bluuebunny/crossref_metadata_2025_split huggingface dataset:
SuperAging: A model for studying mechanisms of resilience and resistance
Authors: Rogalski Emily J , Sridhar Jaiashre , Martersteck Adam , Makowski‐Woidan Beth , Engelmeyer Janessa , Parrish Todd , Besson Pierre , Cobia Derin , Paxton Holly , Weintraub Sandra , Katsaggelos Aggelos , Bandt Katie , Bigio Eileen H , Geula Changiz , Mesulam Marsel 
Published: December 2020

AbstractBackgroundMemory complaints are widespread among the elderly and aging is a major risk factor for Alzheimer’s disease (AD), leading to the impression that gradual loss of memory ability is a nearly universal consequence of getting old. Our longitudinal studies of SuperAgers, 80+ year‐olds with episodic memory performance that remains in the range that is at least normal for 50‐60 year‐olds suggests an alternative aging trajectory is possible. This session will highlight some of the emerging biologic features of the SuperAgers.MethodParticipants include SuperAgers and cognitively average 80+ year‐old cognitively average normal controls. Data from detailed neuropsychological assessments, quantitative neuroimaging measurements (MR and amyloid PET), genetic features and neuropathologic findings will be reported.ResultInitial evidence suggest SuperAgers tend to show mismatch between chronologic and biologic age, including maintenance of cortical but not necessarily hippocampal volume, a tendency to resist significant amyloid PET retention, an abundance of anterior cingulate Von Economo neurons, and some with resistance to cortical Alzheimer’s pathology.ConclusionThese studies contribute to our understanding mechanisms of resilience and resistance in cognitive aging and may help isolate factors that are potentially important for promoting successful cognitive aging and avoiding age‐related brain diseases such as AD.
Understanding caregiver profiles of older adults reporting cognitive decline: A descriptive study from North India
Authors: Dasgupta Jayashree , Faqurudheen Hena 
Published: December 2020

AbstractBackgroundAs India gets closer to an expected 7.6 million dementia cases by 2030, families are tasked with care‐giving in the absence of affordable healthcare and adequate health systems. Those most impacted include elderly caregivers, and are mostly female spouses of persons with dementia. With transitions from joint family systems to more nuclear structures due to urbanization and migration, understanding characteristics of family caregivers will be critical to developing adequate support systems and enabling better home‐based care in urban areas.MethodScreening camps were conducted in 8 locations across a North Indian urban area over 7 months, including a government hospital, communities, and senior centers. Assessment measures involved a brief cognitive assessment and screening for mental health, neurological, and preexisting medical issues. Sociodemographic information was collected from the accompanying family member. Both caregiver and the person reporting cognitive complaints were provided information about dementia symptoms with referrals to neurologists, psychiatrists or medical professionals based on screening results.ResultA total of 194 persons (112 men, 82 women) were screened after reporting subjective cognitive decline; on evaluation, 4% and 5% had symptoms indicative of dementia and definite cognitive decline, respectively. Findings also indicated that 58% of participants also had symptoms of depression and anxiety, causing concern for caregivers. Majority of participants were accompanied by a family member and only 7 participants lived on their own. Sociodemographic information was collected for a total of 187 caregivers (58% women, 42% men). 67% of caregivers were aged 55 years and above, indicative of caregivers themselves ageing whilst having to take care of an aging relative; 33% were aged 20‐34 years. 97% were immediate family members taking on primary care‐giving responsibilities (51% wives, 26% husbands, 16% sons, 4% daughters) indicating high risk for caregiver burden. More than 75% of those surveyed were educated above high school, indicating rising levels of educational achievement in urban areas. 35% of caregivers were homemakers and women, highlighting necessity for low‐cost or cost‐effective models of home‐based care services.ConclusionHealth systems and support mechanisms for the elderly are underdeveloped in India and require effective home‐based care models taking into consideration caregiver characteristics.
Effectively training professional caregivers to screen and refer persons with dementia and intellectual/developmental disability
Authors: Walaszek Art , Schroeder Molly , Krainer Jody , Prichett Gregory , Wilcenski Mickell , Endicott Sarah , Albrecht Tammi , Carlsson Cynthia M , Mahoney Jane 
Published: December 2020

AbstractIntroductionBy age 40, almost all people with Down syndrome, the most common cause of intellectual/developmental disability (I/DD), have neuropathological changes consistent with Alzheimer’s disease; by age 60, about half have dementia. Detecting dementia in persons with I/DD can be challenging because baseline cognitive impairment can be severe and because persons with I/DD may have difficulty reporting symptoms. The National Task Group Early Detection Screen for Dementia (NTG‐EDSD) was developed to aid detection of cognitive impairment in adults with I/DD. We implemented an educational curriculum to increase the ability of professional caregivers to screen for dementia in persons with I/DD using the NTG‐EDSD.MethodsIn November 2018 to April 2019, we held five training sessions for professional caregivers of persons with I/DD, partnering with various managed care organizations (MCO), aging and disability resource centers, adult day programs, and adult family homes. We assessed knowledge and attitudes at baseline, immediately after training, and one week, one month and six months after training.ResultsParticipants (N=154) included direct care workers, case managers, healthcare providers, and other social services staff. Participants reported a marked increase in confidence in their ability to detect changes associated with mild cognitive impairment or dementia (p<0.001), decline in activities of daily living (p=0.02), and changes in behavior and affect (p<0.001). Satisfaction with the training was very high, and 94.0% of participants agreed or strongly agreed they could use the NTG‐EDSD tool with their clients. Following the training, one MCO we partnered with, serving 62 of 72 counties in Wisconsin, made the NTG‐EDSD a standard part of the assessment of adults with Down syndrome starting at age 40.DiscussionA wide variety of social services and healthcare professionals can be effectively trained to screen for dementia in persons with I/DD using a standardized screening tool, the NTG‐EDSD. Satisfaction with the training was high, and use of the NTG‐EDSD was thought to be feasible. This educational intervention led to change in practice at a systems level within an MCO. Next steps could include assessing impact of such training on the quality of life and healthcare outcomes of persons with I/DD.
A longitudinal GWAS in patients with mild cognitive impairment identifies modifiers for the speed of cognitive decline
Authors: Kleineidam Luca ,   EADB
Published: December 2020

AbstractBackgroundThe clinical progression of Alzheimer’s disease (AD) is driven by multiple pathophysiological processes but their influence may change over the disease course. Supporting this hypothesis, amyloid pathology shows a rapid increase at early disease stages reaching a plateau as the disease progresses. The impact of genetic determinants of AD may also change over the disease course. In line with that, among AD‐related loci, only variants in APOE and CLU predict conversion from mild cognitive impairment (MCI) to AD‐dementia. These findings led us to propose that genetic factors modulating the speed of disease progression in MCI go beyond AD genetics discovered by case‐control studies. Consequently, a major aim of the EADB consortium is to uncover genetic determinates of the rate of cognitive decline in patients with MCI.MethodGenome‐wide data was generated for 8313 MCI patients and imputed using the TOPMed reference genome. Cognitive decline was operationalized using follow‐up information on the normalized Mini‐Mental‐State‐Examination. To perform the GWAS, a novel method for the fast conduction of genome‐wide association studies (GWAS) and meta‐analysis using longitudinal data was developed based on generalized least squares. All analyses were corrected for age, gender, education, and principal components.ResultSimulation studies suggested that our novel method for longitudinal GWAS provided precise estimates and high statistical power. First analyses of longitudinal cognitive change in 2984 MCI patients revealed a genome‐wide significant effect of APOE (p = 1.3*10−15) and two additional suggestive loci (p < 5*10−7) on chromosome 7 and 10 that have previously been associated with education. Gene‐based test analysis identified two additional genes on chromosome 4 and 12 (p < 2*10−6) that remained significantly associated after Bonferroni‐correction. None of these loci have been linked to AD before. Currently, we are exploring the predictive value that a polygenic risk score derived from the case‐control GWAS of EADB has on progression to dementia in MCI.ConclusionOur GWAS on cognitive decline in the largest sample of MCI patients with longitudinal data to date reveals novel insights into the genetic underpinnings of disease progression in at‐risk stages of AD. Results from the full EADB sample of 8313 MCI patients will be provided at AAIC.
Impact of MR‐guided PET reconstruction on tau detection and quantification with [18F]‐MK‐6240
Authors: Chen Jenny , Schramm Georg , Ades‐Aron Benjamin , Vahle Thomas , Chen Qi , Turner Arlener D. , Royse Sarah , Lopresti Brian , Shepherd Timothy M. , Osorio Ricardo , Fieremans Els 
Published: December 2020

AbstractBackgroundTau PET offers the potential of in vivo imaging neurofibrillary tangles (NFT) in the brain to assess Alzheimer’s disease (AD) progression and help guide the development of disease‐modifying treatments. In this study, we evaluate visualization and quantification of NFT using simultaneous acquisition of MRI and PET using [18F]‐MK‐6240 [1]. To overcome limitations in PET spatial resolution resulting in partial volume effects (PVE), MRI‐guided PET reconstruction using an asymmetrical Bowsher prior [2,3] was tested.MethodCognitively normal volunteers from the NYU Center Sleep and Brain Health Center (n=18, 15 female, age=65.4±5.6) underwent examination on a 3‐T integrated PET‐MRI system (Biograph mMR (Siemens Healthcare, Erlangen, Germany). MRI and PET were performed simultaneously; MRI contrasts included MPRAGE (1‐mm isotropic) for anatomy and ultrashort echo‐time (UTE) (1.6‐mm isotropic) for attenuation correction. [18F]‐MK‐6240 was injected intravenously and PET data was reconstructed 70‐90 min post‐injection. Standard iterative reconstruction (OSEM) (2‐mm isotropic) was compared to asymmetrical Bowsher [2,3] reconstruction with MPRAGE prior regularization weight β=30 (1x1x2mm3). PET standard uptake value (SUV) maps were co‐registered to respective MPRAGE, and (cerebellum or pons normalized) SUVR values were extracted from FreeSurfer‐derived regions of interest (ROIs).ResultsExample SUVR maps of standard PET and MR‐guided PET (Fig.1) reveal the Bowsher reconstruction to have more localized and increased focal uptake in the amygdala and cortical regions including the entorhinal, posterior cingulate and precuneus, with regional SUVR‐increases of 39%, 53%, 32%, and 16% respectively. Over all subjects (Fig.2), Bowsher reconstruction results in 30% or 48% higher SUVR, and an 64% or 84%‐increase of dynamic SUVR‐range (Fig.3) when normalized versus cerebellum or pons, respectively. These trends are emphasized for entorhinal cortex (Fig.4).ConclusionsThese initial results demonstrate that MR‐guided PET reconstruction of tau data may improve NFT localization and quantification. Study limitations include small number of high uptake tau‐cases and lack of standard such as histology for comparison. Future work will compare against CSF tau‐markers, cognition and comparison to other PVE correction methods. References: [1] Betthauser et al, JNM 2018;60(1):93–99; [2] Bowsher et al, Proc. IEEE Nucl. Sci. Symp., 2004(4):2488–2492; [3] Vunckx & Nuyts, Proc. IEEE Nucl. Sci. Symp., 2010:3262–3266.
Characterising the spatiotemporal heterogeneity of neurodegenerative diseases using subtype and stage inference
Authors: Young Alexandra L , Bocchetta Martina , Cole James , Williams Steven CR , Rohrer Jonathan D , Alexander Daniel C 
Published: December 2020

AbstractBackgroundNeurodegenerative diseases are highly heterogeneous, consisting of multiple disease subtypes with different spatiotemporal patterns of pathology. These patterns evolve dynamically with disease stage, making it challenging to disentangle disease subtypes in vivo from biomarker data where precise staging information is unavailable.MethodSubtype and Stage Inference (SuStaIn) is an unsupervised learning technique that disentangles biomarker heterogeneity into subgroups of individuals (subtypes) with distinct progression patterns (stages). SuStaIn evaluates the optimal grouping of individuals into disease subtypes, where each subtype consists of a sequence in which biomarkers transition between different z‐scores. We used SuStaIn in a number of conditions to identify subgroups of individuals with distinct patterns of brain volume loss using structural MRI data. We present results from several datasets, reviewing results in Alzheimer’s disease (ADNI dataset), and presenting new results in genetic frontotemporal dementia (GENFI dataset), and in the aging population (UK Biobank). In each dataset we explored genetic, neuropsychological, clinical and biomarker associations with each of the subtypes identified by SuStaIn. We used longitudinal data to assess the consistency of the subtypes and stages assigned by the SuStaIn model at follow‐up visits.ResultIn Alzheimer’s disease we identified multiple spatiotemporal patterns of neurodegeneration associated with differences in memory and executive function scores. We found a genetic link between a ‘limbic‐predominant’ atrophy pattern and type 2 diabetes through a GWAS and analysis of polygenic risk scores. In genetic frontotemporal dementia we identified and confirmed two distinct atrophy patterns amongst C9orf72 mutation carriers (N=182). In MAPT mutation carriers (N=82), we identified two atrophy subtypes that were strongly associated with different MAPT mutations: a ‘temporal’ subtype, which had a one‐to‐one mapping with IVS10+16 and R406W mutations, and a ‘frontotemporal’ subtype, which had a near one‐to‐one mapping with P301L mutations. The subtype assignments showed strong stability at follow‐up visits (99% consistency). In the UK Biobank (N=21390), we identified multiple patterns of brain volume loss associated with distinct characteristics.ConclusionOur results demonstrate the utility of SuStaIn for identifying disease subgroups and associating imaging patterns with genetics and cognition. We show that SuStaIn can provide enhanced patient stratification capability across multiple conditions.
Latent patterns of task‐related functional connectivity relate to hyperactivation and associative memory impairment in SCD+ and MCI
Authors: Corriveau‐Lecavalier Nick , Rajah Natasha , Mellah Samira , Belleville Sylvie ,   CIMA‐Q
Published: December 2020

AbstractBackgroundHyperactivation is commonly observed in prodromal Alzheimer’s disease (AD). It is however unknown if it relates to functional network dysfunction, and how hyperactivation‐networks relate to cognitive impairment. We used seed‐based connectivity to assess differences in correlations between activation of hyperactive regions, whole‐brain task‐related activation, and memory performance in persons with subjective cognitive decline plus (SCD+) and mild cognitive impairment (MCI).MethodData from 108 participants from the CIMA‐Q cohort were used in this study: 28 participants with SCD+ which presented with memory complaint and worry in addition to small hippocampal volume and/or were APOE4 carriers, 26 participants with MCI and 54 were healthy controls (HC). Task‐related activation was measured while participants memorized 78 pictures and their location in a four‐position grid. Multivariate seed‐partial least squares (seed‐PLS) analysis was used to identify latent variables (LVs) that assess between‐group differences and similarities in the three‐way association between 1) activation in hyperactive regions of interest (ROIs: left hippocampus, right inferior temporal gyrus (riTG), left superior parietal lobule (lsPL)), 2) whole‐brain activation associated with associative memory encoding, and 3) subsequent associative memory performance. Significance of the seed‐PLS effects were assessed with permutation testing and boostraps.ResultThree LVs were significant (p < 0.05). LV1 (32.11 % of covariance explained) accounted for group similarities in the correlation between activity in all ROIs and activity in the fronto‐parietal and default mode networks. Interestingly, left hippocampus activity did not correlate in SCD+. LV2 (19.17 % of covariance explained) identified a network that was correlated with left hippocampal activity in all three groups; however, left hippocampal activity correlated with better memory in HC but with poorer memory in SCD+. LV3 (10.91 % of covariance explained) identified a network that was positively correlated to lsPL activity in SCD+, and correlated with seed activity in all ROIs and poorer memory performance in MCI.ConclusionHyperactivation is associated with latent patterns of connectivity in prodromal AD, but different hyperactivation‐network associations relate to memory in SCD+ and MCI. Hyperactivation could serve as an early marker of network dysfunction in AD, and reflect the incoming cognitive symptomatology associated with the disease.
Obstructive sleep apnea in older adults: Differential cognitive impairment moderated by sex?
Authors: Legault Julie , Thompson Cynthia , Martineau‐Dussault Marie‐Ève , Carrier Julie , Dang‐Vu Thien Thanh , Lorrain Dominique , Gosselin Nadia ,   CIMA‐Q Group
Published: December 2020

AbstractBackgroundObstructive sleep apnea (OSA) is a risk factor for cognitive decline, but the effect of sex on this association is unknown. This study aims at characterizing the relationship between risk of OSA and cognitive function in older men and women.MethodWe included 152 women (73 ± 6 years) and 89 men (75 ± 6 years) matched for education, age and presence of APOE4 allele. They were part of the Quebec Consortium for Early Identification of Alzheimer’s Disease (CIMA‐Q) and were either cognitively healthy or had subjective cognitive decline or mild cognitive impairment. All participants were tested with a neuropsychological battery measuring cognitive domains typically affected by Alzheimer’s disease. Risk of OSA was determined using a validated questionnaire that considers signs and symptoms associated with OSA such as snoring (S), tiredness (T), observation of apneas (O), high blood pressure (P), high body mass index (B) and larger neck circumference (N), which provides a risk score (STOP‐BN). Multiple linear regressions were performed between STOP‐BN and cognitive scores in men and women separately.ResultHigher risk of OSA, identified by a higher score on the STOP‐BN, is correlated with slower information processing speed (Stroop, condition 2) in women (β= 0,896, p = 0,006) and men (β= 0,954, p = 0,043). In men, higher risk of OSA correlated with worse performance in short (Digit symbol, incidental learning score: β = 0,982, p = 0,034) and long‐term memory (Face‐name associations, delayed recall: β = 0,318, p = 0,047).ConclusionOur results suggest that sex has a moderating effect on the association between OSA and cognitive function. An altered information processing speed has already been reported in apneic patients and does not necessarily reflect a risk of dementia. However, altered memory in men at higher risk of OSA needs to be investigated longitudinally to determine whether OSA could represent an early marker of cognitive decline.
Metabolic syndrome and successful aging: A six‐year cohort study TIGER among community‐dwelling elderly in Taiwan
Authors: Lin Yi‐Hsuan , Chen Yen‐Ching , Chiou Jeng‐Min , Chen Ta‐Fu , Lai Liang‐Chuan , Chen Jen‐Han 
Published: December 2020

AbstractBackgroundMetabolic syndrome (MetS) has known to be associated with disability1, 2, cognitive impairment3 and depression4 in the older adults. However, the association between MetS and successful aging, an overall assessment of elders’ status, is unknown.MethodThis study is part of an ongoing prospective cohort study: Taiwan Initiatives for Geriatric Epidemiological Research (TIGER). A total of 605 participants (age 65+) were recruited at baseline (2011‐2013) with 4‐year and 6‐year follow‐ups. After exclusion of participants with missing data of successful aging and metabolic syndrome as well as loss to follow‐up, a total of 202 participants were included for statistical analysis. MetS was assessed at baseline (2011‐2013). Successful aging was evaluated at baseline, 4‐year and 6‐year follow ups. Successful aging was defined by the following variables: cognitive function, numbers of chronic disease, activity of daily living (ADL), instrumental activities of daily living (IADL), gait speed, depression, self‐rated health, the frequency of participating in social and leisure activities, the family support and annual disposable income. Generalized linear mixed‐effects models with random intercept were utilized to assess the association between MetS and successful aging adjusting for time (follow‐up years), age, sex, years of education, smoking, alcohol consumption and the interaction terms with time. A p value of <0.05 (two‐tailed) for individual covariate and <0.1 for interaction with time was considered statistically significant.ResultsAt baseline, 33.7% (n=68) older adults had MetS. Compared with older adults without MetS, those with MetS had lower diet quality (the modified Alternative Healthy Eating Index: 34.8 vs. 38.2), higher body mass index (25.7 vs. 22.9 kg/m2), higher mean serum C‐reactive protein level (0.26 vs. 0.17 mg/dL), and more chronic diseases [e.g., hypertension (70.6% vs. 30.6%), diabetes mellitus (27.9% vs. 2.2%), hyperlipidemia (70.6% vs. 35.1%) and cardiac disease (29.4% vs. 15.7%)]. The baseline MetS had a negative effect on the probability of successful aging, and the effect increased as time elapsed [MetS×time interaction: odds ratio=0.87, 90% confidence interval=0.76‐0.98, p‐value=0.06].ConclusionMetS is a risk factor of successful aging for community‐dwelling older adults. Prevention of MetS in earlier life will be beneficial to successful aging in their later life.