bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of objective cognitive decline in preclinical Alzheimer’ disease
Authors: Canovas Rodrigo , Maruff Paul , Fowler Christopher J , Rainey‐Smith Stephanie R , Masters Colin L , Doecke James D ,   The AIBL Research Group
Published: December 2023

AbstractBackgroundIn Alzheimer’s disease (AD), a long preclinical and prodromal period precedes dementia onset in which cognition declines slowly, but at variable rates for different domains. Positive AD biomarkers, (e.g., amyloid, Tau, or APOE ε4 carriage), increase rates of cognitive decline and transition to dementia. However, the extent to which cognitive decline, identified in some older adults, reflects neurodegenerative disease or normal aging in the absence of knowledge about biomarkers or genes is not well understood. We applied a novel approach to classify cognitive decline in individuals using six cognitive composite scores (AIBL Pre‐clinical Alzheimer’s Cognitive Composite (AIBL‐PACC), episodic recall, attention, executive function, language and recognition). We examine group‐wise differences across cognitive composite scores and assessed frequencies for AD biomarker positivity amongst the novel groups.MethodProspective data from 1,389 Cognitively unimpaired (CU) participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing were analysed using an unsupervised multivariate mixture modelling framework, accounting for age, gender and APOE ε4 allele status. Participants cognitive status was classified for their final visit. The cognitive profile and biomarker characteristics of adults with abnormal cognitive decline was compared.ResultDifferences in composite score values between cognitive decline and no decline groups were strongest for episodic recall (Cohen’s d = 1.49) and the AIBL‐PACC score (Cohen’s d = 1.45, Table 1, Figure 1A). By comparison, differences in composite scores between Aβ‐PET groups, or APOE ε4 allele carriers/non‐carriers were of less magnitude (Table 1, Figure 1). Participants with cognitive decline were more likely to be amyloid positive, (decline: 42% vs no decline: 28%, p<0.0001), but not ε4 allele carriers (decline: 28% VS no decline: 27%, p>0.05).ConclusionA measure of objective cognitive decline, created using flexible mixture models with six cognitive composite scores from AIBL, has utility for discerning participants with early changes in cognition. Based upon using the cognitive data alone, this method was able to detect amyloid positivity in those CU participants with cognitive decline.
Elucidating the complex role of ABCA7 in late‐onset Alzheimer’s disease
Authors: Howell Gareth R , Kotredes Kevin P , Pandey Ravi S , Rizzo Stacey J Sukoff , Carter Gregory W , Sasner Michael , Lamb Bruce T , Oblak Adrian L , Territo Paul R ,   MODEL‐AD consortium
Published: December 2023

AbstractBackgroundGenome‐wide association studies (GWAS) identified a locus containing the ATP binding cassette subfamily A member 7 (ABCA7) gene as increasing risk for Alzheimer’s disease (AD). ABC proteins transport various molecules across extra and intra‐cellular membranes. ABCA7 is part of the ABC1 subfamily and has high expression in hematopoietic lineage cells including natural killer cells and macrophages. More recently, ABCA7 expression has been shown in brain cells including neurons, astrocytes, microglia, endothelial cells and pericytes. However, the mechanisms by which variations in ABCA7 increase risk for AD are not known.MethodThe IU/JAX/PITT MODEL‐AD Center prioritized the A1527G variant in ABCA7 (ABCA7*A1527G) as a putative LOAD risk factor. CRISPR/CAS9 was used to introduce Abca7*A1527G variant on to B6.APOE4.Trem2*R47H mice (termed LOAD1) and transcriptional profiling of brain hemispheres from mice at 4, 8 and 12 months old (mos) was used to evaluate molecular effects of Abca7*A1527G. The Abca7*A1527G was then incorporated into B6.APOE4.Trem2*R47H.hAb mice (termed LOAD2) to further evaluate the contribution of Abca7.A1527G to LOAD. Female and male LOAD2.Abca7*A1527G and control mice were characterized at 4 and 12 mos using an established phenotyping pipeline that includes behavior, PET/CT, multi‐omics, fluid biomarkers and immunofluorescence.ResultBrain transcriptional profiling at 12 mos showed Abca7*A1527G induced gene expression changes that are similar to some of those observed in human AD. Enriched pathways included insulin receptor signaling, and granulocyte and neutrophil migration that include myeloid (Trem2, Trem1, Csf1r) and endothelial (Pecam1) related genes. LOAD2.Abca7*A1527G mice showed no cognitive deficit at 12 mos, but did show an uncoupling of brain glycolysis and regional perfusion was observed in a sex‐ and age‐ dependent manner. Consistent with the uncoupled phenotype, IL6, IL10, and TNFα were elevated in plasma. Interestingly, TNFα, primarily expressed by microglia in the brain, was decreased. Also by 12 mos, the density of neurons, astrocytes and microglia were reduced. Additional timepoints (18‐24 mos), and assessment of LOAD2.Abca7*A1527G mice fed a high fat diet, are in progress.ConclusionData support ABCA7*A1527G as a risk for LOAD that exerts its effect through interactions between cerebrovasculature, microglia and peripheral immune cells.
Alterations of Astrocytic Aquaporin 4 expression and distribution in Down Syndrome with Alzheimer’s Disease onset
Authors: Stringer Cherie A , Miyasato Haley , Camey Kevin , Andrews Elizabeth J. , Phelan Michael J. , Head Elizabeth 
Published: December 2023

AbstractBackgroundAstrocytic Aquaporin 4 (AQP4) is a water channel that is typically expressed in astrocytic endfeet, associated with the blood brain barrier (BBB). This association is thought to facilitate the removal of waste products (e.g. beta amyloid (Aβ)) via the ‘glymphatic system’. With Aβ plaque deposition in Alzheimer’s Disease (AD), AQP4 becomes dysregulated observed as a shift in distribution from astrocytic endfeet to astrocytic processes, resulting in inefficient Aβ removal. Here, AQP4 expression and distribution within astrocytes was characterized via immunohistochemistry in human brain tissue from people with Down Syndrome without AD (DS) and with AD (DSAD). We hypothesized that AQP4 protein level would be higher and distributed along astrocytic processes as opposed to the BBB in DSAD relative to DS.MethodAQP4 was evaluated by immunohistochemistry and quantified using QuPath (% loads, positive pixel count) for both frontal (FC) and occipital cortex (OC) in the following groups: DS (n = 17, age range = 0‐51) and DSAD (n = 20, age range = 46‐70). In addition, AQP4 distribution was classified by a blinded observer who annotated distinct AQP4 positive astrocytic morphologies, listed as follows: In WM, ‘Star,’ ‘Webbed,’ and ‘Stippled,’ and in GM, ‘Bushy,’ ‘Branched,’ ‘Globular,’ ‘Endfoot/Vascular Associated.’ResultWe show that AQP4 protein staining was higher in GM DS with AD neuropathology than in DS without AD neuropathology for both FC and OC (FC p = 0.0007; OC p = 0.0034). In addition, we observed a shift from ‘star’ shaped distribution within DS astrocytes to more ‘webbed’ and ‘stippled’ shapes in DSAD; this was not observed in OC. We found a shift in GM morphologies from ‘bushy’ morphology of AQP4 immunostaining in DS to more ‘Branched and Globular’ shapes in DSAD in OC whereas there is a shift from a ‘Bushy’ morphology in DS to more ‘Endfoot/Vascular Associated’ morphologies in the DSAD FC.ConclusionAQP4 expression is higher in DSAD than DS and appears to show a spectrum of astrocyte morphologies with distinct patterns based upon spatial location (FC/OC and GM/WM). Taken together, AQP4 dysfunction and shift to abnormal spatial location may reduce Aβ clearance through the glymphatic system, leading to enhanced plaque formation in DSAD.
Involvement of differential tau pathologies in late‐onset bipolar disorder assessed by PET with 18F‐florzolotau
Authors: Kurose Shin , Takahata Keisuke , Sano Yasunori , Tagai Kenji , Ichihashi Masanori , Endo Hironobu , Hirata Kosei , Matsuoka Kiwamu , Kataoka Yuko , Kubota Manabu , Moriguchi Sho , Yamamoto Yasuharu , Oyama Asaka , Oya Masaki , Matsumoto Hideki , Kokubo Naomi , Suzuki Hisaomi , Mashima Yuki , Seki Chie , Kawamura Kazunori , Zhang Ming‐Rong , Tabuchi Hajime , Tokuda Takahiko , Onaya Mitsumoto , Mimura Masaru , Higuchi Makoto 
Published: December 2023

AbstractBackgroundNeurodegenerative pathologies, including tau depositions, have been implicated in late‐onset depression (LOD), while there is a lack of in‐vivo evidence for the neuropathological basis of late‐onset bipolar disorder (LOBD) despite postmortem findings of cerebral tau accumulations. The current study aimed to assess tau pathologies in LOBD and LOD patients positron emission tomography (PET) with 18F‐florzolotau, a radioligand for Alzheimer’s disease (AD) and non‐AD tau fibrils.MethodsWe studied LOBD and LOD patients who developed the first episode of mania or depression after age 45. Twenty‐one patients with LOBD (68.8 ± 9.6 years old; 11 females), 15 patients with LOD (73.0 ± 5.8 years old; 11 females), and 39 age‐matched healthy controls (HCs) (67.1 ± 9.1 years old; 19 females) underwent tau and amyloid PET scans with 18F‐florzolotau and 11C‐PiB, respectively. Amyloid positivity was determined by a visual read of 11C‐PiB‐PET images, and tau depositions were assessed by calculating standardized uptake value ratios (SUVRs) in 52 regions covering the cerebral grey matter and basal ganglia to the optimized reference tissue. All SUVRs were corrected for age and sex and converted to Z‐score relative to HCs. The positivity and topology of tau pathologies were determined according to the presence of a region with a Z‐score ≥ 2.0.Results
18F‐florzolotau‐PET positivity was observed in 13 LOBD (62%), 7 LOD (47%), and 11 HC (28%) subjects, whereas 4 LOBD, 4 LOD, and no HC individuals were 11C‐PiB‐PET‐positive. A significant difference in the prevalence of tau pathologies was only found between LOBD and HCs (P = 0.043, corrected for multiple comparisons). Tau topologies in the cases with 11C‐PiB‐PET‐positive AD pathologies consisted of predominant frontal (1 LOBD and 3 LODs), lateral temporal (3 LOBDs and 1 LOD), and posterior (1 LOBD) accumulations. Meanwhile, tau pathologies in 11C‐PiB‐negative cases showed predominant frontal (2 LOBDs and 1 LOD), temporal (1 LOBD and 1 LOD), posterior (4 LOBDs and 1 LOD), and basal ganglia (2 LOBDs) localizations.ConclusionOur findings suggest that a significant subset of LOBD patients harbor tau lesions linked to various AD subtypes and non‐AD tauopathies indicative of distinct early‐stage frontotemporal lobar degeneration subcategories.
Prevalence of cognitive ‘super‐ageing’ in an Australian sample using different diagnostic criteria
Authors: Powell Alice , Lam Ben C. P. , Foxe David , Close Jacqueline CT , Sachdev Perminder S. , Brodaty Henry 
Published: December 2023

AbstractBackgroundCognitive super‐ageing, which refers to a subset of older individuals who maintain high level cognitive abilities into advanced age, has been variously defined as either superior cognitive performance for age, comparable cognitive performance to younger adults and/or maintenance of cognitive abilities over time. This study aimed to investigate the prevalence of super‐ageing in Australian older adults using different published definitions, to determine the level of agreement between these definitions and to assess the relationship of super‐ageing status with daily function.MethodTwo thousand one hundred and seven adults aged between 65 and 106 years were enrolled in three longitudinal cohort studies: Sydney Memory and Ageing Study (MAS), Older Australian Twins Study (OATS) and Sydney Centenarian Study (SCS) and underwent neuropsychological testing. The prevalence of super‐ageing in these cohorts was assessed using nine different published super‐ageing definitions. Level of agreement between definitions was calculated using unweighted kappa statistics and Gwet’s first‐order agreement coefficient. Association between super‐ageing status and daily functioning was analysed using generalised linear modelling with gamma distribution.ResultPrevalence of super‐ageing varied between 1.3 and 47.8 per cent depending on the definition used with more stringent cut‐offs resulting in a lower prevalence. Agreement between different criteria varied from poor to good with predictably better agreement between definitions using similar tests and cut‐offs. Super‐ageing was associated with better functional performance for all definitions and this association was significant in most cases.ConclusionThe prevalence of super‐ageing is strongly affected by the demographic and neuropsychological testing parameters used. Greater consistency in defining super‐ageing would allow for better characterisation of this exceptional minority. So long as multiple definitions prevail, operational criteria should be explicit and determined by the specific research question.
Cognitive reserve moderates Alzheimer’s disease‐related tauopathic mechanism on cognition mediated by structural connectivity networks
Authors: Song Jeong‐Yeon , Kim Sung‐Woo , Cho Hanna , Kim Han‐Kyeol , Lyoo Chul Hyoung , Seong Joon‐Kyung 
Published: December 2023

AbstractBackgroundCognitive reserve (CR) is the capacity of an individual to maintain cognitive function despite brain damage (Stern et al., 2002). It moderates the effect of Alzheimer’s disease (AD)‐related brain damage on cognition, which is difficult to demonstrate using residual analysis. Recent research has shown a strong effect of tauopathy on the brain damage (Renaud La Joie et al., 2020), but how the CR affects this relationship is still unknown.MethodWe obtained 121 amyloid‐positive individuals, including 15 cognitive unimpaired (CU) individuals, 44 patients with mild cognitive impairment (MCI), and 58 AD. We first identified structural connectivity subnetworks where the relationships between edges’ weights (the number of streamlines) and tauopathy (global cortical tau standard uptake value ratio, standardized by the mean and standard deviation of the amyloid‐negative CU individuals) were modified by the years of education, as a proxy for cognitive reserve, using the network‐based statistics. We chose a subnetwork where its total connectivity significantly mediated the effect of the tauopathy on memory score, based on the Baron and Kenny method (Baron, Kenny et al., 1986). Through the path analysis, we verified the moderated mediation model, in which the moderating effects of education were added to the mediation model.ResultOne subnetwork whose edges were significantly affected by the tauopathy and moderation of education showed partial mediation in the tauopathic mechanism on cognition. The moderated mediation model based on the total connectivity of the subnetwork showed an appropriate model fit (CFI = 0.999, SRMR = 0.006) and a significant moderating effect on both stages of the indirect effect path of mediation when tested using the bootstrap method with 10000 resamples. The simple slope and intercept analyses implied that the highly educated individuals on the AD continuum show higher memory function than the lower educated individuals in the absence of tauopathy, but this score decreased more rapidly as tau increased.ConclusionWe conclude that education modifies the effect of tauopathy on structural connectivity as well as the effect of structural connectivity on cognition when AD‐related tauopathy affects memory score through the structural connectivity subnetwork.
The Amsterdam Approach: optimizing care and research
Authors: van der Flier Wiesje M. 
Published: December 2023

AbstractAlzheimer Center Amsterdam of Amsterdam UMC, the Netherlands, was founded in 2000. Research is embedded in the pan‐Amsterdam research institute Amsterdam Neuroscience. Alzheimer Center Amsterdam is part of the department of Neurology, and closely collaborates with many departments including Radiology & Nuclear Medicine, Clinical Chemistry, Clinical Genetics, Clinical Neurophysiology and Medical Psychology, as well as across campus for Basic Sciences. The Amsterdam Research Ecosystem furthermore involves the Industry Alliance Office, which facilitates collaborations with private partners. For conduct of clinical trials, we collaborate with Brain Research Center, an independent organization dedicated to execution of pharmaceutical trials.Alzheimer Center Amsterdam has a 15 person staff, including neurologists, epidemiologists and neuroscientists. We employ ∼100ft personnel, mostly PhD students, research assistants and postdocs, working on Alzheimer’s disease and other neurodegenerative diseases causing dementia.Our mission is to achieve personalized medicine, with a particular focus on early onset dementia. Research efforts focus on (1) finding the origin of disease, (2) diagnosis & prognosis, and (3) intervention & prevention. It is our vision that patient care and research should go in hand, to achieve the urgently needed breakthroughs. Together, all patients form the Amsterdam Dementia Cohort, to date counting over 7000 individuals.We also have a keen eye for societal outreach. All colleagues, from junior to senior, reach out to society, e.g. via lectures, blogs or (social) media. Our initiative “Alzheimersocks.nl” increases awareness, while also raising research funds. We accelerate brain research on a national level via hersenonderzoek.nl, an online platform to link Dutch citizens to brain researchers looking for participants. Hersenonderzoek.nl has been highly successful, with over 35,000 registrants, >80 studies serviced with >25.000 participants.Alzheimer Center Amsterdam is one of five Dutch Alzheimer Centers, closely working with Alzheimer Nederland. We have initiated the Dutch Memory Clinic Network, connecting the >80 Dutch memory clinics, to foster harmonization and pave the way for implementation of research results. We take the lead in (national) consortia because collaboration accelerates research. An example is the ABOARD project (www.aboard‐project.nl), which is a public‐private consortium of >30 partners, with the mission to work towards personalized medicine for AD.
Elucidating the Role of Brain Senescence and Telomere Attrition in Alzheimer’s Disease Tauopathy
Authors: Palomares Debora , Caballol Nuria Suelves , Saleki Shirine , Kienlen‐Campard Pascal 
Published: December 2023

AbstractBackgroundNeurodegenerative diseases are the most common age‐related pathologies, including Alzheimer’s disease (AD). Recent studies suggest that telomere attrition, the main trigger of cellular senescence, might contribute to brain dysfunction and neurodegeneration with age (Forero et al., 2016). Senescent brain cells have been found in AD patients (Musi et al., 2018), and studies in a transgenic mouse model of tauopathy have shown that the elimination of senescent cells led to an improvement in tau‐related neurodegeneration and cognitive decline (Bussian et al., 2018). However, little is known about the exact connection between senescent brain cells and neurodegenerative disorders on a cellular and molecular level. Here, we studied how brain senescence relates to the onset and progression of AD‐related tau pathology.MethodWe used a mouse model of senescence (TercKO), which is deficient for the RNA component of the telomerase, and presents telomere attrition and premature ageing with increasing generations (Blasco et al., 1997). We crossed it with the tauopathy mouse model Tau P301S (PS19), which carries the P301S mutant form of the human microtubule‐associated protein tau gene (MAPT), exhibiting tau pathology features observed in AD (Yoshiyama et al., 2007). By taking advantage of primary cultures, brain sections and brain extracts, and using biochemistry and molecular biology techniques, we examined the expression of tau neuropathological features in a senescent context. Furthermore, we evaluated the changes in classical and novel markers of senescence in a neurodegenerative context.ResultWe observed that telomere attrition induces several known senescence markers (i.e., senescence‐associated beta‐galactosidase or SA‐β‐gal activity, upregulation of interleukins IL‐1β and IL‐6, and cell cycle regulator p16) and this exacerbates tau phosphorylation in primary neurons and hippocampal tissue. Additionally, our results suggest that the senescent context might enhance tau‐induced neurodegeneration.ConclusionOur work indicates that senescence might be an upstream regulator of tau pathology, aggravating it and triggering tau‐related neurodegeneration. Our results further suggest that TercKO mice could be a useful animal model to study the pathological role of age‐associated brain senescence. Elucidating this process in more detail could lead to the identification of suitable intervention targets for AD treatment.
Inferring Iron Modality Interactions Using Brain Image Based Neural Networks to Predict Blood Iron Levels in UK Biobank
Authors: Sammet Joshua , Liu Qiang , Patel Raihaan , Suri Sana , Nevado‐Holgado Alejo J , Winchester Laura M 
Published: December 2023

AbstractBackgroundDisturbance of iron homeostasis in the brain is linked to cognitive impairment and neurodegenerative diseases. Interactions between changes of iron loads in the blood and changes in the brain are poorly understood. No strong and complete understanding of structural changes in the brain associated with changing values of blood measurements such as haemoglobin concentration has been established. We aimed to establish a link between changes in blood measurements and the accompanying structural changes in the brain.MethodWe analysed 4436 participants from Visit 2 with a mean age of 61.92 years (standard deviation = 7.42). T2* image derived phenotypes, age, sex and blood count to represent iron were used in a linear correlation analysis. We used age, sex, blood count, head volumes, scanning positions and differences between T1 and swMRI for correction in a linear model approach predicting swMRI voxel values. We applied linear correlation analysis and a general linear model using all extracted information. Further, we built a convolutional neural network (CNN) to compare approaches. The CNN used swMRI as input and blood values as output. The blood values were grouped based on percentiles to create classes. Attention maps were extracted from the CNN using Integrated Gradients to identify possible regions driving the decision process of the network for the correct classifications.ResultNo linear relation between blood count and brain imaging was detected in the Visit 2 participant subset we analysed. However, we achieved an accuracy of over 0.99 for predicting haemoglobin concentration values split into 3, 10 or 20 classes for our CNN model. The attention maps showed high attention in the thalamus and the parietal, occipital and temporal lobe.ConclusionWe were able to predict blood iron using MRI imaging. This suggests an association between the two measures. Furthermore, it was possible to show which brain areas were used by the CNN for decision‐making. Using such an integrated model of iron modalities may give a more complete view of iron homeostasis and the potential associations with related diseases such as dementia.