bluuebunny/crossref_metadata_2025_split huggingface dataset:
Serotonin Reuptake Inhibitors are Associated with Less Amyloid‐β Burden Spatial Extent in Military Veterans with only PTSD, but not with TBI or Comorbid PTSD/TBI: Preliminary PET Findings from ADNI‐DOD Project
Authors: Chen Kewei , Goradia Dhruman D. , Chen Yinghua , Luo Ji , Devadas Vivek , Jagust William J. , Mackin R Scott , Su Yi , Landau Susan M. , Weiner Michael W. , Reiman Eric M. 
Published: December 2022

AbstractBackgroundSome but not all studies suggested an association of serotonin reuptake inhibitors (SRIs) with a reduction in “magnitude” of amyloid‐β (Aβ) plaque burden. Using PET images from ADNI‐DOD and a voxel‐based Majority Count Algorithm (MCA), we demonstrated that cognitively unimpaired veterans with post‐traumatic stress disorder (PTSD) had significantly more cerebral voxels with lower rather than higher florbetapir standard uptake value ratios (voxel‐based P<0.05), reflecting Aβ burden reduction in “spatial extent” [Chen, AAIC 2018]). We postulated that this finding might relate their SRI use. Here, we investigate the impact of SRI use on the spatial extent of Aβ burden among ADNI‐DOD veterans with PTSD, comorbid PTSD and traumatic brain injury (TBI), and TBI.MethodsStatistical Brain Mapping (SPM12) adjusted for age, MMSE, education and APOE4 allele, a voxel‐based P<0.05 threshold, and MCA which is free of multi‐comparisons (Stern, NEJM, 2019) were used to compare the greater versus lower number of cerebral voxels with higher Aβ burden in SRI non‐users versus users in 6 groups: 1) PTSD (n=76), 2) PTSD or TBI (n=115), 3) comorbid PTSD/TBI or TBI (n=126), 4) PTSD, PTSD/TBI or TBI (n=202), 5) PTSD/TBI (n=87) and 6) TBI (n=39).ResultsSRI non‐users had a significantly larger number of cerebral voxels with higher Aβ burden than users in the first four groups: 1) 28,539 in non‐users versus 70 in users (voxel count ratio VCR=551) in PTSD; 2) 3,573 versus 21 (VCR=170) in PTSD or TBI; 3) 22,927 versus 1,162 (VCR=20) in comorbid PTSD/TBI or TBI; and 4) 7,569 versus 1,481 (VCR=5) in PTSD, comorbid PTSD/TBI or TBI, MCA p<0.001 for all 4 groups. In contrast, 5) SRI non‐users and users did not differ in the number of cerebral voxels with higher Aβ burden in PTSD/TBI (3,209 versus 4,027, VCR=1, MCA p=0.68); and 6) non‐users had a significantly smaller number of cerebral voxels than users with higher Aβ burden in TBI (60 versus 11,715 VCR=0.005, MCA p<0.001).ConclusionThis study showed SRIs’ association with spatially less extensive Aβ burden in PTSD, more extensive Aβ burden in TBI, and intermediate/opposing effects in other combinations. Finding conformation and mechanism clarification are needed.
Calcineurin activation and scaffolding in Aß‐induced synaptic dysfunction
Authors: Prikhodko Olga , Sanderson Jennifer L , Freund Ronald K , Sullivan Emily , Kennedy Matthew J , Dell'Acqua Mark L 
Published: December 2022

AbstractBackgroundCalcineurin (CaN) is a protein phosphatase that is essential for synaptic long‐term depression (LTD) through its regulation of AMPA‐type glutamate receptors (AMPAR). AMPAR regulation by CaN is critically mediated by the postsynaptic scaffold protein A‐kinase anchoring protein 150 (AKAP150), which localizes a pool of CaN to the postsynaptic membrane. Our lab has generated knockin mice carrying a mutant version of AKAP150 lacking its CaN‐binding site, the PxIxIT motif; AKAP150ΔPIX (PIX). LTD does not occur in these mice, underscoring the importance of the synaptic pool of CaN for normal synaptic function and plasticity. Pharmacological inhibition of calcineurin prevents diverse manifestations of Aβ‐mediated synaptotoxicity, including long‐term potentiation (LTP) blockade, synapse loss, and impaired learning and memory in AD mouse models. However, the importance of synaptically‐localized calcineurin in Aβ synaptotoxicity is unknown.MethodTo test our novel hypothesis that Aβ synaptotoxicity requires spatial positioning of CaN at the synapse via AKAP150 anchoring, we used our innovative AKAP150ΔPIX (PIX) knock‐in mouse model. Primary hippocampal neuronal cultures and acute hippocampal slices from WT and PIX mice were treated with various doses of Aβ oligomers and assayed for Aβ’s effect on dendritic spine density, quantal calcium transients through NMDA receptors (both in culture), and LTP through extracellular field recordings (in slices). Additionally, utilizing the 5xFAD AD mouse model, we generated PIX/5xFAD mice to test long‐term behavioral (via radial arm water maze and contextual fear conditioning tasks) and electrophysiological effects (through field recordings) of the PIX mutation on the 5xFAD phenotype in 6‐month‐old animals.ResultThe PIX mutation protects against acute Aβ‐mediated synaptic loss, decreased Ca2+ entry through NMDA receptors, and LTP deficits. Long‐term, the PIX mutation rescues contextual fear conditioning memory, but not radial arm water maze performance or chronic LTP deficits of 5xFAD mice.ConclusionSynaptically‐localized calcineurin is necessary for early Aβ‐mediated synaptic deficits. Long‐term Aβ exposure engages mechanisms beyond its AKAP‐anchored calcineurin pathway.
The Alzheimer’s Disease‐Health Indices (AD‐HI): Development of Two Novel Outcome Measures for Use in Clinical Trials
Authors: Seabury Jamison , Arky Abigail , Ayles Megan , Dilek Nuran , Hance Margaret , Rosero Spencer , Santos Elizabeth , Weinstein Jennifer , Varma Anika , Heatwole Chad 
Published: December 2022

AbstractBackgroundIn preparation for upcoming clinical trials, there is a clear need for improved clinical trial infrastructure to facilitate therapeutic assessment in Alzheimer’s disease, (AD), mild cognitive impairment (MCI), and related dementias. This research describes the development of a patient‐reported outcome measure, the Alzheimer’s Disease‐Health Index (AD‐HI), and a caregiver‐reported outcome measure, the Alzheimer’s Disease Caregiver‐Health Index (ADCR‐HI). These novel outcome measures were developed using large scale input from patients and caregivers and were designed in accordance with U.S. Food and Drug Administration (FDA) guidelines for use in drug labeling claims.MethodWe first conducted semi‐structured qualitative interviews with individuals with AD, MCI, or dementia and their caregivers to identify potential symptoms of importance to these disease populations. We subsequently performed a cross‐sectional study involving individuals with AD, MCI, or dementia and caregivers to determine the prevalence and relative importance of symptoms identified during preliminary qualitative interviews. Using this data, we developed two outcome measures known as the AD‐HI and the ADCR‐HI. Symptom questions and subscales were selected for the instruments based on their prevalence and importance to the patient populations, their generalizability, and ability to respond to therapeutic intervention. Factor analysis was used to group symptom questions into distinct symptomatic themes of patient health.ResultFifteen individuals with AD, MCI, or dementia and 15 caregivers provided 2,263 quotes regarding the symptomatic burden of AD, MCI, or dementia. One‐hundred and four patients and 329 caregivers participated in a cross‐sectional study to determine the prevalence and relative importance of the most relevant symptoms identified through interviews. The AD‐HI and the ADCR‐HI were developed based on this data and simultaneously measure overall patient disease burden and disease burden in 9 disease specific areas.ConclusionThe AD‐HI provides researchers and clinicians with a valid mechanism to measure disease burden during therapeutic trials involving individuals with AD, MCI, or dementia. Similarly, the ADCR‐HI provides a viable option when a patient can no longer complete a patient‐reported outcome measure on their own behalf. Ongoing steps will further optimize the usability and reliability of these instruments in preparation for upcoming clinical trials.
A Comparison of MMSE and MoCA for Following Cognitive Performance with a Longitudinal Cohort Study
Authors: Li Daniel , Li Wei 
Published: December 2022

AbstractBackgroundMini Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) are two commonly used cognitive screening and diagnostic tools.MethodAt baseline, participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were divided into four groups based on their cognitive diagnoses: healthy control (HC), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI), and Alzheimer’s Disease (AD). MMSE or MoCA scores were compared among the four groups using one‐way analysis of variance (ANOVA) model with post‐hoc Bonferroni correction. For those participants who had both MMSE and MoCA assessments done, a Pearson correlation analysis was performed between the two assessments for each visit.ResultThe MMSE scores were significantly different among the four groups at baseline, which was true for each of the three annual follow‐up visits. By contrast, the MoCA scores were not significantly different between HC and EMCI groups at either baseline or any of the follow‐up visits. For participants with a diagnosis of LMCI, the cognitive performance deteriorated in a linear manner 12 months after the baseline, which was independent of MMSE or MoCA. At last, the MMSE scores were moderately related to MoCA scores, which got stronger along with the time of follow‐up.ConclusionMMSE and MoCA are comparable as cognitive assessment tools to monitor cognitive changes. In addition, the measurements of MMSE and MoCA are moderately correlated for the follow‐up visits.
Metabolite QTL analysis of ROSMAP and ADNI prioritized sequencing data identifies C14:2 genetic locus on Chr 2
Authors: TumSuden Sophia L , Lee Brian N , Bao Jingxuan , Kim Jaesik , Ning Xia , Kim Dokyoon , Shen Li 
Published: December 2022

AbstractBackgroundPeripheral metabolic disturbance is a known component of Alzheimer’s Disease (AD), however predictive genetic markers, as well as the associated pathways, remain to be determined. Two AD studies, ROSMAP and ADNI, have generated Whole Genome Sequencing (WGS) and ante‐mortem serum metabolic biomarker samples. A previous study utilizing ROSMAP data has identified the metabolite tetradecadienylcarnitine, C14:2, as protective against incident AD in both brain and serum data (Brain and blood metabolome for Alzheimer’s dementia: Findings from a targeted metabolomics analysis; Huo et. al).MethodAfter standard QC procedure, WGS data from ROSMAP participants was prioritized to include only variants within +/‐ 1000 bp of 584 AD prioritized genes identified on the AD Knowledge Portal’s Agora Platform (https://agora.adknowledgeportal.org/genes/(genes‐router:genes‐list)), resulting in a subset of 401,415 variants. A metabolite quantitative trait locus (mQTL) study was performed (N = 67) investigating associations between these variants of interest and the C14:2 metabolite measurements collected from the ROSMAP cohort by Biocrates p180 flow injection analysis. A subsequent single‐variant targeted mQTL analysis (N = 464) utilizing ADNI‐GO/2 WGS and C14:2 metabolic data (Biocrates p180 flow injection analysis) was performed. Age, gender and education were used as covariates in both analyses.Result: A novel locus, rs147667251, showed significance to the C14:2 metabolic biomarker in both ROSMAP and ADNI serum mQTL analyses. In ROSMAP data, rs147667251 was identified as most significant to the C14:2 biomarker with a p‐value of 5.507e‐10 (threshold = 1.2e‐7). In a single test mQTL of ADNI C14:2 data, the rs147667251 locus had a significant p‐value of 0.02415 (threshold = 0.05). The locus lies on chromosome two and is an intron variant of the DPP10 gene. The DPP10 gene encodes a type II membrane protein and is known to have altered transcript and protein expression linked to AD.ConclusionIn this AD prioritized mQTL study, a single genetic locus, rs147667251, within the AD nominated gene DPP10 has been identified as associated with serum levels of C14:2. DPP10 is known to be dysregulated in AD and a previous study has identified the C14:2 metabolite as protective against AD, warranting further investigation into the regulatory impact of rs147667251 on DPP10 expression and the C14:2 metabolic pathway.
Association between Lifespan Exercise Habits and Cognitive Function in Older Age: the Bunkyo Health Study
Authors: Shi Huicong , Tabata Hiroki , Otsuka Hikaru , Someya Yuki , Kaga Hideyoshi , Naito Hitoshi , Abulaiti Abudurezake , Umemura Futaba , Kiya Mai , Ito Naoaki , Tajima Tsubasa , Yoshizawa Yasuyo , Kakehi Saori , Kawamori Ryuzo , Tamura Yoshifumi 
Published: December 2022

AbstractBackgroundPreventing or delaying the onset of mild cognitive impairment (MCI) is a crucial strategy for maintaining an independent life in old age (Rodakowski J et al., 2014). Exercise habits for ∼ ten years in the 50s or older were associated with preserving cognitive function (Rovio, S., et al., 2005; J Krell‐Roesch, et al., 2021). However, it is still unclear whether continuous exercise habits throughout the 50s to late life are required to prevent MCI. This study aimed to investigate the association between continuity of exercise habits from the 50s to late life and MCI in older age.MethodWe included 1585 participants (669 males and 916 females) aged 65 to 84 years old living in an urban area (Bunkyo Health Study). MCI was defined as the Japanese version of The Montreal Cognitive Assessment score of 22 points or less. Participants were divided into three groups based on continuity of exercise habits in each decade of the 50s to current age: never having exercise habits in their 50s to current [Never group, reference], having exercise habits in one or several of ages from 50s to current [Intermittent group], and having continuous exercise habits in all of ages [Continuous group]. The odds ratio (ORs) for the prevalence of MCI were obtained using logistic regression models while adjusting for potential confounders including age, years of education, body fat percentage, smoking history, alcohol intake, and cognition‐related diseases (hypertension, diabetes mellitus, dyslipidemia, cerebrovascular disease).ResultCompared with the Never group, none of the ORs for MCI were statistically significant in men (Intermittent group: ORs: 0.60, 95%CI: 0.36 – 1.02; Continuous group: ORs: 0.99, 95%CI: 0.61 – 1.63; P for trend: P = 0.93). In contrast, the ORs for MCI were significantly lower in the Continuous group in women (Intermittent group: ORs: 0.74, 95%CI: 0.47 – 1.17; Continuous group: ORs: 0.50, 95%CI: 0.29‐0.87; P for trend: P = 0.01).ConclusionMore sustained exercise participation from the 50s to late life was associated with a lower prevalence of MCI in women but not in men.
What are the most important prognosticators of Alzheimer's disease progression? – Answers from machine learning
Authors: Chong Yao Feng , Chen Zijiao , Wu Yilei , Kok Bing Cai , Yeo Thomas , Zhou Juan Helen 
Published: December 2022

AbstractBackgroundNumerous variables that influence the risk of decline in Alzheimer’s disease (AD) have been identified. Previous studies have only examined a relatively small number of these variables. To our knowledge, no study has compared all variables in a large dataset to determine which are the most important.We hypothesised that the most important variables are neuropsychological assessment (NPA) scores and neuroimaging findings; moreover, the prognostic value of all variables will vary with disease stage: normal control (NC), mild cognitive impairment (MCI) or dementia. Secondly, we hypothesised that non‐NPA variables, such as imaging, cerebrospinal fluid (CSF) and genetics, will add prognostic value to that provided by NPA variables alone.MethodWe analysed all relevant variables in the Alzheimer’s Disease Neuroimaging Initiative database – the largest open‐access dataset of subjects with or at risk of AD. With machine learning, we identified those variables which are the strongest predictors of the annual rate of change in up to the first 10 years of Alzheimer’s Disease Assessment Scale – Cognitive Subscale, 13‐item version (ADAS‐Cog13) and Clinical Dementia Rating, Sum of Boxes (CDR‐SB) scores. We repeated this analysis for each disease stage subgroup. Secondly, we compared models that only used NPA‐related variables (NPA‐only) with those that used up to 2 non‐NPA modalities (NPA‐plus) and contrasted the findings between the same subgroups.ResultAcross all subjects, the strongest predictors of the rate of change of both ADAS‐Cog13 and CDR‐SB scores are CSF total tau and amyloid levels, fluorodeoxyglucose (FDG) positron emission tomography (PET) findings, and certain NPA measures. At the NC and MCI stages, CSF and imaging variables are strong predictors, but only NPA variables remained useful at the dementia stage. Secondly, NPA‐plus models consistently outperformed NPA‐only models. The non‐NPA modalities which added the most predictive power varied based on a subject’s disease stage in a manner similar to the previous findings.ConclusionWe identified a multi‐modal set of variables that have the strongest impact on predicting decline during different stages of AD. Our findings are clinically relevant as they recommend the investigations that are of most prognostic yield for clinicians to undertake at each stage of AD progression.
Does Caregiver Education Level Influence Confidence in Care Budgeting and Planning for Persons Living with Alzheimer’s Disease or Related Dementias?
Authors: Fields Beth E , Boutilier Justin J , Jolliff Anna , Elliott Christian , Zuraw Matthew , Werner Nicole 
Published: December 2022

AbstractBackgroundThe nearly 11 million unpaid caregivers (‘family members or friends’) who provide care to the 6.5 million people living with Alzheimer’s disease and related dementias (ADRD) in the United States are frequently tasked with substantial and overwhelming care budgeting and planning. Yet, many of these caregivers encounter individual‐level barriers that make it difficult to carry out care budgeting and planning tasks. An individual‐level factor that is not well understood is the education level of ADRD caregivers.ObjectiveThis ongoing study is investigating the role of caregiver education level in predicting confidence in ADRD care budgeting and planning.MethodsCaregivers of people living with ADRD residing in the United States completed the Caregiving Financial and Legal Planning Survey in 2022. Secondary analyses of cross‐sectional data are currently underway. A total of 238 caregivers self‐reported their confidence in care budgeting and planning, which was assessed by the following question “How confident are you in knowing about care budgeting and planning (1 = not at all confident, 5 = extremely confident). Those responding ‘4’ or greater were designated as high confidence. Descriptive statistics were used to examine demographic characteristics of caregivers. Logistic regression analyses will be used to determine the relationship between caregiver education level and confidence in care budgeting and planning while controlling for demographic characteristics.Preliminary ResultsThe average caregiver was 52 years old (range 36‐67), female (78%), white (82%), and had a bachelor’s or equivalent level of education (34%). Thirty‐five percent of the caregivers (83) reported high confidence. Logistic regression analyses are in progress.ConclusionResults may suggest that caregivers with higher education levels feel more confident in care budgeting and planning. Practitioners and researchers may need to evaluate ways to improve training resources on how to budget and plan for ADRD care. A better understanding of factors that contribute to care budgeting and planning may inform tailored caregiving interventions and future social support policies.
Measuring Associations Between Physical Activity, Cognitive Ability, and AD‐Vulnerable Brain Networks in Periadolescent Children
Authors: Heller Abi , Phipps Connor J , Ramirez Meghan K , Sexton Jennifer N , Behm Lillian , Zatkalik Abigail L , Nickolas Kristen , Maerlender Arthur C. , Phatak Vaishali S , Cramer Justin A. , Blair James , Murman Daniel L , Warren David E 
Published: December 2022

AbstractBackgroundAs our population ages, and Alzheimer’s Disease (AD) and related pathologies become more prevalent, the need for preventative interventions continues to increase. Physical activity has been investigated as a mechanism to improve memory and other cognitive processes in both healthy and pathological aging. In adults, there is evidence that exercise increases hippocampal volume and strengthens connectivity within functional brain networks such as the Default Mode Network (DMN), Frontoparietal Network (FPN), and Dorsal Attention Network (DAN). These networks support cognitive functions such as spatial working memory (SWM) which involves maintenance and manipulation of visuospatial information; notably, SWM declines as AD progresses. Underlying connectivity in functional brain networks and SWM ability are both influenced by exercise in adults. However, this effect has not been replicated in younger cohorts. The effects of exercise on brain structure and function during periadolsecence, a neurodevelopmental period characterized by expansive changes to functional networks that support cognition, remains unclear. The current study tested associations between resting‐state functional connectivity (rs‐FC) in brain networks, SWM ability, and self‐reported physical activity in a group of periadolescents.MethodTypically‐developing periadolescent children aged 8 – 13 years (N = 60) completed the Cambridge Neuropsychological Test Automated Battery (CANTAB) SWM task, a self‐report physical activity questionnaire, and underwent an MRI of the brain to assess rs‐FC of several functional networks. MRI data were processed using the Human Connectome Project processing pipelines and AFNI software.ResultAnalysis of covariance between rs‐FC of the DMN and physical activity suggested greater within‐network connectivity was associated with more minutes of exercise. A similar pattern of within‐network connectivity in the DMN was also observed in association with SWM performance. The DAN and DMN demonstrated greater between‐network connectivity associated with increased physical activity. The FPN displayed a pattern of greater within‐network connectivity associated with SWM performance.ConclusionCharacterizing the influence of physical activity on development of brain networks that support memory may provide key insights on preserving those networks. Understanding these developmental trajectories, and ways to potentially enhance them, could be important for developing interventions to promote brain health by reducing the risk of neurological disease, including late‐life disorders such as AD.