bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of age, sex, cognitive status and Apolipoprotein E genotype on plasma biomarkers of amyloid pathology
Authors: Hortsch Sayuri , Carboni Margherita , Kurka Hedwig , Kollmorgen Gwendlyn , Jethwa Alexander , Blennow Kaj , Fowler Christopher J , Laws Simon M , Doecke James D , Masters Colin L 
Published: December 2023

AbstractBackgroundPlasma biomarkers of amyloid pathology may streamline the diagnostic pathway for patients with subjective cognitive decline, MCI, AD . The influence of age, sex, cognitive status, body mass index (BMI) and apolipoprotein E (APOE ε) genotype on phosphorylated‐tau‐181 (phospho‐tau‐181) and apolipoprotein E4 plasma biomarkers was explored.Method597 plasma samples (from the Australian Imaging, Biomarkers and Lifestyle cohort) were retrospectively analysed using the fully automated Elecsys® prototype plasma immunoassays for phospho‐tau‐181 and apolipoprotein E4 on the cobas e 601 and e 411 analysers (Roche Diagnostics International Ltd). A composite score was derived by combining phospho‐tau‐181 and apolipoprotein E4 results. Amyloid‐positron emission tomography (PET) visual read was the reference standard for defining amyloid status. The relationship between biomarker levels and potential influencing factors was assessed.ResultPhospho‐tau‐181 and composite score were increased in samples from amyloid‐positive versus amyloid‐negative subjects and in dependence of cognitive status. The dependence of phospho‐tau‐181 and composite score on APOE ε genotype could largely be explained by the increased prevalence of amyloid positivity in APOE ε4 carriers compared with non‐carriers. A potential confounding relationship between sex and age and phospho‐tau‐181 or composite score was detected, which could not be fully explained by the increasing incidence of amyloid positivity with age. Apolipoprotein E4 was highest in APOE ε4 homozygotes, lower in heterozygotes and undetectable in non‐carriers.ConclusionA single cut‐off value for phospho‐tau‐181 and composite score may be used in clinical routine to determine amyloid pathology in the intended use population, regardless of age, sex and APOE ε genotype. Further evaluation is required in more diverse populations (comorbidities) and using additional biomarkers (β‐amyloid).
How does amyloid beta alter levels of ınflammation parameters in human astrocyte culture?
Authors: Şengül Büşra , Keskin Ebru , Dursun Erdinc , Gezen‐Ak Duygu 
Published: December 2023

AbstractBackgroundIn neurodegenerative diseases, specific neuron types and glial cells undergo degeneration leading to the appearance of specific disease symptoms (1). Neurodegenerative diseases in the central nervous system (CNS) are also highly effective on cells that support neuron life. Astrocytes are dynamic support cells that maintain brain balance, regulate the neurotransmitter system, process synaptic information, energy metabolism, antioxidant system, and inflammatory response (2). The blood‐brain barrier (BBB) may lose its permeability in pathological conditions. Both endothelial cells and astrocytes undergo phenotypic changes and become reactive (3). In Alzheimer’s disease (AD), amyloid beta (Aβ) is suggested to induce a pathological pathway that leads to neurodegeneration and dementia (4). A limited number of studies in the literature reveal a general profile of the neuroinflammatory mediators induced by Aβ, one of the main pathological elements of AD in human astrocytes.MethodBased on this information, AD‐like pathology was created in our study with Aβ1‐42 treatment in human astrocyte cultures. The inflammatory response of these pathologies in human astrocytes was compared with the profile that emerges differently from a healthy astrocyte population. Alterations in the levels of released inflammatory proteins and their receptors were detected with the chemiluminescence‐based Western/dot blot method by using the human inflammation antibody array (Ray Biotech C‐Series Human Antibody Inflammation Array C4).ResultOur data show that Aβ1‐42 treatment predominantly releases IL‐6, MCP‐1, and TIMP‐2 proteins into the culture supernatant in human astrocyte cells. On the other hand, whether reactive astrogliosis was triggered in the presence of Aβ in human astrocytes was followed by immunofluorescent labeling (IF).ConclusionThis is the first study that investigated the general profile of released inflammatory factors in human astrocytes and how this profile is altered by Aβ1‐42 treatment.(The present work was supported by the Research Fund of Istanbul University, Project no: 30666)
Microglia transcriptional heterogeneity across human and experimental models
Authors: Garg Anjali , Novotny Brenna C , D'Oliveira Albanus Ricardo , Brase Logan , Karch Celeste M. , Morris John C , Perrin Richard J. , Sutherland Greg T , Benitez Bruno A. , Harari Oscar 
Published: December 2023

AbstractBackgroundThe molecular data from multiple brain regions, cohorts, experimental models are seldom integrated comprehensively, although it provides a unique opportunity to study the cellular heterogeneity and molecular changes across AD etiology and progression. We have developed a new reference model to bridge across datasets.MethodWe leveraged single‐nuclei transcriptomic profiles (snRNA‐seq) of human microglia (parietal cortex from 67 donors from the Knight ADRC and DIAN brain banks; N = 15,726; Dataset1) [1], iPSC‐MLC CRISPRi/a‐based genetic screens in human iPSC‐derived microglia (N = 15,350; Dataset2) [2], and WT and R47H TREM2 xenografted microglia (xMGs), isolated from chimeric AD mice (N = 25,407; Dataset3) [3] to build a comprehensive atlas of microglia heterogeneity, that captures transcriptional states fairly well represented in each dataset. We employed Seurat v4 [4] to integrate the data, and scArches [5] to build classifiers.ResultWe identified homeostatic, activated, interferon (IFN), and IL1B clusters across datasets present in all data we had integrated. In addition, we identified MHCII. We observed that some of the clusters of original states were combined into single clusters. For example, CXCL10‐IFN and INF. We also observed that the integrated data shows a more distinctive expression profile of Type I+II IFN. Furthermore, we build a multiclassifier to label novel microglia generated from hundreds of samples, and data from various experimental models. The cross‐validation analyses indicate that the overall accuracy of the classifier (scArchers) is 0.85 (Fig. 1), although it changes for the distinct datasets [5]. For human microglia in Dataset1 the accuracy was 0.79, while for iPSC‐MLC was 0.73 and 0.96 for Dataset 3. Our results indicate that this multi‐model reference can capture subtle differences better that study‐centric analyses of the data.ConclusionWe are repurposing microglia transcriptomic single‐cell data to build a cross‐species and experimental iPSC‐MLC to bridge across cohorts, species, and experiments. Our results, indicate that this new resource allows to simultaneously interrogate gene expression across different experiments and transcriptional states, and providing the foundation to integrate additional single‐cell molecular data from model organism, ATAC‐seq, and spatially resolved transcriptomics.
References: [1 https://doi.org/10.1101/2021.11.30.21267072; [2] PMID: 34301296; [3] PMID: 35953545; [4] PMID: 34062119; [5] PMID: 34462589
Determination of molecular chaperone levels in cerebrospinal fluids of Alzheimer’s patients
Authors: Sordu Pelin , Alaylıoğlu Merve , Samancı Bedia , Bilgiç Başar , Hanagasi Hasmet , Gurvit Hakan , Ulutin Turgut , Dursun Erdinc , Gezen‐Ak Duygu 
Published: December 2023

AbstractBackgroundMolecular chaperones are a component of the protein homeostasis network and regulate the biogenesis, folding, and trafficking of proteins, protecting the proteome against misfolding, aggregation, and proteotoxicity [1]. Therefore, they serve as the first line of defense against toxicity caused by misfolded proteins such as Aβ and tau [2]. Amyloid precursor protein (APP) interacts with chaperones from the moments of microtubule‐associated protein tau (MAPT) production. These properties keep the molecular chaperones in close contact with many proteins within the cell, including proteins associated with Alzheimer’s disease (AD), such as APP and tau [3]. According to the data we obtained using the web‐based FpClass protein‐protein association (PPI) prediction program, which investigates protein‐protein interactions, we determined that the AD‐related proteins MAPT and APP strongly interact with the chaperone proteins HSP90AA1, CHIP (STUB1) and HSPA4. In light of this information, we thought these chaperone proteins could interact with Aβ and tau and exit the CSF together, and these chaperones could be used as a biomarker.MethodFollowing this purpose, we determined the levels of HSP90AA1, STUB1, and HSPA4 chaperone proteins in CSF samples of AD, MCI, and FTD patients and individuals diagnosed with SCI using the ELISA method. Depending on the distribution of ApoE, any changes in CSF chaperone levels and co‐localization of these chaperones with MAPT and Aβ1‐42 were demonstrated by double‐immunofluorescence labeling in neuron‐differentiated human SH‐SY5Y cells. Within the scope of the study, these parameters included to be biomarkers that were investigated.ResultCSF HSP90AA1 protein levels were increased in sporadic AD and FTD patients compared to controls, CSF HSPA4 protein levels were increased in sporadic AD patients compared to family history of AD patients, and CSF STUB1 protein levels were decreased in AD, MCI, and FTD patients compared to controls.ConclusionConsidering the findings of our study, the presence of these chaperone proteins in CSF suggests that they may have an important place in the neuropathological processes of neurodegenerative diseases such as Alzheimer’s disease.The present work was supported by the Research Fund of Istanbul University‐Cerrahpasa. Project No. 33638
Multimodal Neuromarkers Predict Successful Physical Activity Engagement in Older Adults with Vascular Disease
Authors: Thovinakere Nagashree , Lin Sue‐Jin , Baumeister Robert , Medina Yasser Iturria , Geddes Maiya R. 
Published: December 2023

AbstractBackgroundPhysical inactivity is a significant risk factor for cognitive decline, particularly in vulnerable populations including those with cardiovascular risk‐factors1. To better understand the mechanisms that support positive physical activity engagement, the current study aimed to evaluate whether neuromarkers can predict future change in physical activity among older adults with a newly diagnosed cardiovascular risk‐factor.MethodWe analyzed baseline resting‐state functional and structural magnetic resonance imaging (MRI) data from the UK‐Biobank, a large population longitudinal cohort (n = 365; mean age = 62.10 years ± 6.5; cognitively normal). Brain imaging was obtained at baseline, and physical activity data was obtained at baseline and follow‐up after 5 years. Inclusion criteria were a new diagnosis of a cardiovascular risk factor (hypertension, type‐II diabetes‐mellitus, dyslipidemia, cardiac angina or myocardial infarction) between baseline and follow‐up; and did not meet the World Health Organization recommended 150 minutes/week of moderate or 75 minutes/week of vigorous physical activity at baseline. Demographic variables including age, sex, and education were included as covariates of non‐interest.To assess whether baseline resting‐state brain imaging predicts future change in physical activity behaviour, we performed a kernel‐ridge‐regression model with 5‐fold nested‐cross‐validation. Preprocessed neuroimaging data was used as input for the analysis, and the machine‐learning pipeline included feature reduction using grid‐search, hyperparameter selection, and model‐building: the model predicts whether test subject successfully increased physical activity engagement at follow up (reported above 150 min/week moderate or 75 min/week vigorous physical activity). Permutation‐testing (100 times) was performed before evaluating prediction metrics using accuracy and Receiver Operating Characteristic curves.ResultOur prediction model delivered an accurate performance with average accuracy of 0.861 ± 3.8, and 0.883 ± 4.2 area under the curve (AUC) in predicting future behaviour change from physically inactive at baseline to physically active in follow up.ConclusionThese results show baseline brain imaging can accurately predict physical activity behavior change in older adults with new cardiovascular disease. Leveraging machine‐learning methods to predict future lifestyle engagement will help characterize the neural mechanisms that support successful lifestyle change after a new cardiovascular diagnosis.1. Gallen et al. Trends in Cog Sci. 2019
Blood‐based markers of neurodegeneration linked with brain atrophy and cognition in aging
Authors: Kalpouzos Grégoria , Magnusson Filip , Gustavsson Jonatan , Falahati Farshad , Papenberg Goran , Mangialasche Francesca , Vetrano Davide Liborio 
Published: December 2023

AbstractBackgroundNeurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) have been linked to aging‐related brain tissue loss and cognitive decline, both related to neurodegeneration. Recently, NfL and GFAP have become quantifiable in blood; little is known about their association with brain structure in aging adults.MethodSingle‐Molecule Array (SIMOA) technology was used for ultra‐sensitive detection and quantification of NfL and GFAP in blood plasma at baseline in healthy volunteers (N = 102, 52 female, 52‐79 years old). These individuals also underwent magnetic resonance imaging twice, 3 years apart (N = 72 at follow‐up), and cognitive testing. We examined the relationships among NfL, GFAP, age, brain atrophy parameters (gray‐matter volume ‐ GMV, cortical thickness ‐ CT) and cognitive performance (composite score of episodic and working memory, executive functions and perceptual speed). The relationships between blood markers, GMV and CT were assessed using voxel‐ and surface‐based morphometry, cross‐sectionally and longitudinally, adjusting for age, sex and education.ResultOlder age was related to higher levels of NfL and GFAP (ps < .001; Figure 1). Cross‐sectionally, older age was related to lower GMV in the hippocampi and lateral middle temporal regions, and lower CT in lateral frontoparietal areas. Longitudinally, atrophy was located in fronto‐parieto‐temporal regions, more strongly in the left hemisphere (all ps < .05 Family‐Wise Error corrected). Controlling for age, sex, education and total intracranial volume, higher NfL levels were associated with lower volume in inferior temporal regions (cross‐sectionally), and with atrophy in right hippocampus (longitudinally) (p < .001 uncorrected; Figure 2). Higher GFAP levels were associated with lower volume and thinner cortex in frontoparietal regions, and atrophy in right frontal cortex (p < .001; Figure 2). After splitting the individuals as decliners and non‐decliners based on their cognitive‐performance changes, it was found that the negative associations between NfL and inferior‐temporal volume, and between GFAP and fronto‐temporal volume, were driven by the decliners (Figure 3).ConclusionHigher NfL or GFAP levels are related to atrophy, beyond age, in key regions known to be affected in neurodegenerative disorders, possibly indicating early neuropathological changes.
Using Virtual Reality to Assess Spatial Cognition in Subjective Cognitive Decline and Mild Cognitive Impairment due to Alzheimer’s Disease
Authors: Pai Ming‐Chyi 
Published: December 2023

AbstractBackgroundSpatial navigation impairment (SNI) is prevalent in people with Alzheimer’s disease (AD) continuum and may appear in the initial clinical stage. To detect this deficit in people at risk may not only help to prevent getting lost or missing incidents, but also provide a useful clinical feature for diagnosis. Traditional assessments for SNI include questionnaires, paper pencil and maze tests, or video games. Although a real‐world setting is more valid, direct, and accurate, it has many unexpected conditions such as weather, obstacles, or accidents. Thanks to technology, virtual reality (VR) is a new way to assess SNI.MethodWe used PJVR to test spatial navigation ability in cognitively unimpaired (CU), subjective cognitive decline (SCD) and mild cognitive impairment due to AD (MCI‐AD). The PJVR is the VR version (Vive Pro Eye Head‐mounted Display, HTC) of the PJ device, which was developed by Pai and Jan and has been successfully verified its power to discriminate each other among CU, MCI, and mild AD. With a map provided and using joysticks or handles, participants were requested to reach five points in a 660‐meter path on our university campus. Linear deviation in meters in each point was treated as the variable for comparison. A pre‐test training course was given to facilitate the procedure.Result118 subjects signed informed consent and 87 (73.7%) completed the trials, including 18 CU, 41 SCD and 28 MCI‐AD. Fourteen, or 11.9%, of all participants failed the trials due to cybersickness. The averaged linear deviations of the CU, SCD and MCI‐AD were 36.1 (38.2), mean (S.D.), 40.8 (44.4), and 93.7 (46.8) meters respectively (p<0.000). The linear deviation of the PJVR of the participants was correlated with the Questionnaire on Everyday Navigation Abilities (p<0.001), indicating a good real‐world validity.ConclusionAlthough the rate of cybersickness is higher as compared with the reports from Western countries, most of the participants completed the trials. The PJVR is feasible to assess spatial cognition and able to discriminate CU/SCD from MCI‐AD. To simplify PJVR to be practical is important to welcome the era of digital cognitive assessment.
Ethnic Disparities in Clinical Presentation of Patients with Early‐Onset Alzheimer’s Disease
Authors: Yang Meredith , Yoon Suemin , Covaciu Rachel , Mastrianni James , Seibert Kaitlin 
Published: December 2023

AbstractBackgroundEarly‐onset Alzheimer’s Disease (EOAD) affects patients under age 65 and may present with non‐amnestic features. Black patients are half as likely as White patients to be diagnosed despite twice as many risk factors. Ethnic disparities in EOAD have not been fully characterized.MethodsWe retrospectively collected data on ethnicity, level of education, Montreal Cognitive Assessment (MoCA) scores on EOAD patients diagnosed between 2017 and 2022 at The University of Chicago Memory Center.ResultsOf 88 total patients, 60 (68.8%) identified as White and 28 (31.8%) identified as Black. Age at diagnosis was 57.3 ± 5.24 years in Black patients compared to 55.9 ± 5.69 years In White patients. Average time to diagnosis was longer in Black patients (5 ± 9.21 yrs.) vs White patients (3.5 ± 6.44 yrs). Black patients had lower MoCA scores than Whites at presentation (12.17 ± 6.91 vs 15.15 ± 5.92), despite similar education levels among Black vs. White patients (14.71 ± 2.30 vs 15.21 ± 3.00).Black patients more commonly displayed an amnestic profile (19 or 67.9%) than a non‐amnestic presentation (9 or 32.1%), although 2 patients (7.14%) presented with visual symptoms suggestive of posterior cortical atrophy (PCA), 5 (17.9%) patients had prominent language symptoms suggestive of logopenic primary progress aphasia (l‐PPA) and 1 (3.6%) patient had an executive presentation, suggestive of executive variant of AD (EAD). In White patients, 11 (18.3%) were diagnosed with PCA, 10 (16.7%) with EAD and 8 (13.3%) with l‐PPA.Differences were noted in the application of diagnostic tests, in that neuropsychological testing (NPT) and CSF testing were less often ordered in Black patients (NPT: 8 (29%) in Blacks vs 45 (75%) Whites, p = 0.001; CSF: 4 (14%) Blacks vs 30 (50%) Whites, p = 0.002).ConclusionIn our cohort, Black patients with EOAD were on average older, more advanced, and experience longer delays and differences in diagnostic management than their White counterparts. Further work is needed to characterize the barriers to diagnosis for Black patients with EOAD and the potential differences in clinical presentations.
FedExosome: profiling AD‐related mitochondrial DNA and microRNAs isolated from neuronal‐enriched peripheral blood packages
Authors: Hall Courtney , Garlotte Isabelle , Subasinghe Kumudu , Barber Robert , Phillips Nicole 
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) is a complex disease characterized by impaired memory, diminished cognition, and specific brain pathology (i.e., accumulation of amyloid beta plaques and tau tangles). AD progression is often difficult to detect with the earliest clinical symptoms appearing decades after key neuropathological changes have occurred. Accurate diagnosis early, between initial disease onset and clinical manifestation, could reveal critical aspects of pathogenesis and inform the development of effective therapeutic strategies to prevent neuronal death. Evidence suggests that early alterations in the AD brain can propagate to local and distal cells through the biological packages secreted by neurons. These neuronal‐enriched extracellular vesicles (NEEVs) can cross the blood‐brain barrier and are capable of mediating systemic inflammation in response to CNS‐sourced stress through their mitochondrial DNA (mtDNA) and microRNA (miRNA) cargo. Circulating NEEVs may therefore serve as an easily accessible, early indicator of the forthcoming neuropathological changes in the AD brain. Here, we develop a higher throughput workflow for profiling mtDNA and miRNA in plasma NEEVs and apply the workflow to clinical samples collected longitudinally from participants in the Texas Alzheimer’s Research and Care Consortium.MethodHuman plasma samples were processed using a two‐step method involving (1) precipitation of total exosomes with ExoQuick (SBI) and (2) immunoprecipitation‐based enrichment of NEEVs with a biotinylated antibody against a well‐established neuronal surface marker (CD171). Captured NEEVs were stained and analyzed using flow cytometry as well as nanoparticle tracking analysis (NTA). DNA and RNA were then extracted for mtDNA quantification and miRNA sequencing.ResultThe protocol modifications implemented in this project were compared based on particle size, distribution, and purity as well as absolute mtDNA load and spike‐in normalized miRNA read counts. These data not only demonstrate the feasibility of profiling the mtDNA and miRNA from 500µL of plasma NEEVs but have also resulted in a higher throughput workflow for processing TARCC patient samples.ConclusionThis work represents the first successful attempt to simultaneously quantify mtDNA and sequence miRNA in the relatively small subpopulation of plasma EVs that originate from neurons. Future studies will harness the protocol developed herein to assess the biomarker potential of NEEVs in the TARCC cohort.