bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterizing plasma biomarkers of the ATN framework among a diverse community‐dwelling cohort: A HABS‐HD study
Authors: Petersen Melissa , Zhang Fan , Hall James , Ances Beau , Cohen Annie , Meeker Karin L. , Mason David , Barber Robert , Johnson Leigh , O'Bryant Sid E. 
Published: December 2023

AbstractBackgroundThe A/T/N research framework for Alzheimer’s Disease calls for the importance of examining differences in these biomarkers across racial and ethnic groups. This study aims to address this need and examine the correlation and application between A/T/N plasma and neuroimaging biomarkers among a diverse cohort.MethodData were analyzed on Non‐Hispanic White (NHW) (n = 14 A+, n = 117 A‐; n = 4 T+, n = 83 T‐; n = 204 N+, 388 N‐) and Mexican American (MA) (n = 2 A+; n = 75 A‐; n = 3 T+, n = 27 T‐; n = 205 N+, n = 443 N‐) participants from the Health and Aging Brain Study‐ Health Disparities. Participants underwent a blood draw and neuroimaging (MRI, PET Amyloid and Tau). Plasma A/T/N biomarkers of Amyloid Beta (Aβ) 40, 42, Total Tau (T‐Tau), PTau‐181, and Neurofilament Light Chain (Nf‐L) were derived using Single Molecule Array (SIMOA) technology on HD‐X. Pearson correlations were conducted using plasma and neuroimaging A/T/N biomarkers. Due to the limited sample size of A+ and T+, support vector machine models were run in the total sample to examine the application of plasma biomarkers in predicting neuroimaging derived A+/T+/N+.ResultIn the total sample, Aβ 42 correlated with all PET amyloid ROIs. Ptau‐181 correlated with PET Tau SUVR in the Medial Temporal and Posterior Cingulate and clinical read of Tau +, same with T‐Tau. Nf‐L also correlated with MRI derived N+. Aβ 40 and 42 produced an AUC of 69% in detecting PET Amyloid + while T‐Tau and Ptau‐181 produced an AUC of 86% in detecting PET Tau +. Nf‐L alone produced an AUC of 66% in detecting MRI derived N+. Among MAs, Aβ 40 correlated with PET amyloid Frontal, Anterior Posterior Cingulate, Lateral Parietal, and Global SUVR while Ptau‐181 correlated with clinical read of Tau +. Nf‐L correlated with MRI derived N+ among MAs. Among NHWs, Aβ 40 and 42 correlated with clinical read of Amyloid +, while the later correlated with all PET amyloid ROIs. Neither T‐Tau, Ptau‐181 nor Nf‐L correlated with respective T or N neuroimaging biomarkers among NHWs.ConclusionThis work supports prior findings and highlights ethnic specific differences in the interconnection between A/T/N plasma and neuroimaging biomarkers.
APOEe4*TREM2 and sickle cell trait in a late onset Alzheimer’s disease mouse model
Authors: Propsom Kat , Gowru Srivani , Wandu Sylvia , Hyacinth Hyacinth I 
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) is a neurodegenerative disease associated with neuroinflammation, dysregulated neurovascular coupling, abnormal neuroplasticity, and neuropathological makers, including tau and β‐amyloid deposition. Advancing age is the greatest risk factor, and apolipoprotein E (APOE) e4 and triggering receptor expressed on myeloid cells 2 (TREM2) are genetic risk factors for late‐onset AD, which comprises >95% of all AD cases. Sickle cell trait (SCT) refers to the heterozygous inheritance of the sickle cell hemoglobin mutation. Studies from our laboratory and others show that SCT is associated with increased risk of microvascular complications and peripheral inflammation. Given the role of cerebral small vessel disease and inflammation in the pathogenesis of AD, we hypothesized that SCT may interact with late‐onset AD gene variants, resulting in earlier development of cognitive impairments, possibly via promoting neuroinflammation.MethodTo test our hypothesis, 10‐12 weeks old mice carrying APOE e4*TREM2 combined late‐onset AD genes were transplanted with bone marrow from humanized Townes mice with SCT (AS) or normal (AA) hemoglobin, following irradiation. Using a longitudinal cross‐sectional design, 3 cohorts were evaluated at 8, 12, and 18 months for presence of cognitive deficits using rodent behavioral testing. Mice were sacrificed immediately following behavioral testing, and brain tissue was evaluated using immunohistochemistry and Golgi‐Cox impregnation histology.ResultBehavioral testing suggested only age‐related cognitive impairments. There were no significant differences in neuroinflammation at any age between AS and AA mice in the hippocampus or corpus callosum and external capsule. Within genotypes, there was an age dependent increase in neuroinflammation, between 8 and 12 months in the hippocampus (p < 0.0001, p = 0.0002) and 12 versus 18 months in white matter tracts (p < 0.0001, p < 0.0001). There were no significant differences in the dendritic spine density or the proportion of immature spines between AS and AA mice. However, within genotypes there was significant differences between 12 and 18 months (p < 0.0001, p < 0.0001), with 18 months having lower spine density and higher proportion of immature spines.ConclusionAddition of SCT to a background of APOE e4*TREM2 did not result in earlier onset of cognitive impairment or more severe neuroinflammation.
The Prediction of Alzheimer’s Disease through Multi‐Trait Genetic Modeling
Authors: Clark Kaylyn , Fu Wei , Liu Chia‐Lun , Ho Pei‐Chuan , Wang Hui , Lee Wan‐Ping , Chou Shin‐Yi , Wang Li‐San , Tzeng Jung‐Ying 
Published: December 2023

AbstractBackgroundPrevious studies have indicated that prediction performance of a genetic risk score is improved when the score is built using information about multiple traits/risk factors associated with the target trait. To better capture the polygenic architecture of Alzheimer’s Disease, we developed a joint genetic score, MetaGRS.MethodWe incorporated genetic variants for AD and 24 other traits from two independent cohorts, NACC (n = 3,174, training set) and UPitt (n = 2,053, validation set).ResultOne standard deviation increase in the MetaGRS is associated with about a 57% increase in the AD risk (HR = 1.577, p = 7.17 E‐56), showing little difference from the HR for AD GRS alone (HR = 1.579, p = 1.20E‐56), suggesting similar utility of both models. We also conducted APOE stratified analyses to assess the role of the e4 allele on risk prediction. Similar to that of the combined model, our stratified results did not show a considerable improvement of the MetaGRS.ConclusionOur study showed that prediction power of the MetaGRS significantly outperformed that of the reference model without any genetic information, but was effectively equivalent to the prediction power of the AD GRS in both the full and stratified analyses. Our findings are broadly consistent with previous studies of Stroke and T2D.
Supporting informed decision‐Making about Alzheimer’s biomarker disclosure: identifying areas of knowledge and information needs in a research cohort
Authors: Ketchum Fred B , Erickson Claire M , Chin Nathaniel A. , Basche Kristin E , Rosario Hannah , Johnson Sterling C. , Clark Lindsay R. 
Published: December 2023

AbstractBackgroundEducation and counseling are recommended prior to Alzheimer’s disease (AD) biomarker disclosure to allow individuals to make an informed decision about whether they want to learn their results. Disclosure is occurring more frequently in research settings, and will likely be implemented in clinical populations in the future. Effective and feasible approaches to education and counseling are needed to ensure individuals are appropriately informed and supported prior to biomarker testing and disclosure.MethodsEligible participants from the Wisconsin Registry for Alzheimer’s Prevention (WRAP) elected to learn their amyloid PET results (n = 97). The disclosure process included an education session, disclosure visit, and lifestyle counseling visit. At the education session, baseline knowledge was assessed using a 15‐item quiz. Next, participants were guided through a 15‐minute interactive presentation on dementia, lifestyle and genetic risk factors for AD, significance of PET results, and potential psychosocial outcomes post‐disclosure. The quiz was then administered again.ResultsParticipants (age = 71.9±4.8, 94.8% non‐Hispanic White) with elevated (n = 28) and not‐elevated (n = 69) biomarker results were enrolled. Mean quiz scores were 12.1 before the educational session and 14.3 after the session, and did not differ based on amyloid positivity. Most participants correctly answered pre‐test questions about the progression of AD and risk factors, the significance of amyloid, and that biomarker results were part of research. The main areas of knowledge gained were about the causes of dementia (22.7% pre‐test vs 69.1% post‐test), significance of APOE genes (57.8% vs 90.7%), and extent of existing protections against discrimination on the basis of genetic tests (48.5% vs 93.8%). For one question about early symptoms of AD, knowledge decreased (70.1% vs 58.8%).ConclusionIn a cohort of currently enrolled AD research participants, baseline knowledge about amyloid and research was high, but information needs existed around causes of dementia, early AD symptoms, genetic information, and protections against psychosocial consequences such as discrimination. To support informed decision‐making about disclosure, future research should determine educational needs among clinical populations and adapt materials to effectively and feasibly communicate this information.
Association of plasma biomarkers with cognitive domains across three neurodegenerative diseases and cerebrovascular disease
Authors: Sanchez Erlan , Wilkinson Tim , Coughlan Gillian T , Baril Andree‐Ann , Binns Malcolm , McLaughlin Paula , Kwan Donna , Hegele Robert , Black Sandra E. , Lang Anthony E , Tartaglia Carmela , Finger Elizabeth , Freedman Morris , Swartz Richard H. , Kvartsberg Hlin , Zetterberg Henrik , Munoz Douglas , Masellis Mario 
Published: December 2023

AbstractBackgroundIt is critical to better understand the value of plasma biomarkers in predicting cognitive deficits before widespread use as diagnostic and prognostic tools in specialized clinics and as markers of neurodegenerative disease progression in trials. Herein, we investigate their association with five cognitive domains across three common neurodegenerative diseases and cerebrovascular disease.MethodPatients from the curated multi‐site Ontario Neurodegenerative Disease Research Initiative (ONDRI) were included in this study, classified by diagnostic group: Alzheimer’s disease/Mild cognitive impairment (AD/MCI, n = 126, age = 71.0±8.2, 55%M), frontotemporal dementia spectrum disorders (FTD, n = 53, age = 67.8±7.1, 64%M), Parkinson’s disease (PD, n = 140, age = 67.9±6.3, 78%M) and cerebrovascular disease (CVD, n = 161, age = 69.2±7.4, 68%M). Plasma concentrations of Aβ40 and Aβ42 (Aβ42/40 ratio), glial fibrillary acidic protein (GFAP), neurofilament light (NfL) and phosphorylated‐tau181 (p‐tau181) were measured using high‐sensitivity Simoa assays. Scores from a 26‐test comprehensive neuropsychological assessment were used to compute composite z‐scores for five cognitive domains: attention & working memory, executive function, language, memory, and visuospatial function. Linear regression models controlling for age, sex, education and APOE E4 allele were used to test the association between plasma biomarkers and cognitive domains in each group separately.ResultIn AD/MCI, higher levels of GFAP, NfL and p‐tau181 were all associated with worse attention & working memory, executive function, and memory. In PD, higher levels of NfL were associated with worse attention & working memory, executive function, and visuospatial function; higher levels of GFAP were also associated with worse executive function. In CVD, higher levels of GFAP were associated with worse executive function, memory and visuospatial function; higher levels of p‐tau181 were also associated with worse memory. In FTD, no associations were found.ConclusionPlasma biomarkers indicative of neuronal and glial pathology are useful to predict the severity of widespread cognitive deficits in AD/MCI, PD, and CVD. Interestingly, p‐tau181 predicted memory deficits in both AD/MCI and CVD, suggesting potential mixed disease or pathological overlap. Plasma Aβ42/40 does not appear to predict any cognitive deficits in any of the neurodegenerative diseases studied. As FTD is highly heterogeneous and had the least number of patients, we are possibly lacking power to detect effects in this group.
Development of neuroimaging biomarkers in non‐human primate model of sporadic Alzheimer’s disease pathology
Authors: Murray Sean , Veraart Jelle , Szabo Jakub , Akers Carolyn , Genovese Thomas S , Goldman Hannah , Llanos Michael , Rusinek Henry , Hopkins William D , Gray Stanton B , Wisniewski Thomas , Zaim‐Wadghiri Youssef , Scholtzova Henrieta 
Published: December 2023

AbstractBackgroundSquirrel monkeys (SQMs) are a non‐human primate (NHP) model of Alzheimer’s disease (AD) pathology with extensive cerebral amyloid angiopathy (CAA). Our work characterizes neuroimaging biomarkers associated with aging and neurodegeneration. Previously, we demonstrated the sensitivity of 1) in vivo regional quantitative R2* alterations to track age‐related changes in neuropathology and 2) ex vivo diffusion‐weighted (DWI) MRI metrics to visualize changes in brain microstructure. We recently extended our analyses to in vivo multi‐shell diffusion metrics for detection and classification of amyloid‐related imaging abnormalities (ARIA), which have been linked to parenchymal vasogenic edema and sulcal effusions. To further facilitate quantitative analysis of MR markers (diffusion and R2*) we have built a novel pipeline for atlas‐based region‐of‐interest (ROI) segmentation using a SQM brain atlas modified from Schilling et al. (2017). Here we evaluate age‐related changes in R2* values and region‐specific volume using this automated workflow.MethodYoung and geriatric female SQMs underwent 2D T2‐weighted (T2‐w) Turbo Spin Echo (TSE) RARE and FLAIR MRI scans, in addition to multi‐shell DWI acquisitions. DTI and DKI metrics were derived from DWI datasets, including mean diffusivity (MD), mean kurtosis (MK), and fractional anisotropy (FA). We utilized in vivo multi‐gradient echo (MGE) scans to generate R2* maps for ROI‐based quantitative assessments of SQM neuropathology.ResultWe identified multiple instances of asymmetric hyperintensities (ARIA‐E) in geriatric SQMs using 2D T2‐w TSE RARE, FLAIR, and DWI MRI sequences in vivo. While RARE and FLAIR scans demonstrated abnormalities in SQM brains, diffusion metrics MD and MK revealed greater propagation of the lesions through WM tracks. Histological analyses of the underlying neuropathology (e.g. myelin, neuroglia, and amyloid burden) are underway. Significant increases in R2* values with age were observed in all defined cortical regions, with subsequent histological confirmation of severe CAA, microhemorrhages, and iron deposits. Preliminary volumetric measurements revealed significant decreases with age in the prefrontal cortex. Additional morphometric analyses are ongoing.ConclusionWe safely monitored age‐dependent changes in neuroimaging parameters derived from diffusion‐weighted, T2‐w TSE RARE, and FLAIR acquisitions. Our study highlights the utility of the SQM model to uncover potential long‐term consequences of ARIA and validates diffusion MRI methodologies to target brain integrity.
Differential Effects of Anticholinergic Medications in a Human Neuronal Model of AD
Authors: Schwarze‐Taufiq Tiara A. , Sammeth Eleanore , Crane Paul K , Gray Shelly L , Young Jessica E. 
Published: December 2023

AbstractBackgroundAnticholinergic (ACh) use remains common in older adults despite evidence of safety risks, including dementia risk. Evidence from population studies suggests that dementia risk may vary by ACh class. This variation might be explained by confounding by indication. In vitro models, using human neural cells where cells are directly experimentally exposed to a drug and phenotypic outcomes are measured, may address this issue. We identified classes of ACh medications that have different degrees of dementia risk based on a population study. We then treated human induced pluripotent stem cell‐derived neurons (hiPSC‐Ns) with each medication and performed cellular assays to examine the effects on AD phenotypes.MethodWe used CRISPR/Cas9 to generate an isogenic set of hiPSCs that harbor the autosomal dominant Swedish mutation in APP (APPSwe) and compared these to wild‐type control cells developed using the same pipeline. We differentiated neurons (hiPSC‐Ns) from these cells using established protocols in our laboratory. We treated these neurons with different classes of ACh medications: antidepressants (amitriptyline, doxepin, paroxetine), antihistamines (diphenhydramine, chlorpheniramine), bladder antimuscarinics (oxybutynin, tolterodine), and antispasmodics (atropine). As a control, we treated cells with the classic cholinergic compound carbachol. Cells were treated with two drug doses (0.01 and 0.01mM) at two time points (24 and 48hrs). We used molecular assays to test AD‐associated cellular outcomes (neurotoxicity, Amyloid beta [Ab], and pTau).ResultWe document differential effects of medications on all AD outcomes measured. Several drugs demonstrated dose‐dependent (doxepin, oxybutynin, paroxetine, amitriptyline) and/or time dependent (oxybutynin, paroxetine) neurotoxicity. We also observed differential effects on Ab secretion, with paroxetine, doxepin, and diphenhydramine lowering Ab and chlorpheniramine having no effect. Interestingly, medications not demonstrating neurotoxicity (diphenhydramine, chlorpheniramine, tolterodine, atropine, carbachol) also reduce intracellular pTau at lower concentrations.ConclusionStem cell‐derived neuronal models provide a useful strategy to complement pharmacoepidemiological studies to help distinguish molecular versus environmental actions of drugs associated with dementia risk. Preliminary results suggest that different ACh drugs have differential effects on AD‐associated cellular outcomes. Future work will test this panel of medications on hiPSC‐Ns derived from Adult Changes in Thought (ACT) cohort subjects with high and low AD genetic risk
The impact of Alzheimer’s disease pathology and cardiovascular risk factors on cross‐sectional brain structure in the U.S. POINTER Imaging study
Authors: Harrison Theresa M. , Ward Tyler J. , Lockhart Samuel N. , Vemuri Prashanthi , Lovato Laura , Snyder Heather M , Baker Laura D , Koeppe Robert A. , Decarli Charles , Jagust William J. , Landau Susan M. ,   the U.S. POINTER Study Group
Published: December 2023

AbstractBackgroundThe U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is a 2‐year randomized controlled trial to evaluate the effect of lifestyle interventions in cognitively unimpaired older adults (60‐79 years) at risk for decline/dementia. Here, using data from the POINTER Imaging ancillary substudy, we explore how Alzheimer’s disease pathology and cardiovascular risk influence brain structure, cognition and their relationship.MethodPOINTER Imaging participants underwent cross‐sectional MRI, [18F]Florbetaben (FBB) Aβ‐PET and [18F]MK6240 tau‐PET. FBB and MK6240 data were processed using previously validated methods. MRIs were processed with voxel‐based morphometry. To quantify cardiovascular risk, the Framingham risk score (FRS) was calculated for each participant. We used linear regression models in the whole sample as well as in Aβ status subgroups to evaluate voxel‐wise associations of brain structure, measured using voxel‐based morphometry, with age, FRS, AD pathology (cortical summary Aβ and entorhinal cortex (ERC) tau burden), and a global cognition composite score.ResultAcross all 624 participants (Table 1), cognition (age‐adjusted) was positively related to brain structure across temporal, frontal and medial parietal cortices (Fig. 1A). ERC tau‐PET was negatively associated with brain structure in bilateral medial temporal lobes (MTL) and, notably, in bilateral basal forebrain (Fig. 1B). FRS showed significant negative associations in superior temporal gyrus and occipital cortex (Fig. 1C), but tau‐PET associations remained similar when adjusting for FRS. In Aβ+ participants, cognition‐ and FRS‐structure relationships were weaker but tau‐PET‐structure associations were stronger and extended outside the MTL. In Aβ‐ participants, cognition‐ and FRS‐structure relationships were similar to those observed in the whole cohort and tau‐PET associations were no longer significant.ConclusionIn this heterogeneous cohort of older adults, tau was associated with brain structure in strikingly specific patterns that were related to Aβ but not to cardiovascular risk as measured by the FRS. Tau‐structure associations were restricted to temporal lobes and basal forebrain and were independent of more widespread cognition‐structure associations, indicating that factors other than tau may play a critical role. Our next steps include comparing the current cohort to others with different at‐risk characteristics (e.g., ADNI, Berkeley Aging Cohort Study).
Differential Microglial activation and Astrocyte reactivity in Alzheimer’s trajectory
Authors: Edison Paul 
Published: December 2023

AbstractBackgroundMicroglial activation and astrocyte activation plays a significant role in the pathogenesis of AD. Here, we evaluate microglial activation, the interrelationship between microglial activation, amyloid and tau pathologies, and the impact of microglial activation in Alzheimer’s disease trajectory. We specifically focus on microglia as a major player in neuroinflammation and evaluate the spatial and temporal variation of microglial activation in the disease trajectory. Additionally, we evaluate astroglial activation using novel astrocyte marker and evaluate the relationship between amyloid, MRI volume changes and glucose metabolism in Alzheimer’s trajectory.MethodWe evaluated AD, MCI and cognitively normal subjects using amyloid PET, tau PET and neuroinflammation using TSPO PET scans. A separate group of AD, MCI and control subjects were evaluated using novel astrocyte marker [11C]BU99008 PET along with [18F]FDG PET and amyloid PET. [11C]PBR28 and [11C]BU99008 PET scans were analysed using two tissue compartmental model, while [18F]Flutemetamol was analysed using target to cerebellar ratio. [18F]FDG PET was analysed using pons as a reference region. We performed regional and voxel wise analysis for all the tracers.ResultMicroglial activation was elevated in different cortical regions in both AD and MCI subjects. Microglial activation was associated with lower grey matter density in later stages of the disease, while higher grey matter volume was associated with increased microglial activation in early mild cognitive impairment subjects. There were areas of increased astrocyte activation in both AD and MCI. Higher microglial activation was associated with increased tau formation and neuronal damage in later stages of the disease. Interestingly, there was increased astrocyte reactivity in the early stages of the disease.ConclusionWhile microglial activation in the late phase of the disease is associated with neuronal damage, however, in the early stages microglial activation was associated with higher grey matter volume. Microglial activation demonstrated a biphasic pattern of activation. In contrast to microglial activation, astrocyte activation was prominent in the early stage of the disease and may be associated with neuroprotection. This suggests that in targeting glial activation as a therapeutic strategy, we must target astrocyte and microglia separately and in different stages of the disease.