bluuebunny/crossref_metadata_2025_split huggingface dataset:
One‐week test‐retest reliability of an unsupervised, online version of the Digit Symbol Modalities task among older adults
Authors: Hooyman Andrew , Duff Kevin , Schaefer Sydney Y 
Published: January 2025

AbstractBackgroundMeasuring individual cognitive ability is critical for the diagnosis of neurodegenerative disease and prognosis of neurorehabilitation. Ideally, individual cognitive ability is achieved through an in‐person neuropsychological assessment by a trained and licensed clinician. However, there are several barriers that may prevent a prospective patient from being assessed (e.g., lack of transportation, reduced access to qualified professionals, etc.). Thus, we developed an online, unsupervised version of the digit symbol modalities task (DSMT), a subtest of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) that measures individual processing speed. The online DSMT can be performed both via a computer or touchscreen device. The purpose of this experiment was to examine the one‐week test‐retest reliability of the online DSMT among a group of adults 55 years and older.MethodSixty‐eight adults (mean age = 59.6 ± 4.8; female = 14, computer/touchscreen = 68/0) completed the initial and one‐week assessment of the online DSMT. Participants were presented with an instructional video on how to complete the assessment and a limited practice set of the DSMT to become familiarized. Presentation of symbol order was the same across each assessment day and between participants. A one‐way model of intraclass correlation for consistency was used to calculate the intraclass correlation coefficient (ICC).ResultResults indicated an ICC = .68 (p<.001, 95% CI = [.52; .79]). Furthermore, a dependent t‐test between the initial test (mean = 29.2+/‐10.6) and the one‐week test (mean = 30.8+/‐11.5) was not statistically significant (p = .16), which indicates that performance was relatively stable between time‐points. This result is consistent with prior examinations of ‘good’ test‐retest reliability of the DSMT administered in‐person.ConclusionOverall, these results indicate that online, unsupervised DSMT performance is consistent across a one‐week period among adults 55 years and older. Furthermore, the transformation of what is commonly a paper‐and‐pencil test into an online assessment allows for the engineering of digital based performance features that may serve as potential digital biomarkers of neurodegeneration. Future research will validate online DSMT performance with other indicators of neurodegenerative disease.
Neuroimaging predictors of cognitive resilience in the presence of Alzheimer’s disease pathology
Authors: Williams McKenna E. , Fennema‐Notestine Christine , Bell Tyler R. , Lin Shu‐Ju , Glatt Stephen J. , Kremen William S. , Elman Jeremy A. 
Published: January 2025

AbstractBackgroundStructural brain measures derived from magnetic resonance imaging (MRI) are commonly used to quantify Alzheimer’s disease (AD) progression, though their relationships with cognitive performance are highly heterogeneous. Some individuals demonstrate greater cognitive resilience—the ability to maintain cognitive performance despite adverse brain‐related changes—through as yet unknown mechanisms. We examined whether cortical thickness in specific regions confers resilience cross‐sectionally and/or longitudinally by moderating the relationships between established markers of AD risk and cognitive performance in amyloid‐positive adults.MethodAmyloid‐positive participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) GO/2/3 cohorts with relevant imaging data were included (n=160, observations=473). Risk markers included a validated cortical thickness/hippocampal volume AD risk signature (weighted sum of cortical thickness from 7 regions plus hippocampal volume) and cerebrospinal fluid phosphorylated tau (p‐tau). Linear mixed effects models tested whether region‐specific cortical thickness moderated relationships between these markers of AD risk and memory or executive functioning.ResultCross‐sectionally, thicker cortex in a composite of 8 regions of interest (ROIs) minimized the negative impact of thinner cortex in AD risk signature regions on executive function performance. Higher thickness in a resilience composite of these 8 ROIs at baseline was associated with less decline in memory over time (p=0.007), independent of effects of other markers of AD risk. Moreover, higher baseline resilience composite scores weakened the negative longitudinal effects of p‐tau (p=0.014), independent of the longitudinal effects of AD risk signatures and age.ConclusionWe identified 8 cortical regions that appear to confer cognitive resilience cross‐sectionally and longitudinally in the face of established indicators of AD pathology. Among amyloid‐positive individuals, thicker cortex in these resilience regions was cross‐sectionally associated with better executive function despite thinner cortex across established AD risk signature regions. Despite any cross‐sectional association with memory, thicker cortex in resilience regions predicted slower decline in memory over time and weakened the negative effects of p‐tau on memory over time. Preserved executive functioning associated with cortical thickness in these resilience ROIs may enable compensation in subsequent memory performance over time. These findings provide insight into possible mechanisms of cognitive resilience and individual variability in cognitive trajectories associated with AD.
Neuroinflammation potentiates the effect of amyloid‐β on longitudinal tau changes
Authors: Rahmouni Nesrine , Wang Yi‐Ting , Therriault Joseph , Servaes Stijn , Tissot Cécile , Macedo Arthur C. , Arias Jaime Fernandez , Hosseini Seyyed Ali , Stevenson Jenna , Kunach Peter , Hall Brandon J , Trudel Lydia , Gauthier Serge , Jeromin Andreas , Zetterberg Henrik , Blennow Kaj , Zimmer Eduardo R. , Ashton Nicholas J. , Benedet Andrea L. , Pascoal Tharick Ali , Rosa‐Neto Pedro 
Published: January 2025

AbstractBackgroundIt has been proposed that microglia release of proinflammatory factors reactive to amyloid plaques constitutes an early event leading to tau pathology. Here, we assessed how the rate of progression of tau‐PET and the rate of change in plasma pTau217 are affected by baseline levels of amyloid‐β and neuroinflammation.MethodsWe included 93 individuals from TRIAD cohort: 11 young individuals, 57 cognitively unimpaired elderlies, 15 with mild cognitive impairment and 10 individuals with Alzheimer’s Disease. Neuroinflammation, tau tangle and amyloid‐β (Aβ) deposition were assessed via [11C]PBR28‐PET, [18F]MK6240‐PET and [18F]AZD4694‐PET, respectively. Individuals also had plasma pTau217 quantified using the Alzpath assay. [11C]PBR28‐PET positivity was defined as a SUVR of 2.5SD above the mean of the young individuals in the precuneus and posterior cingulate. Voxel‐based regression models evaluated the interaction of TSPO‐ and Aβ‐PET with annual change in tau‐PET and plasma pTau217. The effect of the interaction on tau‐PET was also evaluated at the region‐of‐interest level using Braak regions. All models were corrected for age, sex and RFT corrected. Comparison of models was made using the Akaike Information Criterion (AIC) and the models’ goodness‐of‐fit was evaluated using R2 analyses. Models used [18F]MK6240‐PET SUVR yearly change as the outcome and used as predictors [11C]PBR28‐PET SUVR in the precuneus and posterior cingulate and [18F]AZD4694‐PET SUVR in the neocortical region.ResultsPositive associations were found between the interaction of Aβ‐ and TSPO‐PET at baseline predicting the yearly change in tau‐PET (Figure 1A). At the ROI level, the interaction significantly predicts tau load in Braak regions III‐IV in [11C]PBR28 positive individuals (Figure 1B). Positive associations were also found between the interaction of Aβ‐ and TSPO‐PET at baseline predicting the yearly change in plasma pTau217 (Figure 2A), which is driven by [11C]PBR28 positive individuals (Figure 2B). In addition, the interaction between Aβ‐ and TSPO‐PET predicting the yearly change in tau‐PET is the model with the highest R2 and the lowest AIC values in Braak regions III‐IV‐V‐VI (Figure 3).ConclusionThese results support the hypothesis that microglial activation potentiates the effect of Aβ plaques on tau tangle progression and the pTau217 increases across the aging and AD spectrum.
Phase 2 Study Results of Oral ALZ‐801 (Valiltramiprosate) in Early Alzheimer’s Disease Shows Potential Disease Modification Effect: 2‐Year Effect on Plasma Biomarkers, Volumetric MRI, Cognition Outcomes and Clinical Benefit Analysis
Authors: Hey John A. , Abushakra Susan , Blennow Kaj , Kesslak Patrick , Hort Jakub , Prins Niels D. , Sheardova Katerina , Schaefer Jean , Albayrak Adem , Pak Winnie , Power Aidan , Tolar Martin 
Published: January 2025

AbstractBackgroundALZ‐801 (valiltramiprosate), an oral brain‐penetrant amyloid‐oligomer inhibitor in Phase 3 testing in APOE4/4 homozygotes (APOLLOE4 trial). A 2‐year Phase 2 biomarker study was completed evaluating ALZ‐801 (265 mg BID) on plasma biomarkers, MRI, cognition, and clinical benefit in EAD APOE4 carriers. At trial end, subjects could enroll in a 1‐year long‐term extension with an ongoing biomarker and cognition analysis.MethodThis 104‐week, open‐label study enrolled 84 subjects (MMSE 22‐30, CDR‐G 0.5‐1, positive amyloid‐PET or CSF biomarkers). Plasma and clinical testing occurred every 13 weeks; MRI every 52 weeks. Primary outcome was plasma p‐tau181; cognitive tests were Rey Auditory‐Verbal‐Learning Test (RAVLT) and Digit‐Symbol‐Substitution Test (DSST). Dr. Blennow’s Laboratory (Sweden) conducted plasma biomarker analyses (Simoa, Euroimmun assays). Hippocampal volume and cognitive tests were compared to matched group from ADNI‐1 observational study using simple matching (age, APOE4 genotype, disease stage) and propensity scores as covariates in the MMRM analysis. Clinical and HV benefit was determined by Cohen’s d score. For plasma biomarkers, observed data changes‐from‐baseline were analyzed with 2‐sided simple t‐tests.Result84 subjects were enrolled; 51% female, 69 years, MMSE 26.0, 70%/30% had MCI/Mild AD; 70 completed 104‐weeks. Plasma p‐tau181 showed significant reductions at all timepoints reaching 31%‐43% over 52‐104 weeks (p = 0.045); Aβ42 decreased ∼4% over 104 weeks (p = 0.042). Hippocampal atrophy (3.6%) was ∼28% lower than matched external control (ADNI‐1). RAVLT‐total memory and DSST remained above/at baseline through 104 weeks; Cohen’s d clinical benefit effect in RAVLT and hippocampal volume ranged from 0.5 to 0.7. Cognitive stabilization correlated with decreased hippocampal atrophy (Spearman’s r = 0.38‐0.43, p≤0.002); and cortical thinning (r = 0.35‐0.58, p≤0.004). Most common TEAE was mild nausea, and no ARIA‐E was observed.ConclusionOver 2 years, oral ALZ‐801 reduced plasma p‐tau181. Cognitive stabilization correlated with reduced brain atrophy, showing treatment benefit compared to external controls. Cohen’s d values for hippocampal volume and cognition suggest strong clinical benefit. No ARIA‐E/vasogenic edema was detected. These biomarker results support the disease‐modifying effects of ALZ‐801 in Early AD with promising clinical efficacy and favorable safety in APOE4 carriers. A Phase 3 78‐week trial in APOE4/4 homozygotes Early AD (EAD) is ongoing with results expected in 2024.
Large‐Scale Analysis of the Plasma Proteome and Cognitive Correlates in Traumatic Encephalopathy Syndrome and Chronic Traumatic Encephalopathy
Authors: Saloner Rowan , Casaletto Kaitlin B. , VandeVrede Lawren , Abisambra Jose F. F , Smith Glenn E. , Spina Salvatore , Grinberg Lea T. , Seeley William W. , Miller Bruce L. , Kramer Joel H. , Rabinovici Gil D. , Asken Breton M. 
Published: January 2025

AbstractBackgroundChronic traumatic encephalopathy (CTE) is a neurodegenerative tauopathy specific to individuals with repetitive head trauma. Traumatic encephalopathy syndrome (TES) is the proposed clinical syndrome resulting from CTE with or without other contributing neuropathologies. Pathophysiological mechanisms driving CTE and underlying TES symptoms are not understood. Using network‐based bioinformatics, we conducted the first large‐scale analysis of the plasma proteome in TES and CTE.MethodsWe leveraged a proximity extension assay (Olink Explore) to quantify 2,778 plasma proteins in 34 TES, 39 biomarker‐confirmed Alzheimer’s disease (AD), and 44 controls (HC; Table 1). TES was subdivided on Aβ‐PET status (23 TESAβ‐, 11 TESAβ+). Secondary analyses focused on antemortem plasma ofrom brain donors with autopsy‐confirmed CTE (N=8) and without (N=12). Differential abundance and network analyses of proteomic signatures were annotated via gene ontology and cell type enrichment. Protein co‐expression modules were age‐ and sex‐adjusted, and compared between groups using analysis of variance (Tukey’s post‐hoc with Cohen’s d). Within TESAβ‐, differential Spearman’s correlations examined individual protein associations with cognitive composites (memory, executive function, language, visuospatial) and co‐expression modules were tested for overrepresentation of cognitive‐associated proteins using Fisher’s exact tests with false discovery rate (FDR) correction.ResultsDifferential abundance analysis revealed a bias towards increased plasma protein abundance in TESAβ‐, with enrichment for mitochondrial proteins (e.g., MECR, TOMM20). Network analysis identified 9 protein co‐expression modules (M1‐M9), of which 5 were elevated in TESAβ‐, but not TESAβ+ or AD, compared to HC (M1‐cell division/mitochondrion, d=1.4; M2‐TNF signaling/cell adhesion, d=0.72; M4‐cell metabolism, d=0.90; M5‐chemokine, d=0.80; M8‐muscle, d=0.88; Figure 1). Metabolic and immune‐linked signals in TESAβ‐ were replicated when comparing autopsy‐confirmed CTE to plasma of brain donors without CTE or those living with AD and HC. Within TESAβ‐, M2‐TNF signaling was highly enriched for proteins negatively associated with memory (FDR‐p=8.5e‐08) and executive function (FDR‐p=2.3e‐6).ConclusionsNetwork‐based proteomics identified elevated peripheral molecular signatures that differentiated TES and autopsy‐confirmed CTE from healthy older adults and biomarker‐confirmed AD. Mitochondrial and inflammatory pathway dysregulation may be uniquely upregulated in CTE and underly cognitive changes in TES. Future protein‐specific assessment (Figure 2) will inform biomarker and therapeutic targets in older adults at greatest risk for CTE.
Characterization of pulsations in the brain and cerebrospinal fluid using ultra‐high field magnetic resonance imaging
Authors: de Almeida Bruno , Martins Tiago Amaro , Wu Minjie , Wilckens Kristine A , Minhas Davneet S , Ibinson James W , Aizenstein Howard J , Santini Tales , Ibrahim Tamer S 
Published: January 2025

AbstractBackgroundBrain fluid flow plays a crucial role in maintaining brain health by eliminating potentially harmful waste products like amyloid‐beta and tau [1‐2]. This process is potentially facilitated by pulsations in the perivascular space, influenced by the neurovascular unit and autonomic nervous system, which may vary in brain diseases such as Alzheimer’s disease (AD) [3‐4]. Using a 7 Tesla MRI scanner and ultrafast echo‐planar imaging (EPI), we developed a non‐invasive neuroimaging methodology to characterize the in‐vivo frequency and amplitude responses of pulsations of cerebrospinal fluid (CSF) flow.MethodBrain images from six volunteers were acquired using a 7T MRI Scanner and an in‐house developed 16‐channel Tic‐Tac‐Toe transmit array with a 32‐channel receive coil. The human‐connectome EPI multiband MR sequence was optimized to present a real‐time visualization of the CSF flow in the brain. For the first volunteer, two axial and one sagittal slices were obtained, while whole‐brain coverage was acquired for the remaining volunteers, where the acquisition was divided into 19 slabs, each consisting of 3 axial slices. A spectral analysis based on Fast Fourier Transform (FFT) was conducted for the whole brain and grey matter, white matter, and CSF regions.ResultFigure 1 presents the processed axial and sagittal slices acquired from the first volunteer, demonstrating the presence of a periodic variation of the CSF signal. Figure 2 presents the identification of peaks in the spectrum acquisitions of whole‐brain segments for one volunteer, which exhibited similar frequencies, magnitudes and bandwidths among different volunteers. Quantitative results of this analysis are summarized in Table 1.ConclusionThis project developed a real‐time visualization of CSF pulsations based on a non‐invasive ultrafast EPI obtained with a 7T MRI scanner. The identification of similar frequency peaks (around 0.3, 0.8, 1.1, 2.3 and 3.1 Hz) and magnitudes among healthy volunteers suggests its potential as a feasible biomarker. Future work will examine this technique’s potential to identify changes in brain fluid dynamics associated with AD progression and pathology.Funding: NIH R01AG063525, R01MH111265, University of Pittsburgh CRC's RRID:SCR_022735.References:Nedergaard, 2013Xie et al., 2013Peng et al., 2016Ramanathan et al., 2015
Using image‐text similarity scores from picture descriptions for differentiating the logopenic variant of progressive aphasia from amnestic Alzheimer’s dementia
Authors: Pugalenthi Lokesha , Dial Heather R , Li J. Jessy , Schmitz Suzanne , Henry Maya L. , Wauters Lisa , Keller Jeffrey N. , Largent Avery , Chang Patrick , Chang Joshua , Foil Heather , Lester‐Smith Rosemary A , Toprac Paul , Hilsabeck Robin C. 
Published: January 2025

AbstractBackgroundPrimary progressive aphasia (PPA) is a language‐led dementia associated with underlying Alzheimer’s disease (AD) or frontotemporal lobar degeneration pathology. As part of the Alzheimer’s spectrum, logopenic (lv) PPA may be particularly difficult to distinguish from amnestic AD, due to overlapping clinical features. Analysis of linguistic and acoustic variables derived from connected speech has shown promise as a diagnostic tool for differentiating dementia subtypes. Here we investigate the utility of a machine learning (ML)‐based classifier for differentiating lvPPA from amnestic AD using an image‐text similarity metric derived from a picture description task.MethodMonolingual English speakers diagnosed with lvPPA (n=18) and amnestic AD (n=14) were asked to describe a picture (Cat Rescue). A similarity score between the image and patient’s transcription was derived with each model of the Vision‐Language encoder CLIP. This involved computing the cosine similarity between the image‐ and transcription‐based representation vectors. These image‐text similarity scores were fed into 10 ML classification algorithms to differentiate lvPPA from amnestic AD.ResultFor differentiating lvPPA from amnestic AD, our CLIP‐based feedforward neural network classifier achieved F1, AUC, and Accuracy scores of 81%, 80%, and 81% respectively. This outperformed our baselines of stratified random sampling and uniform random sampling by 30%.ConclusionThe current study shows promising differentiation of lvPPA from amnestic AD through the single feature of image‐text similarity. This approach holds potential as an automated connected speech analysis tool for differential diagnosis of dementia subtypes. Future directions include evaluating performance in a larger dataset and comparing the classification performance between image‐text similarity and acoustic‐linguistic features.
Evaluating impact of racialization on imaging and plasma biomarkers
Authors: Gogola Alexandra , Zeng Xuemei , Saeed Anum , Lopresti Brian J , Snitz Beth E. , Tudorascu Dana , Minhas Davneet S , Ikonomovic Milos D , Kofler Julia , Matan Cristy , Mason Neale S , Pascoal Tharick A. , Aizenstein Howard J , Mathis Chester , Klunk William E , Zetterberg Henrik , Blennow Kaj , Lopez Oscar L. , Reis Steven E. , Villemagne Victor L , Karikari Thomas K , Cohen Ann D 
Published: January 2025

AbstractBackgroundImaging and plasma biomarkers are widely used in Alzheimer’s disease (AD) observational studies and clinical trials. Due to the lack of racial or ethnic diversity in earlier studies, a more complete understanding of biomarker differences across racialized groups is needed. Further, results from the few previous studies have disagreed on both the magnitude and direction of AD biomarker differences in racialized groups. We evaluated differences in plasma biomarker and Aβ PET outcomes between participants racialized as either Black or African American (AA) or non‐Hispanic white (NHW).MethodWe evaluated 321 participants enrolled in observational studies at the University of Pittsburgh with PET imaging and plasma biomarker assessments including: Global PiB SUVR, plasma Aβ42/Aβ40, p‐tau181, p‐tau217, p‐tau231, NfL, and GFAP (Simoa HD‐X). Outlier analysis resulted in a total of 88 AA and 166 NHW participants. To further refine the comparison, AA and NHW participants were matched based on age, sex, and ApoE status, resulting in a matched set with 88 AA and 88 NHW participants. A second matched subset was established based on the availability of p‐tau217 measures. Group differences were assessed using Mann‐Whitney U tests.ResultIn both the full and matched sets, Aβ42/Aβ40, NfL, and GFAP showed no differences between the AA and NHW groups (p>0.05). Conversely p‐tau181 and p‐tau231 were higher in AA participants (p<0.05) and global PiB SUVRs and p‐tau217 were higher in NHW participants (p<0.01). (Table 1)ConclusionIn both the full and matched datasets, the AA and NHW groups showed significant differences in Global PiB SUVR and p‐tau217 outcomes in the opposite direction of p‐tau181 and p‐tau231 outcomes. As such, racialization should be given more consideration in AD clinical research, particularly when biomarker results are used for inclusion or exclusion criteria. Future work will explore the influence of racialization on other imaging and plasma biomarkers and their relationship with cognitive performance.