bluuebunny/crossref_metadata_2025 huggingface dataset:
Association of ideal cardiovascular health metrics and cognitive function in older adults: A population‐based study
Authors: Han Xiaolei , Wang Yongxiang , Du Yifeng , Qiu Chengxuan
Published: December 2020

Background

The American Heart Association (AHA) proposed the Life Simple’s 7 to promote cardiovascular health (CVH): four behaviors (e.g., smoking, body mass index (BMI), physical activity, and diet) and three biological factors (e.g., blood pressure, total cholesterol, and fasting blood glucose). We aimed to examine the association of ideal CVH metrics with cognitive performance and dementia among older adults living in the rural communities in China.

Method

This community‐based study included 4868 participants from the Multidomain Interventions to Delay Dementia and Disability in Rural China (MIND‐CHINA), who were aged ≥65 years (mean 71.5 years; 57.2% women). Data on demographic features and CVH metrics were collected through face‐to‐face interviews, clinical examinations, and laboratory tests. The six CVH metrics (except diet) were defined according to the modified AHA recommendations, and participants were divided into concurrently having ≤2 (reference), 3, 4, and ≥5 ideal CVH metrics. Global cognitive function was assessed with the Mini‐Mental State Examination (MMSE). Diagnoses of dementia were reached according to the DSM‐IV criteria. Data were analyzed using multiple binary logistic and general linear regression models.

Result

Of all participants, 31.8% had ≤2, 34.6% had 3, 24.8% had 4, and 8.8% had ≥5 ideal CVH metrics. Multiple logistic regression analysis showed that ideal physical activity (OR = 0.70; 95% CI, 0.52–0.94) and ideal fasting blood glucose (FBG) (OR = 0.37; 95% CI, 0.25–0.54) were associated with a reduced likelihood of dementia. Multiple general linear regression analysis suggested that ideal individual CVH metrics (vs. poor levels) that were significantly associated with MMSE score were physical activity (β = 0.414; 95% CI, 0.119‐0.709), BMI (β = ‐0.751; 95% CI, ‐1.127‐ ‐0.375), and FBG (β = 0.729; 95% CI, 0.243‐1.214). The composite measurement of CVH metrics was not significantly associated with either dementia and MMSE score.

Conclusion

In this cross‐sectional study, the composite measure of CVH metrics is not associated with global cognitive function among rural‐dwelling Chinese older adults, although optimal physical activity and ideal FBG are associated with good global cognitive performance and a low likelihood of dementia.
Amyloid‐β deposition in cognitively normal oldest‐old is associated with cortical thinning and faster memory decline
Authors: Pelkmans Wiesje , Legdeur Nienke , Kate Mara ten , Yaqub Maqsood , Barkhof Frederik , Van Berckel Bart N.M. , van Der Flier Wiesje , Visser Pieter Jelle , Tijms Betty M.
Published: December 2020

Background

The Alzheimer’s disease (AD) pathological cascade is hypothesized to start with the accumulation of amyloid‐β (Aβ). However, the precise effect of Aβ deposition on cognitive decline in the oldest‐old remains controversial, since very old individuals can have intact cognition despite abnormal AD biomarkers. Here we studied, in cognitively normal individuals of 90 years and older, the impact of Aβ on structural brain integrity and the association of Aβ and structural brain integrity on decline over time in memory functioning.

Method

Fifty‐seven cognitively normal individuals (age mean±sd = 92.7±2.9) were selected from the EMIF‐AD 90+ study. Aβ status was determined by visual reads on [18F]‐flutemetamol PET (normal=Aβ‐, abnormal=Aβ+); cortical thickness and hippocampal volume were quantified on structural MRI with FreeSurfer and FSL, respectively. Cortical thickness was computed according to the Desikan‐Killany atlas and averaged across hemispheres. Hippocampal volume was normalized for intracranial volume. Memory performance was evaluated using a composite score of the CERAD (delayed recall), Logical Memory (delayed recall), Rey Complex Figure (delayed copy), and the Visual Association Test, that were repeated after 20 months (n=43). Effects of Aβ status, regional cortical thickness, hippocampal volume, time, and their interactions on memory function were assessed with linear mixed models, adjusted for age and sex.

Result

Roughly one out of three (n=19; 33%) individuals had an abnormal amyloid PET (Table1). Compared to Aβ‐, those with Aβ+ showed at baseline a thinner parahippocampal and medial orbitofrontal cortex (p<.05; Fig.1), while hippocampal volume did not differ. Over time, Aβ+ individuals showed a steeper decline (β±SE=‐.27±.09; p<.01;) on memory performance than Aβ‐ (Fig.1). Faster memory decline was also predicted by cortical thinning in predominantly temporal regions in the whole group (Fig.1).

Conclusion

In the oldest‐old with initially intact cognition, Aβ pathology was associated with a thinner cortex and faster decline in memory performance. These results suggest that Aβ abnormality, even in the oldest old with apparent high reserve and maintenance mechanisms, is indicative of active neurodegeneration. Other pathologies may also contribute to decline in the oldest old as a thinner temporal lobe predicted decline in memory irrespective of Aβ pathology.
Dementias Platform UK (DPUK): Facilitating cross‐cohort analysis in a digital age
Authors: Bauermeister Sarah D
Published: December 2020

Background

Dementias Platform UK (DPUK) is a £53M public‐private partnership established by the MRC to provide access to large‐scale cohort data and accelerate the research and discovery of new treatments for dementia. The DPUK Data Portal facilitates multi‐modal remote data access to 3.4M individuals from 42 cohorts using a secure, robust, persistent, and fully auditable data repository. To facilitate the analysis of multiple independent datasets, DPUK curates cohort data to the C‐Surv data model. This model standardises data structure, variable naming and value labelling conventions to reduce data pre‐processing times and reduce unwanted variation. C‐Surv also enables the harmonisation of datasets for analysis feasibility testing. We present the C‐Surv ontology and demonstrate its impact on data discovery and knowledge management for multi‐cohort, multi‐modal analysis in dementia research.

Method

Ontology: The C‐Surv ontology has 22 level‐1 and 132 level‐2 categories, written to be machine‐readable for mapping to other ontologies and is optimised for cohort (survey) data. C‐Surv accommodates heterogeneous data‐types across cohorts. Higher order data (imaging, genetics, devices) are pre‐processed prior to curation. Researchers may request access to native or curated data.

Results

Standardisation: C‐Surv standardisation process: standardised naming structure of variables – maximum coding structure of 12 uppercase alphanumeric characters selected, with 5 additional characters for the imaging, linkage, genomic categories and accelerometer data. An intuitive coding structure is adopted whereby syllable‐based acronyms, word fragments, abbreviations and minimal numeric characters are utilised. Harmonisation: C‐Surv provides a harmonised dataset of 30 common data elements (variables) which are widely used in neurodegenerative and bio‐epidemiological research, and can be visualised in the DPUK Cohort Explorer. The C‐Surv standard data structure allows efficient data discovery and data selection. Building on the DPUK Cohort Matrix and Cohort Directory, the C‐Surv standard data structure provides a framework for the development of ergonomic data discovery and data selection tools.

Conclusion

The C‐Surv ontology is a data model optimised for analysis of epidemiologic survey data. It enables analysts to conduct multi‐cohort multi‐modal analyses rapidly; offering reduced administrative load to researchers and data managers. It also reduces artifactual variation in data due to non‐standard data pre‐processing.
Pattern recognition to objectively differentiate the etiology of cognitive decay in longitudinal cognitive data: Analysis of stroke, Alzheimer’s disease, and normal aging
Authors: Clouston Sean , Richmond Lauren , Scott Stacey , Luhmann Christian , Natale Ginny , Hanes Douglas , Zhang Yun , Smith Dylan
Published: December 2020

Background

Estimates suggest that Alzheimer’s disease and stroke account for a majority of age‐related cognitive decay. This study utilized novel pattern‐recognition protocols to estimate the extent to which cognitive decay might be attributable to Alzheimer’s disease and stroke.

Method

Secondary analyses of data collected for the Health & Retirement Study (N=17,579) were used to objectively type Alzheimer’s disease and stroke‐related cognitive decay. Patterns of decay in episodic memory were the measure, while rate of linear decay in episodic memory and, separately, in orientation were the outcome.

Result

After adjusting for demographics, Alzheimer’s disease and stroke accounted for approximately half of age‐associated decay in cognition (51.07‐55.6% for orientation and episodic memory respectively) and explained variance attributed to random slopes in longitudinal multilevel models.

Conclusion

Results support prior histopathological and neuroimaging efforts suggesting that approximately half of cognitive decay, commonly attributed directly to aging, may be due to stroke and other cerebrovascular disease, and Alzheimer’s disease.
Differences on autobiographical memory in healthy aging and Alzheimer’s disease
Authors: Escudero Joaquin V. , Melendez Juan C. , Satorres Encarnacion
Published: December 2020

Background

Autobiographical memory (AM) refers to memories from one’s past that are characterized by a sense of subjective time and autonoetic consciousness which involves a feeling of re‐experiencing or reliving the past. Cognitive aging research indicates age‐related deficits in episodic AM, whereas semantic AM is unimpaired in healthy older adults. Regarding research involving subjects with dementia had showed that episodic memories deteriorate rapidly in Alzheimer's disease (AD), whereas semantic memories are preserved until moderate stages. This study aims to compare healthy older adults and AD patients, on the type of AM in order to identify differences between the groups.

Method

Thirty patients with initial AD, and 46 healthy older participants matched on age and education took part in the present study. Participants underwent a neurological and neuropsychological assessment. To evaluated AM, Autobiographical Memory Interview (AMI) was applied. AMI is a semi‐structured interview, applicable to subjects from 18 years old, that evaluates the two components of AM: semantic and episodic. For the study, MANOVA was performed to determine whether there were differences between groups on AM components.

Result

The multivariate contrasts revealed a main effect of group (Λ = .701; F(2, 73) = 85.57; p < .001). Therefore, post hoc Tukey tests were performed for each dependent variable, and significant differences were obtained on all the measures studied. Healthy older people obtained higher score than AD on the episodic AM (F(1, 75) = 8.14; p < .001) and on semantic AM (F(1, 75) = 164.5; p < .001).

Conclusion

Autobiographical recall in AD is mainly characterized by a substantial loss of episodic and semantic information, leading to a decontextualization of autobiographical memories and a shift from mentally reliving past events to a general sense of familiarity. This decline is exacerbated by anterograde and retrograde amnesia, leaving AD patients with limited access to memories that shape self‐consciousness, self‐knowledge, and self‐images.
Prediction of longitudinal clinical outcomes of MCI population using Alzheimer’s AT[N] biomarker profiling: Can machine learning methods improve our predictions?
Authors: Ezzati Ali , Harvey Danielle J. , Davatzikos Christos , Truelove‐Hill Monica , Sreepada Lasya P , Pomponio Raymond , Zammit Andrea R , Jack Clifford R , Aisen Paul S , Lipton Richard B
Published: December 2020

Background

The NIA‐AA Research Framework on Alzheimer’s disease (AD) represents an important advance in the biological characterization of the AD spectrum. While this framework predicts disease progression, definitions of amyloid, tau, and neurodegeneration positivity based on cut‐scores may limit the performance of predictive models.

Method

252 cognitively normal (CN), 424 amnestic mild cognitive impairment (aMCI) and 128 AD participants were included in this study. aMCI participants at baseline were classified using 2 different methods: 1) Using conventional AT[N] criteria based on proposed cut‐offs in CSF or brain imaging measures: participants were classified on the AD continuum (A+T‐N‐, A+T+N‐, A+T‐N+, A+T+N+) and non‐AD continuum (all other subgroups); and 2) using a machine learning (ML) based method (ensemble linear discriminant model built using CN and AD participants) to classify MCI participants as CN‐like or AD‐like based on continuous CSF biomarkers, regional amyloid PET, FDG‐PET, and volumetric MRI (variables contributing to AT[N] classification; Table 1). Predictive performance of AT[N]‐based classification and ML‐based classification were assessed using clinical outcomes at 0.5, 1, 2, 3, 4, and 5 years of follow‐up.

Result

A total of 414 aMCI participants had at least one wave of follow‐up (N of 397, 400, 346, 297, 238, and 93 at 0.5, 1, 2, 3, 4, and 5 years, respectively). The progression rate from aMCI to AD was 5.8% at 6m, 9.5% at 1y, 17.9% at 2y, 19.9% at 3y, 20.2% at 4y, and 15% at 5y of follow‐up. Presence of AD pathology at baseline (AT[N]‐based AD continuum) predicted progression to AD with high sensitivity but modest specificity during follow up (Table 2). ML‐based classification was less sensitive but substantially more specific. ML‐based classification models were significantly more accurate than AT[N]‐based classification at all follow‐up periods (McNemar test, p‐value<0.001 for all).

Conclusion

A single cut‐point approach used in AT[N] classification lacks accuracy when research questions require high diagnostic or prognostic certainty. A multivariate approach using ML methods can improve accuracy of prediction of disease progression. PPVs were higher at all follow‐up time points for ML‐based classification, indicating that progression to AD occurs at a higher rate in persons identified by ML.
Gray and white matter damage are associated with motor symptoms in Parkinson’s disease
Authors: Dadar Mahsa , Gee Myrlene , Duchesne Simon , Camicioli Richard
Published: December 2020

Background

Previous studies have found associations between atrophy in Substantia Nigra (SN) and White Matter Hyperintensities (WMH) of vascular origin and motor deficits in Parkinson’s disease (PD) patients (Zeighami et al. 2015, Pozorski et al. 2019). Here we assess the relationship between WMHs and SN atrophy and motor symptoms in PD.

Method

Data included 50 PD patients and 45 age‐matched controls with T1‐weighted and FLAIR scans at baseline, month18, and month36. WMHs were segmented using T1‐weighted and FLAIR images and a random forests classifier (Dadar et al. 2017, Figure 1.a). Deformation‐based morphometry was used to measure atrophy in Substantia Nigra (SN) (Figure 1.b, Ashburner et al 1998). The relationship between MRI features and clinical scores was assessed using mixed‐effects models: where Cohort denotes a categorical variable contrasting PD versus controls, and ID denotes the categorical random effects. The variables of interest were MRI‐Feature (implying an overall association between the MRI feature and clinical score of interest) and the interaction term Cohort:MRI‐Score (implying an additional PD‐specific impact of the MRI‐Feature on the Clinical‐Score). Log‐transformed WMH volumes and mean DBM score in left and right SN were used as MRI features. The motor subscore of Unified Parkinson's Disease Rating Scale (UPDRSIII) was used as the dependent variable of interest, reflecting motor deficits.

Result

WMH load significantly increased with age in both groups (t=9.95, p<0.0001). We did not find a significant group difference in WMH volumes. However, WMH load was significantly associated with UPDRSIII in PDs (t=2.63, p=0.008), but not in controls (t=0.02, p=0.86), with a marginal interaction (t=1.67, p=0.05, Figure 2). DBM in both left and right SN significantly decreased with age (tLeftSN=‐5.79, tRightSN=‐6.33, p<0.0001), and were significantly different between the cohorts (Figure 3, tLeftSN=‐4.19, tRightSN=‐3.95, p<0.00001). UPDRSIII significantly increased with age (t=4.75, p<0.00001) and decrease in SN DBM (tLeftSN=‐2.02, tRightSN=‐1.88, p<0.05), with a significantly greater impact in PDs (Figure 4, tLeftSN=‐2.10, tRightSN=‐1.73, p<0.04).

Conclusion

In our sample, both SN atrophy and WMH burden were significantly associated with additional motor deficits in PD, implying an additive contribution of both gray and white matter damage to the motor deficits in PD.
Risk factors of participants in the Systematic Multidomain Alzheimer’s Risk Reduction Trial (SMARRT)
Authors: Peltz Carrie , Rosenberg Dori E , Fleckenstein Lynn E , Barnes Deborah E , Dublin Sascha , Balderson Benjamin H , Larson Eric B , Yaffe Kristine
Published: December 2020

Background

Up to 30% of dementia may be preventable by addressing modifiable risk factors. The Systematic Multidomain Alzheimer’s Risk Reduction Trial (SMARRT) is an on‐going two‐year pilot trial in the US comparing a personalized risk reduction intervention to usual care among at‐risk older adults without dementia in an integrated health care system. Here we show the constellation of risk factors experienced by older adults in the SMARRT trial, and which factors individuals in the intervention arm have chosen to target.

Methods

SMARRT recruited participants aged 70‐89, without dementia, and with at least two risk factors verified by electronic medical records or validated questionnaires. Intervention participants work with a health coach and nurse to develop a personalized action plan to address risk factors of their choosing. Chi square tests were used to compare risk factors across men and women.

Results

Of the 148 participants enrolled as of January 2020, the average age was 76±5.1 years, 66% were male, and 80% were white. The most common risk factors were physical inactivity (80%), poorly controlled hypertension (50%), and sleep difficulty (48%) followed by taking medications that may affect cognition (19%), depressive symptoms (18%), poorly controlled diabetes (14%), social isolation (12%), and smoking (9%). Taking risky medications, poor sleep, and depressive symptoms were all more common in women while physical inactivity was more common in men (all p<0.01; see Table). In the intervention group (n=73), most people with poorly controlled hypertension (94%), physical inactivity (92%), and poorly controlled diabetes (83%) chose to work with their health coach or nurse to reduce those risks. Getting better sleep (66%), decreasing risky medications (62%), quitting smoking (50%), reducing depression (43%), and increasing social engagement (27%) were also targets of intervention in people with those risk factors.

Conclusions

Older adults with dementia risk factors are willing to make health and lifestyle changes as well as suggested changes to medical care to potentially lower their dementia risk. The SMARRT intervention may provide valuable information to shape future studies of behavior change to reduce dementia risk.
Utilizing electronic medical record data to predict onset of Alzheimer’s disease and related dementias
Authors: Marra David E , Miller Amber H. , Li Qian , Yang Xi , Smith Glenn E. , Wu Yonghui , Bian Jiang , Maraganore Demetrius M
Published: December 2020

Background

As the population ages, the incidence of Alzheimer’s disease and related dementias (ADRD) are expected to rise and cause a significant burden to the world economy and healthcare systems. Pharmaceutical trials to cure ADRD have largely proven unsuccessful. Therefore, there is a critical need for early identification and intervention for individuals at risk of ADRD to prevent or delay disease onset.

Method

Using electronic medical record (EMR) data from a large, academic medical center, a historical cohort of Floridians aged 50 and older who developed ADRD were identified, along with an age and sex‐matched referent group. Discrete diagnostic codes, medication history, and biomarkers were used to develop 1, 3, and 5‐year ADRD machine learning‐based prediction models through theory‐driven and data‐driven approaches.

Result

A cohort of 59,799 subjects were identified as meeting study criteria, including 5,711 diagnosed with ADRD during the study period. Approximately five controls (n = 18,765) for each patient were matched by birth year and sex. In the theory‐driven experiment, the logistic regression model achieved the area under the curve (AUC) of .664 for 1‐year ADRD prediction, .635 for 3‐year prediction, and .650 for 5‐year prediction. Further analysis exhibited that age, ethnicity, stroke, and history of traumatic brain injury had the highest odd’s ratios for ADRD development; whereas, use of NSAIDs and hormone‐replacement therapy was associated with reduced risk of ADRD (See Table 1). Compared to the theory‐driven models, the data‐driven models (gradient boosting trees) improved the AUC by ∼0.06 for 1‐ and 3‐year prediction.

Conclusion

Using widely available EMR data, a large cohort of adults who developed ADRD and matched controls were used to create 1, 3, and 5‐year prediction models. These models can be adopted in decision‐support systems for detecting individuals at high‐risk of developing ADRD, allowing for interventions to be implemented in a timely manner. Our future research will replicate these models with data from the OneFlorida Clinical Research Consortium, a data repository including 15 million patients, covering more than 60% of the Florida population. These models will be externally validated via neuropsychological assessment before EMR‐tool kits are disseminated to medical practitioners across the state of Florida.
Cumulative cognitive deficits of Lewy body disease and Alzheimer’s disease neuropathology
Authors: Ryman Sephira , Yutsis Maya , Tian Lu , Henderson Victor , Montine Thomas J. , Salmon David P. , Galasko Doug R. , Poston Kathleen
Published: December 2020

Background

Alzheimer’s disease neuropathologic change (ADNC) may contribute to the emergence of dementia in patients with Lewy body disease (LBD) and may act synergistically with LBD. It is unclear to what extent LBD is a domain‐specific predictor of cognitive impairment in isolation and in combination with ADNC.

Method

Data from the National Alzheimer’s Coordinating Center database was obtained for 2,433 participants with antemortem longitudinal neuropsychological assessment and postmortem neuropathological assessment. We employed a novel measurement of cognitive impairment that incorporates information about the individual’s initial deviation from normative performance and decline over time. We compared domain‐specific cumulative cognitive deficits in LBD, ADNC, and combined LBD/ADNC at three pathologic stages of LBD (brainstem, limbic, and cerebral cortical).

Result

This study included 111 participants with LBD only, 741 participants with combined LBD/ADNC, 1,357 participants with ADNC only, and 224 healthy controls (HC). Limbic and cerebral cortical LBD groups exhibited similar executive/visuospatial deficits as combined ADNC and LBD impacting the limbic and cerebral cortical regions. The cerebral cortical LBD group demonstrated a significantly greater executive/visuospatial deficit relative to ADNC only. In contrast, ADNC and ADNC/LBD groups demonstrated significantly greater cumulative memory deficits relative to HC and LBD only groups, across all LBD pathologic stages.

Conclusion

The results of the current study demonstrate that the impact of ADNC and LBD pathology on cognition differs based on the cognitive domain examined and the state of progression of LBD pathology. Limbic and cerebral cortical Lewy body pathologies impact executive/visuospatial functioning independent from the impact of ADNC. In contrast, a greater memory impairment is driven by ADNC, with relatively weaker deficits observed in the LBD only groups. These findings have relevance for predicting progression in Lewy body diseases. Further, detailed characterization of cognitive phenotypes of LBD is crucial for the development of effective disease‐modifying therapeutic trials.
Cognitive characteristics of older adults with history of concussion
Authors: Maietta Julia E. , Caldwell Jessica Z.K. , Hawley Nanako , Cummings Jeffrey L. , Miller Justin B.
Published: December 2020

Background

Concussion is a common injury, and among older adults often results from falls (Thompson, McCormick, & Kagan, 2006). There is some evidence to suggest that older adults with a history of concussion show higher mortality rates than their younger counterparts, as well as increased risk for developing neurodegenerative diseases (such as Alzheimer’s Disease [AD]; Becker, Kapogiannis, & Greig, 2018; Thompson et al., 2006). However, the literature on risk for neurocognitive decline in those with concussion history is limited, and the available evidence is conflicting (Abner et al., 2014). The current study aims to add to the literature regarding the cognitive differences between older adults with and without concussion in a well‐characterized cohort of patients with AD.

Method

This retrospective study investigated cognitive differences in individuals with and without self‐reported concussion history [CH] taking into account age and education level. Participants were enrolled in the Center for Neurodegeneration and Translational Neuroscience and included 52 cognitively normal controls (13 with CH), 68 mild cognitive impairment [MCI] (24 with CH), and 24 mild AD (8 with CH). Cognitive domains assessed included: Global cognitive (MoCA); verbal memory (WMS‐IV Logical Memory; RAVLT); non‐verbal memory (BVMT‐R); attention/working memory (WAIS‐IV Digit Span); verbal set‐shifting (DKEFS Verbal Fluency); and processing speed (SDMT).

Result

Omnibus tests did not reveal a significant difference between those with and without CH in the CN, MCI, or AD, groups after taking into account age at time of evaluation and education [CN – F(14,35)=1.20, p>.05; MCI – F(14,46)=0.50, p>.05; AD – F(9,1)=0.66, p>.05, respectively]. Effect sizes (Cohen’s d) for the CN group ranged from small to medium (min=0.1, max=0.7). For MCI, effect sizes were small (min=0.0, max=0.3). For AD, effect sizes ranged from small to medium (min=0.0, max= ‐0.7).

Conclusion

Results suggest that there are no meaningful differences in cognitive test scores between individuals with and without history of self‐reported concussion after accounting for influences of age and education. Effect sizes were medium despite non‐significant ANCOVAs, suggesting that these results are under‐powered and that future research would find significant results with larger samples. Small sample size and uncertainties regarding self‐report of concussion are limitations of this study.
SUccessful Caregiver Communication and Everyday Situation Support in dementia care (SUCCESS): Using technology to support caregivers
Authors: Caspar Sienna , Garschall Markus , Sfetcu Raluca , Himmelsbach Julia , Fassl Flora
Published: December 2020

Background

Caregivers of people with dementia (PwD) are diverse—they live in urban and rural locations, have varying educational backgrounds, different access to resources, different relationships to the care recipient, etc. However, one common feature of all caregivers is the need to have access to education and support on their caregiving journey. Technology provides a feasible way to reach such a large and diverse population. SUccessful Caregiver Communication and Everyday Situation Support in dementia care (SUCCESS) provides an innovative training and coaching application on a mobile device (an App) to support formal and informal caregivers of PwD. Through the use of an affective avatar, the SUCCESS App aims to help caregivers better understand dementia and related behaviours and learn communication methods grounded on the principle that opinions and needs of PwD should be acknowledged, respected, and addressed. The avatar also assists caregivers in focussing on the remaining abilities of the PwD; thereby, helping to support PwDs’ continued engagement in meaningful activities. Finally, the avatar acts as a wellness coach to help ensure caregivers remain as resilient as possible by encouraging caregivers to actively engage in individualized self‐care activities.

Methods

The SUCCESS App was evaluated in a pilot study in two countries using a pre‐post design. Participants included 63 carers of PwD located in Austria (n=26) and Romania (n=37). Quantitative and qualitative data was collected at baseline, 1‐month, 3‐months and 6‐ months. The primary outcome was satisfaction with care. Secondary outcomes included care‐related knowledge, experience of burden, and the presentation of behavioural and psychological symptoms of dementia by the PwD.

Results

Preliminary analysis of the qualitative data demonstrates the majority of the participants found the application to be very useful and practical; they also indicated they planned to continue to use it once the trial was over because it helped them to have a better understanding of what dementia is and assisted them in tangible ways as they provided care to PwD.

Conclusions

Initial results indicate that the SUCCESS App has the potential to provide information and support to caregivers in a highly accessible way that is both useful and feasible.
Extrastriatal dopaminergic and serotonergic pathways in Alzheimer’s disease: A 123I‐FP‐CIT study
Authors: Pilotto Andrea , Caminiti Silvia , Liguori Claudio , Garibotto Valentina , Presotto Luca , Sala Arianna , Turrone Rosanna , Caratozzolo Salvatore , Scalvini Andrea , Rozzini Luca , D'Amelio Marcello , Mercuri Nicola , Paghera Barbara , Premi Enrico , RIzzetti Cristina , Stefani Alessandro , Padovani Alessandro , Perani Daniela
Published: December 2020

Background

Pathological reports suggest that dopaminergic and serotonergic pathways are early involved in Alzheimer’s disease (AD). 123I‐FP‐CIT SPECT imaging allows the evaluation of both dopamine transporter (DAT) and serotonin transporter (SERT) in several brain regions.

Method

Alzheimer’s disease patients were included in a multicenter study and underwent a standardized neurological examination, structural imaging and CSF, amyloid and metabolism imaging in order to reach a biomarker diagnosis of AD (i.e. A+T+N+ classification). Each patient underwent 123I‐FP‐CIT SPECT imaging and the bindings of extrastriatal regions of interests were calculated from spatially normalized images. The occipital‐adjusted specific to non‐displaceable binding (SBR) in the different regions was compared between AD and controls adjusting for the effect of age, sex, disease duration and serotonergic/dopaminergic treatment.

Result

52 AD patients A+T+N+ and 75 controls entered in the study. AD patients showed lower 123I‐FP‐CIT SPECT SBR in cingulate (p=0.001) and temporal lobe (p=0.007) as well as in insula (p=0.01) and thalamus (p=0.025) compared to controls. When dividing AD according to severity, MCI due to AD (n=17) showed significantly lower parietal SBR compared to controls (p=0.002) and significantly higher SBR in insula (p=0.01), thalamus (p=<0.001) and temporal lobe (p=0.008) compared to AD dementia (n=35).

Conclusion

We demonstrated extrastriatal dopaminergic and serotonoergic impairment in Alzheimer’s disease. In the parietal cortex the alterations was present already at MCI stage, while in the temporal regions, thalamus and insula alterations appeared later in the AD dementia stage. Longitudinal studies will be necessary in order to evaluate the clinical value of extrastriatal 123I‐FP‐CIT SPECT assessment for possible different pattern of progression and response to treatment in AD patients.
Intervention with nostalgic music and reminiscences provide positive emotions for people with dementia and reduces BPSD
Authors: Urabe Mie , Fukuda Hiroko , Noda Yasuha , Miyata Chiharu , Yoneda Sho , Sakai Katsumi , Kato Yuka , Kitajima Kengo , Sawada Chikao
Published: December 2020

Background

Nostalgic music arouses positive changes in mood and social behavior of persons with dementia. (Barnetta L., et al., 2006 )The reminiscence method for a person with dementia supports his/her memories and emotions by having their life history listen to. The intervention using nostalgic music and reminiscence provides stimulation to the emotions of a person with dementia, and positive emotions occur. Through the positive emotions, they may also have a positive effect on the behavioral and psychological symptoms of dementia (BPSD). This project aims to reduce BPSD by extracting positive emotions from people with Alzheimer's disease (AD) with BPSD by listening to and talking about their favorite nostalgic music videos. Since personal computers, Information and Communication Technology (ICT) are used, there is no need to prepare instruments, etc., and anyone can perform this individual intervention anytime, anywhere. This project is researching the interventions that utilize the emotions and the memory function of people with dementia, and has the hypothesis that positive emotions will be able to reinforce their self‐esteem and reduce BPSD. Participants of this project are patients with AD with BPSD in psychiatric hospital in japan. One session is conducted for 30 minutes, four times in total, for each participant for two months. In a session, a participant and a researcher watch the participant’s favorite nostalgic music video of a singer of the time, and talk about impressions and memories of this song. In these sessions, it is an important point to provide images of when the participant was listening to this song.
Polygenic analysis of late‐onset Alzheimer’s disease in a Japanese population
Authors: Kikuchi Masataka , Miyashita Akinori , Hara Norikazu , Shigemizu Daichi , Ozaki Kouichi , Niida Shumpei , Ikeuchi Takeshi , Nakaya Akihiro
Published: December 2020

Background

Late‐onset Alzheimer’s disease (LOAD) is a neurodegenerative disease characterized by cognitive impairment and has a high heritability of 60%–80%. The genetic factor, with the strongest influence identified to date, that is associated with the increased risk of LOAD is the APOE ε4 allele. However, the APOE alleles only explain approximately 6% of LOAD phenotypic variance, and other genetic factors may be responsible for the remainder. The polygenic model explains complex traits, including diseases based on multiple single nucleotide polymorphisms (SNPs) with weak effects as well as several dozen SNPs identified by genome‐wide association studies (GWASs). Recent studies have reported that the polygenic risk score (PRS), which is an index that quantifies polygenic effects, increased the ability to discriminate LOAD patients and correlated with the amount of amyloid β in cerebrospinal fluid. In this study, we calculated PRSs for approximately 2,000 Japanese people using the European LOAD GWAS statistics provided by a previous study. To examine the discrimination ability for LOAD patients, we compared ones between PRSs calculated using the LOAD GWAS statistics and PRSs computed using the GWAS statistics in other diseases. Additionally, we also compared the discrimination ability by LOAD PRS with that of APOE ε4 variation only.

Method

PRS was calculated for each individual as the weighted linear sum of the genotypes of SNPs and the GWAS statistics, including the p‐values or the odds ratios. In this study, we utilized the GWAS statistics from psychiatric disorders, including schizophrenia, and non‐psychiatric disorders, including type 2 diabetes. We performed bootstrapping to evaluate the discrimination ability for LOAD patients and simulation analysis to discuss the differences between populations.

Result

The predictive powers of LOAD were significantly higher than those from other diseases. With GWAS statistics of the same population, the accuracy prominently increased.

Conclusion

We demonstrated the polygenic effects of LOAD in the Japanese population. Our simulation analysis suggested that PRS constructed based on LOAD GWAS statistics in the same population increased the discrimination ability for LOAD patients.
Home‐based evaluation of executive function (Home‐MET) for older adults with mild cognitive impairment
Authors: Ho‐yin Lai Frank
Published: December 2020

Background

Executive function helps older adults maintain their activities of daily living by making plans, setting goals, and carrying them out successfully. It is important for their independence in community living. Clinically, the underlying deficits in executive function (EF) also significantly contributed to their functional disabilities. EF has shown to be important, especially in the fast and complicated contemporary world, because it has been considered as central to independent daily living, solve problems, and resolve conflicts. EF was considered as a vital part of the independent living skills of older adults with dementia in community living. Some researchers commented that executive function is the core psychological deficit underlying dysfunction of mild cognitive impairment. The resulting functional disabilities were the major cause of extended hospital stays and protracted residential care.

Method

With a carefully match‐group of 80 mild cognitive impaired with 80 health control subjects. The home‐based evaluation of executive function (Home‐MET) was validated in subjects’ own living environment.

Result

This Home‐MET showed significant correlation in the assessment of attention control that was assessing by Test of Everyday Attention (TEA) (r = .86, p < .01), with working memory that was assessed with Trail Making Test (TMT) (r = .72, p < .01), with inhibitory control that was assessing with Stroop Test (r = .86, p < .01), with individuals’ functional disability was assessed by Chinese Disability Assessment of Dementia (CDAD) (r = .77, p < .01) and cognitive assessment was assessed by Hong Kong Montreal Cognitive Assessment (HK‐MoCA) (r = .88, p < .01). By benchmarking with the validated performance‐based executive function assessment, the Home‐MET shows significant correlation (r = .92, p < .05) with the executive function test in a standard environment in hospital, i.e. the Chinese Multiple Errands Test (the Chinese‐MET). The two‐stage hierarchical linear regression model with backward method showed functional disability was a marginally significant predictor (p < .059) for the Home‐MET with regression model showed with R2 = .93.

Conclusion

Results indicated the Home‐MET, can provide an objective measure of executive function for subjects with mild cognitive impairment in participants’ own home environment.
Identifying dementia risk factors and implementing a culturally grounded risk‐reduction intervention in urban and regional Aboriginal Australian communities
Authors: Lavrencic Louise , Donovan Terrence , Moffatt Lindy , Allan Wendy , Daylight Gail , Garvey Gail , Hill Thi Yen , Draper Brian , Cumming Robert , Broe Gerald A , Delbaere Kim , Radford Kylie
Published: December 2020

Background

Aboriginal Australians are disproportionately affected by dementia compared to other Australians and many populations globally. Dementia incidence and risk factors have not been identified for Aboriginal Australians living in urban or regional areas (comprising ∼80% of First Nations Australians). There is also a pressing need in this population for non‐pharmacological interventions that are culturally‐grounded and target dementia risk‐reduction. Psychological wellbeing is a risk factor for dementia, and is relevant for Aboriginal communities where there are high levels of exposure to stress and trauma.

Method

The Koori Growing Old Well Study (KGOWS) is a longitudinal, population‐based study with Aboriginal Australians aged 60+ years; participants were from 5 partnering communities in New South Wales (N=336 at baseline; n=165 at follow‐up; n=68 died before follow‐up; mean follow‐up=6 years). Biomedical and psychosocial risk factors (baseline assessment) were examined for cognitive decline (incident MCI or dementia) using logistic regression. To address the impact of lifecourse stress and trauma on dementia risk, a comprehensive co‐design process was employed to develop the Ngarraanga Giinganay (‘thinking peacefully’) mindfulness‐based program, including expert working group, community focus group and pilot trial (n=7 older Aboriginal Australians), with quantitative and qualitative outcomes.

Result

KGOWS demonstrated high rates of incident dementia (17.55/1000 person‐years; age‐standardised rate=34.71) and cognitive decline (42.34/1000 person‐years; age‐standardised rate=73.51), comparable to a remote Aboriginal population. In models adjusted for age (OR=2.12), factors predicting cognitive decline included male sex (OR=2.91), lower education (OR=0.51), moderate to severe hearing (OR=4.80) and vision (OR=3.78) problems, greater waist‐hip ratio (OR=1.56), polypharmacy (OR=2.61) and unskilled work history (OR=5.27). The working group and focus group feedback strongly guided Ngarraanga Giinganay program development, ensuring content and activities aligned with cultural understandings and practices for that community (Gumbaynggirr people). Results from the Ngarraanga Giinganay pilot demonstrated feasibility, acceptability and preliminary effectiveness of mindfulness‐based stress‐reduction; and highlighted aspects for refinement and further evaluation.

Conclusion

These findings provide the first urban incidence rates and identify potentially modifiable risk factors for cognitive decline in Aboriginal Australians. Our work with communities provides insight into partnering with underrepresented populations for dementia research; and highlights the effectiveness of co‐design approaches when developing culturally‐specific interventions.
Combined findings of FDG‐PET and arterial spin labeling in sporadic Creutzfeldt‐Jakob disease
Authors: Yuan Junliang
Published: December 2020

Background

Sporadic Creutzfeldt‐Jakob disease (sCJD) is a fatal progressive neurodegenerative disease. Multimodal approaches, including electroencephalogram, diffusion‐weighted imaging (DWI) of brain MRI, and cerebrospinal fluid biomarkers, have been applied to increase the diagnostic accuracy of sCJD. Although previous studies suggested DWI could be the most useful modality for sCJD diagnosis, whether metabolism changes underlying in sCJD are still poorly understood.To the best of our knowledge, there are only one case using the technique of arterial spin labeling (ASL) to detection and follow‐up of perfusion changes in CJD.

Method

Herein, we described a 71‐year‐old woman presented with progressive cognitive decline, behavioral and psychological symptoms for two months. The patient died one month later after her admission.

Result

As far as we know, this is the first report using the combination of fluorodeoxyglucose positron emission tomography and ASL to explore the metabolism changes in sCJD.

Conclusion

Our case exemplifies the difficulty clinicians may face in the diagnosis of sCJD.
Hearing loss and hearing care disparities among older adults with cognitive impairment
Authors: Nieman Carrie L , Deal Jennifer A , Betz Joshua , Reed Nicholas S , Goman Adele M , Knopman David S , Sharrett A Richey , Windham B Gwen , Oh Esther S , Albert Marilyn S , Lin Frank R
Published: December 2020

Background

Although both age‐related and highly prevalent, little is known regarding the prevalence of hearing loss among persons with dementia (PwD). Current understanding is based on convenience samples primarily from specialized memory clinics. The Atherosclerosis Risk in Communities Neurocognitive Study (ARIC‐NCS) is a large, prospective study of a population‐based cohort from 4 U.S. community sites with audiometric and neurocognitive testing and bi‐racial representation. We examined the prevalence of hearing loss and hearing aid use among older adults with cognitive impairment and whether cognitive status influences hearing aid use.

Method

We analyzed audiometric and hearing care data from ARIC‐NCS Visit 6 (2016‐2018). Participants underwent a full neurocognitive battery and audiometric evaluation at Visit 6. Participants with complete audiometric data and an adjudicated diagnosis of cognitively normal, mild cognitive impairment (MCI), or dementia were included in the analytical cohort (N=3,385). Differences in participant characteristics by cognitive status were descriptively compared using Chi‐square tests or one‐way ANOVAs. We performed a series of logistic regression models to estimate the odds of hearing aid non‐use by cognitive status.

Result

Prevalence of hearing loss was greater with increasing cognitive impairment (cognitively normal:64.7%; MCI:71.3%; dementia:83.3%). Prevalence of hearing aid use among those with hearing loss and cognitive impairment varied by race (African Americans 7.2%; whites 32.8%). In a multivariable‐adjusted model, cognitive impairment was independently associated with higher odds of non‐use of hearing aids (MCI odds ratio (OR):1.4 (95%CI:1.0‐1.8); dementia OR:1.8 (95%CI:1.2‐2.9) versus cognitively normal). The strongest risk factor for non‐use of hearing aids was race, where African Americans have almost a 5 times higher odds of not using hearing aids compared to whites (95% CI:2.9‐7.4).

Conclusion

Hearing loss is highly prevalent but vastly untreated among older adults with cognitive impairment, particularly African Americans, and cognitive impairment is independently associated with hearing aid use. These estimates are some of the first population‐based estimates of audiometric hearing loss among diverse older adults with adjudicated diagnoses of MCI or dementia. With increased calls to address ethnic/racial disparities, we must include hearing loss, as one of the most common co‐morbidities, in order to optimize health and well‐being among all PwD.