bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations between Later‐life Cerebrovascular Reactivity and Brain Structure and Cognitive Decline: A Longitudinal Study in an Aging Cohort with Varying Dementia Risks
Authors: Wang Congxiyu , Patel Raihaan , Jobbins Lucy , Reid Graham , Hobden Georgina , Mackay Clare E , Ebmeier Klaus P , Kivimäki Mika , Singh‐Manoux Archana , Bulte Daniel , Suri Sana 
Published: January 2025

AbstractBackgroundCerebrovascular reactivity (CVR) is implicated in the progression of dementia, though the underlying mechanisms is not understood. This study examines the relationships between CVR and brain structure and cognitive decline, moderated by mid‐life dementia risk.Method163 participants from the Whitehall‐II cohort underwent neuropsychological testing and MRI, including T1‐weighted, FLAIR, and DTI sequences, at two phases (Phase‐I: mean age=68.2±4.4; Phase‐II: mean age=76.9±4.5). CVR was quantified via BOLD response to 5% CO2 only at Phase‐II. Linear regression tested the Phase‐II and Phase‐I to Phase‐II associations between CVR and brain and cognitive outcomes (Table 1), alongside its interaction with dementia risks. Post‐hoc analysis clarified the extent of these associations among different risk groups.ResultTables 2 and 3 list significant cross‐sectional and longitudinal results, respectively. At Phase‐II, global CVR was positively associated with volume of left nucleus accumbens, and temporoparietal junction (p<0.03). Parietal CVR was positively associated with left hippocampus volume (p=0.03). These associations were more pronounced in the low‐risk group. Temporal CVR was related to thalamus volume (p<0.05) across all participants, with associations of the right thalamus exclusive to the high‐risk group (p=0.03). Longitudinally, lower global and regional CVR at Phase‐II was linked to greater reduction in temporoparietal junction volume (p<0.04). In high‐risk individuals, lower frontal, parietal, or global CVR was linked to larger volume declines in total grey matter or right thalamus respectively (p<0.05). Across all participants, lower parietal CVR at follow‐up was linked to greater FA reductions and RD increases between examinations in the corpus callosum (p=0.02) and to greater declines in FA and increases in MD, RD, and L1 in the cingulum bundle (p<0.04), with these effects being more pronounced in the low‐risk group. At Phase‐II, lower parietal and temporal CVR was associated with worse fluency and intelligence, respectively, in high‐risk individuals (p<0.05). Lower frontal CVR was linked to more executive function decline in the low‐risk group over‐time (p=0.03).ConclusionThis study highlights the differential impacts of global and regional CVR on brain structure and cognitive changes dependent on mid‐life dementia risks, which provides evidence for CVR as a potential biomarker for dementia and age‐related cognitive change.
Late‐life hypertension acts together with amyloid‐β pathology to promote memory loss
Authors: Ros Lucas Uglione Da , Ferrari‐Souza João Pedro , Hauschild Lucas Augusto , de Bastiani Marco Antônio , Lussier Firoza Z , Rahmouni Nesrine , Therriault Joseph , Servaes Stijn , Stevenson Jenna , Macedo Arthur C. , Chamoun Mira , Bezgin Gleb , Benedet Andrea L. ,   Alzheimer's Disease Neuroimaging Initiative (ADNI), Pascoal Tharick A. , Rosa‐Neto Pedro , Zimmer Eduardo R. 
Published: January 2025

AbstractBackgroundMidlife hypertension (HTN) is a known risk factor for Alzheimer's disease (AD). However, it remains to be elucidated whether the effect of late‐life HTN is also present. Here, we aimed to assess the associations of late‐life HTN and amyloid‐β pathology (Aβ) with longitudinal changes in global cognition and different domains in cognitively unimpaired (CU) individuals.MethodWe evaluated 475 CU individuals of over 65 years of age from the ADNI cohort, with available baseline medical data and CSF Elecsys biomarkers (Aβ1‐42 and p‐tau181), as well as longitudinal clinical assessments with neuropsychological testing (up to 6 years). We used global cognitive tests, as well as composite scores for memory, executive function and language domains as outcomes. We replicated all the analyses in 162 CU individuals of over 65 years of age from the TRIAD cohort with baseline clinical data and [18F]NAV4694 positron emission tomography (PET) for Aβ, as well as longitudinal clinical assessments with neuropsychological testing (up to 3 years). The presence or absence of HTN was defined based on medical history. In addition, individuals were classified as Aβ+ or Aβ‐ based on CSF p‐tau181/Aβ1‐42 (ADNI) or Aβ‐PET (TRIAD).ResultLinear mixed‐effects (LME) models showed that HTN and Aβ acted together to promote longitudinal global cognitive decline (ADNI: HTN X Aβ X Time, β = ‐0.44, p = 0.001, Figure 1a; TRIAD: HTN X Aβ X Time, β =‐0.62, p = 0.001). Interestingly, additional analyses demonstrated that HTN and Aβ joint effects were observed on the decline of memory function (ADNI: HTN X Aβ X Time, β = ‐0.05, p = 0.012, Figure 1b; TRIAD: HTN X Aβ X Time, β = ‐0.64, p < 0.001), but not for executive function or and language (Figure 1c, ADNI: p = 0 .6767 and TRIAD: p = 0.797 and Figure 1d, ADNI: p = 0.8961 and TRIAD: p = 0.327, respectively).ConclusionIn CU individuals at increased risk for AD, late‐life HTN confers increased risk for cognitive decline, particularly in memory function. Further research is needed to understand the mechanisms involved and how treating hypertension in this population may mediate this risk.
Estimating the time between Aβ positivity and elevated regional tau in preclinical AD
Authors: Coath William , Betthauser Tobey J. , Teague Jordan P , Arstad Erik , Awais Ramla , Sander Kerstin , Scott Catherine J , Thomas David L , Dickson John , Markiewicz Pawel J , Barkhof Frederik , Schöll Michael , Richards Marcus , Fox Nick C , Cash David M , Schott Jonathan M ,   the Insight 46 team
Published: January 2025

AbstractBackgroundUnderstanding when Aβ positive cognitively normal individuals develop tau pathology has important implications for treatment with anti‐Aβ therapies. We employed a changepoint regression approach to estimate time from Aβ‐PET positivity to regionally elevated tau‐PET in a population‐based cohort of primarily cognitively unimpaired individuals.MethodParticipants from Insight 46 (1946 British birth cohort) underwent two [18F]florbetapir Aβ‐PET scans and a sub‐sample enriched for Aβ were also scanned with [18F]MK‐6240 tau‐PET, characteristics are presented in Table 1. Age at Aβ‐PET positivity, defined through Gaussian mixture modelling (GMM) as >12 Centiloids, was estimated using the SILA algorithm (Betthauser et al. 2022). Tau‐PET SUVRs from a temporal‐meta, Braak I‐VI and 34 bilateral FreeSurfer7 regions were calculated 90‐110 mins post‐injection using an inferior cerebellar grey matter reference region. Tau‐PET positivity cutpoints for each region were defined using the 99th percentile of the lower distribution from GMM. For each region, we tested changepoints in the slope of the linear regression between tau‐PET SUVR and time from estimated Aβ positivity with Bonferroni correction (5% significance, p<.001).ResultAt tau‐PET scan, 90 individuals (60%) were >0 years from estimated Aβ positivity. There was a statistically significant difference in slopes before and after the changepoint for all composite regions excluding Braak VI (Figure 1). Changepoint estimates show that tau accumulation started ∼2.5yrs after estimated Aβ positivity in Braak stages I‐III; and ∼10‐12.5yrs for Braak stages IV‐V, and the temporal‐meta region (Figure 2A). Regional estimates broadly followed Braak stages for 16/36 regions showing significant evidence of change in slopes (Figure 2B). Tau positivity rates before changepoints did not exceed 5%, whereas post‐changepoint tau positivity rates were between ∼10% and ∼50%. Regions with later changepoints tended to exhibit higher post‐changepoint slopes with greater uncertainty.ConclusionElevated tau‐PET signal occurs ∼2.5 years after estimated age of Aβ onset in Braak stages I‐III and ∼10‐12.5 years in temporal‐meta and Braak stages IV‐V, with uncertainty within these groupings. These estimates for later Braak stages are consistent with results from previous work on the timing of positive tau PET visual reads. These findings may have implications for determining the optimal time to administer Aβ immunotherapies in asymptomatic individuals.
Early and Genetic Biomarkers in Alzheimer's Disease: Role of Metabolism and Neuroinflammation in the Cognition of Coastal Peruvians
Authors: Zegarra‐Valdivia Jonathan Adrian , Arana‐Nombera Harold Alessandro , Perez‐Fernandez Leandro Aron , Casimiro‐Arana Milagros del Rocio , Alamo‐Medina Reyna Elizabeth , Gallegos‐Manayay Viviana Nayelli , Oliva‐Piscoya María del Rosario , Abanto‐Saldaña Eduardo Sebastián , Vásquez‐Zuñe Nobuko , Ordinola Maria Celinda Cruz , Manrique Carmen Paredes 
Published: January 2025

AbstractBackgroundAlzheimer's Disease (AD) has been associated with neurocognitive, metabolic, and neuroinflammatory alterations. Currently, there are no useful biomarkers in low‐resource countries, and genetic risk/protection factors in Peruvians are unknown.Objective: To establish the first serum bank in the northern part of the country for the analysis of participants with mild cognitive impairment (MCI) or AD. This will enable the identification of a profile of risk/protection factors in the Peruvian population. We will also analyze the interaction between levels of neurocognition, IGF‐I, and neuroinflammation as potential biomarkers for early detection of cerebral deterioration.MethodThis is a quantitative, cross‐sectional, retrospective case‐control study. We will identify the neurocognitive profile and serum biomarkers (IGF‐I, TNF‐α, interleukins) of adult participants (>50 years old), both healthy individuals and those previously identified and diagnosed with MCI or AD by a specialist (neurologist, geriatrician, or psychiatrist).ResultsThis is an ongoing project; to date, we have assessed over 100 participants aged 50 and above. We are in the process of evaluating both control subjects and patients with Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD). We aim to continue our assessments and complete blood sample collections throughout the year.ConclusionThis study proposes to create the first serum bank for the study of genetic and non‐genetic biomarkers associated with dementia in the northern part of the country. We will use the triad of IGF‐1, neuroinflammation, and neurocognition biomarkers for early diagnosis in MCI and AD. Additionally, this will enable new genetic studies to identify risk/protection factors in Peruvians.
The use of MRI, FDG‐PET and CSF biomarkers in young‐onset cognitive disorders: real‐world clinical evidence on the concordance of investigations
Authors: Whitmore Molly J , Gilmartin Christopher G S , Tench Christopher , Mukaetova‐Ladinska Elizabeta , Hosseini Akram A. 
Published: January 2025

AbstractBackgroundCognitive disorders are clinical diagnoses informed by history, cognitive testing and investigations including MRI, FDG‐PET and CSF biomarkers. These investigations do not always correlate however. This study sought to investigate the concordance between MRI, FDG‐PET and CSF biomarkers with final diagnosis in a real‐world clinical context.MethodThis is a prospective longitudinal cohort study (CogNID, NCT03861884, IRAS 250525) of a referral cognitive neurology NHS service (n=345). MRI and FDG‐PET at assessment were appraised for whether they were suggestive of the final diagnosis. An interim analysis was performed on a quality assured dataset of those aged ≥40 and <70 years old.ResultCohort characteristics: 40≤age<70 (n=265), MRI results available (n=245), FDG‐PET available (n=129), CSF analysis available (n=104). Interim results (n=77): Kappa coefficient of concordance of 0.15 (95% CI 0.03‐0.28) between MRI and FDG‐PET for suggestion of final diagnosis, demonstrating a poor level of agreement. MRI at time of assessment was suggestive of final diagnosis in 48% of cases and FDG‐PET in 56%. The positive predictive value for a final diagnosis of Alzheimer’s Disease based on CSF analysis in keeping with Alzheimer’s continuum was 64%, with a negative predictive value of 75%.ConclusionInvestigations must be viewed holistically in combination with a clinical history and cognitive examinations. Initial results at time of assessment are often not indicative of the final diagnosis, and may be discordant. Follow‐up and repeat investigations where appropriate are critical for improving diagnostic accuracy.*CG&MW are joint first authors
Post‐mortem MR imaging of tau pathology – a pilot study
Authors: Sumra Vishaal , Spring Shoshana , Botelho Owen , Nieman Brian , Sled John G , Tartaglia Maria Carmela , Kovacs Gabor G. 
Published: January 2025

AbstractBackgroundIn‐vivo detection of neuropathology is critical for early diagnosis of neurodegenerative diseases. Post‐mortem brain magnetic resonance imaging (MRI) of pathological protein inclusions could further our ability to detect them in vivo and correlate MRI parameters to histopathological substrates. In this post‐mortem study, we aimed to identify MRI correlates of neurodegenerative disease pathology in a brain with various forms of proteinopathies.MethodOne large cortical section containing the temporal cortex, hippocampus and thalamus was used from an 82‐year‐old male patient, with chronic traumatic encephalopathy (CTE), Alzheimer’s disease (AD), TDP‐43, aging related tau astrogliosis (ARTAG) and cerebral amyloid angiopathy (CAA) pathologies. The post‐mortem tissue sample was scanned using high‐resolution Rapid Acquisition with Relaxation Enhancement (RARE) and multi‐gradient echo (MGE) sequences on an 11.7 Tesla MRI (Bruker, Germany). RARE scan parameters were as follows: field of view: 97.2 x 86.4 x 28.8 mm, rep time: 2 s, RARE factor: 8, echo time: 48 ms, echo spacing: 12 ms, 225 μm isotropic resolution. Tissue samples were subsequently sectioned (0.004 mm thick slices) and stained using AT8 – for Tau, GFAP – for astrogliosis and H&E/Luxol – for distinguishing gray (GM) and white matter (WM) and PERLS – for extracellular iron.ResultPost‐mortem MRI allowed for clear visualization of WM and GM structures. Decreased cell density in WM as visualised on H&E stained slices was associated with hyperintensities on T2w images and decreased measured R2*. AT8 immunoreactivity in GM and WM was associated with hyperintensities on T2w images and decreased measured R2*.ConclusionHigh‐resolution MRI of post‐mortem tissue allowed for visualization of fine WM‐GM details, as well as hyperintensities in areas that potentially correspond to increased densities of tau pathology and decreased WM density. Further studies are needed to investigate the potential for high‐resolution post‐mortem MRI to visualize the pathological process in neurodegenerative diseases.
The HOPE4MCI study: AGB101 treatment reduces entorhinal cortex atrophy in patients with amnestic mild cognitive impairment due to Alzheimer’s Disease who are ApoE‐4 non‐carriers
Authors: Rani Nisha , Mohs Richard , Gallagher Michela , Bakker Arnold 
Published: January 2025

AbstractBackgroundHippocampal hyperactivity is a hallmark of prodromal Alzheimer’s disease (AD) that predicts progression in patients with amnestic mild cognitive impairment (aMCI). AGB101 is an extended‐release formulation of levetiracetam in the dose range previously demonstrated to normalize hippocampal activity and improve cognitive performance in aMCI. The HOPE4MCI clinical trial used a 78‐week protocol to assess progression in amyloid‐positive patients with MCI due to AD. Mohs et al. (2024) reported the clinical/cognitive results showing that ApoE‐4 non‐carriers had a more favorable treatment effect of AGB101 over the 78‐week duration of the study. Here we report effects of AGB101 on biomarkers of AD in those patients.MethodsForty‐four participants who completed the 78‐week protocol were ApoE‐4 non‐carriers. Structural MRI scans obtained in the study at baseline and after 78 weeks were analyzed using the Automated Segmentation of Hippocampal Subfields (ASHS) software providing volume measures of key structures of the medial temporal lobe relevant to AD progression. Blood samples collected at 78 weeks in the study were also analyzed for plasma biomarkers in those participants.ResultsTreatment with AGB101 significantly reduced atrophy in the left entorhinal cortex (p < 0.05) compared to placebo. Reduced atrophy in the entorhinal cortex was significantly correlated with the change in CDR‐SB score (r = ‐0.511) over 78 weeks, as well as with biomarkers of neurodegeneration neurofilament light (NfL; r = ‐0.382) and glial fibrillary acidic protein (GFAP; r = ‐0.398) collected at completion of the protocol.ConclusionAs reported in Mohs et al. (2024), progression on the primary clinical/cognitive endpoint of the Clincial Dementia Rating Scale Sum of Boxes score (CDR‐SB) occurred over the 78‐week protocol in the HOPE4MCI study and non‐carriers of ApoE4 treated with AGB101 showed a substantially more favorable effect than carriers. Here we report that treatment with AGB101, in those participants significantly reduced atrophy of the entorhinal cortex. That reduction in atrophy was significantly coupled with the change in CDR‐SB and with plasma biomarkers of disease. These exploratory analyses would be consistent with a reduction in neurodegeneration in the non‐carriers of ApoE4 treated with AGB101 prior to a clinical diagnosis of dementia.
Physical activity pattern mediating the relationship between genetic variants and AD‐like brain atrophy
Authors: Xu Hanxiang , Mu Shizhuo , Bao Jingxuan , Davatzikos Christos , Shou Haochang , Shen Li 
Published: January 2025

AbstractBackgroundStudies have shown physical activity (PA) patterns are heritable traits and are correlated with several known genetic risk factors including APOE, the best‐known gene associated with Alzheimer’s Disease (AD). SPARE‐AD was a previously developed machine learning index known to be sensitive to AD‐like brain atrophy. However, the relationship between genetic variants, physical activity patterns and AD‐related neuroimaging features have yet been extensively studied due to the lack of appropriate data and statistical methods for handling complex multimodal data. To bridge this gap, we perform a high‐dimensional mediation analysis to decompose the pathway from known genetic variants to AD‐like brain atrophy through accelerometry‐based physical activity patterns.MethodWe obtained genetic, accelerometry and neuroimaging data from UK Biobank (n=13,425). SPARE‐AD index was calculated from structural MRI data. Genetic variants were selected by GWAS using SAIGE with SPARE‐AD index as the outcome, adjusting for years of education, age, gender and the first 10 principal components as covariates. The 7‐day accelerometry data were summarized into conventional statistics such as average total log activity counts (TLAC) and percent of moderate‐to‐vigorous PA (MVPA), and data‐driven features derived using functional Principal Component Analysis. We performed high‐dimensional Bayesian mediation analysis (BAMA) to preliminarily identify the physical activity patterns with non‐zero indirect effect of genetic variants on SPARE‐AD. The mediation effect was later confirmed by significant associations between exposure (genetic variant) and mediator (physical activity pattern) using univariate analysis.ResultGWAS of SPARE‐AD identified 22 unique SNPs (p<=5e‐8). These SNPs and 154 physical activity features were included in our mediation analyses. We identified 128 significant (SNP, PA, SPARE‐AD) mediation relationships (one example shown in Figure 1). Most of the SNPs are located on AMPD3 gene, which is associated with energy metabolism. Among all the identified mediators, lower TAC and MVPA were identified to be associated with higher SPARE‐AD, and positive indirect effects on the association between SNPs and SPARE‐AD.ConclusionWe found several significant pathways, where physical activity measures could mediate genetic effects on AD‐related brain atrophy. This could provide insights for developing personalized behavioral intervention strategies that mitigate potential genetic risks.
Alzheimer’s Disease Plasma Biomarker Results from across 14 Alzheimer’s Disease Research Centers
Authors: Russ Kristen A. , Asthana Sanjay , Johnson Sterling C. , Wilson Rachael E , Craft Suzanne , Register Thomas C. , Lockhart Samuel N. , Nairn Angus C , Strittmatter Stephen M , van Dyck Christopher H. , Foroud Tatiana M. , Dage Jeffrey L. 
Published: January 2025

AbstractBackgroundThe Alzheimer’s Disease Center Fluid Biomarker (ADCFB) Initiative samples are analyzed centrally at NCRAD for AD plasma biomarkers. When combining NACC accessible data from across centers, biofluid biomarker data must be evaluated carefully. This will become more critical with the implementation of disease modifying therapies.MethodsBeta amyloid 1‐42 (Aβ42) and beta amyloid 1‐40 (Aβ40) were analyzed utilizing the Neurology 4‐Plex E kits on a Quanterix Simoa HD‐X. All assays were performed according to manufacturer’s instructions. NACC data from participants 65 or older was combined with biomarker results into one data set. Samples with PET results from the same visit as the blood collection were utilized for this analysis (n=114).ResultsData for amyloid and tau PET was used along with Aβ42/40 ratios to assess the area under the curve (AUC) for this data set (Figure 1). Amyloid PET and Tau PET by Aβ42/40 ROC analysis including age and APOE4 carrier status showed lower than expected AUCs (both 0.72). A subset of data (n=90) was analyzed using participants that were not on any FDA‐approved drugs for AD. This had no effect on AUCs for amyloid or tau PET by Aβ42/40 ratios. Distribution of Aβ42/40 ratios across sites showed a single site had a subset of very high Aβ42/40 ratios (n=8) in comparison to other sites. After removal of the Aβ42/40 outliers from the specific site from the data set, diagnostic accuracies of Aβ42/40 for both Amyloid PET (AUC=0.77) and Tau PET (AUC=0.76) were increased. More investigation into the exact cause of the outliers is necessary, but Aβ42/40 elevations independent from other biomarkers have been seen in clinical trials of Solanezumab and some other Aβ targeting antibodies.ConclusionTo avoid errors in data analysis when using shared data, it is important to track clinical trial co‐enrollment and drug type within ADCs at NACC. As FDA‐approved treatments become available or co‐enrollment of AD drug trials at centers occurs, it is critical to carefully track participant variables and review biofluid biomarker data when it is being combined across centers or studies.