bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing approaches based on the global functional organization of the brain versus local connectivity to predict tau‐PET across the Alzheimer’s disease phenotypic spectrum
Authors: Corriveau‐Lecavalier Nick , Botha Hugo , Schumacher Julia , Dicks Ellen , Barnard Leland R , Lee Jeyeon , Sintini Irene , Gunter Jeffrey L. , Kamykowski Michael G. , Graff‐Radford Jonathan , Ramanan Vijay K , Fields Julie A. , Machulda Mary M. , Boeve Brad F. , Lowe Val J. , Kantarci Kejal , Knopman David S. , Whitwell Jennifer L , Josephs Keith A , Petersen Ronald C. , Jack Clifford R. , Jones David T. 
Published: December 2023

AbstractBackgroundPredictive models of tau‐PET accumulation have largely relied on the functional connectome to estimate its spatial patterns in Alzheimer’s disease (AD). Patterns of global functional organization represent a promising avenue as they encapsulate many biological properties relevant to neurodevelopment, cognition and degeneration. We compared approaches based on local connectivity (from task‐free fMRI) and global organization (from FDG‐PET) to predict regional tau‐PET across AD phenotypes.MethodWe included 430 cognitively unimpaired (CU) individuals (214 A+T‐, 216 A+T+) and 62 amnestic mild cognitive impairment (aMCI), 64 amnestic AD, 21 dysexecutive AD (dAD), 41 logopenic progressive aphasia (LPA) and 49 posterior cortical atrophy (PCA) patients (all A+T+) from the Alzheimer’s Disease Research Center, Mayo Clinic Study of Aging, and Neurodegenerative Research Groups (referred to as “Mayo cohort”). The connectivity approach consisted of assessing the relationship between a region’s tau level and its functional connectivity to the region of highest tau (epicenter). The global organization approach consisted of 1) performing a principal component analysis on 3000 FDG‐PET images that did not overlap with the Mayo cohort, 2) projecting FDG‐PET images of the Mayo cohort onto the low‐dimensional space generated in Step 1 and extracting corresponding weighted values across the first 100 components, 3) using these weighted values as predictors of regional tau‐PET in a linear model and determining optimal parameters based on predicted R
2 values, and 4) using the parameters from the model built in Step 3 to predict tau‐PET in the ADNI cohort (n = 86) (Fig.2).ResultThe connectivity‐based approach yielded adjusted R
2 values ranging from 0.19‐0.45 across diagnostic groups (Fig.1). The global organization approach yielded averaged adjusted R
2 and predicted R
2 values of 0.71 and 0.63, respectively, in the Mayo cohort. Out‐of‐sample median R
2 in the ADNI cohort was 0.41 (range 0.10‐0.60) (Fig.3).ConclusionAn unbiased approach based on the global functional organization of the brain and using an imaging modality widely used in clinical settings outperformed a connectome‐based one to predict regional tau‐PET across the AD phenotypic spectrum. Patterns of tau accumulation may better relate to the large‐scale physiology of the brain underlying specific mental functions rather than local connectivity factors.
Immigrant health paradox: Do immigrants have lower risks of dementia than non‐immigrants? A systematic review and meta‐analysis
Authors: Lillard‐Green Arion M , Hosssain M. Mahbub , Hong Y. Alicia 
Published: December 2023

AbstractBackgroundWith rising immigration rates around the globe, there is growing interest in the “immigrant health paradox”. Voluntary immigrants tend to have healthier profiles compared to their native‐born counterparts, especially within the early years after migration. Conversely, most immigrants experience structural racism and barriers to health and social services in the process of acculturation. Limited research is focused on cognitive health of older immigrants and existing evidence on whether immigrants have lower rates of dementia or cognitive impairment compared to native‐born remains inconclusive. The current study aims to address this literature gap with a systematic review and meta‐analysis.MethodThe literature search and review was guided with the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISM). Major databases of PubMed, CINAHL, Global Health, PsycInfo, and Web of Science were searched. Studies that reported prevalence or incidence of dementia or cognitive impairment comparing immigrants and native‐born were included. A random‐effects meta‐analytic model with the DerSimonian‐Laird approach was used to calculate the pooled relative risk (RR) of dementia.ResultsA total of 26 articles were included in this review, of which 14 were reported from North America, 11 were from EU countries, and one from Australia. The included studies represented a total of 12.42 million participants. The pooled RR of dementia was 1.10 (95% confidence interval [CI]: 0.78 – 1.53) among immigrants compared to natives with high heterogeneity (I2 = 99.6%; 95% CI: 99.6% ‐ 99.7%). Stratified analyses suggested that studies based on medical records reported lower risks of dementia in immigrants, whereas most studies based on surveys reported higher risks of dementia in immigrants.ConclusionThis study represents one of the first meta‐analyses of dementia risks comparing immigrants to non‐immigrants. The lower risks of dementia in immigrants documented in medical records may be due to the fact that immigrants are less likely to seek diagnosis or treatment of dementia due to social and cultural barriers in the new country. Immigrants are a diverse population and immigration experience varies in different groups and across countries. We call for more research on rigorous studies on dementia risks in immigrants.
Prevention of release of amyloid beta 1‐42 fibrils by inhibiting Hsc70
Authors: Çamoğlu Tugay , Yurttaş Zuhal , Dursun Erdinc , Gezen‐Ak Duygu 
Published: December 2023

AbstractBackgroundAmyloid beta 1‐42(Aβ1‐42) peptide is famous for its fibrils in amyloid plaques, which are pathological findings of Alzheimer’s disease(AD). The fibrils can amplify themselves like prions by using monomeric peptides as substrates. Therefore, neurons can uptake and release the fibrils, and this process can cause pathology to spread throughout the brain. In addition, hsc70‐mediated tau release by exocytosis has been shown. Therefore, in this study, we examined whether Hsc70 also mediates the release of Aβ1‐42 fibrils(F‐Aβ1‐42).MethodSH‐SY5Y cell was used in the study. Hsc70 dominant negative mutant, D10N, overexpressed with 72 hours plasmid transfection. MOCK plasmid and untransfected cells were used as controls. Hsp70 inhibitor VER‐155008(VER) was applied to other cell groups, and DMSO and untreated cells were controls. F‐Aβ1‐42 was labeled with Alexa Fluor‐488 and fragmented with ultrasonication before applying to the cells. We found that the cells took up fibrils within 6 hours. Therefore, VER, DMSO, D10N, MOCK and untreated cell groups were treated with fibrils, and incubated for 6 hours. Then, the cells were washed to remove extracellular fibrils and incubated for additional 18 hours. Supernatants were collected and measured with a fluorometer. 2 to 0,001 µM fluorescent‐labeled Aβ1‐42 fibrils were measured to make standard graphics.ResultWe showed that SH‐SY5Y cells effectively uptake and release F‐Aβ1‐42. VER application did not significantly affect to release of F‐Aβ1‐42 compared to DMSO and the control groups(p>0,05). However, F‐Aβ1‐42 release was significantly increased in D10N overexpressing cells compared to MOCK and untransfected cells(p<0,05).ConclusionIn this study, we have shown that release of F‐Aβ1‐42 can be prevented by intervention to the pathway that Hsc70 takes roles. Why the release was decreased with D10N but not with VER treatment may be caused by the fact that VER inhibits Hsp70 chaperon class, while D10N targets only Hsc70. These results showed that Hsc70 especially could take a role in the release of F‐Aβ1‐42. Recently, some drugs aiming at clearing extracellular F‐Aβ1‐42 were approved by the FDA. Our findings can provide a new target working in a different pathway for AD treatment. This study was supported by Istanbul University‐Cerrahpaşa BAP (Project ID:33479).
24 hour rest‐activity rhythms and cognition in community dwelling older adults
Authors: Zhang Meina , Hoth Karin F , Linkenmeyer Carinda , Moon Chooza 
Published: December 2023

AbstractBackgroundCognitive decline associated with aging is a growing public health concern as individuals are living longer with chronic medical conditions. Rest activity rhythm (RAR) describes the pattern of physical activity and sleep period in 24 hours. Compared with younger people, older adults are more likely to maintain a sedentary lifestyle with altered RAR. Although there is no doubt that physical activity plays a vital role in health outcomes, little is known about how RAR is linked to cognitive functioning in late life. This study investigated the association between RAR and cognitive performance among older adults.MethodSixty community dwelling older adults aged 70±7.3 years (mean ± standard deviation) wore Phillips actigraphy spectrum plus 2 for two weeks. RAR parameters were analyzed using cosinor approach, such as amplitude (difference between the peak and lowest activity levels), mesor (mean activity level), pseudo‐F‐statistic (the robustness of RAR), and acrophase (peak activity time). A comprehensive neuropsychological battery was used to assess cognition (i.e., Brief Visuospatial Memory Test – Revised (BVMT‐R), California Verbal Learning Test – II, Boston Naming Test, Wechsler Adult Intelligence Scale‐IV Coding, and Trail Making Test A and B). Multiple linear regression models were built to explore associations between different RAR measures and each cognitive task adjusting for age, gender, and years of education.ResultWe found positive associations between RAR amplitude (p = 0.01), mesor (p = 0.008), acrophase (p = 0.006), pseudo F‐statistic (p = 0.002) and visual memory (BVMT‐R). Similarly, positive associations were found between amplitude (p = 0.006), mesor (p = 0.005), acrophase (p = 0.005), pseudo F‐statistic (p = 0.002) and psychomotor processing speed (Coding). Greater pseudo‐F statistics were associated with stronger performance on naming (BNT); p = 0.03). No association was found between RAR and other cognitive tasks.ConclusionsOur findings provide evidence that some RAR characteristics are associated with cognitive performance among older adults, particularly visual memory, psychomotor processing speed, and naming ability. Further research should be undertaken using a large and diverse sample, prospective design, and inclusion of potentially confounding variables to confirm those associations.
Movement Digital Biomarkers for Functional and Cognitive Decline in Dementia
Authors: Abulikemu Subati , Crook‐Rumsey Mark , Carpio‐Chicote Ainara , Jeyasingh‐Jacob Julian , Shah Harshvi , Bugg Josh , Daniels Sarah , Sharp David J , Haar Shlomi 
Published: December 2023

AbstractBackgroundDigital biomarkers based on accurate tracking of motor behaviour can provide a cost‐effective, objective, and robust measure for disease progression in dementia, changes in care needs, and the effect of interventions. Most of our brain is involved in the planning and execution of movement. Hence, quantifying and monitoring movement can produce powerful indicators of both motor and cognitive decline. In this project, we develop an intelligent system that computes and tracks movement‐based digital biomarkers of dementia.MethodsThe project is established in a controlled and ecologically valid mock apartment – the Living Lab – situated in the UK DRI Care Research and Technology Centre. We collected patients’ performance in a set of physical tasks and activities of daily living (ADL) with a depth‐based motion capture system, along with neurocognitive measures using Addenbrooke’s Cognitive Examination III and Cognitron. We first conducted temporal and spatial synchronisations of data collected from six Microsoft Azure Kinect cameras to produce high‐precision three‐dimensional joint coordinates that provide dynamic postural representations. These were then used to compute digital kinematic markers. This was followed by an assessment of the efficacy of the biomarkers in characterising people affected by dementia. We examined the association between the biomarkers with motor and cognitive function and overall efficiency in performing ADL.ResultsOur preliminary analysis showed that patients and healthy controls can be distinguished by the distribution of extracted features (an example feature – spinal curvature – is shown in Figure 1) in structured tasks and free behaviour. The variance of the distribution was correlated with performance in clinical assessments.ConclusionOur analysis suggests the feasibility of digital biomarkers in characterising functional limitations and cognitive decline. Successfully validated biomarkers can be integrated into remote health monitoring systems at home, care‐homes, and clinics, with the potential to revolutionise prognostic prediction and functional assessment of dementia.
Ex‐vivo microbleed detection in community‐based older adults using confidence‐aware learning
Authors: Nikseresht Grant , Evia Arnold M , Bennett David A. A , Schneider Julie A , Agam Gady , Arfanakis Konstantinos 
Published: December 2023

AbstractBackgroundCerebral microbleed (CMB) detection on MRI scans of autopsied brains of community‐based older adults is crucial for MR‐pathology studies of cerebral small vessel disease (SVD). However, training an ex‐vivo CMB detection model is difficult due to the low prevalence of CMBs in the brains of community‐based older adults, and the fact that CMB mimics greatly outnumber CMBs on ex‐vivo MRI. We demonstrate that confidence‐aware deep learning, a technique for enforcing correct ranking of examples during neural network training, significantly improves ex‐vivo CMB detection performance and enhances the interpretability of model predictions.MethodCMBs from 286 participants from two longitudinal cohort studies of aging were included in this work. T2*‐weighted gradient echo scans of autopsied brains with a voxel size of 1×1×1 mm were used. Confidence‐aware learning was used to regularize deep learning model predictions such that they reflect the degree of confidence the detection model has in a prediction. Model confidence was estimated during training by correctness, the number of correct prediction events across epochs divided by the total number of epochs. The objective loss function was modified to include a correctness ranking loss (CRL) term that encourages correspondence between correctness and predicted probabilities. Models are trained with and without the CRL loss term to evaluate the impact of confidence‐aware learning on model performance. An end‐to‐end CMB detection framework that combines data synthesis, candidate selection, false positive reduction, and full scan evaluation was used as the backbone for this work.ResultCMB detection models trained using correctness ranking loss achieved a significantly higher ensemble average precision (0.2915) compared with models trained without correctness ranking loss (0.2379). The CRL trained model achieved a 25% higher sensitivity at 0.5 false positives per subject and 12% higher sensitivity at 3 false positives per subject when compared to models trained without CRL.ConclusionThis work demonstrates that training with confidence‐aware learning can improve the performance and interpretability of ex‐vivo CMB detection algorithms in community‐based cohorts. The use of a confidence‐aware CMB detection algorithm for assisted CMB annotation in ex‐vivo MRI will aid in future MR‐pathology studies into the relationships between CMBs and neuropathology.
Risk of neuropsychiatric symptoms among people who develop cognitive impairment with and without a history of post‐traumatic stress disorder
Authors: Gauthreaux Kathryn , Perales Jaime , Flatt Jason D. , Meyer Oanh L. 
Published: December 2023

AbstractBackgroundMost research studying the link between PTSD and cognitive impairment focuses on PTSD as a risk factor for developing Alzheimer’s disease; however, few studies focus on the impact cognitive impairment has on neuropsychiatric symptoms among people with a history of PTSD. Symptoms associated with cognitive decline may increase or cause the relapse of recurrent intrusive memories, dreams, or flashbacks of traumatic events among individuals with a history of PTSD. Additionally, cognitive impairment may lead to a delayed onset, worsening, or recurrence of PTSD‐related neuropsychiatric symptoms among people with PTSD. We aimed to prospectively assess the change in neuropsychiatric symptoms among people who develop cognitive impairment and have a history of PTSD.MethodData were obtained from the National Alzheimer’s Coordinating Center (NACC). Eligibility criteria included participants who were cognitively unimpaired and had non‐missing assessment of PTSD at initial visit, and who had at least one follow‐up visit with cognitive impairment. Information from the Uniform Data Set (UDS) health history and clinical diagnosis forms at the initial visit was used to separate participants with a history of (PTSD+) and participants without a history of (PTSD‐). Demographics, clinical symptoms, and mean NPI‐Q severity scores at the first UDS visit vs first visit with a Clinical Dementia Rating global score (CDR‐GS) of 0.5 were compared between groups.ResultThe final analytic sample included 18 PTSD+ participants and 585 PTSD‐ participants. While both groups experienced significantly higher mean NPI‐Q severity scores between baseline and the first visit with CDR‐GS = 0.5, there was not a significant difference between the groups (p = 0.79). Additionally, both groups exhibited significantly increased rates of change in NPI‐Q severity scores, but this rate was not statistically different between the groups (p = 0.73).ConclusionIn this sample, we found no differences in NPI‐Q scores. The small sample size of PTSD+ participants as well as the mild nature of participants’ cognitive impairment might account for these null findings, as it might be too mild to impact PTSD symptoms; as such, future research examining these symptoms in larger and more diverse samples is warranted.
The cytosolic antibody receptor TRIM21 is required for effective tau immunotherapy
Authors: Mukadam Aamir , Miller Lauren VC , Smith Annabel E , Keeling Sophie , Vaysburd Marina , Andersen Jan Terje , James Leo C , McEwan William A 
Published: December 2023

AbstractBackgroundUsing a variety of cell and animal model systems we demonstrate that the cytosolic antibody receptor and E3 ligase TRIM21 plays a critical role in antibody‐mediated protection against tau pathologyMethodExperiments with organotypic hippocampal slice cultures and in vivo studies in mouse models were conducted to study the role of TRIM21 in tau immunotherapy.ResultWe demonstrate that tau:antibody complexes were internalised to the cytosol of neurons, enabling TRIM21 engagement and thereby protecting against seeded aggregation. Crucially, antibody‐mediated protection against tau pathology was lost in mice lacking TRIM21ConclusionThe cytosolic compartment provides a site of immunotherapeutic protection, which can help in the design of antibody‐based therapies in neurodegenerative disease.
Effect of genetic clusters related to insulin resistance on neurological traits in diverse populations from the Trans‐Omics for Precision Medicine Program
Authors: Sarnowski Chloé , Zhang Yixin , Ammous Farah , Shade Lincoln MP , Jian Xueqiu , Dupuis Josée , Hivert Marie‐France , Florez Jose C , Seshadri Sudha , Morrison Alanna C ,   the TOPMed Neurocognitive and Diabetes working groups
Published: December 2023

AbstractBackgroundInsulin resistance (IR) is a major risk factor for Alzheimer’s disease (AD) and is primarily driven by obesity, another AD risk factor. The biological mechanism by which IR predisposes to AD is unknown. Genetic clustering analyses of type 2 diabetes (T2D) loci can help characterize which mechanism of impaired insulin action may be involved in AD and related traits.MethodWe constructed five genetic clusters related to IR (Obesity, Lipodystrophy, Liver/Lipid, ALP [alkaline phosphatase] negative, and Hyper‐Insulin Secretion) based on a recent clustering analysis of T2D loci (PMID: 36538063). We evaluated the association of each cluster with the Homeostatic Model Assessment for Insulin Resistance (HOMA‐IR) and neurological traits (AD, dementia, general cognitive function, and four brain MRI volumes) in >38k participants (36% men, mean age 55yrs (14.5)) of diverse race or ethnicity, from the Trans‐Omics for Precision Medicine (TOPMed) Program. We conducted pooled and race/ethnicity‐stratified association analyses (European‐50%, African‐American‐22.5%, and Hispanic/Latino‐21%). We used logistic or linear mixed‐effect models, adjusted for age, sex, study, and the first 11 genetic principal components. We accounted for relatedness and allowed for heterogeneous variances across studies.ResultWe confirmed the association of each IR genetic cluster with HOMA‐IR in the pooled analysis (2.6E‐66≤P≤2E‐4) and detected significant to suggestive associations in group‐stratified analyses (6.3E‐39≤P≤0.05), except for the Hyper‐Insulin Secretion cluster in African‐Americans (P = 0.30). The genetic clusters were not significantly associated with neurological outcomes after multiple testing adjustment (P = 0.05/Ngroups/Nclusters/Noutcomes = 0.05/4/5/7 = 3.6×10−4). We observed nominal associations (P<0.05) for two genetic clusters. The Lipodystrophy cluster was negatively associated with intracranial volume in the pooled analysis (beta = ‐0.51, P = 0.003) as well as in European (beta = ‐0.47, P = 0.02) and Hispanic/Latino (beta = ‐1.23, P = 0.01) participants. The Hyper‐Insulin Secretion cluster was negatively associated with hippocampal volume in Hispanic/Latino participants (beta = ‐0.005, P = 0.03), and positively associated with AD and dementia (OR = 1.02 [1.001‐1.038], P = 0.03) in European participants.ConclusionOur findings are consistent with the literature suggesting that IR may be associated with lower brain volumes and increased AD risk. Our analyses shed light on two biological mechanisms of impaired insulin action potentially involved in AD and related traits, with genetic associations that may differ by race or ethnicity.Funding: R00AG066849