bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association Between Mean Corpuscular Volume and Cognitive Function in Community‐Dwelling Older Adults ‐ An 11‐year Cohort Study
Authors: Yen Pei‐Yu , Chiou Jen‐Ming , Chen Yen‐Ching , Chen Jen‐Hau 
Published: January 2025

AbstractBackgroundThe mean corpuscular volume (MCV) is a common parameter in routine blood tests. Larger MCV tends to be more fragile and pose challenges in passing through capillaries, leading to a diminished capacity for oxygen and nutrient supply to the brain thus impacting cognitive function. Limited studies have explored the association between MCV and cognitive impairment with inconsistent results. This study aimed to investigate the association between MCV and cognitive function in community‐dwelling older adults.MethodThis 11‐year cohort study (2011‐2022) included 530 non‐demented older adults (aged above 65) from the ongoing Taiwan Initiative for Geriatric Epidemiological Research at baseline (2011 to 2013) with four biennial follow‐ups. Global cognition was assessed by the Taiwanese version of the Montreal Cognitive Assessment. Domain‐specific cognition, including memory, attention, verbal fluency, and executive function, was assessed by a battery of neuropsychiatric tests. Blood data were collected, including MCV, red blood cell distribution width, hemoglobin, platelet, and vitamin B12. The cutoff of MCV was determined by the turning point obtained from the generalized additive model. This study utilized a generalized linear mixed model to analyze the association between MCV and cognitive function adjusted for age, sex, years of education, apolipoprotein E ε4 status, years of follow‐up, and other blood parameters.ResultThe average age of the participants is 72.68 years, with females comprising 53.40%. As the follow‐up time increased, older adults with larger baseline MCV (>93.0 fL) exhibited a significantly poor performance of memory (immediate free recall: = ‐0.028, p = 0.021; delayed free recall: = ‐0.039, p = 0.002; delayed theme recall: = ‐0.041, p = 0.003), and attention (digit span forward: = ‐0.028, p = 0.027). Additionally, an interaction was found between MCV and age on global cognition (p interaction=0.008).ConclusionOver time, increased MCV was associated with poor domain‐specific cognition. MCV may potentially serve as an early indicator for assessing cognitive impairment. Larger and longer‐term studies are needed to clarify their temporal relationship and underlying mechanism.
Salivary lactoferrin levels decrease in Alzheimer's disease patients
Authors: Bunprakop Saowalak , Ruchisrisarod Chanida , Luechaipanit Watayuth , Hemachudha Thiravat , Thanapornsangsuth Poosanu 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is referred as one of the most common causes of dementia and frailty. To address this impending public health crisis, there is a critical need to identify simple and reliable biomarkers for early AD diagnosis. Recent research has highlighted the potential utility of salivary lactoferrin (Lf) as a promising biomarker for AD diagnosis. In this study, we aim to assess salivary Lf levels in early‐stage AD patients in comparison to nondemented elderly controls with the goal of further elucidating the diagnostic utility of this biomarker, Lf may be a good biomarker candidate for initial and clinically.MethodA total of 212 patients were included in the study. Saliva samples were collected from nondemented elderly controls (n = 151) and early‐stage AD patients (n = 61). The diagnosis of AD was made clinically using the current guidelines (Jack et al., 2018; Dubois et al., 2021). All patients were diagnosed by PET or plasma phosphorylated tau 181 (P‐tau181), 71 patients including clinical and the Clinical Dementia Rating (CDR). Salivary Lf levels were compared between the two groups and the diagnostic performance of Lf was evaluated in these early‐stage patients.ResultAmong 212 participants included, 139 (65.6%) were female. The median age was 67 years. Salivary Lf levels decreased significantly among early‐stage AD patients (9.02 ug/ml) compared to controls (26.07 ug/ml; P<0.001). Salivary Lf showed moderate correlation with plasma P‐tau181 (Spearman Rho=‐0.472, P<0.001) (Figure 1). For diagnosing AD in early‐stage patients, salivary Lf levels demonstrated an area under the curve of 0.88 (95% confidence interval 0.83‐0.93).ConclusionThe main findings of this study are that salivary Lf levels decreased significantly in early‐stage AD patients in comparison to nondemented elderly controls, diagnostic performance of salivary Lf is substantial. The hypothesis that immune alterations and brain infections might play an initial role in the development of AD pathology. our hypothesis would determine salivary Lf would be an easy and cheap biomarker that could potentially make it an attractive option for population‐wide screening and early identification of undiagnosed individuals with AD in its early stages.
Investigating differences in white matter fibre bundle alterations between amnestic Alzheimer’s disease and LATE: A fixel‐based analysis
Authors: Lebrun Aurélie , Lagarde Julien , Leprince Yann , Olivieri Pauline , Bottlaender Michel , Sarazin Marie 
Published: January 2025

AbstractBackgroundTypical Alzheimer’s disease (AD) and Limbic‐predominant Age‐related TDP‐43 Encephalopathy (LATE) are two neurodegenerative diseases that present with a similar initial amnestic clinical phenotype but have distinct proteinopathies. AD is characterised by ß‐amyloid plaques and intraneuronal neurofibrillary tangles, while LATE is characterised by abnormal neuronal TDP‐43 protein. With reference to the prion‐like hypothesis regarding the propagation of proteinopathies, investigating white matter fibre bundle alterations could provide new insights into the propagation pathways of specific proteinopathies. Because both AD and LATE have a similar initial limbic phenotype but are distinguished by their proteinopathies, they represent a good model to analyse whether white matter fibre bundle alterations differ according to the pathophysiology. We investigated these alterations in AD and presumed LATE using high quality diffusion MRI and fixel‐based analysis.MethodWe included AD patients (n=27, CDR≤1), presumed LATE patients (n=18, CDR≤1), and controls HC (n=19) using strict pathophysiological criteria, including CSF biomarkers, amyloid and tau PET imaging, and the absence of clinical atypia after two years of follow‐up. Both AD (MMSE=24.5) and LATE (MMSE=24.4) exhibited equivalent episodic memory impairment and hippocampal volume. Using multi‐shell diffusion MRI, we first computed a whole‐brain fixel‐based analysis controlling for age, sex, MMSE, and intracranial volume to explore differences in FD (fibre density), FC (fibre‐bundle cross‐section) and FDC (fibre density and cross‐section) between groups, and to identify tracts of interest. We then reconstructed the identified tracts and performed tract‐based analyses with the same covariates to compare (i) AD versus HC, (ii) LATE versus HC, and (iii) AD versus LATE.ResultWe found that both AD and LATE exhibited white matter alterations in tracts of the temporal and limbic lobes (ventral cingulum, inferior longitudinal fasciculus, uncinate fasciculus, temporopulvinar bundle of Arnold). In addition, LATE patients showed more spatially extended alterations in callosal fibres and in fibres of the cerebello‐thalamo‐cortical tract that end near the pre‐supplementary motor area.ConclusionWhite matter fibre bundle alterations in AD and LATE exhibit differenciable patterns that are consistent with the staging system of tau or TDP‐43 accumulation. These findings also shed light on the temporopulvinar bundle of Arnold, that we found significantly altered in both diseases.
Multi‐atlas fully automated segmentation of the locus coeruleus in in vivo neuromelanin‐sensitive MRI
Authors: de Flores Robin , Blanchard Thaïs , Foyard Emilie , Naveau Mikaël , Delcroix Nicolas , Landeau Brigitte , Yushkevich Paul A. , Chételat Gael ,   Medit‐Ageing Research Group
Published: January 2025

AbstractBackgroundLocus coeruleus (LC) imaging using neuromelanin‐sensitive (NM) MRI sequences is a promising biomarker for detecting early Alzheimer’s Disease (AD). Although automatic approaches have been developed to estimate LC integrity by measuring its intensity, these techniques most often rely on a single template built in a standardized space and/or depend on a number of voxels to be accounted that is defined a priori. Thus, these algorithms make it impossible to perform direct volumetric analyses and do not properly account for inter‐individual anatomical variability. To fill this gap, our aim was to develop a new multi‐atlas fully automated segmentation method using the Automatic Segmentation of Hippocampal Subfields (ASHS) software.MethodWe used baseline data from 102 unimpaired older adults (mean age: 73.72 ± 3.5 years; mean education: 13.25 ± 3.1 years; 58 women, 44 men) from the Age‐Well randomized controlled trial for whom high‐resolution NM MRI (T1‐w with magnetization transfer; 0.3x0.3x0.75mm3) and standard T1‐w MRI (1x1x1mm3) were available. The LC were manually segmented in 30 randomly selected participants on NM MRI, and the standard T1‐w MRI, NM MRI and bilateral segmentations were fed into the ASHS training pipeline to generate an atlas. This new atlas was applied to the 72 remaining subjects to segment the LC and we assessed the effects of age, sex and education on both i) LC intensity (normalized by the intensity of the pons) and ii) LC volume (normalized by the total intracranial volume).ResultFive‐fold cross‐validation experiments revealed high accuracy of the automatic segmentation relative to manual segmentation (Dice coefficient = 0,83 ± 0,04). LC intensity was significantly higher in women than in men (F=13.61, p<0.001) while no associations with age (β=‐0.0002, p=0.86) or education (β=0.002, p=0.16) were found. In contrast, LC volume was not different between men and women (F=0.21, p=0.65) but tended to be negatively associated with age (β=‐0.15, p=0.06) and education (β=‐0.19, p=0.06).ConclusionOverall, this new method allows to automatically and accurately segment the LC, and offers the opportunity to measure its integrity both in terms of intensity and volume. This is of importance since these two metrics might provide complementary information about the integrity of the LC.
Deciphering Alzheimer's Disease Complexity: Integrative Analysis of CSF Proteomic and Lipidomic Data through Dimensionality Reduction
Authors: García‐González Pablo , Puerta Raquel , Dehairs Jonas , de Rojas Itziar , Montrreal Laura , Pytel Vanesa Verónica , Marquié Marta , Rosende‐Roca Maitee , Emon Asif , Smets Bart , Orellana Adelina , Tárraga Lluís , Boada Mercè , Swinnen Johannes V , Fernández Victoria , Socorro Alfredo Cabrera , Ruiz Agustin 
Published: January 2025

AbstractBackgroundAlzheimer’s Disease (AD) is a complex disorder and much of its etiopathology is still unknown. Here, we applied dimensionality reduction methods to disentangle cyptic patterns in CSF proteomic and lipidomic data.MethodWe studied 1121 CSF samples using targeted lipidomics based on liquid chromatography (LC)‐MS/MS (mass spectrometry), generated by Lipometrix (Lueven, Belgium), and proteomic data generated by Somalogic (Boulder, Colorado) using the SOMAscan 7k Assay. We independently computed the principal components for the proteomic and lipidomic datasets using good quality lipids (N=388) and proteins (N=2469). CSF samples were obtained by lumbar punctures at ACE Alzheimer Center (Barcelona, Spain), including patients at different points of the dementia continuum (SCD, MCI and dementia). Principal components were calculated using the princomp() function in R.ResultPC1 explained a substantial fraction of the variance in lipidomic (∼40%) and proteomic (∼60%) datasets and was highly correlated between both omics (R2=0.43; p=2.3·10‐138, Figure 1). We explored the association profile of the PCs to AD risk factors (age, sex, APOE, PRS, diabetes, hypertension, dyslipidemia, BMI), endophenotypes (abeta, tau), disease progression and total protein in the CSF. PC1, as well as the individual lipid species, were strongly associated with abeta, tau and total CSF protein levels (Figure 2). Finally, we conducted a GWAS of the first 20 lipidomic and proteomic PCs. PC1 displayed a GWS signal at chr3q28 in both omics. This region has been previously linked with CSF tau levels and brain morphology. Subsequent lipidomic PCs were associated with variants in the FADS1/FADS2 locus, while other proteomic PCs were associated with variants in the APOE locus (Figure 3).ConclusionOur findings revealed a shared major contributor to the variance in CSF between lipidomic and proteomic data, which is related to the tau, abeta and total protein signature, and identified a QTL associated to both the lipidomic and proteomic PC1. Accounting for this major variance contributor may enhance future studies involving CSF biomarkers. Subsequent principal components had specific association profiles to AD risk factors and endophenotypes.
Addressing Unmet Precision Requirements through Improved Automatic Identification of Cerebral Microbleeds
Authors: Jeon Younghoon , Yoo Roh‐Eul , Baek Min Seok , Seong Joon‐Kyung , Choi Seung Hong , Lee Wha Jin 
Published: January 2025

AbstractBackgroundCerebral microbleeds (CMBs) hold significant clinical relevance, linked to elevated risks of hemorrhages, cognitive decline, and mortality. Notably, with the recent advancement in Alzheimer’s treatments, the number of CMBs serves as a crucial safety indicators to assess the risk and occurrence of amyloid‐related imaging abnormalities. However, the commonly utilized manual detection process is time‐consuming and labor‐intensive, prompting the development of various automated detection models. But, most of them are composed of a two‐track system for candidate retrieval and false positive (FP) reduction, resulting in low precision.MethodSusceptibility‐weighted images (SWI) were obtained from 250 participants enrolled in the Seoul National University dementia cohort, with 200 and 50 images allocated to the training and test set, respectively. CMBs were segmented manually based on expert radiologist assessments. Only 75 images in the training set and 29 images in the test set revealed the presence of CMBs. For our analysis, we employed 3D‐nnUNet, an segmantic segmentation model, training it through 5‐fold cross validation. The segmented regions were analyzed for CMB counting, focusing on morphological features. External validation was performed using 15 images from Wonju Severance Christian Hospital.ResultOur model exhibited a concurrent high true positive rate (TPR) of 81.4% and precision of 84.9%. This performance remained consistent across different severities of CMB occurrences, with the best perfomance observed in subjects with five or fewer CMBs (TPR of 92.7% and precision of 84.6%). Additionally, even among non‐CMB subjects, the model demonstrated strong perfomance, yielding an average of 0.23 FPs. External validation confirmed model robustness with a TPR of 86.4% and precision of 79.2% (Table 1). Classification of the severity groups regarding the number of CMBs (None, 1∼4, 5∼10, and >10) revealed an overall accuracy of 87% in the non‐CMB and the test set (Figure 1).ConclusionThis study introduces a novel single‐channel automated CMB detection model using SWI. Our model successfully tackles a notable challenge found in previous automatic CMB counting models, balancing a high TPR with more reliable precision. It underscores its applicability for accurately stratifying CMB severities in clinical contexts, including eligibility assessment for anti‐beta amyloid antibody treatment in AD.
Empowering Better End of Life Dementia Care (EMBED‐Care): Co‐design of a digital holistic assessment and clinical decision support framework
Authors: Davies Nathan , Ellis‐Smith Clare , Gillam Juliet , Aworinde Tofunmi , Kenten Charlotte , Evans Catherine , Sampson Elizabeth L 
Published: January 2025

AbstractBackgroundPeople with dementia have complex palliative care needs including psycho‐social, physical and spiritual; however, they are often unmet. It is important to empower people with dementia, family caregivers and professionals to work together to better assess and monitor ongoing needs. This study aimed to co‐design and test the feasibility of an integrated model of palliative dementia care to support holistic assessment and decision making for care in the community and care homes (assisted living facilities).MethodUsing a systematic and iterative approach we co‐designed the EMBED‐Care framework, a holistic assessment and clinical decision support system hosted on a digital application. Using framework analysis we synthesised evidence from systematic reviews, large data, and a cohort study to identify unmet palliative care needs and concerns of people living with dementia. We presented the data in workshops, using nominal group techniques with people with dementia, family caregivers, and care professionals, to identify targets, components, and design of the framework. We conducted user testing with all groups to refine the framework. We co‐designed training and support to implement the framework, including bitesize animated videos, manuals, in‐person training sessions, local champions, and a telephone support system. The framework is currently being tested in a feasibility trial in two care homes and two community nursing teams.ResultThe framework consists of five components: holistic assessment using the Integrated Palliative Outcome Scale for People with Dementia (IPOS‐Dem); alert system linked to IPOS‐Dem scores, priority setting; clinical decision support tools; and training programme. The IPOS‐Dem helps identify areas of concern and unmet need, providing opportunities for shared decision making and identify priorities of care. Each concern is linked to a decision support tool to support decision making and to address priorities. Alerts and reminders communicate concerns among teams and carers. A desktop version (dashboard) is available for professionals to view all their residents/patients, including IPOS‐Dem results, allowing symptom tracking. Findings from the feasibility study will be presented.ConclusionThis is the first intervention to link IPOS‐Dem with practical decision support to help break down the complexity of palliative dementia care, providing the right care at the right time.
Functional brain network organization supports cognitive function in patients with Alzheimer’s Disease‐related pathological burden and brain atrophy
Authors: Zhang Ziwei , Chan Micaela , Winter‐Nelson Ezra , Wig Gagan S 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is defined by the accumulation of Aβ plaques and tau neurofibrillary tangles. The consequences of these pathologies include neurodegeneration and cognitive dysfunction. However, the process by which AD pathologies leads to cognitive impairment remains unclear. Some individuals can harbor pathological burden yet be cognitively unimpaired; these observations have led to ideas about cognitive reserve (Stern, Lancet, 2012).Dominant models of AD biomarkers do not include direct measures of brain function. To address this gap, we tested whether resting‐state brain system segregation explains discrepancies between AD‐related pathology, structural atrophy, and cognitive function. System segregation changes across the adult lifespan, is stratified in relation to life course exposures, and relates to cognitive function (Wig, Trends in Cognitive Sciences, 2017).MethodParticipants were recruited through the Alzheimer’s Disease Neuroimaging Initiative. Cognitive impairment was quantified using clinical dementia rating (CDR). The participant group included 184 healthy (CDR=0) adults, 101 very mild dementia (CDR=0.5), 24 mild dementia (CDR=1) and 2 moderate dementia (CDR=2) patients (age range: 55–96 years).Functional brain networks were generated using resting‐state fMRI time series. Network edges were defined as correlations between time series of each pair of nodes. Brain system segregation was calculated to quantify functional brain network organization for each participant (Chan et al., PNAS, 2014).ResultMultiple linear regression analyses were used to test whether Aβ and tau relate to brain system segregation, with age, gender, education, and head motion included as covariates. Neither Aβ nor tau burden was associated with brain system segregation (Aβ: p=0.45; tau: p=0.55).Among individuals exhibiting positive pathological burden (either Aβ, tau, or both) based on cut‐off values, individuals with higher system segregation were less cognitively impaired (Aβ+: p=0.007; tau+: p=0.021; Aβ and tau+: p=0.03).Finally, system segregation explained unique variance with respect to CDR status over and above Aβ, tau, and cortical thickness. Brain system segregation was negatively related to CDR status (p=0.003), while accounting for these other factors.ConclusionFunctional brain network organization supports observations of cognitive reserve, and explains unique variance with respect to AD‐related cognitive impairment independent of AD‐related pathology and neurodegeneration.
Prognostic value of a novel plasma pTau217 assay for amyloid accumulation in healthy elderly
Authors: Meyer Steffi De , Luckett Emma S. , Schaeverbeke Jolien , Laere Koen Van , Vanbrabant Jeroen , Vanmechelen Eugeen , Dupont Patrick , Molfetta Guglielmo Di , Zetterberg Henrik , Ashton Nicholas J. , Poesen Koen , Vandenberghe Rik 
Published: January 2025

AbstractBackgroundThe performance of blood‐based phosphorylated tau (pTau) immunoassays to detect asymptomatic Alzheimer’s disease (AD) has important implications for therapeutic trials. pTau217 is often recommended as the preferred epitope due to its high fold changes in AD. The current study investigates the ability of a novel pTau217 assay to predict the dynamic phase of amyloid‐β (Aβ) accumulation in comparison to the best‐performing pTau181 assay.MethodsPlasma pTau217 was quantified by the ALZPath Simoa assay at the University of Gothenburg in 109 cognitively unimpaired older adults (Flemish Prevent‐AD Cohort KU Leuven [F‐PACK] cohort). All subjects underwent baseline plasma sampling and longitudinal Aβ‐PET (median time interval = 6 years). For a subset of 72 subjects, pTau181 was quantified by the Homebrew ADx Simoa assay. Linear mixed‐effects models were used to calculate subject‐specific Aβ change and to assess the age‐, sex and APOE‐corrected predictive value of pTau species for Aβ change, which was assessed in a global and voxelwise manner. Accumulators were defined as having an Aβ rate of change z‐score > 1.5 (based on mean & standard deviation within the Aβ‐ subset). Performance to detect Aβ accumulators was assessed through receiver operating characteristic analyses. Plasma biomarkers were converted to z‐scores for effective comparison. Pearson correlations were calculated between pTau181 and pTau217.ResultsPlasma pTau217 levels were higher in Aβ accumulators than non‐accumulators with an area under the curve (AUC) of 0.69 (95%CI 0.58‐0.81). Moreover, higher pTau217 predicted steeper Aβ accumulation (βs=0.57, P<.001). Plasma levels of pTau217 strongly correlated with those of pTau181 (r=0.93, Figure 1). In the subgroup with matching pTau181 data, pTau181 was also higher in Aβ accumulators than non‐accumulators with an AUC of 0.68 (95%CI 0.53‐0.84), which was comparable to pTau217 (AUC=0.76; PDeLong=.12) or a multibiomarker model including both pTau species (AUC=0.80; PDeLong=.15) in the same subset (Figure 2A). pTau181 demonstrated comparable associations with Aβ accumulation in terms of both strength (βs=0.53, 95%CI 0.21–0.81 for pTau181 versus βs =0.48 for pTau217 in this subset) and spatial distribution (Figure 2B).ConclusionsThe novel ALZPath pTau217 assay predicted Aβ accumulation in asymptomatic elderly with comparable performance to the ADx pTau181 assay.