bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi‐tissue metabolomics analyses identify disrupted processes in Alzheimer’s Disease
Authors: Wang Ciyang , Timsina Jigyasha , Ali Muhammad , Heo Gyujin , Liu Menghan , Ruiz Agustin , Pastor Pau , Sung Yun Ju , Cruchaga Carlos 
Published: January 2025

AbstractBackgroundBrain1,2, cerebrospinal fluid (CSF)3,4, and plasma5,6 metabolomics have been informative in identifying disrupted metabolism pathways in Alzheimer’s disease (AD). However, many AD‐focused metabolomics studies profiled a relatively small number of individuals and metabolites3–6, especially for CSF. In addition, past studies were limited to one or two tissues. Here we present a large‐scaled three‐tissue metabolomics study for Alzheimer’s disease.MethodThe cohorts of our study include Knight‐ADRC, DIAN, ADNI, Barcelona‐1, and Fundació ACE. In this study, 362 brain samples (N.ctrl = 27, N.AD = 335), 1,974 CSF samples (N.ctrl = 855, N.AD = 1,119), and 2,369 plasma samples (N.ctrl = 1,274, N.AD = 1,095) were included. The HD4 Metabolon platform was used to measure metabolomics of plasma, CSF, and brain samples. There were 797, 456, and 1,508, metabolites quantified in brain, CSF and plasma tissues. Linear regression model including age, sex, post‐mortem interval was used to identify differentially present metabolites. FDR correction was applied to the analyzed metabolites.ResultThe analyses in brain, CSF, and plasma identified 3, 65, and 553 metabolites differentially presented in AD compared to healthy controls after FDR multiple‐test correction. There were 31 metabolites shared between plasma and CSF, in which 28 having consistent direction of effects. Of the 31 CSF‐plasma shared metabolites, four metabolites (3‐hydroxyisolutyrate, alpha‐hydroxyisovalerate, ergothionenine, guaiacol sulfate), belonging to the branched‐chain amino acids (BCAAs) or xenobiotics, were nominally significant in brain. The two BCAA‐related metabolites, 3‐hydroxyisolutyrate and alpha‐hydroxyisovalerate, were replicated in another brain study1. Higher 3‐hydroxyisolutyrate7 has been associated with obesity, a risk factor for AD. We found that ergothioneine level was low in AD and a recent study showed that this metabolite improved amyloid beta clearance8 in a mouse model. Using metabolites differentially abundant in the plasma tissue, we found BCAA biosynthesis, taurine metabolism, starch and sucrose metabolism, and tryptophan metabolism pathways being altered in AD.ConclusionOur study performed the first multi‐tissue metabolomics analyses on Alzheimer’s disease. We identified concordant effects across tissues for many differentially abundant metabolites. The shared metabolites throughout tissues were closely linked to the Alzheimer’s disease.
Different phosphorylated tau isoforms in biochemical diagnosis of Alzheimer’s disease
Authors: Dulewicz Maciej , Kac Przemyslaw Radoslaw , Gonzalez‐Ortiz Fernando , Karikari Thomas K , Kulczynska‐Przybik Agnieszka , Mroszko Barbara , Turton Michael , Harrison Peter , Maler Juan Manuel , Oberstein Timo Jan , Kornhuber Johannes , Hanrieder Jörg , Zetterberg Henrik , Blennow Kaj , Lewczuk Piotr 
Published: January 2025

AbstractBackgroundIn the context of Alzheimer's disease (AD), blood‐based biomarkers have become increasingly important for various clinical purposes, such as screening patients and tracking the progression of the disease. Tau is a protein that stabilizes microtubules in nerve cells. In AD, different isoforms of tau become hyperphosphorylated, leading to the formation of neurofibrillary tangles, which are a key pathological feature of the AD. Measuring levels of different phosphorylated tau in the blood can provide insights into the extent of tau pathology in the brain. Phosphorylated tau (pTau) serves as a blood biomarker signaling the existence of AD‐related alterations, with pTau217, pTau181, and pTau231 proving to be significant indicators in this context. The primary goal of this study is to investigate the diagnostic utility of measuring plasma pTau217, pTau181 and pTau231 levels in identifying possible AD cases. This study intends to evaluate how effectively the concentrations of pTau217, pTau181 and pTau231 in the blood can differentiate individuals with CSF biomarker‐confirmed AD in comparison to CSF biomarker‐negative control group.MethodPlasma concentrations of pTau217, pTau181 and pTau231 were measured by in‐house Single molecule array (Simoa) assays developed at the University of Gothenburg (UGOT p‐tau217, pTau181 and pTau231). The quantitative assessment of classical biomarkers (Aβ‐42, Aβ‐42/Aβ‐40, tTau, and pTau181) in the CSF of patients with possible AD according to the Erlangen Score algorithm (ER 2 and 3) and controls (ER 0) were performed by Lumipulse.ResultSignificantly The levels of pTau217, pTau181 and pTau231 correlated positively with CSF tTau, pTau181 and negatively with CSF Aβ1‐42 and Aβ ratio. The greatest effect size was observed for pTau217 (d=1.63), moderate for pTau181 (d=0.57) and pTau231 (d=0.3) respectively.ConclusionThe results of the present study indicate that plasma pTau217 could be the most valuable blood biomarker for AD diagnosis among the tested isoforms.
Left frontoparietal control network connectivity moderates the effect of amyloid on cognitive decline in preclinical Alzheimer’s disease
Authors: Boyle Rory , Shirzadi Zahra , Coughlan Gillian T , Seto Mabel , Properzi Michael J , Klinger Hannah M , Townsend Diana L , Yuan Ziwen , Scanlon Catherine E , Jutten Roos J , Papp Kathryn V , Amariglio Rebecca E , Johnson Keith A , Rentz Dorene M , Chhatwal Jasmeer P. , Sperling Reisa A , Schultz Aaron P , Buckley Rachel F ,   The A4 Study Team
Published: January 2025

AbstractBackgroundStronger default mode (DMN) and bilateral frontoparietal control network (FPCN) resting‐state functional connectivity are associated with reduced β‐amyloid (Aβ)‐related cognitive decline in cognitively unimpaired older adults, who were predominantly Aβ negative. This suggests that these networks might support cognitive resilience in the face of early AD pathology but it remains unclear whether these effects are apparent in preclinical AD. We investigated whether left‐FPCN, right‐FPCN, and DMN connectivity moderated the effect of Aβ on cognitive decline using a large multi‐site dataset from the Anti‐Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4) study.MethodCognitively unimpaired participants with elevated Aβ on screening amyloid‐PET (n=1,062, mean age=71.9 years, 60% women, see Table 1), underwent functional MRI (3T) at baseline. We obtained connectivity estimates of the left‐FPCN, right‐FPCN, and DMN using template‐based rotation (Figure 1). Cognition was measured using the Preclinical Alzheimer’s Cognitive Composite (PACC; average follow‐up including open‐label extension period =280 weeks [SD=115]). We examined three‐way linear and quadratic interactions between functional connectivity and Aβ burden with time in mixed effects models (model 2 = DMN, 3 = left‐FPCN, 4 = right‐FPCN).1. PACC∼time + covariates×time2‐4A. PACC∼FC×time + covariates×time2‐4B. PACC∼FC×Aβ×time + covariates×time2‐4C. PACC∼FC×Aβ×time + FC×Aβ×time2 + covariates×timeCovariates included age, education, APOEe4 status, ICV‐adjusted gray matter volume, treatment group (Solanezumab vs placebo), and head motion. We modeled random effects of intercept and slope for each participant and included scanner as a random effect.ResultThe three‐way quadratic interaction of connectivity and Aβ burden with time was statistically significant for the left FPCN (p‐value corrected for multiple comparisons =.047, Figure 2), with a moderate effect size. That is, stronger left FPCN connectivity was associated with less cognitive decline in those with elevated Aβ. The pattern of effects were similar, but not statistically significant once all covariates were included, for the right FPCN and DMN.ConclusionIn a very large multi‐site clinical trial dataset, individuals with stronger left FPCN connectivity showed reduced Aβ‐related cognitive decline. This effect was specific to the left‐FPCN, in line with previous cross‐sectional findings. Our finding demonstrates that this protective effect of left FPCN connectivity can be observed in preclinical AD.
A novel whole‐brain imaging pipeline for amyloid‐beta plaque integrated with downstream iterative immunolabeling in pre‐clinical Alzheimer’s Disease animal models
Authors: Sasner Michael , Garceau Dylan , Elk Kevin J , Kamelin Peter , Yew Elijah , Chidambaram Ritesh , Ragan Tim 
Published: January 2025

AbstractBackgroundAlzheimer’s Disease (AD) has a strong spatial‐temporal component to its progression, where different brain regions are affected by amyloid‐beta (Aβ) plaque deposition at varying time points and in distinct cell types. Standard imaging and analysis platforms can neglect these details, as they lack the ability to pair high‐yield whole‐brain imaging with region‐specific or high‐resolution analysis. Here we describe a novel high‐throughput whole‐brain imaging pipeline to quantitatively track plaque progression as a function of brain region across time, while also producing indexed tissue sections for secondary staining and analysis that can be registered back to the original brain image.MethodAβ plaques in novel knock‐in mouse models of familial AD were labeled with Methoxy‐X04, an Aβ plaque‐specific compound. In some cases, brain vasculature was also labelled with DyLight. The brains were processed on the TissueCyte Serial Two‐Photon Plus (STP+) imaging platform to produce fully aligned multi‐channel volumetric datasets, yielding high resolution 3D models of each brain. Registration to the Allen Mouse Brain Common Coordinate Framework (CCFv3) and region‐specific plaque analysis were conducted to determine plaque size, density, and total number per brain region. By correlating Methoxy and DyLight signals, cerebral amyloid angiopathy (CAA) was also quantified. Indexed brain sections were then used for iterative immunolabeling (IBEX; see Radtke et al, Nat Protocols 2022) to detect vascular and cellular responses to amyloid on representative sections and remapped to the original 3D whole‐brain dataset.ResultThe analysis of whole‐brain plaque distribution in familial AD mouse models revealed distinct spatial‐temporal changes across the brains. STP+ imaging, combined with CCFv3 mapping and secondary analysis of microglial and astrocytic markers allowed for targeted evaluation of Aβ plaques, vascular pathology, and a comparison of regional molecular changes between models.ConclusionWe demonstrate here that the high sensitivity and precision of the STP+ platform coupled with secondary analysis of cellular responses can facilitate mechanistic understanding of amyloid deposition and cellular responses associated with specific therapeutic approaches. This approach could be very useful to study amyloid‐related imaging abnormalities (ARIA) in preclinical models.
Pilot Study to Probe the Utility of Salivary Lactoferrin as a Stress Biomarker Relevant to Alzheimer’s Disease
Authors: Garbarino Valentina R. , Wang Hanzhou , Yeh Chih‐Ko 
Published: January 2025

AbstractBackgroundApproximately 6.7 million people in the US are diagnosed with an Alzheimer’s disease (AD), with greater incidence in women and minorities. Approximately 11 million family members provide uncompensated care to their family members with dementia, with more than 60% reporting high or very high levels of stress, a condition associated with increased risk for AD. Salivary lactoferrin, which plays a role in immune defense, may have utility as a biomarker for assessing stress with particular relevance to AD, allowing for earlier intervention. Decreases in salivary lactoferrin concentration are associated with stress in animal models, and reduced salivary lactoferrin levels have been associated with AD compared to normal cognition. Characterization of lactoferrin as a biomarker for stress is necessary to understand the mechanisms by which lactoferrin may mediate stress and contribute to AD pathogenesis.MethodsTo probe the relationship between salivary lactoferrin and traditional indicators of stress, we utilized blood and saliva samples from females aged 49‐79 who serve as family caregivers for a parent/spouse with AD. Data was stratified by self‐reported ethnicity, Hispanic (N= 9) or non‐Hispanic (N= 9). Levels of salivary cortisol, IgA, and lactoferrin, and plasma C‐reactive protein were determined by enzyme‐linked immunosorbent assay.ResultsNeither salivary cortisol (Mean Difference ± SEM, ‐0.010 ± 0.045; P=0.827) or lactoferrin levels normalized to salivary flow‐rate (59.77 ± 372.1; P= 0.875) were significantly different between groups. Lactoferrin concentration normalized to salivary flow rate was positively correlated with cortisol levels in non‐Hispanic females (Y = 6502*X – 440.0; R2= 0.5037; P= 0.0322). This correlation did not exist in the samples from Hispanic participants. Though there was a correlation between salivary cortisol and IgA levels in non‐Hispanic female participants (Y= 3.055e‐006*X +0.063; R2= 0.5627; P= 0.02), lactoferrin levels were not correlated with salivary IgA or plasma CRP.ConclusionsSalivary lactoferrin was positively correlated with cortisol levels in non‐Hispanic female caregivers. Future studies controlling for caregiver stress and potential resilience will be necessary to confirm these relationships and determine the mechanisms by which lactoferrin response to stress differs between Hispanic and non‐Hispanic populations, and may mediate risk of neurodegenerative disease.Acknowledgements: P30AG044271 and TR002647.
Associations between cognitive enhancement therapy in old age and temporal‐spatial orientation and language: A case study
Authors: Tziannarou Antonia , Christodoulides Constantinos , Hadjiloizou Andrea , Moza Sotiria 
Published: January 2025

AbstractBackgroundAn 84‐year‐old male, with 16 years of education (retired physics teacher) was admitted to a long‐term rehabilitation centre to receive daily care, with cognitive decline symptoms. This study presents the data from a three‐month cognitive enhancement program.MethodsIn September 2023, the patient underwent the Mini Mental State Examination (MMSE) in Greek, followed by cognitive enhancement sessions (45 minutes, twice a week) for three months. The sessions included exercises such as, reading the calendar, telling the time, planning daily activities, virtual travel videos and media, constructive tasks with cubes, language tasks (e.g., arranging words in the correct order to form sentences, finding synonyms and antonyms, and other). An alternative version of the MMSE was administered in January 2024. The patient’s medication regimen for dementia, depression, cholesterol, and hypertension, had remained unchanged over the last 6 months.ResultsIn the preliminary assessment, the patient scored 15/30 on the MMSE. He scored 0/10 on the temporal/spatial orientation task, 0/3 on the delayed recall task, 2/3 on the 3‐command language item, and 0/1 on the language repetition item. Following the cognitive enhancement program, he achieved 20/30 points on MMSE and specifically 3/10 on orientation, 3/3 on the 3‐command item, and 1/1 on the repetition item.ConclusionsThe findings suggest that participating in targeted cognitive stimulation exercises may be linked to positive effects on orientation and language among older individuals, particularly, those with dementia. Our results could be influenced by the novelty of the stimuli in the patient’s life, potentially elevating cognitive demand temporarily and reaching a plateau over time. The study is ongoing to further explore these aspects.
Indiscriminate adjustment for confounders is worse than you think and what can be done about it
Authors: Sinha Harsh , Raamana Pradeep Reddy 
Published: January 2025

AbstractBackgroundTraining a “robust” predictive model is a non‐trivial task, especially for observational datasets. Datasets often contain confounding variables which must be de‐confounded (also less accurately referred to as “regressed out”) to eliminate the bias in predictive models. Due to the inherent uncertainty and complexity that surrounds the identification of true confounders, typically, all such covariates are regressed out indiscriminately. The prevailing wisdom is that adding more covariates cannot harm the predictive model, rather omitting measured covariates can lead to bias. But, whether inclusion/exclusion covariate has good/bad influence is contingent on the dataset. Therefore, confounding bias induced by an adjustment set must be empirically quantified rather than selecting covariates based on heuristic criteria. We demonstrate an approach to quantify confounding bias that is universally applicable to various machine learning (ML) algorithms facilitating evidence‐based decision making for covariate selection.MethodIn this work, we focus on restricted permutation tests to quantify the confounding bias in ML models. Specifically, the bias is evaluated by summing up the conditional association of residualized features (X) and the target (Y) for an adjustment set C (referred to as residual bias) under the null hypothesis. Using simulated data, we analyze the post‐adjustment residual bias for Random Forest model using various adjustment sets across multiple scenarios.ResultWe demonstrate that 1) adjustment for inappropriate covariates can increase existing confounding bias 2) adjusting for a covariate acting as a mere proxy for a confounder may not be beneficial and 3) finally, adjusting for a true confounder can even increase bias.ConclusionWe don’t advocate the use of independent criteria to select covariates individually. It is possible that bias induced by one covariate is suppressed or amplified by another covariate. Therefore, we recommend that confounding bias for each adjustment set should be quantified rather than choosing covariates based on availability or out‐of‐convenience. Such choices may enhance predictive accuracy in the training sample but can lead to biased predictions in the population‐of‐interest.
Longitudinal association between synaptic dysfunction and Alzheimer’s disease pathology in preclinical Alzheimer’s disease
Authors: Ourry Valentin , Valdez Alfonso Fajardo , Soucy Jean‐Paul , Ashton Nicholas J. , Nilsson Johanna , Brinkmalm Ann , Zetterberg Henrik , Blennow Kaj , Breitner John C.S. , Poirier Judes , Villeneuve Sylvia 
Published: January 2025

AbstractBackgroundSynapse loss in Alzheimer’s disease (AD) is correlates closely with cognitive impairment. Recent evidence suggests that synapse loss is promoted by amyloid‐beta, leading in turn to the spread of tau pathology. We sought to assess: 1) the association in positron emission tomography (PET) between several cerebrospinal fluid (CSF) synaptic biomarkers and amyloid and tau burden, as well as their annual change; and 2) the potential clinical utility of these synaptic biomarkers in preclinical AD.MethodsMass spectrometry assays quantified cerebrospinal fluid (CSF) markers of synaptic dysfunction (GAP43, SYT1, SNAP25 and Neurogranin) on 75 older adults (age 67.1 ± 4.8 years, 69.3% female) from the PREVENT‐AD cohort. These persons also had longitudinal amyloid ([18F]‐NAV4694) and tau ([18F]‐AV1451) PET scans performed over approximately 4.5 years. All were cognitively unimpaired (CU) at baseline, but 19 developed mild cognitive impairment (MCI) during follow‐up. We examined: 1) the association between these synaptic dysfunction biomarkers and global Aβ and entorhinal tau burden as well as their annual change, adjusting for age and sex; and 2) synaptic biomarker differences across those with Aβ at baseline vs. those who subsequently developed such pathology, and between individuals who remained CU vs. those who developed MCI during follow‐up. Analyses were considered significant at p=0.05/5=0.01 to account for multiple comparisons.ResultsAmyloid burden was positively associated with increased SNAP25long, while tau burden was associated with all 5 synaptic biomarkers (Figure 1). No association was found between these markers and amyloid and tau annual change. GAP43 and SNAP25 differed in Aβ‐ and Aβ+ groups but showed no difference across amyloid accumulators’ groups (Figure 2). Finally, MCI individuals had higher SNAP25long and GAP43 concentration than CU individuals (Figure 3).ConclusionsGAP43 and SNAP25, being markers associated with neuronal growth and synaptic vesicle fusion, appear closely related to amyloid and tau burden, but only at baseline, even in preclinical AD. These biomarkers of synapse loss appear also to have clinical relevance, with differences observed in MCI compared to CU individuals. Future studies should explore these biomarkers, alongside pathology reduction, as potential targets for AD prevention to confirm these preliminary findings.
Neuroinflammation in people with Down syndrome and its association with amyloid deposition: a PET imaging study throughout aging
Authors: Mantovani Dimitri Brigide De Almeida , de Oliveira Laura Cavalcanti , Coutinho Artur Martins , da Silva Ana Maria Marques , Forlenza Orestes Vicente , Buchpiguel Carlos Alberto , de Paula Faria Daniele de Paula 
Published: January 2025

AbstractBackgroundDown syndrome (DS) is a genetic disorder characterized by trisomy 21, which is linked to molecular alterations, such as neuroinflammation and accumulation of amyloid‐beta (Ab) peptide that can cause early‐onset Alzheimer's disease (AD). This study aims to evaluate the presence of neuroinflammation in individuals with DS in different ages and the association with Ab plaques.MethodsAge‐matched DS (n=24) and non‐DS individuals (n=15) underwent two hybrid PET/MRI acquisition for neuroinflammation and Ab burden assessment using [11C]PK11195 (∼370 MBq and 60 min acquisition) and [11C]PIB (∼370 MBq and 70 min acquisition) tracers, respectively. Quantification is presented as standard uptake values (SUV 40‐60min) for [11C]PK11195 (PMOD software) and SUVratio (SUVr 50‐70 min) for [11C]PIB using cerebellum grey matter as reference tissue (CortexID software) and cortical areas as a unique VOI called “composite”. Statistical analyses were performed dividing the DS group in <40 (n=13) and ≥40 (n=11) years of age. Differences in [11C]PK11195‐SUV and [11C]PIB‐SUVr were assessed by applying a multivariate one‐way ANOVA test with Bonferroni analysis for multiple comparisons. Correlation analyses were applied between [11C]PK11195‐SUV, [11C]PIB‐SUVr, and age variables.ResultsSignificant higher [11C]PK11195‐SUV was found in the occipital lobe (p<0.001), temporal lobe (p<0.001), and cingulum posterior (p<0.0001) when comparing the older to younger DS groups. Significant [11C]PIB‐SUVr differences were found for all groups, with the DS≥40 group showing the highest [11C]PIB uptake, followed by the DS<40 and non‐DS groups. No correlations were found between [11C]PK11195 and [11C]PIB measurements. However, for DS individuals, positive significant correlations with age was observed for [11C]PK11195‐SUV in the occipital lobe (p<0.05), temporal lobe (p<0.01), cingulum posterior (p<0.001), hippocampus (p<0.05), amygdala (p<0.05), striatum (p<0.05), and cerebellum (p<0.05), and for [11C]PIB‐SUVr in the composite VOI (p<0.01).Conclusion[11C]PK11195‐PET analysis suggests increased neuroinflammation in older DS subjects. [11C]PIB‐PET results show a higher Ab burden in DS≥40 individuals and early accumulation of Ab in DS<40 individuals in comparison to non‐DS age‐matched subjects. More in‐vivo studies are needed to understand the temporal relationship between neuroinflammation and Ab deposition in the brain of individuals with DS.