bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting biological brain age using deep learning methods
Authors: Dartora Caroline , Marseglia Anna , Mårtensson Gustav , Muehlboeck J‐Sebastian , Kern Silke , Zettergren Anna , Schiöth Helgi , Ferreira Daniel , Skoog Ingmar , Westman Eric 
Published: June 2023

AbstractBackgroundThe interplay of genetic and environmental factors can trigger a cascade of neuropathological changes leading to individual differences in brain aging. The apparent age of the brain (brain age) can differ from chronological age, potentially reflecting different resilience mechanisms. Brain age has also the potential as biomarker to predict future cognitive impairments and dementia. In this study, we developed a biological measure of brain age, based on the differences between predicted brain age (PBA) and chronological age (CA) using deep learning model (DLM).MethodThe sample included 16734 T1‐w MRI from multiple time‐points of 15115 healthy individuals, aged 32‐96 yrs., from: 1) ADNI (n = 1489); 2) AIBL (n = 957); GENIC (n = 406); 4) UK Biobank (n = 13882). Healthy status was defined as absence of dementia/cognitive impairment, neuro‐psychiatric disorders, and/or self‐report of good health. Medical diagnoses were collected through physician‐/self‐reports or medical records following the International Classification of Diseases. A DLM based on convolutional neural networks was trained to develop an algorithm to predict brain age from raw MRI images registered to the MNI space using training (90%) and hold‐out test (10%) sets. To assess the model generalizability, we applied the algorithm in the Gothenburg H70‐Birth Cohort 1944 (n = 792 septuagenarians).ResultThe hold‐out method achieved a mean absolute error (MAE) error, between PBA and CA, of 3.04 yrs. In the H70 cohort the mean PBA was 73.9±1.49 [64.7‐86.1] years.ConclusionThe model shows accurate predictions, comparable with those from previous studies using other computation methods. As next steps, we will evaluate hyperparameter optimization and implementation of a cross‐validation methodology. We also seek to include further cohorts of healthy individuals with heterogeneous age‐span to increase the model reliability and generalizability. This will enable to address e.g., differences between normal and pathological aging as well as exploring resilience mechanisms.
Evolution of circulating metabolites through lifespan according to gender and APOE
Authors: Bonnechère Bruno , Liu Jun , Amin Najaf , Kaddurah‐Daouk Rima F. , Van Duijn Cornelia M 
Published: June 2023

AbstractBackgroundThere is increasing interest in blood‐based metabolic biomarkers for Alzheimer’s disease (AD). Studies show consistently that at branched chain amino acids (BCAAs) and a large scale of lipids are changed in patients with AD. Little is known of how these metabolites associate to age, genes and apolipoprotein E (APOE). This study aims to study these metabolites over the lifespan and determine the influence of age, sex and APOE.MethodWe conducted this study in UK Biobank, a large prospective cohort of 459,227 subjects with extensive genotypic and phenotypic data. Using the Nightingale nuclear magnetic resonance technology, 249 metabolites (165 directly measured metabolites and 84 derived measures) have been determined in the blood of 118,071 participants. We used mixed‐effect models to study the effect of age, sex and APOE on metabolite levels and adjust for lifestyle factors and medication.ResultsAPOE*4 is the major determinant of total of 216 metabolic of the Nightingale platform using a FDR < 0.05. We find that 41 were also associated to dementia in the population 60+ years old. Also, APOE*2 is associated with 226 metabolites (FDR<0.05) including 41 dementia associated metabolites. Concerning gender differences, significant differences were found for the metabolites at the FDR 0.05. Overall, we find a significant interaction between age^2 and APOE*4 for valine and BCAA. When stratifying for gender, for most of the metabolites concentrations in blood remain stable over age in men. For amino acids, we observed a decreased concentration level with age in me. For females, we find that the metabolite levels increase over age, reaching a plateau around 55 years old.ConclusionThis study shows that AD associated metabolite levels in blood are determined by sex and APOE. In women, the levels of metabolites in women are also associated to age up until menopause.
AD‐Associated Variants Directly Impair Surface Interactions Between the Hydrophobic Site of TREM2 and the Hinge Region of ApoE
Authors: Dean Hunter B , Greer Rory A , Kober Daniel L , Roberson Erik D , Brett Thomas J , Song Yuhua 
Published: June 2023

AbstractBackgroundTriggering Receptor Expressed on Myeloid Cells 2 (TREM2) and Apolipoprotein E (ApoE) are two of the strongest genetic risk factors for late‐onset Alzheimer’s disease (AD), but while their interplay in the microglial response to AD pathology is hotly studied, surprisingly little is known about the mechanism by which their variants impair this role.MethodTo define the structural mechanism by which AD‐associated variants impair the TREM2‐ApoE interaction, we used sequence‐based in silico methods to predict the binding site between TREM2 and ApoE, validated the predicted binding site with biolayer interferometry (BLI), then constructed initial models of TREM2‐ApoE complex structures using the identified binding site between TREM2 and APOE as restraints for unbiased molecular docking methods. The top four initial models were re‐ranked by comparing the effect of key residue mutations in the TREM2‐ApoE complex on binding affinities calculated from molecular dynamics‐molecular mechanics Poisson‐Boltzmann surface area (MD/MM‐PBSA) binding free energy analyses with binding affinities measured by BLI. The final validated TREM2‐ApoE complex structure model provides for further investigating the molecular and structural effects of AD‐associated TREM2 variants on interactions between hydrophobic site of TREM2 and hinge region of ApoE.ResultOur iterative MD/MM‐PBSA–BLI procedure generated an all‐atom model of the TREM2‐ApoE complex that replicates the binding effects of both engineered mutations in TREM2 and AD‐associated variants in both TREM2 and ApoE. The validated model shows the interaction centered on the apical hydrophobic site of TREM2 and the hinge region of ApoE. The interaction sites in the TREM2‐ApoE complex model are consistent with regions affected by AD‐associated variants in simulations of the individual proteins, with biophysical studies using truncated constructs of the two proteins, and with a recently reported minimal active peptide of TREM2 that is sufficient to stimulate its cytoprotective and cytokine regulating roles in primary microglia.ConclusionIterative molecular modeling and biophysical binding affinity assays show the hydrophobic site of TREM2 binding the hinge region of ApoE, an interaction which is impaired by AD‐associated variants and which can be targeted to generate novel therapeutics for AD.
Executive functions as early cognitive markers and predictors of people with high risk to develop Alzheimer’s Clinical Syndrome
Authors: Guinea Sara Fernández , Fernández Almudena Junquera , Olazarán Javier , Marqués Javier González , Parra‐Rodriguez Mario A 
Published: June 2023

AbstractBackgroundRecent research has pointed to impaired executive functions (EF) as a potential early predictor of progression from Mild Cognitive Impairment (MCI) to dementia in the Alzheimer’s clinical syndrome (ACS) (Junquera et al, 2020). In this study, we investigated the EF tests that hold the best sensitivity and specificity to discriminate, using baseline data, between cognitively unimpaired older adults and MCI patients who converted to ACS or remained stable after two years (aim 1). We then explored which EF components can best predict conversion from MCI to ACS in a two‐year follow‐up (aim 2).MethodWe assessed 210 participants, 71 cognitively unimpaired older adults (CU) and 130 MCI patients. Eight tests assessing EF (Similarities, Arithmetic, Reverse Digits, and Letters and Numbers, Trail‐Making Test, Stroop Test, Verbal Fluency – phonemic and categories, and Zoo Map) were administered at baseline and at 2‐year follow‐up, together with cognitive screening tools and IADL measures. ROC analysis was used to address aim 1. A binary regression model was then used to examine the EF components and tests identified via aim 1 that reliably predict progression from MCI to ACS (aim 2).ResultBaseline scores from the TMT and semantic categories' fluency were significantly lower in MCI patients who later progressed to ACS (p<.001) than those who remained stable. ROC analysis showed that the TMT and semantic category fluency test were the best tests to differentiate at baseline between MCI converter and non‐converter (AUC = 0.768 and 0.77, respectively), CU and MCI converter (AUC = 0.864 and 0.876, respectively), and between CU and MCI no converter (AUC = 0.602 and 0.673, respectively). Binary logistic regression results revealed that indeed, the TMT and semantic categories fluency test significantly predicted the conversion from MCI to ACS (p<.05).ConclusionSwitching abilities and verbal fluency (categories) were the executive function that best predicts MCI to ACS conversion in two years. TMT and semantic verbal fluency clearly identify people with high risk to develop ACS in two years. It is recommended to include these tests in the prodromal Alzheimer’s disease characterization.
Application of advanced language technologies in analysis of category naming fluency task in healthy participants
Authors: Gonzalez‐Recober Carmen , Cho Sunghye , Liberman Mark Y , Grossman Murray , Nevler Naomi 
Published: June 2023

AbstractBackgroundCategory naming fluency tasks have been used frequently to measure patients’ working memory and executive functions. Previous studies show that differences in scores in this task could reflect features of neurodegenerative disease. To better understand decreased performance in patients, it is critical to establish performance in healthy aging populations. Here, we investigated differences in total scores and lexical/speech features of words produced during animal fluency tasks of healthy young and older speakers which can only be derived with novel, automated, computational technologies.MethodData were collected in 52 young participants (26.9% males, mean age = 23.5±3.17) and 46 elderly participants (63.0% males, mean age = 69.9±6.77). Participants were instructed to list as many animals as possible for 60 seconds. Speech was transcribed and automatically force‐aligned. Transcripts were run through our automated Python pipeline to calculate the total number of animals listed and rate each word for the following semantic parameters: age of acquisition (AoA), ambiguity, familiarity, frequency. We also calculated phonetic and semantic distances between each word and its antecedent. Linear regression models tested the association between these automated language measures and total scores. We also examined the differences of the young and elderly groups using t‐tests.ResultElderly participants produced significantly fewer animals than young participants (p<0.001). Higher overall scores were associated with higher mean AoA (beta = 0.22, p = 0.049) and longer word duration (beta = 1.62, p = 0.037), as well as less frequent (beta = ‐0.51, p = 0.021) and familiar (beta = ‐3.96, p<0.001) animal names. We found no interaction with the age groups in any of the models. Elderly participants produced less frequent animal names than young participants (p = 0.029), along with significantly reduced phonetic distance scores (p = 0.008). Elderly participants scored significantly higher articulation rates (p = 0.007) and had a faster speech rate (p<0.001), attributable to producing more non‐animal words.ConclusionThis study demonstrates the applicability of advanced language technologies in analyzing category naming fluency tasks in healthy adults. We developed an automated scoring system and identify novel semantic and phonetic measures from digitally recorded fluency tasks. We also quantified some confounding age effects which could be explained by lexical/speech differences of words produced by the groups.
Indigenous inclusion in the Canadian therapeutic platform trial for multidomain interventions to prevent dementia
Authors: Furlano Joyla , Walker Jennifer D 
Published: June 2023

AbstractBackgroundThe Canadian Therapeutic Platform Trial for Multidomain Interventions to Prevent Dementia (CTU) is Canada’s largest national dementia research initiative, evaluating the effectiveness of a web‐based multimodal program in reducing dementia risk among older adults. To date, CTU has not included Indigenous perspectives, culture, or context in the development of the intervention or study design, and therefore does not reflect the priorities and needs of Indigenous communities.MethodIn consultation with Indigenous community partners, a content analysis of CTU methodologies is currently underway to identify areas for improved cultural relevancy within the program’s modules.ResultBased on findings from the content analysis, an Indigenous adaptation of the program will be developed and piloted in Indigenous communities in Canada. General suggestions on how to improve CTU from a cultural perspective will also be provided to inform future CTU trials.ConclusionThis community‐driven research will help shape current and future dementia prevention trials and ensure cultural relevancy in the development of community‐based preventative strategies. Further, it will help ensure that culturally safe and trauma‐informed dementia prevention tools are available to Indigenous peoples in Canada.
Associations between distinct trajectories of body mass index (BMI) over 15 years preceding dementia and incidence of dementia
Authors: Ren Dianxu , Lopez Oscar L. , Lingler Jennifer H , Conley Yvette 
Published: June 2023

AbstractBackgroundBMI has been reported to associate with dementia, with both increased and decreased risks. The purpose of this study was to examine longitudinal distinct trajectories of BMI over 15 years preceding dementia with incident dementia using the large national dataset from National Alzheimer’s Coordinating Center (NACC).MethodWe used NACC dataset from 2005 to December 2020 and performed a nested case‐control study (up to 1 to 4 match). The sample included 699 cases of all‐causes dementia with at least 5–years follow‐up time preceding dementia diagnosis, and 2120 non‐dementia controls matched on age, sex, race, education and baseline cognitive status. A group‐based trajectory model was applied to identify longitudinal distinct trajectory groups of BMI among this sample. Conditional logistic regression model was used to evaluate the effect of distinct trajectories of BMI, APOE genotype and the interaction between them with incident dementia.ResultFor the case group (n = 699), mean age at enrollment was 75.5 years and average education in years was 16.1, participants were more female (58.8%), non‐Hispanic white (86.8%) and healthy cognitive status at initial visit (64%). A three‐group linear trajectory model best fit BMI trajectory before the onset of dementia that featured a normal weight‐decreasing BMI group (45.5%), overweight‐decreasing BMI group (43.6%) and obese‐decreasing BMI group (10.9%). There is statistically significant linear decreasing trend over 15 years for each trajectory group (P<0.0001). The average BMI at 15 years preceding dementia for each trajectory group was 22.7, 29.9 and 36.7 respectively. Conditional logistic regression model revealed significant interaction between BMI trajectory group and APOE genotype. Comparing to obese‐decreasing and ε4 non‐carriers, the ε4 carriers in either overweight‐decreasing group or obese‐decreasing group were more likely to develop dementia [OR = 1.53, 95% CI (1.00‐2.34), P = 0.05; OR = 1.88, 95% CI (1.06‐3.34), P = 0.03]. Especially, the ε4 carriers within normal weight‐decreasing BMI group had triple the likelihood of dementia ([OR = 3.25, 95% CI (2.13‐4.94), P<0.0001].ConclusionOur findings suggest the existence of distinct developmental trajectories of BMI preceding incident dementia and the possible effect of gene‐environment interaction on dementia. The ε4 carriers within normal weight‐decreasing BMI trajectory group exhibited the highest risk of dementia.
Elevated levels of mosaic aneuploidy in brain cells and fibroblast cell lines from human Huntington’s disease donors and in brain cells from Huntington’s disease mouse models
Authors: Elos Mihret , Caneus Julbert , Ahmed Md. Mahiuddin , Grissom Paula M. , Markham Neil , Johnson Noah R , Chial Heidi J , Potter Huntington 
Published: June 2023

AbstractBackgroundHuntington’s disease (HD) is a progressive neurodegenerative disorder that presents with motor and cognitive deficits and psychiatric disturbances. HD is associated with autosomal dominant inheritance of a CAG trinucleotide repeat expansion mutation in the huntingtin (HTT) gene. The huntingtin protein localizes to spindle poles and is required for proper mitotic spindle orientation, chromosome segregation, and cell cycle regulation. The mature mutant huntingtin protein has an expanded polyglutamine region (>35 repeats) near its N terminus, which leads to neuronal dysfunction and death. Mouse models of HD exhibit defects in microtubule function and cell cycle regulation. Studies from our laboratory and others have shown elevated levels of aneuploidy in many neurodegenerative disorders characterized by cognitive deficits, including Alzheimer’s disease and frontotemporal lobar degeneration. Here, we investigated whether chromosome segregation defects that lead to mosaic aneuploidy and consequent apoptosis may also contribute to neuronal loss in HD.MethodsSingle‐cell suspensions from cortex and cerebellum from human HD donors were analyzed using FISH for chromosome 21, NeuN immunostaining, and/or TUNEL staining. Fibroblast cell lines from human HD donors were also analyzed using FISH. Single‐cell suspensions from cortex and cerebellum from HD mouse models were analyzed using FISH for chromosomes 5 and 16. Cell cycle arrest, mitotic spindle defects, ploidy, and apoptosis profiles in the HD fibroblast cell lines are being analyzed by flow cytometry and immunofluorescence microscopy.ResultsIncreased levels of mosaic aneuploidy and apoptosis were observed in brain cells and in fibroblast cell lines from HD donors compared to age‐matched healthy control donors. Increased levels of mosaic aneuploidy were also observed in brain cells from HD mice compared to age‐matched wild‐type control mice. Results of ongoing studies of cell cycle and mitotic defects will also be presented.ConclusionsTaken together with the results of our previous studies, these data provide evidence that chromosome segregation defects that lead to genomic instability may serve as a shared mechanism underlying many neurodegenerative disorders. Our findings highlight the need to further investigate the biological mechanism(s) that contribute to HD pathology and set the stage for novel therapeutic approaches to HD that may also be applied to other neurodegenerative disorders.
Higher plasma proinflammatory cytokines and reduced microglial TREM2 signaling in Late‐life Major Depression
Authors: Pomara Nunzio , Plaska Chelsea Reichert , Bruno Davide , Cejudo Jaime Ramos , Osorio Ricardo S , Pillai Anilkumar , Heslegrave Amanda , Zetterberg Henrik , Blennow Kaj 
Published: June 2023

AbstractBackgroundElevated circulating cytokines leading to microglia activation have been implicated in the increased risk for Alzheimer’s Disease (AD) in depression. However, correlations between peripheral and central inflammatory markers have been inconclusive. Additionally, only some depressives show evidence of increased inflammation.Microglia can assume anti‐inflammatory states via increased signaling of their TREM2 receptor with potential protective effects against AD including increased phagocytosis and NFkB inflammatory pathway inhibition. This process generates a soluble cleavage product, sTREM2, detected in CSF. Importantly in longitudinal human studies, higher CSF sTREM2 is associated with less brain amyloid deposition, less cognitive decline, and fewer degenerative changes.These considerations prompted us to determine if higher levels of plasma proinflammatory cytokines were associated with decreased TREM2 signaling in late‐life major depression (LLMD).MethodFifty‐one cognitively‐intact subjects aged 60 years and older, completed a 3‐year longitudinal study and an optional lumbar puncture (LP). Of these individuals, 49 were included in the analysis (29 LLMD and 20 controls). Independent‐samples Mann‐Whitney‐U Tests were used to compare groups. Non‐parametric correlations were run between CSF sTREM2 and plasma IL‐1B, Il‐6, Il‐8, TNFα, and CSF C3.ResultIn LLMD, higher plasma IL‐6 (r = ‐0.45, p = 0.02) and TNFα (r = ‐0.41, p = 0.30) were both associated with lower CSF sTREM2, but not with higher CSF C3 (p = 0.19) or other pro‐inflammatory markers consistent with a reduction in TREM2 signaling. These findings were not observed for controls.There were no group differences in Plasma IL‐1B, IL‐6, TNFα and CSF C3. Plasma IL8 was significantly higher in LLMD vs controls (p = 0.03). No correlations between plasma and CSF levels were observed for cytokines within the LLMD group.ConclusionHigher plasma pro‐inflammatory cytokines were associated with lower CSF sTREM2 in LLMD, consistent with a reduction in TREM2 signaling. Future studies should determine if lower CSF sTREM2 levels predict increased AD biomarkers, progressive decline and conversion to AD in LLMD.
Quadratic associations between subthreshold amyloid‐beta retention and cortical volume modulated by APOE genotype in cognitively normal older adults
Authors: Kang Dong Woo , Lim Hyun Kook , Lee Chang Uk 
Published: June 2023

AbstractBackgroundA growing body of evidence suggests a deteriorating effect of subthreshold amyloid‐beta (Aβ) accumulation before the onset of clinical symptoms of Alzheimer’s disease (AD). Despite the association between the Aβ‐dependent pathway and the APOE ε4 allele, the modulating impact of this allele on the associations between subthreshold Aβ retention, cortical atrophy, and neuropsychological performance is unclear. This study aimed to explore the differential effect of the APOE ε4 allele on the association between subthreshold Aβ retention, cortical volume, and cognitive performance in cognitively healthy older adults (CN).MethodA total of 112 CN with subthreshold Aβ retention, consisting of 80 APOE ε4 non‐carrier and 32 APOE ε4 carrier, were included in the study. Participants underwent structural magnetic resonance imaging, [18F] flutemetamol (FMM) PET‐CT, and neuropsychological battery. Potential interactions between APOE status and Aβ accumulation were assessed with F‐tests implemented on both linear and quadratic interaction terms, adjusting for age, sex, and education years.ResultWe found a significant interaction between APOE ε4 allele, subthreshold Aβ deposits, cognitive function for cortical volume of predefined brain regions vulnerable to early Aβ retention. In CN with APOE ε4 carrier, regional Aβ retention in frontal, parietal, temporal lobe, and posterior cingulate cortex/precuneus showed a U‐shaped relationship with cortical volumes of superior parietal, fusiform gyrus, and amygdala. Furthermore, cortical volumes of superior, inferior temporal lobe, and parahippocampal gyrus in APOE ε4 carrier displayed a U‐shaped relationship with attention and executive function scores.ConclusionThis study is the first attempt to thoroughly examine the mechanism at play in the earliest phase of Alzheimer’s disease, focusing on the influence of the APOE ε4 allele on the association between subthreshold Aβ retention and cortical volume during the preclinical phase.