bluuebunny/crossref_metadata_2025_split huggingface dataset:
Examining widowhood duration with depression and cognitive impairment among older women using nationally representative Longitudinal Aging Study in India
Authors: Muhammad T. , Zanwar Preeti Pushpalata , Srivastava Shobhit 
Published: December 2023

AbstractBackgroundLosing loved ones is considered one of the most stressful events in life. With the increase in life expectancy globally over the past century, widowhood has become an older women’s issue. The study aimed to examine the association of widowhood duration with depression and cognitive function among older women in India.MethodWe used the nationally representative Longitudinal Aging Study in India baseline wave, conducted during 2017‐18. Sample comprised of 16,075 older women ages 60 years and above. We conducted descriptive statistics, bivariate analysis and multivariable logistic regression to examine the association of widowhood duration with depression and cognitive impairment.ResultNearly 25% of the older women who suffered from cognitive impairment were widowed for more than 10 years whereas, about 14% of older women who suffered from depression were widowed for at least four years. Older women who were widowed for more than 10 years were 43% significantly more likely to suffer from cognitive impairment in reference to older women who were currently married [adjusted odds ratio (AOR): 1.43, confidence interval (CI): 1.27‐1.61]. Older women who were widowed for at least four years were two times significantly more likely to suffer from depressive symptoms compared to older women who were currently married [AOR: 2.01, CI: 1.66‐2.42].ConclusionThe findings highlight that widowed older Indian women are disadvantaged with respect to the duration of bereavement that leads to worse mental health both in the short and long terms. It suggests that women who are struggling to adjust to such transitions may be particularly at risk for adverse mental health outcomes.
Key considerations when developing and implementing digital technology for early dementia detection
Authors: Wilson Sarah , Tolley Clare , Ardle Ríona Mc , Beswick Emily , Slight Sarah 
Published: December 2023

AbstractBackgroundThe World Health Organisation (WHO) promotes using digital technologies to accelerate global attainment of health and well‐being. This has resulted in an increase in research exploring how digital technology can be used to aid early detection of dementia and to support the successful implementation of new technology into healthcare systems, including the English National Health Service (NHS). We conducted a qualitative study to understand the key considerations amongst healthcare professionals (HCP) when developing and implementing digital technology for the early detection of dementia in the NHS.MethodWe recruited primary and secondary care HCPs from various NHS clinical networks. We explored participants’ views on early dementia detection, using digital technology to aid this approach, and any potential implementation challenges. An inductive thematic analysis approach was taken to identify themes using QSR N‐Vivo (Version 1.6.1). Themes were refined by the authors.ResultEighteen semi‐structured interviews were conducted with seven secondary and 11 primary care HCPs. Key themes included considerations for healthcare users and digital technology. Some healthcare professionals felt early detection of dementia would provide healthcare users with the opportunity to future‐plan, for example by “tak[ing] out lasting powers of attorney” (P3 Primary Care Physician (PCP)). Whilst others were concerned “if we’re now looking at screening people who don’t have symptoms, […] the waiting list for memory clinics [referring to secondary care] would dramatically increase” (P6 PCP) which could negativity affect healthcare users. The use of digital technology to aid early detection raised concerns surrounding health equity, to ensure that we are “not excluding people who already are in digital poverty” (P5 PCP). Many HCPs also felt it was important to consider how “dementias have different features” (P14 PCP), so they “would want a tool that tests different modalities” (P6 PCP) to help differentiate between diagnoses.ConclusionThese results will inform future research in developing and implementing digital technology for early dementia detection. Work is needed to explore how best to support patients receiving information about their early detection of dementia, and the HCPs involved in this process. Research is needed to develop digital inclusion strategies to promote health equity.
AI‐guided patient stratification for neurodegenerative disorders using unsupervised trajectory modelling
Authors: Burkhart Michael C. , Lee Liz Yuanxi , Vaghari Delshad , Venton Jenny , Thomas Spencer , Smith Nadia , Everson Richard , Tino Peter , Kourtzi Zoe ,   the Early Detection of Neurodegenerative diseases initiative
Published: December 2023

AbstractBackgroundPredicting neurodegenerative disorders early has major implications for timely clinical management and patient outcomes. Despite advances in medical technology, we still lack tools to precisely stratify patients for targeted interventions. Here, we propose an unsupervised modelling approach based on mixtures of state space models that learns from longitudinal multimodal (brain imaging, cognitive) data to stratify patients into clusters with different clinical outcomes. Our approach has the potential to support dementia prediction based on cost‐effective, non‐invasive digital measures alone.MethodWe trained (with cross‐validation, 4 components selected with elbow method) a mixture of linear Gaussian state space models on 571 trajectories (2‐4 assessments) from ADNI comprising a) state variables: neuroimaging biomarkers (temporal lobe gray matter density, β‐amyloid) and b) observations: cognitive tests (ADNI‐Mem, ADNI‐EF, MoCA, & ADAS‐13) collected at regular 2‐year intervals. The model clustered individuals based on longitudinal changes in biomarkers and the relationship between biomarkers and cognitive scores (figure 1). We validated model‐derived clusters against clinical outcomes (unseen by the model) based on each individual’s final assessment.ResultOur unsupervised modelling approach effectively stratifies individuals by clinical outcome. Cluster A comprises 65% healthy controls and 33% stable MCI patients (individuals with MCI who do not convert to AD in a 3‐year period) while cluster D comprises 77% Alzheimer’s patients (table 1). Profiling these clusters using MMSE score validates our approach: individuals in cluster A maintain high memory scores over 6 years whereas individuals in cluster D decline (figure 2). Further, we find that our model maintains good stratification when tested a) with a single rather than multiple assessments and b) with cognitive data only (i.e. without biomarkers). These results enhance the clinical utility of our approach, as collecting longitudinal and biomarker data may prove challenging in clinical settings.ConclusionOur modelling approach robustly stratifies patients by clinical outcome when trained on longitudinal multimodal data and tested using cognitive scores alone. Our approach has strong potential to generalize to other non‐invasive and cost‐effective data (e.g. digital markers from wearable technologies), enhancing the translational impact of our AI‐guided tool for early and precise patient stratification in clinical practice.
A new therapeutic approach to Tauopathies: targeting presynaptic tau with antisense oligonucleotides to Synaptogyrin‐3
Authors: Carrano Nicolo 
Published: December 2023

AbstractBackgroundThe protein Tau is central to several neurodegenerative disorders (“tauopathies”). “Tau‐tangles” (aggregations of the Tau protein) are a key hallmark of Alzheimer’s and many other diseases and Tau‐protein is mutated in several forms of dementia. In all these conditions, Tau causes complex, multifactorial defects in neurons that lead to cognitive decline. Under normal conditions, Tau is attached to axonal microtubules, but under pathogenic conditions it detaches and spreads throughout the neuron, including synapses. Work from my lab indicated that when Tau is present at pre‐synaptic terminals it binds to and clusters synaptic vesicles and identified Synaptogyrin‐3 as a physical interactor of Tau. My lab demonstrated that the partial loss of Synaptogyrin‐3 (Syngr3) restores working memory and rescues synaptic degeneration in mice that express pathogenic P301S Tau (“PS19”), a well‐accepted model for tauopathy that recapitulates features seen in patients, including synaptic loss, neuroinflammation and cognitive decline. Partial (and complete) loss of Syngr3 is benign in mice and fruit flies. Based on this, we pursued a radical alternative and innovative approach, supported by strong pre‐clinical data, to tackle Tau‐induced cognitive decline.MethodWe designed and synthetized oligonucleotides covering the whole Syngr3 transcript, and tested their activity in Neuro2A cells and primary cortical murine neurons in transfection and unassisted uptake conditions.ResultThrough this screen we found several active molecules, that were able to significantly downregulate Syngr3 transcript and protein levels. To find the best candidates, we performed dose‐response curves and time course evaluations in primary murine neurons, and we found several molecules that targeted different regions of the Syngr3 transcript with good activity, potency, and no evident toxic effects.ConclusionWe found several molecules that induce an effective and sustained reduction of Syngr3 expression. As part of the pre‐clinical evaluation, these molecules will be tested in vivo in PK/PD and acute toxicity studies in WT mice, to determine the best administration dosage and therapeutic window. Finally, we will evaluate the effect of our best candidates in a therapeutic setting, treating PS19 tau mice to assess if the acute removal of the protein can alleviate presynaptic tau toxicity and revert tau induced synaptic and cognitive defects.
Non‐economic aspects of social deprivation and cognitive health in old age
Authors: Rodriguez Francisca S , Hoffmann Wolfgang , Peters Oliver , Priller Josef , Schneider Anja , Fliessbach Klaus , Düzel Emrah , Buerger Katharina , Teipel Stefan , Laske Christoph , Jessen Frank ,   DELCODE study team
Published: December 2023

AbstractBackgroundIt is well established that socioeconomic disadvantages such as low income are associated with a higher risk for poor cognitive health in old age. Under the concept of social deprivation, researchers have recently started exploring a broader concept of social embedding including, for instance, unemployment and asset ownership. However, little known of other characteristics of social deprivation and to what extent they are associated with cognitive health.MethodParticipants of the multicenter DZNE Cognitive Impairment and Dementia Study (DELCODE) were asked to complete a questionnaire on four characteristics of social deprivation, (1) Conditions of the living environment, (2) Regional accessibility, (3) Neighborhood support, (4) Family social support. A total of N = 296, 48.3% male, M = 70.8 (SD = 5.8) years old, n = 97 cognitive healthy, n = 161 subjective cognitive decline (SCD), n = 38 mild cognitive impairment (MCI)) returned the questionnaire. Using confirmatory factor analysis, we excluded questions with non‐significant loadings and with coefficients <0.5. The latent scores were saved and a sum score was calculated. The scores were categorized into tertiles (high, medium, low).ResultResults from logistic regression (adjusted for age, gender, education, family status, depression, diabetes, hypertension, hypercholesterol, cerebrovascular diseases, heart disease, and body mass index) indicated that those with low (compared to high) social deprivation had a significantly reduced risk for SCD (OR = 0.38, p = 0.006) and MCI (OR = 0.25, p = 0.018). Of the individual factor scores, only Neighborhood support was significantly associated with SCD (OR = 0.48, p = 0.030) and MCI (OR = 0.32, p = 0.049).ConclusionOur findings suggest that social deprivation and, in particularly, neighborhood support such as visits, helping out, and receiving/giving advice can play an important role in cognitive health in old age. Accordingly, individuals with a high risk for age‐related cognitive impairment might benefit from being embedded in a supportive neighborhood.
A target enablement package for modulating the activity of PLCγ2 as a therapeutic strategy for the treatment of Alzheimer’s disease
Authors: Clayton Brent , Bissel Stephanie J , Richardson Timothy I , Massey Steven M , Beck Daniel E , Putt Karson S , Bedford Logan M , Utsuki Tada , Visvanathan Ramya , Mesecar Andrew D , Lendy Emma K , Kaiser Bridget L , Chu Shaoyou , Mason Emily R , Quinney Sara K , Kandasamy Murugesh , Masters Andrea R , Lamb Bruce T , Palkowitz Alan D , Sondek John , Zhang Qisheng 
Published: December 2023

AbstractBackgroundGenome‐wide association studies, whole genome sequencing, and gene‐expression network analyses comparing normal to Alzheimer’s disease (AD) brain tissue have identified risk and protective variants in genes essential to microglial function. Among these genes is phospholipase C gamma2 (PLCγ2). The P522R variant of PLCγ2 is associated with reduced risk for AD and has been characterized as a functional hypermorph. Carriers of P522R with mild cognitive impairment exhibited a slower cognitive decline rate. Therefore, activation of the protein PLCγ2 with small molecules has been proposed as a therapeutic strategy to reduce the rate of disease progression and cognitive decline in AD patients.MethodWe evaluated analogs of a reported phospholipase activator and performed a high‐throughput screen using full‐length PLCγ2 and affinity selection mass spectrometry (ASMS). Soluble substrate and liposomal‐based biochemical assays were developed to evaluate activation and inhibition of the enzyme. A Cellular Thermal Shift Assay (CETSA) was developed to confirm target engagement in cells. A high‐content imaging assay measuring phagocytosis, cell number, and nuclear intensity was implemented using the BV2 and HMC3 cell lines to characterize cellular pharmacology and cytotoxicity. Results were recapitulated in primary murine microglia. Active compounds predicted to have drug‐like properties were subjected to assays measuring solubility, cellular permeability, and mouse microsomal stability.ResultStructurally distinct, novel PLCγ2 activators have been discovered. In preparation for in vivo studies in mice, in vitro absorption, distribution, metabolism, and excretion (ADME) assays have been carried out for activators with sufficient cellular potency and drug‐like properties.ConclusionActivation of PLCγ2 is a novel therapeutic strategy for treatment of AD. We identified structurally distinct molecular scaffolds with varying degrees of enzyme activation and cellular activity. Recommendations for use of probe molecules in target validation studies and the development of lead‐like molecules for clinical studies will be made.
Chinese ADNI study:Characteristic AD biomarkers precisely predicts Alzheimer’s dementia: China Aging and Neurodegenerative Initiative (CANDI) study
Authors: Gao Feng , Dai Linbin , Wang Qiong , Shi Jiong , Shen Yong , Aging China ,   Neurodegenerative Initiative (CANDI) Consortium
Published: December 2023

AbstractBackgroundTo test the utility of the “A/T/N” system in the Chinese population, we study core Alzheimer’s disease (AD) biomarkers in a newly established Chinese cohort.MethodA total of 411 participants were selected, including 96 cognitively normal individuals, 94 patients with mild cognitive impairment (MCI) patients, 173 patients with AD, and 48 patients with non‐AD dementia. Fluid biomarkers were measured with single molecule array. Amyloid beta (Aβ) deposition was determined by 18F‐Flobetapir positron emission tomography (PET), and brain atrophy was quantified using magnetic resonance imaging (MRI).ResultAβ42/Aβ40 was decreased, whereas levels of phosphorylated tau (p‐tau) were increased in cerebrospinal fluid (CSF) and plasma from patients with AD. CSF Aβ42/Aβ40, CSF p‐tau, and plasma p‐tau showed a high concordance in discriminat‐ ing between AD and non‐AD dementia or elderly controls. A combination of plasma p‐tau, apolipoprotein E (APOE) genotype, and MRI measures accurately predicted amyloid PET status.ConclusionThese results revealed a universal applicability of the “A/T/N” framework in a Chinese population and established an optimal diagnostic model consisting of cost‐ effective and non‐invasive approaches for diagnosing AD.
Baseline and Six‐Month Actigraphy and Sleep‐monitoring Devices Help Differentiate Between Alzheimer’s Disease and Dementia with Lewy Bodies
Authors: Tsuang Debby W , Brown Karl , Shutes‐David Andrew , Payne Sarah , Jankowski Adrienne , Seto Edmund , Louis Erik K St , Levendowski Daniel J , Wilson Katie 
Published: December 2023

AbstractBackgroundDementia with Lewy bodies (DLB) and Alzheimer’s disease (AD) are challenging to differentiate. Mobile health devices that measure motor and sleep domains between clinic visits may improve differential diagnosis.MethodParticipants with probable AD and probable DLB wore ActiGraph triaxial wGT3X‐BT actigraphy devices on their nondominant wrists for 2 weeks and multichannel Sleep ProfilerX8TM EEG devices on their foreheads for 2 consecutive nights.3 Actigraphy data were processed and scored using GGIR and activity counts in R. The Sleep Profiler characterizes abnormal slow‐wave sleep and non‐REM hypertonia (NRH).ResultAt baseline, participants with DLB (n = 9) had higher UPDRS scores and a higher likelihood of psychosis than participants with AD (n = 8; see Table 1). Using univariate Wilcoxon Rank‐Sum tests, we found that at baseline participants with DLB had lower daily activity counts, higher % time in NRH, and lower % time in REM sleep than participants with AD (unadjusted p‐values < 0.05; See Figure 1).In a recent 6‐month followup, activity levels were lower on average than baseline activity levels for both DLB (n = 5) and AD (n = 5). at 6‐months, the differences in % sleep in NRH increased between DLB participants (n = 5) and AD participants (n = 3) as average % NRH increase 6% in DLB and decreased 1% in AD (see Table 2). These 6‐month differences are not statistically significant, but data collection are ongoing.An exploration of methods for processing and scoring actigraphy data revealed that processing can result in wide range of findings. As a result, we have focused on actigraphy outcomes which are more suitable to older participants with dementia.ConclusionParticipants with DLB demonstrated lower baseline physical activity and higher rates of baseline sleep disturbances than participants with AD; sleep differences between DLB and AD appeared to increase over 6 months.Actigraphy and sleep‐monitoring devices are well tolerated in participants with dementia and they can reliably collect valid, useful activity and sleep data in between clinic visits.
Cerebral microbleeds in traumatic brain injury associated with differential risk factors and clinical outcomes: the PREVENT‐Dementia study
Authors: Low Audrey , McKiernan Elizabeth , Prats‐Sedano Maria A , Carter Stephen F , Stefaniak James D , Su Li , Dounavi Maria‐Eleni , Muniz‐Terrera Graciela , Jenkins Natalie D , Ritchie Karen , Lawlor Brian , Naci Lorina , Malhotra Paresh A , Thayanandan Tony , Mackay Clare , Koychev Ivan , Raymont Vanessa , Ritchie Craig W , O'Brien John T ,   the PREVENT Dementia group
Published: December 2023

AbstractBackgroundCerebral microbleeds (CMB) are predictive of increased risk of dementia and stroke. Although commonly regarded as vascular markers, CMB can also stem from non‐vascular aetiologies like head injuries or traumatic brain injury (TBI), although these are often overlooked. Therefore, this study examines CMB in relation to TBI, and their differential causes (i.e., risk factors) and consequences (i.e., clinical outcomes).MethodIn 605 healthy middle‐aged adults (aged 40‐59), CMB were rated on 3T susceptibility weighted imaging (SWI) MRI. TBI was assessed using the Brain Injury Screening Questionnaire (BISQ). TBI+ was defined as at least one blow to the head resulting in loss of consciousness (36.0%; n = 217). Memory was assessed using the COGNITO battery. Interaction analyses examined TBI*CMB interactions on hypertension, gait, and memory. Dominance analysis examined the relative contribution of TBI and vascular risk factors on predicting gait disturbances and memory. All models adjusted for sex, age, education, and study site.ResultTBI was related to higher CMB count (t = 2.06, p = .039), and were more common in males (48.3%) than females (28.0%) (Χ2 = 28.91, p<.001). Number of TBI events related to poorer memory (t = ‐2.62, p = .009) and gait disturbances (t = 3.54, p<.001). Interaction analyses demonstrated that hypertension (t = ‐2.26, p = .024), memory (t = 2.70, p = .007) and gait (t = ‐2.29, p = .023) were less closely related to CMB in individuals with greater number of TBI events, relative to those with fewer TBIs. Regionally, these interactions were significant for lobar CMB, but not deep subcortical CMB. Within the TBI+ group, dominance analysis demonstrated that number of TBI events outperformed vascular risk factors in predicting gait disturbances (Contribution to R2: TBI = 52.9%, vascular risk = 32.6%) and memory (TBI = 28.7%, vascular risk = 1.2%).ConclusionCMB appeared to differ aetiologically and clinically in those with and without TBI. In individuals with TBI, TBI itself was the dominant driver of clinical deficits. When compared to CMB of presumed vascular origins cross‐sectionally, TBI‐related CMB may appear to be less detrimental. However, longitudinal analysis is required to determine how TBI‐related CMB differ in clinical trajectory and downstream pathologies. This study highlights the importance of differentiating between CMB of vascular origins vs. TBI in both research and clinically to aid prognosis and treatment decisions.