bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genomic Frontiers in Alzheimer’s Research: A Primer on the Alzheimer’s Disease Sequencing Project (ADSP) and its AI/ML Opportunities
Authors: Wang Li‐San , Leung Yuk Yee , Lee Wan‐Ping , Kuzma Amanda B , Valladares Otto , Bush William S. , Martin Eden R. , Naj Adam C. , Hohman Timothy J. , Schellenberg Gerard D. ,   Alzheimer’s Disease Sequencing Project
Published: January 2025

AbstractBackgroundIn this introductory talk, we embark on a journey of through the genomic frontiers of Alzheimer’s research via the revolutionary Alzheimer’s Disease Sequencing Project (ADSP).MethodADSP integrates together various components that collectively unravel the intricate genetic landscape of Alzheimer’s disease with the ultimate goal of advancing precision medicine for the millions affected globally by this devastating disease. With a goal of sequencing and analyzing up to 150,000 complete genomes and associated clinical and functional data in the next five years, ADSP has amassed an unprecedented wealth of genomic data from diverse populations, providing a comprehensive and holistic understanding of the genetic underpinnings of Alzheimer’s disease.ResultThis presentation serves as a primer, exploring various components of the ADSP and discuss the unprecedented opportunities it presents for Alzheimer’s disease and AI/ML researchers: (1) Diversity Initiative: The ADSP places a paramount emphasis on diversity, ensuring the inclusion of a wide range of populations in its genomic dataset. (2) Phenotype Harmonization: Harmonizing phenotypic data across diverse cohorts is a critical aspect of the ADSP, facilitating meaningful comparisons and analyses. (3) Functional Genomics: Moving beyond genetic variations, the ADSP incorporates functional genomics to discern the biological mechanisms at play. (4) AI/ML Opportunities: the focus of this session, we will start by illuminating the wide range of opportunities the ADSP offers to AI/ML researchers. From predictive modeling to identifying novel biomarkers and therapeutic targets, we will explore the vast landscape of possibilities for data‐driven discoveries that can shape the future of Alzheimer’s research and precision medicine.ConclusionAs we uncover the potential of AI/ML within the ADSP, we will emphasize the need for collaborative initiatives between AI/ML researchers and the broader Alzheimer’s research community. The synergy between these fields holds the key to unlocking breakthroughs that can translate genomic insights into tangible clinical advancements.
Examining pathology of Alzheimer’s disease via clusterin and Aβ interaction
Authors: Kim Danyeong , Shim Kyu Hwan , Gong Yunseo , Yang Hyewon , Kang Min Ju , An Seong Soo 
Published: January 2025

AbstractBackgroundClusterin, a multifunctional glycoprotein, is implicated in Alzheimer’s disease (AD) pathogenesis due to its roles in Aβ aggregation and clearance. Hence, understanding the specific interactions between Clusterin and Aβ would be a crucial for unraveling AD mechanisms and exploring therapeutic avenues. Previous study reported that clusterin bound with Aβ directly. This study investigated the specific fractions of clusterin interacting with Aβ in AD. Our focus extended to analyzing patient samples, offering clinical relevance. This comprehensive approach aimed to deepen insights into AD pathology for potential therapeutic and diagnostic applications.MethodClusterin was synthesized into 4 fragments (CLU #1, 2, 3, 4) and identified in Aβ fibrilization and oligomerization inhibition effects through thioflavin T (ThT) and Multiple detection system (MDS) assay. The fragments were conducted for Aβ inhibition effects through ThT and MDS assay. SH‐SY5Y cells were measured for Aβ protections of clusterin fragments. ELISA was assessed for clusterin and co‐interaction of clusterin‐Aβ in AD plasma samples.ResultOur results proved that clusterin inhibited Aβ fibrilization. Especially, clusterin #2 significantly decreased both Aβ fibrilization and oligomerization. The clusterin #3 also showed Aβ oligomerization inhibition effect, but less than the #2. The #2 and #3 increased cell viability after treatment of Aβ protofibrils. By extension to inhibit clusterin and Aβ from clinical samples, clusterin levels slightly decreased in AD plasma samples in comparison to healthy control. Next, co‐interactions of clusterin‐Aβ were decreased in AD samples.ConclusionThis study highlighted the inhibition effect of Aβ by clusterin through its close interactions. Especially, specific fragments (#2) of clusterin strongly decreased Aβ oligomerization, and recovered cell viability after Aβ protofibril treatment. This suggested that clusterin supported the direct interaction with Aβ, furthermore involving its removal. In clinical aspects, the decreased levels of clusterin in AD plasma were observed, along with reduced clusterin‐Aβ co‐interactions, which indicated the potential impairments in Aβ clearance mechanisms, contributing to AD pathology progression. The findings contributed to our understanding of the complex interplays between Clusterin and Aβ in AD, offering insights for therapeutic and diagnostic development.
Perseverations and switching during a semantic verbal fluency task
Authors: Dubey Neha , Basu Jayanti , Ghosh Amitabha 
Published: January 2025

AbstractBackgroundIt is believed that delayed perseveration on a semantic verbal fluency (SVF) test may occur due to impaired working memory (WM). However, the relation between perseveration and switching, and the self‐generated interference one has to overcome when switching back to a previously visited subcategory has not been explored. In this study we wanted to see: 1) if perseverative errors in SVF test require switching and subsequent switch back to a previously explored subcategory; (2) if this trend would parallel cognitive decline.MethodWe studied three groups, amnestic mild cognitive impairment (aMCI) (n = 30), Alzheimer’s disease (AD) (n = 30) and healthy controls (HC) (n = 60) based on their performance on an SVF task along with tests of executive function. Our primary analysis, focussed on the association of switching and switch back with the first perseverative error.ResultPerseveration was significantly associated with switch back for individuals with cognitive decline and healthy controls (χ2 = 24.88, p = .000359). Fewer switches and switchbacks were needed to trigger a perseveration as we moved along the continuum of cognitively healthy to cognitively impaired (HC>aMCI>AD). Finally, across all groups, perseverations were a result of more switchbacks (Wald chi‐square = 8.909, p = .003) rather than other factors.ConclusionThese findings suggest that it is switching and eventual switch back to a previous subcategory, and not the distance from the index word alone, that trigger perseverative errors in SVF tasks.
Anosognosia in Alzheimer's disease: the interplay between resting state Default Mode Network and Salience Network
Authors: Tondelli Manuela , Ballotta Daniela , Carbone Chiara , Maramotti Riccardo , Chiari Annalisa , Zamboni Giovanna 
Published: January 2025

AbstractBackgroundRecent evidence suggests that unawareness in Alzheimer’s disease (AD) continuum can be explained by a failure of the connections between brain regions involved in accessing and monitoring self and other information. It has been demonstrated that AD patients with anosognosia have reduced network connectivity in the default mode network (DMN); in addition, stronger connectivity of bilateral anterior cingulate cortex (ACC) was showed to be associated with anosognosia in prodromal AD suggesting a possible role of this region in mechanisms of “adaptation” to anosognosia early in the disease. Therefore, we hypothesized that anosognosia in AD could be associated with an imbalance between the activity of the DMN and the salience network (SN) detectable using resting state functional magnetic resonance imaging (fMRI).MethodsSixty patients with MCI and AD dementia underwent fMRI and neuropsychological assessment including the Anosognosia Questionnaire Dementia (AQ‐D), a measure of anosognosia based on a discrepancy score between the patient’s and carer’s judgments. Independent component analysis was applied and: i) correlation analyses between the AQ‐D score and functional connectivity in SN and DMN, and ii) comparison analyses of functional connectivity in DMN and SN between aware or unaware patients were performed.ResultsAQ‐D scores negatively correlated with intrinsic functional connectivity within the DMN in the retrosplenial cortex and precuneus, irrespective of cognitive impairment stage and age. We also found that unaware patients had higher connectivity within the SN in the anterior cingulate cortex compared to aware patients.Conclusionin patients with MCI and AD dementia, higher degrees of anosognosia are associated with lower functional connectivity within the DMN in the retrosplenial cortex and higher functional connectivity within the SN in the anterior cingulate cortex. This suggests that DMN and salience network might interplay in anosognosia expression in the AD continuum.
Differentiating Sporadic behavioural variant Frontotemporal Dementia from late‐onset Primary Psychiatric Disorders: the DIPPA‐FTD study
Authors: de Boer Sterre C. M. , Fenoglio Chiara , Fumagalli Giorgio G , Riedl Lina , Matis Sophie , Chatterton Zac , Rue Ishana , Landin‐Romero Ramon , van der Lee Sven J , Sommer Patrick , Grimmer Timo , Diehl‐Schmid Janine , Teunissen Charlotte , Galimberti Daniela , Halliday Glenda M , Ducharme Simon , Piguet Olivier , Pijnenburg Yolande A.L. 
Published: January 2025

AbstractBackgroundSporadic bvFTD is often misdiagnosed as a primary psychiatric disorder (PPD) due to overlapping clinical features and lack of reliable biomarkers. The multi‐centre study DIPPA‐FTD aims to develop diagnostic‐ and prognostic‐algorithms that can distinguish sporadic bvFTD from late‐onset PPD. The aim of the retrospective DIPPA‐FTD study was to identify the strongest clinical discriminators.MethodDIPPA‐FTD has compiled a retrospective database with 508 sporadic bvFTD and 152 late‐onset PPD cases from five cohorts, making it the largest sporadic FTD cohort to date. Logistic regression models and ROC curve analysis were applied to determine discriminative value per clinical marker in separate subsets; (i) neuropsychological features, (ii) visual brain atrophy rating scales and (iii) serum NfL+GFAP. A global (backward stepwise) logistic regression was also conducted in the most optimal subset that had all markers per modality available. All models were adjusted for age, sex and education when indicated.ResultFor marker (i) (bvFTD n = 217, PPD n = 75) higher scores of letter fluency (OR:1.47, p<0.001), global cognitive screening (OR:1.72, p = 0.01) and lower attention scores (OR:0.77, p = 0.05) were significantly associated with increased likelihood of PPD and reached an AUC of 0.77. Marker (ii) visual atrophy rating composite score (bvFTD n = 211, PPD n = 112) reached diagnostic accuracy of 79% and fronto‐insula was the most useful discriminator (AUC 0.80). Analysis of marker (iii) NfL+GFAP (bvFTD n = 275, PPD n = 82) showed that NfL and GFAP levels were significantly higher in bvFTD. Combination of NfL+GFAP yielded highest AUC value (0.88). The combined dataset with all markers variables available (bvFTD n = 120, PPD n = 40) reached an AUC of 0.89. Higher NfL (OR:1.09, p<0.01), more atrophy in fronto‐insula (OR:2.38, p = 0.02) and enlarged mean ventricular space (OR:3.84, p = 0.05) were significant predictors for sporadic bvFTD.ConclusionGlobal cognition, letter fluency and attention scores, fronto‐insula brain atrophy and NfL+GFAP have a significant role in discriminating sporadic bvFTD from PPD. Combination of markers can increase diagnostic accuracy in clinical setting. Promising markers identified in this retrospective study will be validated in the prospective DIPPA‐FTD study and integrated in a data‐driven approach to develop diagnostic and prognostic tools, enabling early‐stage diagnosis sporadic bvFTD which is required for trial enrolment.
Interrelationships of social determinants with cognition, vascular health, and physical functioning
Authors: Amofa‐Ho Priscilla A 
Published: January 2025

AbstractBackgroundThe primary aim of the current analysis was to evaluate the cumulative effect of different social determinants of health (SDoH) factors on vascular burden, cognition, and physical functioning.MethodWe conducted a secondary data analysis of the MIDUS 2 cross‐sectional study. Participants were ages 55 and above. Measures derived from the Framingham Stroke Risk Profile, Brief Test of Adult Cognition by Telephone, and MOS‐36 were used to represent vascular burden, cognition, and intermediate activities of daily living, respectively. SDoH variables included education, income, health insurance, stress, and support from family and friends. Associations were evaluated using composite‐based structural equation model (c‐SEM) embedded in an overall.ResultAmong cognitively normal adults (N = 568; mean age = 64.6), higher education, less stress, and higher income significantly contributed to the SDoH composite. Better standing in SDoH was associated with better physical functioning (beta = ‐0.21, p<0.001) and higher cognition (beta = 0.54, p<0.001). Significant direct effects of SDoH on vascular burden (beta = ‐0.12, p<0.05) and cognition (beta = 0.51, p<0.001), and of vascular burden on cognition (beta = ‐0.28, p<0.001) were found. Mediation analysis indicated that the unique effects of SDoH on cognition remained significant after controlling for vascular burden (beta = 0.04, p<0.05). After accounting for vascular burden and cognition, SDoH did not have a significant unique effect on physical functioning.ConclusionOur results support the disablement process that suggests that factors outside of the disease model (like SDoH factors) impact both the underlying diseases that lead to physical and functional limitation, all of which are associated with dementia/cognitive decline.
Dynamic disease‐associated gene regulatory transitions unmask genetic risk associated neurodegenerative cell states
Authors: Han Xia , Rexach Jessica E 
Published: January 2025

AbstractBackgroundAbnormal tau protein accumulation selectively affects distinct brain regions and specific neuron and glia populations in tau‐related dementias like Alzheimer’s disease (AD), frontotemporal dementia (FTD, Pick’s disease type), and Progressive supranuclear palsy (PSP). The regulatory mechanisms governing cell‐type vulnerability remain unclear.MethodIn a cross‐disorder single‐nucleus analysis, we examined 663,896 nuclei, assessing chromatin accessibility in three brain regions (motor cortex, visual cortex and insular cortex) across PSP, AD, and FTD in 40 individuals. Integrating genetic data with single‐nucleus RNA sequencing, we identified cell‐type‐specific cis‐regulatory elements (CREs) influencing disease‐associated transcriptional changes. Connecting GWAS signals to cell types enabled precise mapping of risk‐associated genetic elements to disorder‐specific gene regulatory events, accounting for dynamic gene regulation in the diseased brain.ResultDisorder enriched CRE modules were primarily activated in PSP astrocytes and FTD microglia. PSP exhibited increased astrocyte involvement, identified by distinct changes in astrocytes (ast.C1). In contrast, FTD featured microglia with suppressed GRN expression (mg.C4). Differentially accessible gene regulatory elements in mg.C4 uniquely and significantly contributed to FTD risk heritability across microglia. Disease dynamic chromatin accessibility peaks and gene enhancer elements, especially in astrocytes, accounted for more AD and PSP heritability, while FTD heritability predominantly involved microglial upregulated peaks.ConclusionThis study enhances our understanding of disease heritability, reinforcing the multicellular model of neurodegeneration. Glial cell types interacting with disease‐specific elements form disorder‐specific networks, deepening knowledge of genomic and cellular mechanisms in tau‐associated neurodegeneration.
Vascular Burden, dementia biomarkers and Neuropsychiatric Symptoms in Dementia
Authors: Chen Cheng‐Sheng , Lin Hsiu‐Fen 
Published: January 2025

AbstractBackgroundNeuropsychiatric symptoms (NPSs) significantly impact outcomes for individuals with dementia, with multiple factors contributing, including neurobiology. This study aims to enhance our understanding of the neurobiology of NPSs by examining the links between vascular burdens, dementia biomarkers, and NPSs.MethodPatients with dementia receiving outpatient services were included. The Neuropsychiatric Inventory (NPI) assessed NPSs. Vascular burdens were evaluated through clinical vascular diseases and white matter hyperintensities (WMH) severity using the Fazekas score in brain MRI. Additionally, ApoE genotypes and visual ratings of medial temporal atrophy (MTA) in brain MRI were used as dementia biomarkers.ResultForty‐five dementia patients participated, with the majority having Alzheimer’s disease (80%), followed by vascular dementia (8.9%), dementia with Lewy bodies (8.9%), and frontotemporal dementia (2.2%). The results indicated associations between depression symptoms and vascular diseases (p = 0.03), as well as anxiety symptoms (p = 0.03) and the depression/apathy cluster (p = 0.03) with MRI Fazekas scores. Regarding dementia markers, agitation/aggression was associated with ApoE ε4 (p = 0.02).ConclusionThe findings suggest specific associations between vascular burden and ApoE ε4 with certain NPSs, linking vascular burden to depression and anxiety, and agitation to ApoE ε4.
Validation of the measures for activities of daily living in older adult with cognitive disorders: the Korean version of the University of California San Diego Performance‐based Skills Assessment
Authors: Yim Seon Jin , Kim Kayoung , Joo Chaelin , Han Joo Hyun 
Published: January 2025

AbstractBackgroundThe study aimed to evaluate the validity of the Korean version of the University of California San Diego Performance‐based Skills Assessment, Validation of Intermediate Measures (K‐UPSA‐2‐VIM) in patients with dementia (D), Mild cognitive impairment (MCI), cognitive normal control group (CN), and explore the usefulness of the instrument as a measure of ADL in older adults with cognitive disorder.MethodStudy participants were 25 patients with D, 43 patients with MCI, 111 controls with CN group, respectively. For cognitive assessment, Mini Mental State Examination (K‐MMSE‐2), Consortium to Establish a Registry for Alzheimer’s Disease neuropsychological battery (CERAD‐K‐NP), Clinical Dementia Rating (CDR) were used. For functional assessment, Barthel‐Activities of Daily Living (B‐ADL), Instrumental Activities of Daily Living (K‐IADL), Dementia Screening questionnaire (K‐DSQ), K‐UPSA‐2‐VIM were used. Multivariate Analysis of Covariance (MANCOVA) was conducted to assess whether statistically significant differences existed in the scores of K‐UPSA‐2‐VIM and functional assessment measures among the different cognitive subgroups. Receiver Operating Characteristic (ROC) curve analyses were conducted to determine the optimal cut‐off scores for K‐UPSA‐2‐VIM that exhibit maximum sensitivity and specificity in discriminating between CN and MCI groups, MCI and D groups, in respectively.ResultStatistically significant differences were observed in all subdomains and total score of the K‐UPSA‐2‐VIM among three cognitive groups. All subdomains and the total score of K‐UPSA‐2‐VIM demonstrated a significant correlation with all subdomains of CERAD‐K‐NP. K‐UPSA‐2‐VIM demonstrated 75.7% of sensitivity and 65.1% of specificity, with an area under the curve (AUC) of 0.731 (95% CI:0.641‐0.821, p < 0.001) in discriminating between CN and MCI groups. In discriminating between MCI and D groups, 76.7% of sensitivity and 64.0% of specificity, with an AUC of 0.706 (95% CI:0.580‐0.833, p = 0.005) were demonstrated.ConclusionOur study results suggest that the K‐UPSA‐2‐VIM has diagnostic validity in Korean patients with dementia and mild cognitive impairment. The K‐UPSA‐2‐VIM is useful for assessing patients, including elderly individuals living alone without caregivers.
Large‐scale exome sequencing identifies novel genes for socioeconomic status, education, and cognition
Authors: Wu XinRui , Yu Jin‐Tai 
Published: January 2025

AbstractBackgroundCognition and its two critical proxies, socioeconomic status (SES) and educational attainment (EA), contribute substantially to human health and are heritable. Elucidating the genetic characteristics of SES/EA/Cognition not only helps to understand the innate individual differences in cognition, but also aids in unraveling the biological mechanisms of complex cognitive‐related disorders such as Alzheimer’s disease (AD). Here, we explored the rare and common protein‐coding variants impacting the comprehensive cognition phenotypic spectrum by leveraging large‐scale exomes.MethodUsing 350,770 exomes from the UK Biobank, we performed gene‐based collapsing analysis and single‐variant analysis for rare and common variants, respectively. Identified genes were biological annotated at multiple levels of gene sets, tissue types and cell types. The identified genetic associations with SES/EA/Cognition were further extended to brain structure, blood chemical markers, and neuropsychiatric phenotypes. Lastly, Mendelian randomization (MR) analysis and druggability evaluations were performed to reveal potential therapeutic targets.ResultWe identified 79 SES/EA/Cognition‐associated genes (64 novel) after Bonferroni correction, 29 from gene‐based collapsing tests for rare variants (P < 2.19 × 10‐8) and 50 from single‐variant association analysis for common variants (P < 1.08 × 10‐7). The intersection of rare variants with genome‐wide association studies signals prioritized ADGRB2 and KDM5B, and the effect of rare KDM5B variants was independent of nearby common variants. Pathway enrichment analysis revealed the involvement of synapse and hepatic metabolism. Multiple human brain tissue types as well as cell clusters of excitatory neuron and microgila were enriched. Rare variants in five genes (C2CD2L, IGF1R, AKNRD12, GIGYF1, KDM5B) and 35 common variants showed pleiotropy with broader biological phenotypes, including hippocampus volume and neurodegenerative diseases. MR analysis revealed the causal relationships between the expression levels of 23 genes in brain with SES/EA/Cognition (7 mapped to drug targets).ConclusionThis study utilizes large‐scale exome sequencing to provide a more comprehensive genetic framework underlying SES/EA/Cognition, offering informative associated genes and biological insights. The identified 79 genes across full allele frequency spectrum, 64 of which exhibited novel associations, would provide an abundant resource for further in‐depth molecular mechanistic studies and drug development for cognition.