bluuebunny/crossref_metadata_2025_split huggingface dataset:
TRIAD multi‐dimensional biobank for biomarker discovery
Authors: Stevenson Jenna , Rahmouni Nesrine , Chamoun Mira , Benedet Andréa Lessa , Stevenson Alyssa , Pallen Vanessa , Therriault Joseph , Lussier Firoza Z , Tissot Cécile , Bezgin Gleb , Pascoal Tharick A , Vitali Paolo , Gauthier Serge , Rosa‐Neto Pedro 
Published: December 2022

AbstractBackgroundThe Translational Biomarkers in Aging and Dementia (TRIAD) is a longitudinal, biomarker‐based cohort designed to study interactions between the pathophysiological processes driving to dementia. Currently, 50 million people worldwide have dementia [1]. PET and MRI imaging have been widely used to assess disease stage, though expensive and not readily accessible [2]. More recently though, breakthroughs in blood‐based biomarkers have proven a useful, available, and more cost‐effective way of evaluating amyloid and tau positivity. The TRIAD Biobank provides a unique framework to study disease stage using blood‐based biomarkers in conjunction with PET and CSF studies. Our cohort allows for validation of novel biomarkers as we simultaneously acquire gold standard second generation imaging acquisitions with full spectrum fluid biomarkers (CSF, saliva, plasma, urine). Importantly, the data acquired is integrated in a database compliant to multi‐dimensional biomarker analysis.MethodFigure 1 depicts the cohort's banked fluids by diagnostic group. Figure 2 depicts the cohort's banked fluids by sex grouping.ResultThe TRIAD Biobank stores 1,034 blood samples from 655 participants, 658 of these being follow‐up collections. Additionally, cerebrospinal fluid has been collected from 381 individuals accounting for 520 collections in the bank, 812 urine collections from 662 individuals and 591 saliva samples from 432 individuals.Additionally, the cohort has collected 761 tau PET scans using [18F]MK6240, 644 amyloid PET scans using [18F]AZD4694 and 804 MRI using 3 Tesla.ConclusionWith dementia being one of the leading, most costly causes of death, the need for early detection, more affordable, less invasive, and more readily available ways to determine disease stage is apparent [2]. The TRIAD multi‐dimensional biobank provides a wealth of resources to discover affordable biomarkers needed for early diagnosis and Alzheimer’s disease prevention.[1] Patterson, C. 2018. World Alzheimer Report 2018: The state of the art of dementia research, new frontiers. London, England: Alzheimer's Disease International[2] Gauthier S, Rosa‐Neto P, Morais JA, & Webster C. 2021. World Alzheimer Report 2021: Journey through the diagnosis of dementia. London, England: Alzheimer’s Disease International.
Genetic characterization of a Turkish dementia cohort: a focus on leukodystrophy genes
Authors: Dehghani Nadia , Guven Gamze , Westra Kaitlyn , Gardner Eve , Paquette Kimberly , Gibbons Elizabeth , Hanagasi Hasmet , Lohmann Ebba , Samancı Bedia , Gurvit Hakan , Bilgiç Başar , Bras Jose , Guerreiro Rita 
Published: December 2022

AbstractBackgroundLeukodystrophies broadly affect the brain white matter. As such, diseases including cerebral autosomal dominant/ recessive arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL/CARASIL) are included in this group. NOTCH3 and HTRA1 variants are a known cause of CADASIL and CARASIL, respectively. Studies have reported NOTCH3 variants in Alzheimer’s disease, and heterozygous HTRA1 variants in cerebral small vessel disease. Therefore, there is growing evidence of leukodystrophy gene variants in neurodegenerative diseases.MethodWe screened a whole‐exome sequenced Turkish dementia cohort for rare variants in a panel of leukodystrophy genes. Where familial samples were available, we tested for segregation. We also consulted the exome data available from the Turkish Variome to gauge a better estimate of population frequency for candidate variants.ResultWe identified rare variants in leukodystrophy genes in individuals from this Turkish dementia cohort. Variants in NOTCH3 include a known pathogenic gain‐of‐cysteine variant in a family presenting with CADASIL (NOTCH3 p.Arg133Cys); a novel loss‐of‐cysteine variant (NOTCH3 p.Cys65Tyr) in an atypic dementia case, and a novel cysteine‐sparing missense variant (NOTCH3 p.Ala818Thr) in a family with Alzheimer’s disease and mild cognitive impairment.ConclusionConsidering the increased consanguinity of the Turkish population we were expecting to identify bi‐allelic variants in HTRA1 with potential roles in disease. Instead, NOTCH3 presented a higher burden of variability, including known and novel variants expected to be involved in disease.
Plasma Amyloid‐β 40 as a Potential Biomarker in Cerebral Amyloid Angiopathy
Authors: Lee Jin San , Park Key‐Chung , Rhee Hak Young , Hwang Kyo Seon 
Published: December 2022

AbstractBackgroundWe aimed to analyze plasma amyloid‐β (Aβ) using a highly sensitive nano‐biosensing platform to demonstrate the possibility of precise cerebral amyloid angiopathy (CAA) diagnosis in participants classified according to amyloid PET positivity and the neuroimaging criteria for CAA.MethodA total of 25 normal controls (NC) and 19 patients with Alzheimer’s disease (AD), which were further classified into the CAA− and CAA+ groups according to the modified Boston criteria were recruited in this study. All participants underwent plasma Aβ analysis using a highly sensitive nano‐biosensing platform, amyloid PET scanning, and detailed neuropsychological testing.ResultThe average signal levels of plasma Aβ42/40 differed significantly between the NC and AD groups, and the CAA+ group exhibited significantly higher plasma Aβ40 signal levels than the CAA− group in both NC and AD groups. The concordance between the plasma Aβ40 signal level and the neuroimaging criteria for CAA was nearly perfect. Higher plasma Aβ40 signal levels were significantly associated with the presence of CAA based on the regression analyses, and the neuroimaging pattern analysis partly supported this result.ConclusionOur findings suggest that measuring plasma Aβ40 using a highly sensitive nano‐biosensing platform could be a useful non‐invasive diagnostic method for detecting CAA.
Translational potential of JAX humanized‐APOE mice model: Accelerated midlife endocrine aging in hAPOEε4/4 females
Authors: Wang Tian , Mao Zisu , Delatorre Nicole , Wiegand Jean‐Paul L. , Brinton Roberta Diaz 
Published: December 2022

AbstractBackgroundAge, female sex and APOEε4 genotype are the greatest Alzheimer’s (AD) risk factors, with a stronger APOEε4 link to AD in women. The APOE‐sex interaction is also evident in hAPOE mouse models where APOEε4 induces more severe neurodegeneration and cognitive deficits in female mice. However, the mechanisms by which these two risk factors converge to disrupt brain function remain elusive.MethodTo investigate effect of APOE genotype on midlife endocrine aging, 6‐, 9‐ and 15‐month hAPOEε3/3 and hAPOEε4/4 female mice were stratified into 3 different endocrine aging groups based on vaginal cytology profiles: regular cyclers (consistent 4–5 day cycles), irregular cyclers (of 6–9 day cycles), and acyclic (no cycling >9 days). Plasma levels of metabolomic makers were measured. Brain mitochondrial function was quantified.ResulthAPOEε4/4 females exhibited accelerated endocrine aging evidenced by increased magnitude of brain metabolic defect coupled with inability to mount an adaptive bioenergetic response. Systems biology of endocrine aging initially identified in perimenopausal rat model were replicated in the hAPOEε3/3 mouse model. In contrast, hAPOEε4/4 females exhibited accumulation of adipose tissue with high plasma triglyceride and accelerated ketone body dysregulation during perimenopausal transition, indicating deficits in adaptive metabolic response required for sustaining brain metabolic demand during aging. Further, hAPOEε4/4 females exhibited greater perimenopause‐ and menopause‐induced brain mitochondrial dysfunction.ConclusionOutcomes of these analyses provide a plausible mechanistic pathway underlying the greater risk of AD in APOEε4 females. Further, these data indicate that the bioenergetic crisis underlying metabolic reprogramming in brain are greater in the APOEε4 female brain while compensatory adaptive responses are compromised. These findings provide a rational mechanistic precision medicine approach to intervene during midlife to prevent or delay the onset of the prodromal / preclinical stage of AD.This work was supported by NIA grants P01‐AG026572 Project 2 to RDB and Animal Core to TW.
PPA Tele‐Savvy: Piloting an Online Intervention with Care Partners of Persons Living with Primary Progressive Aphasia
Authors: Morhardt Darby , Dyslin‐Kman Deborah Nicole , Maley Kate , Roberts Angela C , Weintraub Sandra 
Published: December 2022

AbstractBackgroundPrimary Progressive Aphasia (PPA) brings unique challenges for caregiving families. Most evidence‐based interventions available to dementia caregivers do not match their needs for tailored psychosocial support.MethodThis pilot study funded by the Emory University Roybal Center is an adaptation of the evidence‐based on‐line psychoeducation program (Tele‐Savvy) to address the unique challenges facing informal caregivers of those living with PPA and to help these caregivers achieve competence in their role. Using focus group data from PPA caregivers previously enrolled in Tele‐Savvy, the program curriculum was adapted to address caring for persons living with PPA. The intervention consists of seven 90‐minute weekly videoconference sessions with weekly homework, coaching and debriefing sessions. Pre/post measures look at the effects of the program on PPA knowledge, mood, caregiver burden, perceived stress, competence, quality of life and couple relationship for 9 spouse caregivers followed by a focus group 2 weeks post‐intervention to obtain additional feedback.ResultThe 7‐week course was not complete by the time of abstract submission. Results will be available at the time of the conference.ConclusionWe aim to demonstrate the feasibility of offering an online PPA caregiver intervention tailored to meet their specific needs. Future research will be conducted based on what is learned from this pilot program.
Beyond the Uniform Data Set (UDS): Benefits of incorporating additional items for the measurement of memory, executive functioning, and language from the University of Pittsburgh Alzheimer’s Disease Research Center
Authors: Choi Seo‐Eun , Mukherjee Shubhabrata , Gibbons Laura E , Trittschuh Emily H. , Lee Michael L. , Scollard Phoebe , Sanders R. Elizabeth , Snitz Beth E , Sweet Robert , Lopez Oscar L. , Mez Jesse B. , Saykin Andrew J. , Hohman Timothy J. , Crane Paul K. 
Published: December 2022

AbstractBackgroundAlzheimer’s Disease Research Centers (ADRCs) administer prescribed cognitive batteries – the Uniform Data Set (UDS) – and report UDS data to the National Alzheimer’s Coordinating Center (NACC). ADRCs may administer other items beyond the UDS. We used data from the University of Pittsburgh ADRC (Pitt) to determine psychometric implications of UDS items alone versus UDS items plus additional Pitt‐specific items.MethodWe used confirmatory factor analyses to co‐calibrate Uniform Data Set 1 and 2 (UDS1/2, broadly overlapping, 2005–2015) and UDS3 (2015‐2020) data for memory, executive functioning, and language. We added Pitt‐specific items for each domain. We compared measurement properties of UDS scores vs. UDS plus Pitt scores, including measurement precision and projected sample sizes needed to show a 25% reduction in rate of decline over 12 months for people with Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD).ResultThere were 2,726 participants with 8,602 visits across UDS1, 2, and 3 (Table 1). Figure 1 summarizes findings for memory. Figure 1a shows boxplots for memory scores for normal cognition (NC), MCI, and AD for UDS1/2 (green) and UDS3 (purple). Figure 1b shows corresponding boxplots and standard error of measurement (SEM) curves for UDS1/2 (left) and UDS3 (right). Incremental improvements in measurement precision can be seen with the lower SEM curve for the UDS plus Pitt curves. Figures 2 and 3 summarize similar findings for executive functioning and for language. In each case UDS Plus Pitt has less measurement error than UDS alone. Proportions of scores with standard errors >0.30 (a commonly used threshold for individual decision‐making) during UDS1/2 and UDS3 are in Table 2. Pitt‐specific items reduced the proportion with imprecise scores for every comparison with the exception of executive functioning in UDS1/2. Sample sizes needed to show a 25% reduction in the rate of decline are shown in Table 3. Improved precision from additional items was associated with greater power to show change over time.ConclusionIntegrating additional data beyond UDS1/2 and UDS3 results in better measurement precision and increased statistical power.
Investigating the role of lysosomal exocytosis in Alzheimer’s disease
Authors: Tsang Adrianna R , Seah Claudia , Krupa Jordan M , Pasternak Stephen H 
Published: December 2022

AbstractBackgroundMany studies have implicated the endosomal‐lysosomal system in the production of beta‐amyloid (Aβ), but the actual compartments involved in Aβ secretion have never been visualized. Although lysosomes are expected to be a site of Aβ clearance, studies have also shown them to be a site of Aβ accumulation. Lysosomal exocytosis is well recognized as a major secretory pathway in non‐neuronal cells but is virtually unstudied in neurons. This project investigates the role and mechanism of lysosomal secretion in neurons. We hypothesize that lysosomal exocytosis is a pathway for Aβ release and could be modulated by Rab27b in iPSC‐derived human neurons.MethodTo study lysosomal exocytosis in a neuronal system, our lab established normal and mutant APP Swedish expressing iPSC‐neurons. The involvement of lysosome‐related secretory proteins (Rab27b, Munc13‐4 and synaptotagmin‐7) were examined using siRNA, dominant‐negative or shRNA constructs. Cells were co‐transduced with a pH‐sensitive dual‐fluorescent lysosomal marker (pHluorin‐LAMP1‐mAppleFP) to identify and track lysosomes. Cells were also loaded with fluorescent exogenous Aβ or a dye to mark endogenous Aβ, and then treated with ionomycin to induce exocytosis. Total internal reflection fluorescence (TIRF) microscopy was performed to capture videos of molecular events occurring within 250nm from the plasma membrane. Imaris software was used to analyze co‐localization of LAMP‐1 with Aβ, and the number and timing of lysosomal secretory events.ResultIn untreated cells, loaded Aβ accumulated in lysosomes. After treatment with ionomycin, a dramatic decrease of lysosomal Aβ was observed. In live cells, TIRF microscopy captured lysosomes docking and fusing with the plasma membrane over 150 seconds after ionomycin treatment. This was visualized by pHluorin‐LAMP1 (which is normally dark in an acidic pH) fluorescing green upon lysosomal fusion with the plasma membrane. Overexpression of Rab27b N133I mutant significantly increased lysosomal exocytosis of Aβ compared to wild‐type, and Rab27b shRNA dramatically reduced lysosomal exocytosis and Aβ secretion.ConclusionOur results demonstrate that lysosomal exocytosis is a novel secretion pathway in human neurons and identify potential pharmacological targets that regulate clearance of toxic Aβ.
Cardiometabolic multimorbidity, genetic risk and dementia
Authors: Tai Xin You , Veldsman Michele , Lyall Donald M , Littlejohns Thomas J , Langa Kenneth M , Husain Masud , Ranson Janice M , Llewellyn David J 
Published: December 2022

AbstractBackgroundThe extent to which multiple cardiovascular and metabolic co‐morbidity and genetic factors combine or interact to increase dementia risk is unknown.MethodWe analysed 435 105 participants from the UK Biobank prospective cohort of European ancestry, aged 40 to 72 years, without dementia at baseline (2006‐2010), followed until 2021. A cardiometabolic multimorbidity index with a point given for co‐morbid stroke, diabetes and heart disease (myocardial infarction, atrial fibrillation or heart failure) was calculated for each participant along with a polygenic risk score for dementia with low (lowest quintile), intermediate (quintiles 2 to 4) and high (highest quintile) risk categories. The primary outcome was incident all‐cause dementia during follow‐up.ResultParticipants with both a high genetic risk and a cardiometabolic multimorbidity index of two or greater had an increased risk of developing dementia, hazard ratio of 5.01(95% confidence interval 3.35 ‐ 7.49), compared to those with a low genetic risk and no cardiometabolic conditions. The risk of developing dementia increased monotonically with increasing cardiometabolic morbidity. Crucially, there was no interaction between cardiometabolic multimorbidity and polygenic risk (P = 0.11).ConclusionCardiometabolic multimorbidity was independently associated with higher dementia risk, compared with genetic dementia risk. Addressing cardiometabolic multimorbidity may help to reduce dementia risk regardless of genetic risk.
Perceived discrimination and cognition in a middle age, racially diverse cohort
Authors: Likos Kelly D. S. , Swieboda Dominika , Williams McKayla , Dotson Vonetta M , Hu William T. , Verble Danielle D , Wharton Whitney 
Published: December 2022

AbstractBackgroundRisk factors for Alzheimer’s disease (AD) include biologic (e.g. vascular), economic, and socio‐cultural factors. AD incidence and prevalence has been linked to race, and African American/Black individuals (AA/B) are at greater risk compared to non‐Hispanic Whites (NHW), due to physiological and social factors, however few clinical research studies are dedicated to prospective and thoughtful data collection on both physiology (biomarkers) and social/structural risk factors, including discrimination.MethodsWe enrolled 49 middle‐age, cognitively normal B/AA (n = 29) and NHW (n = 20) participants with a family history of AD, and examined correlations between cognition and a perceived discrimination. Cognitive assessments included tests of global cognition, executive function, verbal and visuospatial memory, and language. Six discrimination factors were derived from a larger battery of individually validated assessments of perceived discrimination including, Expanded Everyday Discrimination (EED), Major Experiences of Discrimination (MED), Chronic Work Discrimination and Harassment (WORK), and the Heightened Vigilance (HVIGIL). Factor scores derived from these assessments included ‘Disrespect’, ‘Aggression’, ‘Housing’, ‘Avoidance’, ‘Professional’, and ‘Personal’. Models controlled for education, income, race, and age.ResultsPerceived discrimination had an influence on cognitive scores in a race‐independent manner in this cohort. It was also found that this relationship maybe stratified by educational level. Participants were mostly women (73.5%) highly educated (42.9% post‐Graduate education) and B/AA participants reported more perceived discrimination compared to NHWs across all 6 composite discrimination factors. We observed a positive association between episodic memory score and the 'housing’ discrimination factor (p = 0.34 (0.03)), such that increased housing discrimination was associated with increased cognition. A negative correlation was observed between working memory and the discrimination factor ‘Professional’ (p = ‐0.3 (0.05)).ConclusionDiscrimination negatively affects health outcomes and disease risk. Here we report a negative correlation between working memory and ‘professional’ factor score. We also report a positive correlation between cognition and housing discrimination. This latter is likely explained by the relationship between discrimination and geographic mobility, highlighting the presence of systemic and situational racism across all levels of socioeconomic status. Future AD research should incorporate historical and current data collection on redlining, Area Deprivation Index (ADI), and social and housing mobility.
Improved automated cerebral microbleed (CMB) detection
Authors: Gunter Jeffrey L. , Mead Aaron K , Bermudez Camilo L , Wiste Heather J. , Gebre Robel K , Vemuri Prashanthi , Knopman David S. , Petersen Ronald C. , Jack Clifford R. , Graff‐Radford Jonathan , Cogswell Petrice M 
Published: December 2022

AbstractBackgroundCerebral Microbleeds (CMBs) are tracked in anti‐amyloid drug safety monitoring. T2*GRE or SWI MRI images are visually assessed for the presence of CMBs. Automated methods tuned for sensitivity often have unacceptably high false positive rates requiring extensive human cleanup.MethodAssume contemporaneous T2*GRE and T1‐weighted images. CMB detection (Figures 1,2) has three steps: 1) Segmentation outputs from the T1‐weighted image are resampled into the T2*GRE image voxel raster; 2) Normalized cross‐correlation of the T2*GRE with a CMB template identifies “candidate CMBs”; 3) a neural network using voxel patches centered on each candidate CMB rejects false positives. Patches presented to the network are 4D and include five contrasts drawn from the T2*GRE, correlation, T1‐weighted, WM probability and CSF probability images. The simple network architecture consists of convolutional blocks followed by dense blocks. The system is trained using images from ADNI, ARIC, MCSA, and the Mayo Clinic ADRC that have been previously visually graded for CMBs (Table in Figure 3). Importantly, we include participants with and without CMBs in our data reflecting the fact that the majority of people (even the elderly) have no CMBs. Data is split 70:10:20 by subject for training, validation, and testing. Various network configurations were evaluated.ResultHigh candidate detection sensitivity can be achieved at the expense of presenting hundreds to thousands of false positive candidates per input image to the rejection network. Our best performing network configuration to date has AUC 0.982 (95% bootstrap CI 0.971 to 0.990 based on the 10% validation subset). Choosing an operating point with 95% sensitivity in the validation set and admits, on average, 0.6 false positive CMB candidates per input T2*GRE image. Sensitivity is hindered by a small number of obvious errors in the ground truth visual assessment. Validation loss tracks training loss with no indication of over‐fitting. Example patches are shown in Figure 4.ConclusionExcessive false positive detection requires significant human correction and effort, preventing automated CMB detection from being widely adopted. We have an automated detection system that is sensitive (95%) and provides excellent false positive rejection (<1 false positive CMB/input image) reducing needed human effort.