bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distinct regional and hemispheric tau distributions in Primary Progressive Aphasia with neuropathologic Progressive Supranuclear Palsy: A stereological study
Authors: Zouridakis Antonia , Kawles Allegra , Minogue Grace , Keszycki Rachel M , Coventry Christina , Weintraub Sandra , Rogalski Emily J , Flanagan Margaret E , Mao Qinwen , Bigio Eileen H , Mesulam M.‐Marsel , Geula Changiz , Gefen Tamar 
Published: June 2023

AbstractBackgroundPrimary Progressive Aphasia (PPA) is a dementia syndrome characterized by isolated and progressive impairment of language and focal atrophy of left‐hemispheric cortical regions. PPA presents with various underlying FTLD‐tauopathies such as Pick’s disease (PiD), corticobasal degeneration (CBD), and progressive supranuclear palsy (PSP). This study investigated clinicopathologic concordance between the aphasic phenotype of PPA and regional distributions of PSP markers quantified in language‐related cortical areas and the dentate gyrus (DG) of the hippocampus—an area of interest due to intact memory exhibited in PPA. Another goal was to compare regional distributions of tau‐positive markers in PSP compared to CBD and PiD to identify differential susceptibility patterns across FTLD‐tauopathies.MethodParaffin‐embedded sections were stained immunohistochemically with AT‐8 to visualize neuronal tau inclusions and astrocytes containing phosphorylated tau in 8 right‐handed cases with PPA and autopsy‐confirmed PSP. Modified unbiased stereology was performed in bilateral middle frontal gyrus (MFG) and inferior parietal lobule (IPL), and left DG. A secondary analysis compared distributions of tau markers in cases with PiD (N = 6; tau‐positive inclusions) and CBD (N = 4; tau‐positive inclusions + astrocytic plaques). One‐way ANOVAs and students’ t‐tests were used to analyze distributions.ResultWithin the PSP group, there was significant left‐sided asymmetric predominance of tau‐positive neuronal inclusions and astrocytic tau in cortical areas; left MFG showed over double the total marker density vs right (3,490 vs 1,549 counts/mm3, respectively; p<0.05). In PSP, there was significantly less tau‐positive inclusions and astrocytes in the DG relative to cortical regions, where the ratio of left‐sided dentate‐to‐cortical inclusions was ∼1:2. This was remarkably lower than dentate‐to‐cortical ratios of ∼2:1 in CBD and ∼3:1 in PiD (p<0.01). Finally, PSP cases showed significantly greater astrocytic tau in cortical regions compared to CBD, by ∼100 fold in the left hemisphere (p<0.01).ConclusionFindings from this stereological study of PPA with FTLD‐PSP show leftward cortical predominance of pathology concordant with the salience of the aphasic phenotype. Dentate predominance of pathology in PPA due to FTLD‐tau remains a mystery. The relative distribution of dentate‐to‐cortical tau pathology is different across FTLD‐tau species, offering insights into the selective vulnerability of distinct neuronal populations in neurodegenerative dementias.
Epidemiological profile of early‐onset Alzheimer’s mortality in Brazil from 2010 to 2019
Authors: Toscan Luiza , De Mattos Ana Carolina Squeff 
Published: June 2023

AbstractBackgroundEarly‐onset Alzheimer disease (EOAD) is not just late‐onset AD (LOAD) at a younger age; there are substantial differences between these 2 categories of AD (Mendez, 2017). Therefore, the first step is to understand its population context. In this way, we sought in this study to determine the socio‐epidemiological aspects of Early‐onset Alzheimer disease (EOAD) mortality in Brazil. This is the first study that analyzes the epidemiology of EOAD in Brazilian territory.MethodData from the Ministry of Health’s Mortality Information System (SIM) were analyzed for the epidemiological characterization of deaths from Alzheimer’s (ICD‐10 code G30.0) between 2010 and 2019, considering the variables available on the death certificates. EOAD mortality was considered as death from Alzheimer’s in patients younger than 60 years of age. The sociodemographic variables chosen were sex, race/color, marital status, education and region of the country.ResultBetween 2010 and 2019, SIM recorded 804 cases of EOAD. Of these, 50.62% were male and 49.37% were female. As for race, 63.6% were white, 26.6% brown, 4.97% black, 0.62% yellow, and in 4.10% this information was ignored on the death certificate. It was found that 45% were married, 25% single, 10.9% widowed, 8.2% divorced, 2.2% other and 8.45% were ignored. The level of education was 1 to 3 years in 21.3%, 21% for 4 to 7 years, 15.9% for 8 to 11 years, 7.8% for more than 12 years, 12.4% none and in 21.39% we did not obtain this data. It was also observed 48.8% cases in the Southeast, 21.2% in the South, 20.1% in the Northeast, 6.84% in the Midwest and 2.8% in the North.ConclusionThe prevalence of early Alzheimer’s mortality was higher in male, white, married patients, from the Southeast region, with 1 to 3 years of schooling. The epidemiological profile is a fundamental part for the elaboration of programs of preventive actions and health promotion. Strengths of this study include the production of information on mortality from early Alzheimer’s disease in Brazil, in a context of lack of research of this type in the country.
The analysis of fMRI complexity as a biomarker of cognitive decline compared to tau‐PET
Authors: Park Gilsoon , Kim Hosung , Jann Kay 
Published: June 2023

AbstractBackgroundTau‐PET detects the neurofibrillary tangle pathology and is considered a biomarker of neuronal injury and cognitive decline. However, PET imaging has radiation exposure risks and is costly. Recently, brain entropy mapping based on rs‐fMRI has emerged as a brain functionality biomarker that indicates the complexity of BOLD signals. Various studies have implied that reduced brain entropy values correlate significantly with cognitive decline in Alzheimer’s disease. This study analyzes the effect of fMRI complexity as a biomarker of cognitive decline in AD compared to tau‐PET.MethodWe obtained the dataset for this study from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). The dataset consisted of 147 subjects (age = 72.5±7.5, M/F = 60/87, CN/MCI/AD = 95/45/7) with a tau‐PET (tracer: 18F‐AV1451) and two fMRI scans. FMRI images underwent standard processing to generate Multi‐Scale Entropy (MSE) maps. We calculated parametric SUVR values based on cerebellar reference regions from tau‐PET images. To determine the ability of MSE and PET images as a risk factor of cognitive decline in AD, convolutional neural networks were used to classify individuals into CN or MCI/AD groups. Each classifier was trained separately with fMRI complexity images or SUVR images. These two models had the same network structures and hyperparameters. We performed a 5‐fold cross‐validation to evaluate each model.ResultThe classifier using fMRI‐MSE achieved an accuracy equivalent to that using tau‐PET (0.7823 vs. 0.7687). We also calculated the Area Under the ROC curve (AUC) to evaluate sensitivity and specificity and observed that the model using fMRI‐MSE achieved AUC of 0.7022, and that using tau‐PET resulted in AUC of 0.6889.ConclusionThe classification performance showed that use of fMRI‐MSE could potentially be an AD biomarker alternative to tau‐PET. Further studies with multisite, larger datasets are required to validate our preliminary results and provide more conclusive evidence.
A call for utilizing various screening tools in dementia diagnosis: A systematic review
Authors: Dahab Lubaba , Elsayed Sarah , Abdelsamad Alaa Alaa , Sumi Dey , Patel Krupa , Bakhtiarpuri Avinash , Obeid Tamadur , Yousif Samah , Choudhry Varda , Elomeiri Leina , Ibrahim Mohammed B. , Ahmed Samah , Alatta Lina , Ahmed Hilali 
Published: June 2023

AbstractBackgroundDementia is a disorder distinguished by progressive and irreversible global cognitive impairment. About 45 million live with dementia globally, with an estimated increase to 75 million by 2030. Early recognition and diagnosis of dementia could enhance the efficiency of health care and quality of life. Hence, Medicare implemented a covered visit for assessing cognitive function for eligible patients as of January 2021. Previous studies described many tests and screening tools that clinicians can use to diagnose dementia. However, choosing a suitable test is solely left for clinicians to decide. We conducted a systematic review to provide an evidence‐based screening tool guide to facilitate dementia diagnosis.MethodA systematic review of studies published between 2010 and 2020 in English that targeted older patients. The search included multiple global databases; Cambridge Core, Cochrane Library, Google Scholar, PubMed, and Wiley online library. Keywords: “Dementia” “Screening” “Older people” “General Hospital” and “Inpatient''. Seven independent reviewers checked the studies to avoid bias.Result32 articles met the review criteria. More than ten dementia screening tools and tests were identified in the various clinical settings. However, the Mini‐Mental State Examination (MMSE) is the leading test with three times usage compared to other tests, followed by Montreal Cognitive Assessment (MoCA).ConclusionThe Mini‐Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) are the commonly used tools in diagnosing dementia. The review revealed other tests with a higher potential for early detection of dementia in various clinical settings. Thus, this is a call for clinicians to benefit and diversify the tools in diagnosing dementia and enrich the evidence‐based research with more confirmatory studies.
Large‐scale pQTL analysis of over 3,000 CSF samples
Authors: Western Daniel , Wang Ciyang , Timsina Jigyasha , Wang Lihua , Ruiz Agustin , Marquié Marta , Boada Mercè , de Rojas Itziar , Alvarez Ignacio , Aguilar Miquel , Pastor Pau , Sung Yun Ju , Cruchaga Carlos 
Published: June 2023

AbstractBackgroundExpression quantitative trait locus (eQTL) studies have been influential in identifying gene targets for many complex diseases. However, levels of mRNA often correlate poorly with levels of the protein that they encode, due to rates of degradation, translation, or alternative splicing, among other reasons. By correlating protein levels to genetic variation, pQTLs can elucidate a more accurate genetic architecture that underlies disease. While few large‐scale studies have considered cerebrospinal fluid (CSF) protein levels, CSF biomarker levels are one of the primary diagnostic tools in Alzheimer’s disease (AD), highlighting CSF’s relevance to brain aging and AD pathology. Here, we present CSF pQTL analysis of over 3,000 individuals.MethodWe generated CSF levels of 7,584 analytes for 3,065 samples using the aptamer‐based SOMAscan 7k platform. CSF levels of 4,884 analytes for additional 1,158 samples were also included. After stringent quality control, 3,107 unrelated European samples were selected for analysis. We performed pQTL analysis using a linear model with protein levels as the outcome variable, using a three‐stage study design: discovery, replication, and meta‐analysis. We performed colocalization of our pQTLs with eQTLs and GWAS loci, and compared our results to pQTLs from plasma studies to identify CSF‐specific pQTLs. We used Mendelian Randomization (MR) to identify proteins potentially causative for AD and other traits.ResultThis study represents the first use of the SOMAscan 7k platform in CSF, as well as the largest pQTL analysis of CSF to date. Of 3818 analytes currently tested in our discovery set, 1480 have at least one SNP associated with analyte level at p < 5×10−8. Analyses are ongoing.ConclusionWe previously performed pQTL analysis of CSF using the SOMAscan 1.3k platform, where 425 pQTLs were identified and 3 proteins (PTP1B, Siglec‐3, and SLAF5) were found through MR to be involved in AD risk, as well as 48 additional protein associations for other neurodegenerative diseases. This study expands on those findings by including 6,000 more proteins and much larger samples, allowing for greater power. This study will be vital for identifying novel proteins involved in AD and elucidate novel drug targets for AD and other neurodegenerative disorders.
Transient global amnesia recurrence: prevalence and risk factor meta‐analysis
Authors: Hernández Micaela A , Arena Julieta , Alessandro Lucas , Allegri Ricardo Francisco , Calandri Ismael Luis 
Published: June 2023

AbstractBackgroundTGA is an acute amnestic disorder with unclear pathophysiology. Although considered a benign phenomenon, the possibility of a recurrence is a major concern for the patient and their relatives. Our aim is: to identify the prevalence of transient global amnesia (TGA) recurrence and risk factors for it, to help clinicians counsel patients about it.MethodAccording to PRISMA guidance, we screened 1658 studies from MEDLINE, Lilacs and Embase databases, published from 1985 to April 2021, in English or Spanish. We included 36 observational case‐control and cohort studies that included patients with TGA according to Caplan’s or Hodges and Warlow’s diagnostic criteria. We performed a meta‐analysis with a random effect model for proportions and calculation of odds ratio for identified risk factors. Methodological quality was assessed according to the Newcastle‐Ottawa Scale.ResultWe identified 4514 TGA and 544 recurrence events (12.73%). Follow‐up had no impact on its variance. We identified a significant association between recurrence and sexual activity as a trigger, personal history of migraine and depression (OR 1,481 95%CI [1,0341; 2,1222] p = 0,04; OR = 2,0795 IC95% [1,3892; 3,1128] p = 0,003; and OR = 4,487195%CI[1,890; 10,651] p = 0,0288, respectively).ConclusionsThe analysis showed that about 1 out of 8 subjects may have recurrence, with an increased risk in case of history of migraine, depression or sexual intercourse prior to the event. Personal history of migraine and depression are associated with two and four times risk, with cortical spreading depression as a possible pathophysiological mechanism.
Graph deep neural network for discovery of multi‐omic subnetworks related to Alzheimer’s Disease
Authors: Raj Yash , Xie Linhui , Varathan Pradeep , Naidu Divya Sagar Vella , He Bing , Nho Kwangsik , Risacher Shannon L. , Saykin Andrew J. , Salama Paul , Yan Jingwen 
Published: June 2023

AbstractBackgroundThe recent multi‐omics analysis explores the integration of multiple biological data types, which can suggest a more comprehensive view of biological processes underlying complex diseases, such as Alzheimer’s disease (AD). Various biological networks have been leveraged as prior knowledge with attempt to discovery of more interpretable multi‐omics markers [1]. We applied a new graph neural network to take advantage of this rich prior knowledge together with multi‐omics data for identification of system‐level AD markers.MethodWe used GWAS genotype, RNA‐Seq gene expression, and protein expression data from the ROS/MAP Project. In total, 133 subjects with full set of ‐omics features were included in the study (Table. 1). There are 1,751 functionally connected ‐omics features in the prior biological network, including 186 peptides, 743 unique genes, and 822 single‐nucleotide polymorphisms (SNPs). Multi‐omic network of functional connections between SNPs, genes and proteins were created based on the REACTOME database, SNP‐gene mapping relationship and the SNP2TFBS database [2]. This network was applied to guide the architecture design of the neural network. The input layer consists of all ‐omics features. A biological drop‐connect layer of Varmole was set as for transparent layer that duplicate of protein and gene nodes in the input layer [3]. Links between input layer and transparent layer were added based on the prior multi‐omic network. In addition, we also added self‐connection links for all genes and proteins.ResultOur proposed integrated multi‐omic DNN largely outperforms other state‐of‐the‐art models (Table. 2). With cut‐off at 0.00001, 538 features were identified as discriminative. Three largest connected components were observed with more than 30 nodes (Fig. 1), among which 28 SNPs, 309 genes and 31 proteins form the largest connected component. Top hub nodes are proteins PIK3R1, GRB2, FYN. Shown in Fig. 2 is the list of top REACTOME pathways enriched by genes and proteins in the largest connected component [4].ConclusionIntegrated multi‐omic DNN identified multi‐mic subnetworks with great predictive power, providing critical functional connections contributing to AD. [1] Xie, et al., BIB, 2021. [2] Fabregat et al., NAR, 2018. [3] Nguyen, et al., Bioinformatics, 2021. [4] Kanehisa, et al., NAR, 2000.
The correction of health misconceptions in older adults with cognitive impairment
Authors: DeCaro Renee , Marin Anna , Schiloski Kylie A , Hajos Gabor P , Turk Katherine W , Domenico Alberto Di , Palumbo Rocco , Budson Andrew E 
Published: June 2023

AbstractBackgroundThe use of a refutational technique (e.g., “myths” versus “facts”) to correct health‐related misconceptions is ubiquitous, yet little work has addressed whether older adults’ cognitive status influences misconception correction. We examined belief in COVID‐19 misconceptions in older individuals with and without cognitive impairment, and whether a simple refutational technique would be effective at reducing misconception belief in these populations.MethodOlder adults (N = 62, 36 Males) took a pretest of 10 COVID misconceptions (from the CDC) over the telephone. Participants received immediate corrective feedback (i.e., the correct answer and an explanation of the correct answer). Individuals took a surprise retest after 25 minutes and again one week later. Cognitive status was assessed with a telephone‐administered neuropsychological battery and Montreal Cognitive Assessment‐Blind (MoCA‐Blind). Cognitive status groups were compared on misconception belief and corrections. Exploratory analysis correlated corrections with performance on the neuropsychological battery and demographics.ResultsOlder adults (M = 75.26 years, SD = 6.61) were split into a cognitively impaired group (N = 28) and an unimpaired group (N = 34) based on recommended cutoffs for the MoCA‐Blind; these groups did not differ in terms of age or education. Impaired older adults endorsed more misconceptions on the pretest than unimpaired older adults, t(60) = 3.61, p < .001, d = .92. Importantly, both groups made equivalent corrections from the pretest to the first retest (p = .439, d = .21) and maintained those corrections across the one week delay (p = .907, d = .03). Only memory errors on the recognition portion of the neuropsychological battery were associated with performance gains (r = ‐ .33, p < .01). Individuals who made more false alarms (i.e., incorrectly recognizing a word as having been presented) were less likely to correct misconceptions.ConclusionA refutational technique can be effectively used to correct health‐related misconceptions in even older adults who are cognitively impaired. Moreover, this easily‐implementable technique was effective for older adults of all ages and education levels. Rather, recognition memory errors alone were important in the correction of misconceptions.
Deformation‐based morphometry analysis shows early degeneration in Nucleus basalis of Meynert in Alzheimer’s disease
Authors: Shafiee Neda , Fonov Vladimir S , Dadar Mahsa , Spreng R. Nathan , Collins D Louis 
Published: June 2023

AbstractBackgroundNucleus basalis of Meynert (NbM) is the main source of cholinergic projection to the cerebral cortex, including entorhinal cortex (EC). Both cholinergic cells of NbM and their receptive targets in EC show degeneration during early stages of Alzheimer’s disease (AD). While precise delineation of NbM region on T1w scans is difficult due to limited spatial resolution and contrast, we sought to quantify the degeneration of NbM along the disease trajectory and confirm recent studies suggesting that NbM degeneration happens before degeneration in the EC using deformation‐based morphometry (DBM).MethodData included MRI scans of 1473 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. Resolution was increased to 0.5 mm isotropic voxel‐size before non‐linear registration to an ADNI‐based unbiased symmetric template. The resulting deformation fields were used to compute the Jacobian determinant map for each subject as a proxy for local volume. NbM and EC masks were mapped to our high‐resolution template and mean determinant values inside these masks were calculated for groups with different baseline diagnosis, and sex‐ and age‐corrected z‐scores were calculated. Two‐sample t‐tests were then used to compare the scores between different groups.ResultFigure 1 shows the mean DBM score of both NbM and EC regions for Normal Controls (CN), subjects with early‐ and late‐stage mild cognitive impairment (EMCI and LMCI) and subjects with probable AD dementia. Results corrected for multiple comparisons showed a significant difference between CN and both EMCI and LMCI for left and right NbM. A significant difference was also observed between EMCI and LMCI in left NbM (p‐value = 0.0024). Z‐scored EC volumes did not show a significant difference between CN and EMCI groups; However, results from EMCI and LMCI differ significantly in both hemispheres. We also observed the expected differences between each group with AD in both NbM and EC (P<0.001).ConclusionOur results show that while macroscopic changes in EC emerge as MCI subjects advance toward the later stages, NbM degeneration starts sooner, as early as preliminary stages of MCI. This points to MRI‐based measurements of NbM as potential biomarkers for early detection of AD and as a marker of disease burden.