bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating the relationship of drugs prescribed to treat hypertension and hypercholesterolemia with disease progression in Alzheimer’s disease and related dementias
Authors: Sadoo Annie B , Davies Neil M , Kehoe Patrick G , Martin Richard M , Walker Venexia M 
Published: December 2021

AbstractBackgroundDementia is at present incurable. It is seen in a range of neurodegenerative diseases, the most common being Alzheimer’s disease (AD). The debilitating neurocognitive deficits develop over time and available treatments have limited effectiveness. It is of paramount and economic concern to identify new and safe possibilities for treatment. Current treatments are aimed at managing symptoms, but do not address the underlying cause of disease. Existing medications work to minimise toxicity caused from breakdown of neurons and brain connections, and preserve neurochemical levels important in cognitive function. Hypertension and hypercholesterolemia, have been linked with increased risk of developing AD. Antihypertensive drugs may protect against AD and lead to reduced disease progression through decreasing neuropathological mechanisms. Statins treat high cholesterol. High cholesterol relates with elevated levels of β‐amyloid protein, an accumulation in brain tissue leads to formation of amyloid plaques, toxic to neurons. Cholesterol‐lowering medication lowers amyloid plaques in brain tissue.MethodData will be obtained from the Clinical Practice Research Datalink (CPRD), an ongoing database of UK primary care data. The determined sample population, estimated at 105 471 patients, will be divided according to their prescribed medications. Data on treatments will be compared for each group against outcomes such as death and hospitalisation due to AD and related dementias. Potential confounders will be adjusted for in the regression model. Associations between the exposures and outcomes will be assessed through multivariable regression analyses; multivariable Cox regression analysis for assessing survival rate; and marginal structural models to control for treatment switching. Appropriate statistical analysis methods will also be applied to account for other biases, including: propensity score regression to minimise bias due to working with data from non‐randomised comparison of treatments; multiple imputation to account for missing data; and use of appropriate inclusion criteria to prevent collider bias.ResultWe will present the results at a later time.ConclusionThis project will allow us to better understand the link between progression of neurological disorders and pharmacotherapy.
Optimizing software methods for measuring flortaucipir SUVR change over time
Authors: Schwarz Christopher G. , Therneau Terry M. , Weigand Stephen D , Gunter Jeffrey L. , Lowe Val J , Przybelski Scott A. , Senjem Matthew L. , Botha Hugo , Vemuri Prashanthi , Kantarci Kejal , Boeve Bradley F. , Whitwell Jennifer L , Josephs Keith A , Petersen Ronald C. , Knopman David S. , Jack Clifford R. 
Published: December 2021

AbstractBackgroundOptimizing software to measure Flortaucipir (AV‐1451) tau PET SUVR change‐over‐time is crucial for longitudinal observational studies and potential trials of anti‐tau agents. Ideal measurements should have good repeatability (low noise), and should clearly separate clinical cognitive groups.MethodWe compared 456 software methods varying in their use of: two major packages, each with cross‐sectional and longitudinal variants (FreeSurfer and an in‐house pipeline using SPM12, MCALT, and ANTs); three temporal‐lobe target regions (each with/without adjacent WM); seven reference regions; five PVC methods; and two statistics (mean vs. median). We used linear mixed‐effects models to compare methods using scans from 88 Mayo Clinic participants (46 cognitively impaired, 42 impaired, excluding those with symptoms inconsistent with the AD pathology imaged by Flortaucipir), each with three visits with PET and MRI. From these models, we calculated two criteria for each pipeline: relative measurement error (residual from the linear mixed model), and the t‐statistic for testing differences in group‐wise rates of change (which has a Cohen’s d interpretation of effect size for longitudinal data). We plotted both criteria orthogonally, then ranked methods overall according to the average of their ranks on both individual criteria.ResultMethods using the entorhinal cortex target region performed poorly in both criteria (Figure 1). The top 10 methods by the combined criteria (top‐left in Figure 2) all used the Mayo SPM12‐based pipeline with an eroded supratentorial WM (eSWM) or composite (eSWM + pons + cerebellum) reference region. Among them, 9/10 used the longitudinal variant, 8/10 used 2‐compartment PVC, and 7/10 used median. Altogether, our results favored SUVR methods with a longitudinal design (simultaneously calculating all time‐points), a temporal‐lobe meta‐ROI including adjacent WM, a composite reference region, 2‐class voxel‐based (Meltzer) PVC, and median statistics. Methods using GTM‐Tau PVC (Baker et al., Data in Brief, 2017) had the highest group separation but relatively large measurement error, giving them ranks 197 and 199 out of 456 with the joint (average rank) criteria.ConclusionCompared with popular FreeSurfer‐based methods (ranks 176, 258; Figure 2), our top‐ranked approaches approximately halved error in SUVR measurements while maintaining or improving group separation.
Associations of lifestyle factors with amyloid positivity in cognitively normal individuals at different levels of genetic risk: The amyloid biomarker study
Authors: Oomens Julie Elisabeth , Jansen Willemijn J , Janssen Olin , Verhey Frans RJ , Vos Stephanie JB , Visser Pieter Jelle ,   Amyloid Biomarker Study Group
Published: December 2021

AbstractBackgroundThe role of lifestyle factors in the pathophysiology of Alzheimer’s disease is unclear. The aim of this study was to assess the contribution of lifestyle factors to cerebral amyloid pathology in cognitively healthy persons at different levels of genetic risk.MethodsWe selected sixteen cohorts from the Amyloid Biomarker Study. Lifestyle data were available for 5542 participants with normal cognition. Amyloid positivity was determined with amyloid‐PET (center‐specific cutoffs) or with aß42 level in CSF (data‐driven cutoffs). Participants were classified as being at low, intermediate or high genetic risk for amyloid positivity according to ApoE e4 copy number (0 vs. 1 vs. 2 e4‐alleles). Participants for whom data was available for >=3 lifestyle factors (n=5046) were classified as having a favorable or unfavorable lifestyle profile on basis of the lifestyle information available for that cohort. A favorable lifestyle was defined as (dichotomized): not smoking (ever), not drinking, normal sleep, physically active, socially active, cognitively active and/or adhering to a Mediterranean diet. Associations of both lifestyle profile and individual lifestyle factors with amyloid positivity, and their dependency on genetic risk, were assessed using generalized estimating equations. Age was included as covariate in all models,ResultsIndependent of genetic risk level, impaired sleep was associated with lower amyloid positivity (p=0.001) and cognitive inactivity was associated with higher amyloid positivity (p<0.001). Smoking, alcohol use, social activity and diet were not associated with amyloid positivity (table 2). The effects of lifestyle profile and physical activity on amyloid positivity were dependent on genetic risk (p<0.001). Prevalence of amyloid positivity was lower for those with a favorable rather than an unfavorable lifestyle at low (mean difference (md) 3%, p<0.001) and intermediate (md 5%, p<0.001) genetic risk, while this association was reversed for persons at high genetic risk (md 7%, p=0.001, table 3). Amyloid positivity was more common in physically active than inactive participants at high genetic risk only (md 9%, p<0.001).ConclusionIndividual lifestyle factors are limitedly associated with amyloid positivity. However, absence of any unfavorable lifestyle factor is related to lower risk of amyloid positivity in persons at low or intermediate genetic risk.
Sleep disturbance and association with cognitive and functional trajectories in all cause dementia: The Cache County Dementia Progression Study
Authors: Murray Julie , Gonzalez Hector Leonardo , Schwartz Sarah , Rattinger Gail B. , Liu Yin , Hammond Alexandra G , Kauzor Kaitlyn E , Drewel Mikaela , Tschanz JoAnn T 
Published: December 2021

AbstractBackgroundSleep disturbance is common in older adults, with a prevalence rate of approximately 25%. Sleep disturbance has been associated with increased risk for Alzheimer’s disease (AD), brain Aß deposition, and worse cognition in older adults in general. Few studies have examined the association between sleep disturbance and cognitive or functional decline after the onset of dementia. We examined this issue in a population‐based cohort of persons with dementia.MethodFive hundred eighty‐two participants (aged 65+, 60.3% female) with dementia from the Cache County Memory Study were followed for a mean (sd) of 2.47 (2.72) years, and maximum of 13.28 years. Mean (sd) age of dementia onset was 83.49 (6.29) years. A majority (81.3%) had a high school diploma/GED. Cognition was assessed at baseline and semi‐annual follow‐ups with the Mini‐Mental State Exam (MMSE) and functional status with the Clinical Dementia Rating sum‐of‐boxes (CDR‐sum). Sleep disturbance was based on the sleep domain from the Neuropsychiatric Inventory, or if lacking, a question about the subject being “troubled by sleep problems, insomnia.” Presence of depression was also determined from the NPI. Sleep disturbance (time varying) was examined in separate linear mixed effects models to predict changes in MMSE and CDRsum, controlling for age, gender, education, depression (yes/no) and presence of APOE E4 allele.ResultPrevalence of sleep disturbance was 29.7%. The association between sleep disturbance and cognitive and functional outcomes varied by dementia type (p interactions < .001). Compared to those with Alzheimer’s disease and sleep disturbance, individuals with vascular dementia and sleep disturbance exhibited worse (higher) CDR‐Sum scores across time (M_difference = ‐1.55, SE = .41, p < .001, d = .27) while individuals with “other dementias” and sleep disturbance performed worse on the MMSE (M_difference = 2.14, SE = .55, p < .001, d = .38) as did APOE4 carriers (M_difference = 1.45, SE = .35, p < .001, d = .26).ConclusionIndividuals with various dementia types and those with an APOE E4 allele in combination with sleep disturbance had worse cognitive and functional trajectories. Future work will examine effects of sleep medication use on dementia trajectory.
Tau‐PET is associated with knowledge of COVID‐19, COVID‐19‐related distress, and change in sleep quality during the pandemic
Authors: Lussier Firoza Z , Servaes Stijn , Kang Min Su , Bezgin Gleb , Chamoun Mira , Stevenson Jenna , Rahmouni Nesrine , Stevenson Alyssa , Pascoal Tharick A. , King Suzanne , Elgbeili Guillaume , Bzdok Danilo , Gauthier Serge , Rosa‐Neto Pedro 
Published: December 2021

AbstractBackgroundWhile the global COVID‐19 pandemic has hindered many human research operations, it has allowed for the investigation of novel scientific questions. Particularly, the effects of the pandemic and its resulting social isolation on elderly individuals and their association with Alzheimer’s disease biomarkers remains a broad and open question. Here, we sought to investigate whether knowledge of COVID‐19, pandemic‐related distress, and changes in sleep quality were associated with in vivo tau deposition in an AD‐enriched cohort.MethodsCOVID‐19 telephone assessments were conducted in N=292 individuals (29 young/174 CN/52 MCI/19 AD/18 other) of the TRIAD cohort in April‐July 2020. Assessment consisted of clinical and neuropsychiatric, instruments, including scales assessing the individual’s experience of the pandemic. Structural MRI and [18F]MK6240 tau‐PET were acquired before the pandemic. [18F]MK6240 standardized uptake value ratio (SUVR) were calculated 90‐110 minutes post‐injection using cerebellar grey matter as the reference region. Voxel‐based regression analyses were conducted to examine the associations between baseline [18F]MK6240 SUVR and knowledge of COVID‐19, distress related to COVID‐19, and change in sleep quality since the pandemic.ResultsHigher tau‐PET SUVR was associated with less knowledge of COVID‐19 in N=210 individuals in the cuneus, cingulate and superior temporal regions. Tau‐PET was similarly associated with lower levels of COVID‐19‐related distress in the isthmus and rostral anterior cingulate (N=201 individuals). Furthermore, tau‐PET tracer uptake was significantly associated with increases in sleep quality as assessed by rate of change in Pittsburgh Sleep Quality Index before and during the pandemic (N=176 individuals). All results survived correction for multiple comparisons using random field theory with a cluster threshold of p < 0.001.ConclusionOur results suggest that those with increased tau deposition may have a weaker understanding of symptoms and prevention of COVID‐19 and lower levels of distress related to the pandemic than individuals with less brain tau. Individuals with higher tau may also experience improved sleep quality during the pandemic. While these observations appear to be favourable effects of tau, the first may suggest that public health information about COVID‐19 is less accessible to the aging population. The interactions and mediation of these effects remain to be properly elucidated.
Care processes related to clinical detection of Alzheimer’s disease in the U.S. Veterans Affairs Health Care System
Authors: Miller Donald R , Jasuja Guneet , Davila Heather W , Palnati Madhuri , Shao Qing , Dinesh Deepika , McDannold Sarah , Zhang Quanwu , Monfared Amir Abbas Tahami , Xia Weiming , Palacios Natalia , Moo Lauren R. 
Published: December 2021

AbstractBackgroundAlzheimer’s disease (AD) is a debilitating, progressive brain disorder that diminishes quality of life and represents immense burden of public health. This study characterizes healthcare utilization related to clinical detection of AD and care for AD patients in the US Veterans Affairs (VA) Healthcare System.MethodsUsing the VA Corporate Data Warehouse (2000‐2019), we studied Veterans aged ≥50 years who received ≥2 ICD‐10 codes (G30) for AD, with first code appearing in fiscal year 2018. We identified prior related ICD‐10 codes and summarized care processes during the years before and the year after the first AD code, including referrals to dementia‐related medical specialists (neurologists, geriatricians, geriatric psychiatrists), assessments by neuropsychological tests and radiological brain imaging, dementia medication prescriptions (donepezil, galantamine, memantine, rivastigmine), community‐based services (home health, adult day programs), and placements in institutional long‐term care in VA or community nursing homes.ResultsThe study cohort consisted of 6,046 Veterans (mean age of 80 years; 3% women; 22% non‐White race/ethnicity). Prior to the first ICD coding, 53.1% received codes for non‐specific dementia and 29.4% for mild cognitive impairment (MCI), with the first code appearing an average of 3 years before the first AD code. In the year before the first AD code, 51.1% visited specialists, 25.7% received neuropsychological assessments, 31.3% had brain imaging (but only 1.3% had a fluorodeoxyglucose‐PET scan), 30.2% received prescriptions for dementia medication, 45.8% received community‐based services, and 15.0% were admitted to institutional long‐term care. In the year following the initial AD code, 73.2% had specialty visits, 60.5% received dementia prescriptions, 63.6% received community‐based services, and 44.2% were admitted for institutional long‐term care.ConclusionsMedical and pharmacy utilization for non‐specific dementia or MCI begins years before AD detection, marked by the first AD‐specific clinical encounter in VA. Many AD patients do not receive specialty care and very few undergo a PET scan before AD detection. Community‐based home or day care and institutional nursing care increase with AD detection suggesting a substantial need for healthcare resources.
Increased CRP and triglyceride level associate with accelerated progression of Alzheimer's disease
Authors: Horvath Andras Attila 
Published: December 2021

AbstractBackgroundAlzheimer patients show various progression, so therapeutic considerations may also vary from individual to individual. Cardiovascular risk factors were analyzed in a prospective follow‐up.MethodWe included 112 Alzheimer’s patients for follow‐up. We collected epidemiological, demographic, and clinical data. Structural MRI, neuropsychological, and complete laboratory examinations including cardiovascular risk factors (CRP, cholesterol, triglyceride) were performed. Progression was monitored by repeated neuropsychological examinations for 3 years. Correlation analysis between laboratory, neuropsychological and structural MR values obtained at the time of diagnosis and group comparison for cardiovascular risks were used in the 0‐time point study. In the prospective study, correlation analysis and ANCOVA analysis were performed between the rate of cognitive impairment and laboratory values.ResultThe age of the studied patients was 74.3 ± 4.6 at the onset of the disease. No correlation was found between the examined values in the analysis at 0‐time point (all p> 0.05). However, in the prospective study, we found positive correlation between baseline triglyceride levels and disease worsening (r = + 0.27; p = 0.011). We also found significant correlation between baseline CRP levels and disease deterioration (r = + 0.53; p = 0.009), which was also confirmed by ANCOVA analysis taking into account age, sex, disease onset, and disease severity as covariance. There was a significant difference between the + 2SD and ‐2SD groups calculated for the mean CRP mean (F = 44.61, p = 0.013).ConclusionAt the time of diagnosis, there is no direct correlation between laboratory values and disease status, however, initial triglyceride and CRP values may indicate subsequent disease progression. Higher triglyceride and CRP levels are associated with increased disease progression, so these assays may be suitable for risk stratification and modification may be a therapeutic option to be considered individually.
Non‐invasive AI model for human functional patterns recognition in IADLs
Authors: Acosta‐Franco Jesus Alejandro , García‐Moreno Ciro Andrés Martínez , García‐Vázquez Mireya Saraí , Ramírez‐Acosta Alejandro Álvaro 
Published: December 2021

AbstractBackgroundAlzheimer's Disease (AD) diagnosis at early stages currently represents an important challenge for the scientific community, which is gradually accentuated due to the global perspective of population aging. Current clinical processes for the diagnosis of this disease are increasingly effective; these include invasive tests of nervous system biomarkers, which are complemented by non‐invasive tests of human cognitive and functional performance, such as the mini‐mental state examination and the analysis of Instrumental Activities of Daily Living (IADLs).MethodThe present work is centered around the development of technological tools for creating an automated model to support the diagnosis of early AD disease. We present a novel non‐invasive methodology for the development of an Artificial Intelligence‐based model, which analyzes human biomechanical markers of IADLs activities to recognize human functional patterns. For the development of this model, we have built a dataset of egocentric videos containing IADLs activities, organized in four classes, based on the prehensile patterns of the hands: strength and precision, and on the kinematics of the instruments: displacement and manipulation. We have characterized the dataset using mathematical methods to get information to directly emulate the relationship with Lawton and Brody's geriatric test, which is used in clinical protocols to estimate human functional capacity. This characterization relationship between biomechanical markers and human functional patterns represents a benefit for quantitative and objective assessment in support of geriatric evaluation and patient follow‐up.ResultOur proposed model results in an accuracy of 73.74% in the recognition of human functional patterns related to the kinematics of the instruments, 59.84% in the analysis of the prehensile pattern of the hands, and 48.5% when the classes were recognized independently.ConclusionThis allows us to establish in a quantifiable way performance region benchmarks of human functional capacity for IADLs activities, by obtaining a support model in the diagnostic evaluation of AD disease at early stages. Our proposed model allows us to establish the guideline to improve the automatic recognition of human functional patterns, of which we obtained an acceptable percentage testing instruments kinematics', followed by the hands' prehensile patterns.
17alpha‐estradiol improves systemic and neural outcomes in middle‐aged APOE4 mice
Authors: Qian Wenjie , Christensen Amy , Lu Ryan , Finch Caleb E , Benayoun Bérénice A. , Pike Christian J. 
Published: December 2021

AbstractBackgroundIn this study, we investigate the hypothesis that recently identified longevity‐promoting intervention 17α‐estradiol (17αE2) will protect against senescent changes in brain and throughout the body that are associated with APOE4 and heightened AD risk. The most significant genetic factor for late‐onset Alzheimer’s disease (AD) is the apolipoprotein E gene (APOE): AD risk is reduced by the APOE2 variant and increased by the APOE4 variant. APOE genotype is associated with longevity in the same pattern, with APOE2 linked with increased and APOE4 with decreased lifespan. This is of particular interest as advanced age is the single greatest risk factor for AD. Indeed, APOE genotype may regulate AD vulnerability in part by affecting aging processes. Thus, compounds that increase health and longevity may be particularly relevant to APOE4‐associated AD risk.MethodMale mice homozygous for human APOE3 or APOE4 were maintained on normal chow in the absence or presence of 14.4 ppm 17αE2 for 20 weeks, starting at age 10 months. Animals were assessed on a range of systemic metabolic, inflammatory, and frailty outcomes as well as on established areas of APOE4‐associated neural impairment, including neuroinflammation, neurogenesis, and cognition.ResultIn middle‐aged male mice, APOE4 genotype was associated with significantly poorer systemic and neural phenotypes relative to APOE3 genotype. In general, treatment with 17αE2 yielded improvements in both APOE3 and APOE4 mice across multiple measures, though the benefits were typically much stronger in APOE4 mice. For example, 17αE2 reduced body weight, plasma leptin, hepatic steatosis, and frailty index more strongly in APOE4 than APOE3 mice. Neural results are pending.ConclusionThese data confirm and extend prior findings that APOE4 is associated with senescent effects both peripherally and neurally, outcomes linked with AD risk. Importantly, 17αE2 significantly improved a range of measures. This study will establish proof‐of‐principle for 17αE2 as an AD therapeutic with efficacy predicted to be strongest in APOE4 genotype. Given that the majority of AD cases in the U.S. are APOE4 carriers, mitigating the effects of APOE4 would have significant therapeutic potential.Supported by the NIA (RF1AG058068) and the Cure Alzheimer’s Fund.