bluuebunny/crossref_metadata_2025_split huggingface dataset:
Relationship between disturbed sleep and longitudinal changes in cerebral beta‐amyloid accumulation in cognitively normal elderly adults
Authors: Lee Min Ji , Keum Musung , Kim Jee Wook , Suh Guk‐Hee , Choe Young Min ,   Alzheimer’s Disease Neuroimaging Initiative
Published: January 2025

AbstractBackgroundIn our previous study, using cross‐sectional data, we noted that poor sleep quality during midlife increases pathological beta‐amyloid protein (Aβ) deposition. This study aimed to investigate the relationship of disturbed sleep and longitudinal changes in cerebral Aβ accumulation in elderly individuals with normal cognition.MethodThree‐hundred and two cognitively normal old adults from the Alzheimer’s Disease Neuroimaging Initiative received (18F)‐florbetapir positron emission tomography (PET) scans. Sleep disturbance and depression were measured using the baseline Neuropsychiatric Inventory (NPI) or NPI‐Questionnaire sleep and depression items. Multiple linear regression analysis was performed to examine the relationship between poor sleep and baseline Aβ deposition and rate of change in Aβ accumulation after adjusting for age, gender, education, and depression.ResultIn cognitively normal elderly individuals, poorer sleep was significantly associated with higher rates of Aβ accumulation after controlling for age, gender, education and depression. In contrast, we could not find any significant relationship between sleep disturbance and baseline Aβ deposition.ConclusionOur results suggest that disturbed sleep accelerates longitudinal Aβ accumulation in cognitively healthy old adults. On the other hand, the present results do not support the hypothesis of opposite direction that Aβ deposition influences sleep disturbance.
Initial solvent conditions impact the reproducibility and aggregation trajectory of monomeric Amyloid Aβ
Authors: Najarzadeh Zahra , Glabe Charles G 
Published: January 2025

AbstractBackgroundOur goal is to identify conditions to produce structurally homogeneous and reproducible preparations of different polymorphic structures. Here we investigate the effect of several widely used methods for solubilizing Abeta on the subsequent aggregation process.MethodAliquots of HPLC‐purified synthetic Aβ40 in originally lyophilized from acetonitrile/water (AcN) 50% v/v were dissolved in hexafluoroisopropanol (HFIP) 100%, AcN 50% v/v, NH4OH 2%, or 50 mM Phosphate buffer (PB), re‐aliquoted and lyophilized. These aliquots were dissolved in 2% NH4OH, HFIP, AcN 50%, DMSO or 50 mM NaOH to make a stock solution (4mM) or directly dissolved in PB to a final concentration of 50µM. Fibrillation kinetics assays were conducted in triplicate after dilution of the stock solutions 50 uM in PB and fibrillization monitored by thioflavin‐T (ThT).ResultWe observed large differences in the aggregation behavior of Aβ depending on initial solvent conditions, impacting lag phase, ThT kinetics, fluorescence end point, fibrilization rate, and overall reproducibility. Solubilization in 50 mM NaOH significantly enhances the reproducibility of fibrillation compared to other methods confirming previously published work. Initial solubilization HFIP and NH4OH for stock preparation yields less reproducible aggregation behavior. Dissolving peptide in NH4OH leads to a longer lag phase (almost 10 h longer) compared to using other solvents. Directly dissolving the peptide in PB demonstrates better reproducibility compared to preparing stock in solvents like HFIP, NH4OH, AcN50%, and DMSO. Additionally, we demonstrate that sonication and centrifugation of the stock before dilution contribute to achieving an aggregate‐free monomeric solution. Even after monomerization in 50 mM NaOH, prior treatment with other solvents results in reproducible differences in aggregation behavior, suggesting that the monomeric peptide may retain local structure imprinted by prior solvent exposure.ConclusionOur analysis indicates that solubilization with NaOH (50mM) offers a dependable method for solubilizing Aβ monomer. This results in monomeric and homogeneous peptide stock solutions, exhibiting exceptionally reproducible assembly kinetics when returned to near‐neutral pH. Prior solubilization and monomerization of Aβ in HFIP, DMSO, AcN and NH4OH results in variable kinetics and extent of fibrillation. Prior exposure to these other solvents produces reproducible differences in aggregation even after monomerization in NaOH.
DeepHoloBrain: From Geometric Deep Model to Computational Neuroscience
Authors: Dan Tingting , Wu Guorong 
Published: January 2025

AbstractBackgroundThe human brain is a complex inter‐wired system that emerges spontaneous functional fluctuations. In spite of tremendous success in the experimental neuroscience field, a system‐level understanding of how brain anatomy supports various neural activities remains elusive.MethodCapitalizing on the unprecedented amount of neuroimaging data, we present a physics‐informed deep model to uncover the coupling mechanism between brain structure and function through the lens of data geometry that is rooted in the widespread wiring topology of connections between distant brain regions. Since deciphering the puzzle of self‐organized patterns in functional fluctuations is the gateway to understanding the emergence of cognition and behavior, we devise a geometric deep model to uncover manifold mapping functions that characterize the intrinsic feature representations of evolving functional fluctuations on the Riemannian manifold. In lieu of learning unconstrained mapping functions, we introduce a set of graph‐harmonic scattering transforms to impose the brain‐wide geometry on top of manifold mapping functions, which allows us to cast the manifold‐based deep learning into a reminiscent of MLP‐Mixer architecture (in computer vision) for Riemannian manifold.ResultAs a proof‐of‐concept approach, we explore a neural‐manifold perspective to understand the relationship between (static) brain structure and (dynamic) function, challenging the prevailing notion in cognitive neuroscience by proposing that neural activities are essentially excited by brain‐wide oscillation waves living on the geometry of human connectomes, instead of being confined to focal areas.ConclusionIn practice, we evaluate the clinical value of our mixer model in (1) disease early diagnosis and (2) generality of adapting the pre‐trained model to a new dataset. Our extensive experimental results affirm the model’s effectiveness and practicality, marking a significant advancement in the field of neuroscience.
Serological inflammation markers and their association with cognition in the oldest old; The 90+ Study
Authors: Leiby Anne‐Marie C , Farahmand Ghasem , Ramanathan Aanan , Woodworth Davis C. , Jiang Luohua , Yu Jiaxin , Qian Tianchen , Corrada María M. M. , Kawas Claudia H. , Sajjadi S. Ahmad 
Published: January 2025

AbstractBackgroundRecent studies in the younger old have identified associations between cognitive performance and markers of inflammation, including interleukin‐6 (IL‐6) and erythrocyte sedimentation rate (ESR). These associations remain unexplored in the oldest old (age 90+), an age group most vulnerable to dementia. In addition, no studies have examined if amyloid burden impacts these associations. This study aims to: (1) examine the associations between inflammatory markers (IL‐6, ESR) and cognitive performance in individuals age 90+ and (2) to examine if amyloid burden impacts these associations.MethodParticipants with at least one plasma measure of inflammation and amyloid burden measured by positron emission tomography (PET) were selected from The 90+ Study (n = 112 for IL‐6, n = 123 for ESR). Cognitive measures included (1) global cognitive score defined as the average of the standardized scores of Mini‐Mental State Examination (MMSE) and Modified MMSE (3MS), and (2) memory score, that was the average of the standardized scores of California Verbal Learning Test (CVLT) and memory items of 3MS. PET amyloid burden was measured by standardized uptake value ratio (SUVR). We examined the associations between IL‐6 and ESR (independent variables) with cognitive measures (dependent variable) using linear regression models. Two models were implemented: first, without adjustment and second, with adjustment for amyloid. Both models were also adjusted for age at blood draw, sex, and education (college/no college). We additionally adjusted for amyloid burden and years between blood draw and PET scan in the second model.ResultMean age at blood draw was 94.7±2.8 and most participants were female (63.4%) and white (92.7%) (Table 1). In model 1, for both IL‐6 and ESR, higher levels were significantly associated with lower global cognitive scores (Table 2). Only IL‐6 was significantly associated with memory score (Table 2). Amyloid adjustment in model 2 had little effect on our results (Table 2).ConclusionThis study suggests that systemic inflammation could contribute to cognitive performance in individuals aged 90 and older. Additionally, this influence may be linked to a process not attributed to amyloid. Further research is warranted to explore the role of inflammation in non‐Alzheimer’s disease dementias.
Short tandem repeat expansions are a novel genetic risk factor for Alzheimer’s disease
Authors: Guo Michael H , Lee Wan‐Ping , Vardarajan Badri N , Schellenberg Gerard D. , Phillips‐Cremins Jennifer E 
Published: January 2025

AbstractBackgroundStudies of the genetics of Alzheimer’s disease (AD) have largely focused on single nucleotide variants and short insertions/deletions. However, much of the disease heritability has yet to be uncovered, suggesting that other forms of genetic variation promote substantial portions of genetic risk. Uncovering the genetic basis of AD can lead to new disease biomarkers and delineate disease mechanisms. As there are over one million short tandem repeats (STRs) in the genome and pathogenic expansions of STR cause over 30 neurologic diseases, it is important to ascertain whether STRs may also be implicated in AD risk.MethodHere, we utilize PCR‐free whole genome sequencing data from 2,981 individuals (1,489 AD case and 1,492 control individuals) to study the role of STRs in AD. We applied two cutting‐edge algorithms, ExpansionHunter and gangSTR, to genotype 321,742 STR tracts across the genome using the whole genome sequencing data. For each STR, we identified individuals carrying an expansion defined as having an STR tract length that is an outlier from the population. We then calculated the number of STR expansions in each individual and tested for differences in aggregate burden of STR expansions in AD case versus control individuals.ResultIndividuals with AD had a 1.19‐fold increase burden of STR expansions compared to controls (p = 8.27 × 10‐3, two‐sided Mann Whitney test). Individuals carrying > 30 STR expansions had 3.62‐fold higher odds of having AD and had more advanced spread of tau neuropathology as measured by Braak staging. AD STR expansions were highly enriched within gene regulatory elements active in the hippocampus.ConclusionThese results demonstrate that harboring a high burden of STR expansions in the genome increases risk of AD and that STR expansions may serve as a novel genomic biomarker of AD risk and neuropathologic progression. Our findings suggest that STRs may disrupt gene expression and underscore the pivotal role of genomic instability in the onset and progression of AD.
The Digital Clock and Recall is More Equitable and Less Biased than the Mini‐Mental State Examination in Terms of Ethnicity
Authors: Toro‐Serey Claudio , Jannati Ali , Banks Russell , Showalter John , Bates David , Tobyne Sean , Pascual‐Leone Alvaro 
Published: January 2025

AbstractBackgroundEarly detection of cognitive impairment is crucial for maximizing the benefits of disease‐modifying treatments for Alzheimer’s disease (AD). Brief, automatically‐scored digital cognitive assessments such as the Digital Clock and Recall (DCR) show promise in streamlining this early detection. However, wide adoption of such assessments in diverse populations requires evaluation of their demographic biases. Here, we compared the biases due to ethnicity, race, and education level between the DCR and the Mini‐Mental State Examination (MMSE).MethodWe studied 706 primarily English‐speaking participants from Bio‐Hermes‐001 study (age mean±SD = 71.5±6.7; 58.9% female; years of education mean±SD = 15.4±2.7; 85.1% White; 9.3% Hispanic), classified a priori as cognitively unimpaired (CU; n = 360), mild cognitive impairment (MCI; n = 234), or probable Alzheimer’s dementia (pAD; n = 111) based on expert consensus and neuropsychological evaluation. We also studied 770 participants in a prescreening study for AD‐related clinical trials (age mean±SD = 68.8±13.2; 64% female; education = 15±2.6; 78% White; 20% Hispanic) including CU (n = 338), MCI (n = 178), and pAD (N = 254). For each dataset, bias was compared by bootstrapping two multiple linear regressions predicting either Z‐scaled DCR or MMSE scores using race, ethnicity, sex, education, and age as predictors. The bootstrapped demographic coefficients (i.e. mean differences) were compared between tests and significance was determined via 95% confidence intervals on these differences.ResultA larger ethnicity bias was observed for the MMSE than for the DCR, which was significant in the Bio‐Hermes (bias difference = 0.44 larger for MMSE, 95% CI = 0.12–0.75) but not the pre‐screener study (bias difference = 0.20 larger for MMSE, 95% CI = ‐0.32–0.74). We found significant differences between Hispanic and non‐Hispanic individuals only for MMSE in both datasets (Mann‐Whitney test, p<0.01). Bias for race and education was not significantly different between tests.ConclusionUnlike the MMSE, the DCR is not influenced by ethnicity. Given the higher prevalence of cognitive impairment and greater risk of dementia in ethnic minorities (with Hispanics forming the largest minority group), the deployment of less biased assessments such as the DCR is important for more equitable cognitive screening.
Cognitive performance assessment in healthy older adults: Results from an 18‐month multicomponent cognitive stimulation randomized clinical trial
Authors: Silva Thais Bento Lima , Ordonez Tiago Nascimento , dos Santos Gabriela , Moreira Ana Paula Bagli , Costa Laydiane Alves , Perpétuo Bárbara , Lessa Patrícia Prata , Moraes Luiz Carlos , Cardoso Neide Pereira , Brucki Sonia Maria Dozzi , Yassuda Monica Sanches 
Published: January 2025

AbstractBackgroundThis study investigated the effects of cognitive stimulation on older adults over 18 months through a randomized clinical trial with 190 participants divided into Training Group (TG), Active Control Group (ACG), and Passive Control Group (PCG). Initial sociodemographic characterization (Table 1) ensured homogeneity among the groups. The clinical trial design aimed to assess the long‐term impacts of multicompartment cognitive stimulation on the cognitive function of older adults in the TG.MethodParticipants were randomly assigned to TG, ACG, or PCG, with an assessment of initial sociodemographic characteristics to ensure homogeneity. The analysis of cognitive performance (Table 2) and the development of the composite score (Table 3) were conducted. Using standardized z scores and specific formulas, the composite score incorporated assessments of memory, attention, executive functions, and logical reasoning, providing a comprehensive and balanced measure of cognitive function.ResultThe evaluation of cognitive performance (Table 2) using individual instruments did not identify significant variations between the groups. However, composite scores (Table 3) indicated notable improvements in overall cognition for the TG compared to the other groups. Repeated measures ANOVA revealed significant differences in the composite cognition score for TG participants over time (T0 versus T3).ConclusionThe results highlight the effectiveness of long‐term cognitive stimulation, especially in the TG, suggesting measurable benefits in the cognition of healthy older adults. This study contributes to the development of a composite score for analyzing cognition in healthy older adults, utilizing nationally and internationally validated instruments. Additionally, it provides insights into the effects of long‐term multicompartment cognitive stimulation, guiding future interventions to promote cognitive health in older adults.
Genetic correlation and causality assessment between Alzheimer’s disease and asthma
Authors: Bamidele Olasunkanmi David , Adewuyi Emmanuel O , Porter Tenielle , Armstrong Ayeisha Milligan , Verdile Giuseppe , Laws Simon M. ,   Neurological Conditions Group
Published: January 2025

AbstractBackgroundObservational studies have suggested a co‐occurring relationship between Alzheimer’s disease (AD) and asthma. However, the aetiology and biological mechanisms underlying AD and its potential association with asthma, an autoimmune condition, remain unclear.MethodWe examine the genetic relationship between AD and asthma by analysing large‐scale genome‐wide association study (GWAS) summary data from international research consortia and groups. We conducted a linkage disequilibrium score regression (LDSC) analysis to assess AD’s genome‐wide (global) genetic correlation with asthma. We also performed a two‐sample Mendelian randomization (MR) analysis to investigate the potential bi‐directional causal relationships between AD and asthma. We performed additional analyses for possible (partial) replication of our genetic correlation and causality findings on the side of both AD and asthma.ResultOur LDSC‐based genetic correlation estimates revealed a positive and significant global genetic correlation (rG) of AD with asthma (rG = 0.19, SE = 0.04, P = 5.57 × 10‐6). We used additional asthma GWAS data for replication testing, with consistent, significant results across all data. We observed a similar pattern of correlation estimate direction in our (partial) replication testing for AD (clinically diagnosed cases), although only one of the asthma GWAS data’s results was significant (likely due to a smaller sample size). Based on the inverse‐variance weighted (IVW) model, our MR analysis found no evidence for a significant causal association between AD and asthma. This MR result was consistent with AD or asthma as an exposure or outcome variable, respectively. Sensitivity testing using other MR approaches produced results similar to our IVW model, supporting no evidence of a causal association between AD and asthma.ConclusionOur study reveals a significant genetic correlation but non‐causal association between AD and asthma, implicating the presence of shared genetic mechanisms and biological pathways in both conditions.
Alzheimer’s disease‐associated gene ranking using PhenoGeneRanker
Authors: Rahman Most Tahmina , Saeed Fahad , Bozdag Serdar ,   Alzheimer’s Disease Neuroimaging Initiative
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is a neurogenerative disease that affect millions worldwide with no effective treatment. Several studies have been conducted to decipher to genomic underpinnings of AD. Due to its complex nature, many genes have been found to be associated with AD. Despite these findings, the pathophysiology of the disease is still elusive. In this study, we integrated multimodal gene and phenotype datasets of AD using network biology methods to prioritize potential AD‐related genes.MethodWe collected phenotypic and genotypic datasets of AD from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database and protein‐protein interaction (PPI) dataset from STRING database. We constructed a multiplex heterogeneous network composed of patient and gene similarity networks. We built three phenotypic network layers utilizing the patient’s demographic, cognitive and neuroimaging data, and two gene similarity network layers using gene expression and PPI data (Table 1). Starting from AD‐associated gene APP, we applied PhenoGeneRanker to traverse this network to discover potential AD‐associated genes. To assess the impact of each network layer and seed gene, we also run PhenoGeneRanker on different variants of the network and seed genes. We performed Gene Ontology (GO) enrichment to assess the results.ResultWe performed GO enrichment for the top 200 ranked genes. As a negative control, we repeated the same for the bottom 200 ranked genes. The top genes were enriched in terms such as amyloid precursor protein metabolic process, lipid metabolic process, and programmed cell death (Table 2), whereas bottom‐ranked genes had no GO enrichment. We also found some genes in the top 200 such as PSEN2, CLU, SORL1, PICALM, and APOE, which were identified as AD‐related genes in literature. Our top 2000 gene list captured over 50% of genes that were reported as AD‐associated (Figure 1). Ablation studies were performed to assess the impact of each network layer and seed genes. We observed that impact of PPI layer and APP seed gene were high.ConclusionWe identified candidate genes for AD that were enriched in disease‐related GO terms and captured previously reported genes, which suggest that other top‐ranked genes could be novel AD‐associated genes.
Methods and initial characteristics of aged participants in a randomized clinical trial on cognitive stimulation
Authors: Silva Thais Bento Lima , Ordonez Tiago Nascimento , dos Santos Gabriela , Moreira Ana Paula Bagli , Costa Laydiane Alves , Perpétuo Bárbara , Lessa Patrícia Prata , Moraes Luiz Carlos , Cardoso Neide Pereira , Brucki Sonia , Yassuda Monica Sanches 
Published: January 2025

AbstractBackgroundScientific investigations underscore the cognitive, psychological, and social benefits of cognitive stimulation for aged individuals, yet rigorous long‐term studies remain limited.MethodThis abstract outlines the methods and initial participant characteristics of a controlled, randomized clinical trial on cognitive stimulation. A total of 578 aged individuals responded to the study call, with 362 meeting eligibility criteria. Subsequently, 255 participants were selected and randomized into Training Group (TG), Active Control Group (ACG), and Passive Control Group (PCG). During the baseline phase (T0), 48 participants withdrew, resulting in a T0 sample of 207 participants.ResultThe three groups exhibited homogeneity in cognitive performance, sociodemographic, and psychosocial variables, with only depressive symptoms showing a significant difference, where TG scored higher. Despite this difference, other variables indicated equivalence among the research groups.ConclusionThe outlined methods serve as inspiration for future research on cognitive stimulation in the aged.