bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diabetes is related to cognition but not plasma amyloid‐β 42/40 in an African American cohort
Authors: Ennis Gilda E. , Bouges Shenikqua , Zuelsdorff Megan , Van Hulle Carol A. , Jonaitis Erin M. , Koscik Rebecca Langhough , Lambrou Nickolas H. , Salazar Hector , Carter Fabu P , James Taryn T. , Johnson Adrienne L. , Fischer Barbara L. , Kirmess Kris , Holubasch Mary S. , Meyer Matthew R. , Venkatesh Venky , West Tim , Verghese Philip B. , Yarasheski Kevin E. , Chin Nathaniel A. , Asthana Sanjay , Carlsson Cynthia M. , Johnson Sterling C. , Bendlin Barbara B. , Gleason Carey E. 
Published: December 2022

AbstractBackgroundThe prevalence of clinical Alzheimer’s disease (AD) and type 2 diabetes is higher in African Americans (AA) relative to non‐Hispanic White Americans. Although diabetes is a risk factor for Alzheimer’s clinical syndrome, it is unclear whether diabetes associates with amyloid‐β, a pathological hallmark of AD. We investigated whether diabetic status was associated with age‐related decline in plasma amyloid‐β (Aβ) 42/40 ratio and cognition in a predominantly dementia‐free AA cohort.MethodParticipants (N=314) were middle‐aged and older adults (Table 1) enrolled in the African Americans Fighting Alzheimer’s in Midlife cohort. EDTA plasma was collected at 1‐8 visits for Aβ 42/40 quantification using immunoprecipitation mass spectrometry (C2N Diagnostics, St. Louis, MO). 52% had >1 plasma Aβ 42/40 measurements over an average interval of 4.9 years (SD=3). Recall (immediate and delayed) and executive functioning were assessed using Rey’s Auditory Verbal Learning Test and Trails B, respectively. Diabetic status was determined from clinician‐report, self‐report, self‐report of antidiabetic medication use or fasting glucose ≥126 mg/dL. Cognitive data from the first of 1‐6 visits and diabetic status were obtained at the same visit as baseline plasma Aβ 42/40 for 96% of participants. Linear mixed‐effects models tested diabetic status as a moderator of age‐related decline in plasma Aβ 42/40 ratio and cognition. If age x diabetic status was not significant, diabetic status was tested without the interaction. Covariates included APOE4 carrier status and sex, and education was included when cognition was the outcome.ResultsDiabetic status did not significantly moderate age‐related decline in plasma Aβ 42/40 (β=0.0001, p=.21) or predict average plasma Aβ 42/40 ratio (β=‐0.001, p=.22). Diabetes was also not significantly related to aging‐associated decline in cognition but was a significant predictor of worse average Trails B scores (Table 2). Results from a cognitively unimpaired subsample (n=261) revealed a similar pattern.ConclusionIn a predominantly dementia‐free AA cohort, diabetes was unrelated to plasma Aβ 42/40 but was related to worse Trails B performance. Poor Trails B performance has been linked in previous studies to cerebrovascular dysfunction. Determining mechanisms, vascular and AD pathological pathways, that link diabetes to increased dementia risk in AAs warrants further investigation.
Inhibition of calcium‐dependent phospholipase A2 improves blood‐brain barrier integrity in ApoE4 carrying mice
Authors: Kerman Bilal E. , Duro Marlon Vincent V. , Maria Naomi Sta. , Liu Xiaodan , Wang Shaowei , Van Valkenburgh Juno S. , Chen Kai , Jacobs Russell E. , Yassine Hussein N. 
Published: December 2022

AbstractBackgroundBlood‐brain barrier (BBB) is essential for neural health and function. Degradation of BBB is observed in Alzheimer’s disease (AD) and is more pronounced in individuals carrying the apolipoprotein E4 (ApoE4) allele, which is a major genetic risk factor for AD. ApoE4 increases the activation of calcium‐dependent phospholipase A2 (cPLA2), which is linked to BBB function. Here, we asked if cPLA2 inhibition in ApoE4 carrying mice could repair BBB integrity and if the changes could be observed in vivo by dynamic contrast‐enhanced MRI (DCE‐MRI).Method16‐month‐old ApoE4 targeted replacement (ApoE4‐TR) mice were divided into a control group treated with vehicle (n=4) and an experimental group treated with a cPLA2 inhibitor ASB‐14780 (n=4). All imaging was performed using a 7T MRI scanner. DCE‐MRI protocol involved acquisition of baseline images (5min), mice receiving a bolus of gadolinium diethylenetriaminepentaacetic acid (Gd‐DTPA, 0.3mmol/kg, i.v.)) and followed by post‐bolus scans for 20min. Regions of interest (ROIs), such as the hippocampus and isocortex, were manually defined using T2‐weighted (FSE) anatomical scans in ImageJ. Volume transfer constants (KTrans) of the contrast agent uptake were calculated for each subject from the dynamic DCE‐MRI scan using the Patlak model on the Rocketship software (MATLAB).ResultKTrans values for the isocortex and the hippocampus were calculated for two animals from the control group and three animals from the experimental group. The mean KTrans value in the hippocampus region was 60% lower for the mice treated with cPLA2 inhibitor than controls (p=0.056), 0.0459 ± 0.0168 min‐1 and 0.117 ± 0.030 min‐1 respectively. Similarly, the mean KTrans value in the isocortex for the treated mice was 50% lower than the controls (p=0.89), 0.0554 ± 0.018 min‐1 and 0.110 ± 0.028 min‐1 respectively.ConclusionWe observed that cPLA2 inhibition decreased KTrans values implying increased BBB function. Thus, cPLA2 inhibition can be a possible therapeutic path towards reversing some of the damage to the brain due to AD. Currently, we are validating this observation with larger sample sizes and by analyzing the brains of these mice for changes in molecular signatures of BBB.
Agitation in Cognitive Disorders: Use of the National Alzheimer’s Coordinating Center Uniform Data Set (NACC‐UDS) to Evaluate the International Psychogeriatric Association Definition.
Authors: Sano Mary , Zhu Carolyn W , Neugroschl Judith A. , Grossman Hillel , Schimming Corbett , Aloysi Amy 
Published: December 2022

AbstractBackgroundThe consensus‐based definition of agitation by the International Psychogeriatric Association (IPA) has not been evaluated in community‐based samples who are not preselected for behavioral disturbances. Here we use a well‐characterized cohort of community‐dwelling older individuals with cognitive impairment to assess the IPA criteria associated with agitation to validate the construction of this diagnostic entityMethodWe used the National Alzheimer Coordinating Center Unified Data Set (NACC‐UDS) to select a cognitively impaired cohort across etiological diagnoses, excluding those with a primary psychiatric etiology (IPA criteria A). We used this dataset to evaluate the IPA consensus‐based provisional definition of agitation in cognitive impairment. We used clinician diagnosis of agitation as a gold standard in those with MCI and dementia and the Neuropsychiatric Inventory–Questionnaire (NPI‐Q) algorithm to define agitation symptoms (IPA Criteria B); Standardized assessments of function (including Functional Assessment Scale and CDR Sum of Boxes) were used to assess excess social/functional disability (IPA Criteria C). We examined patterns of psychiatric comorbidities to determine if they were consistent with IPA criteria (IPA Criteria D).ResultWe identified a cognitively impaired cohort (N = 19,424), across multiple etiologies (AD = 73.7%, FTLD = 9.7%, LBD = 6.8% and vascular brain injury = 3.5%). Mean (SD) age was 72.7 (10.1) years, 77.0% were non‐Hispanic White, 11.1% non‐Hispanic Black, 8.3% Hispanic, with an average of 14.7(3.7) years of education. Mean (SD) MMSE = 22.0(6.4), FAQ = 12.7(9.5), and GDS = 2.8(2.8). Clinician judgement of agitation was present in 15.7% of the sample. Those with agitation were younger, more likely to be male, had slightly lower educational levels and were more likely to be from under‐represented groups. 38.6% had agitation by NPI algorithm, with high agreement with clinician judgement. More than 84% of those with clinician judgment of agitation and 74% of those meeting the NPI algorithm demonstrated excess social/functional disability. Psychiatric comorbidities were present in 38% of the sample without evidence of agitation, and were higher in those with agitation (56% to 82%, depending on agitation definition).ConclusionAgitation ranges between 15 and 38% in those with cognitive impairment. The pattern of excess disability and presence of comorbid psychiatric symptoms in this well characterized dataset is consistent with IPA published criteria.
Simulations and Experiments Reveal Diverse APOE States that Inform their Pathogenicity
Authors: Levine Zachary 
Published: December 2022

AbstractBackgroundMutations to the lipid transport protein Apolipoprotein E (APOE) can dramatically increase the risk of developing late‐onset Alzheimer’s Disease (AD) by up to 15‐fold, however a molecular description of why some isoforms are protective while others are pathological has remained elusive. We hypothesize that individual APOE isoforms sample distinct conformational landscapes that are modulated by the presence of lipids, and that these landscapes contain co‐existing pathological and protective states.MethodTo test this hypothesis, we carried out a combination of molecular dynamics (MD) simulations and single‐molecule FRET (smFRET) experiments to highlight the conformational heterogeneity of human APOE isoforms, thereby informing states that differentially traffic lipids into neurons.ResultOur data suggests that there is no single pathological or protective APOE conformation, but rather a broad spectrum of protective and susceptible conformations that impact disease and memory impairment.ConclusionBiophysical studies are powerful tools that can inform the molecular mechanisms driving Alzheimer’s Disease and help bridge the gap between genetic associations (e.g. APOE status) and clinical phenotypes such as amyloid buildup or memory impairment.
Pooling CSF Measurements Across Multiple Cohorts in the Preclinical Alzheimer's Consortium
Authors: Lokhande Vishnu Suresh , Wang Jiangxia , Soldan Anja , Pettigrew Corinne , Moghekar Abhay , Morris John C. , Fagan Anne M. , Schindler Suzanne E. , Xiong Chengjie , Albert Marilyn S. , Johnson Sterling C. , Singh Vikas 
Published: December 2022

AbstractBackgroundStudies focused on understanding cerebrospinal fluid (CSF) biomarkers of presymptomatic disease processes in Alzheimer’s disease (AD) are restricted by sample sizes that lack statistical power to investigate subtle effects of interest pertaining to risk. Pooling data across cohorts may be effective to identify early trends in CSF biomarkers to subsequent neurodegeneration and cognitive decline. Unfortunately, different instruments, preanalytics and workflows at each site lead to unique challenges when analysis of a pooled dataset is undertaken. We report initial findings from harmonized pooling of CSF measurements (cross‐sectional) across three preclinical AD studies at different institutions on a combined cohort size of N=733.MethodCSF measurements were contributed from three studies: Adult Children Study (ACS), Wisconsin Registry for Alzheimer’s Prevention (WRAP) and Biomarkers of Cognitive Decline Among Normal Individuals (BIOCARD). For harmonization, ACS was the reference site to which the CSF measurements from WRAP and BIOCARD were transformed using our domain adaptation algorithm (affine transformation to align covariate‐matched distributions under a distributional discrepancy measure). Parameters are optimized using Stochastic Gradient Descent in PyTorch.Resulta) Figure 1 shows each CSF measure as a function of age for each study (using the first CSF timepoint). The trend lines as age progress are preserved in the harmonized pooled data (Figures1‐ 2). b) Figure 3 shows each CSF measure before/after harmonization. c) Figure 4 includes scatter plots of CSF measures before/after harmonization using a categorical coding for APOE e4 status. We see that the shape of the distribution for each measure is preserved.ConclusionThese results show the feasibility of aligning CSF values from different cohorts and assay platforms (Lumipulse G1200 assay in ACS and Biocard and Roche Elecsys in WRAP). Mathematically rigorous schemes for analysis of pooled datasets based on modern developments in machine learning are facilitating AD research. We have shown that deploying such ideas for harmonizing/pooling CSF measures across preclinical AD studies appears viable. Our ongoing investigations are focused on understanding and quantifying the degree of improvements such schemes may offer for downstream statistical analysis tasks such as longitudinal trajectories of these measures as a function of demographic variables and risk factors.
Optimizing early detection of beta‐amyloid accumulation with PET using spatial extent
Authors: Farrell Michelle E. , Thibault Emma G. , Becker Alex , Price Julie C , Schultz Aaron P. , Properzi Michael J , Buckley Rachel F. , Jacobs Heidi I.L. , Hanseeuw Bernard , Sperling Reisa A. , Johnson Keith A. 
Published: December 2022

AbstractBackgroundAs clinical trials shift towards prevention, there has been increasing interest in improving early detection of beta‐amyloid (Aβ), below standard global PET positivity thresholds. While many studies have demonstrated that some regions appear more vulnerable to the earliest deposits, those regions have varied widely across studies. We sought to develop more flexible metrics for identifying subthreshold individuals at risk for progression to global Aβ positivity by evaluating a wide range of early regional targets and expanding our measurement beyond tracer retention (DVR/SUVR) to include spatial extent.Method269 clinically‐normal older adults were included from the Harvard Aging Brain Study, focusing on 150 initially globally PIB‐ adults with longitudinal PET. Region‐specific positivity thresholds were computed using iterative longitudinal two‐level linear mixed effect models that identified the cutoff beyond which local accumulation significantly increases over time. Next, we identified all regions significantly predictive of future global accumulation in initially PIB‐ adults and generated 3 aggregate masks at liberal (p<.05), moderate (p<.001) and conservative a‐levels (Bonferroni p<.0007). DVR and spatial extent (number of elevated ROIs) were computed in each mask. Receiver operator characteristic (ROC) curve analysis determined sensitivity/specificity of each metric to predict future global positivity. External validation was performed using globally florbetapir‐negative (FBP‐) healthy controls from the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n=211).ResultRegional variations in measurement reliability were detected (Fig1) and accounted for by employing accumulation‐based regional positivity thresholds. A broad set of ROIs were identified as potential early targets based on prediction of global accumulation, encompassing bilateral cingulate, medial frontal/parietal cortices and left‐lateralized lateral frontal/parietal/temporal cortices (Fig2). ROC analyses demonstrated that spatial extent outperformed DVR in predicting progression to global PIB+ within 3 years (Fig3), with 82% sensitivity and 97% and 98.5% specificity, respectively, for the two larger aggregate masks. External validation in ADNI (Fig4) again demonstrated the superior performance of spatial extent (SE=100%, SP=91.6%) in predicting progression to global positivity within 3 years.ConclusionOur findings demonstrate that due to a high level of heterogeneity in early Aβ deposition, measures of spatial extent across a broad set of neocortical regions are more sensitive to detect early Aβ than traditional DVR/SUVR.
Impact of amyloid PET in the clinical care of US Veterans in a Tertiary Memory Disorders Clinic
Authors: Vives‐Rodriguez Ana , Schiloski Kylie A , Marin Anna , Wang Ryan , Hajos Gabor P , Powsner Rachel , DeCaro Renee , Budson Andrew , Turk Katherine W 
Published: December 2022

AbstractBackgroundPrior studies assessing the clinical impact of amyloid PET have been limited to assessments before and after the scan. We aim to characterize the impact of amyloid PET in a veterans population with cognitive decline by comparing differences in clinical management within two years of follow‐up.MethodsThe current retrospective observational study includes all patients seen for an initial evaluation for cognitive complaints in the Memory Disorders Clinic at the VA Boston Healthcare System from October 2016 to January 2020. Clinical impact outcomes within two years of follow‐up were compared between patients with and without an aPET scan. Poisson regressions, negative binomial regressions, and binomial logistic regression were used for the analysis. Age, cognitive syndrome, follow‐up time, clinical diagnosis after initial evaluation and MoCA scores were used as covariates. Additionally, propensity score matching was performed to balance confounders between the two groups. To further understand the clinical impact outcomes in the aPET group, multiple regressions were performed within the group.ResultsFive‐hundred‐sixty‐five veterans were included in the analysis. Thirty‐five percent of patients underwent aPET imaging in addition to routine diagnostic workup. The study was positive in 72 patients (36.56%). Having an aPET, in addition to the usual diagnostic workup, was associated with a longer follow‐up time, and a higher diagnostic variability at follow‐up. We did not find an association between aPET use and the number of additional diagnostic studies ordered, early cholinesterase inhibitors prescription, or referrals to social work, research and clinical trials. When analyzing the same clinical utility outcomes within the group with an aPET, we found that a positive result was associated with fewer additional diagnostic tests, less diagnostic variability at follow up visits, more cholinesterase inhibitors prescription, and more research referrals.ConclusionsIn medically complex populations, aPET positivity might be lower than prior studies have described, used more to “rule out” than confirm the diagnosis of Alzheimer’s disease. This lower positivity rate results in less robust differences in classically explored clinical impact variables when comparing patients with and without an aPET.
Translational potential of JAX humanized‐APOE mice: Building the foundation for translational validity by applying human clinical trial principles
Authors: Wiegand Jean‐Paul L. , Skopp Stacy M , Brinton Roberta Diaz 
Published: December 2022

AbstractBackgroundThe 4th isoform of apolipoprotein E is the most prevalent genetic risk factor for Alzheimerʼs Disease (AD) and transgenic APOE animal models are widely used. However, APOE4’s penetrance is only ∼50‐60% and many studies do not use sufficient sample sizes to account for this.MethodTo address knowledge gaps regarding APOE penetrance and advance translatability of JAX humanized APOE (hAPOE) mouse models, we utilized a translational animal data management system recapitulating core aspects of human clinical trials: unique mouse IDs linked to all tissue samples and analytic outcomes. Transgenic C57BL/6J mice carrying hAPOE alleles (hAPOEe3/3, hAPOEe3/4 or hAPOEe4/4) were bred and longitudinally tracked for identification and analysis of susceptible and resilient subpopulations through population‐level studies on monthly weights (N = 1129 mice, N = 13262 weights), clinical observations (N = 2754 mice), and survival rates (N = 559 mice not utilized in studies).ResultColony‐wide analyses showed few differences, potentially leading to incorrect conclusions of minimal allelic effects. In this study, sub‐populations of hAPOEe4/4 mice exhibit divergent weight trajectories beginning at 15mo. Moreover, hAPOEe4/4 females displayed aberrations in fur barbering trajectories. The clinical observation of dermatitis was also noted more often in hAPOEe4/4 mice compared to hAPOEe3/3. Accordingly, hAPOEe4/4 animals, especially females, exhibit reduced survival rates, potentially due to divergent trajectories of susceptibility and resilience.ConclusionThe present study identified distinct subpopulations of hAPOE mice exhibiting clear susceptible vs. resilient phenotypes within longitudinal data. Therefore, results from cross‐sectional studies of hAPOE mice with small, average cohorts will be highly variable. Future studies selecting cohorts based on clinical observations such as weight and phenotypic indicator trajectory will advance translatability to human APOE4‐AD.Acknowledgements: Research supported by T32AG061897, R01AG057931, RF1AG059093, and Center for Innovation in Brain Science (CIBS) to RDB.
Subjective vs. Objective Memory Predictors of AD Biomarkers and Future Cognitive, Clinical, and Functional Decline
Authors: Risacher Shannon L. , Deardorff Rachael , Saykin Andrew J. 
Published: December 2022

AbstractBackgroundSubjective and objective memory have been previously linked to Alzheimer’s disease (AD) biomarkers and future clinical and cognitive decline. We the ability of two subjective memory assessments and two objective memory assessments to predict cross‐sectional amyloid, tau, and neurodegenerative (A/T/N) biomarkers, as well as future cognitive, clinical, and functional decline.Methods298 participants from ADNI were included, specifically 128 with normal cognition without memory concerns (CN), 123 with significant memory concerns (SMC; defined as a score of ≥20 on the first 12 items of the Cognitive Change Index (CCI)), and 47 with early mild cognitive impairment (EMCI). Objective memory was defined as immediate and delayed scores of Logical Memory and the Rey AVLT (RAVLT). Subjective memory measures included the memory sub‐scores of the ECog and CCI. Baseline Aβ and tau positivity were defined as positive on either neuroimaging and/or CSF biomarkers using standard cut‐offs. Neurodegeneration positive was defined as a hippocampal volume w‐score of 1.5 standard deviations below all CNs with 3T MRI in ADNI (adjusted for age, sex, and total intracranial volume). Cognitive decline was defined as a negative slope on the MMSE, while functional decline was defined as a longitudinal increase on the CDR‐sum of boxes and/or FAQ. For CN/SMC, conversion from normal cognition to MCI was also assessed. ROC curves were calculated for each objective and subjective measure for predicting conversion, functional decline, MMSE decline, and A/T/N positivity.ResultsFigure 1 shows ROC curves for the best predictor of each outcome. Baseline Aβ positivity, MCI conversion, and MMSE decline were best predicted by RAVLT immediate recall. However, functional decline and N positivity were best predicted by the CCI‐12. Tau positivity was also best predicted by subjective memory, the ECog memory sub‐score.ConclusionObjective memory provided the best prediction of Aβ positivity, MCI conversion, and cognitive decline, while subjective memory was the best predictor of T and N positivity and functional decline. These findings suggest that objective and subjective performance provide complementary information about prognosis in preclinical and very mild symptomatic individuals. Future evaluations of prognostication of these measures in a clinical setting will expand these findings.