bluuebunny/crossref_metadata_2025_split huggingface dataset:
Caregiving is associated with worse sleep, and worse sleep‐related health and function
Authors: Sprecher Kate E , Hagen Erika W , Ravelo Laurel A , Barnet Jodi H , Peppard Paul E 
Published: December 2020

AbstractBackgroundDisturbed sleep in caregivers of persons with dementia is a leading reason for the decision to institutionalize persons with dementia. Here we quantify the association of caregiving with sleep, and sleep‐related health and function.MethodIn the Retirement and Sleep Trajectories study, 2137 community dwelling adults completed 4 annual mailed surveys (52% female, mean age 64 years (range 46‐86 years)). Caregiving status was determined from questions: (1) How many hours per month do you spend providing unpaid assistance to others? and (2) Indicate how often caring for others kept you up past your intended bedtime. Responses of never or rarely were compared to responses of sometimes, often or always. Participants were asked their usual bedtime, waketime, and sleep need (How many hours and minutes of sleep do you think you currently need each day to feel rested and alert?). Sleep duration was defined as the time from bedtime to waketime, averaged across weekdays and weekends. Sleep debt was defined as the difference between sleep duration and sleep need. A 9‐item version of the functional outcomes of sleep questionnaire (FOSQ) was administered, which reflects general productivity, activity level, vigilance and social outcomes. Mental and physical health were assessed with the SF‐12 Health Survey. Mixed‐effects linear models were used to test associations of caregiving with sleep, health and function, controlling for age.Result5.45% of respondents reported that caregiving delayed their bedtime, which was significantly (p<0.001) associated with 11 (95% CI = 6‐16) minutes/day shorter sleep duration, 13 (95% CI = 7‐18) minutes/day greater sleep debt, worse functional outcomes of sleep (beta = ‐0.58, 95% CI= ‐0.87‐ ‐0.30) and worse mental health (beta = ‐1.88, 95% CI = ‐2.67 ‐ ‐1.10). Delayed bedtime due to caregiving was not associated with physical health. Hours spent caregiving was not associated with sleep duration, sleep debt, health or functional outcomes.ConclusionCaregiving is associated with disturbed sleep, which is associated with worse daytime function and worse mental health. Interventions to improve caregiver sleep could be a strategy to improve caregiver health, function and quality of life.
Musical Bridges to Memory (MBM): Exploring the effects of a dyadic music‐based group intervention on social engagement and neuropsychiatric symptoms in persons with dementia
Authors: Schafer Rhiana , Karstens Aimee J , Hospelhorn Emma , Wolfe Jeffrey , Ziemba Amanda , Wise Peggy , Crown Rickie , Rook Jenni , Bonakdarpour Borna 
Published: December 2020

AbstractBackgroundMusic‐based interventions can reduce the severity of neuropsychiatric symptoms in persons with dementia (PWD), and in turn reduce the need for pharmacological interventions (e.g., psychotropic). However, few intervention trials have used a dyadic group approach. We determine the efficacy of a dyadic music‐based intervention on PWD neuropsychiatric symptoms and social engagement. Musical Bridges to Memory (MBM) uses both perceptive and expressive forms of music‐based intervention, administered in a dyadic group setting, to mediate PWD neuropsychiatric symptoms and improve social interaction between dyads (PWDs and their caregivers).MethodThirty‐one dyads were recruited from memory care facilities; twenty received the MBM intervention, ten were controls. Groups were comparable in age and level of education. All were assessed at baseline and post‐intervention. Caregiver‐reported PWD behavioral symptoms were assessed using the Neuropsychiatric Inventory (NPI). The Verbal and Nonverbal Interaction Scale (VNVIS) was used to rate PWDs social interactions (10min video recordings of dyads) on sociable, unsociable, verbal and nonverbal behaviors. The 12‐week intervention included weekly sessions, which consisted of caregiver training(30m), live concerts(45m), and breakout groups(30m). Music was chosen based on PWDs’ assessed preferences.ResultSociable interactions (e.g. positive affect, eye‐contact, apparent interest/focus), significantly increased (p=0.044) in the MBM intervention group as compared to controls. Caregivers reported a decrease in severity of PWD neuropsychiatric symptoms (p=0.089, indicating a trend) and symptom‐related distress in caregivers (p=0.005) decreased significantly. Analyses controlled for sex and global cognition (Mini Mental State Exam) score at baseline.ConclusionOur preliminary results indicate that a dyadic music‐based group intervention approach administered in a memory care facility is effective at improving PWD social engagement, mitigating PWD behavioral symptoms, and reducing associated caregiver distress. These results complement previous literature, highlighting music‐based interventions as a non‐pharmacological approach to managing neuropsychiatric interventions in PWD. In addition, our use of a dyadic group‐based approach and our reported increase in sociable engagement highlights the benefits of including caregiver participation in music‐based interventions. Future work will examine a larger cohort and directly examine caregiver burden.
CO‐registration of proton magnetic resonance spectroscopy (1H‐MRS) and diffusion imaging (DMRI) in healthy aging: A prospective study of cerebral neurochemistry and microstructure
Authors: Hone‐Blanchet Antoine , Shahid Salman Syed , Krishnamurthy Lisa , Lin Qixiang , Levey Allan I , Lah James J , Qiu Deqiang , Crosson Bruce 
Published: December 2020

AbstractBackgroundChanges in brain microstructure are markers of aging and implicate changes at the neurochemical level. Prior magnetic resonance spectroscopy (MRS) works have demonstrated effect of aging on gamma‐aminobutyric acid (GABA) and myo‐inositol (mI), suggesting changes in cellular metabolism and neuroinflammation. Diffusion MRI (dMRI) works have shown that neurite density (NDI) is decreased in aging, suggesting a decrease in dendritic and axonal health. We obtained MRS and dMRI indices co‐registered within the same voxel in the medial frontal cortex (MFC) to investigate how tissue microstructure locally influences neurochemistry. We hypothesized that NDI would predict age‐related changes in concentration of GABA and age‐related neuroinflammation with concentration of mI.MethodParticipants: 138 healthy older adults (age 64.8±6.52 years; range 51‐86 years). Informed consent was obtained from all subjects. MRS: acquired on a 3T MRI system with a 32‐channel head coil. PRESS and MEGAPRESS spectra were acquired from a 3x3x3cm voxel positioned in the MFC. GABA and mI levels were estimated with Gannet and LC Model. Segmentation of images was performed with SPM 12. A voxel mask registered to T1 was generated to perform registration of dMRI in the same volume. dMRI: acquired in the axial plane with a multi‐band signal‐shot spin echo echo‐planar sequence (MB acceleration factor = 3). A multi‐shell scheme was used with 3 b0, 10 b150, 10 b350, 64 b1000, 64 b2000, 64 b3000 and 104 b5000 directions. Raw images were processed to reduce signal noise. Analyses: Linear regression analyses were performed: Effect of age with NDI and MRS metabolites as dependent variables. Effect of NDI with MRS metabolites as dependent variables with age as covariate.ResultAge predicted levels of GABA (B=0.413, P<0.001), mI (B=0.309, P=0.002), and NDI (B=‐0.351, P<0.001). NDI predicted levels of GABA (B=0.24, P=0.005) and mI (B=‐0.236, P=0.022).ConclusionThis study demonstrates that local microstructure differentially impacts GABA and mI in a healthy aging cohort. It also supports age as a predictor of microstructure and neurochemistry in the MFC. These suggest that neurite density impacts neurochemistry prior to age‐related, clinically significant structural changes and demonstrate relevance of co‐registration of MRS and dMRI in aging.
Microglial activation and brain networks in Alzheimer’s disease: The ActiGliA cohort study
Authors: Rauchmann Boris‐Stephan , Brendel Matthias , Keeser Daniel , Tato Maia , Palleis Carla , Zaganjori Mirlind , Ersözlü Ersin , Janowitz Daniel , Bürger Katharina , Goldhardt Oliver , Grimmer Timo , Levin Johannes , Stöcklein Sophia , Höglinger Günter , Haass Christian , Perneczky Robert 
Published: December 2020

AbstractBackgroundRecent research suggests that brain network degeneration and immune response play important roles in Alzheimer’s Dementia (AD). Brain network connectivity become increasingly impaired as AD progresses. Glial activation in the neuropathology of AD has also been widely recognized both as a consequence and as a contributing factor for the formation of Aβ and tau aggregation. Immune surveillance in the brain and microglial activation can be reliably measured by translocator protein (TSPO) positron emission tomography (PET).MethodTo understand better important associations between network degeneration and immune response in AD, we initiated the ActiGliA prospective cohort study. Here we present an analysis of the initial 55 participants, including 20 participants with subjective cognitive declined, 19 patients with mild cognitive impairment and 16 AD patients. Participants were characterized using CSF biomarker information and underwent TSPO‐PET, fMRT and DTI acquisitions. We assessed topographical associations between microglia activity (TSPO‐PET covariance) with resting state functional and DTI structural connectivity changes using a 210 regions parcellation of the neocortex. PET and MRI preprocessing were performed using standard imaging pipelines.ResultAt baseline, elevated microglia activity was found in TSPO‐PET analysis of AD patients. Resting state fMRI graph‐theory analysis showed reduced global efficiency and increased local efficiency in AD compared to controls. No significant group differences were found in the graph‐theory analysis of structural connectivity. In a further analysis, we assessed the association between microglia activity and functional connectivity. A positive correlation of resting state functional connectivity with microglia covariance (r=0.177, p<0.001), but no correlation of structural connectivity and microglia covariance were detected. Network specific TSPO uptake in resting‐state networks, demonstrating increased uptake in the language, default mode network (DMN), and visual network in the AD group compared to controls.ConclusionIn line with previous findings, we confirm that brain functional connectivity is disrupted and microglial activity is elevated in AD. Preliminary results suggest an association between functional connectivity and microglia activity in AD, furthermore microglia activity is preferentially found in particular resting state networks.
Prediction of Alzheimer’s disease using plasma RNA sequences
Authors: Ibanez Laura , Benitez Bruno A. , Cruchaga Carlos , Harari Oscar , Del‐Aguila Jorge L. 
Published: December 2020

AbstractBackgroundAlzheimer’s disease (AD) is inexorable, incurable, and in many cases very difficult to diagnose before symptom onset. Thus, there is a clear need to develop tools to detect the pathological changes that occur before clinical symptoms onset. Historically, proteins have been the preferred biomarker. However, biofluids also contains ribonucleic acid in its free form (cfRNA). The source of cfRNA in plasma is not fully understood, but it is thought to be the result of normal cell death throughout the body, thus providing a mirror of the status of a normal functioning body. Therefore, if some organs are functioning incorrectly, we can detect it by changes in cfRNA. To date, several species of cfRNA have been investigated as biomarkers for cancer, fetal development and AD. In here we tested plasma cell‐free RNA species as biomarker for AD diagnostic.MethodWe generated cfRNA‐Seq data from a discovery dataset (ten pathologically confirmed AD cases and ten sex, age and APOE genotype matched controls) and a replication dataset containing samples at different stages of the disease and controls (N=80) not matched by sex or APOE. Standard quality control and alignment pipeline for RNAseq data was used. Gene expression was quantified with Salmon and corrected by library complexity and log transformed prior to analysis. Predictive models were built using the wrapper algorithm Boruta and the machine learning tool Tensorflow to define the optimal number of RNA transcripts.ResultsTranscriptome‐wide principal component analyses show that cfRNA reflect significant differences between cases and controls (46% of variance explained, p=0.001). Using machine learning, we identified a set of 24 genes that perfectly predicts cases in the discovery dataset. In the replication dataset, the area under the ROC curve for the model with APOE and sex was 0.84 for advanced clinical stage (CDR=1), 0.82 for early stages (CDR=0.5) and 0.86 for presymptomatic. Exclusion of APOE genotype in the predictive model drastically affected the predictive power.ConclusionCell‐free RNA is a promising biomarker for AD with an accuracy comparable to the one obtained using CSF biomarkers. This non‐invasive approach can provide new biomarkers or screening tool for AD.
Large synaptic genes are more frequently affected by somatic mutations and show reduced expression in Alzheimer's disease: Implications for disease etiology
Authors: van der Linden Robert J. , Soheili‐Nezhad Sourena , Sprooten Emma , Poelmans Geert 
Published: December 2020

AbstractBackgroundAging is associated with the accumulation of somatic mutations in post‐mitotic neurons. While this idea is not new, recent advances in single‐cell sequencing techniques have now made it possible to not only unequivocally prove that these mutations occur but also to estimate their occurrence rates. Here, we aimed to investigate whether somatic mutations are associated with Alzheimer’s disease (AD) and gain insight into the potential pathophysiological consequences of such mutations in the brain.MethodStarting from the average annual somatic variation rate of healthy neurons, we modeled the likelihood of a gene being affected by somatic mutations over time, based on the transcribed length of that gene. Subsequently, we investigated the gene length distribution of genes that are affected by somatic mutations in AD brains and we analyzed differential mRNA expression data from eight AD brain areas, including pathway analysis.ResultOur model predicted that CNTNAP2, the largest gene in the human genome, has a 50% chance of having acquired at least one somatic mutation by the age of 65, which is in sharp contrast with average‐sized genes, in which there is only 1% chance of somatic mutations at 65. We also found that genes affected by somatic mutations are (much) longer than average and that larger genes are more likely to be reduced in their expression levels in AD‐vulnerable brain regions. Lastly, we found that these larger genes are predominantly expressed in neurons and are involved in synaptogenesis and synaptic adhesion, pathways that are predicted to be inhibited in AD based on the transcriptomic data.ConclusionOur findings implicate somatic mutations in large genes as potential contributors to AD pathology through their effect on synaptic function.
Neuropsychological subtypes of incident mild cognitive impairment in Down syndrome
Authors: Hom Christy 
Published: December 2020

AbstractBackgroundPast attempts to characterize the earliest cognitive changes as individuals with Down Syndrome (DS) transition from cognitively stable to mild cognitive impairment (MCI) have been equivocal (Garcia‐Alba et al., 2019; Lautarescu et al., 2017). Difficulties identifying MCI in this population are complicated by variability in pre‐morbid cognitive abilities, the use of neuropsychological tests that were created for the neurotypical population, and participants scoring at floor on the baseline assessment (Krinsky‐McHale and Silverman, 2013).MethodWe examined data from 151 individuals with Down Syndrome (M age=50.25, SD age=6.94). Their pre‐morbid level of intellectual impairment ranged from mild to severe. All participants received comprehensive evaluations. Following data collection, the clinical status of each participant was rated at consensus review that considered performance on a core neuropsychological test battery and the clinical data for each participant. Data from the non‐demented and MCI groups are examined: Cognitive Stable (N=107, 70.9%) and MCI‐DS (N=44, 29.1%). The full battery consists of 27 subtests that were hypothesized a priori to measure five cognitive domains: language, memory, executive function, visuospatial reasoning, and motor coordination.ResultFactor analysis revealed 7 principal components that maximally discriminated between test scores in older adults with DS who have not reached clinical AD status: (1) general intelligence (2) sensorimotor, (3) memory, (4) language comprehension and expression, (5) executive function/speed, (6) attention/language expression, and (7) visuomotor. Cluster analysis for the MCI group produced 3 distinct groups: (1) dysexecutive (n=4), (2) dysnomic/visuospatial impaired (n=28), and (3) amnestic/motor impaired (n=12).ConclusionThe neuropsychological battery assesses 7 distinct cognitive functions in older adults with DS. It can also capture cognitive decline, as we were able to empirically identify three distinct neuropsychological subtypes of MCI: amnestic/visuomotor impaired, dysexecutive, and dysnomic. These subtypes are generally consistent with those that have been found within the neurotypical population (Edmonds et al., 2015; Dick et al., 2016), strengthening the evidence that AD has a similar course in the DS population and late onset AD.
Using seeding models to understand strain differences from Alzheimer’s disease and pathological aging brains
Authors: Moore Brenda D. , Hampton Hailey , Croft Cara L. , Futch Hunter S. , Moran Corey , Levites Yona , Fromholt Susan , Xu Guilian , Dickson Dennis W. , Lewis Jada , Golde Todd E. , Borchelt David R. 
Published: December 2020

AbstractBackgroundPathological aging (PA) patients are individuals that are cognitively normal prior to death but have abundant and widespread amyloid‐β (Aβ) deposits. These individuals typically have few cored amyloid deposits with variable levels of diffuse parenchymal deposits and/or vascular deposits. There is little or no inflammatory reaction, neuritic pathology or neurofibrillary tangles in the cortex. Previously, we have shown that total Aβ levels in PA brain lysates were similar to the levels in Alzheimer’s disease (AD) brain lysates, with overlap in the length of the Aβ peptides that were deposited and no major differences in SDS‐stable Aβ oligomeric assemblies. Despite these similarities, it is unclear whether PA represents a prodromal phase of AD or if the amyloid pathology of PA patients represents a less pathogenic variant. To explore this idea, we examined the seeding capacity of AD and PA brain homogenates to induce Aβ deposition and to secondarily induce tau pathology.MethodWe determined the seeding capacity of two AD, four PA and two control brain homogenates in transgenic mice expressing APPswe/ind with and without Tau‐P301L by intracerebral injection at neonatal day 0. At either 6, 9, 12 or 18 months, we assessed Aβ deposition and neurofibrillary pathology in all 4 genotypes by immunohistochemical and biochemical methods. Furthermore we examined the seeding activity of human AD brain lysates in brain slice cultures from APP/Tau transgenic mice.ResultIn our newborn mouse injections, we observed widespread Aβ seeding as evidenced by accelerated onset of diffuse parenchymal Aβ deposition that was largely proportional to the burden of parenchyma deposits in patient brains. In all cases, high levels of pial deposition were observed and Aβ42 was the predominant peptide deposited. Tau pathology was not induced in any animal, and with the absence of neuritic plaques there was no induction of tau positive neurites.ConclusionThis study provides evidence that the Aβ conformers associated with diffuse Aβ deposits in the brains of cognitively normal individuals possess seeding activities similar to those found in the brains of AD patients. The findings are consistent with the idea that pathological aging is on a continuum with AD.
Spanish translation and adaptation of a family quality‐of‐life survey for families of people with a neurodegenerative disease
Authors: Vicario‐Molina Isabel , Ortega Eva González ,   NEUROQUALYFAM Group
Published: December 2020

AbstractBackgroundOne of the main objectives of NEUROQUALYFAM Project is to assess the quality of life and the needs of support of families of people with a neurodegerative disease (ND) in Spain. For this purpose, The Family Quality of Life Survey‐Adapted for Main Caregivers of Persons with Dementia (FQoLS; DiZazzo‐Miller & Samuel, 2011) has been translated and adapted to the Spanish context.MethodThe “International Test Commission guidelines for test translation and adaptation” were taken into account, thus considering the following phases: 1) Two initial and independent translations of FQoLS; 2) Review and synthesis of the translations; 3) Focus groups with families of people with a ND, as well as with health, social and third sector professionals, in order to assess the relevance, clarity and appropriateness of items; 4) Synthesis and agreement by a committee of experts; 5) Backtranslation and comparison with the original items; 6) Pilot study of the consensual version with a sample of families with an individual with a ND.ResultAfter the translation and adaptation process, the comprehension and appropriateness of items and response options in the preliminary version were verified. The application of the final version of the instrument and the assessment of its psychometric properties will be conducted in a subsequent phase of the study.ConclusionPreliminary results indicate that the instrument has been successfully translated and adapted to the Spanish context. Moreover, this questionnaire seems to be a useful tool for assessing the quality of life of families of patients with ND as well as for designing intervention strategies aimed to optimize support resources and improve families’ health and wellbeing outcomes.ReferenceDiZazzo‐Miller, R., Samuel, P.S. (2011). Family Quality of Life Survey: Main Caregivers of Persons with Dementia. Detroit, MI, USA: Wayne State University.