bluuebunny/crossref_metadata_2025_split huggingface dataset:
The atrophy of specific amygdala subnuclei is associated with temporal tauopathy in preclinical AD individuals
Authors: Salman Yasmine , Gérard Thomas , Huyghe Lara , Colmant Lise , Quenon Lisa , Malotaux Vincent , Boyer Emilien , Ivanoiu Adrian , Lhommel Renaud , Dricot Laurence , Hanseeuw Bernard J 
Published: January 2025

AbstractBackgroundIn AD, tauopathy and atrophy start in the mesiotemporal lobe, including the amygdala‐hippocampal complex. Until recently, subnuclei and subfields within these structures were indistinguishable in‐vivo. FreeSurfer 7.0 now enables their segmentation. Our goal was to study hippocampal and amygdala subregions’ atrophy in preclinical AD to assess whether specific subregion atrophy could indicate early tauopathy at the preclinical stage.MethodsWe conducted an exploratory study in the ADNI3 cohort including 144 amyloid‐positive cognitively‐normal adults (Aß+CN) with 3DT1‐MRI and [18F]AV‐1451 Tau‐PET data. We identified hippocampal and amygdala subregions explaining at least 1% of the variance of the Tau‐PET signal from the temporal meta‐ROI defined by Jack (2017). We validated these results with our in‐house data, including 112 individuals with 3DT1‐MRI and [18F]MK6240 Tau‐PET scans. Groups were categorized by visual Braak‐stage or bioclinical classification based on cognition (CN/MCI) and amyloid status (Aß‐/Aß+).ResultsIn ADNI3, amygdala and hippocampal volumes were not associated with temporal tauopathy in Aß+CN (R²<0.001). However, four amygdala subnuclei (cortical, central, medial, and accessory‐basal nuclei) out of nine and the hippocampal tail (out of twelve subfields) each explained over 1% of the variance in temporal tauopathy in Aß+CN (one‐tail p<0.10). These tau‐associated subnuclei were pooled into an amygdala aggregate whose volume was significantly associated with temporal tauopathy in Aß+CN, even after adjusting for amygdala volume. In Aß+MCI (n=132), global structure volumes were significantly associated with temporal tauopathy, with subnuclei atrophy adding no explanatory power (Figure 1). Within our in‐house data, individuals with early Tau‐PET signal (Braak I‐II) had similar global amygdala and hippocampal volumes than Braak 0 individuals. However, the tau‐associated amygdala aggregate generated in ADNI3 was significantly smaller in Braak I‐II individuals. Similarly, only the aggregate was significantly smaller in Aß+CN compared to Aß‐CN (Figure 2). These results remained significant after adjusting for global structures (Figure 3).ConclusionWe identified four amygdalae subnuclei whose atrophy is earlier than global amygdala. Atrophy in these subnuclei is associated with temporal tauopathy in preclinical AD, distinguishing visual Braak‐stage I‐II from Braak‐stage 0 individuals. Measuring amygdala subnuclei volumes in older adults is a promising approach to identify individuals at‐risk of progression to clinical AD.
The importance of AT(N)‐V imaging biomarkers differs in diverse populations
Authors: Meeker Karin L. 
Published: January 2025

AbstractBackgroundInvestigations into the amyloid, tau, and neurodegeneration (ATN) framework, which is used to stage Alzheimer disease (AD) and advance clinical trials, typically consist of clinic‐based non‐Hispanic White (NHW) populations. The present study sought to cross‐sectionally characterize AT(N) and vascular (V) imaging markers (i.e., amyloid and tau positron emission tomography [PET], AD cortical thickness signature, and white matter hyperintensities), and determine the relative importance of each marker in predicting cognitive status (Clinical Dementia Rating Scale Sum of Boxes) in a large ethnically and racially diverse sample.MethodData were obtained from the community‐based Health and Aging Brain Study – Health Disparities (HABS‐HD) and included Mexican Americans (MAs, n=669), African Americans (AAs, n=747), and NHWs (n=768). Group differences in AT(N)‐V biomarkers were assessed using Kruskal Wallis ANOVAs. Age and gender were included as covariates. Dominance analysis determined the relative ‘importance’ of each biomarker in predicting cognitive status in the entire cohort and separately for each group. All analyses were performed for the entire cohort, and for individuals on the AD trajectory (i.e., amyloid PET+).ResultAcross the entire cohort, amyloid was significantly greater in AAs compared to NHWs (p’s < 0.01). Tau and neurodegeneration were greater in MAs and AAs compared to NHWs (p’s < 0.01). White matter hyperintensities were greater in AAs and NHWs compared to MAs (p’s < 0.01). There were no significant group differences in AT(N)‐V measures in individuals who were amyloid PET+ (p’s > 0.05). In the entire cohort, A was the most important biomarker (as evidenced by greater R2 values; see Figure 1) in predicting cognitive status. In MAs and AAs, A was also the most important while in NHWs, T was the most important. When constraining to amyloid PET+ individuals, T was most important across all individuals and in NHWs while N was most important in MAs and AAs.ConclusionThese results are important for evaluation of the new AT(N) criteria and suggest that the magnitude and overall contributions of AT(N)‐V imaging biomarkers in predicting cognitive outcomes may vary among ethno‐racial groups. Possible differential effects of AD biomarkers should be considered in research, clinical trials, and response to treatment.
Enhancing the insights of the Patient‐and care‐related benefits of amyloid PET imaging ‐ ENABLE ‐ study through a process evaluation: a study protocol
Authors: Grazia Alice , Goerss Doreen , Spottke Annika , Boecker Henning , Daamen Marcel , Graf Erika , Sahlmann Jörg , Buchert Ralph , Mohnike Wolfgang , Mohnike Konrad , Jessen Frank , Krause Bernd J , Boccardi Marina , Teipel Stefan , Kurth Jens 
Published: January 2025

AbstractBackgroundAmyloid PET imaging is an established diagnostic tool for Alzheimer’s disease, but its successful integration into clinical practice requires a comprehensive understanding of its impact on patients and the healthcare system. In 2022, the coverage with evidence development (CED) ENABLE study has been approved by the German Federal Joint Committee (trial registration: DRKS00030839). The study is scheduled to start in early 2024. Primary outcome of ENABLE is the change in patients' functional abilities at 18 months after diagnosis with amyloid PET versus without amyloid‐PET. Here we describe the design of an ENABLE sub‐study aimed at performing a process evaluation.MethodWe will conduct an outcome and process evaluation using a pre‐post descriptive design nested in ENABLE (Figure), based on the Medical Research Council’s Process Evaluation (PE) framework. The PE will focus on acceptability and reach of the target groups of patients and care providers, as well as fidelity of delivery (% of adherence to protocol, study duration), contextual changes and mechanisms (e.g., ability to mirror routine care). We will collect patients’ data independently, but in parallel with ENABLE, using interviews, surveys and checklists to assess acceptance of the intervention, fidelity of adherence to the follow‐up procedures, perceived benefits and challenges. Healthcare providers and administrators will be interviewed to identify implementation hurdles and facilitators, contextual factors influencing uptake and underlying mechanisms. For data analysis we will employ a mixed‐methods approach.ResultExpected outcomes will include acceptability and adherence, barriers and facilitators to implementation, contextual factors influencing implementation, perceived utility of the intervention by patients and providers, and mechanisms by which the intervention can be delivered as part of normal care.ConclusionThis process evaluation can inform researchers on how to design future CED studies to be implemented into clinical care. The lessons learned during the development and approval process of the ENABLE project in Germany, as well as its process evaluation, can benefit other European CED studies and policy‐makers stakeholders in making informed decisions. Likewise, these findings can be generalized beyond the context of amyloid PET to other diagnostic biomarkers, ultimately improving the diagnosis and management of Alzheimer’s disease.
The association between tau pathology and later stages of memory processing is mediated by medial temporal lobe atrophy in typical Alzheimer's Disease
Authors: Wuestefeld Anika , Cui Salena , Das Sandhitsu R. , Xie Long , McGrew Emily , Yushkevich Paul A. , Wisse Laura , Wolk David A 
Published: January 2025

AbstractBackgroundTau pathology is closely related to cognitive decline in Alzheimer’s disease (AD). Neurodegeneration is the putative mechanism by which tau leads to cognitive deficits. However, there is limited work on the associations between tau, neurodegeneration, and specific cognitive domains. We investigate potential mediating effects of medial temporal lobe (MTL) and neocortical neurodegeneration for different cognitive domains in amyloid‐ß‐positive (Aß+) adults.MethodWe included 325 positron emission tomography (PET) Aß+ individuals across the AD spectrum from the Alzheimer’s Disease Neuroimaging Initiative (age: 72±8 [55–90]; 51.1% female, education: 16±2 years). Hippocampal volume and cortical thickness were measured from T1‐weighted structural magnetic resonance imaging in typical AD regions (Fig. 1). Using flortaucipir‐PET, tau was quantified for two composite regions (MTL, neocortical). Included cognitive measures are shown in Fig. 1. Mediation analyses between tau‐PET, thickness/volume, and cognition were performed. Cognitive measures were adjusted to isolate the function of interest (Fig. 1).ResultHigher tau‐PET uptake and lower thickness were associated with lower performance on all cognitive measures. In simple mediations, tau‐immediate recall associations were mediated by MTL, parietal, and temporal regions (Fig. 2A). Tau‐delayed recall associations were mediated by MTL regions. Tau‐late recall and tau‐recognition associations were mediated by MTL and parietal regions. Tau‐fluency and tau‐executive functioning associations were mediated by MTL and parietal regions, as well as temporal regions for fluency. Complex mediations investigated significant mediators simultaneously (Fig. 2B+3). Depending if MTL/neocortical tau remained significant when covarying for the other tau measure in a regression, the complex mediation models focused on MTL and/or neocortical regions (Fig. 2B description). Hippocampus mediated the tau‐late recall and tau‐recognition associations. Brodmann area 35 mediated the tau‐delayed recall association. Tau‐fluency was, at a trend level, mediated by inferior temporal thickness. Tau‐executive functioning did not demonstrate a mediation effect, potentially due to limited frontal atrophy. All mediators were partial mediators explaining up to 23% of variance.ConclusionThe results suggest that MTL tau pathology, partially mediated by macrostructural changes, lead to impairments in specific memory domains in early AD. Impairments in fluency and executive functioning, however, seem more likely to follow from tau‐induced effects in neocortical regions.
Visual classification of tau‐PET detects four subtypes with different long‐term outcomes
Authors: Boccalini Cecilia , Mathoux Gregory , Hristovska Ines , Ribaldi Federica , Peretti Débora Elisa , Arnone Annachiara , Scheffler Max , Frisoni Giovanni B. , Hansson Oskar , Vogel Jacob W. , Garibotto Valentina 
Published: January 2025

AbstractBackgroundSubstantial variability in tau accumulation patterns in Alzheimer’s disease (AD) population has now become accepted. Subtype and Stage Inference (SuStaIn) has distinguished four distinct spatiotemporal trajectories of tau pathology: limbic (S1), medial temporal lobe‐sparing (S2), posterior (S3), and lateral temporal (S4). A visual method to validate and identify them is a requirement for their clinical translation. Our study aims to provide evidence for multiple tau accumulation patterns in a clinical setting by developing and testing a novel topographic visual method for tau‐PET based on SuStaIn subtypes.MethodWe included 245 participants from the Geneva Memory Clinic, who underwent 18F‐Flortaucipir‐PET. All scans were classified into different subtypes by visual ratings and the automated SuStain algorithm. Cohen’s kappa (k) tested the agreement between raters and between visual and automated subtypes. Chi‐squared and Kruskal‐Wallis tests were used to test differences in clinical features, tau, and amyloid (Aß) loads between subtypes. Differences in cognitive trajectories were tested using linear mixed‐effects models, controlling for age, sex, and tau stages.ResultA substantial agreement between raters was found in visually interpreting tau pattern subtypes (k>0.65,p<0.001) and a fair agreement between visual and automated subtypes (k = 0.39,p<0.001), with the automated approach detecting a higher rate of negative scans. According to the visual classification, individuals with S2 subtype were younger than S1 and S3 (p<0.001), had worse MMSE and verbal fluency scores (p<0.05) than S4 and S1, showed higher global tau than other subtypes (p<0.05), and a steeper cognitive decline.ConclusionOur results show that visual classification can reliably identify four tau patterns, differing in global tau loads, clinical characteristics, and long‐term outcomes, suggesting its clinical usefulness for the detection of higher‐risk AD variants. A clinically implementable classification in subtypes with faster decline is paramount for personalized diagnosis and therapy.
Comparison of tau‐PET tracers for in vivo Braak staging: the HEAD Study
Authors: Macedo Arthur C. , Therriault Joseph , Rahmouni Nesrine , Servaes Stijn , Wang Yi‐Ting , Tissot Cécile , Lussier Firoza Z , Arias Jaime Fernandez , Socualaya Kely Monica Quispialaya , Hosseini Seyyed Ali , Ferreira Pamela C.L. , Bellaver Bruna , Ferrari‐Souza João Pedro , Aguzzoli Cristiano Schaffer , Povala Guilherme , Pascual Belen , Gordon Brian A. , Lowe Val J. , Oh Hwamee , Soleimani‐Meigooni David N. , Baker Suzanne L. , Pascoal Tharick Ali , Rosa‐Neto Pedro 
Published: January 2025

AbstractBackgroundTau‐PET tracers allow for in vivo Braak staging of individuals in the Alzheimer’s disease (AD) continuum. The impact of tracers’ characteristics for Braak staging using tau‐PET remains unclear. Therefore, we performed a head‐to‐head comparison of Braak staging using first‐ and second‐generation tau‐PET tracers.MethodWe assessed 51 cognitively unimpaired (CU) and 49 cognitively impaired participants (mean [SD] age 69.4 [7.5] years) with at least two tau‐PET ligands ([18F]MK6240, [18F]AV1451, and/or [18F]RO948) at McGill University, as part of the HEAD study. We calculated standardized uptake value ratios (SUVR) in Braak‐like regions of interest (ROI) for each ligand and investigated their association using Spearman’s correlation. Thresholds defined the presence of tauopathy in each Braak ROI, which was used to assign a Braak stage to each participant. Finally, we assessed the agreement between the Braak staging provided by each tracer, both for the traditional (using separate Braak stages – 0, I, II, III, IV, V, and VI) and simplified (using joint Braak stages – 0, I‐II, III‐IV, and V‐VI) frameworks.ResultIn all Braak ROIs, we found positive correlations between the SUVR values of the three tracers (Fig. 1). The strongest correlation was between [18F]MK6240 and [18F]RO948 in Braak II (r=0.94), and the weakest between [18F]AV1451 and [18F]RO948 in VI (r=0.51). Inter‐tracer agreement regarding the latest stage of abnormality was substantial or nearly perfect between pairs of tracers but moderate between the three tracers (Fig. 2A). The simplified framework presented greater agreement compared to traditional Braak staging, except between [18F]MK6240 and [18F]RO948. At the ROI level, the lowest agreements were observed for Braak II and I‐II, when [18F]MK6240 and [18F]RO948 were compared to [18F]AV1451 (Fig. 2B‐C). [18F]AV1451 had the highest probability of overestimating the Braak stage assigned by [18F]MK6240 and by [18F]RO948, especially at earlier stages (Fig. 3).ConclusionThe ligands presented moderate to nearly perfect agreement for in vivo staging of AD severity. Off‐target binding of [18F]AV1451 to the choroid plexus might explain disagreements at early stages. Overall, slight improvements in agreements were achieved with the simplified framework, as observed in histopathological staging.
Neuropsychiatric symptoms and brain aging in mild cognitive impairment and early dementia: A multicenter study
Authors: Sone Daichi , Beheshti Iman , Tagai Kenji , Kameyama Hiroshi , Takasaki Emi , Kashibayashi Tetsuo , Takahashi Ryuichi , Ishii Kazunari , Kanemoto Hideki , Ikeda Manabu , Shigeta Masahiro , Shinagawa Shunichiro , Kazui Hiroaki 
Published: January 2025

AbstractBackgroundDespite the clinical importance and significant social burden of neuropsychiatric symptoms (NPS) in dementia, the underlying neurobiological mechanism remains poorly understood. Recently, neuroimaging‐derived brain‐age estimation by machine‐learning analysis has shown promise as an individual‐level biomarker. We investigated the relationship between NPS and brain‐age in amnestic mild cognitive impairment (MCI) and early dementia.MethodClinical data, including neuropsychiatric inventory (NPI), and structural brain MRI of 499 individuals with clinical diagnoses of amnestic MCI (N=185), early Alzheimer’s disease (AD) (N=258) or dementia with Lewy bodies (DLB) (N=56) were analyzed. We established a brain‐age prediction model using 694 brain structural MRI scans of healthy subjects and support vector regression model and applied it to the patients’ data. Finally, the brain predicted age difference (brain‐PAD: predicted age minus chronological age) were calculated.ResultAll clinical diagnostic groups showed significantly increased brain‐PAD, and the median (IQR) brain‐PAD was 4.3 (5.4) years in MCI, 6.3 (6.2) years in AD, and 5.0 (6.5) years in DLB. The NPI scores were subdivided into the following four categories: (i) Agitation and Irritability, (ii) Depression and Apathy, (iii) Delusions and Hallucinations, and (iv) Euphoria and Disinhibition. We found a significantly positive correlation between brain‐PAD and the depression/apathy factor (Spearman’s rs = 0.156, FDR‐corrected p=0.002), while no significance was shown in the other NPS factors.ConclusionAbnormal brain aging may be involved in depression and apathy symptoms presented in MCI to early dementia stages, and brain‐age analysis may be useful as a novel biomarker for assessment or monitoring of NPS.
Sleep and Physical Activity are Associated with Cognition and Resting‐State Functional Imaging Measures of Network Segregation in Non‐demented Older Adults
Authors: Callow Daniel 
Published: January 2025

AbstractBackgroundGreater physical activity and better sleep are associated with reduced risk of cognitive decline and dementia among older adults, but little is known about their associations with measures of brain function and neuropathology.MethodThis study investigated potential independent and interactive cross‐sectional relationships between actigraphy‐estimated total volume of physical activity (TVPA) and sleep patterns [i.e., total sleep time (TST), sleep efficiency (SE)] with cognitive performance (n = 157). In a subset of participants, the physical activity and sleep measures were also evaluated in relationship to resting‐state functional magnetic resonance imaging (rs‐fMRI) measures of large‐scale network connectivity, and positron emission tomography (PET) measures of amyloid‐ß (n = 135). Participants were part of the BIOCARD study including 136 cognitively normal individuals and 21 participants with mild cognitive impairment (mean age = 71.7 years). Using linear regression analyses, we assessed the association between TVPA, TST, and SE with cognition, connectivity within the default‐mode, salience, and fronto‐parietal control networks, and with network modularity, a measure of network segregation.ResultGreater TVPA and SE each were positively associated with better global cognitive composite scores and executive function. Importantly, a TVPA by SE interaction suggested that adults with the poorest SE experienced the greatest benefit from physical activity in relation to cognition. In the imaging subsample, higher TVPA and SE were independently associated with greater network modularity, although the positive relationship of SE with modularity was only present in amyloid‐negative individuals. Additionally, higher TVPA was associated with greater connectivity within the default‐mode network, while greater SE was related to greater connectivity within the salience network. In contrast, longer TST was associated with lower network modularity, particularly among amyloid‐positive individuals, suggesting a relationship between longer sleep duration and greater network disorganization. Physical activity and sleep measures were not associated with amyloid positivity.ConclusionThese data suggest that greater physical activity levels and more efficient sleep may promote better cognition and more segregated and potentially resilient functional networks, as well as greater functional connectivity within specific large‐scale networks. Additionally, the relationship between sleep and functional networks connectivity may depend on amyloid status while associations with physical activity may be independent of amyloid status.
Investigating Spatial Characteristics of Brain Atrophy in Alzheimer's and LATE neuropathology
Authors: Saifullah Khalid , Ridwan Abdur Raquib , Bennett David A. , Schneider Julie A. , Arfanakis Konstantinos 
Published: January 2025

AbstractBackgroundAlzheimer’s disease neuropathologic change (AD‐NC) and limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC) are common in older adults and have been associated with brain atrophy, cognitive decline, and dementia. Since AD‐NC and LATE‐NC are often comorbid and due to the fact that LATE‐NC can only be detected at autopsy, in this work, we combined deformation‐based morphometry (DBM) on ex‐vivo brain MRI and detailed neuropathological evaluation in a large number of community‐based older adults to investigate the difference in brain atrophy patterns associated with AD‐NC and LATE‐NC.MethodCerebral hemispheres from 912 older adults participating in four longitudinal, clinical‐pathologic cohort studies of aging were included in this work: MAP, ROS, MARS, and AA Core of the Rush Alzheimer’s Disease Research Center (Rush ADRC) (Figure 1). All hemispheres were imaged ex‐vivo on 3T clinical MRI scanners approximately 1‐month postmortem while immersed in 4% formaldehyde solution. T2‐weighted images of all hemispheres were non‐linearly registered and logarithm of the Jacobian determinant (LogJ) of the deformation field was calculated in each voxel. Following ex‐vivo MRI, the pathologies that were assessed were AD‐NC, LATE‐NC, Lewy bodies, gross infarcts, microscopic infarcts, arteriolosclerosis, atherosclerosis, and cerebral amyloid angiopathy. AD‐NC‐pos was defined as moderate or severe AD‐NC according to the NIA‐AA criteria, and LATE‐NC‐pos was defined as LATE‐NC stages 2 or 3. Voxel‐wise linear regression was used to test the association of the deformations observed in the smoothed log Jacobian maps with the four different groups, controlling for all other neuropathologies, demographics, postmortem intervals, and scanner. We used 5000 permutations, and statistical significance was set at p<0.05 after family wise error (FWE) correction.ResultBoth the AD‐NC‐pos LATE‐NC‐neg group (Figure 2a) as well as the AD‐NC‐neg LATE‐NC‐pos group (Figure 2b) were associated with lower tissue volume mainly in medial temporal lobe structures. The AD‐NC‐pos LATE‐NC‐pos group (Figure 2c) showed substantially lower volume in the temporal, frontal, and parietal lobes. Interestingly, the AD‐NC‐neg LATE‐NC‐pos group showed lower volume in the anterior portion of the hippocampus than the AD‐NC‐pos LATE‐NC‐neg group (Figure 2d).ConclusionThe findings suggest that in the presence of LATE‐NC, the volume of the hippocampus cannot serve as a marker of AD‐NC.