bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lower white matter hyperintensity is associated with lower mild behavioral impairment severity among pre‐dementia people with higher education attainment
Authors: Soo See Ann , Ng Kok Pin , Kumar Dilip , Saffari Seyed Ehsan , Kandiah Nagaendran 
Published: December 2022

AbstractBackgroundMild behavioral impairment (MBI) describes the emergence of neurobehavioral symptoms in later life as harbingers of neurodegeneration. Emerging evidence suggests that white matter hyperintensity (WMH), a known risk factor for cognitive impairment, is associated with MBI. Furthermore, education level which reflects cognitive reserve, influences the risk of dementia. However, the role of education levels on the relationship between WMH and MBI is unknown. Here, we aim to evaluate the effects of education levels on WMH and MBI among a pre‐dementia cohort from a memory clinic in Singapore.MethodIn this retrospective cross‐sectional study, 210 pre‐dementia participants (mean age 64.31, mean MMSE 27.77, mean education level 12.60, 37.6% males), underwent cognitive assessment, Magnetic Resonance Imaging (MRI) and completed the MBI‐checklist (MBI‐C) self‐report in National Neuroscience Institute Singapore from 2017 to 2021. Multiple linear regression models evaluated the main effects of WMH total ratings and years of education on MBI, while moderation analysis evaluated the effects of years of education with WMH on MBI. All analyses were controlled for age and sex.ResultWhile education levels and WMH were not associated with MBI‐C total scores independently (p>0.05), we found that education levels moderated the effects of WMH on MBI‐C total score (β=0.269 , p=0.038). Specifically, higher education attainment is associated with lower MBI‐C total scores among individuals with lower burden of WMH; while higher MBI‐C total score is observed with higher education among people with high WMH burden (Figure 1).ConclusionHigher education attainment is associated with a lower risk of MBI when the WMH load is lower. Our findings support interventions to reduce WMH load in pre‐dementia people with higher education attainment to reduce MBI severity.
Davos Alzheimer’s Collaborative: Building a globally representative cohort through a technologically‐enabled approach
Authors: Au Rhoda , Joung Philip , Ho Jor Sam , Albastaki Omar , Thompson Louisa I , Low Spencer , Philippakis Anthony , Levey Allan I. 
Published: December 2022

AbstractBackgroundIn January 2021, the Davos Alzheimer’s Collaborative (DAC) was launched to develop precision solutions to reduce barriers to AD research for globally underrepresented populations, including older adults from any ethnic/racial group and/or the lowest resource settings. To meet this DAC vision, the Global Cohort Development (GCD) program has been establishing collaborations with existing cohort studies around the world to collect new digital cognitive and behavioral phenotypic data and harmonize digital data with existing cohort data. DAC is also creating open‐source data processing and advanced analytic tools, and building the infrastructure necessary to make these data broadly, but securely accessible to the scientific community.MethodsFifteen cohorts from 13 countries have joined GCD, representing 25,000+ individuals. Each cohort is deploying a protocol using a tablet to document AD‐related cognitive and behavioral symptoms across the disease continuum, as well as a smartphone for remote detection and continuous monitoring of incident changes in these symptoms.ResultsWe will discuss the approach for launching a digital protocol across cohorts from multiple countries, where the participant mix varies in technology access and use, language, culture and education, and extensiveness of existing research infrastructure.ConclusionsGlobal population level research requires a significant paradigm shift in traditional methodology including study design, assessment practices, data accessibility infrastructure and analytic approaches. Achieving global reach that works regardless of available resources and expertise will require major realignment for AD research to be representative of everyone, and clinical assessment and care relevant and equitable to anyone.
Building the Research Path for Identifying and Validating Cognition‐related Digital Biomarkers
Authors: Huang Li‐Kai , Kuan Yi‐Chun , Yang Cheng Chang , Kuo Po Chih , Hu Chaur‐Jong 
Published: December 2022

AbstractBackgroundCognitive dysfunction is a core feature of dementia spectrum disorders but simple screening tests are less sensitive to detect the deficits, especially in the very early stage of disease course using most standardized test instruments. This results in delayed discovery of disease onset and opportunity for early interventions that might be more effective in delaying or arresting progression. Digital phenotyping using a combination or hardware and software solutions provide potentially much more effective tools for helping clinicians identify subtle signs of cognition deficits and track them in a compressed timeline to confirm the accuracy of decreasing slope indicative of a neurodegenerative etiology.MethodsBeginning in 2017, 1,866 participants were recruited from the Dementia Center, Shuang Ho Hospital, New Taipei City, Taiwan and will be invited to use a smartphone application to collect digital phenotypes including information processing speed, response accuracy, error detection, and multitasking capacity and vocal patterns, such as speech pitch, tone, rhythm. Additionally, four groups of 100 new participants each will be recruited; cognitive unimpaired (CU), subjective cognitive decline (SCD), mild cognitive impairment (MCI) and mild dementia. In addition to the smartphone applications, these 400 participants will undergo additional testing that include the cognitive abilities screening instrument (CASI), Clinical Dementia Rating (CDR), Cookie Theft Picture Description, Eye Tracking Test, and gait/balance.ResultsDigital phenotyping profiles will be constructed for the cohort and validated against the smaller sample to determine those metrics that can serve as actual digital biomarkers. For the smaller sample, additional multi‐dimensional profiles will be constructed that add gait parameters (step length, stride length, step width, foot angle) and eye‐tracking (visual fixation changes, speed, duration) and determine to what extent they increase differential diagnostic accuracy.ConclusionsDigital assessment tools can be used for detecting changes in cognitively related behaviors associated with preclinical and early stage clinical dementia. Future research is needed to confirm the efficacy of these digital phenotypes to serve as digital biomarkers that have high prognostic and diagnostic accuracy.
The impact of hypertension on longitudinal cognitive decline in cognitively unimpaired individuals
Authors: Da Ros Lucas Uglione , Ferrari‐Souza João Pedro , Hauschild Lucas Augusto , Brum Wagner Scheeren , Bellaver Bruna , Leffa Douglas Teixeira , Ferreira Pamela C.L. , Bieger Andrei , De Bastiani Marco Antônio , Pascoal Tharick A , Zimmer Eduardo R. 
Published: December 2022

AbstractBackgroundMid‐life hypertension (HTN) is considered a risk factor for the development of clinical Alzheimer´s Disease (AD). Yet, it is not known whether late‐life hypertension relates to AD´s pathophysiology, with current literature being contradictory. We recently demonstrated that a vascular risk factor composite, which includes HTN, interact with the AD pathophysiology to promote cognitive decline. Here, we aimed to assess whether late‐life HTN alone and AD biomarkers interact to promote longitudinal cognitive decline, and if controlling the blood pressure affects this relationship.MethodWe evaluated 503 cognitively unimpaired (CU) individuals from the ADNI cohort, with available baseline medical data and cerebrospinal fluid (CSF) Elecsys biomarkers (Aβ1‐42 and p‐tau181), as well as longitudinal clinical assessments with neuropsychological testing (up to 6 years). Individuals with both Aβ1‐42 and p‐tau181 positivity were defined as having preclinical AD ((AT)+), and individuals with previous diagnosis of HTN or those taking anti‐hypertensive medication were considered HTN+. These participants were further divided based on two different measures of systolic blood pressure, being classified as controlled (C) if at least one of them was inferior to 140 mmHg, or non‐controlled (NC) if both measures were over 140 mmHg. The modified version of Preclinical Alzheimer’s Cognitive Composite (mPACC) was used as the outcome to evaluate the cognitive trajectory.ResultLinear mixed‐effects (LME) models showed that HTN interacted with the AD pathophysiology to promote longitudinal cognitive decline (HTN X AD pathophysiology X Time, β= ‐0.45, p= 0.014), and when the individuals with HTN were further stratified between C and NC, we could see that this effect was seen only in the NC group (HTN+C X AD pathophysiology X Time, β= ‐0.29, p=0.13; Group HTN+NC X AD pathophysiology X Time, β= ‐0.79, p=0.002).ConclusionWe observed that in CU individuals, HTN acted as a risk factor for cognitive decline in (AT)+ patients. Additionally, HTN + NC had an increased risk compared with HTN + C individuals. Thus late‐life HTN is a risk factor for the emerging of cognitive symptoms among the elderly and controlling the blood pressure may reduce this risk.
Combining high‐resolution ex vivo MRI and histopathology to identify medial temporal lobe atrophy patterns specific to tau pathology in Alzheimer’s Disease
Authors: Ravikumar Sadhana , Denning Amanda , Lim Sydney A , Chung Eunice , Ittyerah Ranjit , Wisse Laura EM , Xie Long , Das Sandhitsu R. , Robinson John , Schuck Theresa , Grossman Murray , Lee Eddie B , Tisdall Dylan M , Mizsei Gabor , Artacho‐Perula Emilio , Martin Maria Mercedes Iniguez de Onzono , Jimenez Mar Arroyo , Munoz Monica , Romero Francisco Javier Molina , Rabal Pilar Marcos , Sanchez Sandra Cebada , Gonzalez Jose Carlos Delgado , Prieto Rosa , Parada Marta Corcoles , Irwin David J. , Trojanowski John Q , Wolk David A. , Insausti Ricardo , Yushkevich Paul A. 
Published: December 2022

AbstractBackgroundTau pathology in the medial temporal lobe (MTL) is closely linked to neurodegeneration, and is an early pathological change associated with Alzheimer’s disease (AD). MRI measures of MTL neurodegeneration have proven to be sensitive to change during preclinical AD. Current measures are confounded by the presence of non‐AD pathologies (e.g., TDP‐43, ageing). Here, we combine ex vivo imaging with histopathological ratings of tau and TDP‐43 to identify fine‐grained MTL atrophy patterns specific to tau. Such an analysis could be used to define MTL “hotspots” where in vivo measures of neurodegeneration are expected to be strongly associated with tau, potentially enabling the development of biomarkers that are more effective during early AD clinical trials.MethodEx vivo MRI scans (0.2x0.2x0.2mm3, 9.4T) of human MTL specimens were combined using a customized registration approach to construct a 3D atlas. Using serial histology available in a subset of specimens (n = 11), MTL subregions in the atlas were labelled based on cytoarchitecture (Ravikumar et al., 2021) (Figure 1A). To perform thickness analysis, 29 specimens containing a primary diagnosis of AD or primary age‐related tauopathy were registered to the atlas (13 specimens were registered to the atlas during atlas construction, and 16 were registered to the atlas after it was constructed) (Figure 1B, Table 1). Using histopathology measures of tau and TDP‐43 pathology (based on contralateral sampling), we investigated the association between tau and thickness by fitting a linear model (with age/TDP‐43 as covariates) at each point along the MTL and SRLM surface.ResultPointwise thickness analysis reveals significant atrophy patterns in the transentorhinal region and SRLM. When excluding age from the model, stronger tau associations are observed in the SRLM, entorhinal cortex, and extending further towards Brodmann Area 35 (Figure 2).ConclusionOur findings are consistent with early Braak stages but suggest that covarying for age may be obscuring some associations due to tau since age and tau burden have a highly correlated relationship (Figure 3). In future work, quantitative maps of NFT burden will be mapped from serial pathology images into atlas space, allowing us to characterize NFT distribution in 3D (Yushkevich et al., 2021).
Posterior Cortical Atrophy: Primary Occipital Variant
Authors: Shir Dror , Graff‐Radford Jonathan , Machulda Mary M. , Pham Nha Trang Thu , Jack Clifford R. , Lowe Val J. , Whitwell Jennifer L , Josephs Keith A 
Published: December 2022

AbstractBackgroundPosterior Cortical Atrophy (PCA) is one of the atypical Alzheimer’s Disease (AD) variants, characterized by predominant visuospatial and visuoperceptual deficits, with dorsal and ventral subtypes recognized clinically and radiographically. A third primary occipital (caudal) variant has been suggested. The objective of this study was to determine its demographics, clinical manifestations, and biomarker findings.MethodFifty‐two PCA patients with positive amyloid PET scans were investigated. Patients underwent neuropsychological assessment, 3T MRI imaging and FDG‐, amyloid‐ and tau‐PET scans. Regional FDG‐PET values were normalized to the pons and represented as z‐scores relative to a control population. Patients were divided into “primary occipital” and “other PCA” subgroups according to FDG‐PET defined criteria, with primary occipital defined as patients in which the z‐scores for occipital subregions were at least one standard deviation lower (i.e., more abnormal) than the z scores in all other brain regions. Global amyloid‐PET, temporoparietal FDG‐PET and temporal tau‐PET regions‐of‐interest (ROI) were calculated. Student’s T test and Fisher’s exact analyses were used to investigate differences in demographics, clinical findings, and imaging biomarkers across the two groups.ResultNine patients were classified as primary occipital; primary occipital patients were older (64.8±6.9 versus 59.3±6.8, p=0.034) and had more years of education (17.7±1.7 versus 15.1±2.6, p=0.007) compared to the other PCA patients. Clinical evaluation revealed worse performance for the primary occipital group on the Ishihara test for color perception (p<0.001), while the other PCA patients performed worse on the Western Aphasia Battery (WAB) praxis scale (p=0.005). Overall neuropsychiatric symptom burden as defined by the NPI‐Q was lower in the primary occipital group (p<0.001). The FDG‐PET meta‐ROI (weighted median uptake in angular gyrus, posterior cingulate, and inferior temporal ROIs, normalized to the pons and vermis) was higher in the primary occipital subtype (p=0.006), but no differences were observed in amyloid and tau‐PET.ConclusionClinical and biomarker findings suggest primary occipital PCA is characterized by an older age at onset, more color perception dysfunction, less severe ideomotor apraxia and less hypometabolism in temporal‐parietal meta‐ROI compared to more established phenotypes.
Genetic Risk Score for Alzheimer’s Disease Predicts Brain Volume Differences in Mid‐ and Late‐life in UK Biobank Participants
Authors: Buto Peter , Swinnerton Kaitlin N. , La Joie Renaud , Zimmerman Scott C , Glymour M. Maria , Ackley Sarah F , Brenowitz Willa D 
Published: December 2022

AbstractBackgroundGenetic risk variants for late‐onset Alzheimer’s disease (LOAD) predict brain atrophy, cognitive changes, and dementia onset in late‐life. Little is known about the association between LOAD genetic variants and regional brain volumes in middle aged adults. Further understanding of when associations emerge across mid‐to‐late‐life may point to the earliest manifestations of LOAD.MethodWe studied 41,435 UK Biobank participants aged 45‐80 who enrolled 2007‐2010, had no dementia at baseline, and subsequently underwent a brain MRI (3‐Tesla scanner). A genetic risk score for LOAD (LOAD‐GRS) was calculated as a weighted sum of 27 variants previously confirmed to be genome‐wide significant predictors of LOAD dementia including APOE. MR images underwent standardized quality control and data processing by UK Biobank. Volumes (both hemispheres combined) for 38 regions of interest (ROIs) were derived from Freesurfer (Version 6.0) packages for subcortical segmentation and cortical parcellation with the Desikan‐Killiany‐Tourville atlas. We examined associations of LOAD‐GRS with each ROI tested whether effects differed across age using linear regression with an interaction between age and LOAD‐GRS. A cross‐validated model determined the earliest age at which trends in MRI volume diverged between those with low compared to high LOAD‐GRS. All models adjusted for sex, genetic ancestry, and intracranial volume.ResultUsing a Bonferonni correction (p<0.05/38=0.0013]), 4 of 38 regional volumes had significant interactions between age and LOAD‐GRS, all indicating that for people with 1 SD higher genetic risk of LOAD, older age was more strongly associated with smaller brain volumes than among people with lower LOAD genetic risk. Significant regions included the amygdala (‐172.6 mm3/SD; 95%CI=‐176.7,‐168.5); hippocampus (‐351.9 mm3/SD; 95%CI=[‐359.9,‐343.9], nucleus accumbens (‐87.7 mm3/SD; 95%CI=‐89.4,‐86.0], and thalamus (‐526.4 mm3/SD; 95%CI=[‐538.2,‐514.6]. Best fitting model‐based age‐curves for people with high versus low LOAD‐GRS scores began to diverge around age 45 for the nucleus accumbens, hippocampus, and thalamus and after age 51 for the amygdala.ConclusionGenetic factors that increase risk of LOAD begin to predict lower brain volumes as early as middle age, decades prior to average age of dementia onset. Our findings prioritize particular brain regions that may help predict LOAD onset, including the hippocampus, amygdala, nucleus accumbens, and thalamus.
Associations between brain iron deposition and structural Alzheimer’s disease signature in cognitively unimpaired adults
Authors: Stankeviciute Laura , Falcon Carles , Operto Grégory , Rojas Santiago , Grau‐Rivera Oriol , Garcia Marina , Shekari Mahnaz , Niñerola‐Baizán Aida , Perissinotti Andrés , Minguillon Carolina , Fauria Karine , Molinuevo Jose Luis , Zetterberg Henrik , Blennow Kaj , Suárez‐Calvet Marc , Cacciaglia Raffaele , Gispert Juan Domingo 
Published: December 2022

AbstractBackgroundIron dyshomeostasis appears to be an early event in the Alzheimer’s continuum. However, little is known how incipient cerebral iron deposition affects brain structure and function in cognitively unimpaired (CU) individuals. Here, we assessed the relationship between mean intensities in subcortical nuclei, a proxy measure for iron content, and regional cortical thickness as well as brain metabolism in middle‐aged CU individuals and sought for interactions with biomarkers of Alzheimer’s pathology.MethodWe included 288 CU adults from the ALFA+ cohort (Table 1). Mean intensities were quantified from T2‐weighted magnetic resonance images in 18 a priori defined subcortical nuclei. Due to the high correlations among regional intensities, we performed a principal component analysis to obtain a single measurement of cerebral iron load (Table 2). Cortical thickness (CT) of the “Alzheimer’s disease (AD) signature” composite region of interest (ROI) was assessed using FreeSurfer v6.0. [18F]fluorodeoxyglucose (FDG) PET scans were used to calculate the standardized uptake value ratio (SUVr) within a meta ROI. We created separate general linear models where cortical thickness and PET meta‐ROIs were the dependent variables, while the first principal component (PC1), age, sex, APOE‐ε4 status, and education level were entered as predictors. In additional models, CSF levels of amyloid‐beta ratio (Aβ42/40) and phosphorylated tau (p‐tau) were entered as covariates. We also tested the interaction between PC1 and CSF Aβ42/40 and p‐Tau status. Statistical significance was set at p<0.05.ResultPC1 explained 47.64% of the variance of mean intensities in subcortical regions with lower values denoting higher iron concentration. Lower PC1 values were negatively associated with AD‐signature thickness (p=0.004), but not with brain glucose metabolism in the meta ROI (p=0.936). (Table 3. Figure 1). These results remained unchanged once AD core CSF biomarkers were entered into the model. No significant interactions with abnormal levels of CSF Aβ or p‐Tau were revealed with AD‐signature thickness or brain metabolism.ConclusionIn CU individuals, higher content of iron deposition is associated with reduced thickness, but not glucose metabolism, in cortical areas that typically show atrophy early in the Alzheimer’s continuum. This association was not modified by the presence of altered biomarkers of AD pathology.
Age‐related tau‐PET uptake and its downstream effects extend beyond the medial temporal lobe in cognitively normal older adults
Authors: Wuestefeld Anika , Berron David , Binette Alexa Pichet , van Westen Danielle , Stomrud Erik , Mattsson‐Carlgren Niklas , Strandberg Olof , Smith Ruben , Palmqvist Sebastian , Glenn Trevor , Hansson Oskar , Wisse Laura EM 
Published: December 2022

AbstractBackgroundAmyloid‐beta (Aβ) is hypothesized to facilitate the spread of tau pathology beyond the medial temporal lobe (MTL). However, there is evidence that age‐related Aβ‐independent tau pathology is present outside the MTL (Kaufman et al., Acta Neuropathol, 2018). We examine tau deposition determined by positron emission tomography (PET) in regions typically involved earlier/later in AD and downstream effects on neurodegeneration and cognition in cognitively unimpaired older adults and a low‐Aβ subgroup.MethodsWe included 488 adults (40‐91 years; low‐Aβ: n=355, 65.2±11.5 years) from the BioFINDER‐2 study. MTL volumes (dentate gyrus, subiculum (SUB), cornu ammonis 1) and thickness (entorhinal cortex, Brodmann areas (BA)35/36, and parahippocampal cortex) were obtained, using Automated Segmentation for Hippocampal Subfields packages for T1‐ and T2‐weighted magnetic resonance images. Thickness of early/late neocortical AD‐regions (anterior cingulate, precuneus/posterior cingulate (PPC), orbitofrontal, inferior parietal cortex; and middle frontal, lateral occipital, and precentral/postcentral gyrus) was determined using FreeSurfer. [18F]RO948‐ and [18F]flutemetamol‐PET standardized uptake value ratios (SUVRs) were calculated for local tau and global/local Aβ. Aβ status was determined using Aβ‐PET or cerebrospinal fluid Aβ‐42/40 ratio. Global cognition was measured using delayed word‐list recall, trail making test B, and animal fluency.ResultsIncreasing age was associated with higher tau‐PET SUVRs primarily in MTL/frontal/parietal regions. A significant association between age and local tau‐PET remained even when including Aβ‐PET as a mediator (Fig. 1).Age and local tau‐PET, but not Aβ‐PET, where negatively associated with structure in most examined regions (Figs. 2‐3). Age‐structure associations were serially mediated via tau‐PET in regions with early AD pathology (SUB/BA35/PPC). Also, in the low‐Aβ subgroup, tau‐PET mediated the age‐structure (SUB/BA35/PPC) associations (Fig. 3D). Finally, the age‐global cognition relationship was serially mediated via MTL tau‐PET and subiculum volume, even when including global Aβ‐PET as additional mediator (Fig. 4).ConclusionWe observe partially Aβ‐independent associations between age and tau‐PET signal across the neocortex. Interestingly, partially Aβ‐independent tau‐PET signal appears to mediate the age‐structure associations in and outside the MTL (PPC), also in the low‐Aβ group, and the age‐MTL structure‐cognition associations. This potentially provides in vivo support for Primary Age‐related Tauopathy downstream effects on structure, beyond the MTL, and cognition.