Abstract Background Amyloid‐Related Imaging Abnormalities (ARIA), an adverse event associated with Alzheimer's disease anti‐amyloid immunotherapies, occur in the form of edema or sulcal effusion (ARIA‐E) and microhemorrhages and superficial siderosis (ARIA‐H). Conventional teaching is that ARIA‐H is permanent hemosiderin staining of the brain. In clinical trials we have noticed that some ARIA‐H microhemorrhages that occur with regional ARIA‐E appear to later resolve. The goal of this study is to illustrate that, opposed to current understanding, some ARIA‐H microhemorrhages may resolve. Methods We identified participants from the Dominantly Inherited Alzheimer's Network Trial Unit (DIAN‐TU) and open label extension (OLE) gantenerumab studies that had ARIA‐E and at least one ARIA‐H microhemorrhage. The T2* GRE sequence from all available MRI exams in a patient were co‐registered and reviewed by a board‐certified neuroradiologist. Individual microhemorrhages were tracked over the serial exams. We defined disappearing/resolving microhemorrhages as those appeared with or following ARIA‐E, were visualized on at least 2 MRI exams, and were subsequently not visualized on at least 2 MRI exams. Results A total of 12 patients met inclusion criteria of which 5 (41%) had microhemorrhages that resolved over 10‐40 months follow‐up after the incident ARIA. These microhemorrhages occurred in clusters in the region of ARIA‐E, and only some of the regional microhemorrhages resolved over follow‐up. Examples are shown in Figures 1‐3. Conclusions The disappearance (resolution) of ARIA‐H microhemorrhages is relevant to the management and continued dosing of patients receiving anti‐amyloid immunotherapies as this is guided by the presence of ARIA (including cumulative treatment emergent microhemorrhages) as well as clinical symptoms. A microhemorrhage number alone may not be indicative of the potentially dynamic nature of ARIA‐H.
Multispot white matter hyperintensity pattern as a surrogate marker of cerebral amyloid angiopathy in the population
Abstract Background White matter hyperintensity topography, particularly posterior confluent and subcortical multispot (WMH‐MS), has been implicated as surrogate imaging biomarker of cerebral amyloid angiopathy (CAA). Usefulness of WMH‐MS for prediction of future cerebral microbleeds (CMB's) has significant clinical implications for anti‐amyloid therapy risk assessment. Our primary goal was to identify the prevalence of positive WMH‐MS status and their utility for predicting the incident CMBs in a population‐based sample. Our secondary goal was to evaluate its usefulness after accounting for amyloid (surrogate for CAA) and WMH burden (surrogate of small vessel disease) which are both risk factors for CMBs. Method We identified 651 participants (mean age (SD) 69.8 (10.0) years, 55% male) from the Mayo Clinic Study of Aging, who had 3T baseline whole brain fluid‐attenuated inversion recovery (FLAIR) MRI and at least two T2*‐weighted gradient recalled echo (GRE) sequences (concomitant with or after FLAIR) which were used to ascertain CMBs. Amyloid positron emission tomography (PiB‐PET) scans were available in 87% of the sample. Visual reads on FLAIR scans were performed using a 4‐point Fazekas rating scale of periventricular and deep WMH (positivity: Fazekas ≥ 2) and a 3‐point MS severity visual scale (positivity: nWMH‐MS > 10 circular or ovoid WMH spots, Figure 1) according to established criteria. Using univariate and multivariable logistic regression, we assessed the independent association of WMH‐MS > 10 and Fazekas ≥ 2 for prediction of incident CMB's. Result The frequency of WMH‐MS pattern was greater in those who developed an incident CMB compared to those who did not develop a CMB (20.8% vs. 2.8%, p < 0.001). Older age and male sex were predictive of incident CMBs (Figure 2A). In univariate models, presence of WMH‐MS pattern but not Fazekas was associated with incident CMBs after adjusting for age and sex. The associations remained significant after additional adjustment for APOE4 , hypertension, number of baseline CMBs (Prior CMB), and amyloid effects (Figure 2B). Conclusion Visually identified WMH‐MS patterns on FLAIR‐MRI were predictive of incident CMBs in this population and may be useful markers of CAA. Future studies evaluating its utility as an additional biomarker of amyloid related imaging abnormalities in clinical trials are necessary.
Comparing Age- and Sex-Specific Reference Values of eGFR between the United States and Europe
Clinical Journal of the American Society of Nephrology | December 26, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available
The extent to which eGFR varies across populations, in the absence of risk factors and comorbidities associated with kidney disease, remains uncertain. We aimed to develop eGFR reference values in healthy American adults and to compare them with previously described European eGFR reference values. This cross-sectional study compared newly described age-specific and sex-specific creatinine-based eGFR reference values from over 9000 healthy Americans from National Health and Nutrition Examination Survey with previously described eGFR reference values from over 1.5 million healthy individuals in the European CKD Burden Consortium. Health status was based on 14 criteria related to comorbidities, lifestyle factors, and medication use. eGFR was calculated using the European Kidney Function Consortium equation and modeled over the age span and by sex using a generalized additive model. The median eGFR in both 20-year-old American and European men was 98 ml/min per 1.73 m 2 . In both 20-year-old American and European women, the median eGFR was 101 ml/min per 1.73 m 2 . eGFR started to decrease at age 40 years, a result of the structure of the European Kidney Function Consortium equation. By age 79 years, the median eGFR in American and European men was 68 and 67 ml/min per 1.73 m 2 , respectively. The median eGFR in 79-year-old American and European women was 63 and 64 ml/min per 1.73 m 2 , respectively. When removing the effect of comorbidities, lifestyle factors and medication use associated with kidney function, achieved by restricting the analyses to individuals who did not have a presence or history of certain criteria, the distribution of eGFR was similar between healthy Americans and Europeans. This supports the notion that eGFR reference values may be generalizable to populations they were not derived from.
A conditional two‐step approach for detecting Lewy Body pathology: smell function testing and α‐synuclein seed amplification
Abstract Background Cerebrospinal fluid (CSF) seed amplification assays (SAAs) for detecting α‐synuclein (αsyn) seeds have recently emerged as robust in vivo biomarkers of Lewy body pathology (LBP). However, CSF sampling is invasive, costly, and time‐consuming, limiting its widespread use. We aimed to develop and evaluate a neuropathologically‐validated two‐step workflow, leveraging smell function and CSF αsyn SAA to accurately determine postmortem LBP status. This approach could reduce the number of confirmatory lumbar punctures needed (Figure 1). Methods The study included 358 individuals from the Arizona Study of Aging and Neurodegenerative Disorders with antemortem smell testing, CSF αsyn SAA results, and postmortem neuropathological assessments of regional LBP burden. Step‐1 of the two‐step workflow involved a risk‐stratification model predicting postmortem cortical LBP‐positivity (LBP ctx , defined as at least mild pathology in any cortical region) using logistic regression models with University of Pennsylvania Smell Identification Test (UPSIT) scores (smell testing), age, and sex as predictors. In step‐2, confirmatory CSF αsyn SAA testing was applied only to participants identified as high‐risk in step‐1. Workflow performance ‐ accuracy, positive predictive value (PPV), negative predictive value (NPV), and reduction in CSF testing ‐ was evaluated in (i) the entire study cohort; (ii) patients with clinical parkinsonism; (iii) patients with an Alzheimer's disease (AD) clinical syndrome; and (iv) clinically unimpaired (CU) individuals. Results Participants had a mean age at death of 86.2±7.8 years, 42.6% were female, 35.2% had LBP ctx , and the average time between UPSIT and death was 3.2±2.3 years (Table 1). Using a 95% sensitivity cut‐off for the UPSIT‐based algorithm, the two‐step workflow achieved high accuracy in identifying LBP ctx (whole cohort=94%; clinical parkinsonism=95%; clinical AD=94%; CU=93%; Figure 2a), while reducing CSF testing (whole cohort=‐43%; clinical parkinsonism=‐23%; clinical AD=‐35%; and CU=‐80%; Figure 2d). PPVs ranged from 75‐96% and were highest in the clinical parkinsonism subgroup (96%) where LBP ctx + was highest (62.7%). NPVs ranged between 95‐98% and were highest in the clinical AD subgroup (98%) (Figure 2b‐c). The two‐step approach reached accuracies similar to using CSF tests in all participants. Conclusions Implementing a two‐step workflow in different clinical scenarios may reduce invasive testing with CSF, minimizing the burden for individuals and costs for healthcare providers.
Early & late cerebrovascular biomarkers: Operationalization of cut‐points and temporal progression
Abstract Background Cerebrovascular disease (CeVD), a common co‐pathology with Alzheimer's Disease, has not been sufficiently operationalized, limiting its usage for accurate estimation of vascular contributions to cognitive impairment (VCI). The proposed CeVD biomarker classification uses more recently developed diffusion MRI markers (fractional anisotropy of Genu (FA), free water (FW), peak width of skeletonized mean diffusivity (PSMD), and ARTS score (ARTS)) as surrogates of early CeVD changes and white matter hyperintensities (WMH) as surrogate of late CeVD changes. Our primary goal was to characterize the temporal progression of these biomarkers to enhance CeVD biomarker staging. Our secondary goal was to establish cut‐points for normal/abnormal CeVD biomarkers. Methods Using CeVD biomarker data from 3,953 Mayo Clinic Study of Aging participants (split 80‐20 for training‐testing with training used for cut‐point estimation), we classified participants into VCI+/VCI‐ (Fazekas≥2 and Clinical Dementia Rating (CDR)≥0.5/not). We evaluated cut‐points using four criteria: specificity‐based, sensitivity‐based, accuracy young referent (VCI+ vs. 30‐49 yrs VCI‐), and accuracy age‐/sex‐matched referent (VCI+ vs. age‐/sex‐matched VCI‐). After selecting a cut‐point based on sensitivity and positive predictive value (PPV), we used nonlinear mixed‐effects (NLME) models to examine temporal progression in 2,047 participants (aged 43.39‐92.51 years, 47% female) with longitudinal data incorporating participant‐specific time shifts, correlations between random effects of each biomarker, and covariates (age, sex, vascular risk, education, APOE4 status). Results The accuracy young referent criterion produced the best sensitivity‐PPV tradeoff across all diffusion MRI markers (Figure 1). Diffusion MRI biomarkers consistently progressed 10 years earlier than WMH (Figure 2). Whole‐brain diffusion MRI measures (FW, PSMD, ARTS) were highly correlated with WMH, showing synchronized progression curves with a time offset. The regional genu measure (interhemispheric disconnection) progressed earlier with a steadier slope across decades and had comparatively lower correlation with WMH. Conclusions We developed cut‐points for diffusion MRI markers using classification of VCI based on Fazekas scale and CDR. Cut‐points from the accuracy young referent (VCI+ vs. 30‐49 yrs VCI‐) outperformed the accuracy age‐/sex‐matched referent (VCI+ vs. age‐/sex‐matched VCI‐), suggesting that older VCI‐ individuals may have unmeasured CeVD changes. Diffusion MRI markers progressed earlier relative to WMH, highlighting their potential for early detection, improved clinical assessment, and targeted interventions.
Precise Estimation Of Heterogenous Global Tau Burden In The Brain Sheds Light On Cognitive Resilience Mechanisms
Abstract Background Cognitive resilience to Alzheimer's disease (AD) pathology has been widely studied, but distinguishing resilient individuals from those with typical tau pathologies remains challenging due to the overlap in imaging and plasma biomarker profiles. We hypothesize that our machine learning‐based (ML) tau heterogeneity score, THETA (JNUMED, July 2024), could serve as an effective marker of resilience and provide a better estimation of tau's temporal progression. Method Longitudinal imaging data from the Mayo Clinic Study of Aging (MCSA, n = 1834) and ADRC ( n = 246) were analyzed. Participants were categorized into typical AD and resilient groups using amyloid PiB‐PET (abnormal PiB‐PET≥25 Centiloid units), Flortaucipir (FTP‐PET) (meta‐ROI≥1.29 SUVr, ERC≥1.27 SUVr) and Mini‐Mental State Examination (MMSE). Typical AD was defined as abnormal PiB‐PET and abnormal FTP‐PET for both biomarkers (Figure 1). Resilience to AD pathology was determined by predicted values of MMSE >28 from a linear mixed effects model for cognitively unimpaired participants. In addition, a resistant group was broadly defined as having normal PiB‐PET. To capture the spatial heterogeneity of tau distribution in the brain, regional THETA scores were generated using ML model and visual ratings. Additionally, a progression model, Sampled Iterative Local Approximation (SILA), was fitted using AD and plasma biomarkers ( p ‐tau181 and GFAP) for validation. Result THETA identified regions of reduced tau uptake in the frontal, parietal, temporal, occipital, and limbic regions when compared to the typical AD group (Figure 2A). This was confirmed by the preserved cortical thickness in these same regions (Figure 2D). In addition, SILA showed THETA can distinguish global tau temporal progressions of typical AD, resilient, and resistant groups compared to the other biomarkers (Figure 3). Interestingly, the onset age for GFAP was younger for resilient and typical AD, indicating earlier onset of inflammation in the presence of pathology. Conclusion The significant regions identified by THETA, showing reduced tau and preserved cortical thickness, combined with the clear offset in progression models between resilient and typical AD, suggest that THETA may help uncover pathological tau mechanisms that differentiate these groups. These findings highlight the potential of THETA to provide valuable insights into resilience mechanisms and enhance our understanding of AD.
Electronic Memory Support System (eMSS): An Innovative Digital Calendar and Training Program for Older Adults with Mild Cognitive Impairment
Abstract Background Individuals with mild cognitive impairment (MCI) experience challenges in maintaining independence in their instrumental activities of daily living (IADLs). The memory support system (MSS) is a paper‐based planner intervention to train individuals with MCI to complete personal goals and IADLs independently. As more individuals use electronic calendar systems, the MSS will need to adapt. This project aimed to develop and test an electronic prototype of the MSS (eMSS). Method Drawing on the MSS, an eMSS prototype intended for phone/tablet use was developed in Axure, allowing participants to interact with the planner and its sections (calendar, notes, to do list). The prototype was evaluated with MSS trainers and individuals with MCI and their partners using a computer or tablet over a virtual platform. Participants were asked to go through fictional ‘planning’ scenarios which were assessed using cognitive task analysis (CTA). The scenarios were designed to evaluate overall ease of use, and specifics such as navigation between pages/sections and developing schedules and task lists. During sessions, participants were encouraged to 'think aloud,' providing insight into their eMSS experience. Result To date, CTA has been conducted with 6 MSS trainers, and 2 patient/partner dyads that completed the MSS training program. Early results provide insight on strengths, challenges and opportunities to optimize the eMSS. Participants could identify and use key features (e.g., menus) and found the symbols and language consistent. However, participants didn’t notice some features (e.g., interactive arrows to navigate across dates) and requested more ‘cueing’ or ‘interactive prompts.’ Participants would prefer to see all information entered on individual pages (which is possible with the MSS) to support better situation awareness. Conclusion To respond to the everyday planning needs of individuals with MCI in a digital age, an eMSS was developed, drawing on a clinically trialed hardcopy version (MSS). Positive feedback from MSS trainers and patients with MCI and their partners suggests promise for the overall design. Improvements for the next iteration include designing cues to help users know actions have been completed or when to attend to important information, as well as providing more fulsome information on pages to support awareness of daily tasks.
Diagnostic performance of MK and Flortaucipir tau PET for the biological staging of Alzheimer disease
Abstract Background The Alzheimer's Association workgroup criteria (AA‐2024) suggest four biological stages based on PET imaging. However, the application of this framework may vary depending on the tau PET tracer used, and the distribution of clinical stages by biological stage may differ. Here, we aim to compare the diagnostic performance of the biological staging of Alzheimer Disease using two different tau PET tracers. Method We analyzed 446 individuals and further stratified 167 Aβ‐positive participants from the HEAD study (Longitudinal multicenter head‐to‐head harmonization of tau PET tracers) that underwent both MK‐6240 and Flortaucipir (FTP) tau PET. Four clinical stages (normal, transitional, MCI, and dementia) were defined based on the AA‐2024 criteria. Within stage‐2 we assessed subgroups: subjective cognitive decline (SCD), subtle objective cognitive decline (SOCD), and mild behavioral impairment (MBI). Logistic and linear models corrected by age and sex tested association of groups with amyloid and tau pathology. The biological staging was performed using tracer‐specific thresholds for regional SUVR and testing two regions of interest schemes: (i) proposed by AA‐2024 and (ii) Braak stages (Figure 1). Cohen's weighted‐kappa (K) statistic measured clinical‐biological agreement. Positive predictive value (PPV) of an individual being clinically impaired (MCI or dementia) was calculated for each biological stage. Result Clinical stages showed a progressively increased prevalence of Aβ‐positivity and higher entorhinal tau PET pathology from cognitively normal (CN) to SOCD, MCI, and dementia in both tracers. MBI and SCD transitional groups showed no increased Aβ or tau pathology compared to CN (Figure 2). For this reason, only SOCD was considered part of stage 2 for following analyses. All tested biological staging strategies showed moderate agreement (0.34‐0.59) with clinical stages using either tracers. The distribution of biological across clinical stages were similar for FTP and MK, with MK‐6240 showing lower PPV values in earlier stages than FTP (Table 1). Conclusion Our results support that AA‐2024 biological and clinical stages show similar clinical‐biological concordance using either Flortaucipir or MK‐6240, although this can vary based on methods tested in the study. The MBI and SCD clinical subgroups showed no difference of pathological burden to clinical stage 1, while SOCD transitional stage showed higher burden compared to stage 1.
Immunotherapeutic potential of “Breg-Treg” vs “Th9-Th17” cell axis in post-menopausal osteoporosis
ABSTRACT Photogrammetry has emerged as a powerful tool in medical education, offering precise and cost‐effective 3D anatomical models that enhance spatial learning and accessibility. This systematic review synthesizes evidence from forty‐eight (48) peer‐reviewed studies (2000–2025) to evaluate photogrammetry's applications, technical workflows, and educational outcomes in anatomy and surgical training. Findings demonstrate its effectiveness across training levels, with high learner satisfaction (e.g., 96.4% preference over traditional methods) and sub‐millimeter accuracy in rendering complex structures like neuroanatomy and musculoskeletal systems. Photogrammetry's adaptability for remote learning and specimen preservation addresses critical gaps in resource‐limited settings. However, challenges persist, including the lack of tactile feedback and difficulties in visualizing deep anatomical relationships. Future directions should focus on integrating artificial intelligence (AI)‐assisted processing, hybrid digital–physical models, and immersive technologies like virtual reality (VR)/augmented reality (AR) to bridge these gaps. By balancing innovation with evidence‐based implementation, photogrammetry can further solidify its role as a transformative adjunct in modern medical curricula.