1
|
Endo H, Ono M, Takado Y, Matsuoka K, Takahashi M, Tagai K, Kataoka Y, Hirata K, Takahata K, Seki C, Kokubo N, Fujinaga M, Mori W, Nagai Y, Mimura K, Kumata K, Kikuchi T, Shimozawa A, Mishra SK, Yamaguchi Y, Shimizu H, Kakita A, Takuwa H, Shinotoh H, Shimada H, Kimura Y, Ichise M, Suhara T, Minamimoto T, Sahara N, Kawamura K, Zhang MR, Hasegawa M, Higuchi M. Imaging α-synuclein pathologies in animal models and patients with Parkinson's and related diseases. Neuron 2024; 112:2540-2557.e8. [PMID: 38843838 DOI: 10.1016/j.neuron.2024.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 01/24/2024] [Accepted: 05/07/2024] [Indexed: 08/10/2024]
Abstract
Deposition of α-synuclein fibrils is implicated in Parkinson's disease (PD) and dementia with Lewy bodies (DLB), while in vivo detection of α-synuclein pathologies in these illnesses has been challenging. Here, we have developed a small-molecule ligand, C05-05, for visualizing α-synuclein deposits in the brains of living subjects. In vivo optical and positron emission tomography (PET) imaging of mouse and marmoset models demonstrated that C05-05 captured a dynamic propagation of fibrillogenesis along neural pathways, followed by disruptions of these structures. High-affinity binding of 18F-C05-05 to α-synuclein aggregates in human brain tissues was also proven by in vitro assays. Notably, PET-detectable 18F-C05-05 signals were intensified in the midbrains of PD and DLB patients as compared with healthy controls, providing the first demonstration of visualizing α-synuclein pathologies in these illnesses. Collectively, we propose a new imaging technology offering neuropathology-based translational assessments of PD and allied disorders toward diagnostic and therapeutic research and development.
Collapse
Affiliation(s)
- Hironobu Endo
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan.
| | - Maiko Ono
- Institute for Quantum Life Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Yuhei Takado
- Institute for Quantum Life Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Kiwamu Matsuoka
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; Department of Psychiatry, Nara Medical University, Nara 634-8522, Japan
| | - Manami Takahashi
- Quantum Neuromapping and Neuromodulation Team, Institute for Quantum Life Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Kenji Tagai
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; Department of Psychiatry, The Jikei University School of Medicine, Tokyo 105-8461, Japan
| | - Yuko Kataoka
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Kosei Hirata
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; Department of Neurology and Neurological Science, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Keisuke Takahata
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; Department of Psychiatry, Keio University School of Medicine, Tokyo 160-0016, Japan
| | - Chie Seki
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Naomi Kokubo
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Masayuki Fujinaga
- Department of Advanced Nuclear Medicine Sciences, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Wakana Mori
- Department of Advanced Nuclear Medicine Sciences, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Yuji Nagai
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Koki Mimura
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; Research Center for Medical and Health Data Science, The Institute of Statistical Mathematics, Tokyo 190-8562, Japan
| | - Katsushi Kumata
- Department of Advanced Nuclear Medicine Sciences, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Tatsuya Kikuchi
- Department of Advanced Nuclear Medicine Sciences, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Aki Shimozawa
- Department of Dementia and Higher Brain Function, Tokyo Metropolitan Institute of Medical Science, Tokyo 156-8506, Japan
| | - Sushil K Mishra
- Department of BioMolecular Sciences, The University of Mississippi, Oxford, MS 38677, USA
| | - Yoshiki Yamaguchi
- Division of Structural Glycobiology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University, Sendai 981-8558, Miyagi Japan
| | - Hiroshi Shimizu
- Department of Pathology, Brain Research Institute, Niigata University, Niigata 951-8585, Japan
| | - Akiyoshi Kakita
- Department of Pathology, Brain Research Institute, Niigata University, Niigata 951-8585, Japan
| | - Hiroyuki Takuwa
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; Quantum Neuromapping and Neuromodulation Team, Institute for Quantum Life Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Hitoshi Shinotoh
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; Neurology Clinic, Chiba 260-0045, Chiba Japan
| | - Hitoshi Shimada
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; Department of Functional Neurology & Neurosurgery, Center for Integrated Human Brain Science, Brain Research Institute, Niigata University, Niigata 951-8585, Japan
| | - Yasuyuki Kimura
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; Department of Clinical and Experimental Neuroimaging, Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu 474-8511, Aichi, Japan
| | - Masanori Ichise
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Tetsuya Suhara
- National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Takafumi Minamimoto
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Naruhiko Sahara
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Kazunori Kawamura
- Department of Advanced Nuclear Medicine Sciences, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Ming-Rong Zhang
- Department of Advanced Nuclear Medicine Sciences, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan
| | - Masato Hasegawa
- Department of Dementia and Higher Brain Function, Tokyo Metropolitan Institute of Medical Science, Tokyo 156-8506, Japan
| | - Makoto Higuchi
- Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba 263-8555, Japan; Department of Neuroetiology and Diagnostic Science, Osaka Metropolitan University Graduate School of Medicine, Osaka 545-8585, Japan
| |
Collapse
|
2
|
Chattopadhyay T, Ozarkar SS, Buwa K, Joshy NA, Komandur D, Naik J, Thomopoulos SI, Ver Steeg G, Ambite JL, Thompson PM. Comparison of deep learning architectures for predicting amyloid positivity in Alzheimer's disease, mild cognitive impairment, and healthy aging, from T1-weighted brain structural MRI. Front Neurosci 2024; 18:1387196. [PMID: 39015378 PMCID: PMC11250587 DOI: 10.3389/fnins.2024.1387196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 06/14/2024] [Indexed: 07/18/2024] Open
Abstract
Abnormal β-amyloid (Aβ) accumulation in the brain is an early indicator of Alzheimer's disease (AD) and is typically assessed through invasive procedures such as PET (positron emission tomography) or CSF (cerebrospinal fluid) assays. As new anti-Alzheimer's treatments can now successfully target amyloid pathology, there is a growing interest in predicting Aβ positivity (Aβ+) from less invasive, more widely available types of brain scans, such as T1-weighted (T1w) MRI. Here we compare multiple approaches to infer Aβ + from standard anatomical MRI: (1) classical machine learning algorithms, including logistic regression, XGBoost, and shallow artificial neural networks, (2) deep learning models based on 2D and 3D convolutional neural networks (CNNs), (3) a hybrid ANN-CNN, combining the strengths of shallow and deep neural networks, (4) transfer learning models based on CNNs, and (5) 3D Vision Transformers. All models were trained on paired MRI/PET data from 1,847 elderly participants (mean age: 75.1 yrs. ± 7.6SD; 863 females/984 males; 661 healthy controls, 889 with mild cognitive impairment (MCI), and 297 with Dementia), scanned as part of the Alzheimer's Disease Neuroimaging Initiative. We evaluated each model's balanced accuracy and F1 scores. While further tests on more diverse data are warranted, deep learning models trained on standard MRI showed promise for estimating Aβ + status, at least in people with MCI. This may offer a potential screening option before resorting to more invasive procedures.
Collapse
Affiliation(s)
- Tamoghna Chattopadhyay
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Saket S. Ozarkar
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Ketaki Buwa
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Neha Ann Joshy
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Dheeraj Komandur
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Jayati Naik
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | | | - Jose Luis Ambite
- Information Sciences Institute, University of Southern California, Marina del Rey, CA, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| |
Collapse
|
3
|
Ferschmann C, Messerschmidt K, Gnörich J, Barthel H, Marek K, Palleis C, Katzdobler S, Stockbauer A, Fietzek U, Finze A, Biechele G, Rumpf JJ, Saur D, Schroeter ML, Rullmann M, Beyer L, Eckenweber F, Wall S, Schildan A, Patt M, Stephens A, Classen J, Bartenstein P, Seibyl J, Franzmeier N, Levin J, Höglinger GU, Sabri O, Brendel M, Scheifele M. Tau accumulation is associated with dopamine deficiency in vivo in four-repeat tauopathies. Eur J Nucl Med Mol Imaging 2024; 51:1909-1922. [PMID: 38366196 PMCID: PMC11139736 DOI: 10.1007/s00259-024-06637-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 02/04/2024] [Indexed: 02/18/2024]
Abstract
PURPOSE We hypothesized that severe tau burden in brain regions involved in direct or indirect pathways of the basal ganglia correlate with more severe striatal dopamine deficiency in four-repeat (4R) tauopathies. Therefore, we correlated [18F]PI-2620 tau-positron-emission-tomography (PET) imaging with [123I]-Ioflupane single-photon-emission-computed tomography (SPECT) for dopamine transporter (DaT) availability. METHODS Thirty-eight patients with clinically diagnosed 4R-tauopathies (21 male; 69.0 ± 8.5 years) and 15 patients with clinically diagnosed α-synucleinopathies (8 male; 66.1 ± 10.3 years) who underwent [18F]PI-2620 tau-PET and DaT-SPECT imaging with a time gap of 3 ± 5 months were evaluated. Regional Tau-PET signals and DaT availability as well as their principal components were correlated in patients with 4R-tauopathies and α-synucleinopathies. Both biomarkers and the residuals of their association were correlated with clinical severity scores in 4R-tauopathies. RESULTS In patients with 4R-tauopathies, [18F]PI-2620 binding in basal ganglia and midbrain regions was negatively associated with striatal DaT availability (i.e. globus pallidus internus and putamen (β = - 0.464, p = 0.006, Durbin-Watson statistics = 1.824) in a multiple regression model. Contrarily, [18F]PI-2620 binding in the dentate nucleus showed no significant regression factor with DaT availability in the striatum (β = 0.078, p = 0.662, Durbin-Watson statistics = 1.686). Patients with α-synucleinopathies did not indicate any regional associations between [18F]PI-2620-binding and DaT availability. Higher DaT-SPECT binding relative to tau burden was associated with better clinical performance (β = - 0.522, p = 0.011, Durbin-Watson statistics = 2.663) in patients with 4R-tauopathies. CONCLUSION Tau burden in brain regions involved in dopaminergic pathways is associated with aggravated dopaminergic dysfunction in patients with clinically diagnosed primary tauopathies. The ability to sustain dopamine transmission despite tau accumulation may preserve motor function.
Collapse
Affiliation(s)
- Christian Ferschmann
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | | | - Johannes Gnörich
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Ken Marek
- InviCRO, LLC, Boston, MA, USA
- Molecular Neuroimaging, A Division of inviCRO, New Haven, CT, USA
| | - Carla Palleis
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Sabrina Katzdobler
- Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Anna Stockbauer
- Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Urban Fietzek
- Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Anika Finze
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Gloria Biechele
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Jost-Julian Rumpf
- Department of Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Dorothee Saur
- Department of Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Matthias L Schroeter
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Michael Rullmann
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Leonie Beyer
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Florian Eckenweber
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Stephan Wall
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Andreas Schildan
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Marianne Patt
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | | | - Joseph Classen
- Department of Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - John Seibyl
- InviCRO, LLC, Boston, MA, USA
- Molecular Neuroimaging, A Division of inviCRO, New Haven, CT, USA
| | - Nicolai Franzmeier
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Institute for Stroke and Dementia Research, LMU University Hospital, LMU Munich, Munich, Germany
| | - Johannes Levin
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Günter U Höglinger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Maximilian Scheifele
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany.
| |
Collapse
|
4
|
Gatto RG, Pham NTT, Duffy JR, Clark HM, Utianski RL, Botha H, Machulda MM, Lowe VJ, Schwarz CG, Jack CR, Josephs KA, Whitwell JL. Multimodal cross-examination of progressive apraxia of speech by diffusion tensor imaging-based tractography and Tau-PET scans. Hum Brain Mapp 2024; 45:e26704. [PMID: 38825988 PMCID: PMC11144950 DOI: 10.1002/hbm.26704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/27/2024] [Accepted: 04/17/2024] [Indexed: 06/04/2024] Open
Abstract
Progressive apraxia of speech (PAOS) is a 4R tauopathy characterized by difficulties with motor speech planning. Neurodegeneration in PAOS targets the premotor cortex, particularly the supplementary motor area (SMA), with degeneration of white matter (WM) tracts connecting premotor and motor cortices and Broca's area observed on diffusion tensor imaging (DTI). We aimed to assess flortaucipir uptake across speech-language-related WM tracts identified using DTI tractography in PAOS. Twenty-two patients with PAOS and 26 matched healthy controls were recruited by the Neurodegenerative Research Group (NRG) and underwent MRI and flortaucipir-PET. The patient population included patients with primary progressive apraxia of speech (PPAOS) and non-fluent variant/agrammatic primary progressive aphasia (agPPA). Flortaucipir PET scans and DTI were coregistered using rigid registration with a mutual information cost function in subject space. Alignments between DTI and flortaucipir PET were inspected in all cases. Whole-brain tractography was calculated using deterministic algorithms by a tractography reconstruction tool (DSI-studio) and specific tracts were identified using an automatic fiber tracking atlas-based method. Fractional anisotropy (FA) and flortaucipir standardized uptake value ratios (SUVRs) were averaged across the frontal aslant tract, arcuate fasciculi, inferior frontal-occipital fasciculus, inferior and middle longitudinal fasciculi, as well as the SMA commissural fibers. Reduced FA (p < .0001) and elevated flortaucipir SUVR (p = .0012) were observed in PAOS cases compared to controls across all combined WM tracts. For flortaucipir SUVR, the greatest differentiation of PAOS from controls was achieved with the SMA commissural fibers (area under the receiver operator characteristic curve [AUROC] = 0.83), followed by the left arcuate fasciculus (AUROC = 0.75) and left frontal aslant tract (AUROC = 0.71). Our findings demonstrate that flortaucipir uptake is increased across WM tracts related to speech/language difficulties in PAOS.
Collapse
Affiliation(s)
| | | | | | | | | | - Hugo Botha
- Department of NeurologyMayo ClinicRochesterMinnesotaUSA
| | - Mary M. Machulda
- Department of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | | | | | | | | |
Collapse
|
5
|
Cheong I, Du Y, Smith G, Hua J, Li X, Pantelyat A. Cerebral Tau Deposition in Comorbid Progressive Supranuclear Palsy and Amyotrophic Lateral Sclerosis: An [18F]-Flortaucipir and 7T MRI Study. NEURODEGENER DIS 2024; 23:35-42. [PMID: 38527450 PMCID: PMC11132917 DOI: 10.1159/000536614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 01/28/2024] [Indexed: 03/27/2024] Open
Abstract
INTRODUCTION Progressive supranuclear palsy (PSP) is a four-repeat tauopathy characterized by multiple clinicopathologic subtypes. Advanced neuroimaging techniques have shown an early ability to distinguish PSP subtypes noninvasively for improved diagnosis. This study utilized tau PET imaging and MRI techniques at 7T to determine the neuroimaging profile of a participant with comorbid PSP and amyotrophic lateral sclerosis (ALS). METHOD [18F]-flortaucipir PET imaging was performed on one participant with PSP-ALS, one participant with typical PSP (Richardson's syndrome; PSP-RS), and 15 healthy control volunteers. Standardized uptake value ratio (SUVR) in each brain region was compared between PSP participants and controls. Quantitative susceptibility mapping (QSM) and inflow-based vascular-space occupancy MRI at 7T were performed on the two PSP participants and on two age-matched healthy controls to evaluate for differences in regional brain iron content and arteriolar cerebral blood volume (CBVa), respectively. RESULTS In the participant with PSP-ALS, the precentral gyrus demonstrated the highest [18F]-flortaucipir uptake of all brain regions relative to controls (z-score 1.94). In the participant with PSP-RS, [18F]-flortaucipir uptake relative to controls was highest in subcortical regions, including the pallidum, thalamus, hippocampus, and brainstem (z-scores 1.08, 1.41, 1.49, 1.32, respectively). Susceptibility values as a measure of brain iron content were higher in the globus pallidus and substantia nigra than in the midbrain and pons in each participant, regardless of group. CBVa values tended to be higher in the subcortical gray matter in PSP participants than in controls, although large measurement variability was noted in controls across multiple regions. CONCLUSION In vivo tau PET imaging of an individual with PSP-ALS overlap demonstrated increased tau burden in the motor cortex that was not observed in PSP-RS or control participants. Consistent with prior PET studies, tau burden in PSP-RS was mainly observed in subcortical regions, including the brainstem and basal ganglia. QSM data suggest that off-target binding to iron may account for some but not all of the increased [18F]-flortaucipir uptake in the basal ganglia in PSP-RS. These findings support existing evidence that tau PET imaging can distinguish among PSP subtypes by detecting distinct regional patterns of tau deposition in the brain. Larger studies are needed to determine whether CBVa is sensitive to changes in brain microvasculature in PSP.
Collapse
Affiliation(s)
- Ian Cheong
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yong Du
- Department of Radiology and Radiological Science, Division of Nuclear Medicine and Molecular Imaging, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Gwenn Smith
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jun Hua
- Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Xu Li
- Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Alexander Pantelyat
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| |
Collapse
|
6
|
Nabizadeh F, Zafari R. Progranulin and neuropathological features of Alzheimer's disease: longitudinal study. Aging Clin Exp Res 2024; 36:55. [PMID: 38441695 PMCID: PMC10914850 DOI: 10.1007/s40520-024-02715-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 01/26/2024] [Indexed: 03/07/2024]
Abstract
BACKGROUND Progranulin is an anti-inflammatory protein that plays an essential role in the synapse function and the maintenance of neurons in the central nervous system (CNS). It has been shown that the CSF level of progranulin increases in Alzheimer's disease (AD) patients and is associated with the deposition of amyloid-beta (Aβ) and tau in the brain tissue. In this study, we aimed to assess the longitudinal changes in cerebrospinal fluid (CSF) progranulin levels during different pathophysiological stages of AD and investigate associated AD pathologic features. METHODS We obtained the CSF and neuroimaging data of 1001 subjects from the ADNI database. The participants were classified into four groups based on the A/T/N framework: A + /TN + , A + /TN-, A-/TN + , and A-/TN-. RESULTS Based on our analysis there was a significant difference in CSF progranulin (P = 0.001) between ATN groups. Further ANOVA analysis revealed that there was no significant difference in the rate of change of CSF-progranulin ATN groups. We found that the rate of change of CSF progranulin was associated with baseline Aβ-PET only in the A-/TN + group. A significant association was found between the rate of change of CSF progranulin and the Aβ-PET rate of change only in A-/TN + CONCLUSION: Our findings revealed that an increase in CSF progranulin over time is associated with faster formation of Aβ plaques in patients with only tau pathology based on the A/T/N classification (suspected non-Alzheimer's pathology). Together, our findings showed that the role of progranulin-related microglial activity on AD pathology can be stage-dependent, complicated, and more prominent in non-AD pathologic changes. Thus, there is a need for further studies to consider progranulin-based therapies for AD treatment.
Collapse
Affiliation(s)
- Fardin Nabizadeh
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
- Department of Neurology, Iran University of Medical Sciences, Tehran, Iran.
| | - Rasa Zafari
- School of Medicine, Tehran University of Medical Science, Tehran, Iran
| |
Collapse
|
7
|
Juengling F, Wuest F, Schirrmacher R, Abele J, Thiel A, Soucy JP, Camicioli R, Garibotto V. PET Imaging in Dementia: Mini-Review and Canadian Perspective for Clinical Use. Can J Neurol Sci 2024:1-13. [PMID: 38433571 DOI: 10.1017/cjn.2024.31] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
PET imaging is increasingly recognized as an important diagnostic tool to investigate patients with cognitive disturbances of possible neurodegenerative origin. PET with 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG), assessing glucose metabolism, provides a measure of neurodegeneration and allows a precise differential diagnosis among the most common neurodegenerative diseases, such as Alzheimer's disease, frontotemporal dementia or dementia with Lewy bodies. PET tracers specific for the pathological deposits characteristic of different neurodegenerative processes, namely amyloid and tau deposits typical of Alzheimer's Disease, allow the visualization of these aggregates in vivo. [18F]FDG and amyloid PET imaging have reached a high level of clinical validity and are since 2022 investigations that can be offered to patients in standard clinical care in most of Canada.This article will briefly review and summarize the current knowledge on these diagnostic tools, their integration into diagnostic algorithms as well as perspectives for future developments.
Collapse
Affiliation(s)
- Freimut Juengling
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Division of Oncologic Imaging and Radionuclide Therapy, Cross Cancer Institute, Edmonton, AB, Canada
- Medical Faculty, University of Bern, Bern, Switzerland
| | - Frank Wuest
- Division of Oncologic Imaging and Radionuclide Therapy, Cross Cancer Institute, Edmonton, AB, Canada
| | - Ralf Schirrmacher
- Division of Oncologic Imaging and Radionuclide Therapy, Cross Cancer Institute, Edmonton, AB, Canada
- Medical Isotope and Cyclotron Facility, University of Alberta, Edmonton, AB, Canada
| | - Jonathan Abele
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB, Canada
| | - Alexander Thiel
- Department of Neurology and Neurosurgery, Lady Davis Institute for Medical Research, McGill University, Montréal, QC, Canada
| | - Jean-Paul Soucy
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Richard Camicioli
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Department of Medicine, Division of Neurology, University of Alberta, Edmonton, AB, Canada
| | - Valentina Garibotto
- Diagnostic Department, Nuclear Medicine and Molecular Imaging Division, University Hospitals of Geneva, Geneva, Switzerland
| |
Collapse
|
8
|
Cho SH, Kim S, Choi SM, Kim BC. ATN Classification and Clinical Progression of the Amyloid-Negative Group in Alzheimer's Disease Neuroimaging Initiative Participants. Chonnam Med J 2024; 60:51-58. [PMID: 38304128 PMCID: PMC10828081 DOI: 10.4068/cmj.2024.60.1.51] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/03/2023] [Accepted: 12/05/2023] [Indexed: 02/03/2024] Open
Abstract
Alzheimer's disease has recently been classified using three biological markers (amyloid [A], tau [T], and neurodegeneration [N]) to help elucidate its progression. We aimed to investigate whether there were differences between cognitive function and the clinical dementia symptoms over time relative to the ATN classification in the amyloid-negative group. In the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, 310 participants who underwent all the tests required for ATN classification were enrolled. The cognitive function score differences (Alzheimer's Disease Assessment Scale-Cognitive Subscale 13 [ADAS-Cog 13], Clinical Dementia Rating Sum of Boxes [CDR-SOB], and Mini-Mental State Examination [MMSE]) between the groups were analyzed using the analysis of covariance and score changes over time with a linear mixed-effects model. In the cross-sectional analysis, ADAS-Cog 13 scores were higher for A-T-N+ and A-T+N+ than for A-T-N- (p<0.001) and A-T+N- (p<0.001). In the longitudinal analysis, CDR-SOB scores for A-T+N+ deteriorated faster than A-T-N- (p<0.001), A-T+N- (p<0.001) and A-T-N+ (p<0.001). Hippocampal atrophy progressed faster in A-T-N+ (p<0.001) and A-T+N+ (p=0.02) than in A-T-N-. Through this study, we discovered that even in individuals classified as amyloid negative, neurodegeneration with tau deposition exacerbates cognitive decline and worsens clinical symptoms, underscoring the need for continuous monitoring and observation.
Collapse
Affiliation(s)
- Soo Hyun Cho
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea
| | - Shina Kim
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea
| | - Seong-Min Choi
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea
| | - Byeong Chae Kim
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea
| | | |
Collapse
|
9
|
Steward A, Biel D, Dewenter A, Roemer S, Wagner F, Dehsarvi A, Rathore S, Otero Svaldi D, Higgins I, Brendel M, Dichgans M, Shcherbinin S, Ewers M, Franzmeier N. ApoE4 and Connectivity-Mediated Spreading of Tau Pathology at Lower Amyloid Levels. JAMA Neurol 2023; 80:1295-1306. [PMID: 37930695 PMCID: PMC10628846 DOI: 10.1001/jamaneurol.2023.4038] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 09/07/2023] [Indexed: 11/07/2023]
Abstract
Importance For the Alzheimer disease (AD) therapies to effectively attenuate clinical progression, it may be critical to intervene before the onset of amyloid-associated tau spreading, which drives neurodegeneration and cognitive decline. Time points at which amyloid-associated tau spreading accelerates may depend on individual risk factors, such as apolipoprotein E ε4 (ApoE4) carriership, which is linked to faster disease progression; however, the association of ApoE4 with amyloid-related tau spreading is unclear. Objective To assess if ApoE4 carriers show accelerated amyloid-related tau spreading and propose amyloid positron emission tomography (PET) thresholds at which tau spreading accelerates in ApoE4 carriers vs noncarriers. Design, Setting, and Participants This cohort study including combined ApoE genotyping, amyloid PET, and longitudinal tau PET from 2 independent samples: the Alzheimer's Disease Neuroimaging Initiative (ADNI; n = 237; collected from April 2015 to August 2022) and Avid-A05 (n = 130; collected from December 2013 to July 2017) with a mean (SD) tau PET follow-up time of 1.9 (0.96) years in ADNI and 1.4 (0.23) years in Avid-A05. ADNI is an observational multicenter Alzheimer disease neuroimaging initiative and Avid-A05 an observational clinical trial. Participants classified as cognitively normal (152 in ADNI and 77 in Avid-A05) or mildly cognitively impaired (107 in ADNI and 53 in Avid-A05) were selected based on ApoE genotyping, amyloid-PET, and longitudinal tau PET data availability. Participants with ApoE ε2/ε4 genotype or classified as having dementia were excluded. Resting-state functional magnetic resonance imaging connectivity templates were based on 42 healthy participants in ADNI. Main Outcomes and Measures Mediation of amyloid PET on the association between ApoE4 status and subsequent tau PET increase through Braak stage regions and interaction between ApoE4 status and amyloid PET with annual tau PET increase through Braak stage regions and connectivity-based spreading stages (tau epicenter connectivity ranked regions). Results The mean (SD) age was 73.9 (7.35) years among the 237 ADNI participants and 70.2 (9.7) years among the 130 Avid-A05 participants. A total of 107 individuals in ADNI (45.1%) and 45 in Avid-A05 (34.6%) were ApoE4 carriers. Across both samples, we found that higher amyloid PET-mediated ApoE4-related tau PET increased globally (ADNI b, 0.15; 95% CI, 0.05-0.28; P = .001 and Avid-A05 b, 0.33; 95% CI, 0.14-0.54; P < .001) and in earlier Braak regions. Further, we found a significant association between ApoE4 status by amyloid PET interaction and annual tau PET increases consistently through early Braak- and connectivity-based stages where amyloid-related tau accumulation was accelerated in ApoE4carriers vs noncarriers at lower centiloid thresholds, corrected for age and sex. Conclusions and Relevance The findings in this study indicate that amyloid-related tau accumulation was accelerated in ApoE4 carriers at lower amyloid levels, suggesting that ApoE4 may facilitate earlier amyloid-driven tau spreading across connected brain regions. Possible therapeutic implications might be further investigated to determine when best to prevent tau spreading and thus cognitive decline depending on ApoE4 status.
Collapse
Affiliation(s)
- Anna Steward
- Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Davina Biel
- Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Anna Dewenter
- Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Sebastian Roemer
- Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Department of Neurology, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Fabian Wagner
- Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Amir Dehsarvi
- Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | | | | | | | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology, Munich, Germany
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology, Munich, Germany
| | | | - Michael Ewers
- Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- German Center for Neurodegenerative Diseases, Munich, Germany
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology, Munich, Germany
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden
| |
Collapse
|
10
|
Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
Collapse
Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
| | | | | |
Collapse
|
11
|
Silva-Rodríguez J, Labrador-Espinosa MA, Moscoso A, Schöll M, Mir P, Grothe MJ. Characteristics of amnestic patients with hypometabolism patterns suggestive of Lewy body pathology. Brain 2023; 146:4520-4531. [PMID: 37284793 PMCID: PMC10629761 DOI: 10.1093/brain/awad194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 04/27/2023] [Accepted: 05/16/2023] [Indexed: 06/08/2023] Open
Abstract
A clinical diagnosis of Alzheimer's disease dementia (ADD) encompasses considerable pathological and clinical heterogeneity. While Alzheimer's disease patients typically show a characteristic temporo-parietal pattern of glucose hypometabolism on 18F-fluorodeoxyglucose (FDG)-PET imaging, previous studies have identified a subset of patients showing a distinct posterior-occipital hypometabolism pattern associated with Lewy body pathology. Here, we aimed to improve the understanding of the clinical relevance of these posterior-occipital FDG-PET patterns in patients with Alzheimer's disease-like amnestic presentations. Our study included 1214 patients with clinical diagnoses of ADD (n = 305) or amnestic mild cognitive impairment (aMCI, n = 909) from the Alzheimer's Disease Neuroimaging Initiative, who had FDG-PET scans available. Individual FDG-PET scans were classified as being suggestive of Alzheimer's (AD-like) or Lewy body (LB-like) pathology by using a logistic regression classifier trained on a separate set of patients with autopsy-confirmed Alzheimer's disease or Lewy body pathology. AD- and LB-like subgroups were compared on amyloid-β and tau-PET, domain-specific cognitive profiles (memory versus executive function performance), as well as the presence of hallucinations and their evolution over follow-up (≈6 years for aMCI, ≈3 years for ADD). Around 12% of the aMCI and ADD patients were classified as LB-like. For both aMCI and ADD patients, the LB-like group showed significantly lower regional tau-PET burden than the AD-like subgroup, but amyloid-β load was only significantly lower in the aMCI LB-like subgroup. LB- and AD-like subgroups did not significantly differ in global cognition (aMCI: d = 0.15, P = 0.16; ADD: d = 0.02, P = 0.90), but LB-like patients exhibited a more dysexecutive cognitive profile relative to the memory deficit (aMCI: d = 0.35, P = 0.01; ADD: d = 0.85 P < 0.001), and had a significantly higher risk of developing hallucinations over follow-up [aMCI: hazard ratio = 1.8, 95% confidence interval = (1.29, 3.04), P = 0.02; ADD: hazard ratio = 2.2, 95% confidence interval = (1.53, 4.06) P = 0.01]. In summary, a sizeable group of clinically diagnosed ADD and aMCI patients exhibit posterior-occipital FDG-PET patterns typically associated with Lewy body pathology, and these also show less abnormal Alzheimer's disease biomarkers as well as specific clinical features typically associated with dementia with Lewy bodies.
Collapse
Affiliation(s)
- Jesús Silva-Rodríguez
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
| | - Miguel A Labrador-Espinosa
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
| | - Alexis Moscoso
- Wallenberg Center for Molecular and Translational Medicine and Department of Psychiatry and Neurochemistry, University of Gothenburg, 41345 Gothenburg, Sweden
| | - Michael Schöll
- Wallenberg Center for Molecular and Translational Medicine and Department of Psychiatry and Neurochemistry, University of Gothenburg, 41345 Gothenburg, Sweden
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, WC1ELondon, UK
| | - Pablo Mir
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
- Departamento de Medicina, Facultad de Medicina, Universidad de Sevilla, 41009 Sevilla, Spain
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
- Wallenberg Center for Molecular and Translational Medicine and Department of Psychiatry and Neurochemistry, University of Gothenburg, 41345 Gothenburg, Sweden
| | | |
Collapse
|
12
|
Bhujbal SS, Kad MM, Patole VC. Recent diagnostic techniques for the detection of Alzheimer's disease: a short review. Ir J Med Sci 2023; 192:2417-2426. [PMID: 36525239 DOI: 10.1007/s11845-022-03244-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 11/25/2022] [Indexed: 12/23/2022]
Abstract
Alzheimer's disease (AD) is a neurological condition that affects millions of individuals around the world and for which there are few effective therapies. Dementia is characterized by the formation of senile plaques and neurofibrillary tangles, which is followed by neurotoxicity, which results in memory loss and mortality. Pathogenesis occurs several years before the onset of disease. As the disease-modifying drugs are most effective in the early stages of Alzheimer's disease, biomarkers for early detection of disease and their development are crucial. This review discusses the diagnostic utility, benefits, and limitations of traditional techniques such as neuroimaging, cognitive testing, positron emission tomography, and biomarkers, as well as the novel techniques such as artificial intelligence, machine learning, immunotherapy, and blood test approaches for early detection, understanding, and treatment of AD.
Collapse
Affiliation(s)
- Santosh S Bhujbal
- Dr. D. Y. Patil Institute of Pharmaceutical Sciences & Research, Pimpri, Pune, India.
| | - Minal M Kad
- Dr. D. Y. Patil Institute of Pharmaceutical Sciences & Research, Pimpri, Pune, India
| | - Vinita C Patole
- Dr. D. Y. Patil Institute of Pharmaceutical Sciences & Research, Pimpri, Pune, India
| |
Collapse
|
13
|
Cogswell PM, Fan AP. Multimodal comparisons of QSM and PET in neurodegeneration and aging. Neuroimage 2023; 273:120068. [PMID: 37003447 PMCID: PMC10947478 DOI: 10.1016/j.neuroimage.2023.120068] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/17/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) has been used to study susceptibility changes that may occur based on tissue composition and mineral deposition. Iron is a primary contributor to changes in magnetic susceptibility and of particular interest in applications of QSM to neurodegeneration and aging. Iron can contribute to neurodegeneration through inflammatory processes and via interaction with aggregation of disease-related proteins. To better understand the local susceptibility changes observed on QSM, its signal has been studied in association with other imaging metrics such as positron emission tomography (PET). The associations of QSM and PET may provide insight into the pathophysiology of disease processes, such as the role of iron in aging and neurodegeneration, and help to determine the diagnostic utility of QSM as an indirect indicator of disease processes typically evaluated with PET. In this review we discuss the proposed mechanisms and summarize prior studies of the associations of QSM and amyloid PET, tau PET, TSPO PET, FDG-PET, 15O-PET, and F-DOPA PET in evaluation of neurologic diseases with a focus on aging and neurodegeneration.
Collapse
Affiliation(s)
- Petrice M Cogswell
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.
| | - Audrey P Fan
- Department of Biomedical Engineering and Department of Neurology, University of California, Davis, 1590 Drew Avenue, Davis, CA 95618, USA
| |
Collapse
|
14
|
Miyamoto M, Okuyama C, Kagawa S, Kusano K, Takahashi M, Takahata K, Jang MK, Yamauchi H. Radiation dosimetry and pharmacokinetics of the tau PET tracer florzolotau (18F) in healthy Japanese subjects. Ann Nucl Med 2023; 37:300-309. [PMID: 36890399 PMCID: PMC10129982 DOI: 10.1007/s12149-023-01828-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 02/14/2023] [Indexed: 03/10/2023]
Abstract
OBJECTIVE Abnormal aggregation of tau in the brain is a major contributing factor in various neurodegenerative diseases. Florzolotau (18F) (florzolotau, APN-1607, PM-PBB3) has been shown to be a probe for tau fibrils in an animal model and patients with Alzheimer's disease and those with non-Alzheimer's disease tauopathies. The objective of this study is to evaluate the safety, pharmacokinetics, and radiation dose following a single intravenous administration of florzolotau in healthy Japanese subjects. METHODS Three healthy male Japanese subjects aged between 20 and 64 were enrolled in this study. Subjects were determined to be eligible based on the screening assessments at the study site. Subjects received a single intravenous dose of 195.0 ± 0.5 MBq of florzolotau and underwent the whole-body PET scan 10 times in total to calculate absorbed doses to major organs/tissues and effective dose. Radioactivities in whole blood and urine were also measured for pharmacokinetic evaluation. Absorbed doses to major organs/tissues and effective dose were estimated using the medical internal radiation dose (MIRD) method. Vital signs, electrocardiography (ECG), and blood tests were done for safety evaluation. RESULTS The intravenous injection of florzolotau was well tolerated. There were no adverse events or clinically detectable pharmacologic effects related to the tracer in any subjects. No significant changes in vital signs and ECG were observed. The highest mean initial uptake at 15 min after injection was in the liver (29.0 ± 4.0%ID), intestine (4.69 ± 1.65%ID), and brain (2.13 ± 0.18%ID). The highest absorbed dose was 508 μGy/MBq of the gallbladder wall, followed by the liver of 79.4 μGy/MBq, the pancreas of 42.5 μGy/MBq, and the upper large intestine of 34.2 μGy/MBq. The effective dose was calculated as 19.7 μSv/MBq according to the tissue weighting factor reported by ICRP-103. CONCLUSION Florzolotau intravenous injection was well tolerated in healthy male Japanese subjects. The effective dose was determined as 3.61 mSv when 185 MBq florzolotau was given.
Collapse
Affiliation(s)
| | - Chio Okuyama
- Shiga Medical Center Research Institute, Moriyama, Japan
| | - Shinya Kagawa
- Shiga Medical Center Research Institute, Moriyama, Japan
| | | | | | - Keisuke Takahata
- Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan
| | | | - Hiroshi Yamauchi
- Shiga Medical Center Research Institute, Moriyama, Japan
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| |
Collapse
|
15
|
Wang EW, Brown GL, Lewis MM, Jellen LC, Pu C, Johnson ML, Chen H, Kong L, Du G, Huang X. Susceptibility Magnetic Resonance Imaging Correlates with Glial Density and Tau in the Substantia Nigra Pars Compacta. Mov Disord 2023; 38:464-473. [PMID: 36598274 PMCID: PMC10445152 DOI: 10.1002/mds.29311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 12/13/2022] [Accepted: 12/16/2022] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Susceptibility magnetic resonance imaging (MRI) is sensitive to iron-related changes in the substantia nigra pars compacta (SNc), the key pathologic locus of parkinsonisms. It is unclear, however, if iron deposition in the SNc is associated with its neurodegeneration. OBJECTIVE The objective of this study was to test whether susceptibility MRI metrics in parkinsonisms are associated with SNc neuropathologic features of dopaminergic neuron loss, gliosis, and α-synuclein and tau burden. METHODS This retrospective study included 27 subjects with both in vivo MRI and postmortem data. Multigradient echo imaging was used to derive the apparent transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) in the SNc. Archived midbrain slides that were stained with hematoxylin and eosin, anti-α-synuclein, and anti-tau were digitized to quantify neuromelanin-positive neuron density, glial density, and the percentages of area occupied by positive α-synuclein and tau staining. MRI-histology associations were examined using Pearson correlations and regression. RESULTS Twenty-four subjects had postmortem parkinsonism diagnoses (Lewy body disorder, progressive supranuclear palsy, multiple system atrophy, and corticobasal degeneration), two had only Alzheimer's neuropathology, and one exhibited only mild atrophy. Among all subjects, both R2* and QSM were associated with glial density (r ≥ 0.67; P < 0.001) and log-transformed tau burden (r ≥ 0.53; P ≤ 0.007). Multiple linear regression identified glial density and log-transformed tau as determinants for both MRI metrics (R2 ≥ 0.580; P < 0.0001). Neither MRI metric was associated with neuron density or α-synuclein burden. CONCLUSIONS R2* and QSM are associated with both glial density and tau burden, key neuropathologic features in the parkinsonism SNc. © 2023 International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Ernest W. Wang
- Department of Neurology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Gregory L. Brown
- Department of Neurology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Mechelle M. Lewis
- Department of Neurology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
- Department of Pharmacology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Leslie C. Jellen
- Department of Neurology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Cunfeng Pu
- Department of Pathology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Melinda L. Johnson
- Department of Neurology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Hairong Chen
- Department of Neurology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Lan Kong
- Department of Public Health Sciences, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Guangwei Du
- Department of Neurology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Xuemei Huang
- Department of Neurology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
- Department of Pharmacology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
- Departments of Neurosurgery and Radiology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| |
Collapse
|
16
|
Wu J, Su Y, Chen Y, Zhu W, Reiman EM, Caselli RJ, Chen K, Thompson PM, Wang J, Wang Y. A Surface-Based Federated Chow Test Model for Integrating APOE Status, Tau Deposition Measure, and Hippocampal Surface Morphometry. J Alzheimers Dis 2023; 93:1153-1168. [PMID: 37182882 PMCID: PMC10329869 DOI: 10.3233/jad-230034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) is the most common type of age-related dementia, affecting 6.2 million people aged 65 or older according to CDC data. It is commonly agreed that discovering an effective AD diagnosis biomarker could have enormous public health benefits, potentially preventing or delaying up to 40% of dementia cases. Tau neurofibrillary tangles are the primary driver of downstream neurodegeneration and subsequent cognitive impairment in AD, resulting in structural deformations such as hippocampal atrophy that can be observed in magnetic resonance imaging (MRI) scans. OBJECTIVE To build a surface-based model to 1) detect differences between APOE subgroups in patterns of tau deposition and hippocampal atrophy, and 2) use the extracted surface-based features to predict cognitive decline. METHODS Using data obtained from different institutions, we develop a surface-based federated Chow test model to study the synergistic effects of APOE, a previously reported significant risk factor of AD, and tau on hippocampal surface morphometry. RESULTS We illustrate that the APOE-specific morphometry features correlate with AD progression and better predict future AD conversion than other MRI biomarkers. For example, a strong association between atrophy and abnormal tau was identified in hippocampal subregion cornu ammonis 1 (CA1 subfield) and subiculum in e4 homozygote cohort. CONCLUSION Our model allows for identifying MRI biomarkers for AD and cognitive decline prediction and may uncover a corner of the neural mechanism of the influence of APOE and tau deposition on hippocampal morphology.
Collapse
Affiliation(s)
- Jianfeng Wu
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, USA
| | - Yi Su
- Banner Alzheimer’s Institute, Phoenix, USA
| | - Yanxi Chen
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, USA
| | - Wenhui Zhu
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, USA
| | | | | | - Kewei Chen
- Banner Alzheimer’s Institute, Phoenix, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, USA
| | - Junwen Wang
- Division of Applied Oral Sciences & Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China
| | - Yalin Wang
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, USA
| |
Collapse
|
17
|
Alosco ML, Su Y, Stein TD, Protas H, Cherry JD, Adler CH, Balcer LJ, Bernick C, Pulukuri SV, Abdolmohammadi B, Coleman MJ, Palmisano JN, Tripodis Y, Mez J, Rabinovici GD, Marek KL, Beach TG, Johnson KA, Huber BR, Koerte I, Lin AP, Bouix S, Cummings JL, Shenton ME, Reiman EM, McKee AC, Stern RA. Associations between near end-of-life flortaucipir PET and postmortem CTE-related tau neuropathology in six former American football players. Eur J Nucl Med Mol Imaging 2023; 50:435-452. [PMID: 36152064 PMCID: PMC9816291 DOI: 10.1007/s00259-022-05963-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 09/01/2022] [Indexed: 01/11/2023]
Abstract
PURPOSE Flourine-18-flortaucipir tau positron emission tomography (PET) was developed for the detection for Alzheimer's disease. Human imaging studies have begun to investigate its use in chronic traumatic encephalopathy (CTE). Flortaucipir-PET to autopsy correlation studies in CTE are needed for diagnostic validation. We examined the association between end-of-life flortaucipir PET and postmortem neuropathological measurements of CTE-related tau in six former American football players. METHODS Three former National Football League players and three former college football players who were part of the DIAGNOSE CTE Research Project died and agreed to have their brains donated. The six players had flortaucipir (tau) and florbetapir (amyloid) PET prior to death. All brains from the deceased participants were neuropathologically evaluated for the presence of CTE. On average, the participants were 59.0 (SD = 9.32) years of age at time of PET. PET scans were acquired 20.33 (SD = 13.08) months before their death. Using Spearman correlation analyses, we compared flortaucipir standard uptake value ratios (SUVRs) to digital slide-based AT8 phosphorylated tau (p-tau) density in a priori selected composite cortical, composite limbic, and thalamic regions-of-interest (ROIs). RESULTS Four brain donors had autopsy-confirmed CTE, all with high stage disease (n = 3 stage III, n = 1 stage IV). Three of these four met criteria for the clinical syndrome of CTE, known as traumatic encephalopathy syndrome (TES). Two did not have CTE at autopsy and one of these met criteria for TES. Concomitant pathology was only present in one of the non-CTE cases (Lewy body) and one of the CTE cases (motor neuron disease). There was a strong association between flortaucipir SUVRs and p-tau density in the composite cortical (ρ = 0.71) and limbic (ρ = 0.77) ROIs. Although there was a strong association in the thalamic ROI (ρ = 0.83), this is a region with known off-target binding. SUVRs were modest and CTE and non-CTE cases had overlapping SUVRs and discordant p-tau density for some regions. CONCLUSIONS Flortaucipir-PET could be useful for detecting high stage CTE neuropathology, but specificity to CTE p-tau is uncertain. Off-target flortaucipir binding in the hippocampus and thalamus complicates interpretation of these associations. In vivo biomarkers that can detect the specific p-tau of CTE across the disease continuum are needed.
Collapse
Affiliation(s)
- Michael L Alosco
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Yi Su
- Banner Alzheimer's Institute, Arizona State University, and Arizona Alzheimer's Consortium, Phoenix, AZ, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
- VA Bedford Healthcare System, Bedford, MA, USA
| | - Hillary Protas
- Banner Alzheimer's Institute, Arizona Alzheimer's Consortium, Phoenix, AZ, USA
| | - Jonathan D Cherry
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Charles H Adler
- Department of Neurology, Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Laura J Balcer
- Departments of Neurology, Population Health and Ophthalmology, NYU Grossman School of Medicine, New York, NY, USA
| | - Charles Bernick
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
- Department of Neurology, University of Washington, Seattle, WA, USA
| | - Surya Vamsi Pulukuri
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Bobak Abdolmohammadi
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Michael J Coleman
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
| | - Joseph N Palmisano
- Biostatistics and Epidemiology Data Analytics Center (BEDAC), Boston University School of Public Health, Boston, MA, USA
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jesse Mez
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Gil D Rabinovici
- Memory & Aging Center, Departments of Neurology, Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Kenneth L Marek
- Institute for Neurodegenerative Disorders, Invicro, LLC, New Haven, CT, USA
| | - Thomas G Beach
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Keith A Johnson
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Gordon Center for Medical Imaging, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Bertrand Russell Huber
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- VA Bedford Healthcare System, Bedford, MA, USA
- National Center for PTSD, VA Boston Healthcare, Jamaica Plain, MA, USA
| | - Inga Koerte
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Ludwig Maximilians University, Munich, Germany
- Graduate School of Systemic Neurosciences, Ludwig Maximilians University, Munich, Germany
- NICUM (NeuroImaging Core Unit Munich), Ludwig Maximilians University, Munich, Germany
| | - Alexander P Lin
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
- Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
| | - Jeffrey L Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA
| | - Martha E Shenton
- VA Boston Healthcare System, Boston, MA, USA
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Eric M Reiman
- Banner Alzheimer's Institute, University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix, AZ, USA
| | - Ann C McKee
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
- VA Bedford Healthcare System, Bedford, MA, USA
| | - Robert A Stern
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
- Departments of Neurosurgery, and Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA.
| |
Collapse
|
18
|
Gao F, Zhang PF, Gao J, Song J, Chi S. The CCL2 rs4586 SNP Is Associated with Slower Amyloid-β Deposition and Faster Tau Accumulation of Alzheimer's Disease. J Alzheimers Dis 2022; 90:1647-1657. [PMID: 36314210 DOI: 10.3233/jad-220716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND CC-chemokine ligand 2 (CCL2), the key immunomodulatory chemokine for microglial activation, has been implicated in the pathogenesis of Alzheimer's disease (AD). Whether the association of CCL2 single nucleotide polymorphisms (SNPs) and the risk of AD is still controversial. OBJECTIVE We aimed to investigate whether CCL2 rs4586 SNP is associated with the pathological changes and cognitive decline of AD. METHODS A total of 486 participants with longitudinal cerebrospinal fluid (CSF) amyloid-β (Aβ) and phospho-tau (P-tau) biomarkers, 18F-Florbetapir and 18F-flortaucipir-positron emission tomography (PET), and cognitive assessments from the Alzheimer's disease Neuroimaging Initiative were included in the study. The effects of CCL2 rs4586 SNP on the pathological changes and cognitive decline of AD were assessed with linear mixed-effects models and evaluated according to the Aβ-status so as to identify whether the effects were independent of Aβ status. RESULTS CCL2 rs4586-CC carriers exhibited a slower global Aβ-PET accumulation, particularly within stage I and stage II. However, they exhibited a faster accumulation of CSF P-tau and global tau-PET standard uptake value ratios, especially in Braak I and Braak III/IV and the inferior temporal gyrus. The congruent effects of CCL2 rs4586 on tau accumulation existed only in the Aβ-group, as is shown in global tau-PET and Braak I. However, CCL2 rs4586 was not associated with the cognitive decline. CONCLUSION Our findings showed that the CCL2 rs4586-CC (versus TT/TC) genotype was associated with slower Aβ deposition and faster tau accumulation, and the latter of which was independent of Aβ status.
Collapse
Affiliation(s)
- Fan Gao
- Department of Neurology, the Affiliated Hospital of Qingdao University, Qingdao, China
| | - Peng-Fei Zhang
- Department of Medicine, Hangzhou Juno Genomics Inc, Hangzhou, China
| | - Jing Gao
- Department of Neurology, the Affiliated Hospital of Qingdao University, Qingdao, China
| | - Jinghui Song
- Department of Neurology, the Affiliated Hospital of Qingdao University, Qingdao, China
| | - Song Chi
- Department of Neurology, the Affiliated Hospital of Qingdao University, Qingdao, China
| | | |
Collapse
|
19
|
Steward A, Biel D, Brendel M, Dewenter A, Roemer S, Rubinski A, Luan Y, Dichgans M, Ewers M, Franzmeier N. Functional network segregation is associated with attenuated tau spreading in Alzheimer's disease. Alzheimers Dement 2022; 19:2034-2046. [PMID: 36433865 DOI: 10.1002/alz.12867] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 09/01/2022] [Accepted: 10/05/2022] [Indexed: 11/27/2022]
Abstract
INTRODUCTION Lower network segregation is associated with accelerated cognitive decline in Alzheimer's disease (AD), yet it is unclear whether less segregated brain networks facilitate connectivity-mediated tau spreading. METHODS We combined resting state functional magnetic resonance imaging (fMRI) with longitudinal tau positron emission tomography (PET) in 42 betamyloid-negative controls and 81 amyloid beta positive individuals across the AD spectrum. Network segregation was determined using resting-state fMRI-assessed connectivity among 400 cortical regions belonging to seven networks. RESULTS AD subjects with higher network segregation exhibited slower brain-wide tau accumulation relative to their baseline entorhinal tau PET burden (typical onset site of tau pathology). Second, by identifying patient-specific tau epicenters with highest baseline tau PET we found that stronger epicenter segregation was associated with a slower rate of tau accumulation in the rest of the brain in relation to baseline epicenter tau burden. DISCUSSION Our results indicate that tau spreading is facilitated by a more diffusely organized connectome, suggesting that brain network topology modulates tau spreading in AD. HIGHLIGHTS Higher brain network segregation is associated with attenuated tau pathology accumulation in Alzheimer's disease (AD). A patient-tailored approach allows for the more precise localization of tau epicenters. The functional segregation of subject-specific tau epicenters predicts the rate of future tau accumulation.
Collapse
Affiliation(s)
- Anna Steward
- Institute for Stroke and Dementia Research (ISD) University Hospital LMU Munich Germany
| | - Davina Biel
- Institute for Stroke and Dementia Research (ISD) University Hospital LMU Munich Germany
| | - Matthias Brendel
- Department of Nuclear Medicine University Hospital LMU Munich Munich Germany
- German Center for Neurodegenerative Diseases (DZNE) Munich Germany
- Munich Cluster for Systems Neurology (SyNergy) Munich Germany
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD) University Hospital LMU Munich Germany
| | - Sebastian Roemer
- Institute for Stroke and Dementia Research (ISD) University Hospital LMU Munich Germany
- Department of Neurology University Hospital LMU Munich Munich Germany
| | - Anna Rubinski
- Institute for Stroke and Dementia Research (ISD) University Hospital LMU Munich Germany
| | - Ying Luan
- Institute for Stroke and Dementia Research (ISD) University Hospital LMU Munich Germany
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD) University Hospital LMU Munich Germany
- German Center for Neurodegenerative Diseases (DZNE) Munich Germany
- Munich Cluster for Systems Neurology (SyNergy) Munich Germany
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD) University Hospital LMU Munich Germany
- German Center for Neurodegenerative Diseases (DZNE) Munich Germany
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research (ISD) University Hospital LMU Munich Germany
- Munich Cluster for Systems Neurology (SyNergy) Munich Germany
| | | |
Collapse
|
20
|
Biel D, Luan Y, Brendel M, Hager P, Dewenter A, Moscoso A, Otero Svaldi D, Higgins IA, Pontecorvo M, Römer S, Steward A, Rubinski A, Zheng L, Schöll M, Shcherbinin S, Ewers M, Franzmeier N. Combining tau-PET and fMRI meta-analyses for patient-centered prediction of cognitive decline in Alzheimer’s disease. Alzheimers Res Ther 2022; 14:166. [PMID: 36345046 PMCID: PMC9639286 DOI: 10.1186/s13195-022-01105-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 10/20/2022] [Indexed: 11/09/2022]
Abstract
Background Tau-PET is a prognostic marker for cognitive decline in Alzheimer’s disease, and the heterogeneity of tau-PET patterns matches cognitive symptom heterogeneity. Thus, tau-PET may allow precision-medicine prediction of individual tau-related cognitive trajectories, which can be important for determining patient-specific cognitive endpoints in clinical trials. Here, we aimed to examine whether tau-PET in cognitive-domain-specific brain regions, identified via fMRI meta-analyses, allows the prediction of domain-specific cognitive decline. Further, we aimed to determine whether tau-PET-informed personalized cognitive composites capture patient-specific cognitive trajectories more sensitively than conventional cognitive measures. Methods We included Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants classified as controls (i.e., amyloid-negative, cognitively normal, n = 121) or Alzheimer’s disease-spectrum (i.e., amyloid-positive, cognitively normal to dementia, n = 140), plus 111 AVID-1451-A05 participants for independent validation (controls/Alzheimer’s disease-spectrum=46/65). All participants underwent baseline 18F-flortaucipir tau-PET, amyloid-PET, and longitudinal cognitive testing to assess annual cognitive changes (i.e., episodic memory, language, executive functioning, visuospatial). Cognitive changes were calculated using linear mixed models. Independent meta-analytical task-fMRI activation maps for each included cognitive domain were obtained from the Neurosynth database and applied to tau-PET to determine tau-PET signal in cognitive-domain-specific brain regions. In bootstrapped linear regression, we assessed the strength of the relationship (i.e., partial R2) between cognitive-domain-specific tau-PET vs. global or temporal-lobe tau-PET and cognitive changes. Further, we used tau-PET-based prediction of domain-specific decline to compose personalized cognitive composites that were tailored to capture patient-specific cognitive decline. Results In both amyloid-positive cohorts (ADNI [age = 75.99±7.69] and A05 [age = 74.03±9.03]), cognitive-domain-specific tau-PET outperformed global and temporal-lobe tau-PET for predicting future cognitive decline in episodic memory, language, executive functioning, and visuospatial abilities. Further, a tau-PET-informed personalized cognitive composite across cognitive domains enhanced the sensitivity to assess cognitive decline in amyloid-positive subjects, yielding lower sample sizes required for detecting simulated intervention effects compared to conventional cognitive endpoints (i.e., memory composite, global cognitive composite). However, the latter effect was less strong in A05 compared to the ADNI cohort. Conclusion Combining tau-PET with task-fMRI-derived maps of major cognitive domains facilitates the prediction of domain-specific cognitive decline. This approach may help to increase the sensitivity to detect Alzheimer’s disease-related cognitive decline and to determine personalized cognitive endpoints in clinical trials. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-022-01105-5.
Collapse
|
21
|
Knight AC, Morrone CD, Varlow C, Yu WH, McQuade P, Vasdev N. Head-to-Head Comparison of Tau-PET Radioligands for Imaging TDP-43 in Post-Mortem ALS Brain. Mol Imaging Biol 2022; 25:513-527. [PMID: 36258099 DOI: 10.1007/s11307-022-01779-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/27/2022] [Accepted: 10/03/2022] [Indexed: 11/25/2022]
Abstract
PURPOSE In vivo detection of transactivation response element DNA binding protein-43 kDa (TDP-43) aggregates through positron emission tomography (PET) would impact the ability to successfully develop therapeutic interventions for a variety of neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). The purpose of the present study is to evaluate the ability of six tau PET radioligands to bind to TDP-43 aggregates in post-mortem brain tissues from ALS patients. PROCEDURES Herein, we report the first head-to-head evaluation of six tritium labeled isotopologs of tau-targeting PET radioligands, [3H]MK-6240 (a.k.a. florquinitau), [3H]Genentech Tau Probe-1 (GTP-1), [3H]JNJ-64326067(JNJ-067), [3H]CBD-2115, [3H]flortaucipir, and [3H]APN-1607, and their ability to bind to the β-pleated sheet structures of aggregate TDP-43 in post-mortem ALS brain tissues by autoradiography and immunostaining methods. Post-mortem frontal cortex, motor cortex, and cerebellum tissues were evaluated, and binding intensity was aligned with areas of elevated phosphorylated tau (ptau), pTDP-43, and β-amyloid. RESULTS Negligible binding was observed with [3H]MK-6240, [3H]JNJ-067, and [3H]GTP-1. While [3H]CBD-2115 displayed marginal specific binding, this binding did not significantly correlate with the distribution of pTDP-43 and AT8 inclusions. Of the remaining ligands, the distribution of [3H]flortaucipir did not significantly correlate to pTDP-43 pathology; however, specific binding trends to a positive relationship with tau. Finally, [3H]APN-1607 relates most strongly to amyloid load and does not indicate pTDP-43 pathology as confirmed by [3H]PiB distribution in sister sections. CONCLUSIONS Our results demonstrate the prominent nature of mixed pathology in ALS, and do not support the application of [3H]MK-6240, [3H]JNJ-067, [3H]GTP-1, [3H]CBD-2115, [3H]flortaucipir, or [3H]APN-1607 for selective imaging TDP-43 in ALS for clinical research with the currently available in vitro data. Identification of potent and selective radiotracers for TDP-43 remains an ongoing challenge.
Collapse
Affiliation(s)
- Ashley C Knight
- Azrieli Centre for Neuro-Radiochemistry, Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Canada
- Institute of Medical Science, University of Toronto, 1 King's College Circle, Toronto, Canada
| | - Christopher D Morrone
- Azrieli Centre for Neuro-Radiochemistry, Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Canada
| | - Cassis Varlow
- Azrieli Centre for Neuro-Radiochemistry, Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Canada
- Institute of Medical Science, University of Toronto, 1 King's College Circle, Toronto, Canada
| | - Wai Haung Yu
- Azrieli Centre for Neuro-Radiochemistry, Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Canada
- Department of Pharmacology and Toxicology, University of Toronto, 1 King's College Circle, Toronto, Canada
| | - Paul McQuade
- Takeda Pharmaceutical Company, Ltd, 35 Landsdowne Street, Cambridge, MA, USA
| | - Neil Vasdev
- Azrieli Centre for Neuro-Radiochemistry, Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Canada.
- Institute of Medical Science, University of Toronto, 1 King's College Circle, Toronto, Canada.
- Department of Psychiatry, University of Toronto, 250 College Street, Toronto, Canada.
| |
Collapse
|
22
|
Uchida Y, Kan H, Sakurai K, Oishi K, Matsukawa N. Quantitative susceptibility mapping as an imaging biomarker for Alzheimer’s disease: The expectations and limitations. Front Neurosci 2022; 16:938092. [PMID: 35992906 PMCID: PMC9389285 DOI: 10.3389/fnins.2022.938092] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 07/14/2022] [Indexed: 11/25/2022] Open
Abstract
Alzheimer’s disease (AD) is the most common type of dementia and a distressing diagnosis for individuals and caregivers. Researchers and clinical trials have mainly focused on β-amyloid plaques, which are hypothesized to be one of the most important factors for neurodegeneration in AD. Meanwhile, recent clinicopathological and radiological studies have shown closer associations of tau pathology rather than β-amyloid pathology with the onset and progression of Alzheimer’s symptoms. Toward a biological definition of biomarker-based research framework for AD, the 2018 National Institute on Aging–Alzheimer’s Association working group has updated the ATN classification system for stratifying disease status in accordance with relevant pathological biomarker profiles, such as cerebral β-amyloid deposition, hyperphosphorylated tau, and neurodegeneration. In addition, altered iron metabolism has been considered to interact with abnormal proteins related to AD pathology thorough generating oxidative stress, as some prior histochemical and histopathological studies supported this iron-mediated pathomechanism. Quantitative susceptibility mapping (QSM) has recently become more popular as a non-invasive magnetic resonance technique to quantify local tissue susceptibility with high spatial resolution, which is sensitive to the presence of iron. The association of cerebral susceptibility values with other pathological biomarkers for AD has been investigated using various QSM techniques; however, direct evidence of these associations remains elusive. In this review, we first briefly describe the principles of QSM. Second, we focus on a large variety of QSM applications, ranging from common applications, such as cerebral iron deposition, to more recent applications, such as the assessment of impaired myelination, quantification of venous oxygen saturation, and measurement of blood– brain barrier function in clinical settings for AD. Third, we mention the relationships among QSM, established biomarkers, and cognitive performance in AD. Finally, we discuss the role of QSM as an imaging biomarker as well as the expectations and limitations of clinically useful diagnostic and therapeutic implications for AD.
Collapse
Affiliation(s)
- Yuto Uchida
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- *Correspondence: Yuto Uchida,
| | - Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Keita Sakurai
- Department of Radiology, National Center for Geriatrics and Gerontology, Ōbu, Japan
| | - Kenichi Oishi
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Noriyuki Matsukawa
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Noriyuki Matsukawa,
| |
Collapse
|
23
|
Long-term test-retest of cerebral [18F]MK-6240 binding and longitudinal evaluation of extracerebral tracer uptake in healthy controls and amnestic MCI patients. Eur J Nucl Med Mol Imaging 2022; 49:4580-4588. [DOI: 10.1007/s00259-022-05907-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 07/07/2022] [Indexed: 11/04/2022]
|
24
|
Hicks A, Ponsford JL, Spitz G, Dore V, Krishnadas N, Roberts C, Rowe CC. Amyloid- and Tau Imaging in Chronic Traumatic Brain Injury: A Cross-sectional Study. Neurology 2022; 99:e1131-e1141. [PMID: 36096678 DOI: 10.1212/wnl.0000000000200857] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 05/02/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Traumatic brain injury (TBI) has been promoted as a risk factor for Alzheimer's disease. There is evidence of elevated amyloid-β and tau, the pathological hallmarks of Alzheimer's disease, immediately following TBI. It is not clear whether amyloid-β and tau remain elevated in the chronic period. To address this issue, we assessed amyloid-β and tau burden in long-term TBI survivors and healthy controls using PET imaging. METHODS Using a cross-sectional design, we recruited individuals following a single moderate to severe TBI at least 10 years previously from an inpatient rehabilitation program. A demographically similar healthy control group was recruited from the community. PET data were acquired using 18F-NAV4694 (amyloid-β) and 18F-MK6240 (tau) tracers. Amyloid-β deposition was quantified using the Centiloid scale. Tau deposition was quantified using the standardized uptake value ratio (SUVR) in four regions of interest (ROI). As a secondary measure, PET scans were also visually read as positive or negative. We examined PET data in relation to time since injury and age at injury. PET data were analysed in a series of regression analyses. RESULTS The sample comprised 87 individuals with TBI (71.3% male; 28.7% female; M = 57.53 years, SD = 11.53) and 59 controls (59.3% male; 40.7% female; M = 60.34 years, SD = 11.97). Individuals with TBI did not have significantly higher 18F-NAV4694 Centiloid values (p = 0.067) or 18F-MK6240 tau SUVRs in any ROI (p = ≤ 0.001; SUVR greater for controls). Visual assessment was consistent with the quantification; individuals with TBI were not more likely than controls to have a positive amyloid-β (p = 0.505) or tau scan (p = 0.221). No associations were identified for amyloid-β or tau burden with time since injury (p = 0.057 to 0.332) or age at injury. DISCUSSION A single moderate to severe TBI was not associated with higher burden of amyloid-β or tau pathologies in the chronic period relative to healthy controls. Amyloid-β and tau burden did not show a significant increase with years since injury, and burden did not appear to be greater for those who were older at the time of injury.
Collapse
Affiliation(s)
- Amelia Hicks
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, 3168, Australia.
| | - Jennie L Ponsford
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, 3168, Australia
| | - Gershon Spitz
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, 3168, Australia
| | - Vincent Dore
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, 3084, Australia.,CSIRO Health and Biosecurity Flagship, The Australian e-Health Research Centre, Parkville, 3052, Australia
| | - Natasha Krishnadas
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, 3084, Australia.,Florey Department of Neuroscience and Mental Health, University of Melbourne, Parkville, 3052, Australia
| | - Caroline Roberts
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, 3168, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, 3084, Australia.,Florey Department of Neuroscience and Mental Health, University of Melbourne, Parkville, 3052, Australia
| |
Collapse
|
25
|
Kim MH, Jung WJ, Jeong HJ, Lee K, Kil HS, Chung WS, Nam KR, Lee YJ, Lee KC, Lim SM, Chi DY. Off‐target screening of amyloid‐beta plaque targeting [
18
F
]florapronol ([
18
F
]
FC119S
) in postmortem Alzheimer's disease tissues. B KOREAN CHEM SOC 2022. [DOI: 10.1002/bkcs.12532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Min Hwan Kim
- Research Institute of Radiopharmaceuticals FutureChem Co., Ltd. Seongdong‐gu, Seoul Republic of Korea
| | - Woon Jung Jung
- Research Institute of Radiopharmaceuticals FutureChem Co., Ltd. Seongdong‐gu, Seoul Republic of Korea
| | - Hyeon Jin Jeong
- Research Institute of Radiopharmaceuticals FutureChem Co., Ltd. Seongdong‐gu, Seoul Republic of Korea
| | - Kyongkyu Lee
- Research Institute of Radiopharmaceuticals FutureChem Co., Ltd. Seongdong‐gu, Seoul Republic of Korea
| | - Hee Seup Kil
- Research Institute of Radiopharmaceuticals FutureChem Co., Ltd. Seongdong‐gu, Seoul Republic of Korea
| | - Wee Sup Chung
- Division of Applied RI Korea Institute of Radiological & Medical Sciences Nowon‐gu, Seoul Republic of Korea
| | - Kyung Rok Nam
- Division of Applied RI Korea Institute of Radiological & Medical Sciences Nowon‐gu, Seoul Republic of Korea
| | - Yong Jin Lee
- Division of Applied RI Korea Institute of Radiological & Medical Sciences Nowon‐gu, Seoul Republic of Korea
| | - Kyo Chul Lee
- Division of Applied RI Korea Institute of Radiological & Medical Sciences Nowon‐gu, Seoul Republic of Korea
| | - Sang Moo Lim
- Department of Nuclear Medicine Korea Institute of Radiological & Medical Sciences Nowon‐gu, Seoul Republic of Korea
| | - Dae Yoon Chi
- Research Institute of Radiopharmaceuticals FutureChem Co., Ltd. Seongdong‐gu, Seoul Republic of Korea
| |
Collapse
|
26
|
Lee WJ, Brown JA, Kim HR, La Joie R, Cho H, Lyoo CH, Rabinovici GD, Seong JK, Seeley WW. Regional Aβ-tau interactions promote onset and acceleration of Alzheimer's disease tau spreading. Neuron 2022; 110:1932-1943.e5. [PMID: 35443153 DOI: 10.1016/j.neuron.2022.03.034] [Citation(s) in RCA: 66] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 02/19/2022] [Accepted: 03/28/2022] [Indexed: 12/22/2022]
Abstract
Amyloid-beta and tau are key molecules in the pathogenesis of Alzheimer's disease, but it remains unclear how these proteins interact to promote disease. Here, by combining cross-sectional and longitudinal molecular imaging and network connectivity analyses in living humans, we identified two amyloid-beta/tau interactions associated with the onset and propagation of tau spreading. First, we show that the lateral entorhinal cortex, an early site of tau neurofibrillary tangle formation, is subject to remote, connectivity-mediated amyloid-beta/tau interactions linked to initial tau spreading. Second, we identify the inferior temporal gyrus as the region featuring the greatest local amyloid-beta/tau interactions and a connectivity profile well suited to accelerate tau propagation. Taken together, our data address long-standing questions regarding the topographical dissimilarity between early amyloid-beta and tau deposition.
Collapse
Affiliation(s)
- Wha Jin Lee
- School of Biomedical Engineering, Korea University, Seoul 02841, South Korea
| | - Jesse A Brown
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Hye Ryun Kim
- School of Biomedical Engineering, Korea University, Seoul 02841, South Korea; Global Health Technology Research Center, College of Health Science, Korea University, Seoul 02841, South Korea
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Seoul 06273, South Korea
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Seoul 06273, South Korea
| | - Gil D Rabinovici
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Joon-Kyung Seong
- School of Biomedical Engineering, Korea University, Seoul 02841, South Korea; Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea.
| | - William W Seeley
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Pathology, University of California, San Francisco, San Francisco, CA 94143, USA.
| | | |
Collapse
|
27
|
Ushizima D, Chen Y, Alegro M, Ovando D, Eser R, Lee W, Poon K, Shankar A, Kantamneni N, Satrawada S, Junior EA, Heinsen H, Tosun D, Grinberg LT. Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation. Neuroimage 2022; 248:118790. [DOI: 10.1016/j.neuroimage.2021.118790] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 11/30/2021] [Accepted: 12/04/2021] [Indexed: 01/16/2023] Open
|
28
|
Filippi L, Schillaci O, Palumbo B. Neuroimaging with PET/CT in chronic traumatic encephalopathy: what nuclear medicine can do to move the field forward. Expert Rev Mol Diagn 2022; 22:149-156. [PMID: 35086415 DOI: 10.1080/14737159.2022.2035723] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative syndrome, caused by single or repeated traumatic brain injuries. Since a few years ago, post mortem examination represented the only effective method to diagnose CTE through the detection of its peculiar neuropathological features (i.e. tau protein aggregates) at a macroscopic and microscopic level. Several efforts have been made to develop radiopharmaceuticals characterized by high affinity for tau aggregates, suitable for imaging through Positron Emission Computed Tomography (Tau-PET). AREAS COVERED : The various radiopharmaceuticals utilized for the molecular imaging of CTE through Tau-PET are covered, with specific reference to their applications in clinical practice. Furthermore, PET probes binding to the translocator protein (TSPO), a marker of brain injury and repair, are reviewed as potential tools for the imaging of neuroinflammatory cascade associated with CTE. EXPERT OPINION molecular neuroimaging of CTE with Tau-PET is an intriguing, although still not completely explored, tool for the in vivo detection and monitoring of neuropathological hallmarks associated with CTE. Furthermore, some novel tracers, such as TSPO-ligands, hold the promise to get an insight into the complex physiopathological mechanisms leading from brain injury to symptomatic CTE.
Collapse
Affiliation(s)
- Luca Filippi
- Department of Nuclear Medicine, Santa Maria Goretti Hospital, Via Canova 3, 04100 Latina, Italy
| | - Orazio Schillaci
- Department of Biomedicine and Prevention, University Tor Vergata, Rome, Italy.,IRCCS Neuromed, Pozzilli, Italy
| | - Barbara Palumbo
- Section of Nuclear Medicine and Health Physics, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Perugia, Italy
| |
Collapse
|
29
|
Ni R, Nitsch RM. Recent Developments in Positron Emission Tomography Tracers for Proteinopathies Imaging in Dementia. Front Aging Neurosci 2022; 13:751897. [PMID: 35046791 PMCID: PMC8761855 DOI: 10.3389/fnagi.2021.751897] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 11/17/2021] [Indexed: 12/15/2022] Open
Abstract
An early detection and intervention for dementia represent tremendous unmet clinical needs and priorities in society. A shared feature of neurodegenerative diseases causing dementia is the abnormal accumulation and spreading of pathological protein aggregates, which affect the selective vulnerable circuit in a disease-specific pattern. The advancement in positron emission tomography (PET) biomarkers has accelerated the understanding of the disease mechanism and development of therapeutics for Alzheimer's disease and Parkinson's disease. The clinical utility of amyloid-β PET and the clinical validity of tau PET as diagnostic biomarker for Alzheimer's disease continuum have been demonstrated. The inclusion of biomarkers in the diagnostic criteria has introduced a paradigm shift that facilitated the early and differential disease diagnosis and impacted on the clinical management. Application of disease-modifying therapy likely requires screening of patients with molecular evidence of pathological accumulation and monitoring of treatment effect assisted with biomarkers. There is currently still a gap in specific 4-repeat tau imaging probes for 4-repeat tauopathies and α-synuclein imaging probes for Parkinson's disease and dementia with Lewy body. In this review, we focused on recent development in molecular imaging biomarkers for assisting the early diagnosis of proteinopathies (i.e., amyloid-β, tau, and α-synuclein) in dementia and discussed future perspectives.
Collapse
Affiliation(s)
- Ruiqing Ni
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, ETH & University of Zurich, Zurich, Switzerland
| | - Roger M. Nitsch
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| |
Collapse
|
30
|
PET imaging in dementia. Nucl Med Mol Imaging 2022. [DOI: 10.1016/b978-0-12-822960-6.00089-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
|
31
|
Sexton C, Snyder H, Beher D, Boxer AL, Brannelly P, Brion JP, Buée L, Cacace AM, Chételat G, Citron M, DeVos SL, Diaz K, Feldman HH, Frost B, Goate AM, Gold M, Hyman B, Johnson K, Karch CM, Kerwin DR, Koroshetz WJ, Litvan I, Morris HR, Mummery CJ, Mutamba J, Patterson MC, Quiroz YT, Rabinovici GD, Rommel A, Shulman MB, Toledo-Sherman LM, Weninger S, Wildsmith KR, Worley SL, Carrillo MC. Current directions in tau research: Highlights from Tau 2020. Alzheimers Dement 2021; 18:988-1007. [PMID: 34581500 DOI: 10.1002/alz.12452] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 07/07/2021] [Accepted: 07/22/2021] [Indexed: 11/07/2022]
Abstract
Studies supporting a strong association between tau deposition and neuronal loss, neurodegeneration, and cognitive decline have heightened the allure of tau and tau-related mechanisms as therapeutic targets. In February 2020, leading tau experts from around the world convened for the first-ever Tau2020 Global Conference in Washington, DC, co-organized and cosponsored by the Rainwater Charitable Foundation, the Alzheimer's Association, and CurePSP. Representing academia, industry, government, and the philanthropic sector, presenters and attendees discussed recent advances and current directions in tau research. The meeting provided a unique opportunity to move tau research forward by fostering global partnerships among academia, industry, and other stakeholders and by providing support for new drug discovery programs, groundbreaking research, and emerging tau researchers. The meeting also provided an opportunity for experts to present critical research-advancing tools and insights that are now rapidly accelerating the pace of tau research.
Collapse
Affiliation(s)
| | | | | | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Pat Brannelly
- Alzheimer's Disease Data Initiative, Kirkland, WI, USA
| | - Jean-Pierre Brion
- Laboratory of Histology, Neuroanatomy and Neuropathology, Faculty of Medicine, Université Libre de Bruxelles, Brussels, Belgium
| | - Luc Buée
- Univ Lille, Inserm, CHU-Lille, Lille Neuroscience and Cognition, Place de Verdun, Lille, France
| | | | - Gaël Chételat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Martin Citron
- Neuroscience TA, Braine l'Alleud, UCB Biopharma, Brussels, Belgium
| | - Sarah L DeVos
- Translational Sciences, Denali Therapeutics, San Francisco, California, USA
| | | | - Howard H Feldman
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California, San Diego, La Jolla, California, USA
| | - Bess Frost
- Sam & Ann Barshop Institute for Longevity and Aging Studies, Glenn Biggs Institute for Alzheimer's & Neurodegenerative Disorders, Department of Cell Systems & Anatomy, University of Texas Health San Antonio, San Antonio, Texas, USA
| | - Alison M Goate
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Michael Gold
- AbbVie, Neurosciences Development, North Chicago, Illinois, USA
| | - Bradley Hyman
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Keith Johnson
- Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Celeste M Karch
- Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Diana R Kerwin
- Kerwin Medical Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Walter J Koroshetz
- National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| | - Irene Litvan
- Parkinson and Other Movement Disorders Center, Department of Neurosciences, University of California San Diego, San Diego, California, USA
| | - Huw R Morris
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, London, UK
| | - Catherine J Mummery
- Dementia Research Centre, National Hospital for Neurology and Neurosurgery, University College London, London, UK
| | | | - Marc C Patterson
- Departments of Neurology, Pediatrics and Medical Genetics, Mayo Clinic, Rochester, Minnesota, USA
| | - Yakeel T Quiroz
- Departments of Neurology and Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Gil D Rabinovici
- Memory & Aging Center, Departments of Neurology, Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Amy Rommel
- Tau Consortium, Rainwater Charitable Foundation, Fort Worth, Texas, USA
| | - Melanie B Shulman
- Neurodegeneration Development Unit, Biogen, Boston, Massachusetts, USA
| | | | | | - Kristin R Wildsmith
- Department of Biomarker Development, Genentech, South San Francisco, California, USA
| | - Susan L Worley
- Independent science writer, Bryn Mawr, Pennsylvania, USA
| | | |
Collapse
|
32
|
Hall Z, Chien B, Zhao Y, Risacher SL, Saykin AJ, Wu YC, Wen Q. Tau deposition and structural connectivity demonstrate differential association patterns with neurocognitive tests. Brain Imaging Behav 2021; 16:702-714. [PMID: 34533771 PMCID: PMC8935446 DOI: 10.1007/s11682-021-00531-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/28/2021] [Indexed: 11/25/2022]
Abstract
Tau neurofibrillary tangles have a central role in the pathogenesis of Alzheimer’s Disease (AD). Mounting evidence indicates that the propagation of tau is assisted by brain connectivity with weakened white-matter integrity along the propagation pathways. Recent advances in tau positron emission tomography tracers and diffusion magnetic resonance imaging allow the visualization of tau pathology and white-matter connectivity of the brain in vivo. The current study aims to investigate how tau deposition and structural connectivity are associated with memory function in prodromal AD. In this study, tau accumulation and structural connectivity data from 83 individuals (57 cognitively normal participants and 26 participants with mild cognitive impairment) were associated with neurocognitive test scores. Statistical analyses were performed in 70 cortical/subcortical brain regions to determine: 1. the level of association between tau and network metrics extracted from structural connectivity and 2. the association patterns of brain memory function with tau accumulation and network metrics. The results showed that tau accumulation and network metrics were correlated in early tau deposition regions. Furthermore, tau accumulation was associated with worse performance in almost all neurocognitive tests performance evaluated in the study. In comparison, decreased network connectivity was associated with declines in the delayed memory recall in Craft Stories and Benson Figure Copy. Interaction analysis indicates that tau deposition and dysconnectivity have a synergistic effect on the delayed Benson Figure Recall. Overall, our findings indicate that both tau deposition and structural dysconnectivity are associated with neurocognitive dysfunction. They also suggest that tau-PET may have better sensitivity to neurocognitive performance than diffusion MRI-derived measures of white-matter connectivity.
Collapse
Affiliation(s)
- Zack Hall
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Billy Chien
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yi Zhao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 West 16th Street, Suite 4100, Indianapolis, IN, 46202, USA.,Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 West 16th Street, Suite 4100, Indianapolis, IN, 46202, USA.,Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Clinical Psychology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 West 16th Street, Suite 4100, Indianapolis, IN, 46202, USA. .,Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA. .,Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA. .,Indiana Institute for Biomedical Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN, 46202, USA.
| | - Qiuting Wen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 West 16th Street, Suite 4100, Indianapolis, IN, 46202, USA. .,Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
| |
Collapse
|
33
|
Colato E, Chiotis K, Ferreira D, Mazrina MS, Lemoine L, Mohanty R, Westman E, Nordberg A, Rodriguez-Vieitez E. Assessment of Tau Pathology as Measured by 18F-THK5317 and 18F-Flortaucipir PET and Their Relation to Brain Atrophy and Cognition in Alzheimer's Disease. J Alzheimers Dis 2021; 84:103-117. [PMID: 34511502 PMCID: PMC8609906 DOI: 10.3233/jad-210614] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND In Alzheimer's disease (AD), the abnormal aggregation of hyperphosphorylated tau leads to synaptic dysfunction and neurodegeneration. Recently developed tau PET imaging tracers are candidate biomarkers for diagnosis and staging of AD. OBJECTIVE We aimed to investigate the discriminative ability of 18F-THK5317 and 18F-flortaucipir tracers and brain atrophy at different stages of AD, and their respective associations with cognition. METHODS Two cohorts, each including 29 participants (healthy controls [HC], prodromal AD, and AD dementia patients), underwent 18F-THK5317 or 18F-flortaucipir PET, T1-weighted MRI, and neuropsychological assessment. For each subject, we quantified regional 18F-THK5317 and 18F-flortaucipir uptake within six bilateral and two composite regions of interest. We assessed global brain atrophy for each individual by quantifying the brain volume index, a measure of brain volume-to-cerebrospinal fluid ratio. We then quantified the discriminative ability of regional 18F-THK5317, 18F-flortaucipir, and brain volume index between diagnostic groups, and their associations with cognition in patients. RESULTS Both 18F-THK5317 and 18F-flortaucipir outperformed global brain atrophy in discriminating between HC and both prodromal AD and AD dementia groups. 18F-THK5317 provided the highest discriminative ability between HC and prodromal AD groups. 18F-flortaucipir performed best at discriminating between prodromal and dementia stages of AD. Across all patients, both tau tracers were predictive of RAVL learning, but only 18F-flortaucipir predicted MMSE. CONCLUSION Our results warrant further in vivo head-to-head and antemortem-postmortem evaluations. These validation studies are needed to select tracers with high clinical validity as biomarkers for early diagnosis, prognosis, and disease staging, which will facilitate their incorporation in clinical practice and therapeutic trials.
Collapse
Affiliation(s)
- Elisa Colato
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Mariam S Mazrina
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Laetitia Lemoine
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Rosaleena Mohanty
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Elena Rodriguez-Vieitez
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | | |
Collapse
|
34
|
Biel D, Brendel M, Rubinski A, Buerger K, Janowitz D, Dichgans M, Franzmeier N. Tau-PET and in vivo Braak-staging as prognostic markers of future cognitive decline in cognitively normal to demented individuals. ALZHEIMERS RESEARCH & THERAPY 2021; 13:137. [PMID: 34384484 PMCID: PMC8361801 DOI: 10.1186/s13195-021-00880-x] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 07/21/2021] [Indexed: 11/20/2022]
Abstract
Background To systematically examine the clinical utility of tau-PET and Braak-staging as prognostic markers of future cognitive decline in older adults with and without cognitive impairment. Methods In this longitudinal study, we included 396 cognitively normal to dementia subjects with 18F-Florbetapir/18F-Florbetaben-amyloid-PET, 18F-Flortaucipir-tau-PET and ~ 2-year cognitive follow-up. Annual change rates in global cognition (i.e., MMSE, ADAS13) and episodic memory were calculated via linear-mixed models. We determined global amyloid-PET (Centiloid) plus global and Braak-stage-specific tau-PET SUVRs, which were stratified as positive(+)/negative(−) at pre-established cut-offs, classifying subjects as Braak0/BraakI+/BraakI–IV+/BraakI–VI+/Braakatypical+. In bootstrapped linear regression, we assessed the predictive accuracy of global tau-PET SUVRs vs. Centiloid on subsequent cognitive decline. To test for independent tau vs. amyloid effects, analyses were further controlled for the contrary PET-tracer. Using ANCOVAs, we tested whether more advanced Braak-stage predicted accelerated future cognitive decline. All models were controlled for age, sex, education, diagnosis, and baseline cognition. Lastly, we determined Braak-stage-specific conversion risk to mild cognitive impairment (MCI) or dementia. Results Baseline global tau-PET SUVRs explained more variance (partial R2) in future cognitive decline than Centiloid across all cognitive tests (Cohen’s d ~ 2, all tests p < 0.001) and diagnostic groups. Associations between tau-PET and cognitive decline remained consistent when controlling for Centiloid, while associations between amyloid-PET and cognitive decline were non-significant when controlling for tau-PET. More advanced Braak-stage was associated with gradually worsening future cognitive decline, independent of Centiloid or diagnostic group (p < 0.001), and elevated conversion risk to MCI/dementia. Conclusion Tau-PET and Braak-staging are highly predictive markers of future cognitive decline and may be promising single-modality estimates for prognostication of patient-specific progression risk in clinical settings. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00880-x.
Collapse
Affiliation(s)
- Davina Biel
- Institute, for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377, Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital, LMU Munich, 80336, Munich, Germany
| | - Anna Rubinski
- Institute, for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377, Munich, Germany
| | - Katharina Buerger
- Institute, for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany
| | - Daniel Janowitz
- Institute, for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377, Munich, Germany
| | - Martin Dichgans
- Institute, for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Nicolai Franzmeier
- Institute, for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377, Munich, Germany.
| | | |
Collapse
|
35
|
Okafor M, Nye JA, Shokouhi M, Shaw LM, Goldstein F, Hajjar I. 18F-Flortaucipir PET Associations with Cerebrospinal Fluid, Cognition, and Neuroimaging in Mild Cognitive Impairment due to Alzheimer's Disease. J Alzheimers Dis 2021; 74:589-601. [PMID: 32065800 DOI: 10.3233/jad-191330] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND Tau positron emission tomography (PET) imaging is used in research, but its relation to cerebrospinal fluid (CSF) tau and other Alzheimer's disease (AD)-related clinical measures is unclear in mild cognitive impairment with AD biomarkers (MCI-AD). OBJECTIVE To determine associations between 18F-flortaucipir PET and CSF AD biomarkers, cognitive functioning, and neuroimaging measures in MCI-AD. METHODS In 29 participants 50 years or older with MCI-AD, 18F-flortaucipir PET, CSF total tau (T-tau), phosphorylated tau181p (P-tau), amyloid-β (Aβ), structural MRI, and neuropsychological testing were collected as baseline assessments of an ongoing clinical trial. 11C-Pittsburgh compound B PET was simultaneously conducted in 20 participants. Associations between 18F-flortaucipir PET and these measures were assessed by multiple linear regression adjusted for potential confounders and using global, lobar, and voxel-wise standardized uptake value ratio (SUVr). RESULTS Whole brain 18F-flortaucipir SUVr was significantly associated with CSF T-tau (r = 0.68, p < 0.001) and P-tau (r = 0.42, p = 0.04) after adjusting for age, sex, race, and education, with strongest associations in the temporal region (T-tau: r = 0.69, p < 0.001; P-tau: r = 0.49, p = 0.02). Voxel-wise analysis confirmed these regional associations. 18F-flortaucipir PET was also associated with CSF Aβ (r = -0.45, p = 0.03), episodic memory (r = -0.61, p = 0.001), visuospatial working memory (r = -0.46, p = 0.02), and brain cortical thickness (r = -0.44, p = 0.03) but not hippocampal volume. In the amyloid PET subset, although 11C-PiB PET associated strongly with 18F-flortaucipir (r = 0.79, p≤0.001), associations were stronger between 11C-PiB and key outcomes, compared to 18F-flortaucipir. CONCLUSION 18F-flortaucipir PET is moderately associated with CSF AD biomarkers and other AD-related phenotypes. The associations in this MCI-AD sample are stronger than previously described in other populations.
Collapse
Affiliation(s)
- Maureen Okafor
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Jonathon A Nye
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, USA
| | - Mahsa Shokouhi
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Felicia Goldstein
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Ihab Hajjar
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.,Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| |
Collapse
|
36
|
Schäfer A, Peirlinck M, Linka K, Kuhl E. Bayesian Physics-Based Modeling of Tau Propagation in Alzheimer's Disease. Front Physiol 2021; 12:702975. [PMID: 34335308 PMCID: PMC8322942 DOI: 10.3389/fphys.2021.702975] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 06/22/2021] [Indexed: 11/24/2022] Open
Abstract
Amyloid-β and hyperphosphorylated tau protein are known drivers of neuropathology in Alzheimer's disease. Tau in particular spreads in the brains of patients following a spatiotemporal pattern that is highly sterotypical and correlated with subsequent neurodegeneration. Novel medical imaging techniques can now visualize the distribution of tau in the brain in vivo, allowing for new insights to the dynamics of this biomarker. Here we personalize a network diffusion model with global spreading and local production terms to longitudinal tau positron emission tomography data of 76 subjects from the Alzheimer's Disease Neuroimaging Initiative. We use Bayesian inference with a hierarchical prior structure to infer means and credible intervals for our model parameters on group and subject levels. Our results show that the group average protein production rate for amyloid positive subjects is significantly higher with 0.019±0.27/yr, than that for amyloid negative subjects with -0.143±0.21/yr (p = 0.0075). These results support the hypothesis that amyloid pathology drives tau pathology. The calibrated model could serve as a valuable clinical tool to identify optimal time points for follow-up scans and predict the timeline of disease progression.
Collapse
Affiliation(s)
- Amelie Schäfer
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
| | - Mathias Peirlinck
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
| | - Kevin Linka
- Institute of Continuum and Materials Mechanics, Hamburg University of Technology, Hamburg, Germany
| | - Ellen Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
| | | |
Collapse
|
37
|
Ossenkoppele R, Reimand J, Smith R, Leuzy A, Strandberg O, Palmqvist S, Stomrud E, Zetterberg H, Scheltens P, Dage JL, Bouwman F, Blennow K, Mattsson-Carlgren N, Janelidze S, Hansson O. Tau PET correlates with different Alzheimer's disease-related features compared to CSF and plasma p-tau biomarkers. EMBO Mol Med 2021; 13:e14398. [PMID: 34254442 PMCID: PMC8350902 DOI: 10.15252/emmm.202114398] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 06/15/2021] [Accepted: 06/16/2021] [Indexed: 12/13/2022] Open
Abstract
PET, CSF and plasma biomarkers of tau pathology may be differentially associated with Alzheimer's disease (AD)‐related demographic, cognitive, genetic and neuroimaging markers. We examined 771 participants with normal cognition, mild cognitive impairment or dementia from BioFINDER‐2 (n = 400) and ADNI (n = 371). All had tau‐PET ([18F]RO948 in BioFINDER‐2, [18F]flortaucipir in ADNI) and CSF p‐tau181 biomarkers available. Plasma p‐tau181 and plasma/CSF p‐tau217 were available in BioFINDER‐2 only. Concordance between PET, CSF and plasma tau biomarkers ranged between 66 and 95%. Across the whole group, ridge regression models showed that increased CSF and plasma p‐tau181 and p‐tau217 levels were independently of tau PET associated with higher age, and APOEɛ4‐carriership and Aβ‐positivity, while increased tau‐PET signal in the temporal cortex was associated with worse cognitive performance and reduced cortical thickness. We conclude that biofluid and neuroimaging markers of tau pathology convey partly independent information, with CSF and plasma p‐tau181 and p‐tau217 levels being more tightly linked with early markers of AD (especially Aβ‐pathology), while tau‐PET shows the strongest associations with cognitive and neurodegenerative markers of disease progression.
Collapse
Affiliation(s)
- Rik Ossenkoppele
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Juhan Reimand
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Health Technologies, Tallinn University of Technology, Tallinn, Estonia.,Radiology Centre, North Estonia Medical Centre, Tallinn, Estonia
| | - Ruben Smith
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Antoine Leuzy
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | | | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | | | - Femke Bouwman
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden.,Wallenberg Centre for Molecular Medicine, Lund University, Lund, Sweden
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| |
Collapse
|
38
|
The Evaluation of Tau Deposition with [ 18F]PI-2620 by Using a Semiquantitative Method in Cognitively Normal Subjects and Patients with Mild Cognitive Impairment and Alzheimer's Disease. Mol Imaging 2021; 2021:6640054. [PMID: 34381315 PMCID: PMC8328488 DOI: 10.1155/2021/6640054] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 05/18/2021] [Accepted: 06/22/2021] [Indexed: 11/18/2022] Open
Abstract
Background Some studies have reported the effectiveness of [18F]PI-2620 as an effective tau-binding radiotracer; however, few reports have applied semiquantitative analysis to the tracer. Therefore, this study's aim was to perform a semiquantitative analysis of [18F]PI-2620 in individuals with normal cognition and patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Methods Twenty-six cognitively normal (CN) subjects, 7 patients with AD, and 36 patients with MCI were enrolled. A dynamic positron emission tomography (PET) scan was performed 30–75 min postinjection. PET and T1-weighted magnetic resonance imaging scans were coregistered. The standardized uptake value ratio (SUVr) was used for semiquantitative analysis. The P-Mod software was applied to create volumes of interest. The ANOVA and post hoc Tukey HSD were used for statistical analysis. Results In the AD group, the occipital lobe had a significantly higher mean SUVr (1.46 ± 0.57) than in the CN and MCI groups. Compared with the CN group, the AD group showed significantly higher mean SUVr in the fusiform gyrus (1.06 ± 0.09 vs. 1.49 ± 0.86), inferior temporal (1.07 ± 0.07 vs. 1.46 ± 0.08), parietal lobe, lingual gyrus, and precuneus regions. Similarly, the AD group demonstrated a higher mean SUVr than the MCI group in the precuneus, lingual, inferior temporal, fusiform, supramarginal, orbitofrontal, and superior temporal regions. The remaining observed regions, including the striatum, basal ganglia, thalamus, and white matter, showed a low SUVr across all groups with no statistically significant differences. Conclusion A significantly higher mean SUVr of [18F]PI-2620 was observed in the AD group; a significant area of the brain in the AD group demonstrated tau protein deposit in concordance with Braak Stages III–V, providing useful information to differentiate AD from CN and MCI. Moreover, the low SUVr in the deep striatum and thalamus could be useful for excluding primary tauopathies.
Collapse
|
39
|
Willroider M, Roeber S, Horn AKE, Arzberger T, Scheifele M, Respondek G, Sabri O, Barthel H, Patt M, Mishchenko O, Schildan A, Mueller A, Koglin N, Stephens A, Levin J, Höglinger GU, Bartenstein P, Herms J, Brendel M, Beyer L. Superiority of Formalin-Fixed Paraffin-Embedded Brain Tissue for in vitro Assessment of Progressive Supranuclear Palsy Tau Pathology With [ 18 F]PI-2620. Front Neurol 2021; 12:684523. [PMID: 34276540 PMCID: PMC8282895 DOI: 10.3389/fneur.2021.684523] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 05/25/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives: Autoradiography on brain tissue is used to validate binding targets of newly discovered radiotracers. The purpose of this study was to correlate quantification of autoradiography signal using the novel next-generation tau positron emission tomography (PET) radiotracer [18F]PI-2620 with immunohistochemically determined tau-protein load in both formalin-fixed paraffin-embedded (FFPE) and frozen tissue samples of patients with Alzheimer's disease (AD) and Progressive Supranuclear Palsy (PSP). Methods: We applied [18F]PI-2620 autoradiography to postmortem cortical brain samples of six patients with AD, five patients with PSP and five healthy controls, respectively. Binding intensity was compared between both tissue types and different disease entities. Autoradiography signal quantification (CWMR = cortex to white matter ratio) was correlated with the immunohistochemically assessed tau load (AT8-staining, %-area) for FFPE and frozen tissue samples in the different disease entities. Results: In AD tissue, relative cortical tracer binding was higher in frozen samples when compared to FFPE samples (CWMRfrozen vs. CWMRFFPE: 2.5-fold, p < 0.001), whereas the opposite was observed in PSP tissue (CWMRfrozen vs. CWMRFFPE: 0.8-fold, p = 0.004). In FFPE samples, [18F]PI-2620 autoradiography tracer binding and immunohistochemical tau load correlated significantly for both PSP (R = 0.641, p < 0.001) and AD tissue (R = 0.435, p = 0.016), indicating a high agreement of relative tracer binding with underlying pathology. In frozen tissue, the correlation between autoradiography and immunohistochemistry was only present in AD (R = 0.417, p = 0.014) but not in PSP tissue (R = -0.115, p = n.s.). Conclusion: Our head-to-head comparison indicates that FFPE samples show superiority over frozen samples for autoradiography assessment of PSP tau pathology by [18F]PI-2620. The [18F]PI-2620 autoradiography signal in FFPE samples reflects AT8 positive tau in samples of both PSP and AD patients.
Collapse
Affiliation(s)
- Marie Willroider
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Sigrun Roeber
- Center for Neuropathology and Prion Research, LMU Munich, Munich, Germany
| | - Anja K E Horn
- Institute of Anatomy and Cell Biology, LMU Munich, Munich, Germany
| | - Thomas Arzberger
- Center for Neuropathology and Prion Research, LMU Munich, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Maximilian Scheifele
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Gesine Respondek
- Department of Neurology, Hannover Medical School, Hanover, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Marianne Patt
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Olena Mishchenko
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Andreas Schildan
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | | | | | | | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Neurology, University Hospital Munich, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Günter U Höglinger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Neurology, Hannover Medical School, Hanover, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,Department of Neurology, Technical University Munich, Munich, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Jochen Herms
- Center for Neuropathology and Prion Research, LMU Munich, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Leonie Beyer
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany.,Center for Neuropathology and Prion Research, LMU Munich, Munich, Germany
| |
Collapse
|
40
|
Franzmeier N, Ossenkoppele R, Brendel M, Rubinski A, Smith R, Kumar A, Mattsson-Carlgren N, Strandberg O, Duering M, Buerger K, Dichgans M, Hansson O, Ewers M. The BIN1 rs744373 Alzheimer's disease risk SNP is associated with faster Aβ-associated tau accumulation and cognitive decline. Alzheimers Dement 2021; 18:103-115. [PMID: 34060233 DOI: 10.1002/alz.12371] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 03/16/2021] [Accepted: 04/16/2021] [Indexed: 12/16/2022]
Abstract
INTRODUCTION The BIN1 rs744373 single nucleotide polymorphism (SNP) is a key genetic risk locus for Alzheimer's disease (AD) associated with tau pathology. Because tau typically accumulates in response to amyloid beta (Aβ), we tested whether BIN1 rs744373 accelerates Aβ-related tau accumulation. METHODS We included two samples (Alzheimer's Disease Neuroimaging Initiative [ADNI], n = 153; Biomarkers for Identifying Neurodegenerative Disorders Early and Reliably [BioFINDER], n = 63) with longitudinal 18 F-Flortaucipir positron emission tomography (PET), Aβ biomarkers, and longitudinal cognitive assessments. We assessed whether BIN1 rs744373 was associated with faster tau-PET accumulation at a given level of Aβ and whether faster BIN1 rs744373-associated tau-PET accumulation mediated cognitive decline. RESULTS BIN1 rs744373 risk-allele carriers showed faster global tau-PET accumulation (ADNI/BioFINDER, P < .001/P < .001). We found significant Aβ by rs744373 interactions on global tau-PET change (ADNI: β/standard error [SE] = 0.42/0.14, P = 0.002; BioFINDER: β/SE = -0.35/0.15, P = .021), BIN1 risk-allele carriers showed accelerated tau-PET accumulation at higher Aβ levels. In ADNI, rs744373 effects on cognitive decline were mediated by faster global tau-PET accumulation (β/SE = 0.20/0.07, P = .005). DISCUSSION BIN1-associated AD risk is potentially driven by accelerated tau accumulation in the face of Aβ.
Collapse
Affiliation(s)
- Nicolai Franzmeier
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Anna Rubinski
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Atul Kumar
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Marco Duering
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany.,Medical Image Analysis Center (MIAC AG), Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Katharina Buerger
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Michael Ewers
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | | |
Collapse
|
41
|
Combination of automated brain volumetry on MRI and quantitative tau deposition on THK-5351 PET to support diagnosis of Alzheimer's disease. Sci Rep 2021; 11:10343. [PMID: 33990649 PMCID: PMC8121780 DOI: 10.1038/s41598-021-89797-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Accepted: 04/27/2021] [Indexed: 01/18/2023] Open
Abstract
Imaging biomarkers support the diagnosis of Alzheimer’s disease (AD). We aimed to determine whether combining automated brain volumetry on MRI and quantitative measurement of tau deposition on [18F] THK-5351 PET can aid discrimination of AD spectrum. From a prospective database in an IRB-approved multicenter study (NCT02656498), 113 subjects (32 healthy control, 55 mild cognitive impairment, and 26 Alzheimer disease) with baseline structural MRI and [18F] THK-5351 PET were included. Cortical volumes were quantified from FDA-approved software for automated volumetric MRI analysis (NeuroQuant). Standardized uptake value ratio (SUVR) was calculated from tau PET images for 6 composite FreeSurfer-derived regions-of-interests approximating in vivo Braak stage (Braak ROIs). On volumetric MRI analysis, stepwise logistic regression analyses identified the cingulate isthmus and inferior parietal lobule as significant regions in discriminating AD from HC and MCI. The combined model incorporating automated volumes of selected brain regions on MRI (cingulate isthmus, inferior parietal lobule, hippocampus) and SUVRs of Braak ROIs on [18F] THK-5351 PET showed higher performance than SUVRs of Braak ROIs on [18F] THK-5351 PET in discriminating AD from HC (0.98 vs 0.88, P = 0.033) but not in discriminating AD from MCI (0.85 vs 0.79, P = 0.178). The combined model showed comparable performance to automated volumes of selected brain regions on MRI in discriminating AD from HC (0.98 vs 0.94, P = 0.094) and MCI (0.85 vs 0.78; P = 0.065).
Collapse
|
42
|
Ossenkoppele R, Hansson O. Towards clinical application of tau PET tracers for diagnosing dementia due to Alzheimer's disease. Alzheimers Dement 2021; 17:1998-2008. [PMID: 33984177 DOI: 10.1002/alz.12356] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/22/2021] [Accepted: 03/28/2021] [Indexed: 11/07/2022]
Abstract
The recent development of several tau positron emission tomography (PET) tracers represents a major milestone for the Alzheimer's disease (AD) field. These tau PET tracers bind tau neurofibrillary tangles, a key neuropathological characteristic of AD that is tightly linked to synaptic loss, brain atrophy, and cognitive decline. It is notable that these tau PET tracers show low uptake in most non-AD tauopathies and other neurodegenerative disorders, resulting in a diagnostic specificity that is superior to that of amyloid beta (Aβ) PET and biofluid markers, especially at an older age when incidental Aβ pathology is common. Furthermore, tau PET tracers diagnostically outperform widely used MRI markers. Given its excellent diagnostic performance due to the combination of high sensitivity and specificity for detecting tau pathology in AD dementia, we hypothesize that tau PET can become an important diagnostic tool in specialized clinics for the differential diagnosis of dementia syndromes where AD is among the major possible underlying diseases.
Collapse
Affiliation(s)
- Rik Ossenkoppele
- Lund University, Clinical Memory Research Unit, Lund, Sweden.,Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Oskar Hansson
- Lund University, Clinical Memory Research Unit, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| |
Collapse
|
43
|
Palleis C, Brendel M, Finze A, Weidinger E, Bötzel K, Danek A, Beyer L, Nitschmann A, Kern M, Biechele G, Rauchmann BS, Häckert J, Höllerhage M, Stephens AW, Drzezga A, van Eimeren T, Villemagne VL, Schildan A, Barthel H, Patt M, Sabri O, Bartenstein P, Perneczky R, Haass C, Levin J, Höglinger GU. Cortical [ 18 F]PI-2620 Binding Differentiates Corticobasal Syndrome Subtypes. Mov Disord 2021; 36:2104-2115. [PMID: 33951244 DOI: 10.1002/mds.28624] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 03/23/2021] [Accepted: 04/05/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Corticobasal syndrome is associated with cerebral protein aggregates composed of 4-repeat (~50% of cases) or mixed 3-repeat/4-repeat tau isoforms (~25% of cases) or nontauopathies (~25% of cases). OBJECTIVES The aim of this single-center study was to investigate the diagnostic value of the tau PET-ligand [18 F]PI-2620 in patients with corticobasal syndrome. METHODS Forty-five patients (71.5 ± 7.6 years) with corticobasal syndrome and 14 age-matched healthy controls underwent [18 F]PI-2620-PET. Beta-amyloid status was determined by cerebral β-amyloid PET and/or CSF analysis. Subcortical and cortical [18 F]PI-2620 binding was quantitatively and visually compared between β-amyloid-positive and -negative patients and controls. Regional [18 F]PI-2620 binding was correlated with clinical and demographic data. RESULTS Twenty-four percent (11 of 45) were β-amyloid-positive. Significantly elevated [18 F]PI-2620 distribution volume ratios were observed in both β-amyloid-positive and β-amyloid-negative patients versus controls in the dorsolateral prefrontal cortex and basal ganglia. Cortical [18 F]PI-2620 PET positivity was distinctly higher in β-amyloid-positive compared with β-amyloid-negative patients with pronounced involvement of the dorsolateral prefrontal cortex. Semiquantitative analysis of [18 F]PI-2620 PET revealed a sensitivity of 91% for β-amyloid-positive and of 65% for β-amyloid-negative cases, which is in excellent agreement with prior clinicopathological data. Regardless of β-amyloid status, hemispheric lateralization of [18 F]PI-2620 signal reflected contralateral predominance of clinical disease severity. CONCLUSIONS Our data indicate a value of [18 F]PI-2620 for evaluating corticobasal syndrome, providing quantitatively and regionally distinct signals in β-amyloid-positive as well as β-amyloid-negative corticobasal syndrome. In corticobasal syndrome, [18 F]PI-2620 may potentially serve for a differential diagnosis and for monitoring disease progression. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Carla Palleis
- Department of Neurology, Ludwig-Maximilians-University, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, Ludwig-Maximilians-University, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Anika Finze
- Department of Nuclear Medicine, Ludwig-Maximilians-University, Munich, Germany
| | - Endy Weidinger
- Department of Neurology, Ludwig-Maximilians-University, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Kai Bötzel
- Department of Neurology, Ludwig-Maximilians-University, Munich, Germany
| | - Adrian Danek
- Department of Neurology, Ludwig-Maximilians-University, Munich, Germany
| | - Leonie Beyer
- Department of Nuclear Medicine, Ludwig-Maximilians-University, Munich, Germany
| | | | - Maike Kern
- Department of Nuclear Medicine, Ludwig-Maximilians-University, Munich, Germany
| | - Gloria Biechele
- Department of Nuclear Medicine, Ludwig-Maximilians-University, Munich, Germany
| | - Boris-Stephan Rauchmann
- Department of Radiology, Ludwig-Maximilians-University, Munich, Germany.,Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany
| | - Jan Häckert
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany
| | | | | | - Alexander Drzezga
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.,Institute of Neuroscience and Medicine (INM-2), Molecular Organization of the Brain, Forschungszentrum Jülich, Julich, Germany
| | - Thilo van Eimeren
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.,Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Victor L Villemagne
- Department of Psychiatry, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Andreas Schildan
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | - Henryk Barthel
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | - Marianne Patt
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | | | - Peter Bartenstein
- Department of Nuclear Medicine, Ludwig-Maximilians-University, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Robert Perneczky
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany.,Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College, London, United Kingdom
| | - Christian Haass
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,Chair of Metabolic Biochemistry, Biomedical Center (BMC), Faculty of Medicine, Ludwig-Maximilians-University, Munich, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-University, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Günter U Höglinger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,Department of Neurology, Hannover Medical School, Hannover, Germany
| |
Collapse
|
44
|
Vogel JW, Young AL, Oxtoby NP, Smith R, Ossenkoppele R, Strandberg OT, La Joie R, Aksman LM, Grothe MJ, Iturria-Medina Y, Pontecorvo MJ, Devous MD, Rabinovici GD, Alexander DC, Lyoo CH, Evans AC, Hansson O. Four distinct trajectories of tau deposition identified in Alzheimer's disease. Nat Med 2021; 27:871-881. [PMID: 33927414 PMCID: PMC8686688 DOI: 10.1038/s41591-021-01309-6] [Citation(s) in RCA: 325] [Impact Index Per Article: 108.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 03/04/2021] [Indexed: 01/15/2023]
Abstract
Alzheimer's disease (AD) is characterized by the spread of tau pathology throughout the cerebral cortex. This spreading pattern was thought to be fairly consistent across individuals, although recent work has demonstrated substantial variability in the population with AD. Using tau-positron emission tomography scans from 1,612 individuals, we identified 4 distinct spatiotemporal trajectories of tau pathology, ranging in prevalence from 18 to 33%. We replicated previously described limbic-predominant and medial temporal lobe-sparing patterns, while also discovering posterior and lateral temporal patterns resembling atypical clinical variants of AD. These 'subtypes' were stable during longitudinal follow-up and were replicated in a separate sample using a different radiotracer. The subtypes presented with distinct demographic and cognitive profiles and differing longitudinal outcomes. Additionally, network diffusion models implied that pathology originates and spreads through distinct corticolimbic networks in the different subtypes. Together, our results suggest that variation in tau pathology is common and systematic, perhaps warranting a re-examination of the notion of 'typical AD' and a revisiting of tau pathological staging.
Collapse
Affiliation(s)
- Jacob W Vogel
- Montreal Neurological Institute, McGill University, Montréal, Quebec, Canada.
| | - Alexandra L Young
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Neil P Oxtoby
- Centre for Medical Image Computing, University College London, London, UK
- Department of Computer Science, University College London, London, UK
| | - Ruben Smith
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | | | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Leon M Aksman
- Centre for Medical Image Computing, University College London, London, UK
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Michel J Grothe
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/Consejo Superior de Investigaciones Científicas/Universidad de Sevilla, Seville, Spain
| | | | | | | | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Daniel C Alexander
- Centre for Medical Image Computing, University College London, London, UK
- Department of Computer Science, University College London, London, UK
| | - Chul Hyoung Lyoo
- Departments of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Alan C Evans
- Montreal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
| |
Collapse
|
45
|
Terada T, Therriault J, Kang MSP, Savard M, Pascoal TA, Lussier F, Tissot C, Wang YT, Benedet A, Matsudaira T, Bunai T, Obi T, Tsukada H, Ouchi Y, Rosa-Neto P. Mitochondrial complex I abnormalities is associated with tau and clinical symptoms in mild Alzheimer's disease. Mol Neurodegener 2021; 16:28. [PMID: 33902654 PMCID: PMC8074456 DOI: 10.1186/s13024-021-00448-1] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 03/29/2021] [Indexed: 01/01/2023] Open
Abstract
Background Mitochondrial electron transport chain abnormalities have been reported in postmortem pathological specimens of Alzheimer’s disease (AD). However, it remains unclear how amyloid and tau are associated with mitochondrial dysfunction in vivo. The purpose of this study is to assess the local relationships between mitochondrial dysfunction and AD pathophysiology in mild AD using the novel mitochondrial complex I PET imaging agent [18F]BCPP-EF. Methods Thirty-two amyloid and tau positive mild stage AD dementia patients (mean age ± SD: 71.1 ± 8.3 years) underwent a series of PET measurements with [18F]BCPP-EF mitochondrial function, [11C]PBB3 for tau deposition, and [11C] PiB for amyloid deposition. Age-matched normal control subjects were also recruited. Inter and intrasubject comparisons of levels of mitochondrial complex I activity, amyloid and tau deposition were performed. Results The [18F]BCPP-EF uptake was significantly lower in the medial temporal area, highlighting the importance of the mitochondrial involvement in AD pathology. [11C]PBB3 uptake was greater in the temporo-parietal regions in AD. Region of interest analysis in the Braak stage I-II region showed significant negative correlation between [18F]BCPP-EF SUVR and [11C]PBB3 BPND (R = 0.2679, p = 0.04), but not [11C] PiB SUVR. Conclusions Our results indicated that mitochondrial complex I is closely associated with tau load evaluated by [11C]PBB3, which might suffer in the presence of its off-target binding. The absence of association between mitochondrial complex I dysfunction with amyloid load suggests that mitochondrial dysfunction in the trans-entorhinal and entorhinal region is a reflection of neuronal injury occurring in the brain of mild AD. Supplementary Information The online version contains supplementary material available at 10.1186/s13024-021-00448-1.
Collapse
Affiliation(s)
- Tatsuhiro Terada
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, 6875 Boulevard LaSalle, Montreal, H4H 1R3, Canada.,Department of Biofunctional Imaging, Preeminent Medical Photonics Education & Research Center, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu, 431-3192, Japan.,Department of Neurology, Shizuoka Institute of Epilepsy and Neurological Disorders, 886 Urushiyama, Aoi-ku, Shizuoka, 420-8688, Japan
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, 6875 Boulevard LaSalle, Montreal, H4H 1R3, Canada
| | - Min Su Peter Kang
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, 6875 Boulevard LaSalle, Montreal, H4H 1R3, Canada
| | - Melissa Savard
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, 6875 Boulevard LaSalle, Montreal, H4H 1R3, Canada
| | - Tharick Ali Pascoal
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, 6875 Boulevard LaSalle, Montreal, H4H 1R3, Canada
| | - Firoza Lussier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, 6875 Boulevard LaSalle, Montreal, H4H 1R3, Canada
| | - Cecile Tissot
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, 6875 Boulevard LaSalle, Montreal, H4H 1R3, Canada
| | - Yi-Ting Wang
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, 6875 Boulevard LaSalle, Montreal, H4H 1R3, Canada
| | - Andrea Benedet
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, 6875 Boulevard LaSalle, Montreal, H4H 1R3, Canada
| | - Takashi Matsudaira
- Department of Biofunctional Imaging, Preeminent Medical Photonics Education & Research Center, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu, 431-3192, Japan.,Department of Neurology, Shizuoka Institute of Epilepsy and Neurological Disorders, 886 Urushiyama, Aoi-ku, Shizuoka, 420-8688, Japan
| | - Tomoyasu Bunai
- Department of Biofunctional Imaging, Preeminent Medical Photonics Education & Research Center, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu, 431-3192, Japan
| | - Tomokazu Obi
- Department of Neurology, Shizuoka Institute of Epilepsy and Neurological Disorders, 886 Urushiyama, Aoi-ku, Shizuoka, 420-8688, Japan
| | - Hideo Tsukada
- Central Research Laboratory, Hamamatsu Photonics KK, 5000 Hirakuchi, Hamakita-ku, Hamamatsu, 434-0041, Japan
| | - Yasuomi Ouchi
- Department of Biofunctional Imaging, Preeminent Medical Photonics Education & Research Center, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu, 431-3192, Japan. .,Hamamatsu PET Imaging Center, Hamamatsu Medical Photonics Foundation, 5000 Hirakuchi, Hamakita-ku, Hamamatsu, 434-0041, Japan.
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, 6875 Boulevard LaSalle, Montreal, H4H 1R3, Canada.
| |
Collapse
|
46
|
Clinical validity of increased cortical binding of tau ligands of the THK family and PBB3 on PET as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework. Eur J Nucl Med Mol Imaging 2021; 48:2086-2096. [PMID: 33723628 PMCID: PMC8175292 DOI: 10.1007/s00259-021-05277-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 02/21/2021] [Indexed: 12/28/2022]
Abstract
PURPOSE The research community has focused on defining reliable biomarkers for the early detection of the pathological hallmarks of Alzheimer's disease (AD). In 2017, the Geneva AD Biomarker Roadmap initiative adapted the framework for the systematic validation of oncological biomarkers to AD, with the aim to accelerate their development and implementation in clinical practice. The aim of this work was to assess the validation status of tau PET ligands of the THK family and PBB3 as imaging biomarkers for AD, based on the Biomarker Roadmap methodology. METHODS A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of clinical validity of tau PET ligands of the THK family and PBB3 was assessed based on the 5-phase development framework before the meeting and discussed during the workshop. RESULTS PET radioligands of the THK family discriminate well between healthy controls and patients with AD dementia (phase 2; partly achieved) and recent evidence suggests an accurate diagnostic accuracy at the mild cognitive impairment (MCI) stage of the disease (phase 3; partly achieved). The phases 2 and 3 were considered not achieved for PBB3 since no evidence exists about the ligand's diagnostic accuracy. Preliminary evidence exists about the secondary aims of each phase for all ligands. CONCLUSION Much work remains for completing the aims of phases 2 and 3 and replicating the available evidence. However, it is unlikely that the validation process for these tracers will be completed, given the presence of off-target binding and the development of second-generation tracers with improved binding and pharmacokinetic properties.
Collapse
|
47
|
Sanchez JS, Becker JA, Jacobs HIL, Hanseeuw BJ, Jiang S, Schultz AP, Properzi MJ, Katz SR, Beiser A, Satizabal CL, O'Donnell A, DeCarli C, Killiany R, El Fakhri G, Normandin MD, Gómez-Isla T, Quiroz YT, Rentz DM, Sperling RA, Seshadri S, Augustinack J, Price JC, Johnson KA. The cortical origin and initial spread of medial temporal tauopathy in Alzheimer's disease assessed with positron emission tomography. Sci Transl Med 2021; 13:eabc0655. [PMID: 33472953 PMCID: PMC7978042 DOI: 10.1126/scitranslmed.abc0655] [Citation(s) in RCA: 101] [Impact Index Per Article: 33.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 09/10/2020] [Indexed: 12/15/2022]
Abstract
Advances in molecular positron emission tomography (PET) have enabled anatomic tracking of brain pathology in longitudinal studies of normal aging and dementia, including assessment of the central model of Alzheimer's disease (AD) pathogenesis, according to which TAU pathology begins focally but expands catastrophically under the influence of amyloid-β (Aβ) pathology to mediate neurodegeneration and cognitive decline. Initial TAU deposition occurs many years before Aβ in a specific area of the medial temporal lobe. Building on recent work that enabled focus of molecular PET measurements on specific TAU-vulnerable convolutional temporal lobe anatomy, we applied an automated anatomic sampling method to quantify TAU PET signal in 443 adult participants from several observational studies of aging and AD, spanning a wide range of ages, Aβ burdens, and degrees of clinical impairment. We detected initial cortical emergence of tauopathy near the rhinal sulcus in clinically normal people and, in a subset with longitudinal 2-year follow-up data (n = 104), tracked Aβ-associated spread of TAU from this site first to nearby neocortex of the temporal lobe and then to extratemporal regions. Greater rate of TAU spread was associated with baseline measures of both global Aβ burden and medial temporal lobe TAU. These findings are consistent with clinicopathological correlation studies of Alzheimer's tauopathy and enable precise tracking of AD-related TAU progression for natural history studies and prevention therapeutic trials.
Collapse
Affiliation(s)
- Justin S Sanchez
- Massachusetts General Hospital, Boston, MA 02114, USA.
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - J Alex Becker
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Heidi I L Jacobs
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
- School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, 6211 LK, Netherlands
| | - Bernard J Hanseeuw
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
- Université Catholique de Louvain, Brussels B-1348, Belgium
| | - Shu Jiang
- Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Aaron P Schultz
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Michael J Properzi
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Samantha R Katz
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Alexa Beiser
- Boston University School of Medicine, Boston, MA 02118, USA
- Boston University School of Public Health, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA 01702, USA
| | - Claudia L Satizabal
- Boston University School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA 01702, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 78229, USA
| | - Adrienne O'Donnell
- Boston University School of Public Health, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA 01702, USA
| | | | - Ron Killiany
- Boston University School of Medicine, Boston, MA 02118, USA
- Boston University School of Public Health, Boston, MA 02118, USA
| | - Georges El Fakhri
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Marc D Normandin
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Teresa Gómez-Isla
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Yakeel T Quiroz
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Grupo de Neurociencias, Universidad de Antioquia, Antioquia 050010, Colombia
| | - Dorene M Rentz
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Reisa A Sperling
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Sudha Seshadri
- Boston University School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA 01702, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 78229, USA
| | - Jean Augustinack
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Julie C Price
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Keith A Johnson
- Massachusetts General Hospital, Boston, MA 02114, USA.
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
- Brigham and Women's Hospital, Boston, MA 02115, USA
| |
Collapse
|
48
|
Schäfer A, Mormino EC, Kuhl E. Network Diffusion Modeling Explains Longitudinal Tau PET Data. Front Neurosci 2020; 14:566876. [PMID: 33424532 PMCID: PMC7785976 DOI: 10.3389/fnins.2020.566876] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 12/02/2020] [Indexed: 12/27/2022] Open
Abstract
Alzheimer's disease is associated with the cerebral accumulation of neurofibrillary tangles of hyperphosphorylated tau protein. The progressive occurrence of tau aggregates in different brain regions is closely related to neurodegeneration and cognitive impairment. However, our current understanding of tau propagation relies almost exclusively on postmortem histopathology, and the precise propagation dynamics of misfolded tau in the living brain remain poorly understood. Here we combine longitudinal positron emission tomography and dynamic network modeling to test the hypothesis that misfolded tau propagates preferably along neuronal connections. We follow 46 subjects for three or four annual positron emission tomography scans and compare their pathological tau profiles against brain network models of intracellular and extracellular spreading. For each subject, we identify a personalized set of model parameters that characterizes the individual progression of pathological tau. Across all subjects, the mean protein production rate was 0.21 ± 0.15 and the intracellular diffusion coefficient was 0.34 ± 0.43. Our network diffusion model can serve as a tool to detect non-clinical symptoms at an earlier stage and make informed predictions about the timeline of neurodegeneration on an individual personalized basis.
Collapse
Affiliation(s)
- Amelie Schäfer
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
| | - Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA, United States
| | - Ellen Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
| |
Collapse
|
49
|
Soleimani-Meigooni DN, Iaccarino L, La Joie R, Baker S, Bourakova V, Boxer AL, Edwards L, Eser R, Gorno-Tempini ML, Jagust WJ, Janabi M, Kramer JH, Lesman-Segev OH, Mellinger T, Miller BL, Pham J, Rosen HJ, Spina S, Seeley WW, Strom A, Grinberg LT, Rabinovici GD. 18F-flortaucipir PET to autopsy comparisons in Alzheimer's disease and other neurodegenerative diseases. Brain 2020; 143:3477-3494. [PMID: 33141172 PMCID: PMC7719031 DOI: 10.1093/brain/awaa276] [Citation(s) in RCA: 92] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 07/06/2020] [Accepted: 07/08/2020] [Indexed: 12/21/2022] Open
Abstract
Few studies have evaluated the relationship between in vivo18F-flortaucipir PET and post-mortem pathology. We sought to compare antemortem 18F-flortaucipir PET to neuropathology in a consecutive series of patients with a broad spectrum of neurodegenerative conditions. Twenty patients were included [mean age at PET 61 years (range 34-76); eight female; median PET-to-autopsy interval of 30 months (range 4-59 months)]. Eight patients had primary Alzheimer's disease pathology, nine had non-Alzheimer tauopathies (progressive supranuclear palsy, corticobasal degeneration, argyrophilic grain disease, and frontotemporal lobar degeneration with MAPT mutations), and three had non-tau frontotemporal lobar degeneration. Using an inferior cerebellar grey matter reference, 80-100-min 18F-flortaucipir PET standardized uptake value ratio (SUVR) images were created. Mean SUVRs were calculated for progressive supranuclear palsy, corticobasal degeneration, and neurofibrillary tangle Braak stage regions of interest, and these values were compared to SUVRs derived from young, non-autopsy, cognitively normal controls used as a standard for tau negativity. W-score maps were generated to highlight areas of increased tracer retention compared to cognitively normal controls, adjusting for age as a covariate. Autopsies were performed blinded to PET results. There was excellent correspondence between areas of 18F-flortaucipir retention, on both SUVR images and W-score maps, and neurofibrillary tangle distribution in patients with primary Alzheimer's disease neuropathology. Patients with non-Alzheimer tauopathies and non-tau frontotemporal lobar degeneration showed a range of tracer retention that was less than Alzheimer's disease, though higher than age-matched, cognitively normal controls. Overall, binding across both tau-positive and tau-negative non-Alzheimer disorders did not reliably correspond with post-mortem tau pathology. 18F-flortaucipir SUVRs in subcortical regions were higher in autopsy-confirmed progressive supranuclear palsy and corticobasal degeneration than in controls, but were similar to values measured in Alzheimer's disease and tau-negative neurodegenerative pathologies. Quantification of 18F-flortaucipir SUVR images at Braak stage regions of interest reliably detected advanced Alzheimer's (Braak VI) pathology. However, patients with earlier Braak stages (Braak I-IV) did not show elevated tracer uptake in these regions compared to young, tau-negative controls. In summary, PET-to-autopsy comparisons confirm that 18F-flortaucipir PET is a reliable biomarker of advanced Braak tau pathology in Alzheimer's disease. The tracer cannot reliably differentiate non-Alzheimer tauopathies and may not detect early Braak stages of neurofibrillary tangle pathology.
Collapse
Affiliation(s)
- David N Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Suzanne Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Viktoriya Bourakova
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Rana Eser
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | | | - William J Jagust
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Mustafa Janabi
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Orit H Lesman-Segev
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Taylor Mellinger
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Julie Pham
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Salvatore Spina
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - William W Seeley
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Amelia Strom
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Lea T Grinberg
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| |
Collapse
|
50
|
Clinical Evaluation of 18F-PI-2620 as a Potent PET Radiotracer Imaging Tau Protein in Alzheimer Disease and Other Neurodegenerative Diseases Compared With 18F-THK-5351. Clin Nucl Med 2020; 45:841-847. [PMID: 32910050 DOI: 10.1097/rlu.0000000000003261] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE PET is a useful tool for detecting the presence and extent of brain tau accumulation. However, most first-generation tau PET tracers are limited for high off-target binding and detection of tau in non-Alzheimer disease (AD). This study evaluated potential clinical applications of F-PI-2620 as a novel PET tracer with a high binding affinity for tau deposition in AD and non-AD tauopathies. METHODS Twenty-six participants diagnosed with either mild cognitive impairment, probable AD, frontotemporal dementia, or parkinsonism, as well as healthy controls underwent a 60- to 90-minute brain PET scan after 7 mci (259 MBq) injection of F-PI-2620. Some participants had previous PET scans using F-THK-5351 or F-FP-CIT for dopamine transporter imaging. RESULTS All participants showed no increase in off-target binding in basal ganglia on F-PI-2620 PET images, as noted for first-generation tau tracers. Aβ+ mild cognitive impairment or AD patients showed diverse cortical F-PI-2620 uptake in frontotemporoparietal cortex that correlated with Mini-Mental Status Examination (ρ = -0.692, P = 0.013). Aβ+ Parkinson disease with dementia and (Aβ unknown) primary progressive aphasia patients also showed increased F-PI-2620 uptakes in the frontotemporoparietal cortex. Patients with parkinsonism showed increased uptakes in the pallidum compared with Aβ- healthy controls (left: 1.41 ± 0.14 vs 1.04 ± 0.13, P = 0.014; right: 1.18 ± 0.16 vs 0.95 ± 0.07, P = 0.014). CONCLUSIONS F-PI-2620 PET might be a sensitive tool to detect cortical tau deposits in patients with Aβ+ AD and Aβ+ non-AD tauopathies. Furthermore, this study showed that "off-target" binding in the basal ganglia does not affect F-PI-2620.
Collapse
|