bluuebunny/crossref_metadata_2025_split huggingface dataset:
Designing EXercise for Cognitive hEalth in depression and anxiety: the EXCEL study
Authors: Curran Eleanor , Ellis Kathryn A , Palmer Victoria J , Cox Kay L , Chong Terence W.H , Rego Thomas W H , Anstey Kaarin J. , Southam Jennifer Amanda , Moorhead Rebecca Anne , Westphal Alissa , Lai Rhoda , Lautenschlager Nicola T 
Published: December 2023

AbstractBackgroundPhysical inactivity significantly contributes to chronic disease burden, including increasing dementia risk. Physical activity (PA) can benefit cognitive health for groups at high‐risk of dementia, such as people experiencing cognitive concerns (including mild cognitive impairment and subjective cognitive decline), and mental health symptoms. However, understanding how to best enable people with co‐occurring cognitive and mental health concerns to increase PA for dementia risk reduction (DRR) remains challenging for researchers, resulting in lower adherence in clinical trials and limiting the impact of implementation in clinical practice. The EXCEL PA implementation study incorporated design approaches from behavioral science that were novel to DRR, to improve intervention tailoring and engagement. We report findings from the first phase of EXCEL, which aimed to understand PA behavior change needs in this population and identify unique intervention tailoring requirements to enable more effective engagement.MethodThe study used the Capability, Opportunity and Motivation (COM‐B) model of behavior change as an organizing framework. Middle‐aged and older people (aged 45 – 85 years) experiencing subjective cognitive decline (SCD) or mild cognitive impairment (MCI) and mild‐moderate depression or anxiety were interviewed. Themes from semi‐structured interviews examining PA and DRR perspectives were triangulated with findings from published PA intervention trials to identify convergent and complementary themes. Integrated findings were mapped to the study framework to develop a specified, contextualized model of key factors influencing PA behavior change and matched intervention approaches.ResultData from 21 interviews and 24 relevant papers were included. Identified areas requiring behavior change support in the target population that have not been emphasized in theory or previous interventions included:• Emotional regulation• Turning intentions into action despite distractions or barriers• Confidence in existing skills, including to overcome barriers and regulate emotionThese aligned with and extended COM‐B and provided a model to guide the EXCEL intervention.ConclusionThis novel model used behavioral science methods to tailor an intervention for people experiencing cognitive concerns and depression or anxiety, supporting improved PA engagement and impact for an at‐risk population (see Ellis et al. AAIC‐23, submitted, for trial results).
Identifying Social Visitations in a Household of Person Living with Dementia using Movement Sensors and a Sleep Tracking Device
Authors: Su Ting , Jouaiti Melanie , Barnaghi Payam , Vaidyanathan Ravi 
Published: December 2023

AbstractBackgroundSocial isolation and loneliness are commonly linked to reduced quality of life, neuropsychiatric symptoms, or increased medication usage among people living with dementia (PLwD). Thus, this study aims to monitor the frequency of visitations in households with PLwD, ideally lending insights into these issues. It builds upon the UK Dementia Research Institute and Clinical Research and Technology centre smart home deployment.MethodWe collected activity data from movement sensors and sleep tracking devices, and audio data from a smart chatbot. These devices are deployed to one household where a PLwD is living together with their primary carer. Two scientists listened to all the audio clips captured by the chatbot and manually labelled them as from either carer, PLwD, or visitors (Cohen’s Kappa = 0.96). All the days with audio clips from visitors are labelled as days with visitors, and other days are labelled as days without visitors. A Support Vector Machine (SVM) is trained to classify if the PLwD has had visitors based on sensor data. The cross‐validation (cv = 5) method is used to evaluate the effectiveness of the classification model.Result1719 audio clips from 127 days were recorded by the chatbot between 09‐08‐2021 to 31‐05‐2022. We removed 10 days where there were no bed movements recorded, resulting in a total of 117 days in the dataset. Among these days, 11 days were labelled as with visitors and 106 days as without visitors. We observed significantly fewer bed activities when they have visitors (Mann‐Whitney U test, p = 0.0003 for times getting into bed and p = 0.0003 for getting out of bed), but significantly more times entering bedroom (Mann‐Whitney U test, p = 0.0242). Additionally, we observed that the SVM model could classify if the PLWD has had visitors with 0.768 Accuracy, 0.694 Precision, 0.768 Recall, and 0.728 F1 score.ConclusionVisitors may influence PLwD’s daily routine, as the PLwD has significantly fewer bed activities and significantly more bedroom activities when having visitors at home. The SVM model can classify if PLwD’s household has had visitors using data from movement sensors and the sleep tracking device as input, with 0.768 Accuracy.
Effect of Adeno‐associated Viral Vector Mediated APOE Protective Variants Expression on Tau Pathology in a Tau Mouse Model
Authors: Chatterjee Madhurima , Zuko Amila , Wattimury Hendrina , Boggiani Lorenzo , Paerels Lieke , Schwarz Lukas , Hentschel Lisa , Kusuma Angga , Bosma Bas , Villamil Javier , Spronck Lisa , Pereira Ines Lopes , Nogueira Ana , Peris Sara Gimeno , de Miguel Elena , Dobrynin Greg , Liu Ying Poi 
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) is characterized by two main pathological hallmarks in the brain, namely, the presence of amyloid plaques and neurofibrillary tangles. However, the underlying mechanisms of AD pathogenesis are still largely unknown. Polymorphism in the apolipoprotein E (APOE) gene is a major genetic risk determinant of late‐onset AD, with the APOE*ε4 allele conferring an increased risk and the APOE*ε2 allele conferring protection relative to the common APOE*ε3 allele. Previous studies have shown that the presence of APOE*ε4 exacerbates tau pathology in AD patients as well as AD mouse models. uniQure is developing an AAV gene therapy approach which will simultaneously silence the risk‐increasing APOE allele and overexpress the protective APOE variant. Here, our goal is to investigate the effect of AAV‐mediated APOE protective variants expression on tau pathology in a tau mouse model.MethodProtective APOE‐variants were tested by intra‐striatal delivery of AAV vectors in a humanized tau mouse model. Vehicle or empty AAVs were injected in two separate control groups. Vector DNA, APOE mRNA and human APOE protein levels were measured in different brain areas of these mice. In addition, human tau protein levels were measured.ResultWe successfully expressed protective variants of APOE in a tau mouse model and measured human APOE protein levels in different brain areas. Furthermore, phosphorylated tau protein levels were significantly lower in AAV‐APOE‐protective variants treated tau mice compared to control groups mice indicating reduction in tau pathology in the hippocampus after protective APOE variants expression.ConclusionAAV‐mediated overexpression of protective APOE variants results in reduction of tau pathology in mice. Overexpression of protective APOE variants or in combination with a silencing approach using a new generation of therapeutic microRNAs (miRNAs) from our miQURE® platform could be an attractive treatment approach for AD.
Association between anxiety symptoms and Alzheimer’s disease biomarkers in cognitively healthy adults: A systematic review and meta‐analysis
Authors: Demnitz‐King Harriet , Saba Lisa , Lau Yolanda , Munns Lydia , Zabihi Sedigheh , Schlosser Marco , del‐Pino‐Casado Rafael , Orgeta Vasiliki , Marchant Natalie L 
Published: December 2023

AbstractBackgroundAnxiety has been identified as both a risk factor and prodromal symptom for Alzheimer’s disease (AD) and related dementias, however, the underlying neurobiological correlates remain unknown. The aim of this systematic review and meta‐analysis was to examine the association between anxiety symptoms and two defining markers of AD neuropathology: amyloid‐beta (Aβ) and tau.MethodSystematic literature searches were conducted across 5 databases. Studies investigating the relationship between anxiety and AD neuropathology (i.e., Aβ and/or tau) in cognitively healthy adults were eligible. Where possible, effect sizes were combined across studies, for Aβ and tau separately, using random‐effects meta‐analyses. Sensitivity analyses were performed to assess whether results differed according to anxiety type (i.e., state and trait) and biomarker assessment modality (i.e., positron emission tomography and cerebrospinal fluid). Between‐study heterogeneity was quantified using I
2 with 95% confidence intervals (CI), publication bias evaluated by examining funnel plots, and risk of bias assessed via the National Heart, Lung, and Blood Institute Quality Assessment Tool.ResultTwenty‐seven studies reporting data from 14 unique cohorts met eligibility criteria (Figure‐1). All studies received a quality rating of either ‘good’ (k = 15) or ‘fair’ (k = 12). Random‐effects meta‐analyses revealed no associations between self‐reported anxiety symptoms and either Aβ (13 studies, N = 5141; Fisher’s z = 0.02, 95% CI ‐0.01–0.05, p = 0.194 [Figure‐2]) or tau (4 studies, N = 1126; Fisher’s z = 0.04, 95% CI ‐0.02–0.09, p = 0.235 [Figure‐3]). There was no evidence of publication bias and heterogeneity was low (I
2 = 0.0%). Results remained substantively unchanged across sensitivity analyses assessing the effects of anxiety type and biomarker assessment modality.ConclusionIn cognitively healthy adults, meta‐analytic syntheses revealed no associations between anxiety symptoms and either Aβ or tau. There is a critical need, however, for larger studies with follow‐up periods to examine the effect of anxiety symptom onset, severity, and chronicity on AD neuropathology. An association between anxiety and dementia‐related neurobiological correlates is also likely complex, underpinned by multiple factors, and not restricted to AD neuropathology. Further research investigating other potential neurobiological correlates is crucial to advance understanding of the relationship between anxiety and dementia.
Virtual‐ and Augmented Reality‐Assisted Screening for Early Detection of Cognitive Impairments
Authors: Draxler Theresa , Christova Monica , Fuchs‐Neuhold Bianca , Guggenberger Bernhard , Loder‐Fink Brigitte , Maas Nina , Nischelwitzer Alexander , Palli Christoph , Pilz René , Schadenbauer Sandra , Simi Helmut , Steiner Anna , Strohmaier Robert , Staubmann Wolfgang 
Published: December 2023

AbstractBackgroundA key element in providing future dementia patients with sufficient care is the early detection of cognitive impairment. Using augmented reality (AR) and virtual reality (VR), the project “Smart Cognition & Behaviour Screening powered by Augmented Reality” (SCOBES‐AR) seeks to create a multimodal screening tool (MST) for the early and easy detection of cognitive impairment. The MST focusses on non‐pharmacological prevention by assessing behavioral and lifestyle‐associated risk factors and identifying personal resources.MethodsFirst, a validation study was carried out utilizing the established Cognitive Functions Dementia (CFD) test battery to evaluate a set of selected test procedures. The validated test procedures were implemented in an MST prototype based on AR/VR techniques. Using observational summative evaluation and the co‐discovery method, the usability and applicability of the validated test methods for therapists and subjects were further assessed in a subsequent cross‐over study with 98 healthy individuals (age 60‐75 years).Results310 people were involved in the validation study (age 60‐75 years). Among other things, the assessment of olfactory performance (r = 0.09, p = 0.003), reaction time (r = ‐0.47, p<0.001), and activities of daily living (r = 0.29, p<0.001) revealed a particularly high agreement with the CFD. Further, the MST prototype, that includes a tablet PC, AR head‐mounted display with smartphone, VR head‐mounted display, and Flic Buttons as input devices, was developed (see fig. 1). It allows the therapist to have control and direction over the screening process (see fig. 2).ConclusionThe focus of the MST is on non‐clinical cognitive and physical functionalities, as it integrates tests from multiple health professions and is low‐threshold viable. The development of the MST prototype enables the determination of ideal procedures for multimodal AR/VR‐based testing to measure cognitive impairment in older people. To bolster the findings and advance research, clinical trials involving people with cognitive decline and those who already have dementia would be required.
Screening Alzheimer’s genetic risk factors against amyloid‐βeta synaptotoxicity
Authors: Gelle Carla , Siedlecki‐Wullich Dolores , Coulon Audrey , Chapuis Julien , Lambert Jean‐Charles , Kilinc Devrim 
Published: December 2023

AbstractBackgroundSynapse degeneration is one of the earliest events in Alzheimer’s disease (AD) and toxic oligomers of amyloid‐beta (Aβ) peptide, cleavage product of APP, plays a major role in this process. Genome‐wide association studies recently reported 75 genomic risk loci for developing AD, but how the potential risk genes contribute to AD remains unknown. This project aims to identify AD genetic risk factors that mediate Aβ‐induced synaptotoxicity.MethodWe conducted a high‐content shRNA screening to assess the impact of ca. 200 AD risk genes on synaptic density and connectivity. Twenty‐four genes expressed in neurons with highest impact on synapses when silenced were shortlisted for a medium‐throughput screening to assess their capacity to block Aβ‐induced synaptotoxicity. Synaptotoxicity was modelled in microfluidic devices that allow primary postnatal rat neurons to be co‐cultured with Chinese hamster ovary cells, that overexpress wild‐type APP or APP with V717I (or London) mutation with increased secretion of Aβ1‐42 oligomers. Microfluidic devices allow the fluidic isolation of neurites from neuronal cell bodies and therefore provide exclusive access to pre‐ and post‐synaptic neurons. Target genes expression will be modulated either in pre‐ or post‐synaptic neurons and its impact on synaptic connectivity will be assessed.ResultBased on the shRNA screening, we shortlisted 17 detrimental genes, for which we obtained overexpression vectors packed in lentiviruses, and 6 protective genes. We have developed a medium‐throughput co‐culture device that permits screening twelve genes per imaging session using the INCell 6000 automated microscope, as well as an automated image analysis workflow for detecting and assigning presynaptic to postsynaptic puncta based on their relative proximity. Gene expression modulation is validated and the screen is on‐going.ConclusionWe have developed a microfluidic co‐culture model to rapidly and systematically interrogate genetic risk factors for their impact on synaptic connectivity. This study will help us identify AD genetic risk factors with a potential to block Aβ‐induced synaptotoxicity in vitro. Hit genes will be functionally validated via microelectrode array recordings.
The influence of widowhood on amyloid positivity status in cognitively normal older adults
Authors: Chandra Avinash , Anjum Rifah , Bothongo Phazha LK , Waters Sheena , Uchegbu Ijeoma , Jeraldo Rosario Isabel Espinoza , Byford Michelle , Marshall Charles R 
Published: December 2023

AbstractBackgroundWidowhood and associated spousal bereavement is a life event that may lead to stress, loneliness, and depression. Previous research found associations between widowhood and an elevated risk of dementia. However, no direct relationship has been evidenced between widowhood and beta‐amyloid (Aβ) pathology, which is a hallmark of Alzheimer’s disease. Additionally, little is known about whether particular demographic or background factors might contribute to potential influences of widowhood on Aβ levels in older adults. Our objective was to evaluate the relationship between widowhood and Aβ positivity status in older adults, and to determine whether subgroups based on age, gender, educational attainment, or APOE ε4 status are driving effects.MethodCognitively normal (CN) subjects (n = 182) who were either widowed (including widows and widowers) or married from the Alzheimer’s Disease Neuroimaging Initiative were included in this study that underwent [18F]Florbetapir PET imaging on the baseline study visit. Multivariable logistic regression interrogated associations between widowhood status and Aβ positivity classification based on a global standardised uptake value ratio threshold of 1.11. This analysis included age, gender, APOE ε4 allele possession, education, and MMSE score as covariates. Regressions were also run in subgroups of CN subjects based on gender (male vs. female), APOE ε4 allele possession (carriers vs. non‐carriers), age (youngest, middle, oldest tertiles), and education (at least an undergraduate degree vs. no undergraduate degree).ResultIn CN subjects, there was overall no significant association between widowhood status and Aβ positivity (p = 0.114). When examining subgroups, widowhood was significantly associated with an increased risk of Aβ positivity in CN individuals with an undergraduate degree or higher (p = 0.025) or in the oldest age tertile (ages ranging from 76.3 to 89) (p = 0.024).ConclusionFindings from this cross‐sectional study indicated that a positive relationship between widowhood and in vivo Aβ neuropathology measured by PET exists specifically in those that are highly educated or undergoing advanced ageing. Whereas cognitive reserve is often hypothesised to mediate links between social isolation, depression and dementia risk, these results suggest that there may also be a direct effect on Alzheimer’s disease neuropathology.
Consensus meta‐analysis of genome‐wide association studies for Alzheimer’s disease across the EADB, PGC‐ALZ and IGAP consortia
Authors: Bellenguez Céline 
Published: December 2023

AbstractBackgroundA large number of putative genes have been associated with Alzheimer’s disease (AD), in particular by the International Genomics of Alzheimer’s Project (IGAP), the European Alzheimer & Dementia Biobank (EADB), and the Psychiatric Genomics Consortium (PGC). Those genome‐wide association studies (GWAS) showed that increasing the sample size and performing imputation using the largest reference panel available greatly improves statistical power to detect genetic associations with AD. In order to better characterize the genetic architecture and pathophysiology underlying this disease, the three consortia joined to perform a meta‐analysis of GWAS across all their samples of European ancestry, the UK Biobank, and FinnGen.MethodIn a preliminary analysis, 48 studies were considered, totaling 70,276 AD cases, 610,828 controls, 55,960 proxy‐cases and 235,566 proxy‐controls. This represents an effective sample size of 225,605 (97% of the expected final size). Most of the datasets were imputed with the TOPMed reference panel. A GWAS was performed in each study with a logistic regression or a logistic mixed model adjusted on principal components and/or centers, and results were combined across studies with an inverse variance fixed effect meta‐analysis.ResultMore than 23 million variants were analyzed. We identified a genome‐wide significant signal for 92 loci, including 16 novel loci. Lead variants were InDels for two novel loci, and had a frequency below 5% for four other novel loci. We did not identify any genome‐wide significant signals in six previously reported loci: results are borderline significant for SORT1 and ICA1, and further investigations are required for FOXF1, SLC2A4RG, HAVCR2 and NTN5.ConclusionThis meta‐analysis will provide consensus results for loci previously reported for AD and will identify novel signals. Their robustness will be assessed after exclusion of proxy or biobank samples, and secondary analyses will be performed, such as pathway or functional analyses, to provide further insights into the novel loci.
Predictive value for cerebrospinal fluid Alzheimer’s disease profile of different measures of verbal episodic memory in patients with mild cognitive impairment
Authors: Salvadori Nicola , Chipi Elena , Montanucci Chiara , Marchesiello Marta Sveva Maria , Torrigiani Edoardo Guido , Verderosa Claudio , Paoletti Federico Paolini , Fruttini Daniela , Parnetti Lucilla 
Published: December 2023

AbstractBackgroundEpisodic memory deficits represent the typical manifestation of prodromal Alzheimer’s disease (AD), namely amnestic Mild Cognitive Impairment (a‐MCI). Current neuropsychological criteria for MCI recommend the use of at least two measures for each cognitive domain. Rey Auditory Verbal Learning Test (RAVLT) and Logical Memory (LM) are two widely used verbal episodic memory measures. Our aim was to investigate the value of these measures in predicting cerebrospinal fluid (CSF) AD biomarkers positivity in a retrospective fully characterized consecutive MCI cohort.MethodOne‐hundred and six MCI patients were included. All of them underwent a comprehensive neuropsychological assessment including RAVLT (sub‐measures: RAVLT‐imm, RAVLT‐del, RAVLT‐false_recognitions) and LM. All patients underwent lumbar puncture for the analysis of CSF core AD biomarkers (Aβ42/Aβ40 ratio, phospho‐tau, total tau). By applying the A/T/(N) classification model, patients were classified as AD (A+T+, MCI‐AD, n. 62) and non‐AD (A‐T*, MCI, n. 44). Pearson’s r correlation coefficient was used to assess the relationship of RAVLT and LM sub‐scores with diagnosis. WALD logistic regression model was used to find which memory sub‐measures show the best predictive value on biomarkers positivity. To evaluate the discriminatory power of different sub‐measures for CSF AD profile, receiver‐operating characteristic (ROC) curves were generated.ResultWith respect to non‐AD MCI, MCI‐AD patients showed worse scores on all RAVLT and LM sub‐measures. RAVLT‐del could predict both positivity of each biomarker (p<0.01) and CSF AD‐like profile (p<0.01). The combination of RAVLT‐del with other measures (RAVLT‐imm+RAVLT‐false_recognition+LM) discriminated these groups (AUC: 0.76, 95% CI: 0.67‐0‐85) with a sensitivity of 0.74 and a specificity of 0.66.ConclusionOur study shows that the combination of all RAVLT memory sub‐measures and LM reaches the higher diagnostic accuracy in discriminating non‐AD MCI from MCI‐AD patients. Since RAVLT and LM measure different aspects of verbal episodic memory, they should be considered as complementary, rather than interchangeable, tasks. Our findings support the use of different memory measures in the neuropsychological assessment of MCI patients.