bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations between neuropsychological tests, plasma biomarkers and PET amyloid scans in a memory clinic cohort
Authors: Bucci Marco , Almkvist Ove , Bluma Marina , Savitcheva Irina , Zapater‐Fajari Mariola , Chiotis Konstantinos , Matton Anna , Kivipelto Miia , Jeromin Andreas , Molfetta Guglielmo Di , Ashton Nicholas J. , Blennow Kaj , Zetterberg Henrik , Nordberg Agneta K 
Published: January 2025

AbstractBackgroundStudies on plasma biomarkers have shown promising results for Alzheimer’s disease(AD) neuropathology in a research setting, but their associations to neuropsychological(NP) tests have not been extensively studied in clinical cohorts. The main aim was to investigate associations between NP, plasma biomarkers and amyloid accumulation in the brain(Aβ‐PET).MethodWe quantified plasma biomarkers (tau phosphorylated at 217, 181 and 231, glial fibrillary acidic protein(GFAP) and neurofilament‐light(NFL)) by single molecular array in 126 patients (age=65±8) who were admitted to the Clinic for Cognitive Disorders, Karolinska University Hospital. Patients underwent an extensive initial clinical assessment encompassing MRI/CT, CSF sampling, NP evaluation and, within a year, a [18F]flutemetamol‐PET(Aβ‐PET) scan. NP assessment consisted of the following tests: RAVL(learning&retention), Rey‐Osterrieth(copy&retention), Trail making test(TMT) A&B and Digit Symbol. Test results were transformed in Z‐scores. At this point in the data collection, 47 patients were initially diagnosed as mild cognitive impaired(MCI) and had available >=1 of the NP tests. To refine the diagnosis, Aβ‐PET images were acquired and visually rated for positivity/negativity(VR) and quantified in Centiloid(Aβ‐PET‐CL) and after reassessment of the cohort, 28 subjects with available NP scores became MCI‐Aβ+(n=12) or Aβ‐(n=16). Significant(p<0.05) associations with Spearman’s coefficients(rho) are reported. Z‐scores were used to predict Aβ‐PET+ with receiver‐operating‐characteristic curves and area‐under‐curves(AUC).ResultCognitive performance(Z‐scores) of the MCI cohort(after PET) was on average 1‐2 standard deviations below the reference database and Rey‐Osterrieth‐copy correlated with Rey‐Osterrieth‐retention(rho=0.44) and Digit Symbol(rho=0.43) tests. MCI‐Aβ+ and Aβ‐ groups did not statistically differ in cognitive performance. TMT‐A only presented an association with Aβ‐PET‐CL(rho=0.64, n=11)(Figure 1) and RAVL retention correlated negatively with plasma NFL(rho=0.46, n=26)(Figure 2); these correlations were significant in the Aβ+ group but not in the Aβ‐ group. In the MCI cohort before Aβ‐PET, TMT‐A correlated with plasma pTau231(rho=0.59, n=17)(Figure 3). From preliminary analyses, Z‐Scores seem to poorly predict VR(AUC<=0.65).ConclusionThe most promising results from TMT‐A need to be confirmed when all the data are available, TMT‐A was associated with plasma NFL and pTau231 and Aβ‐PET, but not with pTau217 and GFAP, previously found to be associated to Aβ‐PET. Poor performance of NP tests alone in predicting amyloid accumulation in the brain might require integration with other biomarkers.
Effect of brain network scale on Persistence Cycles: An ADNI comparative study
Authors: Garai Sumita , Liu Mintao , Xu Fredericks , Goñi Joaquín , Duong‐Tran Duy , Zhao Yize , Shen Li ,   for the ADNI
Published: January 2025

AbstractBackgroundOur study aims to understand how network resolution scale impacts the association between topological features in the brain network and Alzheimer’s disease (AD) outcomes. In particular, we examine persistence homological cycles, derived from DTI and fMRI neuroimaging. We study subjects in various stages of AD progression. We utilize structural and functional connectomes extracted from aforementioned modalities and assess between group differences in average persistence of homological cycles, across various scales.MethodThis study is conducted on data obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database and utilizes two different modalities, with two independent datasets. First dataset involves structural connectomes obtained from diffusion tensor imaging (DTI) based on Lausanne parcellation on five scales: 33, 60,125, 250 and 500. The second dataset consists of functional connectome obtain from fMRI scans, measuring Pearson correlations between BOLD signal fluctuations of various regions of interests in the brain, based on Shaefer atlas and ten scales, starting from 100 up to 1000. We use topological data analysis tools, specifically persistence homology and computational package ripser to compute birth and death time for homological cycles for the underlying topological network obtained from both structural and functional connectomes, for all scales. Life of a cycle is defined to be birth time subtracted from death time, also equal to the length of a bar in the persistence barcode. Average Persistence (AP) is average length of a bar in the persistence barcode for each subject’s brain network. We perform a comparative study among different stages of disease progression across all scales of resolution.ResultWe find that the t‐test for the means of average persistence for different stages of disease progression reveals statistically significant between‐group difference in scale‐33 (HC vs MCI and MCI vs AD) and in scale‐125 (MCI vs AD) for structural connectomes (Figure 1) and in scale‐100 (MCI vs AD and HC vs AD) for functional connectomes (Figure 2). We also note that average persistence tends to stabilize as we increase image resolution.ConclusionFrom topological point of view, lower resolution images surprisingly perform better at capturing between group differences in various degrees of disease progression.
Usability assessment in an E‐Health App for Cognitive Stimulation (LABPSI) in Elderly population
Authors: Sarmiento Elsa Araceli Revollo , Sarmiento Gisela Noelia Revollo , Sarmiento Natalia Veronica Revollo , Moreno Maria Celeste López , Vivas Leticia 
Published: January 2025

AbstractBackgroundAdvances in the development of e‐health applications enhance the availability of preventive tools and the adherence to certain treatments in old age (Roberts et al., 2015; Granath et al., 2023). Using these apps provides benefits for cognitive stimulation, offering a technologically accessible option that promotes autonomy in the elderly. In this study, we present the app version of a web platform for cognitive stimulation in the elderly called LABPSI (https://labpsi.mdp.edu.ar). This lite version can be downloaded for android mobile phones and used offline. The app was developed based on user‐centered design, focusing on the elderly. The aim of this study is to assess the usability of the app version of LABPSI in this population.MethodsThe sample consisted of 16 elderly people (81% women) with a mean age of 71.5 (DS = 8.72) and an average of 10.9 years of education.Initially, users were introduced to the app providing the necessary time for use and exploration. Subsequently, they answered the MAUQ (Zhou L. et al., 2019) e‐health application usability questionnaire to assess participants' perceived ease of use, satisfaction, and utility when using LABPSI. The LABPSI final prototype was developed using App Inventor software (MIT APP INVENTOR, 2012).ResultsThe descriptive analysis of the MAUQ usability questionnaire variables were: a) ease of use; b) interface and satisfaction; c) utility. The first variable had a median value of 22 with a maximum questionnaire score of 25 and a range of responses of [6‐25]. The second variable had a median value of 30, with a maximum questionnaire score of 35, and a range of responses of [21, 35]. Finally, the utility variable scored a median of 26 with respect to the maximum questionnaire score of 30, with a range of [16‐30].ConclusionsThis usability study on the new LABPSI cognitive stimulation app shows high levels of ease of use, satisfaction, and perceived utility by participants. The results demonstrate a good interaction between the elderly and the system, defining the app as a usable, appealing, and easy to learn software product for end‐users
Goldilocks Framework: semi‐automated model configuration for democratising data‐driven analyses of Alzheimer’s disease progression
Authors: Oxtoby Neil P 
Published: January 2025

AbstractBackgroundData‐driven models are at the mercy of the data upon which they are built. Poorly configured models can lead to misleading conclusions. Here we introduce a framework called Goldilocks for carefully configuring data‐driven modelling analyses to remain in the Goldilocks Zone — features that are not too weak (in terms of disease signal), and model (hyper)parameters that are not too strong (with respect to available training data).MethodGoldilocks has three key steps: 1. Normalise data. Transform data from cases (e.g., patients) into “disease signal”, e.g., normative z‐scores relative to controls. 2. Feature selection. Identify candidate input features having the necessary minimum signal. 3. Model configuration (hyperparameters). Remain within the available maximum signal.Experiments: we synthesize ADNI‐like biomarker data, define the Goldilocks Zone to lie between two event horizons (minimum and maximum disease signal), and demonstrate Goldilocks for configuring a Subtype and Stage Inference (SuStaIn) analysis. Minimum disease signal zmin is determined by the tipping point between case/control data, where the half‐normal cumulative density function HN‐CDF(zmin)==0.5. Maximum disease signal zmax is defined where the empirical distribution function EDF(zmax)==0.9, such that 10% of the biomarker’s data (from cases, not controls) exceeds zmax.ResultWe synthesized z‐scored ADNI‐like synthetic CSF biomarkers (ABETA, TAU), cognitive test scores (ADAS13, MMSE), and a brain volume (Ventricles normalised by intracranial volume). Figure 1 shows biomarker empirical distributions as a function of z‐score, and the Goldilocks Zone between event horizons at zmin==0.67 and EDF(zmax)==0.9. Since EDF(zmin) < 0.5 for all biomarkers, they each contain sufficient disease signal to be included in a data‐driven modelling analysis like SuStaIn. The maximum disease signal for each biomarker ranged between approximately 2 to 6. Figure 2 compares default parameters in a Z‐Score SuStaIn analysis (using the official pySuStaIn software) to Goldilocks‐informed parameters.ConclusionGoldilocks has the potential to improve validity and interpretability of data‐driven discoveries in general while also making data‐driven modelling accessible to non‐experts. This promotes democratization of data‐driven analyses, unlocking previously untapped data responsibly. This is particularly important in fields such as computational medicine, where data‐driven decisions can relate to life‐or‐death outcomes.
Plasma proteomic profiling of mild cognitive impairment in two cohorts using the NULISAseq CNS Disease panel
Authors: Molfetta Guglielmo Di , Benedet Andrea L. , Zhang Bingqing , Rahmouni Nesrine , Servaes Stijn , Stevenson Jenna , Pola Ilaria , Blennow Kaj , Zetterberg Henrik , Rosa‐Neto Pedro , Ashton Nicholas J. 
Published: January 2025

AbstractBackgroundRecently, the development of ultra‐sensitive immunoassays has allowed for the detection, in blood, of proteins related to the pathophysiology of Alzheimer’s disease (AD), with phosphorylated tau (p‐tau) being the most promising. However, current methods are often limited by their ability to measure one analyte, lacking the potential for discovery and inclusion of additional biomarkers with supplemental value. In this pilot study, we explored proteomic changes using the novel NUcleic acid Linked Immuno‐Sandwich Assay (NULISA™) platform, focusing on patients with mild cognitive impairment (MCI).MethodIn this study, MCI patients with a confirmed Aβ status were recruited from two independent cohorts. A discovery cohort (mean[SD] age, 73.5 [5.5] years; 25 females [62.5%]) was classified by cerebrospinal fluid Aβ42/40 (Aβ+ =28; Aβ‐ =12). For the second cohort (mean[SD] age, 70.7 [7.31] years; 39 females[42.9%]; CDR 0.5), from the TRIAD study, amyloid positron emission tomography was utilized instead (Aβ+ =47; Aβ‐ =44). We performed the NULISAseq CNS Disease Panel measurements on the plasma samples (n=131) in two separate batch analyses. LIMMA models were used to evaluate differential expression of protein NPQ values between the two MCI (Aβ+ Vs. Aβ‐) patient groups, with a total of 121 proteins included in the analysis.ResultIn the discovery cohort (n=40), only p‐tau217 survived multiple comparison (Log2FC, 1.49; Padj <0.001). Further targets were present with a significant unadjusted p‐value (P <0.05) (Figure 1b). In the larger TRIAD cohort (n=91), p‐tau217 (Log2FC, 1.29; Padj <0.001), p‐tau231 (Log2FC, 0.76; Padj <0.05), p‐tau181 (Log2FC, 0.42; Padj <0.05) and GFAP (Log2FC, 0.78; Padj <0.05) remained significant after adjusting for multiple testing. Similarly to the discovery cohort, additional targets were identified as significantly changed with an unadjusted p‐value (P<0.05) (Figure 1A). This included PARK7, which was the only target present in both.ConclusionIn this study, consisting of two independent groups of MCI patients characterized by Aβ burden, we utilized the NULISAseq CNS Disease Panel to identify dysregulated proteins of the prodromal stage of AD. This novel multiplex technology continues to demonstrate the importance of p‐tau217, p‐tau231, p‐tau181 and GFAP as indicators of cerebral amyloid deposition while offering additional markers that may increase their utility.
A‐T+ PET participants in preclinical AD: Clinical progression and concordance with fluid markers
Authors: Yakoub Yara , St‐Onge Frédéric , Fajardo Alfonso , Mohammediyan Bery , Dery Christine , Sylvain Elisabeth , Tremblay‐Mercier Jennifer , Remz Jordana , Gonneaud Julie , Vogel Jacob W. , Soucy Jean‐Paul , Binette Alexa Pichet , Villeneuve Sylvia ,   PREVENT‐AD Research Group
Published: January 2025

AbstractBackgroundAmyloid‐negative tau‐positive PET (A‐T+) participants have been reported in several studies. We assessed the prevalence and characteristics of A‐T+ participants in a cohort of cognitively unimpaired individuals with a first‐degree family history of Alzheimer’s disease (AD) dementia.MethodWe studied 252 participants from the longitudinal PREVENT‐AD cohort (mean cognitive follow‐up = 3.42 years, SD = 2.86) who received an amyloid (18F‐NAV4694) and a tau (18F‐Flortaucipir) PET‐scan. The amyloid‐positivity threshold was 18 centiloids (SUVR=1.27) and tau positive threshold was set as 2SD above the mean of A‐ participants in a temporal meta‐ROI (SUVR=1.29). Follow‐up PET scans were available for 109 participants. We characterized A‐T+ participants on clinical (age, sex, APOE4 status, education, depression, apathy, anxiety, sleep), cognitive (RBANS, MMSE, ECoG) and fluid (CSF, plasma) measurements.ResultIn the PREVENT‐AD cohort, only 3 (1.2 %) of all studied participants were classified as A‐T+ (see Table 1 for participants characteristics). Participants 1 and 2 were positive based on plasma Aβ42/40 and they had relatively low levels of tau binding that could represent early pathology. Participant 3 was also positive based on CSF and plasma, her Aβ‐PET scan was classified as positive on visual read and became quantitatively positive at follow‐up. Participant 3 had extensive unilateral tau binding at baseline that became bilateral at follow‐up (Figure 1). Figure 2 details the longitudinal cognitive trajectory of Participant 3. During the cognitive follow‐up, participants 1 developed mild cognitive impairment and participant 3 developed dementia.ConclusionA‐T+ individuals are rare in the PREVENT‐AD cohort and the 3 A‐T+ were classified as Aβ positive based on fluid biomarkers. One of the 3 A‐T+ individuals showed a very fast clinical progression and a tau uptake pattern atypical of AD.
Cortical tau aggregation drives axonal degeneration in white matter fiber tracts in Alzheimer’s disease
Authors: Pescoller Julia , Dewenter Anna , Steward Anna , Dehsarvi Amir , Wagner Fabian , Gross Mattes , Zhu Zeyu , Ewers Michael , Roemer Sebastian Niclas , Brendel Matthias , Franzmeier Nicolai 
Published: January 2025

AbstractBackgroundIn Alzheimer’s disease (AD), cortical tau aggregation is a strong predictor of cortical brain atrophy as shown by MRI and PET studies, particularly driving the degeneration of neuronal somata in the grey matter. However, tau’s physiological role is to stabilize microtubules within axons in the brain’s white matter (WM) pathways. Therefore, tau’s white‐to‐grey‐matter translocation and aggregation in neurofibrillary tangles close to neuronal somata may induce WM degeneration through destabilization of axonal microtubule integrity. To address this, we determined whether cortical tau predicted faster atrophy of connected WM tracts in AD.MethodWe included from ADNI cohort 37 amyloid‐PET negative (Aβ‐) cognitively normal (CN) participants and 88 amyloid‐PET positive (Aβ+) participants across the AD‐spectrum (i.e. CN/MCI/Dementia = 50/28/10), with baseline amyloid‐PET, longitudinal tau‐PET and longitudinal structural MRI data. For replication, we included baseline amyloid‐PET, tau‐PET and MRI data of 321 CN‐Aβ+ subjects from the A4 cohort. T1‐weighed MRIs were segmented into grey and white matter and non‐linearly normalized to MNI space using CAT12. The cortical Brainnetome Atlas and a diffusion imaging‐based tractography atlas were applied tau‐PET and MRI data to i) determine cortical tau‐PET accumulation rates within Brainnetome ROIs, and ii) assess WM volume changes within fiber tracts connected to each cortical ROI. Statistical regression‐models were adjusted for age, sex, WM hyperintensity volume, global amyloid, intracranial volume, and APOE4‐status.ResultIn ADNI, higher baseline temporo‐parietal tau‐PET predicted faster volume reductions in connected WM tracts (Figure 1A), especially pronounced in Aβ+ subjects (Figure 1B). Similarly, faster tau accumulation was strongly linked to widespread WM volume reductions in connected fiber tracts (Figure 2A; Figure 2B), particularly exacerbated in Aβ+ APOE4 carriers (Figure 3A) compared to non‐carriers (Figure 3B). These results suggest that tau accumulation and WM degeneration are parallel processes in AD, modulated by APOE4. In the A4 validation sample of preclinical AD patients, we detected congruent associations between inferio‐temporal tau‐PET increase and reduced WM volume in connected fiber tracts (Figure 4).ConclusionCortical tau aggregation is associated with progressive WM atrophy in connected fiber tracts throughout the brain, suggesting that tau accumulation triggers axonal degeneration, which may induce neuronal disconnection and dysfunction and thereby contributing to AD progression.
Health Outcomes of Transitional Space Design for Older Adults with Dementia
Authors: Chadalavada Myna , DeCaro Renee , Karaca Meltem , Hagan Brenna , Morreale Kristina , Waskow Emily , Turk Katherine W. , Budson Andrew E. , Anderson Diana 
Published: January 2025

AbstractBackgroundThe built environment is increasingly recognized as a valid medical intervention, known to affect mental and social health, which can carry consequences for cognitive function. “Transitional spaces” are indoor/outdoor areas designed to foster connections to the surrounding world and boost well‐being including windows, porches, and public parks. Little is known about the space design characteristics that might help improve social and mental health. The goal of this study is to better understand how transitional space engagement impacts health outcomes in those with and without Alzheimer’s disease and related dementias (ADRD).MethodSurveys were remotely administered to community‐dwelling healthy older adults and those with early‐stage ADRD. A novel built environment survey assessing community and home design features as well as questionnaires measuring loneliness, social isolation, mood, anxiety, and cognitive performance were included. We hypothesized that greater use of residential transitional design features (such as windows) and greater access to outdoor spaces (such as parks) will be associated with positive health outcomes (e.g., lower depression, loneliness).Result51 older adults with and without ADRD completed the assessment, consisting of 27 healthy adults and 24 cognitively impaired individuals, ages 55 to 90 (<I>M</I> = 73.9, <I>SD</I> = 6.8). Of the sample, 65% of these individuals reported single family homes, and 78% reported living with someone else. The majority of individuals reported access to community parks (Table 1). Indoor space and window use was also characterized, and individuals who frequently look out the window in their home experienced significantly less social isolation, t(41) = 2.92, p = .006 (Figure 1). No such relationships were apparent for depression, anxiety, and loneliness. Additional transitional space features and their use will be discussed in further analyses (Table 2).ConclusionFor older adults who increasingly stay in the home, transitional spaces may allow ways of engaging with the social landscape, promoting benefit, and mitigating effects of isolation. Recognizing the built environment’s role in social connections, mental health and cognition is imperative in designing opportunities for improving the lives of older adults, with and without ADRD.
Therapeutic evaluation of low‐dose IL‐2‐based immunomodulatory approach in patients with early AD
Authors: Sarazin Marie , Lagarde Julien , Olivieri Pauline , Puchois Virginie , Federici Laetitia , Chaigneau Thomas , Potier Marie‐Claude , Auvity Sylvain , Bottlaender Michel , Dorothée Guillaume 
Published: January 2025

AbstractBackgroundChronic innate neuroinflammation mediated by microglia and astrocytes in response to Aβ and pathological Tau species is a cardinal feature of AD that contributes to disease pathogenesis. Accumulating evidence now also highlight an instrumental role of T cells and peripheral‐central immune crosstalk in the pathophysiology of AD. Both preclinical and clinical reports suggest the potential therapeutic interest of peripheral immunomodulatory approaches aimed at amplifying regulatory T cells (Tregs), e.g. through low‐dose IL‐2 treatment, as a strategy for rebalancing T cell subsets and proper central innate neuroinflammation towards beneficial neuroinflammatory patterns.MethodOur study aims at evaluating the therapeutic efficacy and safety of low‐dose IL‐2 immunomodulatory treatment in 35 patients with early AD, in a randomized (2:1), double blind, placebo‐controlled phase II clinical trial. Treatment consists in 21 cures of subcutaneous injections of either placebo or low‐dose of IL‐2 (PROLEUKIN®) at 1 MIU/day for 5 consecutive days for the first week (induction phase), then one injection per week for 16 weeks from day 15 (maintenance phase; total duration of treatment: 18 weeks). Patients are followed‐up for cognitive and functional assessment at 6, 12 and 18 months after the first injection. All subjects undergo [18F]‐DPA‐714‐PET/MRI at inclusion and 18 months after treatment induction, for monitoring the evolution of brain neuroinflammation.ResultAn intermediate analysis of the variation of Tregs percentage was performed after 9 patients were included and treated for 4 doses into the maintenance phase. Percentages of Tregs, among both CD4+ or total CD3+ T cells, showed a 1.5‐fold increase in the treated group (n = 6), while remaining stable in the placebo group (n = 3), as expected. One patient decided to discontinue the treatment because of depression, which appears unlikely to be treatment‐related. No other adverse effect was observed.ConclusionOur intermediate biological analysis evidence a 1.5‐fold increase in Tregs percentages after 4 doses of the maintenance phase, without any significant adverse effect. These data validate our predefined objective of Treg amplification and thus target engagement, while supporting optimal safety of the treatment.