bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of image processing methods on amyloid PET scanner effects for multisite cross‐sectional and longitudinal studies of Down syndrome
Authors: Luo Weiquan , Laymon Charles M , Tudorascu Dana , Cohen Ann D , Ances Beau , Zaman Shahid , Christian Bradley T. , Klunk William E , Handen Benjamin L , Minhas Davneet S 
Published: January 2025

AbstractBackgroundGaussian smoothing to a common image resolution is frequently employed to harmonize Aβ PET in multisite studies. However, spatial smoothing of PET can increase spill‐over contamination between neighboring regions. Geometric transfer matrix partial volume correction (PVC) has been applied, in turn, to correct for such contamination. Despite being common practices, the impact of smoothing and PVC on scanner effects remains unclear for cross‐sectional and longitudinal outcomes.We applied four putative image processing and statistical harmonization methods to unharmonized, multisite 11C‐PiB PET data from the ABC‐DS (11C‐PiB only) Down syndrome dataset to evaluate their impact on amyloid status group separation in cross‐sectional and longitudinal analyses.Method11C‐PiB images (Raw) from 4 different PET scanners (Table 1) were included in the analyses. Putative image‐processing harmonization methods evaluated were: (1) smoothing of PET images to an effective resolution of 8mm (Smo); (2) application of PVC to raw PET (Raw+PVC); (3) application of PVC to smoothed PET (Smo+PVC); and (4) application of ComBat/LongComBat to cross‐sectional/longitudinal Raw regional values.SUVR outcomes were extracted for all methods from 9 Aβ‐relevant regions. Mean normalized additive and multiplicative scanner effects were assessed for image‐processing method outcomes using ComBat/LongComBat frameworks. Hedge’s g effect sizes were evaluated for all image‐processing and ComBat/LongComBat methods between Aβ status groups cross‐sectionally on regional SUVR outcomes and longitudinally on change score outcomes between baseline and follow‐up SUVRs.ResultEstimated scanner effects across image‐processing methods are presented in Figure 1. Smoothing did not decrease scanner effects for any analyses, while Raw+PVC and Smo+PVC tended to increase scanner effects.Effect sizes across methods, including ComBat and LongComBat, are presented in Figure 2. Cross‐sectionally, ComBat outperformed all other methods in 5/9 regions, with the greatest increase in effect size observed in the anterior ventral striatum. Longitudinally, Raw+PVC or Smo+PVC resulted in the greatest effect sizes in 8/9 regions. Importantly, smoothing reduced longitudinal effect sizes in 9/9 regions relative to Raw and obscured group differences in the anterior and posterior cingulates.ConclusionGaussian smoothing may not address 11C‐PiB PET scanner effects estimated using ComBat/LongComBat frameworks. Spatial smoothing, in fact, may confound the ability to differentiate longitudinal change between groups.
Regional brain metabolism across the Alzheimer's Disease continuum in Down Syndrome
Authors: Arriola‐Infante José Enrique , Morcillo‐Nieto Alejandra O. , Zsadanyi Sara E , Franquesa‐Mullerat María , Vaqué‐Alcázar Lídia , Aranha Mateus Rozalem , Arranz Javier , Rodríguez‐Baz Íñigo , Maure‐Blesa Lucía , Videla Laura , Barroeta Isabel , Hoyo Laura Del , Benejam Bessy , Fernandez Susana , Hernandez Aida Sanjuan , Giménez Sandra , Alcolea Daniel , Belbin Olivia , Flotats Albert , Camacho Valle , Lleo Alberto , Carmona‐Iragui Maria , Fortea Juan , Bejanin Alexandre 
Published: January 2025

AbstractBackgroundTo date, limited data exist concerning the utility of FDG‐PET in detecting Alzheimer's Disease (AD) in Down Syndrome (DS). Yet, sensitive biomarkers for neurodegeneration are essential in this population genetically predisposed for AD. Therefore, we aimed at characterizing the effect of age, disease stage and AD pathology on brain metabolism in a large cohort of adults with DS.MethodCross‐sectional study with 72 controls (HC) and 100 participants with DS (63 asymptomatic [aDS], 13 prodromal AD [pDS], 24 AD dementia [dDS]) from the Down‐Alzheimer Barcelona Neuroimaging Initiative, undergoing 3T‐MRI, 18F‐FDG‐PET, lumbar puncture, and clinical assessment. 18F‐FDG‐PET scans were normalized using MRI data and scaled using the pons. CSF biomarkers were assessed utilizing Lumipulse (Aβ42/Aβ40 ratio and phosphorylated tau [p‐tau]) and ELISA (neurofilament light chain [NfL]) methods. Voxelwise analyses in SPM12 examined i) the effect of age, ii) AD clinical stage and iii) relationships with CSF biomarkers on brain metabolism.ResultIn HCs, brain metabolism decreased with age mainly in the frontal lobe, while in DS we observed a more distributed pattern, predominating in temporoparietal regions (Figure 1A‐B). The interaction indicated greater metabolic loss with age in DS compared to HC in lateral temporoparietal regions (Figure 1C). Compared to aDS, symptomatic DS exhibited lower metabolism in most regions, with the strongest effect in medial parietal and lateral temporoparietal structures (Figure 2). Additional comparisons revealed a clear decreased metabolism in posterior cingulate and angular gyrus in pDS vs aDS, and a more subtle metabolic loss in posterior lateral parietal areas in dDS compared to pDS. Associations between metabolism and CSF biomarkers were found in brain regions showing hypometabolism in symptomatic AD, and were most significant for NfL (Figure 3).ConclusionThe age‐related decrease in brain metabolism was more pronounced in DS compared to HCs and likely reflects AD processes. The pattern of hypometabolism at the symptomatic stage predominated in temporoparietal regions and strongly resembles the pattern observed in sporadic AD, further emphasizing similarities between genetic and sporadic AD forms. The hypometabolism in parietal structures at the prodromal stage demonstrated 18F‐FDG‐PET´s sensitivity as biomarker for early AD diagnosis in DS.
Feasibility of A Multi‐Pronged, Multi‐Sensor Cognitive Aging Protocol in a diversified Cohort: Results from the Einstein Aging Study
Authors: Roque Nelson A. , Sliwinski Martin J. , Derby Carol A. , Lipton Richard B. , Buxton Orfeu M. , Katz Mindy J. 
Published: January 2025

AbstractBackgroundOlder adults, especially from diverse populations, are often presumed to be unwilling or unable to participate in mobile health (mHealth) studies. Since 2017, the Einstein Aging Study (EAS) participants have been instructed on and actively supported in completing comprehensive and intensive longitudinal assessments, harnessing the capabilities of smartphones and wearable devices. Notably, since early 2023, the EAS has expanded its scope by incorporating the gathering of data from multiple wearable sensors.MethodIn addition to clinic‐based neuropsychological testing, neurological exams and blood draws, the main protocol of the Einstein Aging Study asks participants to complete 14‐days of app‐based surveys and ambulatory cognitive assessments five times per day (i.e., upon wake‐up, at bedtime, and three notified assessments in between). Participants are also wearing sensors to collect data on air quality (via Atmotube Pro) and monitoring sleep, physical activity, and sedentary behavior (via Actiwatch, Actipal). We present compliance data for our new Ecological Momentary Assessment protocol.ResultThere are 112 total EAS participants (mean age = 80.87, SD= 6.06; % Female = 71.2; % non‐Hispanic Whites = 38.74%, % non‐Hispanic Blacks = 49.55%, % Hispanics = 11.71%). Overall, across our new ambulatory data collection protocol (i.e., data collected after yearly clinic visit on study smartphones and wearables), the EAS has robust compliance, with median total minutes of daily surveys ∼47 minutes. Specifically, for the Ecological Momentary Assessment (EMA) protocol delivered on study smartphones, 85% of participants completed 11 or more days of wake‐up surveys (self‐initiated), 79% of the first notified survey, 80% of the second, 77% of the third, and 82% completed the bedtime surveys (self‐initiated). There were no significant differences by race or ethnicity in adherence (one‐way ANOVA, all p's > 0.05).ConclusionThese preliminary data for our longitudinal protocol provide continuing evidence of feasibility that older adults from diverse populations are adherent to intensive longitudinal data collection procedures, including when involving numerous wearable sensors. Future research may explore the influence or perturbations of EMA adherence when adding additional participant burden to a protocol (e.g., adding a continuous glucose monitor (CGM) sensor).
Effects of Amyloid Pathology and Vascular Risk Factors on Regional Cerebral Blood Flow Patterns
Authors: Taghvaei Mohammad , Sadaghiani Shokufeh , Shakibajahromi Banafsheh , Khandelwal Pulkit , Das Sandhitsu R. , Nasrallah Ilya M. , Yushkevich Paul A. , Wolk David A , Detre John A. , Dolui Sudipto 
Published: January 2025

AbstractBackgroundRegional cerebral blood flow (CBF) can be noninvasively quantified using arterial spin labeled (ASL) perfusion MRI. In Alzheimer’s disease (AD) and mild cognitive impairment (MCI), hypoperfusion typically occurs in precuneus, posterior cingulate cortex (PCC), and hippocampus. Small vessel disease (SVD), a systemic disorder that commonly underlies vascular cognitive impairment, also causes brain hypoperfusion. Many dementia patients demonstrate both neurodegenerative and vascular pathologies, which may interact to accelerate cognitive decline. Here we used advanced background‐suppressed 3D ASL to assess CBF variations across the AD spectrum and in relation to risk factors for AD and SVD.MethodData from 258 participants comprising 180 cognitively unimpaired (CU), 54 MCI, and 24 AD participants, diagnosed by clinical consensus, were obtained from the Penn Alzheimer Disease Research Center. ASL CBF was quantified in gray matter (GM), white matter (WM), AD‐associated cortical regions of PCC+precuneus and hippocampus. We also considered normal‐appearing WM (NA‐WM) and periventricular WM (NA‐PVWM) in which voxels containing T2 white matter hyperintensities were excluded. PVWM is supplied exclusively by microvessels and may be a sensitive region for CBF reductions in SVD despite its small size. Global and regional CBF was compared across diagnostic groups. Furthermore, the influence of PET‐derived amyloid status and vascular risk factors (VRF: presence of any of hypertension, diabetes, obesity, hypercholesteremia, and smoking) on CBF were also evaluated.ResultAcross the AD spectrum, CBF was lower in AD‐associated cortical regions. AD also exhibited reduced CBF in GM, WM, NA‐WM, and NA‐PVWM (Table 1). Voxel‐wise comparisons of CBF contrasting amyloid‐positive or VRF‐positive MCI with corresponding amyloid‐negative or VRF‐negative CU showed that VRF effects were more widely distributed in GM and WM than amyloid status effects (Figure 1). There was a trend of reduced regional CBF with VRF‐positivity in amyloid‐positive AD+MCI suggesting an additive effect of VRF with amyloid and diagnosis (Figure 2).ConclusionPutative SVD regions showed diagnosis‐related CBF changes comparable in magnitude to typical AD cortical regions that may reflect vascular effects. Vascular risk was associated with more spatially distributed CBF reductions than amyloid status and may reflect its additive effect with amyloid on cognitive decline.
Baseline Aβ and tau markers contribute to localized patterns of brain tissue atrophy across 1223 individuals from four harmonized longitudinal datasets
Authors: Somu Sunanda , Zhu Alyssa H , Narula Siddharth , Gari Iyad Ba , Gadewar Shruti , Nir Talia M , Jahanshad Neda 
Published: January 2025

AbstractBackgroundAmyloid‐β (Aβ) plaques and tau pathogenesis in the brain precede cognitive decline in the progression of Alzheimer’s dementia, yet the extent to which these measures can predict localized brain tissue atrophy has not been studied in a large, diverse population. Multisite studies offer robust statistical power with larger sample sizes but are confounded by variations in biomarker quantification across studies, including variations in MRI scanners, PET tracers, and CSF assays. Longitudinal data from N=1223 individuals from four independent AD studies were harmonized to assess localized brain tissue atrophy over 2 to 5 years. We tested for associations between volumetric changes and baseline measures of Aβ, phosphorylated tau (p‐tau), and cognitive function. Associations between atrophy and ApoE4 and diagnostic conversion were also assessed.MethodBaseline (BL) and follow‐up (FU; mean=2.3+/‐0.5 years) 3T T1‐weighted brain MRI (T1w) from ADNI3 (N=373), Prevent‐AD (N=213), HABS‐MGH (N=213), and OASIS3 (N=424) were used along with corresponding PET measures obtained from FBB, FBP or PiB tracers, and CSF measures (Figure 1A). Subject‐wise maps of volumetric brain changes were created and warped to a common template for statistical analyses (Figure 1B). Voxel‐wise mixed effects linear regressions were run to test for associations between change in brain volume and Aβ‐42 positivity (CSF / PET), CSF p‐tau‐181 positivity, ApoE4 genotype, Clinical Dementia Rating (CDR), and diagnostic conversion (i.e., cognitively normal vs decline). Fixed effects included BL age, sex, scan time interval, and PET imaging tracer type or CSF processing batch; scan site was a random effect. FDR was used for voxel‐wise multiple comparisons correction.ResultAβ and p‐tau positivity at baseline, and the ApoE4 genotype, were associated with accelerated atrophy in the temporal lobe, medial‐parietal lobe and amygdala (Figure 2). CDR and conversion were associated with ventricular expansion and atrophy in the insula, temporal lobe, hippocampus and amygdala (Figure 3).ConclusionOur multi‐study brain mapping and harmonization approaches showed how baseline PET and CSF based amyloid and tau metrics are predictive of common and localized brain atrophy across multiple studies with diverse data collection protocols and study designs.
The synaptic marker NPTX2 and longitudinal brain atrophy among cognitively unimpaired adults
Authors: Anderson Claire L , Vazquez Juan , Zhu Yuxin , Pettigrew Corinne , Moghekar Abhay , Erus Guray , Davatzikos Christos , Xiao Mei‐Fang , Worley Paul F , Albert Marilyn S. , Soldan Anja 
Published: January 2025

AbstractBackgroundPrevious studies have shown that higher levels of the synaptic protein NPTX2, measured in cerebrospinal fluid (CSF), are associated with lower risk of progression from normal cognition to Mild Cognitive Impairment (MCI) and dementia. Among those with MCI or dementia, higher NPTX2 levels have been associated with decreased atrophy in AD‐vulnerable brain regions. It is not known, however, whether NPTX2 levels influence brain atrophy among cognitively unimpaired participants. This study examined the association between baseline CSF NPTX2 and longitudinal MRI brain volumetric measures among participants who were cognitively unimpaired at baseline, and whether AD pathology levels modify this relationship.MethodsCSF and MRI data were collected from 213 BIOCARD Study participants (M baseline age = 57.2y, mean MRI follow‐up=13.9y), including 41 who have since progressed to MCI/dementia (Table 1). The analysis focused on a z‐transformed composite measure of three NPTX2 peptides, measured using parallel reaction monitoring mass spectroscopy. CSF Ab1‐42/Ab1‐40 and p‐tau181 were measured using the Fujirebio Lumipulse G1200 assays, with levels of AD pathology summarized as the p‐tau181/(Ab1‐42/Ab1‐40) ratio. Atrophy on volumetric MRI scans was quantified with MUSE and assessed as three composites including: (1) AD vulnerable regions (SPARE‐AD), (2) medial temporal lobe (MTL) regions, and (3) regions indexing advanced non‐AD related brain aging (SPARE‐BA).ResultsIn mixed‐effects models covarying age, sex, and AD pathology levels (i.e., p‐tau181/(Ab1‐42/Ab1‐40)), higher baseline NPTX2 levels were associated with less atrophy over time in AD vulnerable (β=‐.008, p=0.03) and in age‐related regions (β=‐.01 p=0.01), see Table 2. Higher AD‐biomarker levels were associated with greater longitudinal atrophy in all MRI composites (all p<=0.001) but did not moderate the association between NPTX2 and atrophy (all p>0.52 for interactions of NPTX2 x p‐tau181/(Ab1‐42/Ab1‐40) x time).ConclusionsThese findings suggest that among cognitively unimpaired individuals, higher levels of NPTX2 may slow longitudinal atrophy in AD‐vulnerable and age‐related regions, independently of AD pathology levels. As a non‐AD‐specific marker of synaptic and neuronal function, these findings support the view that NPTX2 may be a resilience factor against neurodegeneration and cognitive decline and suggest that developing novel therapeutics that target NPTX2 and related synaptic proteins may have broad applicability.
ALZpath pTau217: Alzheimer’s disease specificity in the context of multiple comorbidities and predictive capabilities for amyloid burden in combination with other blood‐based biomarkers
Authors: Chaby Lauren E , Borello Jacob , Vaughan Timothy , Portbury Stuart D , Frykman Hans , Mammel Anna , Encarnacion Mary , Serrano Geidy E , Beach Thomas G. , Masters Colin L , Rowe Christopher C. , Fowler Christopher J , Wilson Rachael E , Du Lianlian , Jonaitis Erin M. , Johnson Sterling C. , Jeromin Andreas 
Published: January 2025

AbstractBackgroundTau phosphorylated at position 217 (pTau217) is considered to have the highest accuracy in identifying Alzheimer’s disease (AD) pathology using blood. We describe a multi‐cohort evaluation of the Simoa ALZpath pTau217 assay for the prediction of amyloid status in combination with additional blood‐based AD biomarkers (GFAP, pTau181, etc.), as well as comparisons between histopathological and PET based amyloid measurements. We describe the contribution of a spectrum of neurodegenerative diseases and demographic features to circulating plasma pTau217 levels.MethodThe Simoa ALZpath pTau217 assay is an ultra‐sensitive blood‐based assay developed on the semi‐automated single‐molecule array Simoa platform. We evaluate Simoa ALZpath pTau217 in the Banner Brain and Body Donation Program (characterized by several clinically meaningful comorbidities and mid‐to‐late stage AD; pTau217 subset: mean Braak Score = 4.17, ADNC High Plaques = 28%, ADNC Intermediate Plaques = 33%), the Wisconsin Registry for Alzheimer’s Prevention (a longitudinal cohort focused on healthy cognition through MCI), and a cognitively normal amyloid negative subset of the Australian Imaging, Biomarker and Lifestyle (AIBL) study.ResultWe discuss ALZpath pTau217 predictive capabilities in the context of PET imaging and post‐mortem histopathology for total and region‐specific pathological burden and the relative contribution of other blood‐based biomarkers and demographic features. We also report AD and MCI specificity in driving plasma levels of ALZpath pTau217 in the context of multiple comorbidities including CAA, DLB, and VAD.ConclusionFindings support ALZpath pTau217 as a high performing biomarker of CNS amyloid and tau burden that is driven specifically by AD and MCI in the context of multiple comorbidities. The ALZpath pTau217 performance capabilities can support timely AD diagnosis and intervention.
Spatial heterogeneity in white matter hyperintensities revealed by postmortem MRI‐guided histopathological staining
Authors: Mojtabai Mariam , Li Karl , Rashid Tanweer , Li Jinqi , Honnorat Nicolas , Nirmala Anoop Benet , Martinez David M , Wang David H , Charisis Sokratis , Franklin Crystal , Keating Mallory , Boisselier Marco I , Katragadda Haritha V. , Maestre Gladys E. , Flanagan Margaret E , Richardson Tim , Walker Jamie M. , Fox Peter T , Seshadri Sudha , Bieniek Kevin F. , Habes Mohamad 
Published: January 2025

AbstractBackgroundWhite matter (WM) hyperintensities are bright areas on T2 MRI that reflect increased interstitial fluid caused by demyelination and axonal loss; these tissue alterations have been associated with cognitive impairment. Previous in‐vivo studies have suggested that the underlying pathogenesis for WM changes differs between the anterior and posterior brain, with cerebrovascular disease contributing more to anterior WM lesions and neurodegenerative processes contributing more to posterior WM lesions.MethodPeriventricular (PV) and deep subcortical (DS) WM hyperintensities both in the anterior and posterior portions of the brain were identified using postmortem T2 MRI of cerebral hemispheres from the Biggs Institute Brain Bank (Figure 1) in 7 Alzheimer’s Disease patients (four male, three female, average age 75). Normal appearing (NA) WM at the base of the postcentral gyrus was selected as an internal control. Slide sections were obtained from these five regions across seven brains for 35 slides total using MRI landmarks to guide brain sectioning for histopathological analysis. The slides were stained using Luxol fast blue (LFB) and hematoxylin and eosin (H&E) and scanned digitally. Myelin was measured with the LFB, and vacuolation was measured with the H&E. Machine learning methods were used to segment and analyze the slides as the percent area stained in a selected region of interest (Figure 2).ResultsCompared to NA WM, areas of WM hyperintensities exhibited a lower average LFB‐stained area (p=0.001) and H&E‐stained area (p<0.001), indicating increased demyelination and vacuolation within the lesions. Anterior PV WM lesions demonstrated a higher extent of demyelination (p=0.055) and vacuolation (p=0.074) than posterior PV WM lesions (Table 1). Posterior DS WM lesions showed significantly more demyelination than posterior PV WM lesions (p=0.022).ConclusionThe variations in demyelination within the WM lesions suggest differing underlying pathogenesis. This may be mediated by the differences in contribution from vascular and neurodegenerative causes as confirmed in previous studies. These preliminary results encourage the use of additional histopathological methods to better understand how different heterogeneous etiologies contribute to the development of white matter damage and how this can be translated into prevention strategies.