bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microglia‐specific Alzheimer’s disease polygenic risk score is associated with amyloid‐β, tau, and microglial activation
Authors: Yang Hyun‐Sik , Teng Ling , Kang Daniel , Menon Vilas , Ge Tian , Finucane Hilary , Schultz Aaron P. , Properzi Michael J , Klein Hans‐Ulrich , Chibnik Lori B. , Schneider Julie A , Bennett David A , Hohman Timothy J. , Mayeux Richard , Johnson Keith A. , De Jager Philip L , Sperling Reisa A. 
Published: December 2022

AbstractBackgroundGenome‐wide association studies (GWAS) of Alzheimer’s disease (AD) have implicated microglia in AD pathogenesis, and microglia is a promising cellular therapeutic target in AD. However, it remains unclear when and how AD genetic risk localizing to microglia contributes to AD pathophysiology.MethodParticipants are from two community‐based cohorts (Religious Orders Study, the Rush Memory and Aging Project [ROSMAP]; n = 299 deceased; age 88.9±7.1, female 67%) and the screening phase of an AD prevention trial (the Anti‐Amyloid Treatment in Asymptomatic Alzheimer’s study [A4]; n = 2919 cognitively unimpaired; age 71.4±4.8, female 60%). We quantified post‐mortem Aβ and tau in ROSMAP, and used PET to quantify Aβ (florbetapir cortical composite standardized uptake value ratio [SUVR]) and tau (flortaucipir temporal composite SUVR; subset n = 302) in A4. In a subset of ROSMAP participants (n = 31), we evaluated the proportion of activated microglia (PAM) in post‐mortem neocortex. We combined AD GWAS summary statistics with cellular gene expression profiles from human brain single nucleus sequencing, to derive cell‐type‐specific ADPRS (excluding APOE region) in ROSMAP and A4. We assessed the association of each (standardized) cell‐type‐specific ADPRS with AD pathology (linear regression; adjusting for APOE genotypes, age, sex, and first 10 genotype principal components), and examined the correlation between the microglial ADPRS and PAM (Pearson’s correlation). We used Bonferroni‐corrected p‐value threshold, p<6.25×10−3.ResultMicroglial, astrocytic, and endothelial ADPRS were associated with higher Aβ and tau in ROSMAP (Figure 1A‐B). In A4, microglial ADPRS showed the strongest association with Aβ (beta = 0.017, p = 1.6×10−7; Figure 1C), while the association of all other cell‐type‐specific ADPRS with Aβ were no longer significant once adjusted for microglial ADPRS (all p>0.05). Microglial ADPRS showed a suggestive association with temporal composite tau (beta = 0.033, p = 0.012; Figure 1D), even after additionally adjusting for Aβ (beta = 0.024, p = 0.048). Microglial ADPRS was positively correlated with PAM in ROSMAP (Figure 2).ConclusionGenetic risk of AD localizing to microglial genes may contribute to Aβ and tau accumulation and microglial activation, likely starting from the preclinical (cognitively unimpaired) stage. These findings directly connect aggregate microglial AD genetic risk with Aβ and tau accumulation, and provide a genetic rationale to test microglia‐specific interventions in AD prevention trials.
Evaluating the relationship between endostatin and cognition in mild cognitive impairment (MCI), coronary artery disease (CAD), and Alzheimer’s disease (AD)
Authors: Song Bing Xin , Herrmann Nathan , Gallagher Damien , Rapoport Mark J. , Charles Jocelyn , Papneja Purti , Rajji Tarek K. , Andreazza Ana C. , Oh Paul I. , Marzolini Susan , Kiss Alex , Swardfager Walter , MacIntosh Bradley J. , Vieira Danielle , Koo Grace KY , Lanctôt Krista L. 
Published: December 2022

AbstractBackgroundEndostatin is an endogenous angiogenesis inhibitor that can regulate pro‐and anti‐angiogenic factors, notably vascular endothelial growth factor. Research shows that endostatin levels in the brain are associated with amyloid plaque formation in Alzheimer’s disease (AD), and may contribute to AD pathogenesis. Hence, endostatin may be relevant to the broad range of cognitive impairments, namely people with mild cognitive impairment (MCI), AD, and/or coronary artery disease (CAD) who are at risk for cognitive impairment. We examine associations between serum endostatin and global cognition.MethodsParticipants with MCI, AD, or CAD (with or without MCI) were recruited. Serum endostatin concentrations were measured and analyzed using enzyme‐linked immunosorbent assays. MCI was diagnosed using either the Petersen criteria or the Diagnostic and Statistical Manual of Mental Disorders (DSM‐5) criteria. AD was diagnosed using DSM‐5 criteria. CAD was defined as at least 1 of previous hospitalization for acute myocardial infarction, coronary angiographic evidence of ≥ 50% blockage in ≥ 1 major coronary artery or a prior revascularization procedure. Global cognition was assessed by the Montreal Cognitive Assessment (MoCA). Linear regression analyses were used to assess the association between endostatin levels and global cognition with and without covariates. Endostatin levels were log‐transformed prior to analyses due to significant departure from normality in Shapiro‐Wilk tests.ResultsIn 119 participants, 94 (79.0%) were male, 102 (85.7%) had CAD, and 23 (19.3%) had MCI or AD; the mean(SD) age was 65.6(7.5), years of education were 16.4(3.3), and endostatin levels were 156.3(38.6) ng/mL. Endostatin was associated with global cognition alone [F(1,117) = 11.39, p <.001, R2 = .089] and also when considering covariates: age, sex, body mass index (BMI), education, MCI/AD diagnosis, and CAD diagnosis [F(7,111) = 11.27, p< .001, R2 = .415]. All variables except age, sex, BMI, and CAD diagnosis added significantly to the association (p< .05). Controlling for other variables, one log endostatin unit was associated with a total MoCA score 5.08 (SE= 2.52) points lower.ConclusionIn this sample, lower serum endostatin concentrations were associated with higher cognitive performance. This relationship may support the involvement of endostatin in cognitive functions and neurodegenerative diseases.
Associations between cognitive function and endogenous levels of estradiol and testosterone in adults with Type 2 diabetes?
Authors: Robusto Brian Andres , Espeland Mark A. , Bahnson Judy , Bennett Wendy , Cook Delilah R. , Hayden Kathleen M. , Howard Marjorie , Hugenschmidt Christina E , Johnson Karen C , Luchsinger Jose A , Yasar Sevil , Yassine Hussein N. 
Published: December 2022

AbstractBackgroundType 2 diabetes mellitus (T2D) accelerates cognitive decline in women and men. Among older women, prior reports suggest that higher endogenous estradiol levels may further accelerate the cognitive decline associated with T2D and increase risks for cognitive impairment. Testosterone may interact directly with cognitive decline in T2D, or through its conversion to estradiol via the aromatase enzyme.MethodsEstradiol (E2) and total testosterone (TT) concentrations were determined using stored serum from 996 individuals, mean (±SD) age 69±6 and not receiving hormone therapies, collected at two times (averaging 4 years apart). Serum was collected during follow‐up years 8‐18 of the Look AHEAD cohort, a randomized controlled clinical trial of a 10‐year behavioral weight loss intervention in individuals with T2D and overweight or obesity at trial enrollment. One to four standardized assessments of attention, executive function, memory, and verbal fluency were collected during follow‐up years 8‐18. Mixed effects models were used to assess associations that E2 and TT concentrations had with current body mass index (BMI) and cognitive function.ResultsGreater current BMI was associated with higher E2 concentrations in women and men, and greater TT concentrations in women, but lower TT concentrations in men (all p<0.001). The weight loss intervention did not leave a legacy of differences in E2 and TT concentrations. E2 concentrations were not associated with cognitive function in women or men. TT concentrations were not associated with cognitive function in women, but greater TT concentrations were associated with better verbal fluency in men (p<0.001), most strongly among those carrying the APOE‐e4 allele (interaction p = 0.02). While the weight loss intervention left a legacy of relatively lower cognitive functioning among women, this was not mediated by current concentrations of E2 and TT.ConclusionsContrary to prior reports, we found no evidence that higher endogenous E2 concentrations were related to worse cognitive functioning in women with T2D. Higher TT concentrations were associated with better verbal fluency in men, but not women. The legacy of modestly lower cognitive function in women left by a 10‐year weight loss intervention was unrelated to any long‐term alterations in E2 or TT concentrations.
Are infections the missing elements in predicting Alzheimer’s disease?
Authors: Rheault Sylvie , Belleville Sylvie , Duchesne Simon 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) begins many years before its clinical expression. Therefore, an important goal is accurate long‐term prediction, especially for prevention trials and when evaluating the impacts of early intervention. Yet, current efforts still fall short, which is indicative of missing information in the modelling. Recently, the Epstein‐Barr virus has been shown to trigger the development of multiple sclerosis, years after infection. Similarly, some studies have reported odds ratios for AD that were almost as high as age for some chronic infections, such as those caused by either the herpes simplex virus or cytomegalovirus. We aim to review the literature on prediction models to examine whether infection load has been sufficiently studied as an early biomarker of AD.MethodWe used the same strategy employed in previous reviews by Stephen et al. (2010), Tang et al. (2015), and Hou et al. (2018) to perform a systematic review of the literature published between January 2018 to May 2021 for the prediction of AD in cognitively intact individuals from the general population. We examined the type of model and input data as well as the performance of the prediction models in the selected articles with a particular focus on infection load.ResultOur initial search yielded 18,915 articles. Artificial intelligence was found to be the most widely used technique for prediction model computation. Most models included chronological age, and long‐term prediction accuracy was mainly determined by this parameter. Of note, models with a measure of amyloid beta misfolding were highly predictive of the progression to AD. Only one model included data exploring the contribution of infection.ConclusionLong‐term prediction models for AD in the general population of cognitively intact older adults were mostly driven by age. Despite the growing literature associating specific infectious agents with the pathophysiological development of AD, only one model used infection load as a parameter to predict AD. The potential of serological infection status as a parameter to improve prediction models in the general population must therefore be further explored.
Differential roles of ApoE isoforms in regulation of inflammatory cytokine expression
Authors: Arsenault Ryan , Li Qiao , Zhang Wandong 
Published: December 2022

AbstractBackgroundApoE Ɛ4 has long been known as a top genetic risk factor in the development of late‐onset Alzheimer’s disease (LOAD). More recently the genetic variants of the innate immune receptor TREM2 such as R47H, which confers a similar risk as ApoE4 in LOAD, have been identified as genetic risk factors in the development of many neurodegenerative diseases with dysregulated neuroinflammation. TREM2 is expressed highly on microglia and macrophages and plays key roles in inflammation regulation. Our previous study (Dorey et al. 2017) has shown that ApoE isoforms play differential roles in Aβ‐induced inflammatory response. Atagi et al (2015) identified that ApoE is a ligand for TREM2. Given the physiological relationship between ApoE and TREM2 while also considering the three isoforms of ApoE, it is crucial to investigate and understand the mechanisms underlying the possibility differential ApoE isoform signaling through TREM2 surface receptor.MethodTHP‐1 (human monocytic leukemia cell line) cells were differentiated into macrophages (M0) using PMA and subsequently polarized to M1 and M2 using IFN‐γ/LPS and IL‐4/IL‐13, respectively. Following differentiation, 3uM of ApoE2, E3, or E4 was added to polarization media. RNA was extracted following 2 day polarization and used for RT‐qPCR in relative gene expression quantification.ResultApoE2 strongly stimulated the expression of anti‐inflammatory cytokines IL‐10 and TARC/CCL17 in M1 and M2 macrophages as compared to control, ApoE3 and ApoE4. While ApoE4 showed a massive reduction in these same transcripts in M0 and M2 macrophages. In contrast, ApoE4 strongly promoted the expression of pro‐inflammatory cytokines IL‐1β and TNF‐α in M0, M1, and M2 macrophages as compared to control, ApoE3 and ApoE2.ConclusionThe ability for ApoE2 to promote the expression of anti‐inflammatory cytokines in macrophages, suggests that ApoE2 may play a neuroprotective role; while ApoE4’s ability to promote inflammatory cytokine expression indicates its pro‐inflammatory role. Both ApoE2 and ApoE4 may play their roles via interacting with TREM2.
A global functional network biomarker across aging and dysexecutive Alzheimer’s disease
Authors: Corriveau‐Lecavalier Nick , Gunter Jeffrey L. , Kamykowski Michael G. , Radford Jonathan Graff , Botha Hugo , Wiepert Daniela A , Schwarz Christopher G. , Yacoub Essa , Knopman David S. , Boeve Bradley F. , Ugurbil Kamil , Petersen Ronald C. , Jack Clifford R. , Terpstra Melissa , Jones David T. 
Published: December 2022

AbstractBackgroundDisruption of the default mode network (DMN) is thought to be a common feature of aging and across Alzheimer’s disease (AD) clinical phenotypes, while syndromic variability could be reflected in selective degeneration of macro‐scale networks optimally supporting specific mental abilities (Fig 1). As part of a collaborative effort between Mayo Clinic and the Human Connectome Project‐Aging (HCP‐A), we aimed to delineate a biomarker of global network failure across aging and the dysexecutive (dAD) and amnestic phenotypes of AD, and biomarkers of focal degeneration specific to each AD phenotype.MethodWe used a regression framework to assess the relationships between a marker of DMN dysfunction, the network failure quotient (NFQ), and factors relevant to AD such as age, cortical thickness (global cortical thickness, inferior parietal lobe), hippocampal volume, and cognition (episodic memory, cognitive flexibility) in the HCP‐A cohort, which consists of 725 non‐demented older adults. We then fit centile curves to the HCP‐A cohort to assess whether the NFQ and focal degeneration markers could distinguish dAD (n=10) and amnestic AD (n=8) patients from the HCP‐A cohort at the group‐ and individual‐level. Participants were scanned using the HCP‐A protocol, allowing for the acquisition of high‐resolution multi‐echo structural images and longer resting‐state connectivity acquisition time compared to traditional protocols.ResultThe NFQ related to age, cortical thickness, hippocampal volume, and cognition in the HCP‐A cohort. It also strongly discriminated dAD and amnestic AD from the HCP‐A cohort but did not discriminate between AD phenotypes. In contrast, markers of focal degeneration were phenotype‐specific; parieto‐frontal areas yielded largest effect sizes for dAD patients, and hippocampal and temporal areas best discriminated patients with amnestic AD (Fig 2).ConclusionThe NFQ may reflect shared system‐level pathophysiological mechanisms across aging and the dysexecutive and amnestic phenotypes of AD whereas focal degeneration markers highlight distinct pathognomonic processes across AD phenotypes. These findings suggest that inter‐individual variability in cognitive impairment in AD would be closely tied to modular, phenotype‐specific network degeneration combined with a common global functional disruption of the DMN. Such information has crucial implications for clinical biomarkers and to provide a deeper understanding of heterogeneity in AD.
Pulse pressure trajectories predict brain microstructure in an APOE‐dependent manner among cognitively normal older adults
Authors: Parada Humberto , Bergstrom Jaclyn , Reas Emilie T. 
Published: December 2022

AbstractBackgroundArterial stiffness is associated with increased risk of cognitive decline and dementia in older adults; however, the mechanisms by which arterial stiffness impacts brain health remain unclear. We examined whether trajectories of pulse pressure (PP), a surrogate marker of arterial stiffness, beginning in midlife predicted brain microstructure at older age, using the multicompartment diffusion MRI technique restriction spectrum imaging (RSI). We assessed whether effects of PP on executive function were mediated by brain microstructure, and whether APOE genotype modified associations between PP and microstructure.MethodWe included 146 cognitively normal adults (mean age=76.6, SD=6.8 years) who underwent RSI and cognitive testing in 2014‐2016 and measurements of PP up to eight times before MRI, from 1984‐2016. Participants were classified according to PP trajectory using latent class growth modeling. Restricted isotropic diffusion (RI), neurite density, isotropic free water (IFW), and hindered isotropic diffusion (HI) were computed in five subcortical regions and 15 white matter tracts. Multiple linear regression examined associations between PP trajectories and microstructure, and between microstructure and Trails B performance. Mediation analyses, adjusted for covariates, evaluated whether microstructure mediated effects of PP trajectories on executive function. Age‐and‐sex‐adjusted partial correlations tested associations between continuous PP and RSI metrics by APOE genotype (ε4 carriers versus non‐carriers).ResultParticipants with high PP trajectories (n=50) had lower RI and higher HI and IFW in multiple subcortical regions and fiber tracts compared to those with low PP trajectories (n=96), and of these, eight were also associated with Trails B performance. Associations between high PP trajectories and worse executive function were mediated by lower RI in the amygdala (βa*βb=4.13, 95%CI=0.91‐11.01) and in several fiber tracts including the parachippocampal cingulum (βa*βb=3.77, 95%CI=0.95‐9.93) and fornix (βa*βb=3.71, 95%CI=0.59‐10.19). High PP more strongly correlated with lower RI in the hippocampus, uncinate fasciculus, and inferior fronto‐occipital fasciculus (IFO); with high IFW in the IFO and superior corticostriatal fasciculus, and with high amygdala HI, among APOE4 ε4 carriers than non‐carriers (Figure).ConclusionProlonged elevated PP predicts subcortical and white mater microstructural abnormalities, particularly for those at greater risk for dementia, and may contribute to impaired executive function via microstructural injury.
Reproductive health data and its relationship to baseline brain imaging and cognitive measurements in cognitively unimpaired female PSEN1 E280A mutation carriers and non‐carriers from the API ADAD Trial
Authors: Ghisays Valentina , Vila‐Castelar Clara , Giraldo‐Chica Margarita , Acosta‐Baena Natalia , Protas Hillary D. , Malek‐Ahmadi Michael H. , Chen Yinghua , Luo Ji , Lee Wendy , Bocanegra Yamile , Muñoz Claudia , Herrera Karina , Hu Nan , Sink Kaycee M. , Clayton David , Alvarez Sergio , Langbaum Jessica B. , Chen Kewei , Su Yi , Tariot Pierre N. , Quiroz Yakeel T. , Lopera Francisco , Reiman Eric M. , Ríos‐Romenets Silvia , Group API ADAD Colombia Trial 
Published: December 2022

AbstractBackgroundThe impact of sex steroid hormones on Alzheimer’s disease (AD) remains to be further clarified. Research suggests that shorter reproductive span, late menarcheal age, early menopause, oophorectomies and hysterectomies, are associated with increased dementia risk. We examined reproductive health and its associations with brain imaging and cognitive measurements in unimpaired female Presenilin 1 (PSEN1) E280A mutation carriers and non‐carriers from the Alzheimer’s Prevention Initiative Autosomal Dominant AD (API ADAD) Trial (NCT01998841).MethodA total of 151 cognitively unimpaired 30‐53 year‐old females (101 PSEN1 mutation carriers and 50 non‐carriers) were included. Reproductive health data (i.e., menarcheal age, number of pregnancies, deliveries, miscarriages, and living children) from all participants were examined, as well as the extent to which menarcheal age was related to age‐adjusted baseline 1) cortical amyloid plaque burden (florbetapir PET), 2) Precuneus cerebral glucose metabolism (fluorodeoxyglucose PET), 3) hippocampal volume (3TMRI), and 4) the API ADAD preclinical cognitive composite score, which includes the MMSE Orientation score, CERAD Word List Delayed Recall and Constructional Praxis, Multilingual Naming Test and Raven’s Progressive Matrices subset. We examined associations with the cognitive and brain imaging measures corrected for multiple comparisons (Bonferroni).ResultCarrier and non‐carrier females did not differ on number of pregnancies, deliveries, miscarriages, or living children. Female carriers had a significantly younger menarcheal age than non‐carriers (12.8 ±1.5 versus 13.7±1.6 years, p = 0.007, Bonferroni). Among carrier females, older menarcheal age was associated with lower scores on the Raven’s test (Bonferroni: r = ‒0.28,p =0.035). Menarcheal age was not associated with scores on the cognitive composite or other individual subtests, or with brain imaging measures.ConclusionOur findings suggest reproductive health data did not differ between carrier and non‐carrier females, except for a slightly younger menarcheal age compared to non‐carriers, and that menarcheal age may have a very limited impact on brain pathology and function at preclinical stages of ADAD. Longitudinal studies with larger samples are needed to clarify the extent to which earlier menarcheal age may be related to changes in cognitive function in mutation carrier females transitioning from preclinical to clinical stages.
Prediction of Aβ State from Brain Amyloid PET Images Using Machine Learning Algorithm
Authors: Simfukwe Chanda , Youn Young Chul 
Published: December 2022

AbstractBackgroundAnalyzing brain amyloid positron emission tomography (PET) images to access the occurrence of β‐Amyloid (Aβ) deposition in Alzheimer’s patients requires a lot of time and effort from physicians and also the variation of each interpreter may differ. For this reason, a machine learning model was developed using a convolutional neural network (CNN) as an objective decision to predict the Aβ‐positive and Aβ‐negative status from brain amyloid PET images.MethodA total of 154 cognitively impaired subjects were used in this study. The 18F‐florbetaben (18F‐FBB) PET was administered on all participants and the criteria for differentiating Aβ‐positive and Aβ‐negative state was based on brain amyloid plaque load score (BAPL) that depended on the visual assessment of PET images by the physicians. We applied the CNN algorithm trained in batches of 52 augmented 18F‐FBB PET images per subject from two classes: Aβ‐positive and Aβ‐negative states that were determined based on the BAPL scores.ResultThe binary prediction of the model average performance matrices was evaluated after 40 epochs of 5 trial‐based on test datasets. The model accuracy for predicting Aβ‐positivity and Aβ‐negativity was 82.00±0.03 in the test dataset. The sensitivity and specificity were 97.00±0.02 and 97.00±0.02 with an area under the curve (AUC) of 90.00±0.03.ConclusionBased on this study, the designed CNN model has the potential to be used clinically for screening amyloid PET images.