bluuebunny/crossref_metadata_2025_split huggingface dataset:
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.
Measuring the Potential Risk of Re‐identification of Imaging Research Participants from Open‐Source Automated Face Recognition Software
Authors: Prakaashana Carl M. , Savvides Marios , Gunter Jeffrey L. , Senjem Matthew L. , Vemuri Prashanthi , Kantarci Kejal , Graff‐Radford Jonathan , Knopman David S. , Petersen Ronald C. , Jack Clifford R. , Schwarz Christopher G. 
Published: January 2025

AbstractBackgroundResearch subjects can potentially be re‐identified from de‐identified MRI, CT, and PET brain scans with up to 98% accuracy using Microsoft Azure’s cloud‐based commercial facial recognition software. This showed the need to “de‐face” publicly shared research brain scans. Subsequently, Microsoft has begun restricting its face recognition services, intending to prevent misuse. This study tests a variety of popular open‐source computer vision and facial recognition software packages to measure the re‐identification risk with only unrestricted free software.MethodThis study used brain MRI from Siemens 3T scanners and face photographs from 182 participants (ages 30‐90+) in the Mayo Clinic Study of Aging. Each participant had photos taken with an iPad, which were cropped loosely around the head and converted to black and white. A total of 81 renders (2D reconstruction images; Figure 1) were made from each 3D T2‐FLAIR MRI, simulating various camera and lighting positions. These face renders approximate black and white photos, allowing use with software packages developed for matching faces/features between photographs. Open‐source Python packages (OpenCV, DeepFace, face_recognition, scikit‐learn) and their included pre‐trained models (designed for photographs) were used to match participant photographs to the labelled library of MRI‐based face renders. A correct match was recorded when the top‐scoring render or set of renders automatically chosen by the algorithm was from the MRI of the correct participant.ResultFeature matching with ORB and SWIFT (both from OpenCV) produced no correct matches, despite a prior publication reporting moderate success. The best match rates (Figure 2) were 58‐59% accuracy using face_recognition or DeepFace packages with support vector machines (SVMs). Without SVMs, these packages performed modestly worse (51%‐55%).ConclusionWhile the highest match rates obtained by widely available open‐source packages (roughly 60%) are much lower than those of a limited‐access commercial product (Microsoft Azure, with 98%), they show that actors with only access to no‐cost readily available software could still re‐identify a research subject from a brain scan most of the time. This further highlights the need for image refacing software, such as mri_reface, to protect the privacy and identifies of research volunteers.
Associations between tau accumulation and cognitive decline across the AD continuum differ by sex
Authors: Singleton Ellen Hanna , Mattsson‐Carlgren Niklas , Binette Alexa Pichet , Strandberg Olof , Stomrud Erik , Ossenkoppele Rik , Hansson Oskar 
Published: January 2025

AbstractBackgroundfemale sex has been associated with faster tau accumulation over time and greater resilience in Alzheimer’s disease. However, relatively few studies have examined regional tau accumulation rates and cognitive resilience in a large amyloid‐positive cohort.MethodWe included n=761 amyloid‐positive (A+) participants from the Swedish BioFINDER‐2 study who had undergone (longitudinal) tau PET and cognitive testing, of whom n=253 were cognitively unimpaired (CU A+) and n=508 were cognitively impaired (CI A+). [18F]RO948‐tau‐PET SUVR within entorhinal, medial temporal, neocortical temporal, medial parietal, lateral parietal, occipital, frontal, anterior cingulate, insula and cortical composite regions was quantified. Cognition was assessed with the modified preclinical Alzheimer’s disease cognitive composite (mPACC5). Linear mixed models were fitted to assess the effect of the interaction between sex and baseline tau on cognition over time, adjusting for age, education and APOE e4 status.ResultDemographic characteristics are shown in Table 1. Models assessing the effect of the interaction between baseline tau and sex on cognitive decline showed significant positive associations between multiple tau regions in CU A+ and longitudinal mPACC5 (medial parietal: 0.39±0.10, p=0.0005, lateral parietal: 0.31±0.08, p=0.0005, occipital: 0.26±0.07, p=0.0005, lateral temporal: 0.23±0.07, p=0.006, inferior middle temporal: 0.18±0.07, p=0.03, insula: 0.17±0.07, p=0.04, Figure 1), while models showed significant negative associations between some tau regions in CI A+ and longitudinal mPACC5 (lateral temporal: ‐0.38±0.11, p=0.007, inferior middle temporal: ‐0.35±0.11, p=0.01, anterior cingulate: ‐0.35±0.13, p=0.03, Figure 1). Assessing cognitive trajectories by sex per quartiles of baseline tau burden revealed that females show similar cognitive trajectories to males in the 1st‐3rd quartiles of tau burden, but seem to show less cognitive decline in the 4th quartile of tau burden in CU, while in CI, females show a steeper decline than males (Figure 2).ConclusionOur results suggest that cognitively unimpaired A+ females exhibit greater cognitive resilience, while cognitively impaired A+ females exhibit steeper cognitive decline than males in the face of tau pathology, and that these effects occur particularly at high levels of tau pathology.
Multisite Chronic Pain Accelerates Cognitive Decline Particularly in APOE e4 Allele Carriers
Authors: Bell Tyler R. , Franz Carol E. , Lerman Imanuel , Fennema‐Notestine Christine , Panizzon Matthew S. , Bennett David A. , Elman Jeremy A. , Kremen William S. 
Published: January 2025

AbstractBackgroundChronic pain is a predictor of cognitive decline and dementia, but whether risk is related to a specific site of pain versus multisite pain is unclear. Multisite chronic pain is theorized to involve hyper‐excitability in pain receptors and pain‐processing brain regions, possibly caused by neuroinflammation. These factors may increase vulnerability to cognitive decline, particularly in those at elevated risk for Alzheimer’s disease. We examined how multisite chronic pain relates to cognitive decline in older adults, the possible moderating role of APOE‐e4 allele status, and—in a postmortem subsample—associations with amyloid and tau.MethodWe examined 751 participants without dementia at baseline from the Religious Orders Study/Rush Memory and Aging Project (ROSMAP; Mean age = 79.47, SD = 6.93, Mean education = 6.42, SD = 3.63; 64% women) followed for up to 30 years with repeated cognitive testing measuring episodic memory, working memory, perceptual orientation, and processing speed (Mean years followed = 7.32, SD = 4.51). Individuals with multisite chronic pain, defined as joint pain in >2 body regions over the first 2 study waves, were compared to those without pain. Amyloid‐beta and tau were measured in a postmortem subsample assessed around 10 months after their last clinical evaluation using computer‐assisted immunoreactivity assays across 8 regions associated with Alzheimer’s disease (hippocampus; entorhinal cortex; midfrontal cortex; inferior temporal; angular gyrus; calcarine cortex; anterior cingulate cortex; superior frontal cortexResultMultisite chronic pain (n = 105) was associated with accelerated decline in episodic memory (b = ‐.03, p = .016) and processing speed (b = ‐.06, p<.001), particularly in APOE‐e4‐positive individuals (bs = ‐.05 and ‐.04, respectively, ps<.01). Only APOE‐e4‐positive individuals with multisite chronic pain showed significant decline in perceptual orientation (b = ‐.08, p = .015). Only APOE‐e4‐positive individuals with multisite chronic pain had higher levels of amyloid‐beta load compared to those without chronic pain (b = .51, p<.001). No differences in tau burden were detected. People with single‐site chronic pain showed no significant differences from people without chronic pain.ConclusionThe results suggest that multisite chronic pain exacerbates cognitive decline, particularly in those at genetic risk for Alzheimer’s disease. In addition, the postmortem analyses suggest that early treatment of multisite chronic pain—a modifiable risk factor—might help to reduce amyloid accumulation.
Multi‐cohort temporal modeling of tau PET onset age and trajectories
Authors: Teague Jordan P , Heston Margo B. , Chavez Elena Ruiz De , Navaratna Ruvini , Cody Karly Alex , Morse Jacob , Deming Yuetiva , Christian Bradley T. , Johnson Sterling C. , Langhough Rebecca E. , Betthauser Tobey J. 
Published: January 2025

AbstractBackgroundSampled iterative local approximation (SILA) is a temporal modeling method previously validated in three cohorts to estimate person‐level amyloid PET onset age and predicted change. This study validates SILA to model longitudinal tau PET trajectories, generate person‐level estimated tau onset age (ETOA), and characterize forward and backward prediction accuracy in the Wisconsin Registry for Alzheimer’s Prevention (WRAP), Wisconsin Alzheimer’s Disease Research Center (WADRC), and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).MethodN=273 participants (mean(SD) baseline age=70.79(6.70)) from WRAP and WADRC underwent longitudinal 18 F‐MK‐6240 tau PET imaging. Data processing included Harvard‐Oxford ROI parcellation of T1‐weighted MRI and generation of regional MK‐6240 standard uptake volume ratios (SUVR; inferior cerebellar GM reference region; 70‐90 min). Volume‐weighted SUVR corresponding to the meta‐temporal composite (MTC) was averaged across amygdala, parahippocampal gyrus, temporal fusiform cortex, inferior‐temporal, and middle‐temporal bilateral ROIs. Gaussian mixture modeling was applied to baseline SUVR to establish tau positivity (T+) thresholds (MK‐6240 SUVR>1.39; FTP SUVR>1.36) 2SD above the mean of the lower distribution. Ten‐fold cross validation was used to characterize forward and backward SUVR prediction and T+/‐ stratification accuracy. Forward prediction was evaluated by predicting SUVR at each person’s last observation inputting each person’s first observation whereas backward prediction used the last observation to predict SUVR at the first observation. Results were compared with SILA validation using UC‐Berkeley processed ADNI Flortaucipir data with similar processing methods.ResultSILA exhibited similar prediction accuracy and midpoint conversion error in Wisconsin and ADNI studies. Figure 1B/D depicts MTC‐tau onset‐age‐aligned trajectories in Wisconsin and ADNI cohorts, respectively. Backward SUVR prediction error was lower and T+/‐ stratification accuracy was higher than forward prediction (ADNI RMSEforward=0.12, ADNI RMSEbackward=0.08; WI RMSEforward=0.22, WI RMSEbackward=0.17; forward accuracy=0.90, 0.92; backward prediction accuracy=0.96, 0.98 for ADNI and WI, respectively; Table 1). In the T‐ to T+ converters subset, backwards ETOA confidence intervals were within ‐2.68 to 2.04 years of midpoint between the observed last negative and first positive scan (Figure 2).ConclusionSILA provides replicable estimates of T+ onset age and similar prediction accuracy with MK‐6240 and FTP. Future work will investigate how sources of tau PET variability influence temporal modeling outcomes.
Association of Chronic pain with Alzheimer’s‐related brain structure and plasma biomarkers in older men
Authors: Bell Tyler R. , Franz Carol E. , Fennema‐Notestine Christine , Panizzon Matthew S. , Lyons Michael J. , Elman Jeremy A. , Kremen William S. 
Published: January 2025

AbstractBackgroundChronic pain leads to tau accumulation and hippocampal atrophy in mice. Tau accumulation in the locus coeruleus (LC) precedes medial temporal accumulation in humans. Here we provide one of the first human studies examining the association of chronic pain with hippocampal volume, LC integrity, and Alzheimer’s Disease (AD)‐related plasma biomarkers. We predicted associations with rostral‐middle, but not caudal, LC because the former is more aging‐ and Alzheimer’s‐related.MethodData were from 3 waves of the Vietnam Era Twin Study of Aging (VETSA) at average ages 56, 62, and 68. Chronic pain was defined as moderate‐to‐severe pain occurring >2 waves. At wave 3, 424 participants (mean age = 67.06) underwent LC‐sensitive MRI scans from which we calculated an LC contrast‐to‐noise ratio (LCCNR), an index of LC integrity. We measured hippocampal volume with traditional structural MRI. At wave 3, biomarkers were obtained from fasting blood draws taken the morning of the medical interview and cognitive testing, typically a day prior to the MRI exam. Immunoassays calculated levels of plasma total tau, beta‐amyloid (Aß) 40, Aß42, Aß42/Aß40 ratio, and neurofilament light (NfL). All biomarkers were log‐transformed and adjusted for site and storage time. Analyses accounted age, major health conditions, depressive symptoms, and opioid use.ResultMen with chronic pain had smaller hippocampal volume (ß = ‐0.24, p = .039) and lower rostral‐middle LCCNR (ß = ‐0.38, p = .004) but not caudal LCCNR (p = .750). Men with chronic pain also had higher levels of plasma total tau (ß = ‐0.32, p = .047), Aß42 (ß = .42, p = .033), and Aß40 (ß = .31, p = .032) compared to men without chronic pain. However, men with chronic pain did not differ from men without chronic pain on Aß42/Aß40 ratio (p = .979) or NfL (p = .313).ConclusionExtending the animal model, these findings suggest that chronic pain is associated with tau accumulation and reduced structural brain integrity in regions affected very early in the development of AD. Increases in individual Aß measures associated among those with chronic pain but lack of association with the Aß42/Aß40 ratio may reflect non‐AD‐specific health‐related factors rather than brain amyloid, or alternatively, might be due to the relatively young age of the sample or the sensitivity of the assay.
Relationships between PET and blood plasma biomarkers in corticobasal syndrome
Authors: Singh Neha Atulkumar , Alnobani Alla , Graff‐Radford Jonathan , Machulda Mary M. , Mielke Michelle M. , Schwarz Christopher G. , Senjem Matthew L. , Jack Clifford R. , Lowe Val J. , Kanekiyo Takahisa , Josephs Keith A. , Whitwell Jennifer L. 
Published: January 2025

AbstractBackgroundCorticobasal syndrome (CBS) is a progressive neurodegenerative syndrome that can result from several underlying neuropathologies, including Alzheimer’s disease (AD). Little is known about the utility of blood plasma measures to predict PET biomarker confirmed AD in CBS.MethodEighteen CBS patients (8 PET Aß+; 10 PET Aß‐) and 8 cognitively unimpaired Aß‐ individuals (CU) were recruited by the Neurodegenerative Research group from the Department of Neurology, Mayo Clinic, Rochester, MN, underwent Aß (Pittsburgh Compound‐B) and tau (18F‐flortaucipir) PET and provided a blood sample. Blood plasma analysis was performed to assess p‐tau 181, total tau, Aß 42/40, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) using the Quanterix Simoa platform. Plasma concentrations were compared between Aß‐, and Aß+ CBS and controls using Kruskal‐Wallis corrected for multiple comparisons using Dunn’s test, with effect size measured with area under the receiver operating characteristic curve (AUROC) analysis. Spearman correlations were calculated to assess relationships between plasma concentrations and Aß and tau PET uptake.ResultThe CBS Aß+ group showed reduced Aß42/40 ratio, with elevated p‐tau 181, GFAP and NfL plasma concentrations compared to CU, while the CBS Aß‐ group only showed elevated NfL concentration compared to CU (Figure 1). Both p‐tau 181 (AUROC=0.95) and GFAP (AUROC=0.91) plasma concentrations were able to differentiate CBS Aß‐ from CBS Aß+. Plasma p‐tau 181 and GFAP concentrations showed a positive correlation to both Aß and tau PET uptake, and the Aß42/40 ratio showed a negative correlation to Aß PET uptake (Figure 2). No correlations were observed between NfL and Aß and tau PET.ConclusionThis study supports the use of plasma p‐tau 181 and GFAP to detect AD in CBS, while NfL shows potential as a nonspecific disease biomarker of CBS regardless of underlying pathology. Plasma concentrations of these biomarkers may potentially be incorporated into clinical trials targeting CBS patients with underlying AD pathology.
Asymmetrical Neuroimaging Insights in CSF‐Validated Early‐Onset Alzheimer's: Integrating PET, MRI, and Cognitive Assessment
Authors: Özçelik Sinem , Yiğit Pınar , Bozdemir Tolga Can , Kaya Gamze Çapa , Yildirim Zerrin , Tee Boon Lead , Gurvit Hakan , Yener Görsev , Tempini Maria Luisa Gorno , Öz Didem 
Published: January 2025

AbstractBackgroundEarly‐onset Alzheimer's disease (EOAD), manifesting before age 65, demands nuanced diagnostic approaches. FDG18‐PET unveils metabolic insights, the MRI scale captures structural changes, and ACE‐R assesses cognitive impairment details. A holistic evaluation enhances diagnostic precision and enriches our understanding of cognitive decline in early‐onset presentations.MethodEarly‐onset Alzheimer's disease (EOAD), manifesting before age 65, demands nuanced diagnostic approaches. FDG18‐PET unveils metabolic insights, the MRI scale captures structural changes, and ACE‐R assesses cognitive impairment details. A holistic evaluation enhances diagnostic precision and enriches our understanding of cognitive decline in early‐onset presentations.ResultTwenty‐two patients (59.1% women) with a mean age at diagnosis of 55.3 (±6.52 StD) years participated. The mean disease duration was 5.06 (±2.95 StD) years. All of the patients were right‐handed. The mean Aß42 and phos‐tau were 392.49 (±200.13 StD) and 130.93 (±142.56 StD) pg/ml, respectively. No significant difference was found between the right and left insular cortex in PET, and no statistically significant asymmetry was found between VAS scores in MRI (p > 0.05). There was no correlation between PET index with CSF Aß42 and and phos‐tau values.ConclusionThis study underscores notable asymmetries in PET atrophy scores between the corresponding right and left brain regions in Alzheimer's patients. Given that EOAD manifests with atypical clinical symptoms, and all participants in this study exhibited left‐hemispheric dominance, the observed metabolic asymmetry, in the absence of a corresponding structural asymmetry, holds clinical significance.
Association of amyloid and tau pathology in longitudinal cognitive reserve
Authors: Borelli Wyllians Vendramini , Schlickmann Thomas Hugentobler , Ferrari‐Souza João Pedro , de Bastiani Marco Antônio , Bieger Andrei , Schilling Lucas Porcello , Rosa‐Neto Pedro , Zimmer Eduardo R. 
Published: January 2025

AbstractBackgroundHigher educational attainment is frequently associated with lower risk of cognitive decline. Many neuroprotective factors have been suggested as the biological underpinnings of cognitive reserve (CR), though the neural basis of CR is yet unclear. Herein, we aim at investigating the effect of CR using educational attainment in individuals stratified by amyloid and tau status.MethodA total of 135 participants, classified as cognitively unimpaired (CU) or Mild Cognitively Impaired (MCI), were selected from the ADNI cohort. All individuals that presented longitudinal measures and available amyloid and tau PET at baseline were included in this study. Formal years of education were selected as a proxy of cognitive reserve in this study, and individuals were classified into high CR (>17 years of education), intermediate CR (between 17 and 16), and low CR (<16 years of education) based on interquartile range. This analysis was in accordance with the most recent research framework to identify the mechanisms of cognitive reserve. A linear mixed‐effect model was performed to evaluate the interaction of cognitive reserve in the relationship between cognitive decline and AT status. The model was adjusted for age, sex, baseline diagnosis. Data is presented in mean±SD.ResultA total of 58 high CR (71.7±5, 57% males), 41 intermediate CR (70.4±6, 59% males) and 36 low CR (69.8±6.4% males) were included (Table). At baseline, these individuals were divided as A‐T‐ (n = 69), A‐T+ (n = 11), A+T‐ (n = 27) and A+T+ (n = 28). Mean follow‐up time of the sample was 3.15±0.9 years. Linear mixed‐effect model showed a significant interaction of cognitive reserve in the relationship between CDR‐SOB and A+T+ status (beta = 0.24, p‐val = 0.019), after adjusting for covariates. Sensitivity analysis adjusting for APOE status also demonstrated the same relationship.ConclusionThe neuroprotective effect of cognitive reserve was prominent in individuals with both amyloid and tau pathology, but not in the Alzheimer’s pathological changes (A+T‐). Understanding the neural basis of cognitive reserve may greatly improve the advancements in therapeutic targets for secondary prevention of cognitive decline in individuals with identified Alzheimer’s disease pathology.