bluuebunny/crossref_metadata_2025_split huggingface dataset:
CSF SNAP‐25 and Neuronal pentraxin 2 associations with cognitive decline in the presence of CSF ptau181/Aβ42 in an at‐risk cohort
Authors: Planalp Beth M. , Langhough Rebecca E. , Valentino De'Karlos , Ealy Denise , Quijano‐Rubio Clara , Kollmorgen Gwendlyn , Blennow Kaj , Zetterberg Henrik , Jonaitis Erin M. , Johnson Sterling C. 
Published: January 2025

AbstractBackgroundAlzheimer's disease (AD) is identified by the accumulation of amyloid β (Aβ) and tau proteins in the brain. The NeuroToolKit offers automated cerebrospinal fluid (CSF) immunoassays of core AD biomarkers and biomarkers of neurodegeneration and synaptic function, including neurofilament light (NfL), SNAP‐25, and neuronal pentraxin 2 (NPTX2). This work explores whether these three markers predict pre‐dementia cognitive decline synergistically with or after accounting for CSF ptau181/Aβ42.MethodParticipants included N=360 baseline dementia‐free adults (45—85 years) with complete CSF biomarker and cognitive data from the Wisconsin Registry for Alzheimer’s Prevention and the Wisconsin Alzheimer’s Disease Research Center (on‐going, longitudinal preclinical AD studies). We assessed CSF biomarkers using the NeuroToolKit (NTK), a panel of robust prototype biomarker assays (Roche Diagnostics International, Switzerland). Mixed models examined separately whether NfL, SNAP‐25, or NPTX2 biomarkers further modified Preclinical Alzheimer’s Cognitive Composite (PACC3) trajectories beyond Aβ+ effects. Biomarker*ptau181/Aβ42*age (linear and quadratic) interactions were examined, and non‐significant higher order interactions removed sequentially before interpreting NfL, SNAP‐25, and NPTX2 effects.ResultSample characteristics are shown in Table 1, and show significant correlations among all biomarker pair except NPTX2 and ptau181/Aβ42. Table 2 and Figure 1 depict PACC3 model outputs and biomarker associations; Aβ+ performed worse or declined faster than Aβ‐ across all models. Compared to a base “amyloid‐only” model, NfL, SNAP‐25, and NPTX2 “biomarker” models showed an improved model fit (Table 2). The best‐fitting model included the NPTX2* ptau181/Aβ42*age2 interaction (Table 2) which showed greatest average PACC3 decline in those with higher amyloid and lower NPTX2 (Figure 1d). SNAP‐25 also related to cognition such that individuals with lower amyloid and higher SNAP‐25 had the highest PACC3 average (interactions with age were non‐significant), and individuals with higher NfL showed steeper PACC3 decline than those with lower NfL.ConclusionIn addition to known effects of NfL, recently developed NTK immunoassays for SNAP‐25 and NPTX2 accounted for additional variability on AD‐related pre‐dementia PACC3 performance. Future work may identify clinically useful cutpoints for SNAP‐25 and NPTX2 and explore relations with other biomarkers common to neurodegeneration and AD. We will also examine associations with other outcomes including clinical progression of AD.
A diffusion kurtosis MRI signature of subjective cognitive decline
Authors: Flaherty Ryn , Sui Yu Veronica , Li Mu , Ardelean Ana , Rusinek Henry , Masurkar Arjun V. , Lazar Mariana 
Published: January 2025

AbstractBackgroundDiffusion weighted imaging (DWI) of brain white matter is better at predicting future cognitive decline and medial temporal lobe atrophy than cerebrospinal fluid biomarkers in subjective cognitive decline (SCD)1. However, few studies have investigated gray matter DWI in SCD, despite the importance of regional gray matter changes as a biomarker for Alzheimer’s Disease and related dementias.Method316 cognitively normal participants from Cam‐CAN2 (123 SCD) older than 55 were included in the analysis. Participants were placed in the SCD group if they endorsed problems with their memory. Imaging data was collected on a 3T Siemens Trio scanner2. Diffusion imaging included 0, 1000 and 2000 s/mm2 b‐values and 30 gradient directions, and were processed using MrTrix3, PyDesigner, and AMICO to apply diffusion tensor (DTI), diffusion kurtosis (DKI), and neurite orientation density and dispersion (NODDI) models. FreeSurfer with T1w and T2w images was used to segment subcortical and cortical regions (Figure 1B&C), then calculate regional volume and cortical thickness. Segmentations were also registered to diffusion images to generate regional averages of the diffusion metrics. Uncorrected p<0.05 according to Wilcoxon tests were considered significant.ResultThe metric with the most regional group differences was kurtosis fractional anisotropy (KFA) from DKI, an indicator of structural complexity. KFA was significantly lower in SCD in 17 of 84 gray matter regions, including hippocampus (Figure 2‐3B). DTI showed reduced fractional anisotropy (Figure 2‐3C) and increased mean diffusivity (Figure 2‐3D) in SCD, but for fewer regions than KFA. NODDI showed increased free water (Figure 2‐3E), increased orientation dispersion (Figure 2‐3F), and increased neurite density (Figure 3G) in SCD. Volume and thickness were higher in SCD in 5 regions, but lower in 3 regions (Figure 2‐3A). Only KFA showed group differences in hippocampus.ConclusionKFA was more sensitive to SCD and more consistent than regional gray matter volume, cortical thickness, and all other diffusion metrics. This may indicate KFA is a biomarker signature of SCD across the whole brain gray matter.Selnes P, Aarsland D, Bjornerud A, et al. J Alzheimers Dis. 2013;33(3):723‐36.Shafto MA, Tyler LK, Dixon M, et al. BMC Neurol. 2014;14(1):1‐25.
Interplay of inflammatory, vascular, and Alzheimer’s disease biomarkers in cognitively unimpaired older adults
Authors: Rizvi Batool , Adams Jenna N. , Bamford Alison , Sathishkumar Mithra , Kim Soyun , McMillan Liv , Brickman Adam M. , Mapstone Mark , Thomas Elizabeth A. , Yassa Michael A. 
Published: January 2025

AbstractBackgroundNeuroinflammatory processes, assessed by cytokines such as interleukins, are implicated in vascular disease and amyloid‐β (Aβ) burden. White matter hyperintensities (WMH), markers of small vessel cerebrovascular disease, are associated with memory impairment and Alzheimer’s disease (AD)‐related cortical atrophy. Here, we used structural equation modeling (SEM) to test whether inflammatory markers are related to markers of AD pathology and neurodegeneration through their impact on WMH.MethodA sample of 118 older adults without dementia (mean age (SD) = 70.8 (6.22) years, age range: 59.8‐86.4 years, 77 (65%) women) were included. Regional WMH volumes were derived from T2‐FLAIR images using ANTs, parcellated by a vascular territory atlas. Aβ was assessed with 18F‐florbetapir‐PET, with SUVR was extracted from composite ROIs reflecting early, intermediate, and late regions of deposition. Medial temporal lobe (MTL) volume/thickness measures including averaged bilateral hippocampal volumes, entorhinal cortex thickness, and parahippocampal cortex thickness, were derived using FreeSurfer v.6.0. A set of inflammatory markers (IL‐2, IL‐4. IL‐6, IL‐8, IL‐10, IL‐12, IL‐13) and phosphorylated tau (P‐tau217, P‐tau181) were measured in plasma. We tested the relationships among inflammation, amyloid‐β, WMH, P‐tau, and MTL gray matter using structural equation modeling (SEM) and confirmatory factory analysis (CFA).ResultModel fit indices demonstrated acceptable model fit: χ2 (84) = 104.328, p = 0.066; comparative fit index (CFI) = 0.982; Tucker‐Lewis index (TLI) = 0.977; Root Mean Squared Error of Approximation (RMSEA) = 0.070 (90% CI: 0.021, 0.104); and Standardized Root Mean Square Residual (SRMR) = 0.107. Inflammation was associated with WMH (b=0.430, β=0.403, p=0.031), but not with amyloid‐β burden (b=0.099, β=0.099, p=0.549). Only amyloid‐β was related to phosphorylated tau (b=0.535, β=0.462, p<0.001). Both WMH and phosphorylated tau burden were associated with reduced MTL gray matter (WMH: b=‐0.228, β=‐0.231, p=0.049; P‐tau: b=‐0.233, β=‐0.251, p=0.031).ConclusionOur study suggests that inflammation promotes AD‐related neurodegeneration through its impact on vascular disease whereas amyloid appears to operate through tau in its effect on atrophy. The study highlights the possible ways in which inflammatory and vascular pathways converge with amyloid pathways to drive AD‐related neurodegeneration.
Longitudinal assessment of neuronal calcium, glutamate, and hemodynamic changes in aging APP‐PS1 mice
Authors: Cover Christopher G , Peretin Jenna M , Poplawsky Alexander , Vazquez Alberto L 
Published: January 2025

AbstractBackgroundPreclinical Alzheimer’s disease research has gained traction as a potential point of intervention, though it is relatively unknown how early stages of the disease impact cortical health. The following study utilizes optical imaging methods (Figure 1) to characterize changes in neuronal, glutamate, and hemodynamic activities in a preclinical amyloidosis mouse model of the disease.MethodFive (n = 5; 2 females & 3 males) APPswe/PS1dE9 x Thy1‐jRGECO1a double transgenic mice were breed for whole‐brain fluorescent imaging of neuronal activity. At two months of age, mice were injected with a fluorescent glutamate sensor in the right barrel cortex (BC), primary motor cortex (PMC) and retrosplenial cortex (RSP), then implanted with a 5mm cranial window. From 3‐12 months of age, mice were imaged monthly in the awake state using both wide‐field optical and two‐photon microscopy (2PM) to investigate both systems‐level and cellular/synaptic activities, respectively. Imaging sessions consisted of spontaneous resting‐state activity and evoked responses from a single, repeated whisker puff to the left whisker pad. Nonparametric statistical analysis was performed due to the small sample size.ResultPeak amplitudes progressively declined from baseline levels (i.e., 3 months of age) at the systems level in the aging mice and reached significance by 10 months of age (p < 0.05; Figure 2B). Additionally, a trend towards excitatory imbalances were seen from 5‐7 months of age. Interestingly, impairments in glutamate clearance trended towards significance only at 6 months of age, but not at other times. See Figure 3 for example 2PM in response to a single whisker puff.ConclusionLongitudinal decline in stimulus‐evoked neuronal calcium, glutamate, and hemodynamic activities were seen in young, aging AD mice. Future directions will consist of 1) increasing the sample size, 2) analysis of resting‐state data at the systems and cellular levels, and 3) analysis of 2PM data with the whisker stimulus.
Impaired Complex Activities of Daily Living Correlated with Altered EEG Oscillations in the Dementia Spectrum Disorder
Authors: Chen Poyu , Wu Chin‐Yi , Huang Yu‐hua , Hsu Jung‐Lung , Chuang I‐Ching , Sikkes Sietske A.M 
Published: January 2025

AbstractBackgroundLiterature on biomarker studies suggests that pathological changes begin approximately 10 to 20 years before the first cognitive symptom appears in dementia populations. It is an emerging era for developing methods to detect the early signs of progressive cognitive decline. Recently, the instrumental activity of living (IADL) capacity has been regarded as a functional biomarker to predict the progression from MCI to dementia. EEG, combined with cognitive performance, such as IADL performance, might be able to provide a more sophisticated biomarker candidate. Thus, the present study aimed to adopt EEG combined with the Amsterdam Instrument of Daily Living Questionnaire‐Short Version Traditional Chinese (A‐IADL‐SQ‐TC) to early detect cognitive decline in the preclinical stages.MethodWe recruited 76 participants, including those with normal cognition (n=25), SCD (n=21), MCI (n=17), and dementia (n=13) in both community and memory clinics. All of the participants were measured with the Mini‐Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and eye‐closed EEG recording. Furthermore, all proxies of the participants filled out the A‐IADL‐SQ‐TC.ResultIndividuals with MCI and dementia exhibited larger relative power in the low‐frequency bands, specifically the delta (0.5‐4 Hz) and theta bands (4‐8 Hz), and smaller relative power in the high‐frequency band, specifically the alpha (8‐13 Hz) and beta bands (13‐20Hz). These findings are consistent with previous research. Additionally, we discovered that the A‐IDAL‐Q‐SV‐TC T‐score negatively correlated with theta relative power across the scalp (r = ‐.55 to ‐.62, all p**<.001), while positively correlated with beta relative power across the scalp (r =.35 to ‐.46, all p<**.001). Regarding the global theta relative power, the one‐way ANOVA showed significant group differences, F (3,72) = 19.768, p<.001. However, the post‐hoc effect revealed only the dementia group showed a significantly higher relative power than the other groups.ConclusionWe have discovered that the resting‐state EEG oscillations exhibited different patterns across different stages of dementia. Furthermore, A‐IADL‐SQ‐TC was associated with the spectral intensity of the resting‐state EEG oscillations, and together they provide more sensitive indicators for early detection.
Direct comparisons of the associations between the tau PET tracers [18F]Flortaucipir and [18F]MK6240 with tests of general cognitive performance ‐ The HEAD study
Authors: Amaral Livia , Povala Guilherme , Bellaver Bruna , Bauer‐Negrini Guilherme , Lussier Firoza Z , Ferreira Pamela C.L. , Cehula Juli , Tudorascu Dana , Jagust William J. , Klunk William E , Lowe Val J. , Oh Hwamee , soleimani‐meigooni David N. , Pascual Belen , Gordon Brian A. , Rosa‐Neto Pedro , Baker Suzanne L. , Pascoal Tharick A. 
Published: January 2025

AbstractBackgroundTau PET tracers are employed to measure the accumulation of tau in vivo in the brain. Each tau tracer possesses unique characteristics, including binding affinity, sensitivity, and specificity to tau aggregates. This study leverages the HEAD study dataset, which is currently performing baseline tau PET tracers and conducting multiple clinical and cognitive assessments. The objective of this study is to elucidate the relationship between tau PET tracers [18F]Flortaucipir and [18F]MK6240 and commonly used tests of general cognitive performance.MethodsWe assessed 170 individuals (107 cognitively unimpaired, and 63 cognitively impaired) with available PET [18F]Flortaucipir [18F]MK6240 and cognitive assessments (MoCA, MMSE, and CDR‐SB). We calculated tau PET SUVR for [18F]Flortaucipir and [18F]MK6240 using the inferior cerebellar grey matter as a reference. Pearson correlations were performed between SUVR values for each Braak region and MoCA, MMSE, and CDR‐SB. In addition, linear regression models accounting for age, sex, years of education, HEAD site, and diagnosis were used to estimate the relationships. The Akaike Information Criterion (AIC) was utilized to evaluate the models, with smaller AIC values signifying better performance.ResultsPerson correlation coefficients (r), which were calculated without considering any covariates, demonstrated higher numerical values between [18F]MK6240 and the scores of MoCA, MMSE, and CDR‐SB across the Braak regions (Figure 1). Similarly, when we performed linear regressions that accounted for relevant covariates, we found that the [18F]MK6240 SUVR in Braak 1 and Braak 4 regions exhibited a stronger association with cognitive tests than in other Braak regions or any region with [18F]Flortaucipir SUVR (Figure 2).ConclusionsBoth [18F]Flortaucipir and [18F]MK6240 SUVR demonstrated a robust association with tests of general cognitive performance commonly used in AD research and clinical practice. Generally, Braak regions 1 and 4 exhibited a stronger association with general cognitive performance using all tests, whereas Braak regions 5‐6 showed the weakest association.
Clinical use of tau PET in Aβ PET positive individuals: a case series
Authors: Machado Vitor Hugo , Povala Guilherme , Bellaver Bruna , Ferreira Pamela C.L. , Amaral Livia , Bauer‐Negrini Guilherme , Lussier Firoza Z , Tudorascu Dana , Jagust William J. , Klunk William E , Lowe Val J. , soleimani‐meigooni David N. , Oh Hwamee , Pascual Belen , Gordon Brian A. , Rosa‐Neto Pedro , Baker Suzanne L. , Pascoal Tharick A. 
Published: January 2025

AbstractBackgroundIdentifying individuals’ levels of tau PET pathology could prove to be beneficial in clinical settings, given that emerging therapies aimed reducing Aβ seem to be most effective in these individuals. Here, we present the cases of four patients who visited the memory clinic at the University of Pittsburgh Medical Center between June and December 2023 and underwent both Aβ and tau‐PET scans.MethodThese individuals had standard clinical and cognitive outcomes, typical blood tests order in patients with memory impairment, MRI, and, as part of the HEAD study, PET PIB Aβ and two tau PET tracers (MK6240 and Flortaucipir).ResultAll patients presented a primary complaint of progressive memory decline. The results of their blood count, metabolic panel, TSH, and vitamin B12 tests were unremarkable. Patient 1 had a normal MRI, while Patients 2‐4 exhibited mild ischemic changes (Table 1). All patients tested positive for amyloid PET, supporting the diagnosis of AD. However, their tau PET results varied. Patients 1 (MOCA = 6) and 3 (MOCA =19), who were demented with impaired Instrumental Activities of Daily Living (IADL), tested positive for tau PET with Braak stages V‐VI using both tau PET tracers. Conversely, the mild cognitive impairment (MCI) Patients 2 (MOCA = 19) and 5 (MOCA = 29, neuropsych evaluation indicating MCI), who exhibited low tau levels, tested positive for MK6240 but negative for FTP.ConclusionAll four patients exhibited symptoms and signs consistent with typical amnestic AD presentation, which were confirmed using Aβ PET. Aβ PET presented a similar pattern across all individuals (Figure 1). Tau PET demonstrated greater variability, with lower levels in less cognitively impaired patients. Although tau PET can potentially be useful in identifying individuals in the earliest stages that would benefit from Aβ‐lowering therapies, this small series did not exclude that a low MOCA score combined with Aβ PET could achieve a similar outcome. Larger samples in real‐world clinical contexts are necessary to identify individuals with discrepancies between tau PET uptake and cognitive tests. This would reinforce the need for tau PET markers as complementary tests, singularly capable of identifying individuals across various biological stages to indicate therapies in clinical practice.
Will a Culturally Adapted Training Material for Caregivers Improve Dementia Care in Ghana?
Authors: Yalley Sally , Manu Kwaku Sarfo , Romero‐Ortuno Roman 
Published: January 2025

AbstractThe World Health Organization (WHO) emphasizes the need to provide support to caregivers of people living with dementia, as one of seven action areas. This is especially crucial in Ghana, where, similar to other Lower Middle‐Income Countries (LMICs), the majority of people with dementia reside in the community and are cared for by informal caregivers, often family members. These caregivers usually do not have any training in dementia care and may have limited understanding of the disease and its potential symptoms. This increases the physical and psychological burden on caregivers, highlighting the urgent need for education and training of informal caregivers in Ghana (Ayisi‐Boateng et al. 2022).The Alzheimer’s and Related Disorders Association of Ghana operates a caregiver support platform that has expanded since its inception. This aims to provide individualized support and education for caregivers, primarily utilizing freely available or open‐source educational resources such as the WHO iSupport manual, as well as educational materials from organizations like the Alzheimer’s Society UK, Alzheimer’s Association of the USA, and Alzheimer’s Disease International.While the currently available materials offer a much‐needed foundational understanding, addressing translational and cultural differences is essential. Ghanaian cultural practices, marked by its heterogeneity and distinctions from Western culture, presents unique challenges in dementia care. Moreover, considering varying levels of literacy, particularly among older adults, the adaptation of resources to include tailored video content could be beneficial for a more inclusive and effective approach.The WHO’s iSupport manual has been successfully translated and adapted into several languages and cultural settings around the world. Replicating this adaptation in the Ghanaian cultural context would be a momentous step in developing bespoke and culturally relevant dementia care resources in Africa.
Improve Statistical Efficacy Inference: Global Reduction Rate in Disease Progression
Authors: Wang Guoqiao , Jin Kun 
Published: January 2025

AbstractBackgroundIn AD trials, the treatment effect is typically evaluated by estimating the absolute difference in change from baseline to the end‐of‐study visit (e.g., 18 months) between treatment arms using the MMRM model. To enhance clinical interpretability, this absolute difference is often converted into a percentage slowing relative to the placebo decline (e.g., 27% of CDR‐SB in lecanemab trial). We propose to model this percentage directly as a global reduction rate (GRR) in disease progression using multivariate proportional MMRM models (MpMMRM). MpMMRM estimates GRR across all multiple longitudinal and/or survival endpoints, either at the last study visit or for all post‐baseline visits. For example, donanemab lead to 35.9% reduction in iADRS, 36.0% in CDR‐SB, and 38.6% reduction in progression to more advanced disease stages as measured by CDR global, which can be model simultaneously to estimate a GRR. The objective of this presentation is to evaluate the advantages of utilizing GRR as an inference tool for treatment efficacy.MethodWe will compare the global reduction rate (GRR) with three other statistical efficacy inference methods. These methods include: (i) Traditional MMRM inference using a single endpoint. (ii) Global statistics test (GST): GST combines z‐test statistics across multiple endpoints. (iii) Composite analysis utilizing a composite score derived from multiple endpoints. To evaluate these methods, we utilized simulated data that mimicked successful early Alzheimer’s disease trials.ResultOur preliminary simulation results showed that utilizing GRR across multiple longitudinal endpoints shows power advantages compared to the other methods, including GST. These advantages can be observed when considering the GRR at the last visit or overall post‐baseline visits. Additionally, estimating the GRR based on combined longitudinal and survival endpoints also demonstrates power advantages. Importantly, we also demonstrated that Type I errors are well‐controlled for all the methods considered in our simulations.ConclusionGRR evaluates the totality of evidence of a treatment effect. It can be estimated using a one‐step approach based on well‐established SAS procedures. GRR does not require any additional assumptions and offers greater interpretability and power compared to traditional methods like GST and the composite method.