bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between Tau and Cognition as a Function of Age
Authors: Ackley Sarah F , Wang Jingxuan , Decarli Charles , Fletcher Evan , La Joie Renaud , Corrada María M. M. , Glymour M. Maria 
Published: January 2025

AbstractBackgroundThe relationship between tau pathology and cognition as a function of age and whether these relationships are consistent across samples is unknown. A growing number of studies now perform positron emission tomography with tau ligands (tau‐PET), making it possible for an improved understanding of the dynamics of tau and cognition in relation to other biomarkers.MethodWe used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort (ages 55‐90) and The 90+ Study (Table 1) to cover a broad age range. We examined the association between region‐specific tau uptake by composite Braak stage and cognitive outcomes at the visit at which tau‐PET was performed (ADNI) or the closest visit (90+). We examined two cognitive outcomes: the mini mental status exam (MMSE) and clinical dementia rating sum of box scores. Spearman‐rank correlation coefficients between tau‐PET standardized uptake value ratios (SUVRs) with cerebellar cortex normalization and cognitive outcome are calculated for four distinct age ranges in ADNI: <60, 60‐70, 70‐80, and 80+ and among the 90+ study participants. Associations adjusted for age and age‐squared, race/ethnicity, number of APOE‐e4 alleles, educational attainment, and gender are determined using bootstrapped linear regression.ResultThe association between region‐specific tau uptake by composite Braak stage and cognition appears consistent for ages 60‐80 (figures 1 and 2), with worse cognition with higher tau. Over age 80, tau does not appear to be associated with cognition. Based on point estimates, some associations appear to be reversed over age 80 in ADNI, which is not the case in the 90+ study, although these differences between cohorts are not statistically significant.ConclusionTau‐PET association varies with age, becoming less reliably associated with cognition over age 80. This is likely due to increased incidence of co‐occurring pathologies and selective survival. Associations may further depend on features of the source population.
Characterization of pulsations in the brain and cerebrospinal fluid using ultra‐high field magnetic resonance imaging
Authors: de Almeida Bruno , Martins Tiago Amaro , Wu Minjie , Wilckens Kristine A , Minhas Davneet S , Ibinson James W , Aizenstein Howard J , Santini Tales , Ibrahim Tamer S 
Published: January 2025

AbstractBackgroundBrain fluid flow plays a crucial role in maintaining brain health by eliminating potentially harmful waste products like amyloid‐beta and tau [1‐2]. This process is potentially facilitated by pulsations in the perivascular space, influenced by the neurovascular unit and autonomic nervous system, which may vary in brain diseases such as Alzheimer’s disease (AD) [3‐4]. Using a 7 Tesla MRI scanner and ultrafast echo‐planar imaging (EPI), we developed a non‐invasive neuroimaging methodology to characterize the in‐vivo frequency and amplitude responses of pulsations of cerebrospinal fluid (CSF) flow.MethodBrain images from six volunteers were acquired using a 7T MRI Scanner and an in‐house developed 16‐channel Tic‐Tac‐Toe transmit array with a 32‐channel receive coil. The human‐connectome EPI multiband MR sequence was optimized to present a real‐time visualization of the CSF flow in the brain. For the first volunteer, two axial and one sagittal slices were obtained, while whole‐brain coverage was acquired for the remaining volunteers, where the acquisition was divided into 19 slabs, each consisting of 3 axial slices. A spectral analysis based on Fast Fourier Transform (FFT) was conducted for the whole brain and grey matter, white matter, and CSF regions.ResultFigure 1 presents the processed axial and sagittal slices acquired from the first volunteer, demonstrating the presence of a periodic variation of the CSF signal. Figure 2 presents the identification of peaks in the spectrum acquisitions of whole‐brain segments for one volunteer, which exhibited similar frequencies, magnitudes and bandwidths among different volunteers. Quantitative results of this analysis are summarized in Table 1.ConclusionThis project developed a real‐time visualization of CSF pulsations based on a non‐invasive ultrafast EPI obtained with a 7T MRI scanner. The identification of similar frequency peaks (around 0.3, 0.8, 1.1, 2.3 and 3.1 Hz) and magnitudes among healthy volunteers suggests its potential as a feasible biomarker. Future work will examine this technique’s potential to identify changes in brain fluid dynamics associated with AD progression and pathology. Funding: NIH R01AG063525, R01MH111265, University of Pittsburgh CRC’s RRID:SCR_022735.References:• Nedergaard, 2013• Xie et al., 2013• Peng et al., 2016• Ramanathan et al., 2015
Development of AI‐4‐AD tools for evaluation and prognosis of AD conversion: multi‐branch network and multi‐task deep learning algorism
Authors: Han Liang , Pang Ran , Ren Qing , Pu Xiujuan , Liu Yuan , Tan Yuanfan , Yang Qing X 
Published: January 2025

AbstractBackgroundAD prevention and early interventions require tools for evaluation of people during aging for diagnosis and prognosis of AD conversion. Since AD is a complicated continuum of neurodegenerative processes, developing of such tools have been difficult because it needs longitudinal and multimodal data which are often complicated and incomplete. To address this challenge, we are developing AI4AD framework using ADNI data.MethodAs shown in Fig. 1, we used the multimodal features of subjects in the initial four time points to predict the disease status after 1.5 years. The informative feature set with available multi‐modal data (MRI, PET and cognitive score (CSs)), is extracted as a multivariate time series. Then, a multi‐scale local temporal attention network (MCLAN) is constructed to extract corresponding deep features from three categories of multivariate time series respectively. Furthermore, a set of statistical features are extracted from multivariate the time series. Subsequently, fusion of selected deep features, statistical features and background knowledge (demographics, CSF, genetics feature) at baseline are performed using a DL feature network. Finally, AD and CSs predictions are realized utilizing multi‐task DL algorism with Adam optimization algorithm and the five‐fold cross‐validation method. 190 CN subjects, 347 MCI subjects and 20 AD subjects were selected according to the first visit diagnosis from TADPOLE database (Table 1a). The longitudinal data for training and ground truth of AD conversion are shown in Table 1(b).ResultThe accuracy (ACC), accuracy (PRE), recall (REC) and F1 score of the proposed AD prediction method in the AD classification were 93.57%, 93.55%, 93.68%, and 93.59%, respectively, which is greatly improved the predictive ability of those by the conventional methods (Table 2). In addition, the root mean square error (RMSE) on the CSs prediction of CDRSB, ADAS11, ADAS13 and MMSE are 0.5863, 0.5238, 0.4747 and 0.5417 respectively.ConclusionOur DL method consolidates multi‐modal medical information at different visits to predict the disease's progression, which greatly improved AD prognosis from those using traditional DL algorithms (CNN, LeNet and ResNet). The AI4AD framework proposed here can also be tailored to other diseases with similar data characteristics.
Short‐term Sirolimus Treatment Restores Hippocampus and Caudate Volumes and Global Cerebral Blood Flow in Asymptomatic APOE4 Carriers Compared with Non‐carriers
Authors: Flemister Abeoseh , Xing Xin , Overschmidt Jessica , Cassani Joanne , Green Stefan J. , Beversdorf David Q. , Woods Carter , Grinstead John W. , Altes Talissa A. , Lin Ai‐Ling , Govindarajan Maalavika 
Published: January 2025

AbstractBackgroundApolipoprotein e4 allele (APOE4) is the strongest genetic risk factor for late‐onset Alzheimer’s disease (AD). Compared with non‐carriers, cognitively normal APOE4 individuals have shown brain atrophy and lower cerebral blood flow (CBF) decades before AD pathological and clinical symptoms appear. The goal of the study is to determine if using Sirolimus, an FDA‐approved mTOR inhibitor, could restore the brain volumes in structures related to cognitive functions and global CBF (gCBF) for asymptomatic APOE4 carriers compared with non‐carriers.MethodThe study was performed at the University of Missouri. Low dose Sirolimus (1 mg/day) was given for 4 weeks to three middle‐aged, cognitively normal APOE4 carriers (F:M = 2:1) and two female APOE3 individuals (45‐65 yrs; MOCA > 27). Oral swabs were used to determine APOE status. 3T MRI‐based structural MPRAGE and T1‐weighted images, and pseudo‐continuous arterial spin‐labeled (PCASL, 1.7×1.7×4mm resolution) were acquired at baseline (pre‐treatment) and Post‐Sirolimus (the end of treatment). FreeSurfer 7.4 was used to automatically generate segments for volumetric analysis and PCASL images were analyzed via MANGO software for perfusion weighted gCBF.ResultAPOE4 carriers had significantly increased Caudate and Hippocampal volumes (Fig. 1A) and gCBF (Fig. 1B) after 4 weeks of Sirolimus treatment. These differences were not found in the non‐carriers (APOE3 participants). The quantitative data is shown in Table 1. It also shows that APOE4 carriers had significantly lower Hippocampal volume and gCBF at baseline compared with that of APOE3 participants (indicated by “**”), and Sirolimus tends to restore the values to closer to those of the non‐carriers. No side effects were observed, and no changes in blood glucose and HbAc1 levels were found in all the participants.ConclusionWe show that short‐term Sirolimus treatment can effectively restore brain volumes and gCBF for asymptomatic APOE4 carriers. Specifically in the caudate and hippocampus, which play many roles integral in normal cognitive functioning including memory, learning, and emotional regulation, has considerable atrophy in AD. The findings imply that Sirolimus may be useful and effective to mitigate or prevent AD developments for asymptomatic APOE4 carriers.
Association between Default Mode Network Connectivity Compared Between Two Tau Tracers (Flortaucipir vs. MK6240) – HEAD Study
Authors: Karim Helmet T. , Povala Guilherme , Bauer‐Negrini Guilherme , Lussier Firoza Z , Pascual Belen , Gordon Brian A. , Lowe Val J. , Oh Hwamee , soleimani‐meigooni David N. , Rosa‐Neto Pedro , Jagust William J. , Klunk William E , Baker Suzanne L. , Pascoal Tharick Ali 
Published: January 2025

AbstractBackgroundDefault mode network (DMN) resting state connectivity has been correlated with heightened amyloid and tau – hallmarks of Alzheimer’s Disease (AD). Tau is postulated to impact a meta‐temporal area including DMN‐associated regions like amygdala, entorhinal cortex, fusiform gyrus, parahippocampus, inferior temporal, and middle temporal gyrus. We recruited individuals with varying cognitive status to undergo resting state connectivity and imaging with two tau tracers (Flortaucipir and MK6240). We investigated the association between DMN connectivity and both global and regional (meta‐temporal) tau.MethodsWe studied 149 adults who were young cognitively healthy (n = 10, 21‐25 years, 5F), older cognitively healthy (n = 85, 50‐83 years, 51F), had MCI (n = 43, 53‐84 years, 23F), or had AD (n = 11, 62‐84, 6F). All individuals underwent resting state imaging and PET imaging with both Flortaucipir and MK6240 tau tracers. Resting data was preprocessed and DMN connectivity was estimated using bilateral posterior cingulate gyrus as region of interest. Tau tracer uptake was preprocessed (Pascoal. et al), and voxel‐wise standardized uptake value ratio (SUVR) was computed using inferior cerebellar gray matter as reference. We computed universal and meta‐temporal uptake for both tracers. We conducted four voxel‐wise associations between DMN connectivity and uptake in each tracer. We corrected for multiple comparisons using SnPM13 to estimate non‐parametric p‐values (10,000 permutations), we used a cluster forming threshold of p = 0.001 and corrected for multiple comparisons by controlling the family‐wise error rate (FWE) at p = 0.05.ResultsGreater universal Flortaucipir uptake was associated with lower within‐network DMN connectivity (bilateral posterior cingulate, precuneus, angular/supramarginal gyrus, and inferior parietal) but greater between‐network DMN connectivity (superior parietal, postcentral gyrus; Figure 1A). Greater universal MK6240 uptake was associated only with greater DMN‐cerebellum connectivity (Figure 1B). Greater meta‐temporal Flortaucipir was associated with lower within‐network DMN connectivity similar to universal uptake with addition of medial prefrontal cortex and middle temporal gyrus (Figure 2A). Greater meta‐temporal MK6240 was only associated with greater DMN‐superior parietal connectivity (Figure 2B).ConclusionsThese preliminary findings show that uptake using different tau tracers may lead to varying conclusions on association with connectivity. This may have implications for understanding the role of tau in altering resting state connectivity findings.
Potential Relative Effect of Intensive Systolic Blood Pressure Control on Preventing White Matter Damage Across Age Groups
Authors: Pruzin Jeremy J. , Kern Kyle C , Reboussin David M. , Cushman William C. , Gupta Aditi , Wright Clinton B. , Williamson Jeff D. , Tariot Pierre N. , Nasrallah Ilya M. , Pajewski Nicholas M. 
Published: January 2025

AbstractBackgroundIn the Systolic Blood Pressure Intervention Trial (SPRINT), intensive systolic blood pressure (SBP) lowering slowed progression of white matter injury (WMI) on MRI. We hypothesized that intensive lowering would be equally as effective and may confer greater benefits for brain health at younger ages compared to older ages. We tested whether the relative effects of intensive lowering on WMI differed by age using 2 MRI measures: white matter hyperintensity volume (WMHv) and peak‐width skeletonized mean diffusivity (PSMD) in SPRINT.MethodParticipants were age =50 with cardiovascular risk and randomized to intensive (SBP goal <120 mm Hg) or standard treatment (SBP goal <140 mm Hg). We calculated WMHv and PSMD in a subgroup of participants who had a baseline and follow‐up MRI. WMHv were inverse‐hyperbolic sine‐transformed, and the ratio of follow‐up to baseline used to quantify progression. PSMD progression was quantified as a difference. Using mixed‐effects linear models, we estimated the effects of age on relative progression in MRI markers between groups. Age effects were investigated as categorical (<65, 65‐75, or =75 years) or continuous.ResultFor participants in the intensive group (n=251 with follow‐up), mean SBP was 122 mmHg versus 135 mmHg in the standard group (n=201) over a median 3.9‐year MRI interval. The largest treatment effect on WMHv progression was found in the <65 age group (i.e. greatest relative reduction with intensive treatment): ‐0.19, 95%CI [‐0.27, ‐0.11]), followed by the 65‐75 age group (‐0.11, [‐0.21, ‐0.01]), and least in the >75 age group (‐0.06, [‐0.20, ‐0.08]) (Figure 1). Intensive treatment resulted in a 73%, 52%, and 20% reduction in WMHv progression respectively, although this was not statistically significant (p=0.21). Analyses of PSMD progression produced similar results (Figure 2). When using age as a continuous measure, the beneficial effect of intensive treatment waned with increasing age (Figure 3) without reaching statistical significance (p=0.19).ConclusionIntensive SBP lowering was equally as effective and may have a greater relative effect on reducing WMI when implemented at younger ages compared to older ages. Large prospective interventional studies that include younger individuals are needed to determine the effects of SBP on white matter integrity across the lifespan.
Creating Universal Tau PET Scale (Uniτ) Parametric Images – The HEAD Study
Authors: Povala Guilherme , Bauer‐Negrini Guilherme , Bellaver Bruna , Lussier Firoza Z , Amaral Livia , Ferreira Pamela C.L. , Finn Quentin , Zatt Bruno , Tudorascu Dana , Jagust William J. , Klunk William E , Lowe Val J. , Soleimani‐Meigooni David N. , Oh Hwamee , Pascual Belen , Gordon Brian A. , Rosa‐Neto Pedro , Baker Suzanne L. , Pascoal Tharick Ali 
Published: January 2025

AbstractBackgroundThe HEAD study focuses on collecting an extensive dataset from various tau‐PET tracers, aiming to establish robust anchor values, which are essential for harmonizing tau‐PET measurements. Here, we aim to showcase the capability of converting 3D tau‐PET images into a common scale using the Universal Tau‐PET Scale, Uniτ (tau), and to use these 3D images to subsequently obtain ROIs as needed.MethodsWe assessed 185 individuals across the aging and AD spectrum from the HEAD study, with [18F]Flortaucipir and [18F]MK‐6240 tau‐PET tracers. Tau‐PET SUVR images were standardized to a common 8mm FWHM, using the inferior cerebellar gray matter as the reference region. We generated Uniτ Tau‐PET 3D images using a single formula based on Meta‐temporal parameters in two steps: first, within‐tracer anchoring based on young (<25 years) and cognitively impaired individuals; second, between‐tracer anchoring using a piecewise transformation from [18F]Flortaucipir to [18F]MK‐6240, with smoothing at the piecewise inflection point. Subsequently, we extracted mean Uniτ values from these 3D images for key ROIs, including meta‐temporal, mesial, temporo‐parietal, frontal, and Braak stages III‐VI. Finally, we correlated Uniτ values across ROIs between the two tracers to evaluate the accuracy of estimates from the voxel‐wise transformation.ResultsThe original SUVR images present large differences between the two tau‐PET tracers (Figure 1). However, upon applying the Uniτ piecewise transformation with smoothing to all brain voxels, we were able to reasonably harmonize these images to the Uniτ scale, substantially reducing visual variability. Notably, the mean Uniτ values for the ROIs extracted from these harmonized 3D tau‐PET brain images demonstrated a high level of association between the two tracers (Figure 2). Furthermore, estimates generated from ROIs or extracted from our 3D parametric Uniτ model yielded identical estimates (Figure 3).ConclusionThe strong associations between tracers after directly harmonizing 3D images to Uniτ scale using the piecewise transformation with smoothing, underscore the effectiveness of the proposed method. This approach provides a reliable and standardized way to compare tau‐PET data across different tracers. Our results indicate the feasibility of harmonizing 3D tau‐PET images without relying on pre‐established ROIs, overcoming the limitation of restricting the analysis to only few brain regions.
The effect of traumatic brain injury and post‐traumatic stress disorders on AD pathologies, small vessel changes and ultimately cognitive function
Authors: Sibilia Francesca , Cen Steven , Choupan Jeiran , Hazany Saman , Ayala Rene , Cheng Jocelyn , Nejatpoor Tiana , Sheikh‐Bahaei Nasim 
Published: January 2025

AbstractBackgroundAlthough many studies have shown that traumatic brain injury (TBI) and post‐traumatic stress disorder (PTSD) regardless of their severity, are associated with a significantly increased risk of all‐cause dementia, the specific pathophysiological mechanisms that underlie these associations remain poorly understood, resulting in discordance findings among different studies and contradictory claims in the current literature. In this study we investigated the effect of TBI and PTSD on the level of amyloid, tau, as well as markers of small vessel health including white matter hyperintensity and perivascular spaces and consequently assessed their effect on the cognitive function in order to understand the pathways through which TBI and PTSD may result in dementia.MethodThe participants in this study were MCI cases drawn from the ADNI‐DOD (n=58). Cognitive performance was assessed using the Mini‐Mental State Exam (MMSE) and Clinical Dementia Rating (CDR). Inclusion criteria for TBI involved the history of moderate to severe nonpenetrating head trauma as well as combat history or presence in the battlefield. Inclusion in the PTSD group required a minimum Clinician Administered PTSD Scale (CAPS) score of 40 points. PET images with tracers AV1451 and AV45 were obtained. Perivascular spaces (PVS) volume fraction in the total white matter and basal ganglia was obtained using automated segmentation pipeline developed at our institute, as well as the grade of white matter hyperintensities.ResultThe volume of PVS in the white matter was found to be significantly higher in veterans with PTSD (p=0.01) or with TBI (p=0.02) after age adjustment. Elevated amyloid was also found in veterans with PTSD 1.3 (1.23‐1.39) vs. 1.23 (1.1‐1.53), p=0.05 and trend of increased amyloid with TBI 1.3 (1.18‐1.44) vs. 1.28 (1.23‐1.31), p=0.09. Our day also indicates a strong correlation between amyloid and CDR (adjusted ranking score correlation of 0.45 (p<0.01) among veteran sample.ConclusionPreliminary evidence showed the association from PTSD to amyloid as well as TBI to amyloid. Since amyloid strongly associated with cognitive function, it may suggest a biological pathway from PTSD and/or TBI through amyloid deposition to cognitive decline in veteran. Larger sample will be needed to confirm the causal pathway.
Occipital amyloid‐β burden and clinical correlates in Lewy body disease
Authors: Vossler Hillary , Abdelnour Carla , Young Christina B. , Winer Joseph R. , Smith Alena , Smith Viktorija , Shahid Marian , Wilson Edward N. , Davidzon Guido A. , Mormino Elizabeth , Poston Kathleen L. 
Published: January 2025

AbstractBackgroundAccurate assessment of amyloid‐ß burden in Lewy body disease (LBD) is crucial due to the frequent co‐occurrence of amyloidosis. Current amyloid‐ß PET imaging protocols often overlook the occipital lobe, a relevant area in Lewy body disease (LBD). We aimed to determine whether regional amyloid‐ß in LBD is associated with global cognition, daily functioning, and neuropsychological performance.MethodWe included 193 Stanford research participants: 78 Cognitively Normal (CN), 42 Alzheimer’s disease (AD), 38 LBD‐Cognitively Normal (LBD‐CN), and 35 LBD‐Cognitively Impaired (LBD‐CI) who underwent 18F‐Florbetaben PET imaging (Table). We calculated SUVRs for the frontal, cingulate, parietal, temporal, and occipital regions using the cerebellum as the reference region. We then used linear regression models adjusted for age, sex, and education to examine the association between regional amyloid‐ß burden and global cognition (measured with MoCA), daily functioning (measured with CDR‐SB), and performance in memory, executive function, visuospatial function, and attention/working memory/processing speed (measured with composite scores).ResultIn the LBD‐CI group, amyloid‐ß burden in all regions, except the cingulate, was associated with worse MoCA (ß = ‐14.31 (SE = 3.59), p < 0.0001) (Figure) and CDR‐SB scores (ß = 5.05 (SE = 1.71), p < 0.004). Similarly, amyloid‐ß burden in the frontal (ß = ‐1.27 (SE = 0.60), p < 0.05), cingulate (ß = ‐1.24 (SE = 0.59), p < 0.05), parietal (ß = ‐1.42 (SE = 0.62), p < 0.05), and temporal (ß = ‐1.68 (SE = 0.70), p < 0.05) regions was associated with worse memory performance, whereas amyloid‐ß burden in the occipital region (ß = ‐1.76 (SE = 0.88), p < 0.05) was associated with worse executive function. However, only the association between occipital amyloid‐ß burden and MoCA scores survived multiple comparison correction. In the LBD‐CN group, regional amyloid‐ß burden showed no associations with clinical outcomes.ConclusionOur study suggests the potential significance of the occipital region in assessing amyloid‐ß burden among individuals with cognitive impairment due to LBD, as it is associated with worse global cognition. Further validation studies should include the occipital region when calculating SUVRs should be considered in people with LBD.