bluuebunny/crossref_metadata_2025_split huggingface dataset:
Higher fronto‐parietal metabolism parallels a greater impact of amyloid and anxiety on medial temporal areas in women versus men
Authors: Arenaza‐Urquijo Eider M , Salvadó Gemma , Milà‐Alomà Marta , Shekari Mahnaz , Sánchez‐Benavides Gonzalo , Cacciaglia Raffaele , Minguillón Carolina , Vilor‐Tejedor Natalia , Crous‐Bou Marta , Grau‐Rivera Oriol , Sala‐Vila Aleix , Eichenlaub Udo , Kollmorgen Gwendlyn , Suárez‐Calvet Marc , Blennow Kaj , Zetterberg Henrik , Gispert Juan Domingo , Molinuevo Jose Luis , Study ALFA , Consortium EPAD 
Published: December 2020

AbstractBackgroundThe higher prevalence of anxiety‐related disorders in women, as well as the lower opportunities for higher education, may explain differences in brain resilience to AD pathologies. The objectives were to (1) test sex‐differences on brain metabolism and (2) evaluate whether the effects of amyloid, tau, education and anxiety on brain metabolism and structure differ by sex.MethodWe included a total of 1327 non‐demented participants, 235 cognitively unimpaired adults from the ALFA+ study (50‐74 years, 66% women) and 1092 non‐demented older adults from EPAD (50‐88 years, 57% women). Participants had available Aβ42 and p‐tau CSF biomarkers (Roche NeuroToolKit robust prototype assays and Elecsys®), anxiety assessments, FDG‐PET (ALFA+) or hippocampal volumes (EPAD). First, in ALFA+, we ran voxel‐wise multiple regression models to assess the effects of sex, and sex*amyloid, sex*p‐tau, sex*education and sex*anxiety interactions on FDG‐PET scans (adjusted by age). Second, in EPAD, we ran the same models with TIV‐adjusted hippocampal volumes as outcome measures.ResultIn the ALFA+ cohort, there were no sex‐differences in age (p=0.09), or CSF biomarkers (all p>0.7). Women showed lower education (p=0.001) and higher anxiety scores (p<0.001) than men. In the EPAD cohort, women were younger (p=0.003), lower educated p=0.003) and showed higher anxiety levels (p=0.002); men showed lower CSF Aβ42 levels (p=0.02). In voxel‐wise multiple regression analyses (ALFA+), women showed higher FDG‐PET uptake than men in medial fronto‐parietal regions, irrespective of their age, education, anxiety and CSF biomarkers levels (Fig1). There was a sex*Aβ and sex*anxiety interaction, such that with increasing Aβ deposition or anxiety levels, women showed lower metabolism in the parahippocampus and hippocampus than men (Fig2, 3). There was no sex*p‐tau or sex*education interaction. In the EPAD cohort, we did not observe any interactions. However, sex‐stratified analyses showed an association of CSF Aβ42, p‐tau and anxiety levels with lower hippocampal volumes in women but not men (Table 1, Fig4).ConclusionOur results suggest higher fronto‐parietal metabolism coupled with lower metabolic and structural resilience in medial temporal regions in women. The effects of anxiety and AD pathologies converged in memory‐related brain areas. Brain resilience mechanisms may differ between women and men.
TBI and increased risk of non‐Alzheimer’s disease dementia in older male twins
Authors: Chanti‐Ketterl Marianne , Pieper Carl F , Yaffe Kristine , Plassman Brenda L 
Published: December 2020

AbstractBackgroundSeveral studies have reported an association between traumatic brain injury(TBI) and increased risk of Alzheimer’s disease(AD) and all cause dementia. Considering the heterogeneous genetic and environmental factors that may contribute to development of dementia, co‐twin control analyses provide a level of control for confounding factors that is difficult to achieve with other case‐control designs.MethodsA total of 8787 members of the NAS‐NRC Twin Registry of Male WWII Veterans born between 1917‐1927 were included in the study. Self or proxy‐reported history of TBI was collected from 1990–2005. In‐person dementia evaluations were conducted in participants’ homes and differential diagnoses and age of onset of dementia were assigned by an expert adjudication panel. Proportional hazard models, adjusting for education and twin strata, were used to estimate the risk of dementia associated with TBI in the full sample. In a subsample, the McNemar’s test was used to examine the association between TBI and dementia within twin pairs to control for shared genetic and environmental risk factors for dementia within the pairs.ResultsOf the 8787 men, 25% reported a history of TBI, while 3.8% had AD and 1.9% had other types of dementia. Median age of dementia onset was 75 years. The mean age of first TBI for those without dementia was 33 years (SD=23) and 38 (SD=24) for those with dementia. Hazard models show those with TBI had over twice the risk of being diagnosed with other cause dementia after a TBI (hazard ratio (HR) 2.29; 95%CI,1.2‐4.4), but not for risk of AD (HR 1.08; 95%CI,0.7‐1.6). A total of 108 twin pairs were discordant for presence of TBI and diagnosis of dementia or age of onset of dementia by at least 3 years. Within these twin pairs, TBI was associated with greater risk of other cause dementia (n=40 pairs), McNemar odds ratio (OR) 2.6, 95%CI 1.3‐5.3, but not for AD (n=68 pairs), OR 1.1, 95%CI 0.7‐1.8.ConclusionOur findings indicate that TBI may be associated with risk of types of dementia other than AD. This result held even after controlling for many unidentified shared genetic and early life environmental factors within twin pairs.
Untargeted metabolomics reveals sugar and homocysteine dysregulations in prodromal AD
Authors: Hajjar Ihab , Liu Chang , Jones Dean , Uppal Karan 
Published: December 2020

AbstractBackgroundAltered metabolism may occur early in Alzheimer’s disease (AD). We used untargeted high‐resolution metabolomics in the cerebrospinal fluid (CSF) in mild cognitive impairment (MCI) to identify these alterationsMethodCSF from 92 normal controls and 93 MCI underwent untargeted metabolomics using high‐resolution mass spectrometry with liquid chromatography. Partial least squares discriminant analysis was used followed by metabolite annotation and pathway enrichment analysis (PES). Significant features were correlated with disease phenotypes using spearman correlation.ResultWe identified 294 features differentially expressed between the 2 groups and 94 were annotated. PES showed that pathways related to sugar regulation (N‐Glycan, p=0.0007; sialic acid, p=0.0014; Aminosugars, p=0.0042; galactose, p=0.0054) homocysteine regulation (p=0.0081) were differentially activated and significant features within these pathways correlated with disease phenotypesConclusionWe identified a metabolic signature characterized by impairments in sugar and homocysteine regulation in prodromal AD. Targeting these changes may offer new therapeutic approaches to AD.
Characterizing clinical misdiagnosis of dementia using Medicare claims records linked to Rush Alzheimer’s Disease Center (RADC) cohort study data
Authors: James Bryan D , Power Melinda C , Gianattasio Kan Z , Lamar Melissa , Oveisgharan Shahram , Shah Raj C , Marquez David X , Barnes Lisa L , Bennett David A 
Published: December 2020

AbstractBackgroundLinkage of Medicare claims records to cohort studies of aging provides the opportunity to study misdiagnosis of dementia in clinical settings for older adults.MethodsWe linked 1991‐2016 fee‐for‐service Medicare Part A&B claims to data from 5 RADC cohorts (MAP, ROS, MARS, Clinical Core, and Latino Core). We assigned dementia status based on annual detailed cognitive evaluation and assigned clinical dementia diagnosis status using ICD‐9/ICD‐10 codes from Medicare claims (primary or secondary diagnoses) during participants’ study enrollment period. We classified persons as underdiagnosed if they did not have a clinical dementia diagnosis in 2 or more Medicare claims recorded up to 3 years leading to, and 1 year following the date of the first RADC assessment indicating dementia, and overdiagnosed if they did not have any RADC assessments indicating dementia but had a clinical dementia diagnosis in 2 or more claims recorded during the study period.ResultsOf the total 3,533 participants, 78% received the correct clinical diagnosis, 11% were underdiagnosed in Medicare claims, and 11% were overdiagnosed. Of the 703 persons who developed dementia, 381 (54%) were clinically underdiagnosed (i.e., sensitivity=46%), while 389 (14%) of 2,830 persons who did not develop dementia were overdiagnosed (specificity=86%).ConclusionsThis preliminary analysis corroborates previous findings from the Health and Retirement Study (HRS) and others that there is substantial misdiagnosis of dementia in clinical settings as recorded in fee‐for‐service Medicare claims when compared to comprehensive assessment for research, especially in regards to low sensitivity. Future work will examine predictors and consequences of clinical misdiagnosis.
Alternatives to MMRM for preclinical Alzheimer’s clinical trials
Authors: Donohue Michael C. , Sethuraman Gopalan , Langford Oliver , Lin Wenyi , Insel Philip , Thompson Wesley K. , Raman Rema , Sperling Reisa A. , Aisen Paul S. 
Published: December 2020

AbstractBackgroundThe Mixed Model for Repeated Measures (MMRM; Mallinckrodt, et al. 2001) is the most commonly used approach for assessing treatment effects in Alzheimer’s clinical trials. An alternative nonlinear Disease Progression Model (DPM) which assumes the ratio of group means is fixed over time has been proposed for DIAN‐TU (e.g. Wang, et al. 2018). We assess nonlinear models and alternative linear models for Preclinical Alzheimer’s clinical trials like the A4 Study (Sperling, et al. 2014).MethodTables 1 and 2 describe the mean and correlation structures that we considered. Models were fit to data from cognitively normal ADNI participants (amyloid positive vs negative). We compared mean PACC trajectories over time and Akaike Information Criterion (AIC; Sakamoto, et al 1986). All models were fit by maximum likelihood using the R package nlme. Simulations were used to assess power and Type I error for clinical trials in Preclinical Alzheimer’s (Figure 1).ResultsFigure 2 demonstrates the various mean structures fit to ADNI. Models with stronger shape assumptions are smoother than the unstructured mean of MMRM (dashed lines). The DPM‐like nonlinear model with fixed group mean ratio (“NL0”) provides a relative underestimate of the amyloid group difference at final visit. Comparing values of AIC (Figure 3), we find little evidence to support using alternatives to the unstructured mean and variance of the typical MMRM. Simulation studies (Table 3) suggest that power can be improved with simpler mean structures (Hybrid or Quadratic), while maintaining good Type I error control with an unstructured variance. It was difficult to fit the nonlinear models with the full suite of correlation structures. The NL0 could be reliably fit with random intercept and heterogeneous variance but showed no advantage over the simpler Hybrid or Quadratic mean structures.ConclusionADNI data support the use of the MMRM with unstructured mean and variance, but simulations suggest simpler mean structures might provide a modest improvement in the power from 85%, with an unstructured mean, to 90%, with Hybrid or Quadratic mean. Nonlinear DPM‐like models demonstrated no advantage over linear model alternatives in ADNI and in simulations of Preclinical Alzheimer’s clinical trials.
Astrocyte glutamate uptake impacts [18F]FDG‐PET signal
Authors: da Rocha Andreia Silva , de Souza Débora Guerini , Bellaver Bruna , Fontana Igor C. , Machado Luiza Santos , Venturin Gianina Teribele , Greggio Samuel , da Costa Jaderson Costa , Souza Diogo O. , Zimmer Eduardo R. 
Published: December 2020

AbstractBackgroundThe role of astrocytes on brain functioning has become an important topic of debate. In this regard, an issue that still remains controversial is the astrocytes contribution to glucose brain metabolism and, therefore, to the uptake of 2‐Deoxy‐2‐[18F]Fluoroglucose([18F]FDG) detected by positron emission tomography(PET). For many years, it was widely assumed that the brain [18F]FDG‐PET signal directly reflects the neuronal use of glucose, overlooking the possible participation of other brain cells. Recently, rodent and human studies have demonstrated that astrocytes may contribute to [18F]FDG‐PET signal. To further explore these early findings, here, we used a pharmacological challenge on rodents. Clozapine was selected because it is known to decrease, on astrocytes, glutamate transport and the glutamate transporter 1 (GLT‐1) levels, an important trigger for glucose uptake in astrocytes.MethodsClozapine was administered for six weeks (25‐35mg/kg) to adult Wistar rats. Glucose brain metabolism was assessed using [18F]FDG‐microPET before and after the treatment. [3H]D‐Aspartate uptake was evaluated on brain slices. [3H]Glutamate release was analyzed on synaptosomal preparations. [3H]D‐Aspartate and [3H]2‐Deoxyglucose uptake were analyzed on primary cortical astrocytic and neuronal cultures treated with clozapine (50uM) for 48h. Immunocontent and expression of GLT‐1 and Glutamate‐Aspartate Transporter(GLAST) were assessed on the cortical tissue and cell cultures.ResultsClozapine treatment significantly reduced [18F]FDG metabolism in the cerebral cortex, hippocampus, and striatum of adult rats. In addition, clozapine decreased cortical glutamate transport in brain slices – indexed by [3H]D‐Aspartate uptake – and reduced the cortical immunocontent and expression of GLT‐1. Astrocytic cultures treated with clozapine presented a decline on GLT‐1 density, [3H]D‐Aspartate uptake and [3H]2‐Deoxyglucose uptake, while the neuronal cultures presented no changes.ConclusionHere, we present microPET data showing that a challenge with clozapine causes a reduction on [18F]FDG signal in brain regions presenting high GLT‐1 density. Our cell culture findings indicate that astrocytes are, at least partially, the cells underlying the brain glucose metabolism response to clozapine. These results corroborate previous studies that highlight the need for a reevaluation in the way that brain [18F]FDG‐PET data is interpreted. Additionally, clozapine is a drug approved for clinical use, therefore, these findings could have high translational implications.
Cerebral amyloid and white matter hyperintensity volume are independently associated with rates of cerebral atrophy in Insight 46, a sub‐study of the 1946 British birth cohort
Authors: Keuss Sarah E , Poole Teresa , Cash David M , Lane Christopher A , Parker Thomas D , Buchanan Sarah M , Keshavan Ashvini , Coath William , Malone Ian B , Thomas David L , Sudre Carole H , Barnes Jo , Lu Kirsty , James Sarah‐Naomi , Wagen Aaron , Storey Mathew , Murray‐Smith Heidi , Wong Andrew , Richards Marcus , Fox Nick C , Schott Jonathan M 
Published: December 2020

AbstractBackgroundAlzheimer’s (AD) and cerebrovascular disease are common causes of cognitive impairment in later life and often co‐exist. Understanding how AD and vascular pathologies act independently or together to influence neurodegeneration in later life is important for the development of effective treatments and clinical trial design.Method219 cognitively normal participants underwent cognitive testing, structural MRI and 18F‐florbetapir amyloid‐PET scans at two visits approximately two years apart. Changes in whole brain, ventricular and hippocampal volumes between time‐points were determined using the Boundary Shift Integral (BSI) (doi:10.1016/j.neuroimage.2009.12.059). Baseline white matter hyperintensity volume (WMHV) was generated using BaMoS (doi:10.1109/TMI.2015.2419072). Baseline amyloid SUVRs were derived with eroded subcortical white matter as the reference region and a composite grey matter target region. A cut‐point of 0.6104 was used to define amyloid positivity. Linear regression was used to investigate relationships of amyloid and WMHV with atrophy rates. Specifically, models were fitted with BSI as the outcome, scan interval as the explanatory variable, and interactions between scan interval and i) the explanatory variable of interest and ii) each of the covariates (age at baseline scan, sex and total intracranial volume). Amyloid and WMHV were assessed separately and then together within the same model. An interaction between amyloid, WMHV and scan interval was also tested in a further model.Result199 cognitively normal participants (mean baseline age 70.1±0.4 years; 47% female) had high‐quality imaging data (Table 1). Positive amyloid status was associated with greater rates of brain and hippocampal atrophy and ventricular expansion, with a positive relationship between SUVR and ventricular expansion and hippocampal atrophy (Table 2). Larger WMHV was associated with higher rates of brain and hippocampal atrophy and ventricular expansion (Table 2). None of these associations were meaningfully altered by including amyloid and WMHV within the same model (Table 3). There was no evidence of an interaction between amyloid and WMHV for any BSI measure (interaction p>0.13, all tests).ConclusionMarkers of amyloid and presumed small‐vessel disease were independently associated with atrophy rates, and there was no evidence that either pathological process modified the effect of the other.
GAP rater certification program transforms the rater certification process
Authors: Mohs Richard , Smith Katy , Bork Jason , Bartolic Edward I. , Jenkins Cecily , Ward Rick , Rentz Dorene M. 
Published: December 2020

AbstractBackgroundRater certification is a key component in successful study startup and Alzheimer’s disease (AD) trial execution, but the current certification process is time consuming and redundant across trials. Existing rater training has not changed substantially in years, has become more complex, and offers raters limited opportunity to enhance cognitive assessment skills.MethodThe GAP Rater Certification Program is designed to transform rater certification. The GAP‐Net Rater Certification Matrix defines scale‐specific standards for proven, experienced, and developing raters (Figure 1). Standards are based on education, experience, previous certification, and demonstration of mastery. Rater training and certification follow defined processes and include the option to recertify after one year (Figure 2). Training is appropriately targeted to the rater’s level of experience and effectively tests the rater’s knowledge of each cognitive assessment. Rater qualifications maintained in a single database eliminate the need to complete Rater Experience Surveys (RES) on every trial.ResultThe GAP Rater Certification Program has been delivered to over 50 raters across 20 GAP‐Net sites. GAP is surveying participating raters and will share results of the Program’s implementation and impact. Initial results indicate the following: GAP’s Demonstration of Mastery provides effective ‘applied training’ by assessing rater’s knowledge of scales and administration competency and also providing a platform to share strategies that deliver meaningful outcomes. A rater certification process across AD trials is highly likely to save time during the qualification process and accelerate study startup. Expanding the Program to new / developing raters will increase the pool of raters at sites and eliminate potential startup bottlenecks. The applied training is appropriately targeted to rater’s level of experience. Redundant training will be minimized. One model predicts 84 hours would be saved using the Program over 6 trials for every site. GAP Rater Certification Database (InvestigatorSpace) facilitates information collection and sharing and increases efficiency during site selection and study startup.ConclusionThe GAP Rater Certification Program removes redundancies in study startup and incorporates targeted training and Demonstration of Mastery designed to ensure quality raters and study data. Further enhancements will continue to focus on improving efficiencies and precision in rater qualification.
The rat as a model for ketogenic drug formulation development
Authors: Henderson Samuel T , Walker Judith Anne , Morimoto Bruce , Ambarkhane Ameet 
Published: December 2020

AbstractBackgroundKetogenic compounds such as ketone esters and medium chain triglycerides have been tested as treatments for mild‐to‐moderate Alzheimer’s disease (AD) in several studies. Ketogenic compounds are given at high doses in an attempt to compensate for regional cerebral glucose hypometabolism characteristic of AD. Upon ingestion, ketogenic compounds lead to the induction of ketosis. Previous studies have shown the formulation of the ketogenic compounds can influence kinetics of digestion of the drug and transformation into active moieties which induces ketosis, hence any changes in formulation may influence clinical outcomes. In order to rapidly screen new formulations, we have investigated the rat as pharmacokinetic (PK) model of ketogenic potential of formulations in human. PK studies are performed using different formulations to define dose, dosing frequency, route of dosing and onset of action.MethodWe have previously tested several formulations in human PK studies and found several differences in Cmax, Tmax and AUC related to the release from the excipients. In the present study we evaluated the PK profiles of these same formulations in rat to determine if rats qualitatively replicated the human results. Healthy young adult male Sprague Dawley (SD) rats were used as a test system for this PK study. Five animals per group were used, animals were between 9 to 12 weeks old and the weight variation of animals did not exceed ± 20% of the mean weight. Animals were dosed by oral gavage and concentrations of acetoacetate and β‐hydroxybutyrate in rat serum were determined by LC/MS. Ketone body concentrations (µM) were calculated as a sum of acetoacetate (µM) and β‐hydroxybutyrate (µM) concentrations. Ketone body data was analyzed using WinNonlin.ResultRats qualitatively mirrored results from human studies. Formulations that exhibited slow release and thereby lower ketogenic in humans similarly were found to be slow releasing and less ketogenic in SD rats. Formulations that exhibited fast release and more ketogenic in humans were found to be fast releasing and more ketogenic in SD rats.ConclusionFrom these preliminary studies rat represents a model to evaluate future ketogenic drug formulations for ketogenic potential in human.