- Email: [email protected]
NETWORKS OF TAU DISTRIBUTION IN ALZHEIMER’S DISEASE
P136
Poster Presentations: Saturday, July 15, 2017
and PACC were significantly associated in high-PiB (baseline: p¼0.043, baseline-to-change: p¼0.011, change-to-change: p¼0.005), but not in low-PiB individuals (all p>0.40). A marginal association was nevertheless observed in the low-PiB participants between change in cognition and change in tau in the voxels with elevated tau signal at baseline (Fig.5; Est.¼-0.5160.28, p¼0.075). Conclusions: Cognitive decline in CN is associated with temporal tau accumulation, beyond the association with baseline tau. TauPET signal changes faster than cognition, which makes it a promising marker to track disease progression. Using voxel-based thresholds helps detect early tau accumulation, which may have an impact on cognition before amyloidosis is evident on PET, but this requires further studies, in larger samples with longer follow-up durations.
IC-P-182
SUCCESSFUL REDUCTION OF OFF-TARGET BINDING OF QUINOLINE DERIVATIVES AS TAU-SELECTIVE PET TRACERS
Ryuichi Harada1,2, Yoshimi Hayakawa3, Ezura Michinori4, Shozo Furumoto5, Ren Iwata6, Hiroyuki Arai1, Kazuhiko Yanai5,7, Yukitsuka Kudo1, Nobuyuki Okamura5,7,8,9, 1Institute of Development, Aging and Cancer, Tohoku University, Sendai City, Japan; 2Tohoku University Graduate School of Medicine, Sendai City, Japan; 3CYRIC, Tohoku University, Sendai, Japan; 4 Department of Neurology, Tohoku University Graduate School of Medicine, Sendai, Japan; 5CYRIC, Tohoku University, Sendai City, Japan; 6CYRIC, Tohoku University, Sendai City, Japan; 7 Tohoku University School of Medicine, Sendai City, Japan; 8 Tohoku Medical and Pharmaceutical University, Sendai, Japan; 9 Tohoku Medical and Pharmaceutical University, Sendai City, Japan. Contact e-mail: [email protected] Background: 18F-THK5351 is one of putative tau PET radiopharmaceuticals to design for in vivo detection of tau aggregates in the brain of patients with Alzheimer’s disease. However, recent studies have demonstrated that 18F-THK5351 binds with high affinity to monoamine oxidase-B (MAO-B) as off-target binding. The aim of this study was to improve the binding selectivity of quinolone derivatives as tau PET tracervia compound optimization. Methods: In vitro competitive binding assay against recombinant MAO-B was performed using 3H-THK5351 and novel quinoline derivatives. In vitro autoradiography in frozen human brain tissues was performed using 18F-labeled compounds. Pharmacokinetics were assessed in normal mice after intravenous injection of 18F-labeled compounds. Results: In vitro competitive binding assays demonstrated lower binding affinity of several quinoline derivatives against MAO-B (Ki > 100 nM) than THK5351 (Ki ¼ 5 nM). Furthermore, in vitro autoradiography of AD brain sections showed the selective binding ability of these tracers to tau aggregates, and tracer binding was not affected by the treatment with MAO-B inhibitor. One of them showed excellent pharmacokinetics after intravenous administration in mice. Conclusions: Compound optimization resulted in successful improvement of binding selectivity of quinoline derivatives as tau PET tracers. Further in vivo studies are required to validate these findings.
IC-P-183
NETWORKS OF TAU DISTRIBUTION IN ALZHEIMER’S DISEASE
Merle C. H€ onig1, Gerard N. Bischof1,2, Jochen Hammes1, Thilo van Eimeren1,3,4, Alexander Drzezga1,4, 1University Hospital Cologne, Cologne, Germany; 2Institute of Neuroscience
and Medicine III, J€ulich, Germany; 3Institute of Neuroscience and Medicine III, J€ulich, Germany; 4German Center for Neurodegenerative Diseases, Bonn, Germany. Contact e-mail: [email protected] Background: A stereotypical anatomical propagation of tau-pa-
thology has been described in Alzheimer’s disease (AD). According to recent concepts (network degeneration hypothesis), this is thought to be indicative of misfolded tau proteins possibly spreading along functionally connected networks. We examined whether independent coherent components could be identified in the distribution pattern of in vivo AD-related taupathology and if these components coincide with specific functional connectivity networks. Methods: 22 [18F]AV-1451 PET scans of patients with amnestic AD were spatially normalized, intensity standardized to the cerebellum and z-transformed using the mean and deviation image of a healthy control sample to assess AD-related tau-pathology patterns. First, to detect distinct tau-pathology networks (TPNs), the deviation maps were submitted to an independent component analysis. Second, to investigate if regions of high tau-burden are associated via functionally connected networks, we extracted the region with the maximum z-value in each of the generated TPNs and adopted them as seeds in the following resting state functional MRI analysis. The seed-based analysis was conducted in a group of healthy adults who were part of the 1000 Functional Connectome Project. Third, to examine if tau-pathology co-localizes with functionally connected networks, we quantified the spatial overlap between the seed-based networks and the corresponding TPNs by calculating the dice similarity coefficient. Finally, we assessed if the tau-dependent seedbased networks corresponded with commonly known functional resting state networks, previously published by the FIND lab of Stanford University (Shirer et al. 2012). Results: We identified 10 distinct and independent TPNs with the majority showing a symmetrical bi-hemispheric expansion. The tau maxima of the respective TPNs coincided with highly functionally connected regions such as the precuneus and hippocampus. The topographical patterns of the tau-dependent seed-based networks resembled known resting state networks, predominantly the default mode network. Conclusions: A set of independently coherent networks of tau-pathology could be identified in AD, coinciding partly with functional networks previously reported to be disrupted in AD. This supports the idea that the temporal coherence of tau-pathology observed in specific brain regions may be induced by a transneuronal spread within specific functional networks.
IC-P-184
UTILITY OF 18F-THK5351 PET IN DIAGNOSIS AND DIFFERENTIATION OF NEURODEGENERATIVE DISEASES
Etsuko Imabayashi1, Daichi Sone1, Harumasa Takano2, Tadashi Tsukamoto1, Soichiro Shimizu3, Haruo Hanyu3, Nobuyuki Okamura4, Shozo Furumoto5, Yukitsuka Kudo6, Hiroshi Matsuda2, 1National Center of Neurology and Psychiatry, Kodaira, Japan; 2Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodaira, Japan; 3Tokyo Medical University, Tokyo, Japan; 4Tohoku Medical and Pharmaceutical University, Sendai City, Japan; 5CYRIC, Tohoku University, Sendai City, Japan; 6Institute of Development, Aging and Cancer, Tohoku University, Sendai City, Japan. Contact e-mail: [email protected]
Poster Presentations: Saturday, July 15, 2017
and PACC were significantly associated in high-PiB (baseline: p¼0.043, baseline-to-change: p¼0.011, change-to-change: p¼0.005), but not in low-PiB individuals (all p>0.40). A marginal association was nevertheless observed in the low-PiB participants between change in cognition and change in tau in the voxels with elevated tau signal at baseline (Fig.5; Est.¼-0.5160.28, p¼0.075). Conclusions: Cognitive decline in CN is associated with temporal tau accumulation, beyond the association with baseline tau. TauPET signal changes faster than cognition, which makes it a promising marker to track disease progression. Using voxel-based thresholds helps detect early tau accumulation, which may have an impact on cognition before amyloidosis is evident on PET, but this requires further studies, in larger samples with longer follow-up durations.
IC-P-182
SUCCESSFUL REDUCTION OF OFF-TARGET BINDING OF QUINOLINE DERIVATIVES AS TAU-SELECTIVE PET TRACERS
Ryuichi Harada1,2, Yoshimi Hayakawa3, Ezura Michinori4, Shozo Furumoto5, Ren Iwata6, Hiroyuki Arai1, Kazuhiko Yanai5,7, Yukitsuka Kudo1, Nobuyuki Okamura5,7,8,9, 1Institute of Development, Aging and Cancer, Tohoku University, Sendai City, Japan; 2Tohoku University Graduate School of Medicine, Sendai City, Japan; 3CYRIC, Tohoku University, Sendai, Japan; 4 Department of Neurology, Tohoku University Graduate School of Medicine, Sendai, Japan; 5CYRIC, Tohoku University, Sendai City, Japan; 6CYRIC, Tohoku University, Sendai City, Japan; 7 Tohoku University School of Medicine, Sendai City, Japan; 8 Tohoku Medical and Pharmaceutical University, Sendai, Japan; 9 Tohoku Medical and Pharmaceutical University, Sendai City, Japan. Contact e-mail: [email protected] Background: 18F-THK5351 is one of putative tau PET radiopharmaceuticals to design for in vivo detection of tau aggregates in the brain of patients with Alzheimer’s disease. However, recent studies have demonstrated that 18F-THK5351 binds with high affinity to monoamine oxidase-B (MAO-B) as off-target binding. The aim of this study was to improve the binding selectivity of quinolone derivatives as tau PET tracervia compound optimization. Methods: In vitro competitive binding assay against recombinant MAO-B was performed using 3H-THK5351 and novel quinoline derivatives. In vitro autoradiography in frozen human brain tissues was performed using 18F-labeled compounds. Pharmacokinetics were assessed in normal mice after intravenous injection of 18F-labeled compounds. Results: In vitro competitive binding assays demonstrated lower binding affinity of several quinoline derivatives against MAO-B (Ki > 100 nM) than THK5351 (Ki ¼ 5 nM). Furthermore, in vitro autoradiography of AD brain sections showed the selective binding ability of these tracers to tau aggregates, and tracer binding was not affected by the treatment with MAO-B inhibitor. One of them showed excellent pharmacokinetics after intravenous administration in mice. Conclusions: Compound optimization resulted in successful improvement of binding selectivity of quinoline derivatives as tau PET tracers. Further in vivo studies are required to validate these findings.
IC-P-183
NETWORKS OF TAU DISTRIBUTION IN ALZHEIMER’S DISEASE
Merle C. H€ onig1, Gerard N. Bischof1,2, Jochen Hammes1, Thilo van Eimeren1,3,4, Alexander Drzezga1,4, 1University Hospital Cologne, Cologne, Germany; 2Institute of Neuroscience
and Medicine III, J€ulich, Germany; 3Institute of Neuroscience and Medicine III, J€ulich, Germany; 4German Center for Neurodegenerative Diseases, Bonn, Germany. Contact e-mail: [email protected] Background: A stereotypical anatomical propagation of tau-pa-
thology has been described in Alzheimer’s disease (AD). According to recent concepts (network degeneration hypothesis), this is thought to be indicative of misfolded tau proteins possibly spreading along functionally connected networks. We examined whether independent coherent components could be identified in the distribution pattern of in vivo AD-related taupathology and if these components coincide with specific functional connectivity networks. Methods: 22 [18F]AV-1451 PET scans of patients with amnestic AD were spatially normalized, intensity standardized to the cerebellum and z-transformed using the mean and deviation image of a healthy control sample to assess AD-related tau-pathology patterns. First, to detect distinct tau-pathology networks (TPNs), the deviation maps were submitted to an independent component analysis. Second, to investigate if regions of high tau-burden are associated via functionally connected networks, we extracted the region with the maximum z-value in each of the generated TPNs and adopted them as seeds in the following resting state functional MRI analysis. The seed-based analysis was conducted in a group of healthy adults who were part of the 1000 Functional Connectome Project. Third, to examine if tau-pathology co-localizes with functionally connected networks, we quantified the spatial overlap between the seed-based networks and the corresponding TPNs by calculating the dice similarity coefficient. Finally, we assessed if the tau-dependent seedbased networks corresponded with commonly known functional resting state networks, previously published by the FIND lab of Stanford University (Shirer et al. 2012). Results: We identified 10 distinct and independent TPNs with the majority showing a symmetrical bi-hemispheric expansion. The tau maxima of the respective TPNs coincided with highly functionally connected regions such as the precuneus and hippocampus. The topographical patterns of the tau-dependent seed-based networks resembled known resting state networks, predominantly the default mode network. Conclusions: A set of independently coherent networks of tau-pathology could be identified in AD, coinciding partly with functional networks previously reported to be disrupted in AD. This supports the idea that the temporal coherence of tau-pathology observed in specific brain regions may be induced by a transneuronal spread within specific functional networks.
IC-P-184
UTILITY OF 18F-THK5351 PET IN DIAGNOSIS AND DIFFERENTIATION OF NEURODEGENERATIVE DISEASES
Etsuko Imabayashi1, Daichi Sone1, Harumasa Takano2, Tadashi Tsukamoto1, Soichiro Shimizu3, Haruo Hanyu3, Nobuyuki Okamura4, Shozo Furumoto5, Yukitsuka Kudo6, Hiroshi Matsuda2, 1National Center of Neurology and Psychiatry, Kodaira, Japan; 2Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodaira, Japan; 3Tokyo Medical University, Tokyo, Japan; 4Tohoku Medical and Pharmaceutical University, Sendai City, Japan; 5CYRIC, Tohoku University, Sendai City, Japan; 6Institute of Development, Aging and Cancer, Tohoku University, Sendai City, Japan. Contact e-mail: [email protected]