bluuebunny/crossref_metadata_2025_split huggingface dataset:
Formal and informal healthcare utilization in MCI and mild dementia due to AD: Cross‐sectional and longitudinal analyses of RUD‐Lite data from the Tauriel Study
Authors: Teng Edmond , Li Yihao , Blendstrup Mira , Lansdall Claire J 
Published: December 2023

AbstractBackgroundThe Resource Utilization in Dementia‐Lite (RUD‐Lite) scale measures both formal healthcare utilization and informal caregiver time required by individuals with cognitive impairment. The RUD‐Lite has been incorporated into multiple observational and interventional studies of participants with Alzheimer’s disease (AD) dementia of varying severity. However, RUD‐Lite data for earlier stages of AD such as mild cognitive impairment (MCI) is limited and is primarily from observational studies. As healthcare utilization may differ between participants in observational versus interventional studies, we analyzed data from the Tauriel study of semorinemab in MCI and mild dementia due to AD (NCT03289143).MethodsWe performed cross‐sectional and longitudinal RUD‐Lite comparisons between MCI (n = 160) and mild dementia (n = 288) cohorts of the Tauriel study, exploring formal healthcare usage (hospital admissions, emergency department visits, outpatient visits, and ancillary services) and informal caregiver time for assistance with basic (BADLs) and instrumental (IADLs) activities of daily living and participant supervision. Both unadjusted and adjusted (for baseline usage, age, sex) analyses were performed on longitudinal data.ResultsBaseline cross‐sectional analyses (Table 1) indicated that mild dementia participants required significantly greater caregiver time for assistance with IADLs than MCI participants. Other formal and informal healthcare utilization indices did not differ between groups. Unadjusted longitudinal analyses across 18 months (Figure 1) revealed significant increases in informal caregiver assistance with BADLs (MCI:+40%, mild dementia:+231%), IADLs (MCI:+31%, mild dementia:+34%), and supervision (mild dementia:+219%) and in ancillary service usage (mild dementia:+345%). Adjusted longitudinal analyses (Figure 2) revealed significantly greater increases in mild dementia versus MCI for assistance time with BADLs, IADLs, and supervision.ConclusionInformal caregiver time spent providing assistance in early AD increases with disease severity and longitudinal changes are detectable in MCI over 18 months. Formal healthcare utilization indices were less sensitive to disease progression. While the RUD‐Lite results from this interventional study are consistent with observational data from analogous populations, less caregiver assistance time was reported in our cohort. When using RUD‐Lite outcomes in future early AD studies, investigators may need to account for their participant population (e.g., observational versus interventional) in their study design.
AZP2006, a New Promising Treatment for Progressive Supranuclear Palsy patients. Phase 2a Study Assessing Tolerability, Safety and Pharmacokinetics. Effect on Biomarkers and Clinical Readouts
Authors: Verwaerde Philippe , Estrella Cecilia , Blondel Aurélien , Signore Susanna Del , Callizot Noelle 
Published: December 2023

AbstractBackgroundProgressive Supranuclear Palsy (PSP) is a rare progressive, fatal neurodegenerative 4‐repeat tauopathy. AZP2006 (INN: Ezeprogind) is a first‐in‐class disease‐modifying oral small molecule acting via its strong binding to the complex Progranulin (PGRN) / Prosaposin (PSAP), able to increase the circulating contents of PGRN (plasma and brain) in non‐clinical models. Preclinically, AZP2006 promotes neuron survival, synaptic function, decreases Tau hyperphosphorylation and reduces neuroinflammation (in vitro and in vivo models of Alzheimer’s disease, PSP and Parkinson’s disease). In healthy volunteers Phase 1 studies, AZP2006 was well tolerated with a good safety profile.MethodAZP2006 safety, tolerability and pharmacokinetic profiles in plasma, whole blood, and CSF were investigated in a randomized, double‐blind, placebo‐controlled, parallel group study comparing 2 doses of AZP2006 (60 mg once daily during the 12‐week treatment period and 80 mg once daily for 10 days followed by 50 mg once daily) with placebo in 36 men and women aged ≥40 years and ≤80 years diagnosed with probable or possible PSP. Patients were observed for an additional 12‐week follow‐up period (NCT04008355).In secondary objectives, CSF biomarkers including PGRN for the target engagement and markers of neurodegeneration (NfL, phospho‐tau T181) as well as markers of neuroinflammation (sTREM2, interleukins, etc.) were quantified. In addition, exploratory efficacy objectives evaluating clinical endpoints (PSP‐RS total, PSP Gait, PSP Ocular, CGI‐ds, Schwab and England ADL) were investigated.ResultAZP2006 was safe and well tolerated; no related SAEs were reported. PK profile confirmed the long AZP2006 half‐life (as predicted in a prior popPK model). High brain penetrance was observed and AZP2006 CSF expected levels were achieved. In addition, the target engagement was confirmed by significant increase (vs baseline) of PGRN plasma levels. A PD‐PK analysis is planned.ConclusionAZP2006 treatment showed promising effects after a 3‐month‐treatment. Considering these promising results, an open‐labelled extension (OLE) was started (60 mg daily) in France. In addition, a larger Phase 2b/3 study in PSP patients testing AZP2006 efficacy over 12‐month‐treatment is under preparation.
Subgroups of Alzheimer’s Disease determined by longitudinal change across three domains of cognition
Authors: Scollard Phoebe , Mukherjee Shubhabrata , Choi Seo‐Eun , Lee Michael L. , Klinedinst Brandon S , Gibbons Laura E , Trittschuh Emily H. , Mez Jesse B. , Saykin Andrew J. , James Bryan D , Crane Paul K 
Published: December 2023

AbstractBackgroundThere is evidence that Alzheimer’s Disease (AD) may have distinct subtypes. Most approaches for identifying subgroups use cross‐sectional data. Here we use longitudinal cognitive test data from two large cohort studies to determine if there are distinct patterns of cognitive decline among those with AD and if those patterns differ across three domains of cognition.MethodWe used data from the Rush Memory and Aging Project and Religious Orders Study (Table 1). Previously, cognitive test items were assigned to a single domain of memory, language, or executive function and scores for each domain were estimated using confirmatory factor analysis. We used Growth Mixture Models to estimate trajectories of decline starting at AD diagnosis and identified subgroups with differing trajectories. Each domain was modeled individually and in a combined model that included distinct latent processes for each domain. Models with one to five classes were estimated and the number of classes was selected using Bayesian Information Criterion (BIC) and entropy.ResultThe two class models fit best for each of the individual domains (Figure 1). For memory and language one class was characterized by a higher intercept and steeper slope while the other had a lower intercept and flatter slope. For executive function the two classes had similar intercepts, but different slopes. Five classes best fit the data in the combined model. The pattern of decline within a class was similar across the three domains (Figure 2). For each domain, four of the classes were differentiated from each other by lower intercepts and increasingly steep slopes, while a fifth class had the lowest intercept, but a flatter trajectory over time.ConclusionWe did not see different patterns across domains of cognition; knowing the trajectory of one cognitive domain explains the most likely trajectory of the other domains. Still, differences identified in patterns of overall decline may be important for AD treatment. Future work will focus on determining biological relevance of subgroups through association with genetic and other biomarkers as well as addressing methodological issues such as incorporating survival time and accounting for the presence of prevalent cases and floor scores.
White matter myelination is associated with longitudinal changes in processing speed in normative aging
Authors: Gong Zhaoyuan , Bilgel Murat , Resnick Susan M. , An Yang , Bouhrara Mustapha 
Published: December 2023

AbstractBackgroundAlterations in myelin may result in progressive disconnection of cerebral neural networks underlying age‐related cognitive decline and AD. Understanding the role of myelination in cognition may provide insights into the neurobiology of aging, help nominate new MRI biomarkers for longitudinal assessment, and identify targets for intervention in disease. Recently, we showed that low myelin content was associated with steeper longitudinal declines in memory, attention, verbal fluency, and executive function. However, its impact on changes in processing speed has not been established. We hypothesized that myelin content is associated with processing speed, given the central role of myelin in the speed of action potential propagation.Method121 cognitively unimpaired participants from the Baltimore Longitudinal Study of Aging and GESTALT studies were administered the Digit Symbol Substitution Test to measure processing speed over a mean follow‐up duration of 4.34±6.34 years (339 visits total) (Table 1). Myelin content was quantified cross‐sectionally using our advanced MRI method of myelin water fraction (MWF), a specific measure of myelin content, or longitudinal relaxation rate (R1
), a measure highly sensitive to myelin. Linear mixed‐effects models were used to assess associations between cross‐sectional myelin content in lobar white matter and retrospective longitudinal change in processing scores. Age, sex, race, time from MRI and its interaction with MRI measure were included as independent variables.ResultLower MWF or R1
values, that is, lower myelin content, in the temporal WM had trend‐level cross‐sectional associations with lower processing speed (P<0.06) (Table 2). Lower MWF or R1
values were associated with steeper declines in processing speed in all brain regions investigated (P<0.015), with all regions except for occipital WM in the MWF analysis meeting the Bonferroni threshold (P<0.01) (Fig.1, Table 2). Finally, as expected, age and time from MRI were negatively associated with processing speed (P<10−7).ConclusionWe demonstrated statistically significant relationships between myelin content and the rate of change in processing speed among cognitively unimpaired adults. These results highlight the importance of white matter, specifically myelin integrity, in cognitive functioning, and suggest MWF and R1
as potential sensitive imaging biomarkers for predicting cognitive changes.
Neuron‐derived extracellular vesicles blood‐based diagnosis of synuclein TDP43 autophagy and synaptic dysfunction pathologies
Authors: Eitan Erez , Elgart Katya E , Rau Sara , Van Debrake Emma , Volpert Olga 
Published: December 2023

AbstractBackgroundStratifying dementia into different subgroups based on specific pathologies can facilitate the development of more effective treatments for subgroups of individuals with dementia. Effective stratification relies on reliable biomarkers. Neuron‐derived extracellular vesicles (NDEs) are lipid structures released by neurons into the extracellular space, and some get into the bloodstream. NDEs carry proteins and RNA that reflect their cell of origin and thus provide a promising biomarker platform.MethodNeuroDex developed two methods. ExoSORT is an optimized NDE isolation platform by immunoaffinity, where NDEs are captured with antibodies against the neuronal‐specific markers GAP43 and NLGN3. LuminEV is an intact extracellular vesicle (EV) immunoassay based on the Luminex platform. Antibodies against a potential biomarker, general EV marker, and IgG (negative control) are multiplexed to generate a robust assay.ResultThe vesicular nature and size of NDEs were confirmed by electron microscopy and nanoparticle tracking. EV markers were ascertained by western blot and proteomic analyses, and capture specificity was demonstrated by significantly elevated neuron‐specific proteins and mRNA levels compared to procedural control (IgG). Capture efficiency (∼80%) and precision (CV < 20%) demonstrated recovery of spiked NDEs. Measurements of αSYN following ExoSORT with an MSD assay and on EVs with the LuminEV generated a separation with 83% sensitivity and 86% specificity (45 Parkinson and 30 healthy controls plasma samples). LC3, an autophagy marker, was also measured following ExoSORT and was significantly (P<0.03) elevated in PD and Alzheimer’s disease (AD) (P<0.02, N = 30) plasma samples. TDP43 was also significantly (P<0.004) higher in AD plasma samples following ExoSORT. The synaptic marker GLUR2 was measured by the LuminEV assays and was significantly (P<0.001) reduced in AD and PD plasma samples. Its level was also significantly (P<0.03) correlated with the patient’s cognitive score.ConclusionImmunoaffinity isolation of EVs from plasma samples according to their cell of origin is a promising biomarker platform. We demonstrate the NDEs isolation selectivity, specificity, and precision. We also show the platform’s potential to identify pathologies like αSYN, TDP43, autophagy, and synaptic dysfunction; this reflects the potential for patient stratification.
Predicting dementia onset in a US memory clinic using EHR data and machine learning
Authors: Adams Roy , Hu Jiazhen , Liu Anqi 
Published: December 2023

AbstractBackgroundPredicting which patients are most likely to progress to dementia from clinical data remains an open problem with large implications for dementia care. Several predictive models have been developed using volunteer‐based study cohorts; however, practical implementations developed on high‐volume clinical data remain uncommon.MethodWe developed a model for predicting whether a patient would receive a dementia diagnosis in one or three years using electronic health record (EHR) data from patients of a US memory clinic.ResultOn a held out set of patient data, the developed model had an area under the receiver operating characteristic curve (AUROC) of 0.82 (95% CI: 0.73 – 0.88) and 0.81 (95% CI: 0.68 – 0.91) for predicting dementia within one and three years, respectively. The most predictive clinical features were prior neuropsychiatric and non‐dementia cognitive impairment diagnoses, hospital utilization, and cognitive test scores.ConclusionWhile the model’s predictive performance is roughly in line with previous studies using longitudinal data, our subsequent analyses highlight the important role of censoring in the development of dementia risk models and the importance of tailoring a model to specific predictive environments.
Cognitive performance and plasma ADAM10 levels in low‐educated older adults with normal cognition, mild cognitive impairment, and Alzheimer’s disease
Authors: de Carvalho Pelegrini Lucas Nogueira , Manzine Patricia Regina , Vatanabe Izabela Pereira , Grigoli Marina Mantellatto , Cominetti Marcia Regina 
Published: December 2023

AbstractBackgroundADAM10 has been investigated as a potential biomarker for Alzheimer’s disease (AD) (Monteiro et al., 2021). However, most of the production in the literature comes from high‐income countries, where the population usually has high educational attainment (Mukadam et al., 2019). Evidence in the literature suggests an effect of education on cognitive performance; thus, low‐educated older adults tend to have worse scores on cognitive tests. Also, low education has been associated with an increased risk of dementia (Mukadam et al., 2019; Suemoto et al., 2022). However, little evidence is available on plasma ADAM10 levels in a sample of older adults with low educational attainment.MethodParticipants were divided into three groups: Healthy (n = 33), MCI (n = 27), and AD (n = 30). Cognitive performance was assessed through MMSE and ACE‐R. SDS‐PAGE and Western‐Blotting were performed to obtain ADAM10 levels in plasma.ResultParticipants were primarily female (62.1%), the mean age was 74.5 (8.2), and the average years of education was 4.6 (4.3). Healthy participants performed better than the MCI group on MMSE (p = 0.04). Compared to the healthy participants, the AD group was older (p = 0.00); had more comorbidities (p = 0.02), was prescribed more medications (p = 0.00); had worse performance both on MMSE (p = 0.00) and on ACE‐R (p = 0.003); and had higher levels of plasma ADAM10 (p = 0.033). Significant differences between MCI and AD groups for age (p = 0.01), years of education (p = 0.008), medication use (p = 0.02), and MMSE score (p = 0.00) were observed. The logistic regression analysis indicated that having lower levels of plasma ADAM10 decreases the chances of an older adult having a diagnosis of AD by 82.3% (Exp(B) = 0.177; p = 0.005; 95%CI [0.053‐0.593]).ConclusionOur results suggested healthy low‐educated older adults had less plasma ADAM10 compared to individuals with AD. Also, despite low education, cognitive test scores differ for each group.
AI‐based histological analysis in Alzheimer’s disease : the point of view of the biologist
Authors: Delatour Benoit 
Published: December 2023

AbstractBackgroundTauopathies in Alzheimer’s disease are characterized by occurrence of neurofibrillary tangles (NFTs) and neuritic plaques (NPs) that are closely associated to cognitive decline and are key elements for neuropathological diagnosis and staging. The automated detection and segmentation of NFTs and NPs has not been fully implemented but thanks to deep learning (DL) based approaches could be assessed today.MethodWhole‐slide images of phosphotau‐immunostained brain sections (frontal cortex) from AD patients presenting discrete to florid lesion loads were generated. Using a commercial software (©Visiopharm) we developed an iterative “human‐in‐the‐loop” pipeline to improve quality of annotations of NFTs and NPs and create an exhaustive and accurate ground truth database that was used to train DL algorithms for the different objects morphologies to be detected and segmented in brain parenchyma.ResultA U‐Net based CNN was trained, and the obtained algorithm was precise in NP detection (F1 score: 0.86) and segmentation (Dice score: 0.77). A second algorithm was precise in NFT detection (F1 score: 0.85) and segmentation (Dice score: 0.82).ConclusionTwo main objectives were reached : 1) optimization of human annotations thanks to iterative AI‐expert feedbacks, 2) implementation of methods to automatically accelerate, refine and robustify histological analysis of discrete objects. Such approaches may help to uncover and quantify subtle morphological differences between AD variants that otherwise could not be neuropathologically segregated. The biological relevance of dichotomizing NFTs and NPs will be discussed in terms of clinico‐pathological correlations and stratification needs. Also, the scope and limits of user‐friendly and commercially available DL‐learning image analysis softwares, directly accessible to researchers and pathologists with limited IT skills, will be reviewed.
iTRAQ‐based proteomic analysis reveals myeloperoxidase (MPO) as a diagnostic and prognostic biomarker of cognitive decline in Parkinson’s disease
Authors: Tan Yi Jayne , Ng Ebonne YL , Ng Samuel YE , Chia Nicole SY , Choi Xinyi , Heng Dede , Neo Shermyn XM , Xu Zheyu , Tay Kay Yaw , Au Wing Lok , Tan Louis CS , Tan Eng‐King , Ng Adeline Su Lyn 
Published: December 2023

AbstractBackgroundParkinson’s disease (PD) is the second most common progressive neurodegenerative disorder and is characterized by loss of dopaminergic neurons, leading to debilitating motor, cognitive, and behavioral symptoms. At present, there are no biological markers for antemortem PD diagnosis.MethodsTo identify potential blood biomarkers of PD, Isobaric Tags for Relative and Absolute Quantitation (iTRAQ)‐based mass spectrometry (MS) was performed to characterize alterations of serum proteins amongst PD patients of varying disease severity according to their Hoehn and Yahr (HY) stages. Sera of mild PD (HY 1.5‐2.0, n = 10), severe PD (HY 3.0‐4.0, n = 10) patients and healthy controls (n = 10) were enriched and subjected to 2D LC‐MS/MS for proteomic analysis. Candidate protein biomarkers were identified based on the relative abundance of the identified tryptic peptides, and were validated using ELISA in a validation set consisting of 103 early PD and 48 healthy controls (HC). Association with clinical outcomes were analyzed at cross‐sectional and longitudinal timepoints.ResultsA total of 96 proteins in the mild PD group and 78 proteins in the severe PD group were found to differ significantly between PD patients and healthy controls. Thirteen proteins were common between the mild PD and severe PD groups and were chosen for further analysis. These dysregulated proteins represent a diversity of biological processes, including innate immune response, complement activation, cytoskeleton reorganization and response to oxidative stress. Of which, myeloperoxidase showed higher serum levels in mild and severe PD. In the validation PD cohort, higher MPO was significantly associated with worse executive function over 4 years.ConclusionUsing an unbiased proteomic approach, we identified serum MPO (a marker of oxidative stress) as a promising biomarker for PD. Our results suggest that MPO could also potentially be an early marker for cognitive decline in PD. Further studies with larger cohorts are needed to validate these findings.
Sleep disturbances in the memory clinic: Associations with clinical features and neuropsychological performance
Authors: Naismith Sharon L , D'Rozario Angela , Hoyos Camilla M , Ireland Catriona , Michaelian Johannes C , Kong Shawn Dexiao , Mowszowski Loren , Grunstein Ron , Lam Aaron Kin Fu 
Published: December 2023

AbstractBackgroundThe prevalence of sleep disturbances increases in ageing and may further increase in neurodegeneration. In a memory and cognition (MC) clinic setting, our study aims to: 1) determine the rates of various sleep disturbances including obstructive sleep apnoea (OSA), short and long sleep duration, insomnia, sleep quality, and rapid eye movement sleep behaviour disorder (RBD); and 2) examine whether these sleep disturbances are associated with neuropsychological performance in older adults without dementia.MethodWe captured data between 2009 and 2022 from a MC clinic for older adults aged over 50 with new cognitive and/or mood concerns. Self‐reported history, pulse oximetry, and polysomnography (PSG) captured rates of OSA. Actigraphy (>7 days) was used to measure sleep duration (defined short duration as <6 hours and long duration as >9 hours). Validated self‐report questionnaires were used to capture insomnia, sleep quality, and RBD. We examined group differences between those with and without sleep disturbances in the following cognitive composites: verbal learning and memory, processing speed, executive function, and language skills.ResultsWe recruited 1016 participants (mean age = 66.9 (SD = 9.0), mean MMSE = 28.3 (SD = 2.2), male = 436 (43%)). For rates of OSA, 15% (n = 152/1016) self‐reported history of OSA, 76% (n = 383/504) had OSA as classified by PSG, 84% (n = 115/137) had OSA as classified by pulse oximetry. From actigraphy data, 10% (n = 55/566) had short sleep and 5% (n = 29/566) had long sleep duration. From self‐report data, 15% (n = 85/579) had moderate or severe clinical insomnia, 61% (n = 544/893) reported having poor sleep quality, 10% (n = 56/579) had RBD. Individuals with OSA (from PSG) performed worse in verbal learning compared to those without OSA (p<0.05). Individuals who had long sleep duration performed worse on both verbal learning (p<0.05) and memory (p<0.05) than those with short sleep and normal sleep duration. There were no other significant group differences in cognition outcomes, amongst the other sleep disturbance groups (p>0.05).ConclusionIn MC clinics, there are very high rates of sleep disturbance in this at‐risk population. The large discrepancy in rates of OSA between self‐reported history and PSG suggests OSA is under‐diagnosed. Sleep disturbances may be associated with cognitive outcomes, in particular learning and memory.