bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of lifestyle factors on Alzheimer’s disease symptoms in adults with Down syndrome
Authors: Schworer Emily K , Zammit Matthew D , Handen Benjamin L , Okonkwo Ozioma C , Hom Christy L. , Ances Beau , Christian Bradley T. , Hartley Sigan L 
Published: January 2025

AbstractBackgroundLifetime risk for symptomatic Alzheimer’s disease (AD) in people with Down syndrome (DS) is 90%, with the age of onset of symptomatic AD ranging widely. Identifying resiliency factors related to a later age of symptoms is of critical importance for the DS community. This study investigated lifestyle factors hypothesized to moderate the association between amyloid‐beta (Aβ plaques) and AD symptoms in adults with DS.MethodParticipants were 63 adults with DS (M age = 40.21 years, SD = 7.73). The majority of participants were cognitively stable (84.1%), 6.3% had dementia, and 9.6% had mild cognitive impairment. Participants completed an Aβ PET scan using [11C] Pittsburgh Compound‐B (PiB) and Aβ trajectories were modeled using a sampled iterative local approximation algorithm to assign each individual a chronicity value, centered at 18 Centiloids. Participants completed the modified Cued Recall Test (mCRT) and caregivers completed the National Task Group‐Early Detection Screen for Dementia (NTG‐EDSD). Caregivers were also asked to rate the amount of time the adult with DS participated in cognitive, social, and vocational activities. Adults with DS wore an Actigraph accelerometer for 7 days to assess daily step count. A lifestyle composite score was created.ResultTwo moderation tests were run, with Aβ chronicity as the predictor, AD symptoms (mCRT or NTG‐EDSD) as the dependent variable, and lifestyle composite as a moderator. There was a significant interaction of lifestyle composite X chronicity on mCRT, t = 3.03, p = .004 and NTG‐EDSD, t = ‐3.29, p = .002. Participants who engaged in lifestyle activities for less time than average experienced a greater effect of chronicity on mCRT (Figure 1) and NTG‐EDSD (Figure 2).ConclusionLifestyle activities moderated the association between Aβ chronicity and AD symptoms. Participants who had active lifestyles with more cognitive, social, physical, and vocational activities evidenced fewer AD symptoms (i.e., less cognitive impairment) given similar Aβ chronicity values than participants who engaged in fewer activities. This study was limited to cross‐sectional associations. Future longitudinal research should tease out time‐ordered effects. Modifiable lifestyle factors may allow adults with DS to maintain cognitive functioning for longer in the face of early AD pathology.
Integrating multi‐omics data for target and biomarker discovery
Authors: Arnold Matthias ,   the Alzheimer’s Disease Metabolomics Consortium
Published: January 2025

AbstractBackgroundDespite recent breakthroughs, Alzheimer’s disease (AD) remains untreatable. In addition, we are still lacking robust biomarkers for early diagnosis and promising novel targets for therapeutic intervention. To enable utilizing the entirety of molecular evidence in the discovery and prioritization of potential novel biomarkers and targets, we have developed the AD Atlas, a network‐based multi‐omics data integration platform. Through recent extensions, the AD Atlas provides a comprehensive database of high‐quality multi‐omics data that can be utilized for hypothesis‐free ranking of molecular markers and disease modules, as well as prioritization of potential novel targets and drug repositioning candidates.MethodWe developed several graph‐based analysis tools from proximity searches to applications of artificial intelligence that can be applied to the AD Atlas. For prioritization of potential targets and biomarkers, we derived several network‐based metrics to score ‐omics entities for disease relevance by not only assessing evidence for a single marker but also for its functional neighborhood in the AD Atlas network. For disease module identification, we employed graph representation learning coupled with unsupervised clustering to extract functional modules as defined by the network structure. Finally, we propose an ensemble approach that enables weighted aggregation of drug repositioning predictions from both signature‐based and network‐based algorithms.ResultWe demonstrate that the AD Atlas enables complex computational analyses for target and biomarker discovery and prioritization as well as in silico drug repositioning in AD. Using the integrated scores for prioritizing single targets and biomarkers for AD, we observe significantly higher relevance scores for genes that have been nominated as promising targets by the AMP‐AD consortium. We further find that extracted disease modules are enriched for specific AD‐relevant biological domains and can be ranked by disease relevance using similar graph‐based metrics. Finally, we demonstrate that drug repositioning candidates are significantly enriched for compounds that were or are being tested in clinical trials for AD.ConclusionHigh‐quality, multi‐omics networks, such as the AD Atlas, enable exploitation of large‐scale heterogeneous data through computational applications for target, biomarker, disease module, and drug repositioning candidate discovery and prioritization.
Passively collected smartphone behaviour as a reliable and feasible measure for global cognition in Alzheimer’s Disease
Authors: Keijzer Matthijs J. , van Liere Mariska N. , Van De Glind Marie‐Christine M. A. B. J. , Muurling Marijn , de Boer Casper , Redeman Erwin G. M. , Meijer Kim A. , van der Flier Wiesje M. , Sikkes Sietske A. M. 
Published: January 2025

AbstractBackgroundWith the increasing number of potential interventions for Alzheimer’s Disease (AD), there is a growing need to detect meaningful cognitive changes early in the disease. Frequent passive monitoring of smartphone behaviour, such as typing speed and precision, can give insight into the cognitive changes in AD. In the ‘A personalized Medicine Approach for AD’ (ABOARD)‐project we investigated the reliability and validity of typing behaviour to monitor cognition in people with and without AD.MethodIn this prospective study we included forty participants (Healthy controls (N = 9), Subjective Cognitive Decline (N = 11), Mild Cognitive Impairment (N = 10) and dementia due to AD (N = 10)). Typing behaviour and sensor data during typing were collected for 28 days using a smartphone application (Neurokeys). Eight keystroke dynamics (KD) features were calculated (Figure 1a), standardized into z‐scores, and averaged over time to create a single score per feature. Test‐retest reliability was assessed by intra‐class correlations between the first and last 14 days. Concurrent validity was explored with correlations between the Mini‐Mental State Examination (MMSE), KD features and movement in three orthogonal directions (Figure 1b).ResultsAll participants completed the study with an average of 640±413 keystrokes per day (Table 1). The ICC for all features range from 0.62 to 0.88, indicating good reliability. Most KD features show moderate to strong associations with MMSE performance, including the time between characters (flight time, r = ‐0.71, p<0.001), the time between the spacebar and a next character (after‐spacebar pause, r = ‐0.65, p<0.001) and the time between the backspace and a next character (post‐correction slowing, r = ‐0.63, p<0.001, Figure 2). Movement of the phone in the X (r = 0.39, p<0.05) and Z direction (r = 0.38, p<0.05) is also correlated with the MMSE (Figure 2).ConclusionThis study provides a first indication that smartphone behaviour can be a useful and reliable tool for monitoring cognition in AD. The results suggest that individuals with worse global cognition type slower, require more time to correct an error and take more time to initiate the next word, while individuals with better cognition show more movement during typing. A larger validation study can help to confirm the potential of smartphone‐derived AD digital biomarkers.
Presynaptic mechanisms of impaired long term potentiation of lateral entorhinal cortex input to CA1 in the PS19 mouse model of tauopathy
Authors: Thangavel Mohankumar , Tian Chengju , Reyes Isabel , Masurkar Arjun V. 
Published: January 2025

AbstractBackgroundHow tauopathy disrupts direct entorhinal cortex (EC) inputs to CA1 and their plasticity is understudied, despite its critical role in memory. Moreover, dysfunction of lateral EC (LEC) input is less clear, despite its relevance to early Alzheimer’s disease pathogenesis. Here we examined how tau impacts long‐term potentiation (LTP) of LEC→CA1 input in a transgenic model of tauopathy.MethodAcute hippocampal slices were prepared from PS19 and WT mice (8‐10 mo. old, M/F) in which LEC had been injected with an AAV expressing channelrhodopsin ChR2. Ex vivo recordings were achieved with blue LED light to excite LEC axons and an extracellular field electrode in stratum lacunosum moleculare (SLM) of distal CA1 to record field responses. Input‐output curves were established using 25‐100% LED power for field postsynaptic excitatory potentials (fEPSPs) with inhibition blocked (GABAA: 2mm SR95531, GABAB: 1mm CGP55845). LTP of fEPSPs was elicited after a 10” baseline using an LED theta burst stimulation (TBS). Paired pulse ratio (PPR) of fEPSPs was elicited with LED stimulation of 2 pulses at 20Hz. Fluorescence immunohistochemistry (IHC) was performed in separate mice using antibodies to N‐type calcium channels.ResultAll results are based on n = 4‐8/sex/genotype. The LEC fEPSP was of reduced magnitude in female PS19 versus WT mice, while unchanged across genotype in male mice. TBS induced a late‐onset LTP (147% at 45”) of the LEC fEPSP in female WT mice, which was significantly reduced in female PS19 mice (p = 0.0051). There was no LTP reduction in male mice. LTP in female WT mice was associated with a PPR reduction that was reversed by the addition of the N‐type calcium channel blocker w‐conotoxin GVIA, all of which did not occur in PS19 mice (p<0.0001). PPR was appropriately reduced in male mice across genotype. IHC of N‐type calcium channels showed reduced fluorescence in the SLM of female PS19 mice versus WT.ConclusionIn PS19 mice, the impact of tau on LEC→CA1 input is sex‐dependent, with reduced LEC‐driven excitation and LTP only in female mice. A reduction in presynaptic N‐type calcium channels in PS19 mice may serve as a presynaptic mechanism for the reduced plasticity.
Gait Speed Reflects Cognitive Impairment in Early AD
Authors: Wu Che‐Sheng , Chou Chia‐Ju , Chang Chih‐Ting , Lee Chia‐Ying , Fang Chuang Yi‐ , Chiu Yen‐Ling , Liu Yi‐Chien 
Published: January 2025

AbstractBackgroundGait performance has been found to be an effective method for screening cognitive impairment in elderly. Nevertheless, the efficacy of utilizing gait speed as a marker for monitoring cognitive changes remains incompletely substantiated.MethodFrom 2021 to 2023, we recruited 104 participants from the memory clinic of Cardinal Tien Hospital in Taipei, Taiwan. Individuals with organic brain lesions, joint diseases, or any other factors affecting gait speed were excluded. All participants underwent comprehensive neuropsychological tests and the Short Physical Performance Battery (SPPB) to assess physical function. The clinical diagnosis of Alzheimer disease (AD) was established using the 2021 NIA‐AA criteria. Global cognitive impairment was determined using the Cognitive Abilities Screening Instrument (CASI), and gait speed was measured through a 4‐meter walking test derived from the SPPB. Cognition in specific domains was assessed using various tests, such as the Logical Memory Test (LM) from the Wechsler Memory Scale 3rd edition, the Color Trail Making Test (CTT), and the Verbal Fluency Test (VF).ResultThis study revealed a significant difference in SPPB score (11.03 vs. 12.64, p < 0.001) and gait speed (0.78 vs. 0.95 m/s, p = 0.005) between the early AD and normal groups. Furthermore, a positive correlation was observed between gait speed and CASI scores (r = 0.421, p < 0.001) in the early AD group, while no such effect was observed in the normal group (p = 0.24). In multiple regression analysis, our study demonstrated that CASI was better predicted by gait speed (p = 0.001) rather than age, gender, or years of education. LM (r = 0.393, p = 0.001), CTT (r = ‐0.449, p = 0.001), and VF (r = 0.349, p = 0.004) also revealed a significant correlation with gait speed in the early AD group.ConclusionGait speed positively correlated with cognitive impairment in the early AD, but not in normal controls. One possible explanation is the pathological changes of AD in the brain that affect gait and cognition simultaneously. Our study suggests that gait speed should be considered as a marker reflecting global cognitive function.
Discordance between self‐ and study partner‐reported cognitive decline is associated with MCI diagnosis
Authors: Aaronson Anna , Diaz Adam , Ashford Miriam T. , Jin Chengshi , Tank Rachana , Miller Melanie J. , Kang Jaemyeong , Manjavong Manchumad , Landavazo Bernard , Eichenbaum Joseph , Truran‐Sacrey Diana , Camacho Monica R. , Fockler Juliet , Flenniken Derek , Mackin Scott R. , Weiner Michael S. W. , Nosheny Rachel L. ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: January 2025

AbstractBackgroundIn Alzheimer’s disease research, subjective report of cognitive and functional decline from participant‐study partner (SP) dyads is an efficient method of assessing cognitive impairment and risk of clinical progression. The extent to which discordance (disagreement) between self‐ and SP–report is associated with diagnosis of cognitive impairment is not known.MethodWe tested the hypothesis that discordance between baseline self‐ and SP‐report Everyday Cognition Scale (ECog) scores was associated with greater probability of mild cognitive impairment (MCI) diagnosis. Dyads enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the University of California, San Francisco Brain Health Registry (BHR), an online longitudinal aging‐related research registry, completed an online adaptation of the 39‐item ECog to assess subjective change across six cognitive domains.We derived four metrics of discordance between participant and SP ECog scores (dyadic discordance): Raw Score Difference, Absolute Score Difference, Overreport Score, and Underreport Score (Table 1). In the ADNI cohort, we fit a logistic regression model for each of the discordance metrics to independently evaluate their association with MCI diagnosis, after adjusting for dyad relationship and sociodemographic factors. Then, to further evaluate the predictive utility of these measures, we carried out a model selection procedure using cross‐sectional data collected from ADNI dyads (N = 921; Table 1). Finally, we externally validated the model in a BHR cohort with clinically confirmed diagnoses (N = 279; Table 1).ResultHigher Raw and Absolute Score Difference, greater Underreport scores, and lower Overreport scores were associated with greater probability of MCI in the ADNI cohort (Table 2). The model selection procedure identified a number of highly predictive variables, which were then included in a model that was externally validated in the BHR cohort. This model distinguished diagnostic groups in the BHR cohort with AUC = 0.892, Sensitivity = 0.61, Specificity = 0.95 (Figure 1) based on a restricted cubic spline regression model.ConclusionResults indicate that ECog score discordance is associated with MCI diagnosis. The selected model showcased good predictive performance in the validation cohort, and highlights the potential utility of subjective dyadic discordance metrics to help identify older adults with MCI in diverse settings.
The relationship between dyadic perspective in subjective reports and objective cognitive decline in preclinical Alzheimer's
Authors: López‐Martos David , Brugulat‐Serrat Anna , Cañas‐Martínez Alba , Canals‐Gispert Lidia , Marne Paula , Gramunt Nina , Suárez‐Calvet Marc , Milà‐Alomà Marta , Minguillon Carolina , Fauria Karine , Zetterberg Henrik , Blennow Kaj , Molinuevo Jose Luis , Gispert Juan Domingo , Grau‐Rivera Oriol , Sánchez‐Benavides Gonzalo ,   for the ALFA study
Published: January 2025

AbstractBackgroundSubjective Cognitive Decline (SCD) may represent the initial symptom of Alzheimer’s disease (AD), but SCD may be absent and/or unrelated to actual cognitive decline. Objective Subtle Cognitive Decline (obj‐SCD) can be identified through longitudinal standardized neuropsychological tests in individuals not yet meeting criteria for Mild Cognitive Impairment (MCI). We argue that the relationship between SCD and obj‐SCD might help to inform clinical and research criteria in pre‐MCI stages. This study explores the dyadic perception (participant‐informant) of SCD as an early symptomatic marker of obj‐SCD in Cognitively Unimpaired (CU) population at increased risk of (AD) dementia.MethodThree hundred thirty‐seven CU participants from the ALFA+ prospective cohort study (with three‐year follow‐up) were included. AT(N) profiles were defined at baseline with Cerebrospinal Fluid (CSF) biomarkers. Baseline reports of SCD, “My‐Cognition” for the participant and “Their‐Cognition” for the informant, were measured with the SCD‐Questionnaire (SCD‐Q). AD biomarker‐based reliable change indices adjusted for practice effect (A‐T‐[N]‐ group’s longitudinal performance as reference) were computed for the robust measurement of cognitive trajectory. Considering the relationship between the number of neuropsychological measures and the base rate of impaired scores, obj‐SCD was defined as longitudinal biomarker‐based performance below ‐1.645 SD (<5th‐percentile) in at least 3 variables within each domain (episodic memory | global). Episodic memory and global obj‐SCD were analyzed using logistic linear regression with CSF Aβ42/40 status and SCD reports as predictors.ResultCSF Aβ‐status was not associated with global, but with memory obj‐SCD (OR = 2.743, 95%CI = 1.013‐7.811). SCD scores in My‐Cognition and Their‐Cognition were associated with global obj‐SCD (OR = 1.096, 95%CI = 1.003‐1.192; OR = 1.228, 95%CI = 1.075‐1.394), and Their‐Cognition was further associated with memory obj‐SCD (OR = 1.183, 95%CI = 1.020‐1.354). Descriptives in Table‐1, inferential results in Table‐2 and Figure‐1.ConclusionAβ‐pathology was linked to memory, but not global obj‐SCD, in participants not yet meeting MCI criteria. Subjective reports from informants showed greater effect sizes than reports from participants and were associated to memory and global obj‐SCD. The participant‐informant discrepancy observed for memory obj‐SCD and its association to AD‐related impairment suggested that participants with objective memory problems might not be fully aware of these subtle changes, highlighting the relevance of tracking dyadic reports in preclinical Alzheimer’s.
Development and validation of language as an endpoint in Alzheimer’s Disease clinical trials
Authors: Robin Jessica , Spilka Michael J , Xu Mengdan , Simpson William 
Published: January 2025

AbstractBackgroundChanges in the structure and use of language are well established clinical characteristics of Alzheimer’s disease. In recent years, there has been a concerted effort to objectively quantify these changes using the latest advances in Natural Language Processing (NLP) tools. Much academic research has been conducted to evaluate how these speech characteristics change with the course of illness, but they have yet to be elevated beyond exploratory endpoints in trials. Through a series of studies, we apply a validation framework with the goal of creating a speech based biomarker suitable for use in trials as a language endpoint.MethodIn order to accurately capture the spectrum of disease, a biomarker should be able to 1) detect disease in case‐control samples, 2) be able to capture severity within clinical groups and 3) capture change over time. We conducted a series of studies leveraging multiple methods to assess how NLP derived speech and language features perform at each of these validation tasks.ResultUsing machine learning based approaches, we were able to accurately differentiate patients with dementia from demographically matched controls with >80% accuracy. Numerous characteristics of speech, including syntactic complexity, information content, use of nouns and pronoun:noun ratios were shown to correlate with gold standard measures of cognition and function including the CDR, ADAS‐Cog, MMSE and ADCS‐ADL. Many of these same features also showed significant change over time, in line with traditional endpoints. Analytical strategies to combine these characteristics into composite scores have yielded measures which are correlated, but not identical to gold standard endpoints, with generally similar effect sizes and acceptable test‐retest reliability.ConclusionCollectively, these studies indicate that speech and language can detect disease, align with severity and track clinical changes over time. While additional characteristics, including cross‐language performance, speech source optimization and precise evaluations of patient relevance are required, speech based digital biomarkers are a promising advance in the measurement of AD.
Chronic heavy alcohol intake and liver‐specific LRP‐1 reduction increase amyloidosis in Alzheimer’s disease mice
Authors: Chandrashekar Devaraj V. , Roules G. Chuli , Steinberg Ross A. , Panchal Urvashi R. , Jagadeesan Nataraj , Oyegbesan Adenike , Roselyn Trinh , Yang Joshua , Bhagwat Sharda R. , Rakholia Hiya , Mevawala Rutvi D. , Roosan Moom , Han Derick , Sumbria Rachita K. 
Published: January 2025

AbstractBackgroundChronic heavy alcohol drinking may be a modifiable risk factor for Alzheimer’s disease (AD), but studies in rodent AD models more closely mimic chronic moderate alcohol drinking in humans and largely focus on the brain. The role of the liver, which is significantly impacted by chronic heavy alcohol intake, in driving brain changes in alcohol‐dependent AD remains unexplored. Our study using intragastric‐ethanol feeding, which mimics chronic heavy alcohol intake in humans, in C57BL/6J mice showed significant AD‐relevant changes in the brain and liver. Therefore, we aimed to investigate how hepatic changes using this model of chronic heavy drinking drive AD pathology in AD mice, which has never been attempted.MethodsEight‐month‐old male APP/PS1 mice were fed ethanol or control diet intragastrically for 5 weeks (n = 7‐11/group). Brain and liver Aβ were assessed using immunoassays. Three important mechanisms of brain amyloidosis were investigated: hepatic LRP‐1 (major peripheral Aβ regulator), blood‐brain barrier (BBB) function (vascular Aβ regulator), and microglia (major brain Aβ regulator) using immunoassays. Hepatic LRP‐1 expression was confirmed using Nanostring spatial transcriptomics. To elucidate the role of hepatic LRP‐1 in brain amyloidosis, hepatic LRP‐1 was silenced by injecting LRP‐1 microRNA delivered by the adeno‐associated virus 8 (AAV8) and the hepato‐specific thyroxine‐binding globulin promoter to 4‐month‐old male APP/PS1 mice (n = 6). Control APP/PS1 mice received control AAV8 (n = 6). Spatial memory was assessed 12 weeks after LRP‐1 silencing using Y‐maze, and brains and livers were harvested to detect Aβ.ResultsAlcohol feeding increased aggregated Aβ (p<0.05) by ELISA and 6E10‐positive Aβ load (p<0.05) by immunostaining, and reduced plaque‐associated microglia in APP/PS1 mice brains. Further, alcohol‐fed APP/PS1 had liver steatosis and significantly downregulated hepatic LRP‐1 (p<0.01) at the protein and transcript level, and brain and hepatic Aβ were positively correlated (p<0.05). Hepato‐specific LRP‐1 silencing significantly increased brain Aβ load (p<0.05) and reduced entries into the novel arm of the Y‐maze (p<0.05) in APP/PS1 mice.ConclusionChronic heavy alcohol intake reduced hepatic LRP‐1 expression, and hepato‐specific LRP‐1 silencing increased brain Aβ and spatial memory deficits in APP/PS1 mice. Our results place hepatic LRP‐1 as a potential key driver of brain amyloidosis in alcohol‐dependent AD.