bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deletion of the adaptor protein p66ShcA prevents the apoptosis of neural stem cells in response to mitogen deprivation
Authors: Powell Andrew M , Betts Dean H , Cumming Robert C 
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) has been associated with altered hippocampal neurogenesis and the depletion of the neural stem cell (NSC) niche. NSCs rely on cues from their extracellular environment to mediate their survival and maturation. The Shc adaptor family mediates this mitogenic signaling in response to a wide range of growth factors and is necessary for embryonic neurogenesis. A member of this family, p66ShcA has been found to antagonize mitogenic signalling, however its role in neurogenesis has not been established. Moreover, the genetic ablation of p66ShcA, has a been reported to reverse cognitive decline in mouse models of AD, despite its minimal expression in mature neurons.MethodTo evaluate p66ShcA’s role in the fate of NSCs, we generated and characterized a p66ShcA‐null murine NSC line (p66KO‐NSC). The NSCs were characterized by assessing their differentiation competency and viability in response to alterations in epidermal growth factor (EGF) signalling.ResultThe p66KO‐NSCs exhibited enhanced neurogenesis in response to EGF withdrawal, relative to WT NSCs. The pharmacologic inhibition of either EGFR or ERK induced the apoptosis of the WT NSCs via the release of cytochrome C and caspase activation. Surprisingly, the inhibition of EGFR or ERK had a negligible effect on the survival of the p66KO‐NPCs and instead induced their neuronal differentiation.Conclusionp66ShcA mediates NSC apoptosis in response to the loss of mitogenic cues. The deletion of p66ShcA increases neurogenesis by facilitating the survival of NSCs during their neuronal differentiation.
A novel humanized Tau‐FAD mice represent a robust model for studying AD‐related dysfunction
Authors: Sambamurti Kumar , Cromwell Ian , Pappolla Miguel A , Kanthasamy Anumantha , Padhi Piyush , Lahiri Debomoy K. , Greig Nigel H , Sarkar Sumit , Padmaraju Vasudevaraju 
Published: December 2023

AbstractBackgroundFamilial AD (FAD) mice expressing mutant forms of the Amyloid β protein (Aβ) precursor (APP) and presenilin‐1 (PS1) have been key models for AD research. While other studies combined FAD and the Tau protein, none, except 3xTgAD, have been made freely available or characterized well. As APP and Tau are linked in 3xTgAD mice, one cannot evaluate their contribution. This study combined the popular hTau strain lacking mouse Mapt and expressed human wild‐type MAPT with FAD.MethodWe generated HTAP by crossing hTau mice in C57BL6/J (JAX #005491) with FAD mutant APP‐PS1 (MMRRC #034833‐JAX) and HTAP2 with 5xFAD (#032882‐JAX). While hTau hyperphosphorylates Tau at 3 mo, the FAD models deposit Aβ after 5 mo. We compared mouse spatial memory with either a radial arm water maze or a Barnes maze. We also compared the levels of norepinephrine in the hippocampus, cortex, and striatum of HTAP2 with the parental C57BL6/J mice by HPLC analysisResultHTAP and HTAP2 mice deposit plaques similar to parental FAD mice and hTau hyperphosphorylated Tau. The combined HTAP mice showed hyperphosphorylated Tau, but the structures appeared distorted. We noted that after 7 months of age, HTAP mice performed poorly in the radial arm water maze compared to wild‐type, FAD, and hTau mice. We observed a similar deficit in HTAP2 in the Barnes Maze. HTAP2 mice showed a significant drop in norepinephrine in all evaluated brain regions, reminiscent of early AD‐related changes.ConclusionHTAP/2 mice have exacerbated behavioral deficits, suggesting that it is a more robust model for studying AD‐related dysfunction. However, these mice still perform well in activities of daily living, such as grooming and feeding. Such novel tau mice, which contain the human MAPT gene, would accelerate our ongoing studies on human microRNAs that target human 3'UTR MAPT mRNA without interference from the host Mapt gene. We propose that this system may better represent the behavioral deficits in AD.
Temporal evaluation of imaging and biofluid biomarkers, spatial neuropathology and glial function in the TgF344‐AD rat model
Authors: da Rocha Andreia Silva , Soares Carolina , Machado Luiza Santos , Ferreira Pamela C.L. , Bellaver Bruna , Kunach Peter , Kang Min Su , Souza Diogo O. , Rosa‐Neto Pedro , Green Kim N , Zimmer Eduardo R. ,   MODEL AD
Published: December 2023

AbstractBackgroundThe development and characterization of Alzheimer’s disease (AD) animal models is particularly important for the investigation of pathophysiological mechanisms and drug development. The TgF344‐AD rat is a model harboring human APP/PS1 mutations with comprehensive presentation, including age‐dependent development of amyloid‐β (Aβ) plaques, neuronal loss and tau deposits, but not yet fully characterized. In light of this, we evaluated imaging and biofluid biomarkers, spatial neuropathology and glial function in these animals across multiple key ages.MethodsTgF344‐AD rats and wild‐type littermates were longitudinally evaluated at 3, 6, 9, 12 and 16‐18 months of age. Rats underwent [18F]FDG‐microPET scans and CSF samplings. CSF glial and immune markers (GFAP, S100B, TREM2, IL‐6, TNF‐α, IL‐10) were measured by multiplex immunoassay. A cross‐sectional cohort was used to measure cortical glutamate uptake (ex‐vivo slices) and follow the spatial distribution of Aβ plaques (6E10 antibody) at the same time points.ResultsAt 3, 6, 12 and 16‐18mo, no changes in [18F]FDG metabolism were observed. At 9mo, we identified a significant cortical hypermetabolism in the TgF344‐AD rats. CSF GFAP levels were elevated at 6 and 9 months of age, while CSF S100B was decreased at 9mo. The CSF inflammatory markers IL‐6, TNF‐α and IL‐10 were elevated at 16‐18mo. Additionally, the glutamate uptake was increased in the cortex at 9mo and 12mo, and in the hippocampus at 12mo. TREM2 was not altered in any of the ages evaluated. The (Aβ) plaques deposition starts at 6mo in the posterior temporal cortices and hippocampus and spreads slowly to frontal brain regions, reaching a plateau around 16mo.ConclusionThis work shows that the TgF344‐AD rat model recapitulates the early and transient glucose hypermetabolism seen in AD patients. Our results also indicate an associated early astrocyte response in these animals, with changes in relevant astrocyte biomarkers and function (glutamate uptake). Due to the critical role of astrocytes in brain glucose handling, these findings suggest that astrocyte reactivity could be driving glucose hypermetabolism. In contrast, the neuroinflammatory biomarkers changes identified suggest a strong neuroinflammatory response only at later stages in this rat model, however, further investigations are necessary to better elucidate these findings.
Neighborhood disadvantage is associated with changes in cerebrovascular function among older adults over a 9 year follow‐up period
Authors: Cambronero Francis E. , Zhang Panpan , Gogniat Marissa A. , Liu Dandan , Vytla S. Soumya , Ratangee Brina A. , Roby Dominic V. , Pechman Kimberly R. , Verde Audrey R. , Davis L. Taylor , Landman Bennett A. , Gifford Katherine A. , Hohman Timothy J. , Blennow Kaj , Zetterberg Henrik , Jefferson Angela L. 
Published: December 2023

AbstractBackgroundStressful social environments exert a strong influence on unhealthy aging, both in greater magnitude and independent of individual socioeconomic and lifestyle factors. Neighborhood disadvantage specifically has been linked to accelerated biological aging, cognitive decline, and core Alzheimer’s disease (AD) neuropathology, but little is known about whether neighborhood disadvantage contributes to cerebrovascular dysfunction commonly observed in aging and AD. We examine whether neighborhood disadvantage relates to changes in cerebrovascular outcomes over time, including blood‐brain barrier (BBB) integrity, cerebral blood flow (CBF), and small vessel disease (SVD) biomarkers.MethodsVanderbilt Memory and Aging Project participants (n = 296, 73±7 years, 40% female) underwent fasting blood and cerebrospinal fluid (CSF) acquisition serially over a 9‐year follow‐up period (mean follow‐up = 5.5 years). Area Deprivation Index (ADI), representing neighborhood disadvantage, was quantified at baseline based on 17 components [e.g., housing, income, education, and household characteristics (Kind & Buckingham, 2018)]. BBB markers (MMP‐2, MMP‐3, MMP‐9, TIMP‐1, TIMP‐2, PDGFRβ) were quantified from CSF and CSF/plasma albumin ratio was quantified from both CSF and plasma. 3T multimodal MRI images were used to quantify grey matter CBF and SVD markers, including white matter hyperintensities (WMHs), perivascular spaces (PVS), and lacunes. Linear mixed effects regression models related time x ADI to longitudinal BBB, CBF, and SVD outcomes adjusting for age, sex, race/ethnicity, education, cognitive status, Framingham Stroke Risk Profile (minus age), apolipoprotein ε4 status, and follow‐up time. CBF models additionally adjusted for corresponding grey matter volume while SVD models adjusted for T1‐weighted intracranial volume.ResultsBaseline ADI related to increased MMP‐9 (β = 0.03, p‐value = 0.01) and decreased PDGFRβ (β = ‐0.1407, p‐value<0.05) over time but unrelated to longitudinal changes in CBF (p‐values>0.35), SVD (p‐values>0.36), or other BBB outcomes (p‐values>0.07).ConclusionsNeighborhood socioeconomic disadvantage relates to changes in BBB integrity among older adults over time, particularly molecular markers of barrier disruption and pericyte damage. Findings support the hypothesis that adverse environmental conditions, including low quality housing and community‐wide resource constraints, may contribute to early‐stage cerebrovascular dysfunction beyond individual socioeconomic and lifestyle factors.FundingHHMI James H. Gilliam Fellowship for Advanced Study; IIRG‐08‐88733; R01‐AG034962; R01‐AG056534; K24‐AG046373; P20‐AG068
Prompting cognitive assistive technology for multistep tasks in dementia homecare: Testing of mode and sequencing options
Authors: Roberts Emily , Fan Guoliang 
Published: December 2023

AbstractFor people living with dementia, information‐processing capabilities and previously acquired knowledge is generally limited. Daily tasks such as making coffee or teeth brushing may become too difficult to complete independently. People with normal cognitive functioning learn about the environment as they move through it with spatial information obtained sequentially, requiring mental activity to process this successive input into a comprehensive understanding of a task. Without this ability, individuals with dementia in many cases then rely on repetitive cuing for tasks from their family member or caregiver. The approach for this project was the evaluation of task prompting for a wearable cognitive assistive technology for support in cueing on for multi‐step home tasks. Choosing meaningful tasks, and breaking them down in a way that a caregiver would usually provide prompting support is not trivial. The physical or environmental context of the task can also affect the flow of the task, and the personality of the person carrying out the task can influence how methodically the prompts are followed. The testing took place in a lab setting set up to represent a one‐bedroom apartment. A sample of older adults 65+ took part in a series of protocols for eight multi‐step tasks and for each task four delivery modes options (written text, audio, still photo, video) and four sequencing modes (auto‐generated, self‐request, one‐time, step by step) which included: kitchen‐ loading the dishwasher, setting the table and making coffee, bedroom‐ making the bed, folding clothes, bathroom‐ brushing teeth, hand washing and face washing. This pre‐testing of system components was performed in order to reduce marginal risks, increase effectiveness, and maximize benefits for the end‐user population of individuals with dementia who will test the device in future projects and the outcomes from this research will ultimately enable the mode and sequencing of task prompting for this populations' frequently changing needs.
Deep Learning patterns of Aβ accumulation in Alzheimer’s Disease
Authors: Srinivasan Dhivya , Nasrallah Ilya M. , Yang Zhijian , Bilgel Murat , Wen Junhao , Erus Guray , Cui Yuhan , Mamourian Elizabeth , Sotiras Aristeidis , Betthauser Tobey J , Resnick Susan M. , Tosun Duygu , Albert Marilyn S. , Davatzikos Christos ,   for the Alzheimer’s Disease Neuroimaging Initiative,the iSTAGING consortium, & the Preclinical AD consortium
Published: December 2023

AbstractBackgroundAccumulation of amyloid (Aß) plaques is an early pathologic change of Alzheimer’s Disease (AD). However, the mechanisms and pathways by which amyloid spreads across the cerebrum are not fully understood. Deriving distinct dimensions of amyloid deposition and their associations with biomedical factors could be useful to understand how amyloid propagates. In this analysis, we identified two distinct subtypes of progression based on spatiotemporal variations using a recently developed data‐driven, deep learning clustering method called Surreal‐GAN1.MethodWe used data from 482 A+ and 801 A‐ subjects with 18F‐florbetapir PET from the Alzheimer’s Disease Neuroimaging Initiative (ADNI; N = 832) and 11C‐PiB from the Preclinical AD consortium (PAC; N = 451). Standardized uptake value ratio (SUVR) maps (cerebellar GM reference) were transformed to reference space. We derived amyloid status using Gaussian mixture modelling of mean total cortical SUVR for each of 4 sites. We then applied non‐negative matrix factorization2 on the SUVR maps to identify data‐driven common patterns of deposition across the sample. Next, we applied Surreal‐GAN on a total of 1283 subjects to determine the amyloid spatiotemporal subtypes. Correlations with clinical and cognitive variables were evaluated.ResultsParticipants were 30%/22% female and had mean age 74.9 (±7.4)/ 67.9(±9.1) years for ADNI and PAC, respectively. We identified 24 components from NMF (Fig 1A) after excluding 6 as non‐target features. Surreal‐GAN showed optimal agreement indices for two patterns. While both patterns shared involvement of posterior cingulate/precuneus and inferior frontal cortex, pattern r1 shows relatively more occipital deposition and pattern r2 shows more frontal deposition (Fig 1B), as seen when comparing strongly r1 vs strongly r2 participants using voxel‐based morphometry (Fig 2). Both were associated with worse global cognitive function and worsening neurodegeneration (Table 1). r1 correlates with white matter hyperintensity volume, a measure of cerebrovascular disease, while pattern r2 is associated with the presence of APOE e4 alleles.ConclusionEmploying a data‐driven deep learning‐based approach, we derived more than one dissociable pattern of amyloid deposition, potentially differently influenced by vascular disease (r1/occipital) and genetics (r1/frontal). These findings could inform identification of subgroups of individuals who may or may not be responsive to particular clinical intervention.
Height and intracranial volume as protective factors against Alzheimer’s disease: a Mendelian randomization analysis
Authors: Taylor Jack C , Brenowitz Willa D , Yaffe Kristine , Andrews Shea J 
Published: December 2023

AbstractBackgroundMeta analyses have identified height as a risk factor inversely associated with Alzheimer’s disease. Height as a protective factor may be reflective of overlapping genetics with intracranial volume (ICV), which has also been shown to be inversely associated with AD, or height may reflect early life influences such as nutritional intake. Here we use Mendelian randomization (MR) analysis to further investigate these causal relationships.MethodTwo sample MR was used to obtain causal estimates of height and ICV on AD, using GWAS summary statistics from the GIANT consortium (n = 5,380,080), meta analyzed summary statistics from studies measuring ICV, brain volume, and head circumference, and the International Genomics of Alzheimer’s Project (n = 94,437). Independent (r2<0.001, 10mb window) genome‐wide significant single nucleotide polymorphisms (p<5×10−8) were included as genetic instruments (n = 960). MR methods included inverse variance weighted (IVW), weighted median, weighted mode, and MR Egger. Cochran’s Q test was used to test for heterogeneity; the MR‐Egger intercept for pleiotropy; and Radial MR to identify individual variants that were outliers.ResultGenetically predicted height was associated with a reduced risk of AD (IVW logOR [95% CI]: ‐0.11 [‐0.16, ‐0.06], p = 7.3e−5). There was, however, evidence of heterogeneity and pleiotropy. After outlier removal (n = 1), height remained significantly associated with reduced risk of AD (IVW OR [95% CI]: ‐0.12 [‐0.18, ‐0.07], p = 1.49e−5), with sensitivity analyses showing the same direction of effect. Genetically predicted ICV was significantly associated with AD (IVW logOR [95% CI]: 0.16 [0.003, 0.31], p = 0.046), though tests of heterogeneity and pleiotropy were significant while sensitivity analyses were not. After outlier removal (n = 1), ICV was no longer significantly associated with reduced risk of AD (IVW logOR [95% CI]: 0.13 [‐0.03, 0.30], p = 0.11).ConclusionGenetically predicted height was protective against AD, while ICV had a suggestive protective causal effect. Together, these findings may imply a link between these phenotypes and AD. Further research using multivariate MR is needed to fully evaluate the potential mediating role of ICV in the protective effect of height on AD, as well as to explore other potential mediators such as nutritional intake.
Plasma biomarkers of Alzheimer’s Disease associate with gray matter volume and cerebral glucose metabolism in older adults with Mild Cognitive Impairment
Authors: Green Zachary D. , Morris Jill K , Lepping Rebecca , Vidoni Eric , Honea Robyn A 
Published: December 2023

AbstractBackgroundAlzheimer’s Disease (AD) pathology in vivo has traditionally been measured in the cerebrospinal fluid or by positron emission tomography (PET). Developments in measuring plasma biomarkers present less invasive, cheaper ways to quantify AD pathology. However, the associations between these new plasma markers and neuroimaging markers of AD are not fully understood. We examined the relationship between plasma biomarkers of AD and measures of whole brain gray matter volume (GMV) and cerebral glucose metabolism in both cognitively unimpaired (n = 83) and impaired (n = 30) individuals.MethodWe collected data from individuals within the University of Kansas Alzheimer’s Disease Research Center’s (KU ADRC) Clinical Cohort who underwent MRI and FDG‐PET scans and had available plasma data. Participants included 64 females, and age of the neuroimaging cohort was 76.0 ± 6. Plasma biomarkers were measured in EDTA plasma using the Quanterix Simoa® HD‐X, and included NfL, Aβ42, Aβ40, GFAP, and p‐tau181. GMV was estimated using MPRAGE MRI processed in FreeSurfer. Cerebral glucose metabolism was estimated from FDG‐PET data using SUVR values calculated through SPM12, with standardization to pons. We used linear regression to examine the relationship between each biomarker to whole brain GMV and glucose metabolism. ANCOVA was used to evaluate differences in the plasma biomarkers between diagnosis groups. Analyses included sex and age as covariates.ResultWhole brain GMV (F = 8.4, p = .004) and cerebral glucose metabolism (F = 10.9, p = .002) differed between diagnostic groups. In the linear regression, we observed an interaction effect between cognitive diagnosis and each biomarker, such that the slopes of regressions between each plasma biomarker and neuroimaging marker was significant in the impaired group, but not significant in the unimpaired. In the impaired group, the strongest association observed was between plasma NFL and whole brain GMV (β = ‐1.4, p = .020) and cerebral glucose metabolism (β = ‐1.7, p = .014). Additionally, all plasma biomarkers were found to differ between diagnostic groups.ConclusionWe show that plasma markers of AD pathology associate with whole brain GMV and cerebral glucose metabolism in individuals with cognitive impairment. Further work will examine the relationship between biomarkers and regional neuroimaging measures
Early‐onset Lewy body dementia associated with PRKN gene mutation
Authors: Singh Neeraj 
Published: December 2023

AbstractBackgroundA 42‐year‐old woman presented with a 1‐year history of head tremors, visual hallucinations, and concentration difficulty. On initial evaluation by a neurologist, she was told that her symptoms were due to anxiety, and no further workup was done. After seeking a second opinion, further workup was pursued.MethodThe patient underwent cognitive testing, with Montreal Cognitive Assessment revealing a normal score of 29/30. MRI Brain revealed a midline frontal meningioma without mass effect. Routine EEG revealed no evidence of seizure tendency. Due to persistent head tremors and visual hallucinations, further testing was considered.ResultPET‐FDG CT Brain revealed bilateral parietotemporal and occipital hypometabolism with preserved cingulate gyrus metabolism, consistent with Lewy body dementia. Another PET‐FDG MRI Brain performed 13 months later revealed a similar hypometabolism pattern. Genetic testing revealed a heterozygous mutation for the PRKN gene.ConclusionIn this case, a patient showing clinical signs of a potential neurodegenerative disorder was initially dismissed as having anxiety, but further workup with appropriate neurological studies revealed a genetic basis for early‐onset Lewy body dementia. This case demonstrates a unique association with the PRKN gene mutation with Lewy body dementia even though it is typically associated with Parkinson’s disease. This case also highlights the underrepresentation of young patients with neurodegenerative diseases, which is reinforced by biases against pursuing appropriate workup for young patients showing relevant clinical signs.