bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations between Low‐value Medication in Dementia and Healthcare Costs
Authors: Platen Moritz , Hoffmann Wolfgang , Michalowsky Bernhard 
Published: December 2022

AbstractBackgroundLow‐value medication (Lvm) provides little or no benefit to patients may be harmful and wastes healthcare resources. However, there is evidence from the literature that Lvm is highly prevalent in age‐associated mental illnesses, such as dementia. Evidence about the financial consequences of Lvm among people living with dementia (PwD) is limited. This study analyzed the association between receiving Lvm and healthcare costs from a payers’ perspective.MethodThis analysis is based on data of 516 community‐dwelling PwD. In total, 14 Lvm were extracted from 1) dementia‐specific guidelines, 2) the German equivalent of the Choosing Wisely campaign, and 3) the PRISCUS list. Healthcare utilization was retrospectively assessed via face‐to‐face interviews with PwD, caregivers, and professional care staff and monetarized by standardized unit costs to calculate costs from a payer perspective. Associations between Lvm and healthcare costs were analyzed using multiple linear regression models.ResultEvery third person living with dementia (n = 159, 31%) received Lvm. PwD who received Lvm were less cognitively impaired (Mini Mental State 23.0 vs. 21.7, p = 0.013). To receive Lvm was associated with higher medical care costs (b = 2,520€; CI95% 1,252€ – 3,788€, p< 0.001), particularly due to higher prevalence of in‐hospital treatment (b = 1,576€; CI95% 424€ – 2,728€, p = 0.007) and higher cost for medication (b = 784€; CI95% 466€ – 1,101€, p< 0.001).ConclusionLvm was very prevalent, more likely to occur in the early stages of dementia and can cause financial harm for payers due to higher costs for in‐hospital care and medications. Further research is required to derive measures to prevent cost‐driving Lvm in primary care and move health expenditures towards higher‐value resource use.
Prediction of cognitive decline for enrichment of Alzheimer’s disease clinical trials with machine learning
Authors: Tam Angela , Laurent César , Dansereau Christian 
Published: December 2022

AbstractBackgroundMany participants do not experience cognitive decline during clinical trials, which reduces the power of trials to detect treatment effects. As an enrichment strategy, we use machine learning to identify individuals who will likely decline throughout the typical duration of a clinical trial.MethodBaseline MRI, cognitive tests, demographics, and APOE genotype were used to classify decliners, i.e. individuals whose CDR‐Sum of Boxes increased during a predefined time window, and stable individuals. A model to predict decline at 24 months was trained on a discovery dataset of patients with early AD (clinical diagnosis of mild cognitive impairment or AD dementia) from ADNI1 and NACC2 (n = 1151). This model was then validated on a Phase 3 trial placebo arm (n = 115) and the PharmaCog3 initiative (n = 76). A second model to predict decline at 48 months in presymptomatic populations was trained on a discovery dataset of 628 individuals from ADNI and NACC who were cognitively unimpaired at baseline and then validated on OASIS‐34 (n = 128).ResultThe models achieved up to 79% AUC (cross‐validated and out‐of‐sample). We estimated the required sample sizes per arm to detect a 30% treatment effect at 80% power. An early AD clinical trial with an unenriched cohort would require 422 participants, while using the enriched cohort of likely decliners identified by our model can reduce the necessary sample size to 206 individuals. Similarly, a presymptomatic AD trail would require 2577 individuals, while using the enriched cohort of likely decliners identified by our model can reduce the necessary sample size to 1412 individuals. In both early AD and presymptomatic populations, the predicted decliners experienced a cognitive worsening that was at least three times as severe as the predicted stable group (Figure 1).ConclusionOur prognostic tool to enrich trials with participants likely to decline can reduce sample sizes by as much as 51%. Such a tool can improve trial quality, reduce trial costs, and increase the likelihood of a trial’s success.[1] adni.loni.usc.edu[2] naccdata.org[3] www.imi.europa.eu/projects‐results/project‐factsheets/pharma‐cog[4] oasis‐brains.org
Posttraumatic Stress Disorder and Risk For Dementia
Authors: Neylan Thomas C. 
Published: December 2022

AbstractBackgroundAccumulating evidence demonstrates that PTSD is associated with higher risk for neurodegenerative disorders. However, the mechanism which drives this relationship and the question of whether the increased risk pertains to the full spectrum of all neurodegenerative disorders is not known. Given that neurodegeneration, as with most illnesses, is caused by complex gene by environment factors, PTSD may be an important disorder to study given that trauma exposure is a large impact environmental exposure.MethodThis presentation will start with a brief review of prospective epidemiologic studies that examine the potential bidirectional relationship between PTSD and dementia disorders. Next, data from the Department of Defense Alzheimer’s Disease Neuroimaging Initiative (DoD ADNI) on amyloid and tau PET imaging in older Vietnam veterans will be presented.ResultData from multiple prospective studies show that having a diagnosis of PTSD is associated with higher risk of subsequent dementia. Further, evidence suggests that PTSD is associated with elevated risk for all types of neurodegenerative disorders including Parkinson’s Disease, though there may be a stronger link to Frontotemporal and Vascular Dementias. Results from a sample 289 non‐demented veterans with PTSD and/or TBI and controls in the DoD ADNI cohort did not show evidence of higher cortical amyloid or tau burden. PTSD was associated with higher prevalence of mild cognitive impairment but in the absence of elevated biomarkers of Alzheimer’s Disease.ConclusionThere are many important questions that need to be resolved to understand what mechanistic pathways for neurodegeneration are facilitated by PTSD. If results from the DoD ADNI study generalize, then future work should focus on whether PTSD increases risk for non‐AD tauopathies or synucleinopathies. Further, the strong association of PTSD with chronic sleep disturbance and elevated pro‐inflammatory cytokines also suggest that need to focus on these candidate mechanisms for accounting for the link between traumatic stress exposure and the development of neurodegenerative disorders.
Sex differences in dementia risk and gray matter volume associated with hearing impairment
Authors: Fitzhugh Megan C , Pa Judy 
Published: December 2022

AbstractBackgroundHearing impairment is highly prevalent in older adults and was recently recognized as a modifiable risk factor for dementia. However, it is unknown if risk differs by sex and whether other issues associated with hearing, like social engagement or depression, impact these associations.MethodUK Biobank data was used to identify 165,471 participants (57±8 years, 55% female) without dementia who had a hearing assessment at baseline. Hearing was assessed using a speech reception threshold task, with scores grouped into good, insufficient, and poor severity levels based on previously derived cut‐offs (Dawes et al., 2014). Cox proportional‐hazard models were used to investigate sex differences in the association between hearing impairment and dementia risk. Sensitivity analyses were conducted to determine if social engagement or depressive symptoms mediated these associations. In a subset of participants with MRI data (n=2,322, 62±7 years, 52% female), linear mixed models stratified by sex were conducted to examine if development of impaired hearing from baseline was associated with gray matter atrophy in auditory and limbic regions.ResultInsufficient and poor hearing were associated with increased risk for dementia compared to good hearing (HR=1.76, 95%CI 1.43‐2.18 and HR=2.13, 95%CI 1.46‐3.11, respectively), but differed by sex. Women with insufficient (HR=1.73, 95% CI 1.25‐2.40) and poor (HR=3.08, 95%CI 1.80‐5.28) hearing had the greatest risk of dementia, whereas only men with insufficient hearing had increased risk (HR=1.78, 95%CI 1.34‐2.35; poor HR=1.60 95%CI 0.94‐2.73). These relationships were not mediated by social engagement or depression. In the MRI subset, women who developed or maintained impaired hearing had greater atrophy over 2.29 years in auditory pathway (e.g., primary auditory cortex, thalamus) and limbic (e.g., hippocampus, parahippocampus, amygdala) regions compared to women with good hearing. Men who developed impairment exhibited decreases over 2.30 years in a secondary auditory region only.ConclusionWomen with impaired hearing have greater risk of dementia compared to men. These sex differences are not mediated by social engagement or depression. Women with impaired hearing exhibit greater atrophy in auditory and limbic regions, while men do not. Sex differences in gray matter atrophy may explain why women with impaired hearing are at greater risk of dementia.
Tracing the metabolic rewiring of glycolytically compromised neurons
Authors: Sei Yoshitaka J , Bennet Neal , Yang Joyce , Li Huihui , Nakamura Ken 
Published: December 2022

AbstractBackgroundWhile a reduction in cerebral glucose uptake is a diagnostic trait of Alzheimer’s Disease, the neuronal requirement for the uptake and metabolism of glucose is not well understood. To dissect how neurons metabolize glucose, we tracked [U‐13C]glucose metabolism in human iPSC‐derived neurons.MethodHuman WTC‐11 iPSCs expressing the CRISPR inhibition machinery dCas9‐KRAB were differentiated into neurons using a doxycycline‐inducible NGN2. After a 2 week maturation period, neurons were incubated with [U‐13C]glucose at either a physiologically relevant 1.5 mM or a glucose‐scarce 0.15 mM concentration for 24 hours prior to metabolite extraction. To determine the importance of glucose uptake to neurons, a guide for the neuronal glucose transporter GLUT3 was added to the CRISPR machinery to limit the neuronal uptake of glucose (GLUT3 KD). These GLUT3 KD neurons were compared to neurons with uninhibited glucose uptake (non‐target). Student t‐tests or two‐way ANOVAs with Bonferonni correction were used to compare metabolite levels between neuronal groups and the concentration of extracellular [U‐13C]glucose.ResultUnder physiologically relevant glucose conditions, GLUT3 KD neurons had decreased levels of labeled glucose. Despite the difference in internalized glucose, GLUT3 KD did not affect the amount of [U‐13C]glucose‐derived citrate that feeds the TCA cycle. The labeled level of a critical pentose phosphate pathway (PPP) metabolite, R5P, was decreased in GLUT3 KD neurons. When measuring the total levels, both labeled and unlabeled, of R5P and citrate, we found there to be no significant effect of GLUT3 KD. This trend was also observed in a 0.15 mM [U‐13C]glucose condition. With the change in R5P levels exclusively in the amount derived from [U‐13C]glucose, we found that neurons prioritize the usage of glucose to feed the TCA cycle over the PPP.ConclusionNeurons rewire their metabolism in response to glucose shortages, demonstrating their sensitivity to and reliance on the availability of glucose. During limited access to glucose, glucose utilization was pulled away from the PPP and shunted to the TCA cycle. In the context of AD, the connection between glucose shortages in neurons and their bioenergetic dysfunction is a critical point of discussion centered on understanding the mechanistic initiation of neurodegeneration.
Overlap of genetic risk for Lewy body and Alzheimer’s disease pathology
Authors: Talyansky Seth D. , Guen Yann Le , Pham Kaitlyn , Belloy Michael E , Kasireddy Nandita , Greicius Michael D 
Published: December 2022

AbstractBackgroundLewy body (LB) pathology is relatively understudied compared to Alzheimer’s disease (AD) pathology, and the genetic risk overlap between the two remains unclear. Chia et al. (2021) identified five genomic loci significantly associated with LB pathology in a genome‐wide association study (GWAS) of LB dementia cases and controls (N = 6,618), where 69% of cases and 15% of controls were pathologically confirmed. Here we gathered a largely distinct set of individuals (5.1% overlap) with genetic data and postmortem assessment for both AD and LB pathology (N = 6,002) to estimate the odds ratio (OR) for risk of sole AD pathology (AD+LB−), sole LB pathology (AD−LB+), and dual AD‐LB pathology (AD+LB+) for the five variants reported by Chia et al. We compared our results for APOE to ORs reported by Tsuang et al. (2013).MethodOur initial study population comprised 4,579 subjects from the National Alzheimer’s Coordinating Center and 1,423 from the Rush University Medical Center assessed for AD and LB pathology. We separately used criteria from Tsuang et al. and from Kaivola et al. (2021) to classify subjects as AD+LB+, AD+LB−, AD−LB+, or AD−LB−. We performed a GWAS for three phenotypic contrasts: each of AD+LB−, AD−LB+, and AD+LB+ against AD−LB−. We estimated ORs for the variants of interest.ResultWe found that rs769449 (APOE locus) was associated with AD+LB+ and AD+LB− at the genome‐wide significance level and nominally associated with AD−LB+, though with OR estimates lower than those reported by Tsuang et al. We obtained qualitatively similar results for rs6733839 (BIN1). The lead variants reported at the GBA, TMEM175, and SNCA‐AS1 loci (or proxies in high linkage disequilibrium) were not associated with a pathological phenotype, although an independent intronic variant of GBA was nominally associated with AD+LB+ and AD−LB+.ConclusionOur results suggest that APOE and BIN1 are associated with both AD and LB pathology, while GBA is associated with LB but not AD pathology. The ORs reported by Tsuang et al. for APOE‐associated risk for single and dual AD‐LB pathology may overestimate the true population values. Overall, AD and LB pathology share APOE and BIN1 as risk factors.
Weights analysis for CNN models in MRI classification
Authors: Khagi Bijen , Kwon Goo‐Rak 
Published: December 2022

AbstractBackgroundIn deep neural network learnable parameters like weights and bias of convolution kernel, normalization layer or fully connected layers (FCLs) are the one responsible for giving prediction score. Though one parameter or parameters in a layer has not decisive role, however when whole network prediction is to be done, each one has role to generate prediction value. Hence, they are important for the network performance.MethodWe modeled a CNN for classification and trained it using 50% of total MRI scans for 3 classes. After training the network for 50 epochs, the network reaches convergences with 100% training accuracy and around 70% validation accuracy. Then, the trained models’ parameters i.e., weights and bias of FCL layers were analyzed class wise for any correlation with its parent class.ResultThe weights of final FCL are plotted as in Figure 1. The correlation matrix for weights on sample MRIs with trained weights are shown in Tables 1 and 2. Here, two activation functions were used for final test results were ReLU and Leaky ReLU with final test accuracy around 67.3% and 70.9% respectively.ConclusionWe attempted to study the weights pattern in FCL layer for a trained CNN model along with its correlation value for each class.[Acknowledgement]This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF‐2021R1I1A3050703). And this research was supported by the BrainKorea21Four Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (4299990114316).
Mild behavioral impairment symptom severity predicts tau hyperphosphorylation assessed by plasma p‐tau181 across the Alzheimer’s disease spectrum
Authors: Lussier Firoza Z , Therriault Joseph , Tissot Cécile , Servaes Stijn , Benedet Andréa Lessa , Ashton Nicholas J. , Karikari Thomas K , Chamoun Mira , Stevenson Jenna , Rahmouni Nesrine , Zetterberg Henrik , Blennow Kaj , Ismail Zahinoor , Pascoal Tharick A , Rosa‐Neto Pedro 
Published: December 2022

AbstractBackgroundMild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by the emergence of persistent non‐cognitive neuropsychiatric symptoms (NPS) in older adults, representing an at‐risk state for dementia and a potential marker of Alzheimer’s disease (AD). However, few studies have investigated associations between MBI and plasma biomarkers of AD pathophysiology, specifically tau hyperphosphorylation.MethodIndividuals across the AD spectrum (cognitively unimpaired (CU) and impaired (CI)) were selected from the Translational Biomarkers of Aging and Dementia (TRIAD) cohort. MBI was assessed using the MBI‐Checklist (MBI‐C), which assesses NPS severity in five subdomains: decreased motivation (apathy), emotional dysregulation (mood/anxiety symptoms), impulse dyscontrol (agitation, impulsivity, abnormal reward salience), social inappropriateness (impaired social cognition), and abnormal thoughts/perception (psychosis). Plasma levels of p‐tau181 were quantified in all individual, and log‐transformed due to right skew. Spearman correlation analysis investigated cross‐sectional associations between plasma p‐tau181 and MBI‐C scores, and between baseline plasma p‐tau181 and annual change in MBI‐C. Multivariable linear regression analyses assessed the ability of cross‐sectional and longitudinal MBI‐C scores to predict plasma p‐tau181, adjusting for age, sex, education, and diagnostic group (CU/CI, Aβ +/‐).ResultCross‐sectional MBI data were available for 211 individuals, with longitudinal data available for 128 individuals (). Significant correlations were found between plasma p‐tau181 and MBI‐C total and apathy scores in the cross‐sectional sample (Figure A). Further, significant correlations were found with plasma p‐tau181 and the annual change in MBI‐C total and apathy scores (Figure B). These associations were corroborated by significant standardized and adjusted regression coefficients from multivariate regression models, which showed that baseline and longitudinal MBI‐C total and apathy score predicted plasma level of p‐tau181 (Figure C).ConclusionOur study provides novel findings on the association between MBI and tau hyperphosphorylation assessed using plasma biomarkers in an AD cohort. These results add to the existing evidence for MBI as a clinical manifestation of AD pathology and support the use of the MBI‐C as an enrichment tool for clinical trial enrollment and therapeutic intervention.
Association between mid‐ and late‐ life cardiometabolic multimorbidity and dementia risk: a nationwide twin study
Authors: Dove Abigail , Guo Jie , Fastbom Johan , Marseglia Anna , Vetrano Davide Liborio , Pedersen Nancy L. , Xu Weili 
Published: December 2022

AbstractBackgroundCardiometabolic diseases (CMDs) have been linked to increased dementia risk, but their combined impact on dementia and its major subtypes remains unknown. We aimed to examine the association between mid‐ and late‐ life onset cardiometabolic multimorbidity with risk of dementia, Alzheimer’s disease (AD), and vascular dementia (VaD), and to explore whether genetic background contributes to this association.MethodWithin the Swedish Twin Registry, 17,387 dementia‐free individuals aged ≥60 were followed for up to 18 years to detect incident dementia. Dementia (including AD and VaD) was identified based medical records from the National Patient Registry (NPR) and the Swedish Cause of Death Register. CMDs (including type 2 diabetes, heart disease, and stroke) and age at onset (mid‐life [<60 years] vs. late life [≥60 years]) were ascertained from NPR records. CMD multimorbidity was defined as the presence of ≥2 co‐morbid CMDs. Data were analyzed using two strategies: 1) unmatched analysis using Cox models conducted among all twin individuals (to assess the CMD‐dementia association); and 2) co‐twin matched analysis using Cox models stratified by zygosity in dementia‐discordant pairs (to assess the role of genetics in this association).ResultOf all participants, 3,176 (18.3%) had a single CMD and 789 (4.5%) had CMD multimorbidity at baseline. During the follow‐up, 2,494 participants developed dementia (including 817 AD and 515 VaD cases). The hazards ratios (HRs, 95% CIs [confidence intervals]) of dementia were 1.36 (1.23‐1.51) (1.23, 1.03‐1.49 for AD and 1.53, 1.23‐1.89 for VaD) for a single CMD, and 1.82 (1.48‐2.23) (1.39, 0.93‐2.09 for AD and 2.41, 1.64‐3.55 for VaD) for CMD multimorbidity. In stratified analysis, the HRs of the associations between mid‐ and late‐ life onset CMD multimorbidity and dementia were 2.47 (1.43‐4.28) and 1.72 (1.39‐2.14), respectively. In co‐twin matched analysis, the CMD‐dementia association remained significant in dizygotic twins (n = 544; HR 1.68, 95% CI 1.26‐2.39), but was greatly attenuated among monozygotic twins (n = 102; 0.84, 0.42‐1.65) (p = 0.045 for interaction).ConclusionCardiometabolic multimorbidity, particularly in mid‐life, is associated with an increased risk of dementia, AD, and VaD after age 60. Genetic background appears to underpin the CMD‐dementia association.
Tau PET shows both direct and atrophy‐mediated effects on cognition: 4‐way decomposition of the effects of tau PET and atrophy on cognitive performance
Authors: Higgins Cesar , Aslanyan Vahan , Cody Karly Alex , Ward Tyler J. , Choi Seo‐Eun , Wei Jingkai , Amofa Priscilla A , Crane Paul K. , Harrison Theresa M. 
Published: December 2022

AbstractBackgroundEvidence suggests that tau pathology predicts subsequent neurodegeneration and that atrophy is associated with cognitive impairment. However, in vivo studies have shown that structural measures only partially mediate tau‐cognition relationships, with direct effects of tau on cognition remaining. The objective of current study is to decompose the overall effect of tau on domain‐specific cognitive performance, in the presence of atrophy as a mediator with which tau may interact.Method705 participants with flortaucipir (FTP)‐PET were selected from Alzheimer’s Disease Neuroimaging Initiative—3 (Table 1). MRI scans closest to FTP were used to measure cortical thickness and volume in a priori regions (Desikan atlas, FreeSurfer v7.1) associated with memory, executive function, language, and visuospatial cognitive domains. Using a causal mediation framework, tau accumulation measured with FTP‐PET in a temporal meta‐region was the primary exposure, cognitive domain scores were the primary outcomes and regional structural measures were the hypothesized mediators. Statistical models incorporating exposure—mediator interactions (4‐way decomposition) were used to identify natural direct and indirect effects.ResultAcross the entire cohort (age 74.26 (7.82), 58% cognitively unimpaired, 30.8% MCI, 11.2% Demented), regional morphometry in medial temporal lobe (MTL) subregions selected a priori for their relationship with memory function mediated the effect of tau on all cognitive domains (Table 2). Hippocampal volume had the largest total indirect effect (mediating the effect of tau) across all domains (37% (95% confidence intervals (CI): 28%, 47%) for memory, 28% (CI: 18%, 38%) for executive function, 37% (CI: 24%, 50%) for language, and 29% (CI: 10%, 49%) for the visuospatial domain). Similar mediating effects were observed for entorhinal cortical thickness and to a lesser extent parahippocampal cortical thickness. In contrast, the morphology of regions selected a priori based on functional neuroanatomical associations with executive function, language or visuospatial domains did not mediate tau‐cognition relationships.ConclusionOur results suggest that the effect of MTL atrophy on tau‐cognition associations may extend beyond memory function and be an important mechanism by which tau accumulation affects multiple cognitive domains. Follow‐up longitudinal studies will help to characterize the temporal dynamics of atrophy‐mediated associations between tau and cognition.