bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blood‐derived extracellular vesicles phosphoproteome as a resource of biomarker candidates for Alzheimer’s disease
Authors: Martins Tânia Soares , Rosa Ilka Martins , da Cruz e Silva Odete , Henriques Ana Gabriela 
Published: December 2023

AbstractBackgroundProtein phosphorylation plays a crucial role in cell communication, signaling and by extension is relevant to Alzheimer´s disease (AD) pathogenesis. Extracellular vesicles (EVs) are recognized as important mediators in intercellular communication and can be isolated from peripheral biofluids, where the content reflects the cellular origin. EVs’ role in AD pathophysiology and their value as biomarker resources is being unraveled. However, little is known regarding EVs’ phosphoproteome in AD and it has still to be determined if blood‐derived EVs are suitable for phosphoproteome profiling. Hence, this work aimed to characterize plasma‐derived EVs (pdEVs) and plasma supernatant EVs free (plasma‐depleted EVs) phosphoproteomes, to potential unravel disease mechanisms and/or new biomarker candidates for AD.MethodA pool of human plasma was used for pdEVs isolation using a precipitation‐based methodology. Both pdEVs and plasma‐depleted EVs samples were analyzed using an antibody‐based phosphospecific microarray. Characterization of the phosphoproteomes obtained was achieved by Gene Ontology enrichment analysis and the most relevant Reactome pathways associated, using ClueGo and CluePedia plugins from Cytoscape v3.9.1. In addition, protein‐protein interaction network of the pdEVs phosphoproteome was retrieved from STRING database and analyzed using Cytoscape “Network Analyzer”, employing the betweenness centrality option to highlight central nodes. Further, the pdEVs phosphoproteome (corresponding gene names) was overlapped with a list of genes associated with AD, collated from DisGenet database.ResultsMore than 70 proteins were enriched ≥40% in bdEVs when compared to plasma‐depleted. Top biological processes were mainly related to cell proliferation/division, apoptosis and phosphorylation. Reactome pathways analysis revealed terms associated to toll like receptor cascade and MAPK signaling. In the network constructed for the pdEVs enriched proteins, PTEN appeared as a central node. Additionally, overlap with AD gene list from DisGenet revealed that 60% of the pdEVs phosphoproteome is AD‐related. Among these, several kinases already described in senile plaques and/or neurofibrillary tangles were identified.ConclusionIn sum, bdEVs phosphoproteome is enriched in AD‐related targets, exhibiting potential as a biomarker candidate resource for AD diagnosis.This work was funded by the Alzheimer’s Association under Grant 2019‐AARG‐644347, supported by iBiMED‐UIDB/04501/2020,iBiMED‐UIDB/04501/2020,ADPro‐SAICT‐45‐2021‐02 and TSM individual PhD grant SFRH/BD/145979/2019. Health Ethics Committee ARS Centro(No.012804‐04.04.2012) and CNPD(No.369/2012).
Topline results of INTERCEPT‐AD: A phase I trial of Aβ oligomer‐targeting ACU193 in early Alzheimer’s disease
Authors: Siemers Eric R , Feaster Todd , Skljarevski Vladimir , Sundell Karen L , Sethuraman Gopalan , Johnson Kimball ,   INTERCEPT‐AD Study Group
Published: December 2023

AbstractBackgroundACU193 is a humanized IgG2 subclass monoclonal antibody targeting soluble amyloid‐beta oligomers (sAβOs). Growing evidence supports the view that sAβOs may be the most toxic and pathogenic form of Aβ relative to Aβ monomers and amyloid plaques and are one of the primary drivers of Alzheimer’s disease (AD) neurodegeneration. Thus, blocking the toxicity of sAβOs with ACU193 is a promising approach for treating AD.MethodINTERCEPT‐AD is a phase 1 randomized, placebo‐controlled, single‐ and multiple‐ ascending dose (SAD/MAD) study of the safety, tolerability, and pharmacokinetics (PK) of intravenous ACU193 in participants with early AD, i.e., mild cognitive impairment or mild dementia due to AD. Key inclusion criteria are 55‐90 years of age, confirmation of amyloid pathology with a PET scan, MMSE score of 18‐30, and CDR‐Global score (CDR‐GS) of 0.5 or 1.0. The MAD portion of the study includes three administrations of ACU193 at doses of 10, 25, or 60 mg/kg. In addition to standard safety measures, MRI is assessed periodically. Cerebrospinal fluid is collected to assess PK and evidence of target engagement. The study also includes exploratory measures such as standard cognitive and functional assessments, a computerized cognitive test battery, measures of cerebral blood flow via arterial spin labeling on MRI, and various plasma biomarkers.ResultSixty‐five participants from 17 U.S. study sites were randomized to INTERCEPT‐AD, with 53% female and baseline age of 72.1 ± 7.8 years (mean ± SD). The baseline MMSE was 24.2 ± 3.6, CDR‐GS was 0.64 ± 0.27, and CDR‐Sum of Boxes was 3.5 ± 1.8. In addition to baseline characteristics, the presentation will provide topline safety results, frequency of amyloid‐related imaging abnormalities (ARIA), PK assessments, and evidence of target engagement. Some exploratory measures including cognitive and functional assessments, computerized cognitive testing, and endpoint florbetapir PET results will also be presented.ConclusionWe will present topline results, along with key baseline demographic, clinical, and cognitive characteristics of participants in the INTERCEPT‐AD trial. The data generated from this trial will guide further development of ACU193 in a subsequent trial to test the novel mechanism of action of ACU193 in the treatment of early AD.
Longitudinal robustness of resting‐state functional connectivity signatures across different stages of the Alzheimer’s disease continuum
Authors: Behjat Hamid , Strandberg Olof , Binette Alexa Pichet , Spotorno Nicola , Vogel Jacob W , Ossenkoppele Rik , Hansson Oskar 
Published: December 2023

AbstractBackgroundA growing number of resting‐state fMRI (rs‐fMRI) studies report changes in network activity to be a frequent and often early pathological feature in many neurodegenerative conditions. The majority of studies have primarily focused on changes in group averages, failing to account for individual functional connectivity (FC) idiosyncrasies that have been shown to provide a unique identifier or “fingerprint” in healthy individuals (Finn et al., 2015). It thus remains unclear to what extent FC‐signatures are stable in the context of cognitive decline and Alzheimer’s Disease (AD) pathology (e.g., β‐amyloid [Aβ] and tau). We studied the robustness of subject‐specific FC in a longitudinal cohort covering the AD spectrum.Method275 participants with longitudinal rs‐fMRI data—baseline plus a follow up after approximately two‐years—were selected from the Swedish BioFINDER‐2 cohort, split into six groups: cognitively normal (CN) Aβ‐, subjective cognitive decline (SCD) Aβ‐, SCD Aβ+, mild cognitive decline (MCI) Aβ‐, MCI Aβ+, and AD Aβ+. FC matrices were derived from each subject rs‐fMRI session using the Schaefer cortical parcellation (200 and 400 ROIs), and consequently, a 275×275 identifiability matrix (IM) was derived; see Fig. 1B. For each subject, two fingerprinting measures were extracted from the IM: self identifiability (I‐self) and differential identifiability (I‐diff); see Fig.1B.ResultI‐self and I‐diff show varied distributions across the six groups, but values remain notably high even within the AD Aβ+ (Fig.2A). Both I‐self and I‐diff show significant differences between CN Aβ‐ and AD Aβ+ (Fig.2B). SCD Aβ‐ not only show a greater difference to AD Aβ+, but also to SCD Aβ+ and MCI Aβ+; see Fig.2B. Baseline tau‐PET was associated with I‐self (r = ‐0.1928,p = 0.0014) and to a lesser degree with I‐diff (r = ‐0.1293, p = 0.0334), whereas baseline MMSE was only found associated to I‐self (r = 0.1671,p = 0.0055); neither I‐self nor I‐diff were associated with age (Fig.3).ConclusionOur results suggest that resting‐state FC is mostly stable under cognitive decline and presence of AD pathology. FC was most notably differentiable for SCD Aβ‐, suggesting it as a potential signature to decipher underlying cognitive status and to predict likelihood of future conversion to AD.
Comparing feature selection methods to improve the classification of Mild Cognitive Impairment patients based on Magnetoencephalography data
Authors: Martínez‐Évora Adelia‐Solás , Carrasco‐Gómez Martín , Shpakivska‐Bilán Danylyna , Nebreda Alberto , García‐Colomo Alejandra , Maestú Fernando 
Published: December 2023

AbstractBackgroundMachine learning (ML) algorithms are generating great interest for early diagnose of Alzheimer’s disease (AD). Despite several approaches have been developed, limited research has been conducted on the impact of feature selection in classification performance. In this study we compare two feature selection methods, LASSO and Elastic Nets (EN), applied to ML algorithms based on magnetoencephalography (MEG) data from mild cognitive impairment (MCI) patients.MethodAn eyes‐closed resting‐state MEG recording was performed by 262 participants (117 healthy controls and 145 MCI). Functional connectivity measures were estimated for all classical frequency bands using the Phase‐Locking Value. To develop the ML algorithms, specific regions of interest from the default mode network, based on the Automatic Anatomical Labelling atlas, were selected, resulting in a total of 325 features. After dividing the dataset into training (80%) and test (20%) sets, feature selection with 10000 iterations and five‐fold cross validation was performed independently for each band using LASSO and EN algorithms. Afterwards, several classification models were trained with a five‐fold cross validation and then validated on the test set, over 500 iterations.ResultThe classifier showing the best performance was the linear Support Vector Machine for the beta frequency band (12‐30 Hz). Given the similarity of the training and test performance values, the results reveal that overfitting was avoided when using the 45 features selected by LASSO instead of the 47 features selected by EN, reaching a validation accuracy of 77%. Additionally, LASSO consistently identified three functional connectivity links as relevant in all frequency bands but alpha: right superior frontal gyrus & right superior frontal gyrus orbital, left posterior cingulate cortex & left hippocampus, right posterior cingulate cortex & right precuneus.ConclusionML algorithms applied to MEG data can successfully discriminate MCI patients from healthy controls. In addition, LASSO algorithm applied for feature selection leads to better classification performance. Moreover, the resulting relevant functional connectivity links involve areas affected by AD pathology even in early stages of its development (López‐Sanz et al., 2019). Further exploration of this methodology is needed, combining this data with structural neuroimaging or complementary biomarkers.
A novel fluid biomarker for TDP‐43 loss of function
Authors: Irwin Katherine E , Jasin Pei , Braunstein Kerstin E , Sinha Irika , Bowden Kyra D , Moghekar Abhay , Oh Esther S , Raitcheva Denitza , Bartlett Dan , Berry James D , Traynor Bryan J , Ling Jonathan P , Wong Philip C 
Published: December 2023

AbstractBackgroundTDP‐43 nuclear clearance and cytoplasmic aggregation occur in multiple neurodegenerative diseases, including amyotrophic lateral sclerosis‐frontotemporal dementia (ALS‐FTD), Alzheimer’s disease (AD), and limbic‐predominant age‐related TDP‐43 encephalopathy (LATE). Nuclear clearance of TDP‐43 leads to its failure to repress splicing of nonconserved cryptic exons. This loss of TDP‐43 splicing repression is well‐documented in postmortem tissues, but there is currently no method of detecting TDP‐43 dysfunction in living patients. As some cryptic exons are spliced in‐frame and translated into proteins carrying novel epitopes, we hypothesize that these “cryptic peptides” may be found in patient CSF as biomarkers of TDP‐43 dysfunction.MethodWe generated novel monoclonal antibodies against several TDP‐43 cryptic exon targets and then developed a sandwich ELISA using the Meso Scale Discovery (MSD) platform, which we validated in cells deficient in TDP‐43 for the cryptic exon target in HDGFL2. We then screened CSF samples of C9ORF72‐mutation carriers with or at risk of ALS‐FTD and control individuals for the presence of this cryptic peptide.ResultThe MSD signal for cryptic HDGFL2 was elevated in CSF of C9ORF72‐mutation carriers with ALS (n = 5, mean = 1601) compared to those of controls (n = 5, mean = ‐64.10; p<0.013), so we examined a larger cohort of C9ORF72‐mutation carriers. In symptomatic individuals (n = 27), cryptic peptide levels showed a correlation nearing significance with symptom duration (r = ‐0.368, p = 0.059), suggesting that levels of the cryptic peptide tend to be higher during the earlier symptomatic phase. We also found elevated cryptic peptide levels in CSF of several pre‐symptomatic individuals. To clarify cryptic peptide dynamics during disease progression, we began to assess longitudinal CSF samples and found that in 82.35% (14/17) of symptomatic individuals, levels of the cryptic peptide decreased with disease progression.ConclusionOur findings indicate that loss of TDP‐43 splicing repression occurs early in disease progression in ALS‐FTD, even pre‐symptomatically, and that detection of HDGFL2’s cryptic neoepitope may facilitate earlier diagnosis of TDP‐43‐related diseases. Further efforts linking the presence of cryptic HGDFL2 to TDP‐43 co‐pathology in AD may help expand biomarker development in AD. Additionally, evaluating dynamics of these biomarkers could provide a way of measuring target engagement for new therapeutics aimed at restoring TDP‐43 function.
The tauopathy‐associated PERK variant, PERK‐B, induces maladaptive translation and reveals novel pathogenic mechanisms of PSP
Authors: Lessard Christian B , Tolton Samantha G , McFarland Karen , Criado‐Marrero Marangelie , Bagchi Pritha , Seyfried Nicholas T , Abisambra Jose F. F 
Published: December 2023

AbstractBackgroundA major challenge in the field is identification of molecular mechanisms driving pathological tau accumulation in tauopathies such as progressive supranuclear palsy (PSP). The largest GWAS for PSP identified a protein kinase endoplasmic reticulum kinase haplotype B (PERK‐B) hypomorph as a risk factor for the disease. This variant is less effective at reducing translation as its counterpart, PERK haplotype A (PERK‐A) and promotes the accumulation of pathological hyperphosphorylated tau species. However, the functional differences between PERK‐A and ‐B remain unknown, and this is partly due to the need for chemical induction of ER stress with compounds that provoke pleiotropic effects.MethodTo address these gaps in knowledge and overcome technical issues, we developed novel molecular tools and models to study PERK function. Using CRISPR/Cas9, we generated PERK‐KO HEK cells, transfected them with newly designed PERK plasmids, ER stress sensors, and markers of cap‐dependent translation. We also measured changes in tau accumulation and insolubility because of PERK‐B. In addition, we performed transcriptomic and puromycin proteomics to specifically identify the transcriptome and the nascent proteome resulting from PERK‐B expression.ResultWe established that expression of both PERK variants equally induced ER stress and reduced cap‐dependent translation. In addition, the PERK‐A and ‐B transcriptomes were virtually identical. However, while PERK activity was protective, PERK‐B less effectively cleared tau, leading to accumulation of insoluble pathological hyperphosphorylated tau. SUnSET proteomics revealed four proteins that were only present in the PERK‐B translatome. Given that these proteins had not been previously associated with PSP, we measured their levels in human brains and identified that at least one of them was significantly increased in PSP cases.ConclusionOur data suggest that the PERK‐B variant promotes accumulation of specific proteins associated with PSP. The new link between these proteins and PSP may reveal novel pathogenic mechanisms and could uncover new and effective therapeutic targets. Efforts to establish the role of these proteins in PSP is underway.
NeuroAI: AI‐based prediction model of Amyloid PET positivity using MR images and APOE genotype
Authors: Park Jun Young , Kim Byeong‐Chae , Ha Jung‐Min , Chong Ari , Lee Kun Ho 
Published: December 2023

AbstractBackgroundSince acquiring amyloid PET data is costly and long waiting period due to the inaccessibility of PET machine, predicting positivity of amyloid PET data has many benefits. Therefore, we aimed to develop an artificial intelligence (AI) model for predicting amyoloid PET positivity for mild cognitive impairment (MCI) subjects with MR images and APOE genotype.MethodA total 1,742 MCI subjects were enrolled in the Gwangju Alzheimer’s and Related Dementia cohort registry, Korea. We trained the deep learning model using MR images (T1 and Flair) and their APOE genotyping data. Finally, we conducted an external validation with 227 MCI subjects (118 with Aβ(+) and 109 with Aβ(‐)) from Chonnam National University Hospital and Chosun University Hospital in Korea.ResultWith independent test set, our model had the great performance with an AUC of 0.84 (0.78‐0.89), Accuracy of 78% (72‐83%), Sensitivity of 73% (64‐81%), and Specificity of 83% (74‐89%). The Korea Ministry of Food and Drug Safety granted clearance for the Phase III clinical trail of our model (NeuroAI) in March 2023 (NCT05383053).ConclusionOur model could help reduce the need for costly and time‐consuming amyloid PET scans, while also improving the accuracy of Alzheimer’s Disease diagnosis.
Plasma oligomeric amyloid‐β and the correlation with cognitive function across the clinical spectrum of Alzheimer’s disease
Authors: Min Jin‐Young , Min Kyoung‐bok , Ha Sang‐Won , Kang Min‐Ju , Jeong Da‐Eun , Lee Ryan 
Published: December 2023

AbstractBackgroundThe amyloid hypothesis linking amyloid β protein (Aβ) to Alzheimer’s disease (AD) is the key pathological event. It has shifted in recent years to suggest Oligomeric Amyloid‐β (OAβ) as a promising candidate for AD diagnosis. We aimed to depict the plasma levels of OAβ across a spectrum of cognitive stages and to explore the correlation between OAβ and specific cognitive domains.MethodIn this single‐center observational study, we included 494 individuals who had normal cognition (NC), mild cognitive impairment (MCI), and AD. Cognitive function was assessed across four cognitive domains (language and related functions, visuospatial functions, memory, and frontal/executive functions) and with the Mini‐Mental State Examination (MMSE). Participants were defined as: 1) NC with a percentile >16th in all sub‐tests of the SNSB‐C, 2) MCI with a percentile >16th in one or more sub‐tests of the SNSB‐C and K‐IADL < 0.43, and 3) AD with a percentile >16th in one or more sub‐tests of the SNSB‐C and K‐IADL ≥ 0.43. The MDS‐AD assay kit (PeopleBio Inc., Gyeonggi‐do, Republic of Korea) was used to quantify the levels of OAβ in the plasma.ResultThe plasma OAβ levels gradually increased among different cognitive stages of AD, with the lowest concentration in the NC (0.72 ng/ml), an increase in the MCI (0.76 ng/ml), and the highest concentration in AD (1.08 ng/ml). The plasma OAβ levels were significantly correlated with MMSE scores (r = ‐0.119, P‐value = 0.0083), the Korean‐Boston Naming Test (r = ‐0.090, P‐value = 0.0464), and the Trail Making Test‐Elderly (TMT‐E) (r = ‐0.146, P‐value = 0.0012). After adjusting for confounding variables, the elevated plasma OAβ were associated with worse performance on MMSE (Adjusted beta = ‐0.691; SE = 0.27, P‐value = 0.0100) and TMT‐E (Adjusted beta = ‐7.721; SE = 2.33, P‐value = 0.0100) as frontal/executive functions.ConclusionPlasma OAβ has correlated with language and related functions and frontal/executive functions, suggesting its potential biomarker for clinical manifestations of AD.
Digital Cognitive Assessment Leveraging the Boston Process Approach Can Flag Emergent Cognitive Decline in Individuals with Subtle and Mild Functional Disability
Authors: Libon David J , Swenson Rodney , Gomes‐Osman Joyce Rios , Banks Russell E , Jannati Ali , Higgins Connor , Tobyne Sean , Bates David , Pascual‐Leone Alvaro 
Published: December 2023

AbstractBackgroundEarly detection of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease and Related Dementias (ADRD) is key to optimal management. Digital tests allow for the reliable capture of meaningful, process‐based neuropsychological test parameters that traditional paper/pencil measures fail to detect, thus enabling earlier detection. We assessed how subtle functional decline relates to process features extracted from the digital Clock Drawing Test (dCDT) and the digital Trail Making Test‐Part B (dTrB).Methods629 community dwelling participants (58.5% female) were assessed with the Functional Assessment Questionnaire (FAQ), the MMSE, the digital clock drawing test (dCDT) and the digital Trail Making Test‐Part B (dTrB). Three FAQ groups were constructed: FAQ = 0‐2 (minimal functional disability, n = 490); FAQ = 3‐5 (subtle functional disability, n = 90); FAQ = 6‐8 (mild functional disability, n = 49).ResultsParticipants with minimal functional disability were younger (p = 0.027) and scored better on the MMSE (p = 0.001) than other groups. Groups were equated for education. dCDT command/copy component placement was more accurate among participants with minimal functional disability compared to other groups (command dCDT p = 0.001 versus mild functional disability; copy dCDT p = 0.006 versus both subtle and mild functional disability). On the dTrB, participants with minimal disability drew faster than those with subtle or mild disability (mean stroke velocity, p = 0.001). Analyses for percent pen lift time found no difference between participants with minimal versus subtle disability; however, both groups differed from participants with mild disability (p = 0.001). Optimal group classification using stepwise nominal regression with the minimal functional disability group as the reference was achieved using dCDT copy component placement and dTrB mean stroke velocity (X
2 = 28.37, p = 0.001), where dTrB mean velocity entered first (X
2 = 17.73, p = 0.001) followed by dCDT copy component placement (X
2 = 11.19, p = 0.004). Both variables contributed comparably to group classification (Wald statistic range 5.82‐8.88, p = 0.012, respectively).ConclusionsThe digital assessment described above, targeting executive, scanning, visuoconstructional and motor domains, captures highly nuanced, discrete behaviors with precision/ operationalism heretofore unattainable. Consequently, it is reasonable to posit that digital cognitive assessments leveraging the Boston Process Approach can both objectively detect emergent cognitive impairment and infer its likely impact on functional activities, critical for practical assessment in clinical care.