bluuebunny/crossref_metadata_2025_split huggingface dataset:
A mobile application (chatbot) to automate delivery of sleep‐dependent memory tasks
Authors: Lam Aaron Kin Fu , D'Rozario Angela , Bradford Dana , Ireland David , Fripp Jurgen , Simonetti Simone , Mills Peta , Naismith Sharon L 
Published: December 2023

AbstractBackgroundPrior work has shown that sleep is critical for memory through a process called sleep‐dependent memory (SDM). However, SDM appears to diminish with age, and may be further compromised in those with mild cognitive impairment (MCI) and dementia. Typically, studies examining SDM have been small, often restricted by the need for administration in the sleep laboratory. Consequently, understanding of SDM decrements in MCI has been limited, hindering targeted developments of treatments for SDM. We aimed to develop an app‐based ‘chatbot’ for measuring SDM, allowing data to be obtained at scale and in response to treatments without the need for sleep laboratory attendance.MethodAn initial prototype of the chatbot was developed for Android and iOS utilising a 32‐item word‐pair task demonstrated to be suitable for people with MCI. The task delivery included pre‐sleep learning and memory and post‐sleep recall. To reduce content‐specific practice effects, an alternative word‐pair list was included for repeat testing.Co‐design focus group methodologies were used to ascertain usability and acceptability for older people with MCI who attended a memory clinic. Participants (N = 11) attended one of two 90‐minute focus groups in which semi‐structured questions probed technology use and gathered feedback for app improvement.ResultsParticipant feedback validated that core useability and content features of the chatbot were appropriately developed for the specific use of older adults at risk of dementia. Participants were comfortable with the chatbot obtaining demographics and habitual sleep and wake times and providing notifications for completing the task pre‐ and post‐sleep. No negative feedback was received on the layout of the instructions for the test or delivery of the word‐pairs task. Suggested improvements included ability to defer testing and customise notifications, and provision of performance feedback or rewards for compliance. This information was used to further develop the chatbot.ConclusionThe SDM chatbot app will now undergo further clinical and psychometric testing to determine how performance changes in relation to, rest‐activity rhythms, clinical features, and sleep and dementia biomarkers.
Reproductive span as a modifier of the association between AD biomarkers and cognitive decline in cognitively unimpaired women
Authors: Milà‐Alomà Marta , Brodu Margot M Casals , Brugulat‐Serrat Anna , Sánchez‐Benavides Gonzalo , Escalante Armand González , Brinkmalm Ann , Kvartsberg Hlin , Shekari Mahnaz , Arenaza‐Urquijo Eider M , Fuentes‐Julian Sherezade , Deulofeu Carme , Grau‐Rivera Oriol , Kollmorgen Gwendlyn , Carboni Margherita , Ferretti Maria Teresa , Gispert Juan Domingo , Ashton Nicholas J. , Zetterberg Henrik , Blennow Kaj , Suárez‐Calvet Marc 
Published: December 2023

AbstractBackgroundEstrogens exert neuroprotective effects and regulate cognitive functioning and memory, and reduction of estrogen levels during menopause is proposed as a contributor to the increased risk for Alzheimer´s disease (AD) observed in women. However, previous results on the effects of estrogen exposure on AD biomarkers and risk of cognitive decline are conflicting.We aimed to study whether reproductive span, as a proxy of endogenous estrogen exposure, influences AD‐related biomarkers and their association with cognitive change in cognitively unimpaired (CU) women.MethodWe studied 125 CU women with CSF biomarkers, amyloid PET (Centiloids), and longitudinal cognitive measures (3 years’ follow‐up) (Table 1). CSF biomarkers were measured with Roche NeuroToolKit, Elecsys® immunoassays, or IP‐MS. We used longitudinal change in PACC and in a memory composite as cognitive outcomes. Reproductive span was calculated by subtracting the age at menarche from the age at menopause. ANCOVA models adjusted by age, education, and time between visits were used to test the main effect of reproductive span on biomarkers (baseline and longitudinal change), and the interaction between reproductive span and biomarkers with cognitive change as the outcome.ResultReproductive span was not associated with baseline levels or longitudinal change of AD biomarkers. Reproductive span modified the association of Aβ PET Centiloids with change in PACC, and the association of Centiloids, CSF p‐tau181, SNAP‐25, synaptotagmin‐1, and ɑ‐Synuclein with change in the Memory Composite (Figure 1). Specifically, higher baseline levels of these biomarkers were associated with cognitive decline only in women with a shorter reproductive span. Reproductive span also modified the association between longitudinal change in CSF sTREM2, IL‐6, and NfL and cognitive change. In women with a shorter reproductive span, increases in these biomarkers were associated with greater memory declines. In women with a longer reproductive span, an increase in CSF sTREM2 was associated with improved memory performance at follow‐up (Figure 2).ConclusionIn women with a shorter reproductive span, higher baseline levels of Aβ deposition and tau and synaptic CSF biomarkers are associated with a steeper decline in memory. Our results suggest that longer estrogen exposure contributes to resilience against AD‐related pathology.
Perceived social status modifies associations of plasma Alzheimer’s disease biomarkers on cognitive performance among Foreign Born Hispanic/Latinos
Authors: Diminich Erica D , Farina Mateo , Miller Joshua D , Mindt Monica Rivera , Scott Stacey B , Ailshire Jennifer , Clouston Sean A.P. 
Published: December 2023

AbstractBackgroundForeign born (FB) adults from Latin America are projected to account for the largest proportion of the aging immigrant population in the United States (U.S.) Migration related stressors may increase vulnerability for impairments of stress regulatory systems that are vital in maintaining brain health. We assessed how subjective social status, an individual’s perceived sense of standing in society may be associated with brain health and cognitive performance among community dwelling FB Hispanic/Latinos.MethodAnalyses included 133 FB adults (ages 22‐85) with beta‐amyloid (Aβ42, Aβ40), phosphorylated tau (p‐tau181), neurofilament light (NfL), glial fibrillary acidic protein (GFAP), cardiometabolic, sociodemographic, sociocultural data and concurrent cognitive scores, assessed with the NIH Cognition Toolbox. Participants used the McArthur Scale, a 10‐rung ladder representative of social status in the U.S., to indicate their standing relative to all others. Descriptive statistics were calculated to examine differences by perceived social status tertiles, (i.e., Low (1‐3), Average (4‐5), High (6‐10). Cross sectional multivariable linear regression models estimated the independent effects of biomarkers on outcome scores for episodic memory, processing speed, and total cognition. Model one included age, sex. Model two added education, income, employment, and health insurance. Model three adjusted for covariates in model two and included biological indicators associated with brain health (i.e., glucose, systolic blood pressure, triglycerides). Model four included nativity factors (i.e., age of migration, years of acculturation). An interaction term between plasma biomarker and perceived status examined whether perceived status modified the relationship between plasma biomarker and cognitive outcome.ResultOver 27.1% of FB Hispanic/Latinos reported low perceived status. Compared to those with average and high status, participants categorized as low status, reported fewer years of residence in the U.S. (P = 0.020) In multivariable adjusted models, perceived status modified associations between GFAP (P<0.001) and NfL (P<0.001) on composite scores of total cognition (P<0.001) and NfL (P<0.001) and Aβ42/40 (P<0.0001) on episodic memory and processing speed (P<0.001).ConclusionPerceived status among undocumented FB Hispanic/Latino adults was associated with lower scores on cognitive tasks sensitive to stress, age related decline and neurological impairments. Future studies should explore biological mechanisms through which perceived status may influence brain health and cognitive aging.
Cerebrospinal fluid metabolome‐wide association study of Alzheimer’s disease provides insight into molecular pathways
Authors: Reus Lianne M. , Boltz Toni , Francia Marcelo , Bot Merel , Loohuis Loes Olde , Teunissen Charlotte E. , Ophoff Roel , Tijms Betty , van der Lee Sven J , Visser Pieter Jelle , van der Flier Wiesje M. , Ramesh Naren 
Published: December 2023

AbstractBackgroundMany genetic risk variants have been identified for Alzheimer’s disease (AD), but their functional consequence on molecular pathways are unclear. Quantitative trait loci (QTL) studies help elucidate the functional effect of genetic variance on (neuro)biological processes. The understanding of AD mechanisms has been limited due to the relative inaccessibility of in vivo brain tissue and its surroundings. In this study, we integrated genetic and metabolomics cerebrospinal fluid (CSF) data, to understand how AD risk variants influence neurobiological processes.MethodWe performed a genome‐wide mQTL study on 5,543 CSF metabolite levels using data from 977 subjects (age 52.7±16.6 years, 63.8%female) from the Amsterdam Dementia Cohort (n = 487; 220 controls, 87 mild cognitive impairment, 180 AD‐type dementia) and the Utrecht cohort (n = 490 controls). We measured CSF metabolites with three platforms: GC‐TOF MS (primary metabolism, 393 metabolites), CSH‐QTOF MS/MS (complex lipids, 3,532 metabolites), and HILIC‐QTOF MS/MS (biogenic amines, 1,618 metabolites). Association signals between genetic variants and CSF metabolite levels were tested using linear regression, adjusted for principal components, age, sex and site (Amsterdam/Utrecht) using a Bonferroni‐corrected genome‐wide significance threshold (5.0e−8 /754 independent CSF signals = 6.0e−11). To identify metabolites with predicted CSF levels associated with AD, we integrated metabolite summary statistics with AD summary statistics (Kunkle et al., 2019; Bellenguez et al., 2022), using a metabolome‐wide association study (MWAS) approach (FUSION software).ResultWe identified 89 genome‐wide CSF mQTLs, including 89 independent loci for 62 CSF metabolite levels. Most mQTLs were biogenic amines (81), followed by mQTLs for the primary (5) metabolism and complex lipids (3) (Figure 1). MWAS results included 24 metabolite‐AD associations with P<0.05. The strongest associations included variants proximal to the CANX gene with unannotated CSF metabolite 1.09_397.32 (PBellenguez = 2.4e−6; PKunkle = 3.4e−3), and CCDC124 variants with 8.76_225.06 (PBellenguez = 2.9e−3; PKunkle = 2.8e−5) (Figure 2).ConclusionWe identified novel metabolite‐AD risk associations, including CANX and CCDC124 with unknown CSF metabolites. In future work we aim to identify these CSF metabolites using raw spectra and intensity data. This study shows that the multi‐modal integration of genetics with CSF metabolomics helps in the functional interpretation of genetic variance, and could therefore serve as useful approach for other brain‐related disorders.
Clinical Variables Contributing to Identification of Mild Cognitive Impairment Individuals With Defined ATN Profile
Authors: Marcolini Sofia , Mondragon Jaime , Dominguez‐Vega Zeus T. , Maurits Natasha M. , De Deyn Peter Paul ,   Alzheimer’s Disease Neuroimaging Initiative
Published: December 2023

AbstractBackgroundThe framework globally used to classify Alzheimer’s Disease stages for research purposes includes three core biomarkers: A) Aβ burden; T) tau pathology; and N) neuronal injury. A lack of consensus exists in linking cognitive and behavioral tests used in everyday clinical practice to biological stages of dementia as defined by the ATN classification. The aim of the current study is to identify the clinical variables that best classify individuals into biologically defined cognitive profiles.MethodA total of 751 subjects, from the Alzheimer’s Disease Neuroimaging Initiative cohort, were categorized into seven ATN groups: 112 cognitively unimpaired with ATN‐; 46 cognitively unimpaired with ATN or AT+; 65 cognitively unimpaired with T, N or TN+; 128 amnestic Mild Cognitive Impairment (aMCI) with ATN‐; 223 aMCI with ATN or AT+; 94 aMCI with T, N or TN+ and 83 dementia with ATN or AT+. The groups for which the features exhibited differences during data exploration were classified employing 28 cognitive, behavioral, and demographic features using a supervised machine learning algorithm, specifically, a random forest classifier in combination with a synthetic oversampling technique.ResultWe found that the selected features were not able to distinguish between all seven groups and in particular between the three cognitively unimpaired groups. Therefore, classification was only performed for the three ATN‐defined aMCI groups achieving 58% overall accuracy. The Logical Delayed Recall was the most relevant feature (explaining 17% of the variance), followed by the Alzheimer’s Disease Assessment Scale‐Cognitive Subscale 13 (16%), Everyday Cognition Informant (8%), and Alzheimer’s Disease Assessment Scale 4 (8%). Marital status, Everyday Cognition Patient and sex were not relevant (0%).ConclusionCognitive and behavioral tests were not able to accurately distinguish cognitively unimpaired individuals with different biological profiles. Although accuracy could be improved, our first results showed that a test of delayed memory, one of general cognition, and one on activities of daily living are relevant variables for distinguishing between patients with aMCI and different biological profiles. During diagnosis, treatment monitoring, or in research contexts, these variables might be informative in differentiating the three ATN‐defined aMCI profiles, especially when biomarkers are not available.
Associations between ruminative brooding and white matter change amongst healthy middle‐aged and older adults
Authors: Solé‐Padullés Cristina , Cattaneo Gabriele , Marchant Natalie L , Demnitz‐King Harriet , Cabello‐Toscano María , Mulet‐Pons Lídia , Solana Sánchez Javier , Tormos‐Muñoz Josep Mª , Bargalló Núria , Abellaneda‐Pérez Kilian , Pascual‐Leone Alvaro , Bartrés‐Faz David 
Published: December 2023

AbstractBackgroundRepetitive Negative Thinking (RNT) includes negative thoughts about the future (worry) and past (ruminative brooding). RNT has been associated with Alzheimer’s disease (AD) pathology (Marchant et al. Alzheimers Dement. 2020;16(7)) and different patterns of functional connectivity of the triple network of attention, namely, the default mode, executive control and anterior salience networks (Solé‐Padullés et al. Front Aging Neurosci. 2022;14). However, the association between RNT and white matter microstructure is unclear (Demnitz‐King et al. Psychiatry Res Neuroimaging. 2021;316) and no existing studies have examined this association longitudinally among non‐clinical adults.MethodHealthy adults (age range: 50‐70, 51.2% women) from the Barcelona Brain Health Initiative (Cattaneo et al. Front Aging Neurosci. 2018 11;10) completed the Perseverative Thinking Questionnaire (PTQ), Rumination Response Scale (RRS), and Penn‐State Worry Questionnaire (PSWQ) at baseline to measure RNT levels. Participants underwent a magnetic resonance imaging (MRI) with T1 and T2‐weighted acquisitions to assess volume of white matter hypointensities (WMH) at baseline (N = 588) and two years later (N = 425). Change in WMH was computed taking into account time interval between scans. Stepwise linear regression analyses were conducted to investigate associations between change in WMH and baseline age, sex, PTQ, PSWQ and RRS subscale scores (brooding, reflection and depression).ResultBaseline age (t = 3.71, p<0.0001) and brooding (t = 2.82, p = 0.005) were associated with increased WMH across scans (see partial regression plots, Fig 1A/B). No cross‐sectional associations were observed between volume of WMH and RNT‐related variables.ConclusionBrooding was associated with increase of WMH in healthy adults. Brooding, a maladaptive form of emotion regulation, enhances repetitive focus on one’s distress and is associated with altered connectivity of attentional networks and greater asymmetry of the Superior Longitudinal Fasciculus in depressed adults (Pisner et al. Neuroimage Clin. 2019;24). Our results are of importance considering that: WMH correlate with CSF‐amyloid in cognitively unimpaired older adults (Wei et al. Brain Behav. 2019;9(12)) and this is the first longitudinal study focusing on white matter change as related to psychological variables linked to cognitive decline and AD‐related pathology. The putative impact of psychological factors on brain integrity can be detected even at sub‐clinical levels and in earlier stages within the dementia continuum.
An exploratory pilot study on diffusion MRI measurement of cortical microstructural neurodegeneration for the assessment of dementia in a Japanese hospital setting
Authors: Ridgway Gerard R , Nakajima Takashi , Torso Mario , Valotti Michele , Hardingham Ian , Ehsan Omar , Chance Steven A 
Published: December 2023

AbstractBackgroundThe use of diffusion MRI (dMRI) to assess cortical microstructure has demonstrated promise for measuring neurodegeneration in Alzheimer’s disease (PMID:33174658, PMID:36281682) and frontotemporal dementia (PMID:32641807, PMID:34686217) using retrospective research datasets. The ultimate translation of research findings to clinical practice requires prospective studies in hospital settings. A pilot study at the National Hospital Organization, Niigata, was designed and successfully delivered.MethodThe study was registered on Oct 5th 2021 (jRCT1032210367). Scanning took place between Oct 13th 2021 and June 30th 2022, on a 1.5T Philips Ingenia. MRI data was transferred using a secure cloud gateway (Cimar). A total of 10 healthy controls (HC), 10 Alzheimer’s disease (AD) patients, and 5 frontotemporal dementia (FTD) patients were recruited.Structural (3D T1‐weighted) and dMRI (2mm isotropic, 32 directions at b = 1000 s/mm2) scans were used to calculate cortical mean diffusivity and three neuropathologically‐inspired cortical diffusivity measures: the angle between the radial minicolumnar direction and the principal diffusion direction (AngleR); the principal diffusion component parallel with the minicolumns (ParlPD), and the diffusion components perpendicular to the minicolumns (PerpPD+). Metrics were also summarized over AD signature regions (Ridgway et al., CTAD 2022).ResultOf the n = 25 cases, 18 had clear clinical diagnoses after neurological and radiological assessment, while 7 were more complex (including focal bleeding, focal ischemia, meningioma, supra‐sellar tumour). Characteristics are given in Table 1.Figure 1 plots two whole‐brain measures: PerpPD+ and AngleR. A threshold of PerpPD+ > 1.325 has 100% sensitivity to the 8 clear AD cases, with 86% specificity for 7 controls vs AD. Results were less clear for FTD using whole‐brain measures alone.The Cohen’s d effect size for clear AD versus clear HC was 2.82 using whole‐brain PerpPD+. Using signature regions (Figure 2b) improved separation to d = 3.08 for PerpPD+, compared to d = 1.87 for the cortical thickness signature (Figure 2a).ConclusionThe pilot study demonstrated practical feasibility and good performance for distinguishing AD from HC using cortical diffusivity measures acquired at the 1.5T field‐strength common in hospitals in Japan. Future work will investigate FTD signature regions. A larger multicentre study assessing diagnostic accuracy using additional AD biomarkers is warranted.
Yerba mate (Ilex paraguariensis) consumption and risk of cognitive impairment: a prospective study project
Authors: Guillen Jonathan Cubas , Gatto Emilia , del Hierro Xavier Merchan , Rojas Galeno , Melcon Carlos Mario , Eizaguirre Barbara , Gonzales Claudio , Crotti Beatriz , Tribbia Liliana Teresita , Gilbert Afra , Taravini Irene 
Published: December 2023

AbstractBackgroundAging is the main risk factor for neurodegenerative diseases, such as Alzheimer’s disease (AD) dementia. Yerba mate (YM) tea or mate Ilex paraguariensis is an infusion widely consumed in Argentina and other South American countries such as Brazil, Paraguay, and Uruguay. Experimental studies suggest a YM antioxidant and protective effect against amyloid deposition in AD. Previously, our group and others identified an inverse association between YM consumption and Parkinson’s Disease. The aim of this project is to evaluate a potential association between YM consumption and the risk of cognitive impairment development.MethodTwo different stages were designed. Stage I is a descriptive study designed. Adult patients fulfilling mild cognitive impairment criteria (MCI) evaluated at the Sanatorio de la Trinidad Mitre between January 2021 and December 2022 will be included. Each participant or their caregiver will be invited to complete a survey about lifestyle and nutritional information, including YM consumption. Stage II is a case‐control study. Patients with MCI will be distributed by severity and subtypes of MCI. The control group will be constituted by individuals with normal cognitive evaluations matched by age, sex and educational level who agree to answer the afore mentioned survey. All data will be recorded in an anonymized electronic database and statistical analysis will be carried out. Project duration is estimated at 12 months for each stage.ResultResults from stage I will describe epidemiological and clinical characteristics of patients with MCI and the frequency and duration of YM consumption in this group of patients, as well as any potential correlation between neuropsychological tests and YM consumption. Results from stage II are expected to identify an inverse association between the magnitude of YM consumption and MCI.ConclusionObservational evidence of the association between YM consumption and MCI might be the first step to develop experimental studies using Ilex paraguariensis in neurodegenerative cognitive disorders.