bluuebunny/crossref_metadata_2025_split huggingface dataset:
Longer leukocyte telomere length is associated with lower markers of early Alzheimer's disease pathology, astrocytic reactivity, and synaptic dysfunction
Authors: Rodríguez‐Fernández Blanca , Escalante Armand González , Genius Patricia , Ortiz‐Romero Paula , Brinkmalm Ann , Minguillón Carolina , Kollmorgen Gwendlyn , Quijano‐Rubio Clara , Ashton Nicholas J. , Zetterberg Henrik , Blennow Kaj , Gispert Juan Domingo , Navarro Arcadi , Suarez‐Calvet Marc , Crous‐Bou Marta , Vilor‐Tejedor Natalia ,   for the ALFA study
Published: January 2025

AbstractBackgroundLeukocyte telomere length (LTL) serves as a proxy for tissue‐specific TL and peripheral immune aging. Its association with aging‐related brain endophenotypes, cognitive functioning, and Alzheimer's disease (AD) risk is established, but the underlying molecular mechanisms remain elusive. Investigating LTL's association with AD biomarkers is crucial for identifying its role in brain resilience and disease progression.MethodWe included middle‐aged adults at risk of AD dementia from the ALFA+ study. In CSF, we measured Aβ42, Aβ40, NfL, GFAP, α‐synuclein, neurogranin, S100B, sTREM2, YKL40, and IL6 using the exploratory Roche NeuroToolKit robust prototype assays; p‐tau181 was measured using Elecsys®; GAP‐43 using an in‐house ELISA; and Synaptotagmin‐1 using mass spectrometry. In plasma, we measured Aβ42, Aβ40, p‐tau231, NfL, and GFAP using Simoa. LTL was determined by qPCR from DNA extracted from peripheral blood leukocytes. Multiple linear regression models were used to evaluate the association between LTL and both baseline and the change in CSF and plasma biomarker levels over a three‐year period. Models accounted for age, sex and APOE‐ε4 status, and time between measurements, when interrogating the change in biomarkers. Sensitivity analyses included models adjusted by CSF Aβ42/40, CSF p‐tau181. Sex‐, APOE‐ε4 and disease‐specific effects were explored through interaction and stratified models.ResultIn plasma, longer LTL was associated with lower plasma p‐tau231 at baseline [Figure 1A]. This association was mainly driven by women [Figure 1B]. In CSF, longer LTL was associated with reduced S100B at baseline [Figure 2A] and decreased α‐synuclein over time [Figure 2B], independently of CSF Aβ42/40 and p‐tau181 levels. Over time, longer LTL was associated with increasing CSF IL6 levels among A+T‐ individuals, while the opposite direction was observed among A+T+ individuals [Figure 3A‐3B].ConclusionLonger LTL was associated with lower plasma p‐tau231, an early marker of AD pathology, specifically in women. Furthermore, longer LTL was independently associated with lower biomarkers of astrocytic and synaptic dysfunction, regardless of AD pathology. Nevertheless, an AT‐dependent shift in LTL's impact on CSF IL6 change emerged over time. These results collectively propose that peripheral immune aging could be related to the central nervous system along the AD continuum, either independently or in a sex‐ and disease‐specific manner.
White‐matter myelin is reduced in monogenic small vessel disease and MCI: evidence from MRI source separation
Authors: Denecke Jannis , Dewenter Anna , Lee Jongho , Pirpamer Lukas , Franzmeier Nicolai , Gesierich Benno , Duering Marco , Ewers Michael 
Published: January 2025

AbstractBackgroundThe myelin sheath around axons is of fundamental importance for signal transduction. Myelin is reduced in white matter hyperintensities (WMH), which occur in both small vessel disease (SVD) and Alzheimer’s disease (AD), giving rise to the question to what extent myelin is reduced in these diseases. Here, we employed an advanced MRI based method to assess myelin independently from a major confounding factor, i.e. iron‐related signal, in monogenic small vessel disease (i.e. CADASIL) and in mild cognitive impairment (MCI) & AD dementia.MethodsWe included 62 CADASIL subjects, 11 with MCI or AD dementia, and 22 elderly controls (HC). Using 3D‐T2‐star‐weighted multi‐echo gradient‐echo MRI, we performed susceptibility source separation of diamagnetic (|χ‐negative|, e.g. myelin) and paramagnetic (χ‐positive, e.g. iron) sources (Shin et al., 2021). Mean diffusivity (MD) was calculated from diffusion tensor imaging. We extracted |χ‐negative| and MD values within WMH, normal appearing white matter (NAWM), and two ROIs including the left anterior thalamic radiation and forceps minor (genu) of the corpus callosum, i.e. two strategic tracts for processing speed. Subject‐level difference‐scores between CADASIL or MCI/dementia patients and group‐averaged HC were derived as abnormality scores. Voxel‐based WMH frequencies were mapped for each group. Group differences in |χ‐negative| and MD values were tested using linear regressions, controlled for χ‐positive scores, age, sex, and education.ResultsVoxel‐wise proportions of WMH are mapped for each group in Figure 1. For CADASIL, |χ‐negative| values were decreased, and MD values increased in each ROI compared to the HC group, with intermediate values for the MCI/dementia group (Figure 2 A&B). Worse |χ‐negative| and MD alterations were observed in WMH compared to NAWM (Figure 2 C‐F) in each disease group. Lower |χ‐negative| values were associated with higher MD in WMH (r=‐0.57, Figure 3) and NAWM (r=‐0.56).Conclusion|χ‐negative| values showed a marked decrease in WMH of CADASIL patients, suggesting myelin loss in SVD, with less pronounced myelin reduction present in MCI/AD. |χ‐negative| values were only moderately associated with MD, suggesting that each provides complimentary information. Our results encourage future studies to test the cognitive consequences of myelin loss in SVD and MCI.
Integrated Proteomic Analysis of Alzheimer and Mild Cognitive Impairment in Biofluid using Mass Spectrometry and NULISATM Technology
Authors: Chen Yao , Wesseling Hendrik , Levit Mikhail , Zhang Bailin 
Published: January 2025

AbstractBackgroundOne hypothesis of lack of effectiveness in most current clinical trials for the AD (Alzheimer’s disease) is the advanced stages of the disease at the time of pharmacological intervention. To aim a robust effect from disease‐modifying therapies, there is an urgent need for biomarkers that can identify patients with MCI and early stages of AD. In this study, we combined in‐house large‐scale LC‐MS and new emerging highly sensitive NULISA proteomics analysis on a medium sized AD cohort sample, aiming an early‐stage protein biomarker discovery in MCI and AD.Method59 AD set plasma and 65 AD set CSF were purchased from the vendor. Donor classification strictly followed the disease inclusion/exclusion criteria. One aliquot from each sample were sent to Alamar Bioscience for NULISAseq analysis on ARGOTM system using 120‐plex CNS disease panel. In house LC‐MS was performed on the same set of samples.ResultOf 59 AD set plasma samples (19 HC, 22 MCI AND 18 AD), 3 significantly up‐regulated protein in MCI and 16 significantly down‐regulated protein in AD and MCI were identified by NULISAseq 120plex CNS panel. One significantly up‐regulated protein in MCI and 3 significantly down‐regulated proteins in AD were also confirmed by in house LC‐MS. Of 65 AD set CSF samples (19 HC, 22 MCI and 24 AD), 12 significantly up‐regulated proteins and 11 significant down‐regulated protein in AD and MCI were identified by NULISAseq 120plex CNS panel. CSF protein profiling by in house LC‐MS is still pending. 5 (3 from plasma, and 2 from CSF) significantly up‐regulated novel proteins in MCI and CD have been reported to be associated with neuronal connectivity, neuro inflammation or acting as a neuromodulator. Sample correlation in CSF between NULISAseq and Simoa (Single Molecule Array) was also verified by NFL and pTau181. Both proteins displayed excellent correlation (R2 was 0.88 and 0.92).Conclusion5 novel significantly upregulated protein biomarkers in MCI and AD were identified by combined in house MS and new emerging NULISAseq technologies. The integrated proteomic method could be a powerful tool to identify the molecular signature and pathological pathways associated with AD and MCI.
Plasma biomarkers discrimination accuracy of biologically defined Alzheimer’s disease in a memory clinic setting
Authors: Anastasi Federica , Puig‐Pijoan Albert , Ashton Nicholas J. , Ortiz‐Romero Paula , Jiménez‐Moyano Esther , Torres‐Torronteras Javier , Escalante Armand González , Milà‐Alomà Marta , Contador José , Fernández‐Lebrero Aida , Garcia‐Escobar Greta , Bastard Nathalie Le , Nadal Alicia , Sahajan Aparna , Hao Qinyu , Zhang Bingqing , Grau‐Rivera Oriol , Zetterberg Henrik , del Campo Marta , Blennow Kaj , Suárez‐Calvet Marc 
Published: January 2025

AbstractBackgroundBlood‐based biomarkers offer a non‐invasive and cost‐effective means for Alzheimer's disease (AD) detection. In this study, we performed a direct comparison of these novel biomarkers in a memory clinic population to facilitate their implementation into clinical practice.MethodWe included a total of 208 patients with cognitive complaints from the BIODEGMAR cohort at Hospital del Mar (Barcelona, Spain). CSF was used as standard‐of‐truth and patients were categorized as having an AD CSF profile with two approaches: Lumipulse CSF Aβ42/p‐tau181<10.25 (N=208) or Elecsys® p‐tau181/Aβ42>0.022 (N=157). The following biomarkers were measured in paired plasma and CSF samples: Aβ42 and p‐tau181 (Lumipulse CSF<CE>, plasma<RUO>, Fujirebio), Aβ42 and p‐tau181 (NeuroToolKit (NTK) a panel of robust prototype assays (Roche Diagnostics International Ltd), and p‐tau181, p‐tau217, p‐tau231 and MAP‐T (NULISA, Alamar). P‐value and effect size of the group comparison (AD vs non‐AD CSF profiles) were calculated using a Mann‐Whitney U test. ROC curve analysis evaluated plasma biomarkers accuracy to discriminate AD from non‐AD CSF profiles. Spearman test was used to assess the correlation between plasma and CSF biomarkers.ResultDemographic information of the study cohort is reported in Table 1 for both classification thresholds. All plasma biomarkers were significantly different between the AD and non‐AD CSF profile groups, but the effect size varied among them. Specifically, NULISA p‐tau217, Lumipulse p‐tau181 and NULISA p‐tau231 reported the greatest effect sizes for the Lumipulse threshold and NULISA p‐tau217, NTK p‐tau181, Lumipulse p‐tau181 and NULISA p‐tau231 reported the greatest effect sizes for the Elecsys® threshold (Table 1). ROC curve analysis performed consistently over the two thresholds with the following discrimination accuracy (AUC) values (from highest to lowest): NULISA p‐tau217, NTK p‐tau181, NULISA p‐tau231, Lumipulse p‐tau181, NULISA p‐tau181 (Figure 1). In comparison to the p‐tau assays, Aβ42 reported modest effect size and AUCs. NULISA p‐tau217 and NULISA p‐tau231 had the highest correlation between plasma and CSF (Spearman ρ=0.75 and ρ=0.60, respectively, with both FDR corrected p‐values<0.001), Figure 2.ConclusionIn a memory clinic population, various plasma Aβ and tau plasma biomarkers, targeting different epitope and using different platforms, demonstrated high performance in distinguishing patients with biologically defined AD from those without.
A Large Public Release of Clinical and Imaging Data from the Mayo Clinic Study of Aging
Authors: Schwarz Christopher G. , Kremers Walter K. , Prakaashana Carl M. , Przybelski Scott A. , Christenson Luke R. , Wiliams Josie M. , Gunter Jeffrey L. , Senjem Matthew L. , Arani Arvin , Reid Robert I. , Machulda Mary M. , Fields Julie A. , Lowe Val J. , Kantarci Kejal , Graff‐Radford Jonathan , Vemuri Prashanthi , Petersen Ronald C. , Knopman David S. , Jack Clifford R. 
Published: January 2025

AbstractBackgroundThe Mayo Clinic Study of Aging (MCSA) is a longitudinal, population‐based study of residents of Olmsted County, Minnesota, USA. MCSA is releasing de‐identified clinical and imaging data on GAAIN.org to benefit the research community.MethodWe included longitudinal clinical data from all participants of the Mayo Clinic Study of Aging 30‐90 years of age (average 70.0y) through the first 15 years of the study. Clinical data includes age, sex, self‐reported race/ethnicity, APoE4 allele status, cognitive impairment status (normal, MCI, dementia, or other), height, weight, blood pressure, multi‐domain neuropsychological scores, neuroimaging summary measurements, medications, cardiovascular risk factors, social activity, sleep, mood/anxiety, functional measures, and more.For our initial release of imaging data, we selected the first imaging timepoint acquired on 3T GE MRI scanners and amyloid (PiB) PET during the same visit, from all available imaging participants 50‐90 years of age (average 70.7y). Currently, we included 3D T1‐weighted (MPRAGE) MRI (1x1x1.2mm3), T2‐weighted FLAIR MRI (0.85x0.85x3.6mm3), diffusion MRI (2.7mm resolution with 41 directions at b=1000 and 5 b=0), and numeric cortical global SUVR and Centiloid values from PiB PET scans at 40‐60 minutes post‐injection. All images are released in DICOM format and thoroughly de‐identified using CTP while ensuring preservation of necessary fields for analyses. T1‐weighted and T2‐FLAIR MRI were also de‐faced (identifiable face imagery was removed and replaced with an average) using mri_reface version 0.3.3 to further protect participants’ privacy, and all de‐faced images were visually inspected by a trained data scientist for quality assurance.ResultThe first phase of our public data release includes clinical data from 5925 unique participants from the Mayo Clinic Study of Aging (MCSA), each ranging from 1‐12 visits at roughly 15‐month intervals, and three MRI sequences (T1‐w, T2‐w‐FLAIR, and diffusion) from 1802 unique participants. Demographic summaries are given in Table 1.ConclusionThis large, richly characterized, de‐identified clinical and imaging dataset is available to the research community at https://www.gaaindata.org/partner/MCSA, and it is suitable for a wide range of research uses. Additional data will be released over time, including de‐faced amyloid PET images.
Multi‐ancestry genome‐wide association study of plasma glial fibrillary acidic protein (GFAP)
Authors: Fornage Myriam , Xia Rui , Almeida Marcio A , Bis Joshua C , Cui Biqi , de Rojas Itziar , Decarli Charles , Gudmundsdottir Valborg , Jian Xueqiu , Mishra Aniket , Mosley Thomas H. , Olivé Clàudia , Yang Qiong , Sanchez‐Juan Pascual , Blangero John , Debette Stéphanie , González Hector M , Gudnason Vilmundur , Launer Lenore J. , Psaty Bruce M. , Ruiz Agustin , Satizabal Claudia L , Seshadri Sudha 
Published: January 2025

AbstractBackgroundGlial fibrillary acidic protein (GFAP) is an astrocytic cytoskeletal protein and a promising blood biomarker for Alzheimer's disease (AD) and other neurodegenerative diseases. To date, the genetic architecture of plasma GFAP has not been characterized. We conducted a multi‐ancestry meta‐analyses of genome‐wide association studies (GWAS) in diverse population‐based cohorts to identify genetic variants associated with plasma levels of GFAP and to investigate their implication for neurological diseases.MethodsCirculating GFAP levels were assayed by ultrasensitive single molecule array (Simoa) immunoassay. We performed ancestry‐specific and ancestry‐combined meta‐analyses of GWAS in 17,028 individuals (mean age: 64.5 years; 60% women) of diverse ancestry (African (AA), N=1163; Hispanic (HA), N=7405; European (EA), N=8460) from 12 community‐based cohorts.ResultsIn the combined sample, we identified 7 loci associated with plasma GFAP. These were located in or near genes encoding APOE, CAPN1, CAPN2, GFAP, TMEM106B, PPP1R3C, and LOC105375672. The strongest association was with the APOE4 variant rs429358 (P=2.6x10‐40). However, this association was heterogeneous by ancestry, with stronger effects in EA, weaker in HA, and no association in AA. Ancestry‐specific meta‐analyses identified additional loci, including ZFAND3 in EA (Figure 1) and CAPN2 in HA (Figure 2), which were not observed in the other ancestries. No locus reached genome‐wide significance in AA. Using fine‐mapping methods incorporating functional annotation, gene expression, and linkage disequilibrium, we further prioritized potential causal variants and genes at the identified loci and investigated their implication for major neurological diseases, including AD.ConclusionOur GWAS of plasma GFAP has identified multiple loci with ancestry‐specific or cross‐ancestry effects. Our multi‐ancestry, integrative approach extends knowledge about the biology of GFAP and its shared genetic architecture with neurological disease.
Comparing de‐facing software MiDeFace and mri_reface according to privacy protection and effects on downstream measurements
Authors: Schwarz Christopher G. , Prakaashana Carl M. , Kremers Walter K. , Gunter Jeffrey L. , Senjem Matthew L. , Vemuri Prashanthi , Kantarci Kejal , Graff‐Radford Jonathan , Knopman David S. , Petersen Ronald C. , Jack Clifford R. ,   The Alzheimer's Disease Neuroimaging Initiative
Published: January 2025

AbstractBackgroundSeveral programs are available for automatically “de‐facing” brain images. These are designed to prevent the potential use of face imagery to re‐identify research participants. Previous works have compared available software and mri_reface is frequently among the top methods. The “Minimally Invasive DeFacing of MRI images” (MiDeFace) program was more recently added to FreeSurfer, but minimal validation of MiDeFace has been published.MethodWe ran mri_reface 0.3.3 and MiDeFace 7.3.2 on two datasets: A) 207 participants with face photographs and 3D T1‐weighted and 3D T2‐weighted‐FLAIR MRI from the Mayo Clinic Study of Aging (all unimpaired, Siemens); and B) 300 participants from ADNI3 with 3D T1‐weighted MRI (50 unimpaired + 50 with clinical AD, from each of 3 vendors). For dataset A, we tested the rate at which Microsoft Azure face recognition matched each participant’s photographs with the correct MRI, comparing unmodified images, those from mri_reface, and those from MiDeFace. For dataset B, we compared measured regional brain volume and cortical thickness from original vs. de‐faced images with SPM12, FreeSurfer 7.4.1, and the FSL‐UK Biobank pipeline. For both datasets, images were visually rated to assess removal of the face and retention of brain tissue.ResultAutomated face recognition match rates were lower with mri_reface (17/207 8.2%) than with MiDeFace (24/207 11.6%), indicating stronger identity protection with mri_reface, but both were greatly reduced vs. unmodified images (203/207 98.1%). Example images with both programs are shown in Figure 1. From visual ratings (Table 1), rates of complete success (modification of the entire face while retaining the entire brain) were much higher with mri_reface, but the great majority of failures from MiDeFace were subtle and occurred in relatively less recognizable face regions. The effects of both programs on downstream imaging measurements (Figure 2) were small and very comparable, but MiDeFace was favored mildly for SPM12 and for FSL, while mri_reface was more favored for FreeSurfer.ConclusionAltogether, mri_reface more reliably removed the complete face, leading to smaller rates of potential re‐identification (8.2% vs 11.6%). Effects on downstream image measurements were small and comparable with both methods.
Spatial Pattern of Medial Temporal Lobe Cross‐Sectional and Longitudinal Structural Change in Cognitively Normal Individuals
Authors: Xie Long , Das Sandhitsu R. , Li Yue , Wisse Laura E.M. , McGrew Emily , Lyu Xueying , DiCalogero Michael , Shah Ujashi , Ilesanmi Ademola , Denning Amanda E , Brown Christopher D. , Cohen Jesse S , Sreepada Lasya P , Dong Mengjin , Sadeghpour Niyousha , Khandelwal Pulkit , Ittyerah Ranjit , Ravikumar Sadhana , Sadaghiani Shokufeh , Hrybouski Stanislau , de Flores Robin , Gibson Eli , Yushkevich Paul A. , Wolk David A 
Published: January 2025

AbstractBackgroundThe medial temporal lobe's (MTL) early involvement in tau pathology makes it a key focus in the development of preclinical Alzheimer’s disease (AD) biomarkers. ROI analyses in prior studies reported significant MTL structural differences in cognitively normal individuals with and without β‐amyloid (A+/‐CN). Pointwise analysis, offering spatial information of early neurodegeneration, has potential to pinpoint “signature regions” of pathological change, but has been underexplored in the MTL. This study employs a specialized pointwise analysis pipeline to examine the spatial pattern of MTL structural change in subgroups dichotomized by both β‐amyloid and tau status in a large cohort of CN individuals.MethodsA dataset of 3036 CN (A‐/A+: 1270/1558, Table 1) individuals from ADNI, HABS, A4 and ABC were analyzed. We extracted MTL regional thickness maps from MRI using tailored pipelines, ASHS‐T1 and CRASHS. For participants with prospective longitudinal MRI (five years follow‐up), regional maps of longitudinal atrophy rate were extracted using SkelDBM. Subjects with cross‐sectional tau PET available (N=563) were further divided into A and T subgroups by tracer uptake. General linear modeling was performed on each surface point to investigate cross‐sectional and longitudinal MTL structural group differences (detailed in Figure 1) and their correlation with MTL tau burden in All/A+/A‐ CN. Age and sex were covariates and cluster‐level multiple comparison correction was performed.ResultsA+CN demonstrated a significantly faster atrophy rate than A‐CN across the whole MTL, primarily driven by A+T+CN individuals (Figure 1‐b). Notably, A‐T+CN showed significantly faster atrophy rate in the entorhinal cortex (ERC) and Brodmann area 35 (BA35), the earliest sites of tau pathology (Figure 1‐b, second column). Figure 2‐b displays an MTL‐wise significant correlation between atrophy rate and tau in All/A+/A‐ CN. In both analyses, cross‐sectional effects are consistently weaker than longitudinal ones, but have some significant clusters in ERC and BA35.ConclusionsPointwise analysis revealed extensive tau‐associated accelerated neurodegeneration in the MTL in preclinical AD. Furthermore, accelerated atrophy was observed in early Braak regions in A‐CN with evidence of tau pathology, potentially driven by primary age‐related tauopathy (PART). These pointwise longitudinal MTL measures provide sensitive measures that may allow for disease monitoring in preclinical AD.