Browsing by Subject "Tau PET"
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Item Amyloid and Tau Pathology are Associated with Cerebral Blood Flow in a Mixed Sample of Nondemented Older Adults with and without Vascular Risk Factors for Alzheimer’s Disease(Elsevier, 2023) Swinford, Cecily G.; Risacher, Shannon L.; Vosmeier, Aaron; Deardorff, Rachael; Chumin, Evgeny J.; Dzemidzic, Mario; Wu, Yu-Chien; Gao, Sujuan; McDonald, Brenna C.; Yoder, Karmen K.; Unverzagt, Frederick W.; Wang, Sophia; Farlow, Martin R.; Brosch, Jared R.; Clark, David G.; Apostolova, Liana G.; Sims, Justin; Wang, Danny J.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineIdentification of biomarkers for the early stages of Alzheimer's disease (AD) is an imperative step in developing effective treatments. Cerebral blood flow (CBF) is a potential early biomarker for AD; generally, older adults with AD have decreased CBF compared to normally aging peers. CBF deviates as the disease process and symptoms progress. However, further characterization of the relationships between CBF and AD risk factors and pathologies is still needed. We assessed the relationships between CBF quantified by arterial spin-labeled magnetic resonance imaging, hypertension, APOEε4, and tau and amyloid positron emission tomography in 77 older adults: cognitively normal, subjective cognitive decline, and mild cognitive impairment. Tau and amyloid aggregation were related to altered CBF, and some of these relationships were dependent on hypertension or APOEε4 status. Our findings suggest a complex relationship between risk factors, AD pathologies, and CBF that warrants future studies of CBF as a potential early biomarker for AD.Item Comparative binding properties of the tau PET tracers THK5117, THK5351, PBB3, and T807 in postmortem Alzheimer brains(BMC, 2017-11-11) Lemoine, Laetitia; Gillberg, Per-Göran; Svedberg, Marie; Stepanov, Vladimir; Jia, Zhisheng; Huang, Jinghai; Nag, Sangram; Tian, He; Ghetti, Bernardino; Okamura, Nobuyuki; Higuchi, Makoto; Halldin, Christer; Nordberg, Agneta; Pathology and Laboratory Medicine, School of MedicineBackground The aim of this study was to compare the binding properties of several tau positron emission tomography tracers—THK5117, THK5351, T807 (also known as AV1451; flortaucipir), and PBB3—head to head in the same human brain tissue. Methods Binding assays were performed to compare the regional distribution of 3H-THK5117 and 3H-THK5351 in postmortem tissue from three Alzheimer’s disease (AD) cases and three control subjects in frontal and temporal cortices as well as in the hippocampus. Competition binding assays between THK5351, THK5117, PBB3, and T807, as well as off-target binding of THK5117 and T807 toward monoamine oxidase B (MAO-B), were performed using binding assays in brain homogenates and autoradiography of three AD cases. Results Regional binding of 3H-THK5117 and 3H-THK5351 was similar, except in the temporal cortex, which showed higher 3H-THK5117 binding. Saturation studies demonstrated two binding sites for 3H-THK5351 (K d1 = 5.6 nM, Bmax = 76 pmol/g; K d2 = 1 nM, Bmax = 40 pmol/g). Competition studies in the hippocampus between 3H-THK5351 and unlabeled THK5351, THK5117, and T807 revealed super-high-affinity sites for all three tracers (THK5351 K i = 0.1 pM; THK5117 K i = 0.3 pM; T807 K i = 0.2 pM) and an additional high-affinity site (THK5351 K i = 16 nM; THK5117 K i = 20 nM; T807 K i = 78nM). 18F-T807, 11C-THK5351, and 11C-PBB3 autoradiography of large frozen sections from three AD brains showed similar regional binding for the three tracers, with lower binding intensity for 11C-PBB3. Unlabeled THK5351 and T807 displaced 11C-THK5351 to a similar extent and a lower extent, respectively, compared with 11C-PBB3. Competition with the MAO-B inhibitor 3H-l-deprenyl was observed for THK5117 and T807 in the hippocampus (THK5117 K i = 286 nM; T807 K i = 227 nM) and the putamen (THK5117 K i = 148 nM; T807 K i = 135 nM). 3H-THK5351 binding was displaced using autoradiography competition with unlabeled THK5351 and T807 in cortical areas by 70–80% and 60–77%, respectively, in the basal ganglia, whereas unlabeled deprenyl displaced 3H-THK5351 binding by 40% in the frontal cortex and 50% in the basal ganglia. Conclusions THK5351, THK5117, and T807 seem to target similar binding sites, but with different affinities, whereas PBB3 seems to target its own binding site. Both THK5117 and T807 demonstrated off-target binding in the hippocampus and putamen with a ten times lower binding affinity to the MAO-B inhibitor deprenyl compared with 3H-THK5351. Electronic supplementary material The online version of this article (doi:10.1186/s13195-017-0325-z) contains supplementary material, which is available to authorized users.Item Deep learning detection of informative features in tau PET for Alzheimer’s disease classification(BMC, 2020-12-28) Jo, Taeho; Nho, Kwangsik; Risacher, Shannon L.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineBackground: Alzheimer's disease (AD) is the most common type of dementia, typically characterized by memory loss followed by progressive cognitive decline and functional impairment. Many clinical trials of potential therapies for AD have failed, and there is currently no approved disease-modifying treatment. Biomarkers for early detection and mechanistic understanding of disease course are critical for drug development and clinical trials. Amyloid has been the focus of most biomarker research. Here, we developed a deep learning-based framework to identify informative features for AD classification using tau positron emission tomography (PET) scans. Results: The 3D convolutional neural network (CNN)-based classification model of AD from cognitively normal (CN) yielded an average accuracy of 90.8% based on five-fold cross-validation. The LRP model identified the brain regions in tau PET images that contributed most to the AD classification from CN. The top identified regions included the hippocampus, parahippocampus, thalamus, and fusiform. The layer-wise relevance propagation (LRP) results were consistent with those from the voxel-wise analysis in SPM12, showing significant focal AD associated regional tau deposition in the bilateral temporal lobes including the entorhinal cortex. The AD probability scores calculated by the classifier were correlated with brain tau deposition in the medial temporal lobe in MCI participants (r = 0.43 for early MCI and r = 0.49 for late MCI). Conclusion: A deep learning framework combining 3D CNN and LRP algorithms can be used with tau PET images to identify informative features for AD classification and may have application for early detection during prodromal stages of AD.Item Memory concerns in the early Alzheimer’s disease prodrome: Regional association with tau deposition(Elsevier, 2018-03-24) Swinford, Cecily G.; Risacher, Shannon L.; Charil, Arnaud; Schwarz, Adam J.; Saykin, Andrew J.; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: Relationship between self- and informant memory concerns and tau aggregation was assessed in adults at risk for Alzheimer's disease (AD). Methods: Regional mean standardized uptake value ratios were extracted from [18F]flortaucipir positron emission tomography (PET) scans of 82 at-risk adults in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Associations between self- and informant ECog memory scores and tau aggregation were analyzed on both regional and voxelwise bases. Analyses were completed both on the whole sample and restricted to amyloid-positive individuals only. Results: Memory concerns were associated with tau aggregation. Self-perception was more associated with frontal tau. In contrast, informant scores were more associated with parietal tau. This source-by-region interaction was more prominent in amyloid-positive participants and observed in both regional and voxelwise analyses. Discussion: Quantitative assessment of perceived memory functioning may be useful for screening older adults at risk for Alzheimer's disease. Individuals and their informants may provide complementary information relating to the anatomical distribution of tau.