single‐cell analyses revealed that the accumulation of pS65‐Ub was most abundant in hippocampal neurons from PART. Cells with lower signal intensity contained mostly granular pS65‐Ub deposits, while those with higher intensity harbored rather vacuolar inclusions. Across tau aggregate subtypes, pS65‐Ub levels were strongly correlated and often co‐resided with neurofibrillary tangles and Pick bodies. Such correlations were weaker for coiled bodies and tufted astrocytes, and absent for astrocytic plaques. Conclusion Our study highlights distinct mitophagy alterations in primary tauopathies that are associated with specific tau inclusions in neurons, oligodendrocytes, and astrocytes. The observed pathological heterogeneity and complex mitophagy disruption underscores the need for future studies to elucidate pathogenic mechanisms and advance targeted therapeutics for each tauopathy.

Abstract Background Individual environmental exposures, the exposome, can play an influential role in the development and progression of neurodegenerative diseases such as AD. The protein components of the main AD neuropathologies, amyloid (Aβ) plaques and tau neurofibrillary tangles (NFTs), can be measured using immunohistochemical and biochemical approaches. The main genetic risk factor for AD is the APOE e4 allele. APOE levels can also be measured in the brain. We hypothesize that social determinants of health, specifically alcohol and tobacco consumption, and the area deprivation index (ADI), could play a considerable role in severity of neuropathology and brain biochemical phenotypes of AD. Method We evaluated 478 neuropathologically characterized AD donors, from the Mayo Clinic Brain Bank. 469 samples had available biochemical measures (APOE, Aβ40, Aβ42, tau, and phospho‐tau (Thr231)), collected across three isolated fractions (soluble (TBS), membrane‐bound (TX), and insoluble (FA)) of the superior temporal gyrus. Exposome variables were extracted from the available records. ADI from the Neighborhood Atlas® version from the year 2015 was obtained from de‐identified addresses. ADI, smoking and alcohol were available for 263 of these donors and were examined for association with biochemical measures using linear regression adjusting for age at death and sex. Result Higher ADI levels representing neighborhoods with increased deprivation, were nominally associated (β=0.006, p =0.01) with soluble levels of APOE. Alcohol consumption was associated with lower levels of membrane bound APOE (β=‐0.23, p =0.04). Analysis with neuropathological variables including CAA ( N =454), Braak ( N =454), Thal ( N =454), Hippocampal sclerosis ( N =453), Lewy bodies ( N =455) will also be performed. Conclusion Different components of the social exposome may impact levels of core AD proteins. Additional analyses in expanded cohorts to further explore the associations with neuropathology are ongoing. We expect that understanding how the social exposome impacts specific aspects of neurodegenerative diseases will provide key insights into underlying, potentially modifiable, mechanisms of disease.

Abstract Background Alzheimer’s Disease (AD) progression is conceptualized as a cascade of sigmoidal (S‐shaped) curves, with biomarkers shifting sequentially from normal to abnormal states. Estimating these curves requires sophisticated modeling, with challenges including (1) selecting appropriate sigmoidal‐type functions, (2) achieving algorithmic convergence, and (3) producing clinically useful parameters. We compare commonly used sigmoidal‐functions and effects on novel estimates of early and late AD‐biomarker progression ages. Method Using 3,999 Amyloid PET (PiB SUVR) measurements from 1,367 Mayo Clinic Study of Aging participants, we compared model fits (AIC, BIC) between logistic and hyperbolic functions using Non‐Linear Mixed Effect (NLME) models with subject‐specific age‐shifts. We defined novel “initial” and “maximum” acceleration points (IAP and MAP) to compare clinically “earlier” and “later” AD‐progression ages between sigmoidal‐curves. The MAP uses the maximum second‐derivative point, reflecting the age of fastest acceleration in biomarker accumulation. The IAP is defined as the first point where the second derivative of the sigmoidal‐curve exceeds a clinical threshold (here, 5% velocity increase per year), indicating onset age of early accelerated biomarker accumulation. Estimates for C 2 N plasma p ‐tau217 were also attempted (1,306 measurements on 457 participants). Models adjusted for sex and APOE4‐positivity. Result In the larger PET sample, the hyperbola had lower AIC/BIC (better fit), but showed a decreasing early PiB‐SUVR trend (Table 1A, Figure 1). Ages of late MAP were comparable, as were sex and APOE4+ related PiB‐SUVR‐curve shifts. Age of early AD‐onset was estimated 1.5 years earlier for logistic (IAP=63.6) versus hyperbola (IAP=65.1) functions. The logistic function always converged, while the hyperbolic function did not converge for p ‐tau217 in the smaller C 2 N sample. Early‐onset and late‐progression ages were 7‐8 years later for p ‐tau217 versus PiB‐SUVR using logistic‐curves. Conclusion Late AD‐progression and covariate‐related shifts in progression were comparable across models, suggesting robustness to sigmoid choice. In contrast, estimates of early AD‐onset may be more dependent on functional form. While logistic‐sigmoids inherently increase monotonically, hyperbolas do not, here estimating a decline in initial amyloid trend. Future work may explore adding biologically informed constraints to flexible sigmoidal‐functions, and alternative Bayesian approaches, to optimize both model fit and estimation of early AD‐onset age.