bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanistic Model of Alzheimer’s Disease Progression: Linking Amyloid and Tau Pathologies
Authors: Duffull Stephen , Stone Julie A , Robey Seth 
Published: January 2025

AbstractBackgroundRecent anti‐amyloid mAb trial results demonstrate slowing of Alzheimer’s disease progression, but to date do not fully halt or reverse this progression. Optimization of anti‐amyloid therapy (timing and duration of intervention, modality, combinations, biomarker guidance) is limited by incomplete understanding of the disease, such as relationship between amyloid and tau pathways. Mechanistic Alzheimer’s progression modeling investigated how amyloid and tau pathologies are connected in driving progression.MethodCalibration data (amyloid PET, CSF Ab42, CSF p‐tau, tau PET) were obtained from a wide‐range of publications including observational trials and interventional trials with BACE inhibitors, anti‐amyloid mAbs, and anti‐tau antisense oligonucleotides. First, mechanistic representations of the key features of amyloid (monomer, oligomer, plaque) and tau (tau, p‐tau, NFTs with spatial spread in brain) pathology were developed separately. Next a broad empiric exploration of a large range of amyloid‐tau links was undertaken with an objective to identify a limited number of models that can describe all the available clinical data.ResultTwenty eight variations on connecting models were considered; 12 were eliminated by review of their signature profiles, 3 due to redundancy of mechanisms, 6 due to implausible spatial mechanisms, 5 due to an inability to calibrate an amyloid component. The remaining 2 models (Amyloid plaque drives tau production or drives tau phosphorylation) could holistically describe all the available clinical data. Tau PET data from anti‐tau antisense trials were best described by a model with NFT loss (turnover 4‐times faster than amyloid plaque turnover). Further data is needed to fully characterize this process and related elements of the tau portion of the model. Simulations of early anti‐amyloid intervention (prior to emergence of tau pathology) suggested effects on progression would be enhanced relative to later intervention and emergence of tau pathology could be substantially delayed.ConclusionModeling which combines mechanistic representation of understood aspects of disease biology and empiric explorations of less well‐understood aspects and is calibrated to human trial data only can yield important insights. Such approaches have an important role to play in optimizing therapeutic strategies as the field moves into complex questions of combinations or sequencing of multiple therapeutic interventions.
CSF biomarkers trajectories across the AD spectrum reveal the temporal dynamics of amyloid and tau
Authors: de Leeuw Diederick Martijn , Trieu Calvin , Vromen Eleonora M. , Verberk Inge M.W. , Blujdea Elena Raluca , Teunissen Charlotte , Pijnenburg Yolande A.L. , van der Flier Wiesje M. , van Harten Argonde C. , Visser Pieter Jelle , Tijms Betty M. 
Published: January 2025

AbstractBackgroundThe Alzheimer’s disease (AD) research framework proposes a biological definition of the disease. Still, little is known about longitudinal dynamics of core AD biomarker trajectories and how they map to each stage on the clinical spectrum.MethodsParticipants with abnormal amyloid across the cognitive spectrum (i.e. preclinical AD, prodromal AD and AD dementia) and cognitively unimpaired controls with initially normal CSF markers were included from Amsterdam Alzheimer Center studies when they had at least one repeated CSF sample available. In all 452 samples, we measured Aß1‐42, Aß 1‐40, Aß1‐42/Aß1‐40 ratio, total tau (tTau), phosphorylated tau (pTau) with the Lumipulse multiplex. We tested longitudinal changes in all markers with linear mixed models including random intercepts and slopes, adjusting for age and sex. Each model included an interaction term of time and clinical stage. The Emmeans package in R was used to extract stage specific estimates.ResultsBy definition, all controls had higher (i.e., normal) amyloid markers and lower tau markers compared to subjects with preclinical, prodromal and AD dementia at baseline (p<0.001; Figure 1). Prodromal AD and dementia had the highest levels of tTau and pTau (all p<0.001) and the lowest levels of Aß1‐42/1‐40 ratio (all p<0.001), but were similar between both stages. Over 4±1sd years, Aß1‐42/1‐40 ratios decreased in controls and preclinical AD (p<0.001 and p=0.01 respectively), but remained unchanged in prodromal AD and dementia. CSF tTau and pTau increased over time in controls, preclinical and prodromal AD (all p<0.05), but did not in the dementia stage. Increases in pTau levels over time were steeper in both preclinical and prodromal AD than in controls (p<0.05) with 10% of controls reaching abnormal levels. Increases in tTau levels were steeper in prodromal AD only compared to controls (p<0.05).ConclusionIn this sample, we found that amyloid shifts towards abnormal levels in controls, becomes more abnormal in preclinical AD, and stabilizes in MCI and dementia. Tau markers become more abnormal in preclinical and prodromal AD only, suggesting that increase in CSF tau requires abnormal amyloid. This suggests that interventions targeting amyloid optimally happen before CSF amyloid becomes abnormal to prevent tau accumulation.
Synaptic dysfunction mediates the association between the CSF t‐tau and PACC change among cognitively unimpaired multiparous women
Authors: Brugulat‐Serrat Anna , Sánchez‐Benavides Gonzalo , López‐Martos David , Escalante Armand González , Milà‐Alomà Marta , Shekari Mahnaz , Ashton Nicholas J. , Kollmorgen Gwendlyn , Cacciaglia Raffaele , Grau‐Rivera Oriol , Quijano‐Rubio Clara , Zetterberg Henrik , Blennow Kaj , Suárez‐Calvet Marc , Sundermann Erin E. , Gispert Juan Domingo ,   ALFA study
Published: January 2025

AbstractBackgroundCSF t‐tau is considered a marker of neuronal injury in AD and strongly correlates with cognitive impairment. Evidence suggests that women accumulate more tau pathology early in AD than men. However, how pregnancy influences this relationship is unclear. We explored association between the number of childbirths and t‐tau and the interaction of these factors on cognitive change in cognitively unimpaired (CU), middle‐aged women and tested whether late‐life biological pathways mediate these associations.MethodWe included 226 CU postmenopausal parous women and 144 men with children from the ALFA+ cohort (Table 1). As late‐life biological pathways we analyzed neuroinflammation (YKL 40, GFAP, and sTREM2), synaptic dysfunction (GAP‐43 and Neurogranin), and vascular dysregulation (sICAM1). All CSF biomarkers were measured using the NeuroToolKit and Elecsys® immunoassays (both Roche Diagnostics International Ltd), except GAP‐43 (ELISA). Cognitive change (3‐year follow‐up) was measured with a PACC‐like composite and individual cognitive domains. Independent linear models with t‐tau and cognitive change as dependent variables were constructed with age, education, APOE‐ε4, reproductive span, and age at first birth as covariates. We replicated the same models, adding Aβ42 as a covariate. Interaction terms between the number of childbirths and biomarkers were modeled. Causal mediation model stratified by number of childbirths was conducted to test whether late‐life biological pathways mediates t‐tau and cognitive change association.ResultMore childbirths were positively associated with higher CSF t‐tau. Number of childbirths interacted with CSF t‐tau to predict a steeper decline in PACC performance (Table 2, Figure 1A) with GAP‐43 levels mediating this relationship (Figure 1B). These results remained significant after covarying by CSF Aβ42. No significant associations among men were found.ConclusionA greater number of childbirths are linked to higher CSF t‐tau levels in CU middle‐aged women with a more deleterious effect on the change of PACC performance. This association was partially mediated by the effects of CSF GAP‐43, suggesting synaptic dysfunction in multiparous women in the context of early cognitive deterioration. These findings contribute to our understanding of the higher risk for AD observed in CU multiparous women, who show higher susceptibility and more adverse downstream consequences of tau pathology.
Plasma GFAP influences tau aggregation and cortical thickness thinning in Alzheimer’s disease
Authors: Guo Tengfei , Li Anqi , Sun Pan , He Zhengbo , Cai Yue , Lan Guoyu , Shi Dai , Lu Jie , Han Ying 
Published: January 2025

AbstractBackgroundThe thresholds of plasma β‐amyloid(Aβ)42/Aβ40 and phosphorylated Tau181 (p‐Tau181) to detect Alzheimer’s disease (AD) pathophysiology in Chinese community older adults have not been well established. Besides, it is still unclear about the role of astrocyte reactivity in Aβ plaque deposition, tau tangle aggregation, and neurodegeneration in AD.MethodIn this study, we analyzed plasma Aβ42/Aβ40, p‐Tau181, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) using the Simoa platform in 470 Chinese older participants. Among them, 301, 195, and 70 individuals had MRI, Aβ PET, and tau PET images. The receiver operating characteristic curve analysis (Youden index) was conducted to define plasma Aβ42/Aβ40 (A) and p‐Tau181 (T) thresholds as £0.0609 and ³2.418 by comparing Aβ‐PET negative cognitively individuals and Aβ‐PET positive cognitively impaired patients. We compared plasma GFAP, Aβ plaque, tau tangle, plasma NfL, hippocampal volume, and temporal‐metaROI cortical thickness between different plasma A/T profiles and studied their association with each other using general linear models, controlling for age, sex, APOE‐ε4, and clinical diagnosis.ResultWe found that plasma A+/T+ individuals had the most astrocyte reactivity, Aβ plaque, tau tangle, axonal degeneration, hippocampal atrophy, and temporal‐metaROI cortical thinning (Figure 1). Lower plasma Aβ42/Aβ40 (p < 0.001) and higher plasma p‐Tau181 concentrations (p < 0.001) were associated with higher Aβ PET SUVR (Figure 2). Besides, higher plasma p‐Tau181 (p < 0.001) and plasma GFAP (p = 0.015) concentrations were associated with higher temporal‐metaROI tau PET SUVR, and they also showed significant interactive relation (p < 0.001) with higher tau PET SUVR (Figure 2). Higher plasma GFAP (p = 0.012) was related to more shrinking in temporal‐metaROI cortical thickness and showed significant interaction with plasma Aβ42/Aβ40 (p = 0.042) and plasma p‐Tau181 (p < 0.001) at predicting temporal‐metaROI cortical thinning (Figure 3). The voxel‐wise imaging analysis replicated these findings.ConclusionThese findings offer significant reference for using plasma biomarkers to detect AD in the Chinese community older population and provide novel insights into understanding how astrocyte reactivity affects cortical tau aggregation and thickness thinning in AD. This study emphasizes the importance of controlling reactive astrogliosis to prevent AD progression.
Computerized decision support to optimally funnel patients through the diagnostic pathway
Authors: van Gils Aniek M. , Tolonen Antti , van Harten Argonde C. , Koikkalainen Juha , Barkhof Frederik , Herukka Sanna‐Kaisa , Hasselbalch Steen G. , Mecocci Patrizia , Remes Anne , Soininen Hilkka , Lemstra Afina Willemina , Teunissen Charlotte , Lötjönen Jyrki , van der Flier Wiesje M. , Meester Hanneke F.M. Rhodius‐ 
Published: January 2025

AbstractBackgroundThe increasing dementia prevalence and potential introduction of disease‐modifying therapies (DMTs) highlight the need for efficient diagnostic pathways. Clear recommendations to guide the choice of diagnostic tests are lacking and may vary depending on different clinical scenarios. We used a data‐driven approach to identify efficient and effective stepwise diagnostic testing for three clinical scenarios: 1) syndrome diagnosis, 2) etiological diagnosis, 3) potential eligibility for DMT.MethodWe used data from two memory clinic cohorts (ADC, PredictND), including 504 patients with dementia (302 Alzheimer’s disease, 107 frontotemporal dementia, 35 vascular dementia, 60 dementia with Lewy bodies), 191 patients with mild cognitive impairment, and 188 cognitively healthy controls (CN). Tests included digital cognitive screening (cCOG), neuropsychological and functional assessment (NP), MRI with automated quantification, and CSF biomarkers. Sequential testing followed a predetermined order (Figure 1). Subsequent tests were conducted if the diagnosis remained uncertain. Diagnostic certainty was ascertained through a data‐driven clinical decision support system (CDSS) that generated a disease state index probability score (DSI, 0‐1), indicating the probability of each diagnosis. Diagnosis was confirmed if the DSI exceeded a predefined threshold, set based on sensitivity/specificity cutoffs relevant for each clinical scenario and step. We assessed correct diagnoses and the need for additional testing at each step.ResultFor syndrome diagnosis, stepwise testing (cCOG, NP, MRI) accurately identified 71% of the patients, with NP needed in 42%, and MRI in 31%. For etiological diagnosis, starting with cognitive testing to rule out dementia resulted in the need for MRI in 84% of cases, including 91% of dementia patients and 25% CN. Subsequent MRI reduced CSF required to 29%, ultimately diagnosing 81% of patients with 71% accuracy. In determining DMT eligibility, stepwise testing (cCOG, NP, MRI) correctly identified 91% of potential eligible patients for confirmatory CSF testing, while only 51% of ineligible patients.ConclusionDepending on the setting, alternative diagnostic pathways are accurate and efficient. As such, a data‐driven tool can assist clinicians in selecting tests of added value across different clinical contexts. This becomes especially important with DMT availability, where the need for more efficient diagnostic pathways is crucial to maintain accessibility and affordability of diagnoses.
Brain Health Services for the prevention of dementia: aligning pilot experiences for clinical deployment
Authors: Ribaldi Federica 
Published: January 2025

AbstractBackgroundThe European Task Force for Brain Health Services (BHS) has developed the concept for evidence‐based and ethical services targeting individuals with intact cognition and a high risk of dementia. BHS are complementary to current memory clinics and their missions consists of four pillars: risk assessment and profiling, risk communication, personalised risk reduction, and cognitive enhancement. Recommendations for the deployment of the four pillars have been published, and pilot BHS experiences are underway in European countries and the United States. The field is now ripe to draw lessons from these pilot experiences and move forward towards routine clinical deployment.MethodExperts specializing in the four pillars are collaborating to assess the opportunities and challenges associated with implementing BHS in clinical practice, drawing on lessons from ongoing pilot programs. Additionally, experts in health economics are developing a business plan for the practical deployment of BHS in Geneva, along with a European business case. The BHS task force is actively formulating a comprehensive roadmap for clinical deployment, accounting for anticipated advancements over the next 3‐5‐10 years, including the incorporation of blood‐based biomarkers for risk profiling, personalized prevention and cognitive enhancement through pharmacological and non‐pharmacological interventions (e.g., non‐invasive brain stimulation).ResultPractical programs and protocols for implementing BHS in different environments and countries will be presented ad AAIC 2024. Furthermore, we will present the roadmap for the clinical deployment of each service, along with expected timelines and the business plan for the setup of BHS as hybrid or stand‐alone services, emphasizing the progress made in aligning pilot experiences and the potential impact on dementia prevention.ConclusionThe development and widespread diffusion of BHS in Europe and USA will contribute to fighting dementia and reduce its burden on patients, their families, and society.
Significance of plasma biomarkers in predicting long‐term dementia risk in community dwellings: insights from machine learning approaches
Authors: Xiao Zhenxu , Zhou Xiaowen , Zhao Qianhua , Cao Yang , Ding Ding 
Published: January 2025

AbstractBackgroundThe role of plasma biomarkers for predicting incident dementia in the general population is still undetermined.MethodA total of 1857 baseline non‐demented older adults with follow‐ups within 10 years were included from a community‐based cohort. Consensus diagnoses of dementia and Alzheimer’s disease (AD) were based on clinical criteria. The Recursive Feature Elimination algorithm was used to select the important features from 90 baseline candidate predictors for developing dementia and AD prediction models. Area Under the Receiver Operating Characteristic Curve (AUC) was used to evaluate models’ performance. Models were further validated in the testing sets and subsets.ResultDuring the follow‐up of 12,716 person‐years, 207 participants developed dementia (including 145 AD). The constructed Naive Bayes, Random Forest, and Bagged Trees models showed moderate‐to‐high AUCs predicting future dementia (AUCs = 0.700‐0.828) and AD (AUCs = 0.630‐0.844) in the testing sets. Age, neuropsychological tests, plasma p‐tau217, and neurofilament light chain (NfL) were the prioritized variables in all models. The models showed robustness in diverse subgroups.ConclusionPlasma p‐tau217 and NfL in combination with age and cognitive performance showed important values in predicting incident dementia and AD among community older adults. In the resource‐limited settings, these variables may be convenient‐collected and cost‐effective to identify participants with high risk of dementia in the general population.
Choosing wisely: Evaluating reference regions for improved longitudinal 18F‐AV‐1451 tau PET consistency
Authors: Saguer Isaac Llorente , Oxtoby Neil P 
Published: January 2025

AbstractBackgroundPositron emission tomography (PET) can facilitate precise spatial and temporal measurement of Alzheimer's disease pathology in the brain. The default quantification measure is the standardized uptake value ratio (SUVR) of radiotracer uptake in a target region of interest normalised by uptake in a reference region. Evaluations of new radiotracers commonly assess test‐retest consistency in scans with no pathological changes, but rarely question the SUVR paradigm. Notably, even the Centiloid/CenTauR scales depend on SUVR. This study aims to quantitatively assess the impact of different reference regions on 18F‐AV‐1451 tau‐PET scans.MethodWe analysed SUVR data from 399 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) having at least two 18F‐AV‐1451 tau‐PET scans (199 CU, 149 MCI, 51 AD). Across multiple target regions of interest and common reference regions we compared SUVR longitudinal consistency for this radiotracer using median percent test‐retest (PTRT), average intraclass correlation coefficient (ICC), and average within‐subject coefficient of variation (WSCV). Target regions considered: cerebellum, brainstem, eroded subcortical white‐matter. Reference regions considered: inferior cerebellum grey‐matter, composite (cerebellum, eroded subcortical white‐matter, brainstem), and a data‐driven linear combination of these regions.Four‐fold cross‐validation stratified by diagnostic group was used to train the linear model (optimizing the three metrics factored), using 75% of data for training and 25% for testing.ResultTable 1 presents test‐retest performance across reference regions. The inferior cerebellum gray‐matter was the worst‐performing reference region with only 2.2% test‐retest consistency. The composite reference region produced 26% lower (better) PTRT, 33% lower (better) WSCV and 5% higher (better) ICC. Our data‐driven linear combination of reference regions outperformed inferior cerebellum gray‐matter by 32% PTRT, 37% WSCV and 3% ICC.ConclusionLongitudinal consistency varied based on the reference region chosen. The composite reference region and the linear model both outperformed the inferior cerebellum grey‐matter. This study emphasizes the importance of selecting an appropriate reference region for accurate assessment and tracking of Alzheimer's disease pathology in 18F‐AV‐1451 tau PET scans, in line with other studies (Young et al. 2021).
Alzheimer’s disease drug discovery centering on Hyperphosphorylated tau
Authors: Wang Kuang‐Wei 
Published: January 2025

AbstractBackgroundAlzheimer’s Disease (AD) is a neurodegenerative disorder characterized by the accumulation of neurofibrillary tangles (NFTs) which consist primarily of hyperphosphorylated tau protein. Abnormal phosphorylated tau has been considered as a pathogenic species that impairs cellular function and propagates from neuron to neuron. AD affects millions of people around the world, however, there’s no effective drug that can prevent or cure the disease to date. Drug development based on A‐beta plague has encountered a bottleneck in the past few decades. Thus, finding a drug candidate against hyperphosphorylated tau pathology becomes a key topic.MethodWith the use of recombinant hyperphosphorylated tau (p‐tau) which possesses several disease‐relevant characteristics, we have done a 100,000 – compound high‐throughput screening (HTS) based on p‐tau aggregation and cell‐based assays. The hits from the HTS were studied and modified with medicinal chemistry. The efficacy of synthetic compounds would be tested by our p‐tau cytotoxicity assay with SH‐SY5Y cells and then further verified with mice primary neurons and other functional assays.ResultFrom the high‐throughput screening, 29 hits were selected to be verified in our lab. We then focused on two potential compounds, MSU‐45028 (C9) and MSU‐45031 (C13), which showed overall better molecular, chemical, and biophysical characteristics. Within C9 and C13 series, a few analogs with improved structure‐activity relationship (SAR) property also performed good or even better EC50 against p‐tau cytotoxicity.ConclusionThe results showed that the hits identified from HTS could effectively inhibit p‐tau cytotoxicity. Our medicinal chemistry studies could improve the SAR while maintaining the efficacy of the compounds. The structural information of C9 and C13 analogs not only created potential AD drug candidates, but also provided hints for further drug development based on tau protein.