bluuebunny/crossref_metadata_2025_split huggingface dataset:
White matter abnormalities in association with amyloid and tau deposition in a diverse cohort with increased risk for Alzheimer’s disease
Authors: Blujus Jenna K , Rego Eliza , Bica Sarah , Demos Kathryn , Lee Athene KW , Riddle Meghan C. , Wing Rena R. , Salloway Stephen , Maillard Pauline , Fan Audrey P. , Decarli Charles , Vemuri Prashanthi , Lockhart Samuel N. , Baker Laura D , Landau Susan M. , Oh Hwamee 
Published: January 2025

AbstractBackgroundNeuritic plaques with fibrillar beta‐amyloid (Aß) peptides and tau‐protein neurofibrillary tangles, hallmark features of Alzheimer’s disease (AD) pathology, have been concomitantly associated with white matter (WM) integrity loss, while a unique effect of each pathology on WM integrity in a more demographically diverse population remains unknown.MethodTo examine the degree to which each pathology affects WM integrity in a more diverse non‐demented cohort, Aß and tau PET, diffusion‐weighted imaging (DWI), and cognition (memory and executive function composites) were examined from the U.S. POINTER neuroimaging participants (N = 608; age = 68.34±5.2; 61.8% females; 29% Aß+) and a subset of Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants (N = 291; age = 72.85±7.3; 50% females; 39% Aß+) (Table). Aß‐positivity was determined using tracer‐specific standardized cut‐offs. Tau SUVR was estimated for each Braak stage. For WM integrity, voxel‐based GLMs were applied to FSL‐processed fractional anisotropy (FA) maps using Braak stage tau SUVR and Aß‐positivity status, along with covariates of age, sex, and b‐value profiles.ResultIn U.S. POINTER, independent from Aß‐positivity status, greater tau burden in Braak stages I and II was related to lower FA across the tracts including the superior longitudinal fasciculus, fornix (cres), corpus callosum, and anterior thalamic radiation (Figure). Average FA from supra‐threshold clusters for Braak I and II significantly predicted executive function but not episodic memory. No association between FA and tau burden in Braak stages III/IV or V/VI was found. In the ADNI sample, greater tau burden in Braak I was related to lower FA mostly in left inferior longitudinal fasciculus and left uncinate fasciculus, while negative associations with FA became more diffuse with tau load in Braak III/IV and V/VI. Average FA from supra‐threshold clusters significantly predicted both episodic memory and executive function scores. Across both samples, after accounting for tau burden in each Braak stage, there were no association between Aß‐positivity status and WM integrity.ConclusionDistinct associations between tau burden, WM integrity, and cognition were found across the studies, indicating greater impact of early tau burden on WM integrity in U.S. POINTER, accounting for Aß‐positivity status. Factors contributing to the distinct associations across studies need further investigation.
Longitudinal multicenter head‐to‐head harmonization of tau‐PET tracers: an overview of the HEAD study cohort
Authors: Lussier Firoza Z , Povala Guilherme , Bauer‐Negrini Guilherme , Amaral Livia , Cehula Juli , Fine Devin J , Lemaire Peter , Bloomquist Madeleine , Pascual Belen , Gordon Brian A. , Lowe Val J. , Oh Hwamee , soleimani‐meigooni David N. , Rosa‐Neto Pedro , Tudorascu Dana , Jagust William J. , Klunk William E , Baker Suzanne L. , Pascoal Tharick Ali 
Published: January 2025

AbstractBackgroundStandardizing tau pathology quantification in vivo is challenged by differences in binding characteristics between tau‐PET tracers. The HEAD study aims to generate a leading, longitudinal head‐to‐head dataset of MK‐6240, Flortaucipir, RO948, and PI‐2620 tau‐PET to harmonize these tracers' outcomes and develop tools allowing for the generalization of findings across large studies and trials. Here, we present current advancements in building the HEAD study cohort and dataset.MethodsThe HEAD study is managed at the University of Pittsburgh. HEAD comprises several sites across the US and Canada in which 620 subjects (young, cognitively unimpaired, mild cognitive impairment, and Alzheimer’s disease (AD)) will undergo tau‐PET with at least two tracers, amyloid‐PET with PiB or NAV4694, MRI, blood collection, and standardized neuropsychological testing at baseline and at 18‐month follow‐up. PET and MRI acquisition parameters are based on ADNI4 protocols and neuropsychological testing employs the NACC Uniform Data Set. The National Centralized Repository for AD serves as the biorepository for blood samples and the Laboratory of Neuroimaging provides a centralized database for imaging and neuropsychological archiving. PET data is reconstructed to maximize cross‐scanner harmonization and is processed uniformly similarly to ADNI4 PET.ResultsIn one year of active enrollment (Jan 2023‐Jan 2024), 362 participants were enrolled at six active sites; over 80% of participants completed neuropsychological testing and MRI, and over 70% completed Flortaucipir, MK‐6240, and amyloid‐PET, with a mean tau‐PET acquisition window of 29.1 days. RO948 and PI‐2620 tau‐PET are additionally acquired in a subset currently including 41 participants (Fig.1). Current HEAD cohort demographics including age, sex, underrepresented populations, and group distributions, APOEe4 carrier status, and amyloid positivity are shown in Fig.2. A case of a subject with AD with all 4 tau‐PET tracers acquired head‐to‐head within 49 days is shown in Fig.3.ConclusionThe HEAD study represents a continued effort in the optimization of AD imaging biomarkers. Baseline data collection is projected to be completed in 2024; results being generated by multiple groups from this dataset will provide novel and crucial guidance on the use of tau‐PET tracers in research, clinical trials, and prospectively in clinical practice.
Associations between BDNF Val66Met and tau‐PET and episodic memory performance in sporadic AD
Authors: Thomson Diny , Rosenich Emily , Maruff Paul , Lim Yen Ying 
Published: January 2025

AbstractBackgroundIn the presence of abnormally high amyloid (Aß+), carriage of the brain‐derived neurotrophic factor (BDNF) Val66Met polymorphism Met allele (Met66) is associated with faster clinical disease progression, greater neuronal loss and faster rate of CSF total‐tau and p‐tau181 compared to matched Val66 Aß+ homozygotes. Aß levels are unaffected by carriage of Met66. This suggests reduced neurotrophic support may accelerate Aß‐related neuronal dysfunction and cognitive decline. We aimed to clarify the role of BDNF Val66Met in moderating region‐specific neurofibrillary tangle (NFT) formation in the brain in sporadic Alzheimer’s disease (AD).MethodData from 26 Aß+ older adult Met66 carriers and 68 Val66 homozygotes enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were included in the analysis if they had at least one tau‐PET scan, Aß‐PET scan, and neuropsychological assessment available. Participants were not excluded based on disease stage. ANCOVAs were conducted to determine, cross‐sectionally, whether levels of tau‐PET tracer retention at each Braak stage, episodic memory performance (measured on ADNI’s memory composite), and Aß levels differed between Met66 carriers and Val66 homozygotes at the time of their first tau‐PET scan. Aß levels, APOE e4 status, sex, age, baseline diagnosis, and years of education were included as covariates.ResultAß+ Met66 carriers showed significantly greater tracer retention in the entorhinal cortex (i.e., Braak 1) compared to Val66 homozygotes (p=.03), with the magnitude of this difference moderate (d=0.39; Table 1). There were no significant differences between Met66 carriers and Val66 homozygotes in tracer retention across all other Braak stages, episodic memory performance or Aß levels (Table 1).ConclusionThe greater tau‐PET tracer retention in the entorhinal cortex in Met66 carriers may reflect their greater NFT pathology relative to Val66 homozygotes during early stages of AD. This is consistent with previous observations of higher levels of CSF total‐tau and p‐tau181 in Aß+ Met66 carriers, both in sporadic AD and autosomal dominant AD. Together, these findings support the hypothesis suggesting that loss of neurotrophic support, associated with Met66 carriage, may confer greater vulnerability to Aß‐related neurodegeneration compared to Val66 homozygosity.
Utility of plasma p‐tau217 as a secondary outcome for clinical trials across AD continuum
Authors: Ferreira Pamela C.L. , Bellaver Bruna , Povala Guilherme , Aguzzoli Cristiano Schaffer , Ferrari‐Souza João Pedro , Leffa Douglas Teixeira , Lussier Firoza Z , Madeiros Marina Scop , Zalzale Hussein , Rohden Francieli , Soares Carolina , Abbas Sarah , Bauer‐Negrini Guilherme , Karim Helmet T. , Hong Chang Hyung , Roh Hyun Woong , Tudorascu Dana , Karikari Thomas K , Snitz Beth E. , Son Sang Joon , Pascoal Tharick A. 
Published: January 2025

AbstractBackgroundBlood‐based biomarkers offer a cost‐effective and simple alternative for clinical use in the context of Alzheimer’s disease (AD). It has already been shown that plasma phosphorylated tau at threonine 217 (p‐tau217) is associated with amyloid (Aß), neurofibrillary tau tangles, and cognitive decline. Longitudinal studies confirmed its ability to track AD progression. Therefore, the aim of this study is to evaluate the potential utility of changes in plasma p‐tau217 as secondary outcome in clinical trials across the AD spectrum.MethodWe included 189 individuals with available plasma p‐tau217 measurements at two time points (24 months follow‐up) across two cohorts:[MYHAT‐NI, population‐based(USA): 51 Cognitively Unimpaired(CU); BICWALZS, memory clinic(South Korea): 135 Cognitively Impaired(CI) individuals], all with baseline Aß‐PET. Plasma p‐tau217 was quantified using the ALZpath assay. We used linear regression to investigate p‐tau217 association with cognitive decline. Effect size was determined by biomarker mean change divided by the standard deviation. We also estimated the sample size required to detect a 25% drug effect on p‐tau217 reduction with 80% power at a significance level of 0.05.ResultBaseline and longitudinal changes in p‐tau217 were significantly associated with cognitive decline independently of Aß status in both CU and CI individuals (Table 1). Functionally, individuals classified with mild dementia(CDR‐SB>4.5) showed greater and pronounced annual changes in p‐tau217 compared to the other groups (Figure 1A). Notably, Aß+ individuals presented a higher effect size for p‐tau217 changes in both CU(0.79) and CI(0.74) groups, compared to the whole population (Figure 2B). The sample size required for a clinical trial including of Aß+ individuals were 1,276 for CU and 940 for the CI. Cost analysis revealed that in trials recruiting CU Aß+ individuals targeting tau pathology using p‐tau217 as a secondary outcome was 1.5, 3.7, and 3.9 times more cost‐effective than 18F‐MK‐6240 tau‐PET, 18F‐Flortaucipir tau‐PET, and p‐tau181, respectively (Figure 2). Similarly, in trials with CI Aß+ participants, p‐tau217 was 1.5 times less expensive than [18F]‐MK‐6240 tau‐PET, and 3.7 times less than [18F]‐Flortaucipir tau‐PET.ConclusionOur results demonstrated that changes in plasma p‐tau217 is associated with cognitive decline across the AD continuum. Furthermore, p‐tau217 shows promise as a secondary outcome in AD clinical trials.
The role of biofluid markers in predicting near‐term cognitive impairment
Authors: Yakoub Yara , Gonzalez‐Ortiz Fernando , Ashton Nicholas J. , Karikari Thomas K , Strikwerda‐Brown Cherie , St‐Onge Frédéric , Ourry Valentin , Schöll Michael , Geddes Maiya R. , Ducharme Simon , Rosa‐Neto Pedro , Soucy Jean‐Paul , Breitner John C.S. , Zetterberg Henrik , Blennow Kaj , Poirier Judes , Villeneuve Sylvia 
Published: January 2025

AbstractBackgroundPET biomarkers have proven valuable for identifying cognitively unimpaired (CU) individuals at‐risk of near‐term clinical progression. Given the increasing interest in plasma biomarkers to detect Alzheimer’s pathology, we assessed levels of amyloid (Aß42/40) and tau (p‐tau217 and p‐tau181) biomarkers in plasma (A+T+plasma) in CU individuals as predictors of clinical progression to mild cognitive impairment (MCI). We then repeated these analyses using cerebrospinal fluid (CSF) and PET biomarkers.MethodWe studied 218 participants from the PREVENT‐AD cohort with cognitive follow‐up (mean 5.34 years, range 1–10 years) and plasma biomarkers available while CU. Cognition was assessed annually using the RBANS. Plasma biomarkers were measured using IP‐MS for Aß42/40 and in‐house single molecular arrays for p‐tau217 and p‐tau181. An overlapping 71 participants had Aß42/40 (Mesoscale Discovery assay) and p‐tau181 (Innotest immunoassay) CSF data available, and 135 participants had Aß (18F‐NAV4694) and tau (18F‐florbetapir) PET data. We also performed receiver operating characteristic (ROC) curves to compare the performance of plasma (Aß42/40 and p‐tau217; Aß42/40 and p‐tau181), CSF (Aß42/40 and p‐tau181) or PET (Aß‐ and tau‐PET) biomarkers in predicting progression to MCI. We examined an additional model including only Aß‐PET, given the importance of this technique as a stand‐alone marker for recruitment in anti‐Aß trials.ResultThe proportion who progressed from CU to MCI was 62% in individuals with A+T+plasma217; and 41% with A+T+plasma181; 56% with A+T+CSF181 and 100% with A+T+PET (Figure 1). Cox proportional hazard models indicated a faster progression rate in all A+T+ groups compared with their matched A‐T‐ biomarker groups (Figure 2). Considering longitudinal RBANS scores, all A+T+ groups declined faster than the other groups, except for the plasma181 group. Finally, the PET (Aß and tau‐PET) and CSF models were superior to the plasma or Aß‐PET alone in identifying progressors, with no meaningful difference between the Aß‐PET and the biofluid models (Figure 3).ConclusionCU individuals with A+T+ based on plasma biomarkers are at increased risk of cognitive decline and clinical progression. Nevertheless, the proportion who progressed to MCI in individuals classified with plasma was lower than that found using PET. Thus, the latter should remain the gold standard to identify presymptomatic pathological changes.
The Role of ApoE4 in The Acceleration of Tau Aggregation
Authors: Steward Anna , Biel Davina , Roemer Sebastian Niclas , Zhu Zeyu , Pescoller Julia , Wagner Fabian , Gross Mattes , Dichgans Martin , Ewers Michael , Dehsarvi Amir , Brendel Matthias , Franzmeier Nicolai 
Published: January 2025

AbstractBackgroundUnderstanding modulators of Alzheimer's disease’s (AD) progression is crucial for determining optimal treatment windows and targets. Apolipoprotein E e4 (ApoE4), i.e. a key AD risk factor, is associated with earlier tau accumulation at lower Aß levels (Steward et al. 2023), yet, the mechanisms driving this connection remain unclear. Thus, we assessed whether ApoE4 accelerates initial Aß‐related tau secretion measurable in CSF or subsequent tau aggregation as determined via PET (Figure 1A).MethodWe combined cross‐sectional CSF measures of phosphorylated tau (p‐tau181) and Aß‐PET in 287 APOE genotyped non‐demented (cognitively normal [CN]; mildly cognitively impaired [MCI]) ADNI participants. P‐tau181 was adjusted to Aß40 to account for inter‐individual variability in CSF protein concentrations. Using linear regression, we investigated i) whether ApoE4 was related to accelerated Aß‐related p‐tau secretion (i.e., Aß‐PET by ApoE4 interaction on p‐tau181), ii) whether ApoE4 accelerated the p‐tau‐induced fibrillisation of tau (i.e. p‐tau181 by ApoE4 interaction on tau‐PET) and iii) whether regional effects of ApoE4 on p‐tau‐related tau fibrillisation were associated with ApoE4 mRNA expression levels.ResultApoE4 did not moderate the relationship between Aß‐PET and p‐tau181 (Figure 1B, p=0.76) but strengthened the effect of p‐tau181 on global Tau‐PET increase (Figure 1C, ß=0.7, p<0.001). At the regional level, this ApoE4 x p‐tau181 interaction on tau‐PET was correlated with regional APOE mRNA expression in CN (Figure 2B, r=0.5, pspin<0.001), but not in MCI (p=0.141), suggesting that ApoE4 drives earliest p‐tau‐induced tau aggregation. Supporting this further, we found that the regional effect of p‐tau181 on Tau‐PET was more strongly correlated with APOE mRNA expression in CN ApoE4 carriers (Figure 2C, r=0.54, pspin<0.001) than in CN non‐carriers (r=0.4, pspin=0.05). Lastly, we confirmed that the effect of Aß on tau aggregation is mediated by p‐tau increases (Figure 1D, ACME: B=0.28; p<0.001; ADE: B=0.206; p=0.008) which is strengthened in ApoE4 carriers (B=0.21, p=0.006).ConclusionApoE4 promotes p‐tau‐induced tau aggregation, particularly in early disease stages and in regions that express high APOE. This suggests that ApoE4 can trigger earlier Aß‐related tau spreading most likely due to facilitated p‐tau induced tau aggregation. This suggests that preventing soluble p‐tau increases may attenuate tau aggregation and therefore dementia.
Support for transmission of tau pathology in humans using individualized epicenters and structural connectomes
Authors: Brown Christopher , Das Sandhitsu R. , Nasrallah Ilya M. , Detre John A. , Yushkevich Paul A. , McMillan Corey T , Wolk David A 
Published: January 2025

AbstractBackgroundPopulation‐based functional connectomes help explain heterogeneity in tau spread in Alzheimer’s disease by demonstrating spread among connected neurons from canonical epicenters. However, if the hypothesis of cell‐to‐cell transmission of tau is correct, individual structural connectomes seeded from individual‐specific epicenters of PET‐tau pathology should improve prediction of regional tau patterns.Method86 participants from the Penn Aging Brain Cohort and 158 participants from ADNI with multi‐shell diffusion MRI and AV1451 Tau PET within 18 months of each other were included. A schematic of methods is shown in Figure 1. Tau PET standard uptake value ratios were converted to Tau Pathology Indices (TPI) based on Gaussian‐mixed models. Regions > 2.5 standard deviations above the mean TPI within an individual were used as individualized epicenters, while entorhinal cortex (ERC) was used as a canonical group epicenter. Probabilistic tractography generated individual connectomes and a group connectome in amyloid‐negative participants. Network‐analysis calculated structural connectivity distances from epicenters for each region. Data were re‐arranged by tau pathology rank to average across all participants using each combination of individualized and group epicenters and connectomes. The model of Regional TPI = ß*Distance + e was tested in the training dataset using each of the 4 approaches: 1) Group canonical epicenter and group connectome (GE‐GC), 2) Group canonical epicenter and individual connectome (GE‐IC), 3) Individualized epicenters and group connectome (IE‐GC), and 4) Individualized epicenters and connectomes (IE‐IC). The resulting models were then applied to the validation dataset to predict regional TPI and compare to actual TPI.ResultThe fully individualized model demonstrated a significantly stronger relationship between connectivity and regional tau burden (ß = ‐0.95[‐1.03, ‐0.87]) compared to all other models (Z = ‐5.81, p < .001, Figure 2). When the four trained models were applied to the validation dataset, the fully individualized model explained 80% of regional TPI variance, while the other models explained = 52% (Figure 3).ConclusionIndividualized structural connectomes and tau epicenters capture the heterogeneity of Alzheimer’s disease and provide strong support for the cell‐to‐cell transmission of tau pathology in vivo.
Metabolic Hyperconnectivity in Underrepresented Individuals with long‐COVID
Authors: Machado Luiza Santos , Silveira Maiele Dornelles , de Bastiani Marco Antônio , Povala Guilherme , Borelli Wyllians Vendramini , Senger Joana Emilia , da Silva Ana Paula Bornes , da Ros João Pedro Uglione , de Mello Guilherme Bastos , Jotz Arthur Viana , Kadan Matheus Fakhri , Peixoto Guilherme G. Schu , Radaelli Graciane , Pascoal Tharick A. , Rosa‐Neto Pedro , Matushita Cristina Sebastião , Soder Ricardo Benardi , Schumacher‐Schuh Artur Francisco , Souza Diogo O. , Lourenco Mychael V , Faria Daniele de Paula de Paula , Coutinho Artur Martins , da Costa Jaderson Costa , de Souza Débora Guerini , Zimmer Eduardo R. 
Published: January 2025

AbstractBackgroundLong‐COVID is characterized by persistent symptoms post‐infection with SARS‐CoV‐2. This condition includes neurological manifestations and has been proposed as a potential risk factor for the development of dementia. Individuals presenting with dementia due to Alzheimer's disease have dysfunctional brain metabolism, including metabolic brain network (MBN) hypoconnectivity. However, whether long‐COVID alters brain metabolic architecture remains elusive. Here, we aimed to evaluate the brain metabolic connectivity in a Brazilian cohort of individuals presenting with long‐COVID.Method[18F]FDG‐PET images were acquired from 52 community‐dwelling Brazilians above 50 year old. Standardized uptake value ratio (SUVr) parametric maps were processed to a common 8 mm FWHM and generated using the pons as the reference region (Figure 1). We extracted the mean values of regions of interest using the ICBM152 atlas. [18F]FDG‐PET MBNs were constructed using a novel multiple sampling scheme, which assembles a stable group representative MBN based on bootstrap (n = 2000). Adaptive Synthetic Sampling Approach for Imbalance (ADASYN) was used to account for group imbalance and generated the ADA‐MBNs. Graph measures, including density, global efficiency, average degree, and assortativity coefficient were computed. Data were corrected for multiple comparisons using the False Discovery Rate (FDR) method (p<0.05).Result41 individuals with long‐COVID and 11 healthy controls (HC) were included (Table 1). We observed that long‐COVID individuals present PET hyperconnectivity in both MBN and ADA‐MBN. (Figure 2a‐b). The long‐COVID group presented increased density, global efficiency and average degree whereas assortativity coefficient were reduced in both MBN and ADA‐MBN.ConclusionOur findings showed that individuals with long‐COVID presented a brain metabolic hyperconnectivity, which is supported by increased density and average degree and may indicate a potential compensatory mechanism within the brain. In addition, the increase in global efficiency indicates that the brain of long‐COVID individuals exchanges metabolic information more efficiently, but the decreased assortativity coefficient suggests vertices with different properties connect to each other. Further longitudinal studies should follow these individuals for assessing microstructural and cognitive changes.