bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cross‐cohort epigenome‐wide association study in Alzheimer's disease risk and related traits
Authors: Milicic Lidija , Vacher Michael , Porter Tenielle , Dore Vincent , Bourgeat Pierrick , Doecke James D. , Shishegar Rosita , Maruff Paul , Masters Colin L. , Rowe Christopher C. , Villemagne Victor L , Laws Simon M. 
Published: January 2025

AbstractBackgroundEpigenome‐wide association studies (EWAS) have identified multiple loci that are differentially methylated in Alzheimer’s disease (AD). However, for complex diseases such as AD, single methylation sites associated with disease and disease‐related traits have relatively low effect sizes. At the genetic level, measures of cumulative genetic risk, such as polygenetic risk scores, have yielded success in risk prediction as well as in association and interaction studies. Such approaches have the potential to be directly transferred to DNA methylation data.MethodThis study utilised data from two well‐characterised longitudinal cohort studies, the Australian Imaging, Biomarker and Lifestyle (AIBL) study (n=707) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI; n=620) and aimed to investigate the association between peripheral blood DNA methylation, at CpG sites across the epigenome, and eight AD‐related phenotypes: AD risk, MRI‐derived brain volumetric measures (hippocampal, ventricle, grey and white matter volumes), PET derived brain Aß‐amyloid burden (as a continuous and binary (high/low) variable) and cognition (Pre‐Alzheimer’s Cognitive Composite (PACC)). Each trait‐specific EWAS was first undertaken in the AIBL cohort, and eight trait‐specific methylation risk scores (MRS) were then developed using summary statistics. An additional MRS was also developed using an elastic net machine learning method. MRSs were then validated within and across traits in the ADNI cohort.ResultNominally significant associations were observed between CpG sites within several of the EWAS that were performed; however, no individual CpG sites remained significant after FDR correction. Several MRSs were associated with AD risk after correction for the false discovery rate.ConclusionWhile this study adds to the growing literature supporting the role of MRSs in AD‐related traits, it suggests that there are limited associations of individual epigenome‐wide CpG sites with cognitive and neuroimaging traits using the methods undertaken in this study. Future studies with larger cohort sizes and phenotypically rich datasets will help to confirm these findings and potentially elucidate further associations.
Associations between imaging biomarkers and sleep quality in the U.S. POINTER study baseline cohort
Authors: Winer Joseph R. , Ward Tyler J. , Scales Margaret , Taggett Jacinda , Howard Marjorie , Stone Katie L , Lockhart Samuel N. , Baker Laura D , Hayden Kathleen M. , Landau Susan M. , Harrison Theresa M. 
Published: January 2025

AbstractBackgroundWorse sleep is associated with a greater risk of Alzheimer’s disease (AD). However, few studies have linked objective sleep with neuroimaging outcomes, limiting our understanding of how poor sleep impacts the brain. The U.S. POINTER trial, which has enrolled a heterogeneous cohort of older adults at elevated risk for cognitive decline, is a unique sample differing from prior investigations of sleep, aging, and brain health. Here we investigate how actigraphy‐assessed sleep duration and efficiency are cross‐sectionally associated with baseline neuroimaging measures of brain structure and AD pathology.MethodParticipants underwent neuroimaging (MRI, 18F‐florbetaben amyloid PET, and 18F‐MK6240 tau PET), cognitive testing, and wristwatch actigraphy, which assessed sleep duration and sleep efficiency averaged across six nights. Imaging analyses focused on bilateral entorhinal tau PET, cortical amyloid PET, hippocampal volume, white matter hyperintensity (WMH) volume, and diffusion free water. Based on prior literature suggesting short and long sleep duration are disadvantageous, quadratic models were fit for sleep duration predicting neuroimaging and cognitive measures, with age, sex, years of education, body mass index, and self‐identified racial ethnic category as covariates. Linear models were fit for sleep efficiency with the same covariates.ResultAcross 454 participants (Table 1), sleep measures were not related to cognition. Hippocampal volume, WMH volume, and free water showed U‐shaped relationships with sleep duration such that average sleep durations shorter and longer than approximately 6‐7 hours were associated with worse brain health outcomes (Figure 1). There were no associations between tau or amyloid PET and sleep duration. When stratified by amyloid status, associations between sleep duration and brain structure were significant in only the amyloid negative group. Unexpectedly, there were no associations between neuroimaging measures and sleep efficiency except for a significant positive relationship with entorhinal tau PET uptake.ConclusionIn the largest and most heterogeneous sample to date of older adults with actigraphy and neuroimaging measures, sleep duration was associated with multiple measures of brain structure but not AD pathology. These relationships may reflect heterogeneity and selection characteristics of the at‐risk POINTER cohort, which differ from previous studies of sleep and AD biomarkers.
The association between the age and the rate of tau accumulation and spreading in different sexes
Authors: Zhu Zeyu , Dehsarvi Amir , Roemer Sebastian Niclas , Steward Anna , Dewenter Anna , Gross Mattes , Wagner Fabian , Ewers Michael , Brendel Matthias , Franzmeier Nicolai 
Published: January 2025

AbstractBackgroundNeuroimaging studies have revealed age and sex‐specific differences in Alzheimer’s disease (AD) trajectories. However, how age and sex modulate tau spreading remains unclear. Thus, we investigated how age and sex modulate the amyloid‐beta (Aß)‐induced accumulation and spreading of tau pathology from local epicenters across connected brain regions.MethodWe included 313 ADNI participants (female/male, n=167/146), i.e. 110 cognitively normal (CN) Aß‐negative, and 203 Aß‐positive subjects across the AD spectrum (i.e. CN/MCI/Dementia, n=98/70/35) with baseline amyloid‐PET and longitudinal Flortaucipir tau‐PET. Annual tau‐PET change rates for 200 cortical regions of the Schaefer atlas were calculated. Sex‐specific resting‐state fMRI‐connectivity templates across the 200 Schaefer regions were determined in independent Aß‐negative controls (female/male, n=118/82) to determine the connectivity of tau epicenters to the rest of the brain. Using linear regression, we investigated interactions between age, sex and Aß on tau accumulation and spread, controlling for APOE4‐status and diagnosis.ResultHigher Aß (i.e. centiloid) predicted faster tau accumulation, where this association was pronounced in younger individuals (i.e. age x centiloid interaction, b=‐3.64, p<0.001, Figure 1A). This age x centiloid interaction was stronger in men (b=‐4.82, p<0.001, Figure 1B) vs. women (b=‐1.67, p=0.029, Figure 1C), suggesting that younger age promotes Aß‐related tau accumulation predominantly in men. Bootstrapping analysis further confirmed this effect (Figure 1D). In Aß+, epicenters with highest baseline tau‐PET showed a similar temporal‐lobe distribution in men and women (Figure 2A&B), yet epicenter connectivity to the rest of the brain was stronger in men vs. women (Figure 2C). Stronger connectivity of tau epicenters to the rest of the brain was linked to faster tau accumulation especially in younger Aß+ subjects (i.e. interaction age x epicenter connectivity, b= 4.41, p<0.001, Figure 3A). However, this effect was clearly driven by men (b=6.13, p<0.001, Figure 3B) and not observed when tested in women only (b=1.55, p=0.252, Figure 3C).ConclusionAß drives faster tau accumulation and this effect is particularly strong at younger age and even further pronounced in men, whose tau epicenters are more densely interconnected with the rest of the brain. Together, age and sex have clear modulating effects on tau spreading, and heterogeneous AD trajectories may be partly arisen due to sex‐specific differences in brain network architecture.
Distinct Spatial Patterns for White Matter Microstructure Changes in an Aging and Alzheimer's Disease Cohort
Authors: Tian Jianqiao , Raghavan Sheelakumari , Cogswell Petrice M , Reid Robert I. , Przybelski Scott A. , Schwarz Christopher G. , Graff‐Radford Jonathan , Lowe Val J. , Kantarci Kejal , Knopman David S. , Petersen Ronald C. , Jack Clifford R. , Vemuri Prashanthi 
Published: January 2025

AbstractBackgroundWhite matter (WM) damage is seen with neurodegenerative and cerebrovascular pathologies and contributes to cognitive dysfunction. We hypothesized that there are multiple disease progression patterns in WM microstructural changes related to aging and dementia, and these can be identified using SuStaIn (data‐driven clustering algorithm for disease subtype and stage discovery) on multishell diffusion MRI (NODDI) data. NODDI provides information on cellular tissue architecture – neurite density index (NDI) measures packing density of axons and dendrites, and free water fraction (FWF) measures unrestricted water, e.g., interstitial and cerebrospinal fluid.MethodWe identified 1136 participants (mean age=70 years, 51% male, 40% Aß‐positive, 19% MCI/AD dementia) from the Mayo ADRC and Mayo Clinic Study of Aging. We analyzed NDI and FWF in 55 WM regions. We selected a subset of WM features that monotonically changed with clinical disease progression and then applied the Z‐score SuStaIn algorithm.ResultNDI in seven regions and FWF in six regions survived selection criteria (Figure 1). Noteworthy, the NDI regions were predominantly located in the temporal lobe, while FWF regions were primarily distributed in the frontal and subcortical regions. The SuStaIn algorithm discovered two stable clusters: the NDI‐First (Temporal) and FWF‐First (Frontal) groups (Figure 2). For the NDI‐First group, temporal lobe NDI changed early followed by frontal FWF. The FWF‐First group had the reverse order. There was clear phase separation based on which measure changed first. Stages of the NDI‐First group correlated better with meta‐ROI Tau‐PET SUVR and with MMSE than the FWF‐First group (p<0.01), suggesting that NDI‐First may be indicative of a primarily AD pathway.ConclusionGiven NDI changes are likely degenerative and FWF are suggested to be other processes such as neurodegeneration or inflammatory, the observed changes in the temporal and frontal regions may be due to distinct etiologies, i.e., neurodegenerative in the temporal lobes vs. vascular dysfunction often observed in the frontal lobes. The SuStaIn algorithm showed promise in discovering disease subtypes of WM microstructural changes. Further work is needed to understand the mechanistic basis of these observed changes and integrate WM changes for differential etiology identification and disease staging.
MRI Assessment of Healthy Aging Trajectories in the Marmoset Brain
Authors: Szczupak Diego , Bhik‐Ghanie Rebecca , Zhang Bei , Papoti Daniel , Campos Vinicius , Dubberley Lauren R , Hitchens T Kevin , Yeh Fang‐Cheng , Schaeffer Lauren K Hayrynen , Carter Gregory W , Rizzo Stacey J Sukoff , Schaeffer David J , Silva Afonso C 
Published: January 2025

AbstractBackgroundThe common marmoset (Callithrix jacchus) is an important animal model in neuroscience and neurological diseases (e.g., Alzheimer’s disease ‐ AD), as they present primate‐specific evolutionary features such as an expanded frontal cortex. We established a new consortium with funding support from the National Institute on Aging to generate, characterize, and validate MArmosets as Research MOdels of AD (MARMO‐AD). This consortium develops and studies gene‐edited marmoset models carrying genetic risk for AD, comparing them against wild‐type aging marmosets from birth throughout their lifespan, using non‐invasive longitudinal assessments. Here, we aim to characterize healthy aging trajectories of regional brain volume in a population of marmosets.MethodsWe imaged a cohort of 59 marmosets ( 45 males, 14 females) across the lifespan (8 to 150 months) using a dedicated 9.4T 30cm bore MRI scanner (Bruker BioSpin Corp, Billerica). The animals were anesthetized under isoflurane and maintained under normal physiological conditions. High‐resolution (250 µm isotropic) T1‐, T2‐, and diffusion‐weighted structural MRI were acquired. The brain images were aligned and registered to the Marmoset Brain Mapping V3 template. The brain was segmented into cortical (CTX) and subcortical (SUB CTX) grey matter, white matter (WM), and cerebral spinal fluid (CSF), and voxel‐based‐morphometry was used to quantify regional brain volume in the left and right hemispheres.ResultsWe discovered a decrease in grey matter volume in both males and females with age (Figure 1), reflected by the reduction in several cortical and subcortical brain regions in both sexes. Overall, we discovered that age affects female marmoset brains (38 CTX and 5 SUB CTX regions) more than males (15 CTX and 2 SUB CTX regions). We found no significant age‐dependent changes in WM and CSF.ConclusionsOur work is the first to thoroughly describe the normal aging of the marmoset brain, a valuable model for age‐related neuropathologies (e.g., AD). This research will establish normative baselines for changes in regional marmoset brain volume with aging that will be used to evaluate our genetically engineered marmoset models of AD, which is the goal of the MARMO‐AD consortium.
Exploring Microtubule Dynamics in Alzheimer’s Disease: Longitudinal Assessment Using [11C]MPC‐6827 PET Imaging in APP/PS1 and PS301S Mouse Models
Authors: Damuka Naresh , Gollepalli Krishna Kumar , Krizan Ivan , Bhoopal Bhuvanachandra , Miller Mack , Deep Ojasvi , Bashetti Nagaraju , Kumar JV Shanmukha , Orr Miranda E. , Macauley Shannon L , Whitlow Christopher T , Mintz Akiva , Lockhart Samuel N. , Craft Suzanne , Sai Kiran K. Solingapuram 
Published: January 2025

AbstractBackgroundBrains affected by Alzheimer’s disease (AD) exhibit senile plaques containing amyloid beta (Aß) peptides and neurofibrillary tangles, formed when tau becomes hyperphosphorylated and disengages from microtubules (MTs). Early instability in MTs is observed in the AD process, emphasizing its significance in connecting the hallmark pathologies of Aß/tau‐based degenerative events. While current Aß and tau PET approaches can characterize disease lesions, they fall short in capturing earlier molecular events. MT‐PET aims to address this gap by targeting these early events, providing crucial insights into AD pathophysiology. The PET radiotracer, [11C]MPC‐6827, capable of tracking and quantifying MT‐based changes in real‐time and in vivo, addresses an urgent unmet need and facilitates the monitoring of MT changes in the early stages of AD. Here we present for the first time a comprehensive longitudinal PET imaging study of [11C]MPC‐6827 in Aß‐overexpressing (APP/PS1) and tau‐overexpressing (P301S) mouse models of AD.MethodsLongitudinal [11C]MPC‐6827 PET imaging, biodistribution studies, autoradiography, and behavioral assessments were conducted at multiple time points in APP/PS1 (3 to 22 mo old) and P301S (3 to 13‐mo‐old) transgenic (TG) and age‐matched wild‐type (WT) mice (n = 7/group). Whole‐brain standard uptake values for PET, %injected dose/gram for biodistribution, specific brain uptake for autoradiography, and nesting weight for cognitive assessments were determined and PET correlations for TG mice at different age‐points were calculated.ResultsLongitudinal PET imaging demonstrated a 1.3‐fold (***p<0.0001) and 0.9‐fold (**p<0.005) higher brain uptake in APP/PS1 TG mice from 3 to 22 mo and P301S TG mice from 3 to 13 mo respectively (Fig1) and uptake increased with increasing Aß and tau loads in AD brains. Longitudinal PET data positively correlated with biodistribution (Pearson r = 0.94), and autoradiography results (r = 0.55) and negatively correlated with cognitive data (r = ‐0.65) in APP/PS1 mice (Fig2).ConclusionIncreased [11C]MPC‐6827 brain PET uptake with both increasing Aß and tau depositions longitudinally in AD brains (along with corroborating biodistribution and autoradiography results) clearly demonstrate the role of early MT dysregulations in Aß and tau‐based neurodegeneration processes. These findings highlight the potential of [11C]MPC‐6827 PET as a powerful tool for monitoring MT disintegration early‐on. Ongoing experiments are exploring translational potential in humans.
Multimodal phenotyping of successful cognitive aging
Authors: Behrenbruch Niklas , Molloy Eóin N. , Schwarck Svenja , Schumann‐Werner Beate , Garcia‐Garcia Berta , Vockert Niklas , Morgado Barbara , Rullmann Michael , Hochkeppler Anne , Fischer Larissa , Baldauf Kathrin , Schulze Peter , Müller Patrick , Stephens Andrew W. , Patt Marianne , Schildan Andreas , Behnisch Gusalija , Seidenbecher Constanze I. , Schott Björn H. , Esselmann Hermann , Wiltfang Jens , Barthel Henryk , Sabri Osama , Kreißl Michael C. , Düzel Emrah , Maass Anne 
Published: January 2025

AbstractBackgroundWhile some memory decline in old age is “normal”, there are some older individuals with maintained high cognitive performance. Using a multimodal approach including neuroimaging, fitness, genetic and questionnaire data (Fig1A), we aimed to identify factors that are related to successful cognitive aging and whether these differ between sexes.MethodWe analyzed 165 cognitively normal older adults age = 60 years from an ongoing study (SFB1436) (age = 71±8years, 43% female). For all participants, we determined plasma Abeta1‐42/Abeta1‐40. Temporal lobe tau burden was estimated by [18F]PI‐2620 in a subsample (see Fig.1A for sample sizes). We assessed global white matter hyperintensity (WMH) volumes and gray matter thickness for medial temporal lobe (MTL), anterior cingulate cortex (ACC) and whole brain. We measured aerobic and muscular capacity (and blood pressure) by fitness assessment and trait/state anxiety by self‐reports. Genetic profiling included KLOTHO and KIBRA polymorphisms and APOE genotype. To phenotype successful cognitive aging, we i) grouped individuals age = 79.5 years into SuperAgers (N = 18) based on delayed verbal recall performance = normative values at age of 50‐60 years versus typical agers (N = 19). For the whole sample we ii) calculated cognitive age gap (CAG) as the difference between cognition‐predicted age and chronological age (Fig.3A). We assessed how markers of pathology, brain structure, fitness, mental health and genetics were related to CAG, covarying for chronological age, sex and education.ResultSuperAgers and typical agers did not differ in age, sex, education, fitness, anxiety or Abeta42/40 (all p‐values>0.1). However, SuperAgers had less WMH volume, higher ACC thickness, lower blood pressure and less temporal lobe tau‐tracer binding (small subgroup;). In the whole sample, younger cognitive age related to higher MTL and global cortical thickness, less temporal tau‐tracer binding, less anxiety (all p<0.05; Figure 3B) and marginally to higher muscular capacity (p = .06). Only the association between anxiety measures and CAG was moderated by sex (Fig.3B). CAG was not related to genotype.ConclusionOur results suggest that successful cognitive aging is related to resistance against age‐related pathology and higher brain integrity. Younger cognitive age is linked to better mental health, especially in females.
Cavum Septum Pellucidum (CSP) as a Neuroimaging Signature of Head Impact Exposure compared to Non‐exposed Patients with Neurodegenerative Disease and Controls
Authors: Kamps Suzie , Hempel Hugo L. , van Amerongen Suzan , de Bruin Hannah , van der Linden Fleur H.C. , Barkhof Frederik , Scheltens Philip , Ossenkoppele Rik , Vijverberg Everard G.B. 
Published: January 2025

AbstractBackgroundCavum Septum Pellucidum [CSP] is commonly observed on neuroimaging in individuals exposed to repetitive head impacts [RHI] and in post‐mortem examination in Chronic Traumatic Encephalopathy [CTE]. A CSP is proposed as a potential biomarker for CTE, yet prevalence across neurodegenerative diseases and its clinical implications are largely unknown. We assessed CSP prevalence and clinical associations in RHI‐exposed individuals in comparison to veterans with a history of traumatic brain injury [TBI], individuals with a neurodegenerative disease (i.e. Alzheimer’s Disease [AD] or Frontotemporal dementia [FTD]) and Cognitively Unimpaired individuals [CU].MethodThe group‐of‐interest, i.e., individuals exposed to RHI in contact sports or military service (n = 66), was compared against age‐ and sex‐matched ADNI‐DOD participants with TBI (n = 62) and non‐exposed participants of the Amsterdam Dementia Cohort (AD, n = 30; FTD, n = 25; CU, n = 25). Structural 3D brain MRI scans were visually rated on CSP grade (ranging 0‐4, Figure 1) according to established criteria by two independent raters without access to clinical information. A CSP scored at least grade 2 was considered abnormal. If scores between raters differed, scans were discussed to reach consensus. Inter‐rater reliability was assessed with Cohens’ weighted Kappa (κ). We investigated group differences in CSP grade as well as associations between CSP grade and neuropsychiatric symptoms (using the Neuropsychiatric Inventory [NPI]) and CTE probability (using the Traumatic Encephalopathy Syndrome [TES] criteria).ResultInter‐rater reliability was substantial (κ = 0.712). Prevalence of an abnormal CSP differed between groups (χ2 = 11.72, p = .020). An abnormal CSP was observed most often in the RHI group (43%), followed by TBI (31%, OR = 0.589, p = .158), and significantly less in AD (16%, OR = 0.255, p = .014), FTD (17%, OR = 0.267, p = .029), and SCD (14%, OR = 0.222, p = .012) compared to RHI (Figure 2). Across groups, CSP grade was not associated with severity of neuropsychiatric symptoms (F = 1.7, p = 0.151). An abnormal CSP was observed more in RHI‐exposed individuals with probable (57%) or possible (55%) CTE compared to suggestive of CTE (36%) or no TES (36%).ConclusionA CSP was more prevalent in RHI‐exposed individuals and veterans with TBI compared to patients with a neurodegenerative disease or CU individuals. Presence of a CSP on MRI may be indicative of head impact exposure, especially repetitive impacts.