bluuebunny/crossref_metadata_2025_split huggingface dataset:
Glial and synaptic biomarkers as early indicators of mild cognitive decline
Authors: Kulczynska‐Przybik Agnieszka , Dulewicz Maciej , Zetterberg Henrik , Hanrieder Jörg , Blennow Kaj , Mroczko Jan , Krawczuk Daria , Doroszkiewicz Julia , Borawska Renata , Slowik Agnieszka , Mroczko Barbara 
Published: January 2025

AbstractBackgroundCognitive disorders are a growing cause of morbidity and mortality worldwide. Diagnostic approaches to improve early diagnosis of cognitive disorders are constantly being sought. The pathogenesis of cognitive impairment is multifactorial and complex. It is believed that microglial activation and synaptic disturbance are crucial mechanisms leading to disease progression thus study of the interrelationships of the proteins involved in these processes appears to be important. Chemokine CX3CL1 seems to play a pivotal role in the central nervous system and it is involved in microglia‐neuron communication, neuronal survival, synaptic plasticity, as well as neuronal excitability. Findings from preclinical studies on AD models have reported the crucial role of CX3CL1 in microglial activation, regulation of plaque load, and cognition. Neurogranin is considered, as a biomarker of early synaptic dysfunction in AD. Additionally, it may serve as a marker to predict disease progression. Therefore, we aimed to investigate and compare CX3CL1 and neurogranin (Ng) levels in CSF patients with mild cognitive decline (MCI) and cognitively normal subjects from the control group. We also assessed an association between CSF concentrations of CX3CL1, Ng, and neurochemical dementia biomarkers.MethodThe concentrations of CX3CL1, neurogranin as well as neurochemical dementia biomarkers, including amyloid beta 1‐42 (Aß‐42), amyloid beta 1‐40, Tau, as well as pTau181 were measured in cerebrospinal fluid patients with mild cognitive impairment and individuals without cognitive decline by multiplexing and enzyme‐linked immunosorbent techniques.ResultSignificantly higher CSF concentrations of CX3CL1 and neurogranin were found in MCI patients in comparison to subjects without cognitive decline. Furthermore, in the group of patients with MCI the CSF levels of CX3CL1 and Ng significantly correlated with Aβ‐42, and pTau181 proteins. Similarly, a significant association between neurogranin and Tau protein was observed. Additionally, a positive correlation between CSF levels of Ng and CX3XL1 was noticed.ConclusionOur findings indicate that both proteins CX3CL1, as well as neurogranin, could be applied as complementary early biomarkers for more accurate diagnosing and stratification of patients with cognitive decline.
Presynaptic toxicity of the AD susceptibility gene BIN1
Authors: Dourlen Pierre , Lambert Erwan , Freire‐Regatillo Alejandra , Gelle Carla , Leclerc Valentin , Barois Nicolas , Hermant Xavier , Malfoi Tommy , Verstreken Patrik , Amouyel Philippe , Lafont Frank , Kilinc Devrim , Lambert Jean‐Charles 
Published: January 2025

AbstractBackgroundBIN1 is a major susceptibility gene for AD and BIN1 protein interacts with Tau. However, the contribution of BIN1 and its isoforms to AD pathogenesis remains unclear. We recently described that human BIN1 isoform1 (BIN1iso1) induces an accumulation of early endosome vesicles leading to neurodegeneration in Drosophila retina and that the early endosome size regulation was conserved in human induced neurons. This role was specific to BIN1iso1, as compared to BIN1iso8 and BIN1iso9. Because endosomal trafficking is essential for synapse, we further analyzed BIN1 isoforms neurotoxicity at the synaptic level.MethodWe first used electrophysiology, immunofluorescence and electron microscopy in vivo in transgenic Drosophila adult retina photoreceptor neurons and larval neuromuscular junction. We then tested a functional conservation in transduced rat primary neurons using tricompartment microfluidic devices, immunofluorescence and Multi‐Electrode‐Array to assess a presynaptic vs post‐synaptic role.ResultWe observed an early loss of synaptic transmission upon BIN1iso1 expression specifically, in Drosophila retina photoreceptor neurons. This was characterized by a strong accumulation of abnormally large vesicles in the presynaptic compartment. In addition, expression of BIN1iso1 in motoneurons of the neuromuscular junction altered the morphology of synaptic boutons, with an increase in their number and a decrease in their size, and the appearance of satellite boutons. BIN1iso1 synaptic toxicity could be partially rescued by modulating endosomal regulators, suggesting that an endosomal defect would be the cause of synaptotoxicity. Finally, we observed a functional conservation in rat primary neurons as shown by the loss of synaptic connectivity only when expressing BIN1iso1 in the presynaptic compartment.ConclusionOur results suggest that BIN1 has an isoform‐specific, deleterious effect on synaptic integrity when expressed in the presynaptic terminal. This effect could contribute to the synaptic loss observed early in AD.
A study of the efficacy of 500nm blue‐green light therapy on cognition, mood, and sleep in prodromal Alzheimer's disease
Authors: Feng Qiansen , Chen Lei , Li Linlin , Yang Junlan , Wu Jiajing , Yue Yuchuan , Wang Ziqi 
Published: January 2025

AbstractBackgroundThe study aimed to evaluate the effects of four weeks of 500 nm blue‐green light visual stimulation on cognition, mood, and sleep in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI).MethodEighty patients were recruited from the Memory Clinic. The experimental group comprised 42 cases (22 SCD and 20 MCI), while the control group comprised 38 cases (27 SCD and 11 MCI). The experimental group was treated with a 500nm blue‐green light (light spectrum intensity of 506 lux lm/m² and 230 µW/cm²) for 50 minutes in the morning for four weeks, while the control group received no treatment. General cognitive function was evaluated using the Mini‐mental State Examination (MMSE), Montreal Cognitive Assessment‐Basic (MoCA‐B), and Alzheimer’s Disease Assessment Scale‐cognitive subscale (ADAS‐cog), and mood was evaluated using the Hamilton Anxiety Scale (HAMA) and Hamilton Depression Scale (HAMD). The Pittsburgh Sleep Quotient Index (PSQI) was used to assess the sleep quality. Paired t‐test and Wilcoxon signed‐rank test were used to compare the differences in cognition, sleep, and mood between the experimental and the control group before and after the intervention.ResultThere were no significant differences in baseline demographic information, cognition, mood, and sleep between the experimental and control groups (P>0.05). As shown in Table 1. After the intervention, the experimental group showed a significant reduction in the ADAS‐cog (P = 0.034), HAMA (P = 0.044), HAMD (P<0.001) and PSQI scores (P = 0.035). The control group showed a significant reduction in HAMA (P = 0.002) and HAMD (P = 0.018) scores. As shown in Table 2.ConclusionFour weeks of 500 nm blue‐green light therapy significantly improved overall cognitive function and sleep quality in SCD and MCI patients.
Rescue of impaired hippocampal consolidation in the APP/PS1 mouse model of Alzheimer’s disease after increasing cerebral blood flow
Authors: Berkowitz Laura E , Todorova Ralitsa , Harvey Ryan E , Shimizu Jean‐Luc , Dong Xuelai , Oliva Azahara , Fernandez‐Ruiz Antonio , Nishimura Nozomi , Schaffer Chris B 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) manifests with early spatial memory impairment and is linked to the degeneration of hippocampal circuits. Hippocampal sharp wave ripples (SWRs) are high‐frequency population‐burst events that coordinate the reactivation of neural assemblies (groups of neurons that become correlated in their firing patterns during learning) in post‐learning sleep, which is the neural basis of memory consolidation. SWRs are reduced in the APP/PS1 mouse model of AD‐like pathology. Previously, we showed that cerebral blood flow (CBF) decreases and memory deficits were rescued following treatment with anti‐Ly6G antibodies. Here, we examine the potential normalization of hippocampal circuit activity with CBF increase.MethodMale, 7‐14‐month‐old APP/PS1 mice and wild‐type controls were implanted with 64‐channel silicon probes in hippocampal area CA1. Neural activity was recorded during sleep before and after the exploration of an open field. Putative cell types were identified using feature‐based classification, and neural assemblies were detected using independent component analysis.ResultAPP/PS1 mice had reduced magnitude and duration of assembly reactivation in post‐task sleep SWRs. After treatment with anti‐Ly6G antibodies, which increase CBF and improve memory performance, we found increased reactivation of these assemblies in post‐task sleep SWRs, relative to no‐treatment controls (Figure 1).ConclusionWe found that increasing CBF normalizes neural mechanisms of memory consolidation that are altered in AD mouse models, supporting the development of treatment approaches to increase CBF in AD.
NIA Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS)
Authors: Saravanan Naveensri , Kuzma Amanda B , Valladares Otto , Nicaretta Heather Issen , Manuel Joseph , Gangadharan Prabhakaran , Katanic Zivadin , Kirsch Maureen , Ren Youli , Bass Lauren , Brettschneider Jascha , Wilk Andrew , Zhao Yi , Qu Liming , Moon Michelle K , Rose Alexis Lerro , Keskinen Peter , Cifello Jeffrey , Horng Wenhwai , Tate Sam , Robbins Flawless , White Heather , Carter Luke , Chou Shin‐Yi , Naj Adam C. , Greenfest‐Allen Emily , Kuksa Pavel P. , Leung Yuk Yee , Lee Wan‐Ping , Schellenberg Gerard D. , Wang Li‐San 
Published: January 2025

AbstractBackgroundNIAGADS is a national genomics data repository that facilitates access of genotypic and sequencing data to qualified investigators for the study of the genetics of Alzheimer’s disease (AD) and related neurological diseases. Collaborations with large consortia and centers such as the Alzheimer’s Disease Genetics Consortium (ADGC), Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, the Alzheimer’s Disease Sequencing Project (ADSP), and the Genome Center for Alzheimer’s Disease (GCAD) allow NIAGADS to lead the effort in managing large AD datasets that can be easily accessed and fully utilized by the research community.MethodNIAGADS is supported by the National Institute on Aging (NIA) under a cooperative agreement. All data derived from NIA funded AD genetics studies are expected to be deposited in NIAGADS or another NIA approved site. NIAGADS manages a Data Sharing Service (DSS) that facilitates the deposition and sharing of genomic data and association results with approved users in the neurodegenerative research community. In addition, researchers are able to freely use the NIAGADS Alzheimer’s Genomics Database (www.niagads.org/genomics/) to search annotation resources that link published AD studies to AD‐relevant sequence features and genome‐wide annotations.ResultAs of January 2024, NIAGADS houses 105 datasets comprised of >183,000 samples including array data, sequencing, gene expression, annotations, deep phenotypes, summary statistics, among others. Qualified investigators can retrieve ADSP sequencing data with ease and flexibility through the NIAGADS DSS. To date, the ADSP and other contributing studies have completed whole exome sequencing (WES) of 20,499 samples and whole genome sequencing (WGS) of 36,352 samples. Raw WES and WGS files, quality controlled VCF files, and phenotype data files are available via qualified access. The next round of sequencing currently underway will generate around 30,000 additional genomes to be released in mid‐2024.ConclusionNIAGADS is a rich resource for AD researchers, with the goal of facilitating advances in Alzheimer’s genetics research. By housing datasets from many projects and institutions, NIAGADS enables AD researchers to meet their research goals more efficiently. Datasets, guidelines, and features are available on our website at https://www.niagads.org.
Hippocampal neuronal loss, LATE‐NC, Alzheimer’s disease pathology, and cognitive decline
Authors: Agrawal Sonal , Yu Lei , Leurgans Sue E. , Barnes Lisa L. , Bennett David A. , Schneider Julie A. 
Published: January 2025

AbstractBackgroundHippocampal neuronal loss (HNL), LATE neuropathologic changes (LATE‐NC), and Alzheimer’s disease (AD) are common neuropathological findings in older persons. However, the inter‐relationship between AD, LATE‐NC, HNL, and cognition is not well understood.MethodParticipants without known dementia (n = 420; mean age‐at‐death = 92 years, women = 72%) enrolled, in the Rush community‐based cohorts and underwent annual cognitive testing and autopsy. At autopsy, the severity of HNL in the CA1‐subiculum sector was semi‐quantitatively graded from 0 (none) to 5 (severe) on H&E stain without regard to AD or LATE‐NC pathology. Hippocampal sclerosis (HS) was defined as severe hippocampal neuronal loss (grade 5). Tau‐tangle density, β‐amyloid burden, LATE‐NC, and other age‐related pathologies were also recorded. Logistic regression and mixed‐effect models adjusted for demographics and neuropathologies were used to examine the association of HNL with AD (tangles/ β‐amyloid) and LATE‐NC, and separately with cognitive decline. Path analyses examined the extent to which the associations of LATE‐NC and tau tangles with cognitive decline was attributable to HNL.ResultHNL was common: mild in 61%, moderate in 16%, and severe in 20% of participants. Advanced LATE‐NC stage 2/3 and tau‐tangles, but not β‐amyloid pathology, were associated with worse hippocampal neuronal loss. More HNL was associated with faster decline in global cognition and four cognitive domains: episodic, semantic, and working memory and perceptual speed. These associations remained robust even after excluding participants with HS. LATE‐NC and tangles were also associated with cognitive decline but the association between LATE‐NC and cognitive decline was lost while the association of tangles with cognitive decline was partially attenuated after adding HNL in the model. The result from path anlayses suggested that two‐thirds of the association between LATE‐NC and cognitive decline was attributable to HNL whereas only 5% of the association of tau tangles was through HNL.ConclusionOur results support that HNL and tangles are the major contributors of cognitive dysfunction. LATE‐NC is also associated with cognitive decline but may causes most dysfunction via HNL.
Differential Patterns of Gut and Oral Microbiomes in Patients with Mild‐cognitive Impairment
Authors: Ngouongo Yannick Joel Wadop , Mathews Julia J , Muhammad Jazmyn A , Pirela‐Mavarez Rosa P. , Mahaney Michael C , Maestre Gladys E. , Seshadri Sudha , Kautz Tiffany F. , Fongang Bernard 
Published: January 2025

AbstractBackgroundOral and gut microbiomes have been associated with Alzheimer’s disease and related dementias (ADRD). Although the role of the gut microbiome and gut dysbiosis in ADRD has been extensively studied, research on the oral microbiome is lacking. Moreover, the synergetic contribution of oral and gut microbiomes to ADRD is unexplored. This study aimed to assess the differential patterns of oral and gut microbiomes and their synergetic effects in patients with mild cognitive impairment (MCI) compared to normal cognition (NC).MethodGut and saliva microbiome abundance and diversity measurements were obtained using 16S rRNA gene sequencing of stool and saliva samples from 27 participants (12 MCI, 15 NC, %F = 66.7, Age = 70.2 ± 6.4) recruited in San Antonio, Texas, USA (Table 1). The indexes Chao1, ACE, Observe, Shannon, and Simpson were computed to assess the 〈‐diversity of samples. However, the ®‐diversity was investigated after carrying out the principal coordinates analysis (PCoA) based on Bray‐Curtis distances to visualize group separation in compositional data. We used linear discriminant effect size and differential abundant analysis to identify gut and saliva features statistically different between MCI and NC (adjusted p‐value < 0.005).ResultNo differences in bacteria 〈‐ and ®‐diversity between MCI and NC (Figure 1) were found. However, we found an increased abundance of oral pathogenic genera, including Anaeroglobus, Centipeda, Cardiobacterium, Dialister, Fretibacterium, Leptotrichia, Mycoplasma, Tannerella, and Treponema in patients with MCI (Figure 2). We also found that MCI patients have a decreased abundance of gut genera Butyricicoccus, Defluviitaleaceae, Lachnospira, Paludicola, Shuttleworthia, and Subdoligranulum. These differential abundant gut genera have been shown to harbor anti‐inflammatory properties. We did not find evidence of synergetic contributions of oral and gut genera to MCI.ConclusionOur results suggest that the saliva microbiome, like the gut microbiome, is disrupted as patients progress from NC to MCI. The pathogenic oral microbes we found were previously linked to periodontal and gingivitis pathogens. Further studies with larger sample sizes are needed to validate these findings.
DNA Methylation Drives Gene Networks Dysregulated in Alzheimer’s Disease
Authors: Wang Erming , Wang Minghui , Yu Gefei , Thorpe Abigail , Haroutunian Vahram , Zhang Bin 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disease that inflicts the elderly worldwide. Recent studies revealed the association of abnormal methylomic alterations in AD. However, a systematic and comprehensive study is needed to investigate the effects of methylomic changes on the molecular networks underpinning AD, in particular, in brain regions most vulnerable to AD neuropathology.MethodWe profiled genome‐wide methylomic variations in the parahippocampal gyrus across 201 postmortem control, mild cognitive impaired (MCI) and AD brains in the Mount Sinai Brain Bank (MSBB) cohort. We next investigated the influence of methylomic changes on both gene and protein co‐expression networks. We then integrated the methylomic, epigenomic (ATAC‐seq), transcriptomic and proteomic data to infer the regulatory relationships among DNA methylation, chromatin accessibility, transcription and translation. Finally, we validated our key findings using an independent cohort (Religious Orders Study/Memory and Aging Project (ROSMAP)).ResultWe first demonstrated the existence of significant AD‐associated variation in methylomic sites genome‐wide, which were subsequently summarized into distinct differentially methylated regions (DMRs) that are critical in AD. We then quantified the effect of the DMRs on each gene and each protein as well as gene and protein co‐expression networks. We found that DNA methylation had profound influences on not only the AD‐associated gene/protein modules but also their key regulators in the networks. With the integration of the matched multiomics data, we unveiled that DNA methylation likely influenced gene/protein expression via epigenomic peak domains in AD. Further integration of the matched bulk tissue methylation and single nucleus multiomics data revealed cell‐type specific methylomic regulation of transcriptomics in AD.ConclusionOur study is the most extensive genome‐wide investigation on the impact of methylation on AD pathology, and the first integrative survey on the complex interactions between methylation, chromatin accessibility, and multiscale transcriptomic and proteomics networks in AD.
From Normal Cognition to Dementia: Using Natural Language Processing to Identify Cognitive Stages from Clinical Notes
Authors: Amini Samad , Cheng You , Magdamo Colin G. , Paschalidis Ioannis , Das Sudeshna 
Published: January 2025

AbstractBackgroundThis study responds to the urgent need for automated and reliable methods to detect cognitive impairments on a large scale. It leverages natural language processing (NLP) techniques to predict dementia and mild cognitive impairment (MCI) using clinical notes from electronic health records (EHR).MethodOur study used an EHR dataset from Massachusetts General Brigham, which included clinical notes from a 2‐year period (2017‐2018) covering 12 types of patient encounters. Sentence segmentation and keyword‐specific extraction were performed using the NLTK tool, focusing on dementia and activities of daily living, thus providing a comprehensive base for our analysis. Our analysis, designed for classifying cognitive stages into normal cognition, MCI, and dementia, involved three binary classification tasks. We employed two innovative NLP methods based on a transformer‐based language model, the Universal Sentence Encoder (USE). The first, Random Sampling, involved extracting and randomly batching sentences containing relevant keywords, each batch processed through the Universal Sentence Encoder (USE) to generate unique 512‐dimensional embeddings. The second method, Encounter‐based Sampling, grouped sentences by their corresponding note encounter types and keyword categories, creating 24 distinct embeddings for each patient. These methods, leveraging the USE’s deep learning capabilities, provided nuanced approach to classifying cognitive stages, enhancing the predictive accuracy of our model.ResultWe evaluated the performance of various classification tasks on the data containing 531 Normal, 153 MCI, and 229 Dementia subjects. These classifications include classifying between normal cognition and dementia (AUC 97.8% in random sampling, AUC 93.6% in encounter‐based sampling), normal cognition and MCI (AUC 81% in random sampling, AUC 74.6% in encounter‐based sampling), as well as normal cognition and cognitive impairment (i.e., merged MCI and dementia stages; AUC 92.4% in random sampling, AUC 85.4% in encounter‐based sampling). Our NLP‐based approaches also significantly outperforms the baseline model based on the number of relevant sentences by a margin of 6‐13% in AUC in these three classification tasks.ConclusionOur study harnessed NLP techniques for enhanced dementia staging accuracy using EHR clinical notes. We introduced a highly accurate, fully automated approach with scalability potential, promising to transform hospital practices in managing clinical notes.