bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognitive impairment, brain connectivity, and long‐Covid: understanding the complex interplay
Authors: Hernández Micaela A , Travi Fermin , Kamienkowski Juan , Bianchi Bruno , Carello Agostina , Helou Belén , Crivelli Lucia , Slezak Diego Fernández , Sevlever Gustavo , Allegri Ricardo , Calandri Ismael Luis 
Published: January 2025

AbstractBackgroundThe persisting cognitive symptoms observed in individuals after a Covid‐19 infection (long‐Covid) remain an enigmatic aspect of the disease. Clinical descriptions in the literature are dissimilar, suggesting more than one clinical phenotype. Our study aims to explore cognitive performance and brain network of long‐Covid patients, to determine the neural correlates of cognitive impairment.MethodCase‐Control study of individuals with cognitive complaints persisting at least 12 weeks after Covid‐19 infection, and age‐ and sex‐ matched healthy controls without history of covid‐19 infection. We performed a brain MRI with rs‐fMRI sequences and a neurocognitive test (NCT) based on the UDS‐3 protocol. We generated z‐scored neuropsychological data, normalized to the normal population, and averaged them to create 7 cognitive domains. We segmented rs‐fMRI data into seven distinct functional neural networks (Salience/Ventral Attention, Dorsal Attention, Default, Frontoparietal, Visual, Somatomotor, and Limbic) and measured network efficiency, largest connected component, average participation coefficient, and modularity. We applied a Wilcoxon test to assess the significance of differences in measurements over networks.ResultForty‐two subjects were recruited, 30 were female. Mean age 56 (±12). The control group consisted of 43 subjects, 25 were female. Mean age 59 (±9). The NCTs scores yielded statistical significant differences in long‐Covid subjects compared to controls, at memory (mean difference:‐1.12, IQR: ‐1.78; ‐0.32), attention (mean difference: ‐1.21, IQR: ‐1.80; ‐0.40), executive (mean difference: ‐0.82, IQR: ‐1.37; ‐0.12), and global composites (mean difference: ‐0.87, IQR: ‐1.36; ‐0.25). Regarding functional networks, we observed significant differences (p < 0.001) in the global and mean local efficiency of the Salience/Ventral Attention and Global networks, and to a lesser extent (p < 0.005 and p < 0.01) in the Default and Dorsal Attention networks (Figure 1).ConclusionOur study identified that long‐Covid subjects differ in their cognitive performance compared to controls with less effective and organized connection among Salience/Ventral Attention and Global networks.
Aβ42/40 and p‐tau 181 as disease biomarkers in Atypical Alzheimer’s disease
Authors: Singh Neha Atulkumar , Graff‐Radford Jonathan , Li Danni , Mielke Michelle M. , Machulda Mary M. , Schwarz Christopher G. , Senjem Matthew L. , Jack Clifford R. , Lowe Val J. , Josephs Keith A. , Whitwell Jennifer L. 
Published: January 2025

AbstractBackgroundBlood plasma metrics provide excellent biomarkers of the presence of Alzheimer’s disease (AD) pathology in population cohorts. However, it is less clear whether plasma metrics correlate with PET measures of AD pathology in cohorts of patients with advanced AD disease, particularly in those with atypical clinical presentations of AD.MethodSeventy‐seven patients (visual variant=43, language variant=32, motor variant=1 and dysexecutive variant=1) with PET biomarker‐confirmed atypical AD were recruited by the Neurodegenerative Research group at Mayo Clinic, Rochester, MN, underwent Aβ (Pittsburgh Compound‐B) and tau (18F‐flortaucipir) PET and provided a blood sample. Blood plasma analysis was performed to assess p‐tau 181 and Aβ42/40 ratio concentrations using the Quanterix Simoa platform. Multivariate linear regression models assessed the relationship between plasma concentrations and both global Aβ, atypical AD summary and regional tau PET measures. For each PET measure, two separate models were fit to assess the influence of each plasma biomarker separately, while the third model included all plasma measures to assess the combined influence of all biomarkers on PET uptake. To investigate differences in plasma concentrations between atypical AD phenotypes, we performed Mann‐Whitney’s test across the visual and language variants of AD.ResultPlasma Aβ42/40 ratio showed positive associations with tau PET uptake, specifically within precuneus, parietal and temporal regions and was not associated with Aβ PET. There was no relationship between plasma p‐tau 181 and Aβ or tau PET uptake. However, the model that included both plasma biomarkers showed that with the addition of p‐tau 181, all significant associations between Aβ42/40 ratio and regional tau uptake were weakened to trends. The Aβ42/40 ratio continued to show no relationship with global Aβ‐PET uptake and plasma p‐tau 181 showed no relationship to PET measures (Figure 1). Lastly, no significant difference in plasma Aβ42/40 and p‐tau 181 levels was noted between the visual and language variants of AD (Figure 2).ConclusionThe lack of associations between plasma concentrations and PET measures of Aβ and tau in this relatively advanced AD cohort may suggest that plasma concentrations have greater utility as diagnostic biomarkers of early AD as compared to advanced AD.
Utility of Plasma Biomarkers in Screening for Brain Amyloid in the 1Florida Alzheimer Disease Research Center (ADRC)
Authors: Barker Warren W , Velasquez Karen , Loewenstein David A. , Curiel Rosie E , Armstrong Melissa J , Rosselli Monica , Adjouadi Malek , Asken Breton M. , Vaillancourt David , DeSimone Jesse , Smith Glenn E. , Marsiske Michael , Fiala Jacob , Weber Darren M , Kim Jueun C , Herrera Mileidys , Velez‐Uribe Idaly , Duara Ranjan 
Published: January 2025

AbstractBackgroundWith the emergence of anti‐amyloid drugs, there is an increased need to determine the presence of brain amyloid in people using non‐invasive, cost‐effective biomarkers. The goal of this study was to determine the added and stand‐alone value of plasma biomarkers for predicting positive amyloid PET in a mixed sample of Hispanic and non‐Hispanic older adults.MethodParticipants (n=209) from the 1Florida ADRC at Mount Sinai Medical Center, Miami Beach had neurological and neuropsychological evaluations; MRI, rated positive (Hpc+) or negative (Hpc‐) for hippocampal atrophy on visual read; amyloid PET brain scans, rated amyloid positive (A+) or negative (A‐) on visual read; blood draws for APOE ε4 genotyping (e4+, e4‐); and plasma biomarkers including Abeta 42/40 ratio (Quest Diagnostics), p‐tau217 (ALZPath), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) (Quanterix). A base logistic regression model including age, sex, APOEε4 status, and hippocampal atrophy was a reference to assess the value of adding plasma markers in predicting A+/A‐. Areas under the receiver operating characteristic (ROC) were computed and DeLong’s approach was used to compare ROC curves. Youden’s index was used to identify optimal sensitivities/specificities to discriminate A+ from A‐ participants.ResultDemographics and clinical data are shown in Table 1. In the base model, the AUC was 0.78 with both APOEe4 and hippocampal atrophy as significant independent predictors of A+ (Table 2). Prediction of A+ was improved by adding all plasma biomarkers (AUC=0.96; 93%/87% sensitivity/specificity), with APOEe4, Abeta42/40, and p‐tau217 as independent predictors. Adding either Abeta 42/40 (AUC=0.88) or p‐tau217 (AUC=0.94) alone to the base model also improved model prediction.As stand‐alone predictors of A+, the optimal specific/sensitivity was 85%/89% for p‐tau217 and 77%/81% for Abeta42/40; p‐tau217 outperformed Abeta42/40 (AUC=0.92 versus 0.82) (Figure 1). There was a trend for the combination of both biomarkers to outperform p‐tau217 alone (AUC=0.94 versus 0.92).ConclusionPositive amyloid PET status can be predicted with high accuracy in an ethnically diverse population using combinations of biomarkers, APOE genotype, and a measure of hippocampal atrophy. As a stand‐alone biomarker, p‐tau217 performed better than other biomarkers in predicting amyloid status.
Multimodal Analysis of Behavior During Stroop Test for Characterization of Alzheimer's Disease Signs
Authors: Meyer Trevor , Favaro Anna , Oh Esther S , Irazoqui Pedro , Dehak Najim , Moro‐Velazquez Laureano 
Published: January 2025

AbstractBackgroundClinical rating scales and neuropsychological tests are commonly used for assessing sign and disease severity, yet lack detail in the early stages Alzheimer’s Disease (AD). Existing evaluation methods can be subjective, nonlinear, expensive, or reliant on anecdotal evidence making objective and consistent characterization and phenotyping of AD difficult. Multimodal analysis of patient behavior, rather than scoring of patient‐generated output which can be skewed by compensation strategies, presents a unique opportunity to objectively quantify AD related changes. Using the Stroop Test (ST), we present a multimodal analysis of eye movement and spoken responses during completion of ST tasks, with the goal to characterize patient behavior.Method17 individual AD subjects and 24 age‐matched cognitively normal controls (CTL) were recruited from the Johns Hopkins Memory and Alzheimer’s Treatment Center and the Movement Disorders Clinic at the Johns Hopkins University School of Medicine. Eight subjects returned for two or three follow up sessions at least 20 weeks apart, totaling 29 AD recording sessions. An Eyelink Portable Duo in head‐free‐to‐move mode was used to record eye movements and spoken responses. We analyzed subjects’ interaction with ST using several metrics relating to blinking, saccade, fixation, gaze, prosodic, accuracy, and timing characteristics. We summarize patient behavior abnormality by scaling behavioral metrics into positive z‐scores using CTL performance and summarize the overall abnormality as the average z‐score across 45 metrics.ResultThe average deviation across metrics correlates with MoCA scores (p<0.001). These metrics display significantly different distributions between the AD from CTL subjects (p<0.001). A visualization we’ve coined as a “sign profile” summarizes patient behavior abnormality during ST. In all subjects our abnormality measurement closely matches MoCA scores and clinician observations.ConclusionAD subjects execute the ST with eye movement and speech behaviors which significantly differ from CTL subjects, and subjects with longitudinal recordings show encouraging results for the use of this analysis in monitoring. By utilizing measures from more than one feature, we detect early clinical changes a single‐score test might miss. This analysis offers comprehensive patient profiling, providing an intuitive and quantitative understanding of patient signs enabling more accurate detection and management of disease.
APOE‐ε4 carriership modifies the association of CCL11 and sVCAM1 plasma protein levels with cognitive performance in individuals at risk of Alzheimer's disease
Authors: Hernández‐Villamizar Luis Felipe , Segura‐Retana Pol , Escalante Armand González , Milà‐Alomà Marta , Ortiz‐Romero Paula , Diego‐Osaba Marina De , Braun‐Wolhfahrt Luisa , López‐Martos David , Sánchez‐Benavides Gonzalo , Zetterberg Henrik , Blennow Kaj , Anastasi Federica , Suarez‐Calvet Marc 
Published: January 2025

AbstractBackgroundIn murine models, peripheral blood factors have been identified as having either a brain rejuvenating or ageing effect. However, it is unclear whether these blood factors have similar effects in humans. We aimed at testing the association between these blood factors and cognitive performance in cognitively unimpaired (CU) individuals at risk of Alzheimer’s disease (AD).MethodWe included 414 CU participants from the ALFA+ cohort [mean age: 61.1(±4.72), women:60.4%, APOE‐ε4 carriers:54.8%, and amyloid‐positive:34.2%]. A subset of participants (n=341) had longitudinal follow‐up [mean follow of 3.28 years (0.50)]. Amyloid positivity was determined by CSF‐Aβ42/40<0.071. Blood factors associated with an ageing effect [β2‐microglobulin(β2‐M), CCL2, CCL11, CCL19, Haptoglobin, sVCAM1] or rejuvenating effect (CSF2 and TIMP2) were measured using ELISA, MSD, or Simoa immunoassays.Through linear regression analyses we first tested the association between chronological age and each protein, correcting by sex. Then, we tested the association of each protein with baseline cognition and longitudinal cognitive changes at follow‐up, adjusting for age, sex and years of education. Cognitive data included the PACC score and domain‐specific composites (attention, episodic memory[EM] and executive function). The modifying effect of sex, APOE‐ε4 carriership, and amyloid status was also tested and significant interactions stratified.Resultβ2‐M and CCL11 significantly increased with chronological age (Figure 1). Only APOE‐ε4 carriership modified the association of age‐related blood factors CCL11 (pint=0.011) and sVCAM1 (pint=0.006) with cross‐sectional and longitudinal EM, respectively (Figure 2). In APOE‐ε4 non‐carriers, higher CCL11 was associated with better EM at baseline (β=0.105, p=0.025), while higher sVCAM1 was associated with better EM at follow‐up (β=0.076, p=0.010). Inversively, in APOE‐ε4 carriers, higher CCL11 was associated with worse EM at baseline (β=‐0.104, p=0.014), and higher sVCAM1 was associated with worse EM at follow‐up (β=‐0.073, p=0.014).ConclusionWe observe an association between higher CCL11 and sVCAM1 and worse cognition in APOE‐ε4 carriers. This may suggest that the APOE‐ε4 carriers are more susceptible to the ageing effect of these blood factors.
Cognitive changes in co‐pathological Alzheimer’s disease and Synuclein diseases: A study of amyloid, tau, and alpha‐Synuclein biomarkers in the ADNI dataset
Authors: Wang Jian , Lu Ming , Shcherbinin Sergey , Morris Amanda , Rathore Saima , Iaccarino Leonardo , Pontecorvo Michael , Collins Emily C. , Mintun Mark 
Published: January 2025

AbstractBackgroundAlzheimer’s and Synuclein diseases are characterized by distinct biomarkers and frequently co‐occur, suggesting potential interactions between their pathological pathways. This study leverages amyloid and tau PET imaging, along with CSF Phosphorylated tau (P‐tau) and alpha‐synuclein measurements from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to investigate the impact of co‐pathology on cognitive functions.MethodWe conducted an analysis using ADNI data (Table 1) from the 2024‐01‐08 download, including results from the CSF alpha‐Synuclein Seed Amplification Assay (SAA, 2023‐09‐29 release, 1637 samples out of 1638 records included in the analysis). The diagnostic performance of the CSF alpha‐Synuclein SAA was assessed by comparing it to autopsy alpha‐Synuclein immunohistochemistry (IHC) findings. Cognitive and functional assessments were examined in relation to amyloid, tau, and alpha‐synuclein biomarkers, both individually and collectively. Mixed‐model repeated measures (MMRM) analysis was utilized to evaluate ADAS‐Cog13, MMSE, and CDR‐SB score change up to 36 months following CSF collection, adjusting for age, sex, number of APOE e4 alleles, cognitive scores and clinical diagnoses at CSF collection.ResultThe CSF alpha‐Synuclein SAA showed a strong agreement with postmortem alpha‐Synuclein IHC (Figure 1). The probability of positive alpha‐Synuclein (Syn+) was associated with aging and the severity of clinical diagnosis (cognitively normal to mild cognitive impairment to dementia). Cross‐sectionally, subjects with Amyloid+Syn+ had worse cognitive scores compared to those with Amyloid+Syn‐ status. Investigation of the relationship between alpha‐Synuclein and tau biomarkers was pending on additional samples in upcoming data release. MMRM analysis (Figure 2) revealed that longitudinally subjects of MCI or dementia with Amyloid+Syn+ status declined faster in ADAS13, MMSE, and CDRSB scores than those with Amyloid+Syn‐ status. These differences were statistically significant at 36 months post‐CSF collection for MMSE (p < 0.01) and CDR‐SB (p < 0.05).ConclusionThe worse cross‐sectional cognitive scores, as well as faster longitudinal decline in Amyloid+Syn+ vs Amyloid+Syn‐ subjects suggest that the co‐occurrence of these biomarkers indicates a more aggressive trajectory of dementia. These observations reinforce the importance of comprehensive biomarker profiling in predicting cognitive decline and underscore the need for further studies to investigate the complex dynamics of co‐pathology in Alzheimer’s and Parkinson’s diseases.
Association between temporal lobe cortical NODDI measures and memory function
Authors: Pillai Jay J , Reid Robert I. , Weigand Stephen D. , Cogswell Petrice M , Vemuri Prashanthi , Machulda Mary M. , Knopman David S. , Graff‐Radford Jonathan , Petersen Ronald C. , Jack Clifford R. 
Published: January 2025

AbstractBackgroundCortical structural changes in the temporal lobes including global and hippocampal volume loss and decrease in cortical thickness are well‐associated findings linked to cognitive decline in MCI and dementia patients. Neurite orientation dispersion and density imaging (NODDI) is a multishell diffusion MRI method enabling assessment of tissue microstructural integrity at the axonal and dendritic level. We wished to determine whether changes in temporal cortex orientation dispersion index (ODI) & neurite density index (NDI) correlate with decreases in memory function.MethodThe MCALT_ADIR122 cortical atlas was used for ROI designation. NODDI imaging was obtained on a 3T Siemens Prisma scanner with 2 mm isotropic resolution. Participants (ages 60‐95 years) were cognitively unimpaired (CU) or had mild cognitive impairment (MCI). CU & MCI subjects were enrolled in the Mayo Clinic Study of Aging (MCSA) and underwent neuropsychological testing including 3 memory tests from which a composite memory z score was calculated. A generalized additive regression model was used to estimate z scores as a smooth function of ODI, NDI and cortical thickness or volume with adjustment for age, gender, education, MCSA cycle number, WMH and intracranial volume.ResultThe Table displays demographic data. Figures 1 and 2 show the relationship of NDI and ODI measures to memory z scores across participants in individual ROIs both before and after adjustment for cortical thickness (“structural MRI”) as well as for confounds listed above. Both higher cortical thickness and higher NDI values in the hippocampus and entorhinal cortex were associated with significantly higher memory z‐scores (p<0.001) (Figure 1). Higher ODI values in addition to greater cortical thickness in temporal lobe regions, including within the hippocampus, parahippocampal gyrus, entorhinal cortex and inferior temporal gyrus, were associated with higher memory z‐scores (Figure 2). These significant associations (p <=0.01) were maintained after adjusting for cortical thickness in all these regions except entorhinal cortex for ODI.ConclusionNODDI‐derived measures of microstructural integrity (NDI & ODI) within the temporal cortex may provide information about memory decline, beyond what cortical thickness analysis provides, and may be potentially useful for monitoring therapeutic effects of AD immunotherapy in the future.
Astrocyte reactivity associates with tau phosphorylation and neurodegeneration before detectable amyloid‐β pathology
Authors: Saha Pampa , Povala Guilherme , Ferreira Pamela C.L. , Amaral Livia , Abbas Sarah , Lussier Firoza Z , Rodrigues Matheus Scarpatto , Oliveira Markley , Rahmouni Nesrine , Tissot Cécile , Soares Carolina , Therriault Joseph , Servaes Stijn , Stevenson Jenna , Hong Chang‐Hyung , Roh Hyun Woong , Karim Helmet T. , Benedet Andrea L. , Ashton Nicholas J. , Zetterberg Henrik , Blennow Kaj , Karikari Thomas K , Kim Sang Joon , Bellaver Bruna , Pascoal Tharick Ali , Rosa‐Neto Pedro 
Published: January 2025

AbstractBackgroundAβ plaques are the first detectable signs of AD pathology. Our group recently demonstrated that the astrocyte activation marker, glial fibrillary acidic protein (GFAP), has a pivotal role in the association between Aβ burden and tau phosphorylation. However, the role of astrocyte activation in individuals that do not present detectable Aβ pathology using biomarkers is still underexplored. Here we sought to understand the association between plasma GFAP with tau phosphorylation and neurodegeneration in Aβ negative individuals.Method598 study participants [cognitively unimpaired, (CU)=200, and cognitively impaired, (CI)=398] from two cohorts (TRIAD, Canada and BICWALZ, South Korea) were assessed for Aβ‐PET, plasma GFAP, p‐tau217, NfL, and hippocampal volume measures. Pearson correlations between plasma GFAP and plasma p‐tau217, plasma NfL along with hippocampal volume was performed in Aβ‐PET negative individuals.ResultRemarkably, we found that plasma GFAP levels positively correlate with plasma p‐tau217 levels in Aβ‐PET negative individuals in both cohorts [TRIAD cohort: r=0.23, p=0.01; BICWALZ cohort: r=0.21, p=0.0001; Figure: 1A, B]. Further, the correlation between plasma GFAP with plasma NfL has also been found to be positively correlated among the two cohorts [TRIAD cohort: r=0.45, p=0.0001; BICWALZ cohort: r=0.49, p=0.0001; Figure: 2A, B]. We also observed that hippocampal volume, as a neurodegeneration marker, reveals a significant negative Pearson correlation with plasma GFAP levels in Aβ‐PET negative human individuals from both the cohorts [TRIAD cohort: r=‐0.27, p=0.0009; BICWALZ cohort: r=‐0.24, p=0.0001; Figure: 3A, B].ConclusionOur study provides evidence from research and clinical cohorts that astrocyte reactivity may be associated with very early tau phosphorylation and neurodegeneration in the absence of Aβ pathology.
Resting‐State EEG Features of Cognitive Fluctuations in Patients with Lewy Body Dementia
Authors: Negida Ahmed , Lageman Sarah , Mukhopadhyay Nitai , Barrett Matthew J 
Published: January 2025

AbstractBackgroundLewy body dementia (LBD) is characterized by fluctuations in arousal and alertness, i.e., cognitive fluctuations (CF). Although CF significantly impacts quality of life, its neurophysiological basis remains poorly understood. This study's objective was to identify specific EEG features associated with cognitive fluctuations in patients with LBD.MethodWe conducted a cross‐sectional study of 35 patients prospectively enrolled through the outpatient clinics of the Department of Neurology at Virginia Commonwealth University. Based on the Clinician Assessment of Fluctuations, participants with Parkinson’s disease, Parkinson disease with dementia, and dementia with Lewy bodies were categorized as Lewy body disease without CF (LBwoCF) and Lewy body dementia with CF (LBDwCF). All patients underwent resting‐state EEG recording with eyes closed and eyes open for 3 minutes each. EEG data were preprocessed and cleaned, and the following features were extracted: dominant frequency (DF), dominant frequency variability (DFV), dominant frequency prevalence (DFP) within the alpha band (8 to 13 Hz), individual alpha peak frequency (IAF), and alpha reactivity. Kruskal‐Wallis tests and logistic regression models were used to evaluate the relationship between EEG features and group (LBDwCF vs. LBwoCF).ResultWe analyzed EEG features for 17 LBDwCF and 18 LBwoCF. For both EEG conditions, eyes open and eyes closed, the LBDwCF group had significantly lower DF, posterior DF, DFP (alpha), and IAF but not alpha reactivity or DFV, compared to LBwoCF (all P<0.003, Table 1). The EEG feature with the largest effect size (ε²=0.43) was DFP within the alpha band measured from the posterior electrodes in the eyes closed condition. These EEG features, except for IAF, remained significant predictors of group (LBDwCF vs. LBwoCF, all P<0.03, Table 2) in logistic regression models adjusting for age and Montreal Cognitive Assessment (MoCA) score.ConclusionAmong patients with LBD and PD, resting‐state EEG features were associated with CF. These features were significant predictors of CF even after adjustment for MoCA scores and age. The development of an EEG‐based biomarker of cognitive fluctuations may improve diagnosis of this clinical feature and thus diagnosis of LBD.