Abstract Background Neuropathologic evaluation is essential for diagnosing and treating dementia, but definitive diagnoses is only available after post‐mortem brain autopsy. Positron emission tomography (PET) offers a potential in vivo proxy for predicting neuropathology. This study proposes a semi‐supervised learning (SSL) model using a single FDG‐PET image to predict underlying neuropathology. Method The SSL model leverages a self‐organized graph structure based on a patient similarity network (PSN) created from 1,495 FDG‐PET images across the aging and neurodegenerative spectrum. Each patient is represented by a node, with edges indicating image similarity derived from principal component analysis features and cosine similarity weights. The PSN structure connects 20 nearest neighbors. Neuropathologic labels were available for 204 autopsied patients. The Poisson Learning Method was employed to propagate labels from these annotated nodes to unlabeled nodes, guided by the PSN structure. FDG‐PET images were collected from clinical and research participants at the Mayo Clinic and processed using an MRI‐free pipeline. Neuropathologic labels were assigned based on widely accepted diagnostic criteria. Leave‐one‐out cross‐validation (LOOCV) was used to assess model performance. Results The confusion matrix demonstrated high accuracy in predicting Alzheimer's disease, frontotemporal lobar degeneration with tau inclusions, and Lewy body disease pathology. A Sankey diagram and label distribution analysis revealed strong correlations between clinical and predicted neuropathologic labels. Conclusion This study highlights the potential of a graph‐based SSL pipeline to predict neuropathological changes using FDG‐PET imaging data, despite limited pathology labels. The findings underscore the value of SSL in bridging the gap between abundant neuroimaging data and scarce neuropathologic labels, contributing to improved dementia diagnosis and understanding.
Senescent Mesenchymal Stromal Cells Differentially Alter Adipogenesis in Adipose Tissue, Skeletal Muscle, and Bone Marrow
ABSTRACT Objective Aging alters mesenchymal stromal cell (MSC) function, leading to dysregulated adipogenesis across tissues through biased lineage commitment. Fat redistribution from adipose depots to skeletal muscle and bone marrow is common in aging, but the underlying mechanisms remain unclear. This study investigates how MSC senescence modulates adipogenesis. Methods Primary MSCs were isolated from mouse skeletal muscle (FAPs), adipose tissue (APCs), and bone marrow (BMSCs). Single‐cell RNA sequencing was performed to compare transcriptional profiles among these populations. In vitro adipogenic differentiation and DNA damage–induced senescence assays were conducted, and the effects of autologous conditioned media from senescent MSCs on adipogenesis were assessed. Results Transcriptional analyses revealed that FAPs and APCs share greater similarity with each other than with BMSCs. All MSC types exhibited adipogenic potential and developed a robust senescence‐associated secretory phenotype (SASP) upon senescence induction. Conditioned media from senescent MSCs enhanced adipogenesis in BMSCs but inhibited adipogenesis in FAPs and APCs, revealing tissue‐specific paracrine effects. Conclusions MSC senescence reprograms adipogenic bias in a tissue‐dependent, non–cell autonomous manner, contributing to age‐related fat redistribution among adipose tissue, skeletal muscle, and bone marrow. Understanding these mechanisms may provide new therapeutic approaches for improving tissue composition and function in the context of aging.
Effects on blood neurodegeneration biomarkers of a randomized hearing rehabilitation intervention: ACHIEVE Clinical Trial update
Abstract Background The Aging and Cognitive Health Evaluation in Elders (ACHIEVE) randomized trial ( n = 977;ClinicalTrials.gov:NCT03243422) demonstrated that hearing intervention slowed 3‐year cognitive decline by 48% among a subgroup of participants. To further investigate differences by treatment with respect to cognitive benefit, we tested the hypothesis that hearing intervention is associated with improved neurodegeneration blood biomarkers 3‐years post‐randomization and assessed whether combining biomarkers and cognitive results improved power in the trial design. Method The ACHIEVE study is a multicenter, parallel‐arm, randomized trial (hearing intervention vs health education control) on 3‐year cognitive decline among adults 70–84years with untreated hearing loss and without substantial cognitive impairment. Participants were recruited from two populations: (1) a long‐standing cardiovascular health observational study (Atherosclerosis Risk in Communities [ARIC]), and (2) de novo community volunteers. Plasma was collected in year 3 in a subsample ( n = 540) while ARIC participants ( n = 164) also had baseline plasma. Glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) neurodegenerative biomarkers were derived using the Alamar CNS protein panel. Regression models estimated the association of treatment with 3‐year biomarkers and global cognitive differences in the combined sample and by recruitment source and annualized change from baseline in the ARIC sample. We included a simple composite score of the standardized outcomes (Table 2). Result Among the subsample, baseline characteristics were balanced by treatment. There were no significant differences on 3‐year neurodegeneration biomarker levels by treatment in the combined (Table 1) or de novo groups (Table 2). Among ARIC participants, intervention resulted in lower 3‐year GFAP (mean:‐0.415;95%CI:‐0.712,‐0.118) and NfL (mean:‐0.349;95%CI:‐0.652,‐0.046) (Table 2). Annualized change from baseline analyses among ARIC participants (Table 3) revealed intervention was associated with a slower rate of cognitive decline (difference‐in‐means:0.059;95%CI:0.018,0.100) and a slower rate of increase in GFAP (difference‐in‐means: ‐0.060;95%CI:‐0.112,‐0.009). Differences in estimates suggest combined score, relative to cognition alone, may increase power in clinical trials that show a positive effect (ARIC subgroup: p = 0.02vs. 0.08[Table 2] and p = 0.0009vs.0.048[Table 3]). Conclusion Hearing intervention was associated with positive 3‐year effects on neurodegeneration blood biomarkers in ARIC participants which parallels cognitive decline results. Results provides objective evidence of brain changes following hearing intervention and potential signal of a more powerful combined outcome approach for future brain health clinical trials.
Decades of Discovery: Contributions of the Atherosclerosis Risk in Communities (ARIC) Study to Dementia Research
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.
Discrepant tau‐PET signal between [
18
F]FTP and [
18
F]MK6240 in low tau individuals
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.
Estimating Early Biomarker Accelerations in AD‐progression: Modelling the Jack Curves
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.
Association of Centrally Acting Medications, Chronic Pain, and Orthopedic Surgical History with Cognitive Impairment and Neurobehavioral Dysregulation in Former American Football Players
Abstract Background Exposure to repetitive head impacts (RHI) is associated with developing chronic traumatic encephalopathy (CTE) neuropathology. Cognitive and behavioral symptoms have been associated with CTE neuropathology, but efforts to define the specific clinical syndrome are ongoing. This study characterizes the current use of centrally acting medications (CAMs), chronic pain, and number of orthopedic surgeries in former American football players and evaluates for associations with cognitive and behavioral symptoms. Methods This study analyzed data from the DIAGNOSE CTE Research Project, which includes 120 former professional football players, 60 collegiate football players, and 56 asymptomatic men without history of RHI. Medical history was obtained by self‐report, and participants completed the Montreal Cognitive Assessment (MoCA), Brief Pain Inventory, Barratt Impulsiveness Scale‐11 (BIS‐11), BRIEF‐A Behavioral Regulation Index (BRI), Beck Depression Inventory‐II (BDI‐II), Beck Anxiety Index (BAI), and Brown‐Goodwin Lifetime History of Aggression adulthood score (BGLHA). Logistic regression assessed the association of CAMs, average pain score, and orthopedic surgeries on the cognitive impairment and neurobehavioral dysregulation components of the NINDS traumatic encephalopathy syndrome (TES) research criteria, in former American football players. Linear regression assessed the associations with MoCA and behavioral scales. Models were adjusted for age, education, race, and years of football played. Results Tables 1 and 2 describe the sample and CAM burden. More orthopedic surgeries, CAMs, and higher average pain were observed in former American football players. Number of CAMs was associated with neurobehavioral dysregulation (OR = 2.18), lower MoCA (β = ‐0.47), and higher BIS‐11 (β = 2.23), BDI‐II (β = 2.01), BRI (β = 3.71), BAI (β = 2.04), and BGLHA (β = 0.68) scores. Higher average pain was associated with neurobehavioral dysregulation (OR = 1.57) and higher BIS‐11 (β = 2.20), BDI‐II (β = 1.98), BRI (β = 2.20), BAI (β = 1.84), and BGLHA (β = 0.52) scores. No associations were observed with orthopedic surgeries. Conclusions In former American football players, the number of CAMs and higher average pain were associated with neurobehavioral dysregulation. No associations were observed with diagnosis of cognitive impairment by TES criteria, though the number of CAMs was associated with decreased MoCA.
Head‐to‐head in vivo Braak staging with MK6240 and Flortaucipir
Abstract Background In vivo Braak staging stratifies patients across the AD spectrum and has the potential to harmonize tau PET tracer staging. This study aims to compare and test harmonization procedures for Braak staging individuals using MK6240 and Flortaucipir tau PET tracers. Methods We assessed 437 participants across the AD spectrum (245 cognitively unimpaired (CU) and 192 cognitively impaired; mean age 68.5 ± 8.6) using head‐to‐head MK6240 and Flortaucipir scans. We computed SUVRs in Braak regions of interest (ROIs) and assessed four cut‐off methods for Braak positivity: (a) mean + 2.5 SD of young controls (age <28 years), (b) mean + 2.5 SD of elderly CU Aβ−, (c) Gaussian mixture modeling (GMM), and (d) the Youden index. Braak stages were assigned using seven (0 to VI) or four (0, I–II, III–IV, V–VI) categories. We evaluated inter‐ and intra‐tracer concordance (intra‐tracer, i.e., whether it follows the sequential Braak pattern). Results The intra‐tracer seven‐class Braak staging concordance ranged from 63% to 94%. With the highest intra‐tracer Braak concordance being achieved when using GMM cutoffs: 94% (MK6240) and 89% (Flortaucipir; Figure 1). Inter‐tracer agreement concordance ranged from 56% to 76%. The highest concordance emerged from the CU Elderly Aβ– cutoff optimizing the Braak II region for spill‐off (Figure 2). Using the Braak staging simplified version improved intra‐tracer concordance in both tracers (MK6240as well as inter‐tracer agreement (86.5%). Most inter‐tracer discrepancies were observed at Braak stages II–IV. Despite showing staging discordances, the distribution of cognitive status across the Braak stages is similar for both tracers (Figure 3). Conclusion These preliminary findings reveal some discrepancies in Braak staging when comparing MK6240 and Flortaucipir. Our results also suggest that adjustments in cutoffs and regions of interest can partially mitigate both inter‐ and intra‐tracer divergences. Finally, our analysis suggests robust concordance after adjustment and using 4 classes (0, I‐II, III‐IV, V‐VI).
Harmonizing visual readings of tau PET tracers ‐ the HEAD study
Abstract Background Tau‐PET provides critical topographic information on tau deposition in the living brain. Integrating research‐based practices into clinical settings through qualitative methods, such as visual reads, is becoming increasingly important. This study aims to compare the performance of existing visual reading methods for [ 18 F]Flortaucipir (FTP) and [ 18 F]MK‐6240 (MK) and provide preliminary data toward a unified visual reading approach for all tau‐PET tracers using a head‐to‐head dataset. Methods The study design and development plans are illustrated in Figure 1. To evaluate previously published visual reading methods, two blinded raters conducted FTP and MK visual reads on 340 participants from the HEAD study. A unified visual reading method was developed and tested on 101 participants, using a composite of adjusted Braak regions to determine 3 stages of severity while harmonizing between tracers. For external validation, the method will be tested on four additional cohorts, each using one of the following tracers: FTP, MK, PI, or RO. Results Inter‐rater agreement using previous methods (Figure 2A) showed high Cohen’s kappa values (0.71‐0.77) for the low and high tau burden categories in both FTP and MK visual reads. However, agreement was substantially lower in the non‐AD‐like category, leading to overall agreement rates of 0.55 for FTP and 0.69 for MK. In contrast, the method developed here improved inter‐rater agreement across all categories (0.87‐0.96) and introduced a moderate tau (0.79‐0.83) burden group (Figure 2B), leading to higher overall agreement rates of 0.81 for FTP and 0.87 for MK (Figure 2C). For inter‐tracer agreement (Figure 3), previous methods resulted in discordant visual reads for FTP and MK in 34.4% of cases for rater 1 and 24.7% for rater 2. The developed method reduced this disagreement to 11.9% (rater 1) and 15.8% (rater 2), demonstrating improved consistency across different tracers. Conclusion This study demonstrates that previously published visual reading methods produced varying classifications depending on the tracer used. The method proposed here improved inter‐rater and inter‐tracer visual read agreements by developing a unified, tracer‐agnostic approach easy to be used. Importantly, this clinician‐friendly method has the potential for widespread adoption, offering a single harmonized visual reading technique for all tau‐PET tracers.
Different Patterns of Propagation of Tau Tangle Pathology in Typical Alzheimer's Disease Determine Clinical Sub‐Phenotypes
Abstract Background One of the hallmarks of Alzheimer’s disease (AD) is the progressive spread of tau pathology. However, heterogeneity in the spatial patterns of tau deposition at the individual level may contribute to distinct clinical presentations. Here, we investigated the different patterns of tau deposition across disease progression and the different cognitive profiles linked to these patterns. Method We investigated 106 tau PET positive individuals (16% cognitively unimpaired, 84% amnestic cognitively impaired) from the HEAD study using head‐to‐head Flortaucipir and MK6240 tau PET. For each tracer, we extracted the SUVR values from seven major brain networks: Limbic, Visual (Vis), Default Mode (Default), Dorsal Attention (DorsAttn), Frontoparietal, Somatomotor (SomMot) and Salience Ventral Attention (SalVentAttn) as well as the Entorhinal cortex. Pathways were identified by ranking regions from highest to lowest SUVR, with the region displaying the highest SUVR value being defined as the peak region. Individuals in late stages of tau deposition displaying distinct pathways were compared. Image averages and voxel‐wise group comparisons using tau negative individuals as the reference were generated for each pathway and tau PET tracer. Cognitive differences were assessed using ANOVA for MoCA score and domain‐specific composite scores for Memory, Attention and Visuospatial skills. Result In all individuals and tracers, tau in the Entorhinal cortex progressed to the Limbic network, supporting a common starting point for tau propagation. Beyond these initial stages, tau propagation followed three main distinct pathways following either the Vis, Default or DorsAttn networks (Figure 1). Voxel‐wise comparison between individuals across these three pathways captured clear and similar differences in tau PET uptake as measured with Flortaucipir and MK6240. (Figure 2). While MoCA and Memory scores did not differ between groups, individuals following the Vis network exhibited significantly lower Attention scores compared to those in the Default and DorsAttn networks. Additionally, individuals following the Vis network exhibited lower Visuospatial scores compared to the Default network group (Figure 3). Conclusion Our results indicate a model in which, although tau progresses hierarchically, its deposition peaks mainly follow specific networks, which drive tau deposition and, consequently, the clinical manifestations of AD.