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Soleimani-Meigooni DN, Smith R, Provost K, Lesman-Segev OH, Allen IE, Chen MK, Cho H, Edwards L, Janelidze S, La Joie R, Mundada N, Ossenkoppele R, Stomrud E, Strandberg O, Strom A, Boxer AL, Dage JL, Gorno-Tempini ML, Kramer JH, Miller BL, Rojas JC, Rosen HJ, Lyoo CH, Hansson O, Rabinovici GD. Head-to-Head Comparison of Tau and Amyloid Positron Emission Tomography Visual Reads for Differential Diagnosis of Neurodegenerative Disorders: An International, Multicenter Study. Ann Neurol 2024. [PMID: 38888212 DOI: 10.1002/ana.27008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 05/29/2024] [Accepted: 05/29/2024] [Indexed: 06/20/2024]
Abstract
OBJECTIVE We compared the accuracy of amyloid and [18F]Flortaucipir (FTP) tau positron emission tomography (PET) visual reads for distinguishing patients with mild cognitive impairment (MCI) or dementia with fluid biomarker support of Alzheimer's disease (AD). METHODS Participants with FTP-PET, amyloid-PET, and diagnosis of dementia-AD (n = 102), MCI-AD (n = 41), non-AD diseases (n = 76), and controls (n = 20) were included. AD status was determined independent of PET by cerebrospinal fluid or plasma biomarkers. The mean age was 66.9 years, and 44.8% were women. Three readers interpreted scans blindly and independently. Amyloid-PET was classified as positive/negative using tracer-specific criteria. FTP-PET was classified as positive with medial temporal lobe (MTL) binding as the minimum uptake indicating AD tau (tau-MTL+), positive with posterolateral temporal or extratemporal cortical binding in an AD-like pattern (tau-CTX+), or negative. The majority of scan interpretations were used to calculate diagnostic accuracy of visual reads in detecting MCI/dementia with fluid biomarker support for AD (MCI/dementia-AD). RESULTS Sensitivity of amyloid-PET for MCI/dementia-AD was 95.8% (95% confidence interval 91.1-98.4%), which was comparable to tau-CTX+ 92.3% (86.7-96.1%, p = 0.67) and tau-MTL+ 97.2% (93.0-99.2%, p = 0.27). Specificity of amyloid-PET for biomarker-negative healthy and disease controls was 84.4% (75.5-91.0%), which was like tau-CTX+ 88.5% (80.4-94.1%, p = 0.34), and trended toward being higher than tau-MTL+ 75.0% (65.1-83.3%, p = 0.08). Tau-CTX+ had higher specificity than tau-MTL+ (p = 0.0002), but sensitivity was lower (p = 0.02), driven by decreased sensitivity for MCI-AD (80.5% [65.1-91.2] vs. 95.1% [83.5-99.4], p = 0.03). INTERPRETATION Amyloid- and tau-PET visual reads have similar sensitivity/specificity for detecting AD in cognitively impaired patients. Visual tau-PET interpretations requiring cortical binding outside MTL increase specificity, but lower sensitivity for MCI-AD. ANN NEUROL 2024.
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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
| | - Ruben Smith
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Karine Provost
- Department of Nuclear Medicine, University of Montreal Hospital Center, Montréal, Canada
| | - Orit H Lesman-Segev
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Isabel Elaine Allen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Miranda K Chen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Clinical Psychology, San Diego State University & University of California, San Diego, CA, USA
| | | | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Nidhi Mundada
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands
| | - Erik Stomrud
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Amelia Strom
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Health Sciences and Technology, Harvard & Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Jeffrey L Dage
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Joel H Kramer
- 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
| | - Julio C Rojas
- 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
| | - Chul H Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
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Tetzloff KA, Martin PR, Duffy JR, Utianski RL, Clark HM, Botha H, Machulda MM, Thu Pham NT, Schwarz CG, Senjem ML, Jack CR, Lowe VJ, Josephs KA, Whitwell JL. Longitudinal flortaucipir, metabolism and volume differ between phonetic and prosodic speech apraxia. Brain 2024; 147:1696-1709. [PMID: 38217867 PMCID: PMC11068100 DOI: 10.1093/brain/awae016] [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: 03/13/2023] [Revised: 11/29/2023] [Accepted: 12/30/2023] [Indexed: 01/15/2024] Open
Abstract
Progressive apraxia of speech (PAOS) is a neurodegenerative motor-speech disorder that most commonly arises from a four-repeat tauopathy. Recent studies have established that progressive apraxia of speech is not a homogenous disease but rather there are distinct subtypes: the phonetic subtype is characterized by distorted sound substitutions, the prosodic subtype by slow and segmented speech and the mixed subtype by a combination of both but lack of predominance of either. There is some evidence that cross-sectional patterns of neurodegeneration differ across subtypes, although it is unknown whether longitudinal patterns of neurodegeneration differ. We examined longitudinal patterns of atrophy on MRI, hypometabolism on 18F-fluorodeoxyglucose-PET and tau uptake on flortaucipir-PET in a large cohort of subjects with PAOS that had been followed for many years. Ninety-one subjects with PAOS (51 phonetic, 40 prosodic) were recruited by the Neurodegenerative Research Group. Of these, 54 (27 phonetic, 27 prosodic) returned for annual follow-up, with up to seven longitudinal visits (total visits analysed = 217). Volumes, metabolism and flortaucipir uptake were measured for subcortical and cortical regions, for all scans. Bayesian hierarchical models were used to model longitudinal change across imaging modalities with PAOS subtypes being compared at baseline, 4 years from baseline, and in terms of rates of change. The phonetic group showed smaller volumes and worse metabolism in Broca's area and the striatum at baseline and after 4 years, and faster rates of change in these regions, compared with the prosodic group. There was also evidence of faster spread of hypometabolism and flortaucipir uptake into the temporal and parietal lobes in the phonetic group. In contrast, the prosodic group showed smaller cerebellar dentate, midbrain, substantia nigra and thalamus volumes at baseline and after 4 years, as well as faster rates of atrophy, than the phonetic group. Greater hypometabolism and flortaucipir uptake were also observed in the cerebellar dentate and substantia nigra in the prosodic group. Mixed findings were observed in the supplementary motor area and precentral cortex, with no clear differences observed across phonetic and prosodic groups. These findings support different patterns of disease spread in PAOS subtypes, with corticostriatal patterns in the phonetic subtype and brainstem and thalamic patterns in the prosodic subtype, providing insight into the pathophysiology and heterogeneity of PAOS.
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Affiliation(s)
| | - Peter R Martin
- Department of Quantitative Health Sciences (Biostatistics), Mayo Clinic, Rochester, MN 55905, USA
| | - Joseph R Duffy
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Rene L Utianski
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Heather M Clark
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychiatry (Neuropsychology), Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
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Gérard T, Colmant L, Malotaux V, Salman Y, Huyghe L, Quenon L, Dricot L, Ivanoiu A, Lhommel R, Hanseeuw B. The spatial extent of tauopathy on [ 18F]MK-6240 tau PET shows stronger association with cognitive performances than the standard uptake value ratio in Alzheimer's disease. Eur J Nucl Med Mol Imaging 2024; 51:1662-1674. [PMID: 38228971 PMCID: PMC11043108 DOI: 10.1007/s00259-024-06603-2] [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: 09/11/2023] [Accepted: 01/04/2024] [Indexed: 01/18/2024]
Abstract
PURPOSE [18F]MK-6240, a second-generation tau PET tracer, is increasingly used for the detection and the quantification of in vivo cerebral tauopathy in Alzheimer's disease (AD). Given that neurological symptoms are better explained by the topography rather than by the nature of brain lesions, our study aimed to evaluate whether cognitive impairment would be more closely associated with the spatial extent than with the intensity of tau-PET signal, as measured by the standard uptake value ratio (SUVr). METHODS [18F]MK6240 tau-PET data from 82 participants in the AD spectrum were quantified in three different brain regions (Braak ≤ 2, Braak ≤ 4, and Braak ≤ 6) using SUVr and the extent of tauopathy (EOT, percentage of voxels with SUVr ≥ 1.3). PET data were first compared between diagnostic categories, and ROC curves were computed to evaluate sensitivity and specificity. PET data were then correlated to cognitive performances and cerebrospinal fluid (CSF) tau values. RESULTS The EOT in the Braak ≤ 2 region provided the highest diagnostic accuracies, distinguishing between amyloid-negative and positive clinically unimpaired individuals (threshold = 9%, sensitivity = 79%, specificity = 82%) as well as between prodromal AD and preclinical AD (threshold = 38%, sensitivity = 81%, specificity = 93%). The EOT better correlated with cognition than SUVr (∆R2 + 0.08-0.09) with the best correlation observed for EOT in the Braak ≤ 4 region (R2 = 0.64). Cognitive performances were more closely associated with PET metrics than with CSF values. CONCLUSIONS Quantifying [18F]MK-6240 tau PET in terms of EOT rather than SUVr significantly increases the correlation with cognitive performances. Quantification in the mesiotemporal lobe is the most useful to diagnose preclinical AD or prodromal AD.
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Affiliation(s)
- Thomas Gérard
- Nuclear Medicine Department, Cliniques Universitaires Saint Luc, Brussels, Belgium.
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium.
| | - Lise Colmant
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
- Neurology Department, Cliniques Universitaires Saint Luc, Brussels, Belgium
| | - Vincent Malotaux
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
| | - Yasmine Salman
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
| | - Lara Huyghe
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
| | - Lisa Quenon
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
- Neurology Department, Cliniques Universitaires Saint Luc, Brussels, Belgium
| | - Laurence Dricot
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
| | - Adrian Ivanoiu
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
- Neurology Department, Cliniques Universitaires Saint Luc, Brussels, Belgium
| | - Renaud Lhommel
- Nuclear Medicine Department, Cliniques Universitaires Saint Luc, Brussels, Belgium
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
| | - Bernard Hanseeuw
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
- Neurology Department, Cliniques Universitaires Saint Luc, Brussels, Belgium
- WELBIO Department, WEL Research Institute, Avenue Pasteur, 6, 1300, Wavre, Belgium
- Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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Mathoux G, Boccalini C, Lathuliere A, Scheffler M, Frisoni GB, Garibotto V. Neuroimaging-guided diagnosis of possible FTLD-FUS pathology: a case report. EJNMMI Res 2024; 14:35. [PMID: 38573556 PMCID: PMC10994884 DOI: 10.1186/s13550-024-01102-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 03/27/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND This case report presents a patient with progressive memory loss and choreiform movements. CASE PRESENTATION Neuropsychological tests indicated multi-domain amnestic mild cognitive impairment (aMCI), and neurological examination revealed asymmetrical involuntary hyperkinetic movements. Imaging studies showed severe left-sided atrophy and hypometabolism in the left frontal and temporoparietal cortex. [18F]Flortaucipir PET exhibited moderately increased tracer uptake in hypometabolic areas. The diagnosis initially considered Alzheimer's disease (AD), frontotemporal degeneration (FTD), and corticobasal degeneration (CBD), cerebral hemiatrophy syndrome, but imaging and cerebrospinal fluid analysis excluded AD and suggested fused-in-sarcoma-associated FTD (FTLD-FUS), a subtype of the behavioural variant of FTD. CONCLUSIONS Our case highlights that despite the lack of specific FUS biomarkers the combination of clinical features and neuroimaging biomarkers can guide choosing the most likely differential diagnosis in a complex neurological case. Imaging in particular allowed an accurate measure of the topography and severity of neurodegeneration and the exclusion of AD-related pathology.
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Affiliation(s)
- Gregory Mathoux
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
| | - Cecilia Boccalini
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
| | - Aurelien Lathuliere
- Department of Rehabilitation and Geriatrics, Memory Clinic, Geneva University and University Hospitals, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Giovanni B Frisoni
- Department of Rehabilitation and Geriatrics, Memory Clinic, Geneva University and University Hospitals, Geneva, Switzerland
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland.
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland.
- CIBM Center for Biomedical Imaging, Geneva, Switzerland.
- Neuroimaging and Innovative Molecular Traces Lab, Hôpitaux Universitaires de Genève (HUG) & University of Genève, Rue Gabrielle-Perret-Gentil 4, Genève 14, CH-1205, Switzerland.
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Costoya-Sánchez A, Moscoso A, Sobrino T, Ruibal Á, Grothe MJ, Schöll M, Silva-Rodríguez J, Aguiar P. Partial volume correction in longitudinal tau PET studies: is it really needed? Neuroimage 2024; 289:120537. [PMID: 38367651 DOI: 10.1016/j.neuroimage.2024.120537] [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: 12/12/2023] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 02/19/2024] Open
Abstract
BACKGROUND [18F]flortaucipir (FTP) tau PET quantification is known to be affected by non-specific binding in off-target regions. Although partial volume correction (PVC) techniques partially account for this effect, their inclusion may also introduce noise and variability into the quantification process. While the impact of these effects has been studied in cross-sectional designs, the benefits and drawbacks of PVC on longitudinal FTP studies is still under scrutiny. The aim of this work was to study the performance of the most common PVC techniques for longitudinal FTP imaging. METHODS A cohort of 247 individuals from the Alzheimer's Disease Neuroimaging Initiative with concurrent baseline FTP-PET, amyloid-beta (Aβ) PET and structural MRI, as well as with follow-up FTP-PET and MRI were included in the study. FTP-PET scans were corrected for partial volume effects using Meltzer's, a simple and popular analytical PVC, and both the region-based voxel-wise (RBV) and the iterative Yang (iY) corrections. FTP SUVR values and their longitudinal rates of change were calculated for regions of interest (ROI) corresponding to Braak Areas I-VI, for a temporal meta-ROI and for regions typically displaying off-target FTP binding (caudate, putamen, pallidum, thalamus, choroid plexus, hemispheric white matter, cerebellar white matter, and cerebrospinal fluid). The longitudinal correlation between binding in off-target and target ROIs was analysed for the different PVCs. Additionally, group differences in longitudinal FTP SUVR rates of change between Aβ-negative (A-) and Aβ-positive (A+), and between cognitively unimpaired (CU) and cognitively impaired (CI) individuals, were studied. Finally, we compared the ability of different partial-volume-corrected baseline FTP SUVRs to predict longitudinal brain atrophy and cognitive decline. RESULTS Among off-target ROIs, hemispheric white matter showed the highest correlation with longitudinal FTP SUVR rates from cortical target ROIs (R2=0.28-0.82), with CSF coming in second (R2=0.28-0.42). Application of voxel-wise PVC techniques minimized this correlation, with RBV performing best (R2=0.00-0.07 for hemispheric white matter). PVC also increased group differences between CU and CI individuals in FTP SUVR rates of change across all target regions, with RBV again performing best (No PVC: Cohen's d = 0.26-0.66; RBV: Cohen's d = 0.43-0.74). These improvements were not observed for differentiating A- from A+ groups. Additionally, voxel-wise PVC techniques strengthened the correlation between baseline FTP SUVR and longitudinal grey matter atrophy and cognitive decline. CONCLUSION Quantification of longitudinal FTP SUVR rates of change is affected by signal from off-target regions, especially the hemispheric white matter and the CSF. Voxel-wise PVC techniques significantly reduce this effect. PVC provided a significant but modest benefit for tasks involving the measurement of group-level longitudinal differences. These findings are particularly relevant for the estimations of sample sizes and analysis methodologies of longitudinal group studies.
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Affiliation(s)
- Alejandro Costoya-Sánchez
- Molecular Imaging Group. Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Av. Barcelona SN, 15782, Santiago de Compostela, Galicia, Spain; Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Travesía da Choupana s/n, Santiago de Compostela, Spain
| | - Alexis Moscoso
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden; Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden
| | - Tomás Sobrino
- NeuroAging Laboratory Group (NEURAL), Clinical Neurosciences Research Laboratories (LINC), Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
| | - Álvaro Ruibal
- Molecular Imaging Group. Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Av. Barcelona SN, 15782, Santiago de Compostela, Galicia, Spain; Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Travesía da Choupana s/n, Santiago de Compostela, Spain
| | - Michel J Grothe
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden; Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain; Reina Sofía Alzheimer's Centre, CIEN Foundation, ISCIII, Madrid, 28031, Spain
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden; Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden; Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom
| | - Jesús Silva-Rodríguez
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain; Reina Sofía Alzheimer's Centre, CIEN Foundation, ISCIII, Madrid, 28031, Spain.
| | - Pablo Aguiar
- Molecular Imaging Group. Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Av. Barcelona SN, 15782, Santiago de Compostela, Galicia, Spain; Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Travesía da Choupana s/n, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain.
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Lu J, Ge J, Yu H, Zhao G, Chen X. Colocalization of Increased Midbrain Signals in Neuroinflammation and Tau PET Imaging Suggests the Diagnosis of Progressive Supranuclear Palsy. Clin Nucl Med 2024; 49:346-347. [PMID: 38271226 DOI: 10.1097/rlu.0000000000005062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2024]
Abstract
ABSTRACT Clinical overlap with multiple other neurological diseases makes the diagnosis of autoimmune encephalitis challenging; consequently, a broad range of neurological diseases are misdiagnosed as autoimmune encephalitis. A 58-year-old man presented with abnormal behavior, irritability for 3 years, oculomotor disturbance, unsteady walking, and dysphagia and was suspected as having anti-dipeptidyl-peptidase-like protein 6 (DPPX) encephalitis as the anti-DPPX antibody was positive in the serum. However, the therapeutic effect of immunotherapy was unsatisfactory. Subsequently, colocalization of increased midbrain signals was observed in neuroinflammation PET using [ 18 F]DPA-714 and in tau PET using [ 18 F]florzolotau, suggesting the diagnosis of progressive supranuclear palsy.
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Su Y, Protas H, Luo J, Chen K, Alosco ML, Adler CH, Balcer LJ, Bernick C, Au R, Banks SJ, Barr WB, Coleman MJ, Dodick DW, Katz DI, Marek KL, McClean MD, McKee AC, Mez J, Daneshvar DH, Palmisano JN, Peskind ER, Turner RW, Wethe JV, Rabinovici G, Johnson K, Tripodis Y, Cummings JL, Shenton ME, Stern RA, Reiman EM. Flortaucipir tau PET findings from former professional and college American football players in the DIAGNOSE CTE research project. Alzheimers Dement 2024; 20:1827-1838. [PMID: 38134231 PMCID: PMC10984430 DOI: 10.1002/alz.13602] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 10/27/2023] [Accepted: 11/20/2023] [Indexed: 12/24/2023]
Abstract
INTRODUCTION Tau is a key pathology in chronic traumatic encephalopathy (CTE). Here, we report our findings in tau positron emission tomography (PET) measurements from the DIAGNOSE CTE Research Project. METHOD We compare flortaucipir PET measures from 104 former professional players (PRO), 58 former college football players (COL), and 56 same-age men without exposure to repetitive head impacts (RHI) or traumatic brain injury (unexposed [UE]); characterize their associations with RHI exposure; and compare players who did or did not meet diagnostic criteria for traumatic encephalopathy syndrome (TES). RESULTS Significantly elevated flortaucipir uptake was observed in former football players (PRO+COL) in prespecified regions (p < 0.05). Association between regional flortaucipir uptake and estimated cumulative head impact exposure was only observed in the superior frontal region in former players over 60 years old. Flortaucipir PET was not able to differentiate TES groups. DISCUSSION Additional studies are needed to further understand tau pathology in CTE and other individuals with a history of RHI.
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Affiliation(s)
- Yi Su
- Banner Alzheimer's Institute and Arizona Alzheimer's ConsortiumPhoenixArizonaUSA
| | - Hillary Protas
- Banner Alzheimer's Institute and Arizona Alzheimer's ConsortiumPhoenixArizonaUSA
| | - Ji Luo
- Banner Alzheimer's Institute and Arizona Alzheimer's ConsortiumPhoenixArizonaUSA
| | - Kewei Chen
- Banner Alzheimer's Institute and Arizona Alzheimer's ConsortiumPhoenixArizonaUSA
| | - Michael L. Alosco
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Charles H. Adler
- Department of NeurologyMayo Clinic College of Medicine, Mayo Clinic ArizonaScottsdaleArizonaUSA
| | - Laura J. Balcer
- Departments of NeurologyNYU Grossman School of MedicineNew YorkNew YorkUSA
- Department of Population Health and OphthalmologyNYU Grossman School of MedicineNew YorkNew YorkUSA
| | - Charles Bernick
- Cleveland Clinic Lou Ruvo Center for Brain HealthLas VegasNevadaUSA
- Department of NeurologyUniversity of WashingtonSeattleWashingtonUSA
| | - Rhoda Au
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Framingham Heart StudyFraminghamMassachusettsUSA
- Slone Epidemiology Center; Departments of Anatomy & Neurobiology, Neurology, and MedicineDepartment of EpidemiologyBoston University Chobanian & Avedisian School of Medicine; Boston University School of Public HealthBostonMassachusettsUSA
| | - Sarah J. Banks
- Departments of Neuroscience and PsychiatryUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - William B. Barr
- Departments of NeurologyNYU Grossman School of MedicineNew YorkNew YorkUSA
| | - Michael J. Coleman
- Departments of Psychiatry and RadiologyPsychiatry Neuroimaging LaboratoryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - David W. Dodick
- Department of NeurologyMayo Clinic College of Medicine, Mayo Clinic ArizonaScottsdaleArizonaUSA
| | - Douglas I. Katz
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Encompass Health Braintree Rehabilitation HospitalBraintreeMassachusettsUSA
| | - Kenneth L. Marek
- Institute for Neurodegenerative Disorders, Invicro, LLCNew HavenConnecticutUSA
| | - Michael D. McClean
- Department of Environmental HealthBoston University School of Public HealthBostonMassachusettsUSA
| | - Ann C. McKee
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- VA Boston Healthcare SystemBostonMassachusettsUSA
| | - Jesse Mez
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Framingham Heart StudyFraminghamMassachusettsUSA
| | - Daniel H. Daneshvar
- Department of Physical Medicine & RehabilitationMassachusetts General Hospital, Spaulding Rehabilitation Hospital, Harvard Medical SchoolCharlestownMassachusettsUSA
| | - Joseph N. Palmisano
- Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Biostatistics and Epidemiology Data Analytics Center (BEDAC), Boston University School of Public HealthBostonMassachusettsUSA
| | - Elaine R. Peskind
- Department of Psychiatry and Behavioral SciencesVA Northwest Mental Illness Research, Education, and Clinical Center, VA Puget Sound Health Care System; University of Washington School of MedicineSeattleWashingtonUSA
| | - Robert W. Turner
- Department of Clinical Research & LeadershipThe George Washington University School of Medicine & Health SciencesWashingtonDistrict of ColumbiaUSA
| | - Jennifer V. Wethe
- Department of Psychiatry and PsychologyMayo Clinic School of Medicine, Mayo Clinic ArizonaScottsdaleArizonaUSA
| | - Gil Rabinovici
- Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Keith Johnson
- Gordon Center for Medical Imaging, Mass General Research Institute, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yorghos Tripodis
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Jeffrey L. Cummings
- Department of Brain HealthChambers‐Grundy Center for Transformative NeuroscienceSchool of Integrated Health Sciences, University of Nevada Las VegasLas VegasNevadaUSA
| | - Martha E. Shenton
- Departments of Psychiatry and RadiologyPsychiatry Neuroimaging LaboratoryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Robert A. Stern
- Department of NeurologyBoston University Alzheimer's Disease Research CenterBoston University CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Eric M. Reiman
- Banner Alzheimer's Institute and Arizona Alzheimer's ConsortiumPhoenixArizonaUSA
- University of Arizona, Arizona State University, Translational Genomics Research InstitutePhoenixArizonaUSA
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Lee J, Burkett BJ, Min HK, Senjem ML, Dicks E, Corriveau-Lecavalier N, Mester CT, Wiste HJ, Lundt ES, Murray ME, Nguyen AT, Reichard RR, Botha H, Graff-Radford J, Barnard LR, Gunter JL, Schwarz CG, Kantarci K, Knopman DS, Boeve BF, Lowe VJ, Petersen RC, Jack CR, Jones DT. Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning. Brain 2024; 147:980-995. [PMID: 37804318 PMCID: PMC10907092 DOI: 10.1093/brain/awad346] [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: 02/20/2023] [Revised: 08/30/2023] [Accepted: 09/24/2023] [Indexed: 10/09/2023] Open
Abstract
Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.
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Affiliation(s)
- Jeyeon Lee
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea
| | - Brian J Burkett
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Hoon-Ki Min
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Matthew L Senjem
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ellen Dicks
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Carly T Mester
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Heather J Wiste
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Emily S Lundt
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Aivi T Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ross R Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
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9
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Yang J, Liu X, Oveisgharan S, Zammit AR, Nag S, Bennett DA, Buchman AS. Inferring Alzheimer's disease pathologic traits from clinical measures in living adults. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.05.08.23289668. [PMID: 37214885 PMCID: PMC10197717 DOI: 10.1101/2023.05.08.23289668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Background Alzheimer's disease neuropathologic changes (AD-NC) are important for identify people with high risk for AD dementia (ADD) and subtyping ADD. Objective Develop imputation models based on clinical measures to infer AD-NC. Methods We used penalized generalized linear regression to train imputation models for four AD-NC traits (amyloid-β, tangles, global AD pathology, and pathologic AD) in Rush Memory and Aging Project decedents, using clinical measures at the last visit prior to death as predictors. We validated these models by inferring AD-NC traits with clinical measures at the last visit prior to death for independent Religious Orders Study (ROS) decedents. We inferred baseline AD-NC traits for all ROS participants at study entry, and then tested if inferred AD-NC traits at study entry predicted incident ADD and postmortem pathologic AD. Results Inferred AD-NC traits at the last visit prior to death were related to postmortem measures with R2=(0.188,0.316,0.262) respectively for amyloid-β, tangles, and global AD pathology, and prediction Area Under the receiver operating characteristic Curve (AUC) 0.765 for pathologic AD. Inferred baseline levels of all four AD-NC traits predicted ADD. The strongest prediction was obtained by the inferred baseline probabilities of pathologic AD with AUC=(0.919,0.896) for predicting the development of ADD in 3 and 5 years from baseline. The inferred baseline levels of all four AD-NC traits significantly discriminated pathologic AD profiled eight years later with p-values<1.4 × 10-10. Conclusion Inferred AD-NC traits based on clinical measures may provide effective AD biomarkers that can estimate the burden of AD-NC traits in aging adults.
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Affiliation(s)
- Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, 615 Michael St, Atlanta, GA, 30322, USA
| | - Xizhu Liu
- Department of Biostatistics, Yale University School of Public Health, 60 College St, New Haven, CT, 06510, USA
| | - Shahram Oveisgharan
- Rush Alzheimer’s Disease Center, Rush University Medicine Center, 1620 W Harrison St, Chicago, IL, 60612, USA
| | - Andrea R. Zammit
- Rush Alzheimer’s Disease Center, Rush University Medicine Center, 1620 W Harrison St, Chicago, IL, 60612, USA
| | - Sukriti Nag
- Rush Alzheimer’s Disease Center, Rush University Medicine Center, 1620 W Harrison St, Chicago, IL, 60612, USA
| | - David A Bennett
- Rush Alzheimer’s Disease Center, Rush University Medicine Center, 1620 W Harrison St, Chicago, IL, 60612, USA
| | - Aron S Buchman
- Rush Alzheimer’s Disease Center, Rush University Medicine Center, 1620 W Harrison St, Chicago, IL, 60612, USA
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10
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Yang J, Liu X, Oveisgharan S, Zammit AR, Nag S, Bennett DA, Buchman AS. Inferring Alzheimer's Disease Pathologic Traits from Clinical Measures in Living Adults. J Alzheimers Dis 2024; 98:95-107. [PMID: 38427476 PMCID: PMC11034758 DOI: 10.3233/jad-230639] [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: 03/03/2024]
Abstract
Background Alzheimer's disease neuropathologic changes (AD-NC) are important to identify people with high risk for AD dementia (ADD) and subtyping ADD. Objective Develop imputation models based on clinical measures to infer AD-NC. Methods We used penalized generalized linear regression to train imputation models for four AD-NC traits (amyloid-β, tangles, global AD pathology, and pathologic AD) in Rush Memory and Aging Project decedents, using clinical measures at the last visit prior to death as predictors. We validated these models by inferring AD-NC traits with clinical measures at the last visit prior to death for independent Religious Orders Study (ROS) decedents. We inferred baseline AD-NC traits for all ROS participants at study entry, and then tested if inferred AD-NC traits at study entry predicted incident ADD and postmortem pathologic AD. Results Inferred AD-NC traits at the last visit prior to death were related to postmortem measures with R2 = (0.188,0.316,0.262) respectively for amyloid-β, tangles, and global AD pathology, and prediction Area Under the receiver operating characteristic Curve (AUC) 0.765 for pathologic AD. Inferred baseline levels of all four AD-NC traits predicted ADD. The strongest prediction was obtained by the inferred baseline probabilities of pathologic AD with AUC = (0.919,0.896) for predicting the development of ADD in 3 and 5 years from baseline. The inferred baseline levels of all four AD-NC traits significantly discriminated pathologic AD profiled eight years later with p-values < 1.4×10-10. Conclusions Inferred AD-NC traits based on clinical measures may provide effective AD biomarkers that can estimate the burden of AD-NC traits in aging adults.
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Affiliation(s)
- Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, 615 Michael St, Atlanta, GA, 30322, USA
| | - Xizhu Liu
- Department of Biostatistics, Yale University School of Public Health, 60 College St, New Haven, CT, 06510, USA
| | - Shahram Oveisgharan
- Rush Alzheimer’s Disease Center, Rush University Medicine Center, 1620 W Harrison St, Chicago, IL, 60612, USA
| | - Andrea R. Zammit
- Rush Alzheimer’s Disease Center, Rush University Medicine Center, 1620 W Harrison St, Chicago, IL, 60612, USA
| | - Sukriti Nag
- Rush Alzheimer’s Disease Center, Rush University Medicine Center, 1620 W Harrison St, Chicago, IL, 60612, USA
| | - David A Bennett
- Rush Alzheimer’s Disease Center, Rush University Medicine Center, 1620 W Harrison St, Chicago, IL, 60612, USA
| | - Aron S Buchman
- Rush Alzheimer’s Disease Center, Rush University Medicine Center, 1620 W Harrison St, Chicago, IL, 60612, USA
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11
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Wang Y, Zhang Y, Yu E. Targeted examination of amyloid beta and tau protein accumulation via positron emission tomography for the differential diagnosis of Alzheimer's disease based on the A/T(N) research framework. Clin Neurol Neurosurg 2024; 236:108071. [PMID: 38043158 DOI: 10.1016/j.clineuro.2023.108071] [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: 06/08/2023] [Revised: 11/24/2023] [Accepted: 11/25/2023] [Indexed: 12/05/2023]
Abstract
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases among the older population. Its main pathological features include the abnormal deposition of extracellular amyloid-β plaques and the intracellular neurofibrillary tangles of tau proteins. Its clinical presentation is complex. This review introduces the pathological processes in AD and other common neurodegenerative diseases. It then discusses the positron emission tomography (PET) probes that target amyloid-β plaques and tau proteins for diagnosing AD. According to the A/T(N) research framework, combined targeted amyloid-β and tau protein detection via PET to further improve the diagnostic accuracy of AD. In particular, the properties of the 18F-flortaucipir and 18F-MK6240 tracers-may be more beneficial in helping to differentiate AD from other common neurodegenerative diseases, such as dementia with Lewy bodies, Parkinson's disease dementia, and frontotemporal dementia. Furthermore, the A/T(N) research framework should be used as the clinical diagnosis model of AD in the future.
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Affiliation(s)
- Ye Wang
- The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou 310053, China; Department of Psychiatry, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), 310022, China
| | - Yuhan Zhang
- The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Enyan Yu
- Department of Psychiatry, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), 310022, China.
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12
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Strobel J, Müller HP, Ludolph AC, Beer AJ, Sollmann N, Kassubek J. New Perspectives in Radiological and Radiopharmaceutical Hybrid Imaging in Progressive Supranuclear Palsy: A Systematic Review. Cells 2023; 12:2776. [PMID: 38132096 PMCID: PMC10742083 DOI: 10.3390/cells12242776] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 11/28/2023] [Accepted: 12/04/2023] [Indexed: 12/23/2023] Open
Abstract
Progressive supranuclear palsy (PSP) is a neurodegenerative disease characterized by four-repeat tau deposition in various cell types and anatomical regions, and can manifest as several clinical phenotypes, including the most common phenotype, Richardson's syndrome. The limited availability of biomarkers for PSP relates to the overlap of clinical features with other neurodegenerative disorders, but identification of a growing number of biomarkers from imaging is underway. One way to increase the reliability of imaging biomarkers is to combine different modalities for multimodal imaging. This review aimed to provide an overview of the current state of PSP hybrid imaging by combinations of positron emission tomography (PET) and magnetic resonance imaging (MRI). Specifically, combined PET and MRI studies in PSP highlight the potential of [18F]AV-1451 to detect tau, but also the challenge in differentiating PSP from other neurodegenerative diseases. Studies over the last years showed a reduced synaptic density in [11C]UCB-J PET, linked [11C]PK11195 and [18F]AV-1451 markers to disease progression, and suggested the potential role of [18F]RO948 PET for identifying tau pathology in subcortical regions. The integration of quantitative global and regional gray matter analysis by MRI may further guide the assessment of reduced cortical thickness or volume alterations, and diffusion MRI could provide insight into microstructural changes and structural connectivity in PSP. Challenges in radiopharmaceutical biomarkers and hybrid imaging require further research targeting markers for comprehensive PSP diagnosis.
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Affiliation(s)
- Joachim Strobel
- Department of Nuclear Medicine, University Hospital Ulm, 89081 Ulm, Germany;
| | - Hans-Peter Müller
- Department of Neurology, University Hospital Ulm, 89081 Ulm, Germany; (H.-P.M.); (A.C.L.); (J.K.)
| | - Albert C. Ludolph
- Department of Neurology, University Hospital Ulm, 89081 Ulm, Germany; (H.-P.M.); (A.C.L.); (J.K.)
- German Center for Neurodegenerative Diseases (DZNE), Ulm University, 89081 Ulm, Germany
| | - Ambros J. Beer
- Department of Nuclear Medicine, University Hospital Ulm, 89081 Ulm, Germany;
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany;
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Jan Kassubek
- Department of Neurology, University Hospital Ulm, 89081 Ulm, Germany; (H.-P.M.); (A.C.L.); (J.K.)
- German Center for Neurodegenerative Diseases (DZNE), Ulm University, 89081 Ulm, Germany
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13
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Blazhenets G, Soleimani-Meigooni DN, Thomas W, Mundada N, Brendel M, Vento S, VandeVrede L, Heuer HW, Ljubenkov P, Rojas JC, Chen MK, Amuiri AN, Miller Z, Gorno-Tempini ML, Miller BL, Rosen HJ, Litvan I, Grossman M, Boeve B, Pantelyat A, Tartaglia MC, Irwin DJ, Dickerson BC, Baker SL, Boxer AL, Rabinovici GD, La Joie R. [ 18F]PI-2620 Binding Patterns in Patients with Suspected Alzheimer Disease and Frontotemporal Lobar Degeneration. J Nucl Med 2023; 64:1980-1989. [PMID: 37918868 PMCID: PMC10690126 DOI: 10.2967/jnumed.123.265856] [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: 04/13/2023] [Revised: 09/27/2023] [Indexed: 11/04/2023] Open
Abstract
Tau PET has enabled the visualization of paired helical filaments of 3 or 4 C-terminal repeat tau in Alzheimer disease (AD), but its ability to detect aggregated tau in frontotemporal lobar degeneration (FTLD) spectrum disorders is uncertain. We investigated 2-(2-([18F]fluoro)pyridin-4-yl)-9H-pyrrolo[2,3-b:4,5c']dipyridine ([18F]PI-2620), a newer tracer with ex vivo evidence for binding to FTLD tau, in a convenience sample of patients with suspected FTLD and AD using a static acquisition protocol and parametric SUV ratio (SUVr) images. Methods: We analyzed [18F]PI-2620 PET data from 65 patients with clinical diagnoses associated with AD or FTLD neuropathology; most (60/65) also had amyloid-β (Aβ) PET. Scans were acquired 30-60 min after injection; SUVr maps (reference, inferior cerebellar cortex) were created for the full acquisition and for 10-min truncated sliding windows (30-40, 35-45,…50-60 min). Age- and sex-adjusted z score maps were computed for each patient, relative to 23 Aβ-negative cognitively healthy controls (HC). Mean SUVr in the globus pallidus, substantia nigra, subthalamic nuclei, dentate nuclei, white matter, and temporal gray matter was extracted for the full and truncated windows. Results: Patients with suspected AD neuropathology (Aβ-positive patients with mild cognitive impairment or AD dementia) showed high-intensity temporoparietal cortex-predominant [18F]PI-2620 binding. At the group level, patients with clinical diagnoses associated with FTLD (progressive supranuclear palsy with Richardson syndrome [PSP Richardson syndrome], corticobasal syndrome, and nonfluent-variant primary progressive aphasia) exhibited higher globus pallidus SUVr than did HCs; pallidal retention was highest in the PSP Richardson syndrome group, in whom SUVr was correlated with symptom severity (ρ = 0.53, P = 0.05). At the individual level, only half of PSP Richardson syndrome, corticobasal syndrome, and nonfluent-variant primary progressive aphasia patients had a pallidal SUVr above that of HCs. Temporal SUVr discriminated AD patients from HCs with high accuracy (area under the receiver operating characteristic curve, 0.94 [95% CI, 0.83-1.00]) for all time windows, whereas discrimination between patients with PSP Richardson syndrome and HCs using pallidal SUVr was fair regardless of time window (area under the receiver operating characteristic curve, 0.77 [95% CI, 0.61-0.92] at 30-40 min vs. 0.81 [95% CI, 0.66-0.96] at 50-60 min; P = 0.67). Conclusion: [18F]PI-2620 SUVr shows an intense and consistent signal in AD but lower-intensity, heterogeneous, and rapidly decreasing binding in patients with suspected FTLD. Further work is needed to delineate the substrate of [18F]PI-2620 binding and the usefulness of [18F]PI2620 SUVr quantification outside the AD continuum.
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Affiliation(s)
- Ganna Blazhenets
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
- Department of Nuclear Medicine, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - David N Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Wesley Thomas
- Lawrence Berkeley National Laboratory, Berkeley, California
| | - Nidhi Mundada
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Stephanie Vento
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Lawren VandeVrede
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Hilary W Heuer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Peter Ljubenkov
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Julio C Rojas
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
| | - Miranda K Chen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Alinda N Amuiri
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Zachary Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Maria L Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Howie J Rosen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Irene Litvan
- University of California, San Diego, San Diego, California
| | - Murray Grossman
- Penn FTD Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | | | | | | | - David J Irwin
- Penn FTD Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | | | | | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California;
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14
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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.
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Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
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15
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Cho H, Mundada NS, Apostolova LG, Carrillo MC, Shankar R, Amuiri AN, Zeltzer E, Windon CC, Soleimani-Meigooni DN, Tanner JA, Heath CL, Lesman-Segev OH, Aisen P, Eloyan A, Lee HS, Hammers DB, Kirby K, Dage JL, Fagan A, Foroud T, Grinberg LT, Jack CR, Kramer J, Kukull WA, Murray ME, Nudelman K, Toga A, Vemuri P, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu J, Mendez M, Musiek E, Onyike CU, Riddle M, Rogalski EJ, Salloway S, Sha S, Turner RS, Wingo TS, Wolk DA, Koeppe R, Iaccarino L, Dickerson BC, La Joie R, Rabinovici GD. Amyloid and tau-PET in early-onset AD: Baseline data from the Longitudinal Early-onset Alzheimer's Disease Study (LEADS). Alzheimers Dement 2023; 19 Suppl 9:S98-S114. [PMID: 37690109 PMCID: PMC10807231 DOI: 10.1002/alz.13453] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 09/12/2023]
Abstract
INTRODUCTION We aimed to describe baseline amyloid-beta (Aβ) and tau-positron emission tomograrphy (PET) from Longitudinal Early-onset Alzheimer's Disease Study (LEADS), a prospective multi-site observational study of sporadic early-onset Alzheimer's disease (EOAD). METHODS We analyzed baseline [18F]Florbetaben (Aβ) and [18F]Flortaucipir (tau)-PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aβ+) from EOnonAD (Aβ-) based on the combination of visual read by expert reader and image quantification. RESULTS 243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid-PET; 231 (95.1%) of them were tau-PET positive (A+T+). Tau-PET signal was elevated across cortical regions with a parietal-predominant pattern, and higher burden was observed in younger and female EOAD participants. DISCUSSION LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau-PET binding at baseline might have implications for therapeutic strategies in patients with EOAD. HIGHLIGHTS 72% of patients with clinical EOAD were positive on both amyloid- and tau-PET. Amyloid-positive patients with EOAD had high tau-PET signal across cortical regions. In EOAD, tau-PET mediated the relationship between amyloid-PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau-PET.
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Affiliation(s)
- Hanna Cho
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
- Global Brain Health Institute, University of California, San Francisco, California, USA
| | - Nidhi S Mundada
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Maria C Carrillo
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
| | - Ranjani Shankar
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Alinda N Amuiri
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Ehud Zeltzer
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Charles C Windon
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - David N Soleimani-Meigooni
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Jeremy A Tanner
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Courtney Lawhn Heath
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Orit H Lesman-Segev
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Diagnostic Imaging, Sheba Medical Center, Tel HaShomer, Israel
| | - Paul Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Rhode Island, USA
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Dustin B Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jeffrey L Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Anne Fagan
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Lea T Grinberg
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Pathology, University of California - San Francisco, San Francisco, California, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joel Kramer
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Walter A Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Rhode Island, USA
| | - Emily J Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Rhode Island, USA
| | - Sharon Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | | | - Thomas S Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Robert Koeppe
- Division of Nuclear Medicine, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Renaud La Joie
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Gil D Rabinovici
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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16
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Hong J, Lu J, Liu F, Wang M, Li X, Clement C, Lopes L, Brendel M, Rominger A, Yen TC, Guan Y, Tian M, Wang J, Zuo C, Shi K. Uncovering distinct progression patterns of tau deposition in progressive supranuclear palsy using [ 18F]Florzolotau PET imaging and subtype/stage inference algorithm. EBioMedicine 2023; 97:104835. [PMID: 37839135 PMCID: PMC10590768 DOI: 10.1016/j.ebiom.2023.104835] [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: 04/13/2023] [Revised: 09/29/2023] [Accepted: 10/02/2023] [Indexed: 10/17/2023] Open
Abstract
BACKGROUND Progressive supranuclear palsy (PSP) is a primary 4-repeat tauopathy with diverse clinical phenotypes. Previous post-mortem studies examined tau deposition sequences in PSP, but in vivo scrutiny is lacking. METHODS We conducted [18F]Florzolotau tau positron emission tomography (PET) scans on 148 patients who were clinically diagnosed with PSP and 20 healthy controls. We employed the Subtype and Stage Inference (SuStaIn) algorithm to identify PSP subtype/stage and related tau patterns, comparing clinical features across subtypes and assessing PSP stage-clinical severity association. We also evaluated functional connectivity differences among subtypes through resting-state functional magnetic resonance imaging. FINDINGS We identified two distinct subtypes of PSP: Subtype1 and Subtype2. Subtype1 typically exhibits a sequential progression of the disease, starting from subcortical and gradually moving to cortical regions. Conversely, Subtype2 is characterized by an early, simultaneous onset in both regions. Interestingly, once the disease is initiated, Subtype1 tends to spread more rapidly within each region compared to Subtype2. Individuals categorized as Subtype2 are generally older and exhibit less severe dysfunctions in areas such as cognition, bulbar, limb motor, and general motor functions compared to those with Subtype1. Moreover, they have a more favorable prognosis in terms of limb motor function. We found significant correlations between several clinical variables and the identified PSP SuStaIn stages. Furthermore, Subtype2 displayed a remarkable reduction in functional connectivity compared to Subtype1. INTERPRETATION We present the evidence of distinct in vivo spatiotemporal tau trajectories in PSP. Our findings can contribute to precision medicine advancements for PSP. FUNDING This work was supported by grants from the National Natural Science Foundation of China (number 82272039, 81971641, 82021002, and 92249302); Swiss National Science Foundation (number 188350); the STI2030-Major Project of China (number 2022ZD0211600); the Clinical Research Plan of Shanghai Hospital Development Center of China (number SHDC2020CR1038B); and the National Key R&D Program of China (number 2022YFC2009902, 2022YFC2009900), the China Scholarship Council (number 202006100181); the Deutsche Forschungsgemeinschaft (DFG) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy, ID 390857198).
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Affiliation(s)
- Jimin Hong
- Department of Nuclear Medicine, Inselspital, University of Bern, Bern, Switzerland; Graduate School for Cellular and Biomedical Sciences, University of Bern, Switzerland
| | - Jiaying Lu
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China; Department of Nuclear Medicine, Inselspital, University of Bern, Bern, Switzerland; National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Fengtao Liu
- National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China; Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Min Wang
- Institute of Biomedical Engineering, School of Life Science, Shanghai University, Shanghai, China; Department of Informatics, Technical University of Munich, Munich, Germany
| | - Xinyi Li
- National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China; Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Christoph Clement
- Department of Nuclear Medicine, Inselspital, University of Bern, Bern, Switzerland; Graduate School for Cellular and Biomedical Sciences, University of Bern, Switzerland
| | - Leonor Lopes
- Department of Nuclear Medicine, Inselspital, University of Bern, Bern, Switzerland; Graduate School for Cellular and Biomedical Sciences, University of Bern, Switzerland
| | - Matthias Brendel
- Department of Nuclear Medicine, University of Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Axel Rominger
- Department of Nuclear Medicine, Inselspital, University of Bern, Bern, Switzerland
| | | | - Yihui Guan
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China; National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Mei Tian
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China; International Human Phenome Institutes (Shanghai), Shanghai, China
| | - Jian Wang
- National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China; Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
| | - Chuantao Zuo
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China; National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China.
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital, University of Bern, Bern, Switzerland; Department of Informatics, Technical University of Munich, Munich, Germany
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17
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Vöglein J, Levin J, Höglinger G. [Treatment-Quo vadis neurodegeneration?]. DER NERVENARZT 2023; 94:904-912. [PMID: 37801166 DOI: 10.1007/s00115-023-01544-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/09/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND Hallmarks of neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease are pathological protein aggregation, neuroinflammation, neurodegeneration and progressive symptoms. Due to the limited causal treatment options they represent a big challenge. OBJECTIVE Overview of disease-modifying strategies in neurodegenerative diseases and outlook regarding future treatment development. MATERIAL AND METHODS Literature search regarding treatment development in neurodegenerative diseases and integration of the results. Additionally, consideration of expert opinions. RESULTS The development of biomarkers and genetic parameters for the detection of causal pathologies of neurodegenerative diseases as an indispensable basis for the development of disease-modifying treatment is rapidly advancing. Targets for causal interventions are all steps in the pathophysiological cascade of neurodegenerative diseases. Therapeutic antibodies are most advanced in the development and are able to remove protein deposits from the brain and to reduce the clinical progression in Alzheimer's disease. A combination of biomarkers, genetic characteristics and clinical parameters could enable an individualized treatment. CONCLUSION The future of the treatment of neurodegenerative diseases focuses on disease modification using molecular-based approaches. Targeted interventions against protein aggregation, inflammation and genetic factors as well as a personalized stratification of treatment hold promise for more effective forms of treatment. Although challenges still remain, current research and clinical studies give optimism for the development of disease-modifying treatment for neurodegenerative diseases.
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Affiliation(s)
- Jonathan Vöglein
- Neurologische Klinik und Poliklinik mit Friedrich-Baur-Institut, LMU Klinikum, Ludwig-Maximilians-Universität (LMU) München, Marchioninistr. 15, 81377, München, Deutschland
- Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE) München, München, Deutschland
| | - Johannes Levin
- Neurologische Klinik und Poliklinik mit Friedrich-Baur-Institut, LMU Klinikum, Ludwig-Maximilians-Universität (LMU) München, Marchioninistr. 15, 81377, München, Deutschland
- Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE) München, München, Deutschland
| | - Günter Höglinger
- Neurologische Klinik und Poliklinik mit Friedrich-Baur-Institut, LMU Klinikum, Ludwig-Maximilians-Universität (LMU) München, Marchioninistr. 15, 81377, München, Deutschland.
- Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE) München, München, Deutschland.
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18
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Costoya-Sánchez A, Moscoso A, Silva-Rodríguez J, Pontecorvo MJ, Devous MD, Aguiar P, Schöll M, Grothe MJ. Increased Medial Temporal Tau Positron Emission Tomography Uptake in the Absence of Amyloid-β Positivity. JAMA Neurol 2023; 80:1051-1061. [PMID: 37578787 PMCID: PMC10425864 DOI: 10.1001/jamaneurol.2023.2560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 05/16/2023] [Indexed: 08/15/2023]
Abstract
Importance An increased tau positron emission tomography (PET) signal in the medial temporal lobe (MTL) has been observed in older individuals in the absence of amyloid-β (Aβ) pathology. Little is known about the longitudinal course of this condition, and its association with Alzheimer disease (AD) remains unclear. Objective To study the pathologic and clinical course of older individuals with PET-evidenced MTL tau deposition (TMTL+) in the absence of Aβ pathology (A-), and the association of this condition with the AD continuum. Design, Setting, and Participants A multicentric, observational, longitudinal cohort study was conducted using pooled data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain Study (HABS), and the AVID-A05 study, collected between July 2, 2015, and August 23, 2021. Participants in the ADNI, HABS, and AVID-A05 studies (N = 1093) with varying degrees of cognitive performance were deemed eligible if they had available tau PET, Aβ PET, and magnetic resonance imaging scans at baseline. Of these, 128 participants did not meet inclusion criteria based on Aβ PET and tau PET biomarker profiles (A+ TMTL-). Exposures Tau and Aβ PET, magnetic resonance imaging, cerebrospinal fluid biomarkers, and cognitive assessments. Main Outcomes and Measures Cross-sectional and longitudinal measures for tau and Aβ PET, cortical atrophy, cognitive scores, and core AD cerebrospinal fluid biomarkers (Aβ42/40 and tau phosphorylated at threonine 181 p-tau181 available in a subset). Results Among the 965 individuals included in the study, 503 were women (52.1%) and the mean (SD) age was 73.9 (8.1) years. A total of 51% of A- individuals and 78% of A+ participants had increased tau PET signal in the entorhinal cortex (TMTL+) compared with healthy younger (aged <39 years) controls. Compared with A- TMTL-, A- TMTL+ participants showed statistically significant, albeit moderate, longitudinal (mean [SD], 1.83 [0.84] years) tau PET increases that were largely limited to the temporal lobe, whereas those with A+ TMTL+ showed faster and more cortically widespread tau PET increases. In contrast to participants with A+ TMTL+, those with A- TMTL+ did not show any noticeable Aβ accumulation over follow-up (mean [SD], 2.36 [0.76] years). Complementary cerebrospinal fluid analysis confirmed longitudinal p-tau181 increases in A- TMTL+ in the absence of increased Aβ accumulation. Participants with A- TMTL+ had accelerated MTL atrophy, whereas those with A+ TMTL+ showed accelerated atrophy in widespread temporoparietal brain regions. Increased MTL tau PET uptake in A- individuals was associated with cognitive decline, but at a significantly slower rate compared with A+ TMTL+. Conclusions and Relevance In this study, individuals with A- TMTL+ exhibited progressive tau accumulation and neurodegeneration, but these processes were comparably slow, remained largely restricted to the MTL, were associated with only subtle changes in global cognitive performance, and were not accompanied by detectable accumulation of Aβ biomarkers. These data suggest that individuals with A- TMTL+ are not on a pathologic trajectory toward AD.
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Affiliation(s)
- Alejandro Costoya-Sánchez
- Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostel, Travesía da Choupana s/n, Santiago de Compostela, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
| | - Alexis Moscoso
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden
| | - Jesús Silva-Rodríguez
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
- 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, Seville, Spain
| | - Michael J. Pontecorvo
- Avid Radiopharmaceuticals, Philadelphia, Pennsylvania
- Eli Lilly and Company, Indianapolis, Indiana
| | - Michael D. Devous
- Avid Radiopharmaceuticals, Philadelphia, Pennsylvania
- Eli Lilly and Company, Indianapolis, Indiana
| | - Pablo Aguiar
- Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostel, Travesía da Choupana s/n, Santiago de Compostela, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden
- Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom
| | - Michel J. Grothe
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- 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, Seville, Spain
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19
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Quattrini G, Ferrari C, Pievani M, Geviti A, Ribaldi F, Scheffler M, Frisoni GB, Garibotto V, Marizzoni M. Unsupervised [ 18F]Flortaucipir cutoffs for tau positivity and staging in Alzheimer's disease. Eur J Nucl Med Mol Imaging 2023; 50:3265-3275. [PMID: 37272955 PMCID: PMC10542510 DOI: 10.1007/s00259-023-06280-7] [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: 03/01/2023] [Accepted: 05/19/2023] [Indexed: 06/06/2023]
Abstract
PURPOSE Several [18F]Flortaucipir cutoffs have been proposed for tau PET positivity (T+) in Alzheimer's disease (AD), but none were data-driven. The aim of this study was to establish and validate unsupervised T+ cutoffs by applying Gaussian mixture models (GMM). METHODS Amyloid negative (A-) cognitively normal (CN) and amyloid positive (A+) AD-related dementia (ADRD) subjects from ADNI (n=269) were included. ADNI (n=475) and Geneva Memory Clinic (GMC) cohorts (n=98) were used for validation. GMM-based cutoffs were extracted for the temporal meta-ROI, and validated against previously published cutoffs and visual rating. RESULTS GMM-based cutoffs classified less subjects as T+, mainly in the A- CN (<3.4% vs >28.5%) and A+ CN (<14.5% vs >42.9%) groups and showed higher agreement with visual rating (ICC=0.91 vs ICC<0.62) than published cutoffs. CONCLUSION We provided reliable data-driven [18F]Flortaucipir cutoffs for in vivo T+ detection in AD. These cutoffs might be useful to select participants in clinical and research studies.
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Affiliation(s)
- Giulia Quattrini
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, 25123, Brescia, Italy
| | - Clarissa Ferrari
- FONDAZIONE POLIAMBULANZA ISTITUTO OSPEDALIERO via Bissolati, 57, 25124, Brescia, Italy
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Andrea Geviti
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Federica Ribaldi
- LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, 1205, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, 1205, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Giovanni B Frisoni
- LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, 1205, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, 1205, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocentre, Faculty of Medicine, University of Geneva, 1205, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva, 1205, Geneva, Switzerland
- Centre for Biomedical Imaging (CIBM), 1205, Geneva, Switzerland
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy.
- Biological Psychiatric Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy.
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20
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Horie K, Salvadó G, Barthélemy NR, Janelidze S, Li Y, He Y, Saef B, Chen CD, Jiang H, Strandberg O, Pichet Binette A, Palmqvist S, Sato C, Sachdev P, Koyama A, Gordon BA, Benzinger TLS, Holtzman DM, Morris JC, Mattsson-Carlgren N, Stomrud E, Ossenkoppele R, Schindler SE, Hansson O, Bateman RJ. CSF MTBR-tau243 is a specific biomarker of tau tangle pathology in Alzheimer's disease. Nat Med 2023; 29:1954-1963. [PMID: 37443334 PMCID: PMC10427417 DOI: 10.1038/s41591-023-02443-z] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 06/05/2023] [Indexed: 07/15/2023]
Abstract
Aggregated insoluble tau is one of two defining features of Alzheimer's disease. Because clinical symptoms are strongly correlated with tau aggregates, drug development and clinical diagnosis need cost-effective and accessible specific fluid biomarkers of tau aggregates; however, recent studies suggest that the fluid biomarkers currently available cannot specifically track tau aggregates. We show that the microtubule-binding region (MTBR) of tau containing the residue 243 (MTBR-tau243) is a new cerebrospinal fluid (CSF) biomarker specific for insoluble tau aggregates and compared it to multiple other phosphorylated tau measures (p-tau181, p-tau205, p-tau217 and p-tau231) in two independent cohorts (BioFINDER-2, n = 448; and Knight Alzheimer Disease Research Center, n = 219). MTBR-tau243 was most strongly associated with tau-positron emission tomography (PET) and cognition, whereas showing the lowest association with amyloid-PET. In combination with p-tau205, MTBR-tau243 explained most of the total variance in tau-PET burden (0.58 ≤ R2 ≤ 0.75) and the performance in predicting cognitive measures (0.34 ≤ R2 ≤ 0.48) approached that of tau-PET (0.44 ≤ R2 ≤ 0.52). MTBR-tau243 levels longitudinally increased with insoluble tau aggregates, unlike CSF p-tau species. CSF MTBR-tau243 is a specific biomarker of tau aggregate pathology, which may be utilized in interventional trials and in the diagnosis of patients. Based on these findings, we propose to revise the A/T/(N) criteria to include MTBR-tau243 as representing insoluble tau aggregates ('T').
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Grants
- P30 AG066444 NIA NIH HHS
- R01 AG070941 NIA NIH HHS
- P01 AG003991 NIA NIH HHS
- P01 AG026276 NIA NIH HHS
- P30 NS048056 NINDS NIH HHS
- S10 OD025214 NIH HHS
- The Tracy Family SILQ Center established by the Tracy Family, Richard Frimel and Gary Werths, GHR Foundation, David Payne, and the Willman Family brought together by The Foundation for Barnes-Jewish Hospital.
- Eisai industry grant
- The European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie action grant agreement No 101061836, from Greta och Johan Kocks research grants and, travel grants from the Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson’s disease) at Lund University
- U.S. Department of Health & Human Services | National Institutes of Health (NIH)
- The Swedish Research Council (2016-00906), the Knut and Alice Wallenberg foundation (2017-0383), the Marianne and Marcus Wallenberg foundation (2015.0125), the Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson’s disease) at Lund University, the Swedish Alzheimer Foundation (AF-939932), the Swedish Brain Foundation (FO2021-0293), The Parkinson foundation of Sweden (1280/20), the Cure Alzheimer’s fund, the Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse, the Skåne University Hospital Foundation (2020-O000028), Regionalt Forskningsstöd (2020-0314) and the Swedish federal government under the ALF agreement (2018-Projekt0279)
- The Knight ADRC developmental project
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Affiliation(s)
- Kanta Horie
- The Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Eisai Inc., Nutley, NJ, USA
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Nicolas R Barthélemy
- The Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Yingxin He
- The Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Benjamin Saef
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Charles D Chen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Hong Jiang
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Chihiro Sato
- The Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | | | | | - Brian A Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
| | - Randall J Bateman
- The Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO, USA.
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA.
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.
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21
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Limpengco RR, Liang C, Sandhu YK, Mukherjee J. [ 125I]INFT: Synthesis and Evaluation of a New Imaging Agent for Tau Protein in Post-Mortem Human Alzheimer's Disease Brain. Molecules 2023; 28:5769. [PMID: 37570739 PMCID: PMC10421386 DOI: 10.3390/molecules28155769] [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: 06/03/2023] [Revised: 07/24/2023] [Accepted: 07/29/2023] [Indexed: 08/13/2023] Open
Abstract
Aggregation of Tau protein into paired helical filaments causing neurofibrillary tangles (NFT) is a neuropathological feature in Alzheimer's disease (AD). This study aimed to develop and evaluate the effectiveness of a novel radioiodinated tracer, 4-[125I]iodo-3-(1H-pyrrolo[2,3-c]pyridine-1-yl)pyridine ([125I]INFT), for binding to Tau protein in postmortem human AD brain. Radiosynthesis of [125I]INFT was carried out using electrophilic destannylation by iodine-125 and purified chromatographically. Computational modeling of INFT binding on Tau fibril was compared with IPPI. In vitro, autoradiography studies were conducted with [125I]INFT for Tau in AD and cognitively normal (CN) brains. [125I]INFT was produced in >95% purity. Molecular modeling of INFT revealed comparable binding energies to IPPI at site-1 of the Tau fibril with an affinity of IC50 = 7.3 × 10-8 M. Binding of [125I]INFT correlated with the presence of Tau in the AD brain, confirmed by anti-Tau immunohistochemistry. The ratio of average grey matter (GM) [125I]INFT in AD versus CN was found to be 5.9, and AD GM/white matter (WM) = 2.5. Specifically bound [125I]INFT to Tau in AD brains was displaced by IPPI (>90%). Monoamine oxidase inhibitor deprenyl had no effect and clorgyline had little effect on [125I]INFT binding. [125I]INFT is a less lipophilic imaging agent for Tau in AD.
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Affiliation(s)
- Roz R Limpengco
- Preclinical Imaging, Department of Radiological Sciences, University of California-Irvine, Irvine, CA 92697, USA
| | - Christopher Liang
- Preclinical Imaging, Department of Radiological Sciences, University of California-Irvine, Irvine, CA 92697, USA
| | - Yasmin K Sandhu
- Preclinical Imaging, Department of Radiological Sciences, University of California-Irvine, Irvine, CA 92697, USA
| | - Jogeshwar Mukherjee
- Preclinical Imaging, Department of Radiological Sciences, University of California-Irvine, Irvine, CA 92697, USA
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22
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Donato L, Mordà D, Scimone C, Alibrandi S, D'Angelo R, Sidoti A. How Many Alzheimer-Perusini's Atypical Forms Do We Still Have to Discover? Biomedicines 2023; 11:2035. [PMID: 37509674 PMCID: PMC10377159 DOI: 10.3390/biomedicines11072035] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/17/2023] [Accepted: 07/17/2023] [Indexed: 07/30/2023] Open
Abstract
Alzheimer-Perusini's (AD) disease represents the most spread dementia around the world and constitutes a serious problem for public health. It was first described by the two physicians from whom it took its name. Nowadays, we have extensively expanded our knowledge about this disease. Starting from a merely clinical and histopathologic description, we have now reached better molecular comprehension. For instance, we passed from an old conceptualization of the disease based on plaques and tangles to a more modern vision of mixed proteinopathy in a one-to-one relationship with an alteration of specific glial and neuronal phenotypes. However, no disease-modifying therapies are yet available. It is likely that the only way to find a few "magic bullets" is to deepen this aspect more and more until we are able to draw up specific molecular profiles for single AD cases. This review reports the most recent classifications of AD atypical variants in order to summarize all the clinical evidence using several discrimina (for example, post mortem neurofibrillary tangle density, cerebral atrophy, or FDG-PET studies). The better defined four atypical forms are posterior cortical atrophy (PCA), logopenic variant of primary progressive aphasia (LvPPA), behavioral/dysexecutive variant and AD with corticobasal degeneration (CBS). Moreover, we discuss the usefulness of such classifications before outlining the molecular-genetic aspects focusing on microglial activity or, more generally, immune system control of neuroinflammation and neurodegeneration.
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Affiliation(s)
- Luigi Donato
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Division of Medical Biotechnologies and Preventive Medicine, University of Messina, Via Consolare Valeria 1, 98125 Messina, Italy
- Department of Biomolecular Strategies, Genetics, Cutting-Edge Therapies, Euro-Mediterranean Institute of Science and Technology, Via Michele Miraglia, 98139 Palermo, Italy
| | - Domenico Mordà
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Division of Medical Biotechnologies and Preventive Medicine, University of Messina, Via Consolare Valeria 1, 98125 Messina, Italy
- Department of Biomolecular Strategies, Genetics, Cutting-Edge Therapies, Euro-Mediterranean Institute of Science and Technology, Via Michele Miraglia, 98139 Palermo, Italy
| | - Concetta Scimone
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Division of Medical Biotechnologies and Preventive Medicine, University of Messina, Via Consolare Valeria 1, 98125 Messina, Italy
- Department of Biomolecular Strategies, Genetics, Cutting-Edge Therapies, Euro-Mediterranean Institute of Science and Technology, Via Michele Miraglia, 98139 Palermo, Italy
| | - Simona Alibrandi
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Division of Medical Biotechnologies and Preventive Medicine, University of Messina, Via Consolare Valeria 1, 98125 Messina, Italy
- Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, Viale Ferdinando Stagno D'Alcontres 31, 98166 Messina, Italy
| | - Rosalia D'Angelo
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Division of Medical Biotechnologies and Preventive Medicine, University of Messina, Via Consolare Valeria 1, 98125 Messina, Italy
| | - Antonina Sidoti
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Division of Medical Biotechnologies and Preventive Medicine, University of Messina, Via Consolare Valeria 1, 98125 Messina, Italy
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23
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Lu J, Ma X, Zhang H, Xiao Z, Li M, Wu J, Ju Z, Chen L, Zheng L, Ge J, Liang X, Bao W, Wu P, Ding D, Yen TC, Guan Y, Zuo C, Zhao Q. Head-to-head comparison of plasma and PET imaging ATN markers in subjects with cognitive complaints. Transl Neurodegener 2023; 12:34. [PMID: 37381042 PMCID: PMC10308642 DOI: 10.1186/s40035-023-00365-x] [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: 02/19/2023] [Accepted: 06/02/2023] [Indexed: 06/30/2023] Open
Abstract
BACKGROUND Gaining more information about the reciprocal associations between different biomarkers within the ATN (Amyloid/Tau/Neurodegeneration) framework across the Alzheimer's disease (AD) spectrum is clinically relevant. We aimed to conduct a comprehensive head-to-head comparison of plasma and positron emission tomography (PET) ATN biomarkers in subjects with cognitive complaints. METHODS A hospital-based cohort of subjects with cognitive complaints with a concurrent blood draw and ATN PET imaging (18F-florbetapir for A, 18F-Florzolotau for T, and 18F-fluorodeoxyglucose [18F-FDG] for N) was enrolled (n = 137). The β-amyloid (Aβ) status (positive versus negative) and the severity of cognitive impairment served as the main outcome measures for assessing biomarker performances. RESULTS Plasma phosphorylated tau 181 (p-tau181) level was found to be associated with PET imaging of ATN biomarkers in the entire cohort. Plasma p-tau181 level and PET standardized uptake value ratios of AT biomarkers showed a similarly excellent diagnostic performance for distinguishing between Aβ+ and Aβ- subjects. An increased tau burden and glucose hypometabolism were significantly associated with the severity of cognitive impairment in Aβ+ subjects. Additionally, glucose hypometabolism - along with elevated plasma neurofilament light chain level - was related to more severe cognitive impairment in Aβ- subjects. CONCLUSION Plasma p-tau181, as well as 18F-florbetapir and 18F-Florzolotau PET imaging can be considered as interchangeable biomarkers in the assessment of Aβ status in symptomatic stages of AD. 18F-Florzolotau and 18F-FDG PET imaging could serve as biomarkers for the severity of cognitive impairment. Our findings have implications for establishing a roadmap to identifying the most suitable ATN biomarkers for clinical use.
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Affiliation(s)
- Jiaying Lu
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoxi Ma
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Huiwei Zhang
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhenxu Xiao
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Ming Li
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jie Wu
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Zizhao Ju
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Li Chen
- Department of Ultrasound, Huashan Hospital, Fudan University, Shanghai, China
| | - Li Zheng
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingjie Ge
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoniu Liang
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Weiqi Bao
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Ping Wu
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Ding Ding
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | | | - Yihui Guan
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China.
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
| | - Chuantao Zuo
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China.
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
- Human Phenome Institute, Fudan University, Shanghai, China.
| | - Qianhua Zhao
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
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24
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Samudra N, Lane-Donovan C, VandeVrede L, Boxer AL. Tau pathology in neurodegenerative disease: disease mechanisms and therapeutic avenues. J Clin Invest 2023; 133:e168553. [PMID: 37317972 PMCID: PMC10266783 DOI: 10.1172/jci168553] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023] Open
Abstract
Tauopathies are disorders associated with tau protein dysfunction and insoluble tau accumulation in the brain at autopsy. Multiple lines of evidence from human disease, as well as nonclinical translational models, suggest that tau has a central pathologic role in these disorders, historically thought to be primarily related to tau gain of toxic function. However, a number of tau-targeting therapies with various mechanisms of action have shown little promise in clinical trials in different tauopathies. We review what is known about tau biology, genetics, and therapeutic mechanisms that have been tested in clinical trials to date. We discuss possible reasons for failures of these therapies, such as use of imperfect nonclinical models that do not predict human effects for drug development; heterogeneity of human tau pathologies which may lead to variable responses to therapy; and ineffective therapeutic mechanisms, such as targeting of the wrong tau species or protein epitope. Innovative approaches to human clinical trials can help address some of the difficulties that have plagued our field's development of tau-targeting therapies thus far. Despite limited clinical success to date, as we continue to refine our understanding of tau's pathogenic mechanism(s) in different neurodegenerative diseases, we remain optimistic that tau-targeting therapies will eventually play a central role in the treatment of tauopathies.
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25
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Shi Y, Ghetti B, Goedert M, Scheres SHW. Cryo-EM Structures of Chronic Traumatic Encephalopathy Tau Filaments with PET Ligand Flortaucipir. J Mol Biol 2023; 435:168025. [PMID: 37330290 PMCID: PMC7615338 DOI: 10.1016/j.jmb.2023.168025] [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: 12/12/2022] [Revised: 02/20/2023] [Accepted: 02/20/2023] [Indexed: 06/19/2023]
Abstract
Positron emission tomography (PET) imaging allows monitoring the progression of amyloid aggregation in the living brain. [18F]-Flortaucipir is the only approved PET tracer compound for the visualisation of tau aggregation. Here, we describe cryo-EM experiments on tau filaments in the presence and absence of flortaucipir. We used tau filaments isolated from the brain of an individual with Alzheimer's disease (AD), and from the brain of an individual with primary age-related tauopathy (PART) with a co-pathology of chronic traumatic encephalopathy (CTE). Unexpectedly, we were unable to visualise additional cryo-EM density for flortaucipir for AD paired helical or straight filaments (PHFs or SFs), but we did observe density for flortaucipir binding to CTE Type I filaments from the case with PART. In the latter, flortaucipir binds in a 1:1 molecular stoichiometry with tau, adjacent to lysine 353 and aspartate 358. By adopting a tilted geometry with respect to the helical axis, the 4.7 Å distance between neighbouring tau monomers is reconciled with the 3.5 Å distance consistent with π-π-stacking between neighbouring molecules of flortaucipir.
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Affiliation(s)
- Yang Shi
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.
| | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA. https://twitter.com/GhettiBernardi1
| | - Michel Goedert
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.
| | - Sjors H W Scheres
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.
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26
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Jack CR, Wiste HJ, Algeciras-Schimnich A, Figdore DJ, Schwarz CG, Lowe VJ, Ramanan VK, Vemuri P, Mielke MM, Knopman DS, Graff-Radford J, Boeve BF, Kantarci K, Cogswell PM, Senjem ML, Gunter JL, Therneau TM, Petersen RC. Predicting amyloid PET and tau PET stages with plasma biomarkers. Brain 2023; 146:2029-2044. [PMID: 36789483 PMCID: PMC10151195 DOI: 10.1093/brain/awad042] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/20/2022] [Accepted: 01/21/2023] [Indexed: 02/16/2023] Open
Abstract
Staging the severity of Alzheimer's disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer's Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer's clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1-2, 3-4, 5-6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1-42 and Aβ1-40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78-0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72-0.85 versus C = 0.73-0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer's disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.
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Affiliation(s)
- Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Heather J Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Dan J Figdore
- Department of Laboratory Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Terry M Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
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27
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Soleimani-Meigooni DN, Rabinovici GD. Tau PET Visual Reads: Research and Clinical Applications and Future Directions. J Nucl Med 2023; 64:822-824. [PMID: 37116910 PMCID: PMC10152121 DOI: 10.2967/jnumed.122.265017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 11/28/2022] [Indexed: 12/13/2022] Open
Affiliation(s)
- David N Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California; and
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California; and
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California
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28
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Liu FT, Lu JY, Li XY, Liang XN, Jiao FY, Ge JJ, Wu P, Li G, Shen B, Wu B, Sun YM, Zhu YH, Luo JF, Yen TC, Wu JJ, Zuo CT, Wang J. 18F-Florzolotau PET imaging captures the distribution patterns and regional vulnerability of tau pathology in progressive supranuclear palsy. Eur J Nucl Med Mol Imaging 2023; 50:1395-1405. [PMID: 36627498 PMCID: PMC10027831 DOI: 10.1007/s00259-022-06104-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 12/28/2022] [Indexed: 01/12/2023]
Abstract
PURPOSE Human post mortem studies have described the topographical patterns of tau pathology in progressive supranuclear palsy (PSP). Recent advances in tau PET tracers are expected to herald the next era of PSP investigation for early detection of tau pathology in living brains. This study aimed to investigate whether 18F-Florzolotau PET imaging may capture the distribution patterns and regional vulnerability of tau pathology in PSP, and to devise a novel image-based staging system. METHODS The study cohort consisted of 148 consecutive patients with PSP who had undergone 18F-Florzolotau PET imaging. The PSP rating scale (PSPrs) was used to measure disease severity. Similarities and differences of tau deposition among different clinical phenotypes were examined at the regional and voxel levels. An 18F-Florzolotau pathological staging system was devised according to the scheme originally developed for post mortem data. In light of conditional probabilities for the sequence of events, an 18F-Florzolotau modified staging system by integrating clusters at the regional level was further developed. The ability of 18F-Florzolotau staging systems to reflect disease severity in terms of PSPrs score was assessed by analysis of variance. RESULTS The distribution patterns of 18F-Florzolotau accumulation in living brains of PSP showed a remarkable similarity to those reported in post mortem studies, with the binding intensity being markedly higher in Richardson's syndrome. Moreover, 18F-Florzolotau PET imaging allowed detecting regional vulnerability and tracking tau accumulation in an earlier fashion compared with post mortem immunostaining. The 18F-Florzolotau staging systems were positively correlated with clinical severity as reflected by PSPrs scores. CONCLUSIONS 18F-Florzolotau PET imaging can effectively capture the distribution patterns and regional vulnerability of tau pathology in PSP. The 18F-Florzolotau modified staging system holds promise for early tracking of tau deposition in living brains.
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Affiliation(s)
- Feng-Tao Liu
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, China
| | - Jia-Ying Lu
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235, China
| | - Xin-Yi Li
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, China
| | - Xiao-Niu Liang
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, China
| | - Fang-Yang Jiao
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235, China
| | - Jing-Jie Ge
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235, China
| | - Ping Wu
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235, China
| | - Gen Li
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, China
| | - Bo Shen
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, China
| | - Bin Wu
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, China
| | - Yi-Min Sun
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, China
| | - Yu-Hua Zhu
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235, China
| | - Jian-Feng Luo
- Department of Biostatistics, School of Public Health, Fudan University, Shanghai, China
| | | | - Jian-Jun Wu
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, China
| | - Chuan-Tao Zuo
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235, China.
- Human Phenome Institute, Fudan University, Shanghai, China.
| | - Jian Wang
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, China.
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29
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Santillo AF, Leuzy A, Honer M, Landqvist Waldö M, Tideman P, Harper L, Ohlsson T, Moes S, Giannini L, Jögi J, Groot C, Ossenkoppele R, Strandberg O, van Swieten J, Smith R, Hansson O. [ 18F]RO948 tau positron emission tomography in genetic and sporadic frontotemporal dementia syndromes. Eur J Nucl Med Mol Imaging 2023; 50:1371-1383. [PMID: 36513817 PMCID: PMC10027632 DOI: 10.1007/s00259-022-06065-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 11/28/2022] [Indexed: 12/15/2022]
Abstract
PURPOSE To examine [18F]RO948 retention in FTD, sampling the underlying protein pathology heterogeneity. METHODS A total of 61 individuals with FTD (n = 35), matched cases of AD (n = 13) and Aβ-negative cognitively unimpaired individuals (n = 13) underwent [18F]RO948PET and MRI. FTD included 21 behavioral variant FTD (bvFTD) cases, 11 symptomatic C9orf72 mutation carriers, one patient with non-genetic bvFTD-ALS, one individual with bvFTD due to a GRN mutation, and one due to a MAPT mutation (R406W). Tracer retention was examined using a region-of-interest and voxel-wise approaches. Two individuals (bvFTD due to C9orf72) underwent postmortem neuropathological examination. Tracer binding was additionally assessed in vitro using [3H]RO948 autoradiography in six separate cases. RESULTS [18F]RO948 retention across ROIs was clearly lower than in AD and comparable to that in Aβ-negative cognitively unimpaired individuals. Only minor loci of tracer retention were seen in bvFTD; these did not overlap with the observed cortical atrophy in the cases, the expected pattern of atrophy, nor the expected or verified protein pathology distribution. Autoradiography analyses showed no specific [3H]RO948 binding. The R406W MAPT mutation carriers were clear exceptions with AD-like retention levels and specific in-vitro binding. CONCLUSION [18F]RO948 uptake is not significantly increased in the majority of FTD patients, with a clear exception being specific MAPT mutations.
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Affiliation(s)
- Alexander F Santillo
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden.
- Memory Clinic, Skåne University Hospital, SE-20502, Malmö, Sweden.
| | - Antoine Leuzy
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - Michael Honer
- Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche, Basel, Switzerland
| | - Maria Landqvist Waldö
- Clinical Sciences Helsingborg, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Pontus Tideman
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - Luke Harper
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - Tomas Ohlsson
- Radiation Physics, Skane University Hospital, Scania, Sweden
| | - Svenja Moes
- Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche, Basel, Switzerland
| | - Lucia Giannini
- Alzheimer Center, Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jonas Jögi
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Colin Groot
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - Rik Ossenkoppele
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Olof Strandberg
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - John van Swieten
- Alzheimer Center, Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ruben Smith
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Oskar Hansson
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
- Memory Clinic, Skåne University Hospital, SE-20502, Malmö, Sweden
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30
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Salvadó G, Ossenkoppele R, Ashton NJ, Beach TG, Serrano GE, Reiman EM, Zetterberg H, Mattsson-Carlgren N, Janelidze S, Blennow K, Hansson O. Specific associations between plasma biomarkers and postmortem amyloid plaque and tau tangle loads. EMBO Mol Med 2023; 15:e17123. [PMID: 36912178 PMCID: PMC10165361 DOI: 10.15252/emmm.202217123] [Citation(s) in RCA: 46] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 03/14/2023] Open
Abstract
Several promising plasma biomarkers for Alzheimer's disease have been recently developed, but their neuropathological correlates have not yet been fully determined. To investigate and compare independent associations between multiple plasma biomarkers (p-tau181, p-tau217, p-tau231, Aβ42/40, GFAP, and NfL) and neuropathologic measures of amyloid and tau, we included 105 participants from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) with antemortem plasma samples and a postmortem neuropathological exam, 48 of whom had longitudinal p-tau217 and p-tau181. When simultaneously including plaque and tangle loads, the Aβ42/40 ratio and p-tau231 were only associated with plaques (ρAβ42/40 [95%CI] = -0.53[-0.65, -0.35], ρp-tau231 [95%CI] = 0.28[0.10, 0.43]), GFAP was only associated with tangles (ρGFAP [95%CI] = 0.39[0.17, 0.57]), and p-tau217 and p-tau181 were associated with both plaques (ρp-tau217 [95%CI] = 0.40[0.21, 0.56], ρp-tau181 [95%CI] = 0.36[0.15, 0.50]) and tangles (ρp-tau217 [95%CI] = 0.52[0.34, 0.66]; ρp-tau181 [95%CI] = 0.36[0.17, 0.52]). A model combining p-tau217 and the Aβ42/40 ratio showed the highest accuracy for predicting the presence of Alzheimer's disease neuropathological change (ADNC, AUC[95%CI] = 0.89[0.82, 0.96]) and plaque load (R2 = 0.55), while p-tau217 alone was optimal for predicting tangle load (R2 = 0.45). Our results suggest that high-performing assays of plasma p-tau217 and Aβ42/40 might be an optimal combination to assess Alzheimer's-related pathology in vivo.
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Affiliation(s)
- Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, King's College London, London, UK.,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley, NHS Foundation, London, UK
| | | | | | - Eric M Reiman
- Banner Alzheimer's Institute, Arizona State University and University of Arizona, Phoenix, AZ, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK.,UK Dementia Research Institute at UCL, London, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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31
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Protas H, Ghisays V, Goradia DD, Bauer R, Devadas V, Chen K, Reiman EM, Su Y. Individualized network analysis: A novel approach to investigate tau PET using graph theory in the Alzheimer's disease continuum. Front Neurosci 2023; 17:1089134. [PMID: 36937677 PMCID: PMC10017746 DOI: 10.3389/fnins.2023.1089134] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 02/14/2023] [Indexed: 03/06/2023] Open
Abstract
Introduction Tau PET imaging has emerged as an important tool to detect and monitor tangle burden in vivo in the study of Alzheimer's disease (AD). Previous studies demonstrated the association of tau burden with cognitive decline in probable AD cohorts. This study introduces a novel approach to analyze tau PET data by constructing individualized tau network structure and deriving its graph theory-based measures. We hypothesize that the network- based measures are a measure of the total tau load and the stage through disease. Methods Using tau PET data from the AD Neuroimaging Initiative from 369 participants, we determine the network measures, global efficiency, global strength, and limbic strength, and compare with two regional measures entorhinal and tau composite SUVR, in the ability to differentiate, cognitively unimpaired (CU), MCI and AD. We also investigate the correlation of these network and regional measures and a measure of memory performance, auditory verbal learning test for long-term recall memory (AVLT-LTM). Finally, we determine the stages based on global efficiency and limbic strength using conditional inference trees and compare with Braak staging. Results We demonstrate that the derived network measures are able to differentiate three clinical stages of AD, CU, MCI, and AD. We also demonstrate that these network measures are strongly correlated with memory performance overall. Unlike regional tau measurements, the tau network measures were significantly associated with AVLT-LTM even in cognitively unimpaired individuals. Stages determined from global efficiency and limbic strength, visually resembled Braak staging. Discussion The strong correlations with memory particularly in CU suggest the proposed technique may be used to characterize subtle early tau accumulation. Further investigation is ongoing to examine this technique in a longitudinal setting.
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Affiliation(s)
- Hillary Protas
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
| | - Valentina Ghisays
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
| | - Dhruman D. Goradia
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
| | - Robert Bauer
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
| | - Vivek Devadas
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
| | - Kewei Chen
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Department of Neurology, The University of Arizona, Tucson, AZ, United States
- Department of Psychiatry, The University of Arizona, Tucson, AZ, United States
- Department of Neuroscience, School of Computing and Augmented Intelligence, Biostatistical Core, School of Mathematics and Statistics, College of Health Solutions, Arizona State University, Tempe, AZ, United States
| | - Eric M. Reiman
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Department of Neurology, The University of Arizona, Tucson, AZ, United States
- Department of Psychiatry, The University of Arizona, Tucson, AZ, United States
- Department of Neuroscience, School of Computing and Augmented Intelligence, Biostatistical Core, School of Mathematics and Statistics, College of Health Solutions, Arizona State University, Tempe, AZ, United States
- Translational Genomics Research Institute, Phoenix, AZ, United States
| | - Yi Su
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
- Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
- Department of Neuroscience, School of Computing and Augmented Intelligence, Biostatistical Core, School of Mathematics and Statistics, College of Health Solutions, Arizona State University, Tempe, AZ, United States
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32
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Mohammadi Z, Alizadeh H, Marton J, Cumming P. The Sensitivity of Tau Tracers for the Discrimination of Alzheimer's Disease Patients and Healthy Controls by PET. Biomolecules 2023; 13:290. [PMID: 36830659 PMCID: PMC9953528 DOI: 10.3390/biom13020290] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 01/12/2023] [Accepted: 01/25/2023] [Indexed: 02/09/2023] Open
Abstract
Hyperphosphorylated tau aggregates, also known as neurofibrillary tangles, are a hallmark neuropathological feature of Alzheimer's disease (AD). Molecular imaging of tau by positron emission tomography (PET) began with the development of [18F]FDDNP, an amyloid β tracer with off-target binding to tau, which obtained regional specificity through the differing distributions of amyloid β and tau in AD brains. A concerted search for more selective and affine tau PET tracers yielded compounds belonging to at least eight structural categories; 18F-flortaucipir, known variously as [18F]-T807, AV-1451, and Tauvid®, emerged as the first tau tracer approved by the American Food and Drug Administration. The various tau tracers differ concerning their selectivity over amyloid β, off-target binding at sites such as monoamine oxidase and neuromelanin, and degree of uptake in white matter. While there have been many reviews of molecular imaging of tau in AD and other conditions, there has been no systematic comparison of the fitness of the various tracers for discriminating between AD patient and healthy control (HC) groups. In this narrative review, we endeavored to compare the binding properties of the various tau tracers in vitro and the effect size (Cohen's d) for the contrast by PET between AD patients and age-matched HC groups. The available tracers all gave good discrimination, with Cohen's d generally in the range of two-three in culprit brain regions. Overall, Cohen's d was higher for AD patient groups with more severe illness. Second-generation tracers, while superior concerning off-target binding, do not have conspicuously higher sensitivity for the discrimination of AD and HC groups. We suppose that available pharmacophores may have converged on a maximal affinity for tau fibrils, which may limit the specific signal imparted in PET studies.
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Affiliation(s)
- Zohreh Mohammadi
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz 5166/15731, Iran
- Student Research Committee, Tabriz University of Medical Sciences, Tabriz 5166/15731, Iran
| | - Hadi Alizadeh
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz 5166/15731, Iran
| | - János Marton
- ABX Advanced Biochemical Compounds Biomedizinische Forschungsreagenzien GmbH, Heinrich-Glaeser-Straße 10-14, D-01454 Radeberg, Germany
| | - Paul Cumming
- Department of Nuclear Medicine, Bern University Hospital, Freiburgstraße 18, CH-3010 Bern, Switzerland
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, QLD 4059, Australia
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33
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McKenna MC, Lope J, Bede P, Tan EL. Thalamic pathology in frontotemporal dementia: Predilection for specific nuclei, phenotype-specific signatures, clinical correlates, and practical relevance. Brain Behav 2023; 13:e2881. [PMID: 36609810 PMCID: PMC9927864 DOI: 10.1002/brb3.2881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 12/17/2022] [Accepted: 12/18/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Frontotemporal dementia (FTD) phenotypes are classically associated with distinctive cortical atrophy patterns and regional hypometabolism. However, the spectrum of cognitive and behavioral manifestations in FTD arises from multisynaptic network dysfunction. The thalamus is a key hub of several corticobasal and corticocortical circuits. The main circuits relayed via the thalamic nuclei include the dorsolateral prefrontal circuit, the anterior cingulate circuit, and the orbitofrontal circuit. METHODS In this paper, we have reviewed evidence for thalamic pathology in FTD based on radiological and postmortem studies. Original research papers were systematically reviewed for preferential involvement of specific thalamic regions, for phenotype-associated thalamic disease burden patterns, characteristic longitudinal changes, and genotype-associated thalamic signatures. Moreover, evidence for presymptomatic thalamic pathology was also reviewed. Identified papers were systematically scrutinized for imaging methods, cohort sizes, clinical profiles, clinicoradiological associations, and main anatomical findings. The findings of individual research papers were amalgamated for consensus observations and their study designs further evaluated for stereotyped shortcomings. Based on the limitations of existing studies and conflicting reports in low-incidence FTD variants, we sought to outline future research directions and pressing research priorities. RESULTS FTD is associated with focal thalamic degeneration. Phenotype-specific thalamic traits mirror established cortical vulnerability patterns. Thalamic nuclei mediating behavioral and language functions are preferentially involved. Given the compelling evidence for considerable thalamic disease burden early in the course of most FTD subtypes, we also reflect on the practical relevance, diagnostic role, prognostic significance, and monitoring potential of thalamic metrics in FTD. CONCLUSIONS Cardinal manifestations of FTD phenotypes are likely to stem from thalamocortical circuitry dysfunction and are not exclusively driven by focal cortical changes.
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Affiliation(s)
- Mary Clare McKenna
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
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34
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Dang M, Chen Q, Zhao X, Chen K, Li X, Zhang J, Lu J, Ai L, Chen Y, Zhang Z. Tau as a biomarker of cognitive impairment and neuropsychiatric symptom in Alzheimer's disease. Hum Brain Mapp 2023; 44:327-340. [PMID: 36647262 PMCID: PMC9842886 DOI: 10.1002/hbm.26043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 06/28/2022] [Accepted: 07/28/2022] [Indexed: 01/25/2023] Open
Abstract
The A/T/N research framework has been proposed for the diagnosis and prognosis of Alzheimer's disease (AD). However, the spatial distribution of ATN biomarkers and their relationship with cognitive impairment and neuropsychiatric symptoms (NPS) need further clarification in patients with AD. We scanned 83 AD patients and 38 cognitively normal controls who independently completed the mini-mental state examination and Neuropsychiatric Inventory scales. Tau, Aβ, and hypometabolism spatial patterns were characterized using Statistical Parametric Mapping together with [18F]flortaucipir, [18F]florbetapir, and [18F]FDG positron emission tomography. Piecewise linear regression, two-sample t-tests, and support vector machine algorithms were used to explore the relationship between tau, Aβ, and hypometabolism and cognition, NPS, and AD diagnosis. The results showed that regions with tau deposition are region-specific and mainly occurred in inferior temporal lobes in AD, which extensively overlaps with the hypometabolic regions. While the deposition regions of Aβ were unique and the regions affected by hypometabolism were widely distributed. Unlike Aβ, tau and hypometabolism build up monotonically with increasing cognitive impairment in the late stages of AD. In addition, NPS in AD were associated with tau deposition closely, followed by hypometabolism, but not with Aβ. Finally, hypometabolism and tau had higher accuracy in differentiating the AD patients from controls (accuracy = 0.88, accuracy = 0.85) than Aβ (accuracy = 0.81), and the combined three were the highest (accuracy = 0.95). These findings suggest tau pathology is superior over Aβ and glucose metabolism to identify cognitive impairment and NPS. Its results support tau accumulation can be used as a biomarker of clinical impairment in AD.
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Affiliation(s)
- Mingxi Dang
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
| | - Qian Chen
- Department of Nuclear Medicine, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Xiaobin Zhao
- Department of Nuclear Medicine, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Kewei Chen
- Banner Alzheimer's InstitutePhoenixArizonaUSA
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
| | - Junying Zhang
- Institute of Basic Research in Clinical MedicineChina Academy of Chinese Medical SciencesBeijingChina
| | - Jie Lu
- Department of RadiologyXuanwu Hospital of Capital Medical UniversityBeijingChina
| | - Lin Ai
- Department of Nuclear Medicine, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
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35
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Abstract
Brain PET adds value in diagnosing neurodegenerative disorders, especially frontotemporal dementia (FTD) due to its syndromic presentation that overlaps with a variety of other neurodegenerative and psychiatric disorders. 18F-FDG-PET has improved sensitivity and specificity compared with structural MR imaging, with optimal diagnostic results achieved when both techniques are utilized. PET demonstrates superior sensitivity compared with SPECT for FTD diagnosis that is primarily a supplement to other imaging and clinical evaluations. Tau-PET and amyloid-PET primary use in FTD diagnosis is differentiation from Alzheimer disease, although these methods are limited mainly to research settings.
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Affiliation(s)
- Joshua Ward
- Division of Neuroradiology, Mallinckrodt Institute of Radiology, Washington University in Saint. Louis, Saint Louis, MO 63130, USA
| | - Maria Ly
- Division of Neuroradiology, Mallinckrodt Institute of Radiology, Washington University in Saint. Louis, Saint Louis, MO 63130, USA
| | - Cyrus A. Raji
- Division of Neuroradiology, Mallinckrodt Institute of Radiology, Washington University in Saint. Louis, Saint Louis, MO 63130, USA,Department of Neurology, Washington University in St. Louis, 4525 Scott Avenue, St. Louis, MO 63110, USA,Corresponding author. Division of Neuroradiology, Mallinckrodt Institute of Radiology, Washington University in Saint. Louis, Saint Louis, MO 63130.
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36
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Toledo JB, Abdelnour C, Weil RS, Ferreira D, Rodriguez-Porcel F, Pilotto A, Wyman-Chick KA, Grothe MJ, Kane JPM, Taylor A, Rongve A, Scholz S, Leverenz JB, Boeve BF, Aarsland D, McKeith IG, Lewis S, Leroi I, Taylor JP. Dementia with Lewy bodies: Impact of co-pathologies and implications for clinical trial design. Alzheimers Dement 2023; 19:318-332. [PMID: 36239924 PMCID: PMC9881193 DOI: 10.1002/alz.12814] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 08/29/2022] [Accepted: 09/09/2022] [Indexed: 02/01/2023]
Abstract
Dementia with Lewy bodies (DLB) is clinically defined by the presence of visual hallucinations, fluctuations, rapid eye movement (REM) sleep behavioral disorder, and parkinsonism. Neuropathologically, it is characterized by the presence of Lewy pathology. However, neuropathological studies have demonstrated the high prevalence of coexistent Alzheimer's disease, TAR DNA-binding protein 43 (TDP-43), and cerebrovascular pathologic cases. Due to their high prevalence and clinical impact on DLB individuals, clinical trials should account for these co-pathologies in their design and selection and the interpretation of biomarkers values and outcomes. Here we discuss the frequency of the different co-pathologies in DLB and their cross-sectional and longitudinal clinical impact. We then evaluate the utility and possible applications of disease-specific and disease-nonspecific biomarkers and how co-pathologies can impact these biomarkers. We propose a framework for integrating multi-modal biomarker fingerprints and step-wise selection and assessment of DLB individuals for clinical trials, monitoring target engagement, and interpreting outcomes in the setting of co-pathologies.
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Affiliation(s)
- Jon B Toledo
- Nantz National Alzheimer Center, Stanley H. Appel Department of Neurology, Houston Methodist Hospital, Houston, Texas, USA
| | - Carla Abdelnour
- Fundació ACE. Barcelona Alzheimer Treatment and Research Center, Universitat Autónoma de Barcelona, Barcelona, Spain
| | - Rimona S Weil
- Dementia Research Centre, Wellcome Centre for Human Neuroimaging, Movement Disorders Consortium, National Hospital for Neurology and Neurosurgery, University College London, London, UK
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer's Research, Karolinska Institutet, Stockholm, Sweden
| | | | - Andrea Pilotto
- Department of Clinical and Experimental Sciences, University of Brescia, Parkinson's Disease Rehabilitation Centre, FERB ONLUS-S, Isidoro Hospital, Trescore Balneario (BG), Italy
| | - Kathryn A Wyman-Chick
- HealthPartners Center for Memory and Aging and Struthers Parkinson's Center, Saint Paul, Minnesota, USA
| | - Michel J Grothe
- Instituto de Biomedicina de Sevilla (IBiS), Unidad de Trastornos del Movimiento, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Joseph P M Kane
- Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Angela Taylor
- Lewy Body Dementia Association, Lilburn, Georgia, USA
| | - Arvid Rongve
- Department of Research and Innovation, Institute of Clinical Medicine (K1), Haugesund Hospital, Norway and The University of Bergen, Bergen, Norway
| | - Sonja Scholz
- Department of Neurology, National Institute of Neurological Disorders and Stroke, Neurodegenerative Diseases Research Unit, Johns Hopkins University Medical Center, Baltimore, Maryland, USA
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, Ohio, USA
| | - Bradley F Boeve
- Department of Neurology and Center for Sleep Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Dag Aarsland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Ian G McKeith
- Newcastle University Translational and Clinical Research Institute (NUTCRI, Newcastle upon Tyne, UK
| | - Simon Lewis
- ForeFront Parkinson's Disease Research Clinic, School of Medical Sciences, Brain and Mind Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Iracema Leroi
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - John P Taylor
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
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Buchman AS, Leurgans SE, Kim N, Agrawal S, Oveisgharan S, Zammit AR, VanderHorst V, Nag S, Bennett DA. Alzheimer's Disease Pathology Outside of the Cerebrum Is Related to a Higher Odds of Dementia. J Alzheimers Dis 2023; 96:563-578. [PMID: 37840485 DOI: 10.3233/jad-230223] [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: 10/17/2023]
Abstract
BACKGROUND Assessments of Alzheimer's disease pathology do not routinely include lower brainstem, olfactory bulb, and spinal cord. OBJECTIVE Test if amyloid-β (Aβ) and paired helical filament (PHF) tau-tangles outside the cerebrum are associated with the odds of dementia. METHODS Autopsies were obtained in decedents with cognitive testing (n = 300). Aβ plaques and PHF tau-tangles were assessed in 24 sites: cerebrum (n = 14), brainstem (n = 5), olfactory bulb, and four spinal cord levels. Since spinal Aβ were absent in the first 165 cases, it was not assessed in the remaining cases. RESULTS Age at death was 91 years old. About 90% had Aβ in cerebrum and of these, half had Aβ in the brainstem. Of the latter, 85% showed Aβ in the olfactory bulb. All but one participant had tau-tangles in the cerebrum and 86% had brainstem tau-tangles. Of the latter, 80% had tau-tangles in olfactory bulb and 36% tau-tangles in one or more spinal cord levels. About 90% of adults with tau-tangles also had Aβ in one or more regions. In a logistic model controlling for demographics, Aβ and tau-tangles within the cerebrum, the presence of Aβ in olfactory bulb [OR, 1.74(1.00, 3.05)]; tau-tangles in brainstem [OR, 4.00(1.1.57,10.21)]; and spinal cord [OR, 1.87 (1.21,3.11)] were independently associated with higher odds of dementia. CONCLUSION Regional differences in Aβ and tau-tangle accumulation extend beyond cerebrum to spinal cord and their presence outside the cerebrum are associated with a higher odds of dementia. Further studies are needed to clarify the extent, burden, and consequences of AD pathology outside of cerebrum.
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Affiliation(s)
- Aron S Buchman
- Rush Alzheimer's Disease Research Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Sue E Leurgans
- Rush Alzheimer's Disease Research Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Namhee Kim
- Rush Alzheimer's Disease Research Center, Rush University Medical Center, Chicago, IL, USA
| | - Sonal Agrawal
- Rush Alzheimer's Disease Research Center, Rush University Medical Center, Chicago, IL, USA
- Department of Pathology, Rush University Medical Center, Chicago, IL, USA
| | - Shahram Oveisgharan
- Rush Alzheimer's Disease Research Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Andrea R Zammit
- Rush Alzheimer's Disease Research Center, Rush University Medical Center, Chicago, IL, USA
- Department of Behavioral Sciences, Rush University Medical Center, Chicago, IL, USA
| | | | - Sukrit Nag
- Rush Alzheimer's Disease Research Center, Rush University Medical Center, Chicago, IL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Research Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
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38
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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.
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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.
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Long JM, Coble DW, Xiong C, Schindler SE, Perrin RJ, Gordon BA, Benzinger TLS, Grant E, Fagan AM, Harari O, Cruchaga C, Holtzman DM, Morris JC. Preclinical Alzheimer's disease biomarkers accurately predict cognitive and neuropathological outcomes. Brain 2022; 145:4506-4518. [PMID: 35867858 PMCID: PMC10200309 DOI: 10.1093/brain/awac250] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 05/30/2022] [Accepted: 07/20/2022] [Indexed: 01/24/2023] Open
Abstract
Alzheimer's disease biomarkers are widely accepted as surrogate markers of underlying neuropathological changes. However, few studies have evaluated whether preclinical Alzheimer's disease biomarkers predict Alzheimer's neuropathology at autopsy. We sought to determine whether amyloid PET imaging or CSF biomarkers accurately predict cognitive outcomes and Alzheimer's disease neuropathological findings. This study included 720 participants, 42-91 years of age, who were enrolled in longitudinal studies of memory and aging in the Washington University Knight Alzheimer Disease Research Center and were cognitively normal at baseline, underwent amyloid PET imaging and/or CSF collection within 1 year of baseline clinical assessment, and had subsequent clinical follow-up. Cognitive status was assessed longitudinally by Clinical Dementia Rating®. Biomarker status was assessed using predefined cut-offs for amyloid PET imaging or CSF p-tau181/amyloid-β42. Subsequently, 57 participants died and underwent neuropathologic examination. Alzheimer's disease neuropathological changes were assessed using standard criteria. We assessed the predictive value of Alzheimer's disease biomarker status on progression to cognitive impairment and for presence of Alzheimer's disease neuropathological changes. Among cognitively normal participants with positive biomarkers, 34.4% developed cognitive impairment (Clinical Dementia Rating > 0) as compared to 8.4% of those with negative biomarkers. Cox proportional hazards modelling indicated that preclinical Alzheimer's disease biomarker status, APOE ɛ4 carrier status, polygenic risk score and centred age influenced risk of developing cognitive impairment. Among autopsied participants, 90.9% of biomarker-positive participants and 8.6% of biomarker-negative participants had Alzheimer's disease neuropathological changes. Sensitivity was 87.0%, specificity 94.1%, positive predictive value 90.9% and negative predictive value 91.4% for detection of Alzheimer's disease neuropathological changes by preclinical biomarkers. Single CSF and amyloid PET baseline biomarkers were also predictive of Alzheimer's disease neuropathological changes, as well as Thal phase and Braak stage of pathology at autopsy. Biomarker-negative participants who developed cognitive impairment were more likely to exhibit non-Alzheimer's disease pathology at autopsy. The detection of preclinical Alzheimer's disease biomarkers is strongly predictive of future cognitive impairment and accurately predicts presence of Alzheimer's disease neuropathology at autopsy.
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Affiliation(s)
- Justin M Long
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - Dean W Coble
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - Chengjie Xiong
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - Suzanne E Schindler
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - Richard J Perrin
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - Brian A Gordon
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - Tammie L S Benzinger
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - Elizabeth Grant
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - Anne M Fagan
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - Oscar Harari
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Department of Psychiatry, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - Carlos Cruchaga
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Department of Psychiatry, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - David M Holtzman
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
| | - John C Morris
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
- Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA
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Topçuoğlu ES, Akdemir ÜÖ, Atay LÖ. What is New in Nuclear Medicine Imaging for Dementia. Noro Psikiyatr Ars 2022; 59:S17-S23. [PMID: 36578980 PMCID: PMC9767133 DOI: 10.29399/npa.28155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 04/02/2022] [Indexed: 12/31/2022] Open
Abstract
Advances in the molecular biology, pathology and genetics of Alzheimer's disease (AD) and other degenerative dementias have led to the development of biomarkers specific to these diseases and radiotracers that are used in nuclear medicine. Imaging and non-imaging markers have enabled very early recognition of these diseases and have caused significant changes in their definitions. Amyloid positron emission tomography (PET) and tau PET, which are molecular imaging methods, [F18]fluorodeoxyglucose (FDG) PET showing the glucose metabolism pattern in the brain, dopamine transporter single photon emission computerized tomography (SPECT) that marks dopaminergic terminals are valuable tools for early recognition and differentiation of AD and its atypical variants, frontotemporal dementias and dementia with Lewy bodies. These imaging methods, which have different advantages over each other, have different indications for use and sometimes provide complementary information. In addition, research on radiotracers targeting neuroinflammation, astrocytes, synaptic density, and cholinergic terminals is ongoing. In this review, routinely used and newly developed nuclear imaging methods in AD and other neurodegenerative dementias, the agents used and their diagnostic features will be presented together with case examples.
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Affiliation(s)
- Esen Saka Topçuoğlu
- Hacettepe University Faculty of Medicine, Department of Neurology, Ankara, Turkey,Correspondence Address: Esen Saka Topçuoğlu, Maidan İş Merkezi, B-blok, 146 no’lu ofis, Mustafa Kemal Mah. Ankara, Turkey • E-mail:
| | - Ümit Özgür Akdemir
- Gazi University Faculty of Medicine, Department of Nuclear Medicine, Ankara, Turkey
| | - Lütfiye Özlem Atay
- Gazi University Faculty of Medicine, Department of Nuclear Medicine, Ankara, Turkey
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41
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Moscoso A, Karikari TK, Grothe MJ, Ashton NJ, Lantero-Rodriguez J, Snellman A, Zetterberg H, Blennow K, Schöll M. CSF biomarkers and plasma p-tau181 as predictors of longitudinal tau accumulation: Implications for clinical trial design. Alzheimers Dement 2022; 18:2614-2626. [PMID: 35226405 DOI: 10.1002/alz.12570] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 11/11/2021] [Accepted: 12/12/2021] [Indexed: 01/31/2023]
Abstract
INTRODUCTION Clinical trials targeting tau in Alzheimer's disease (AD) need to recruit individuals at risk of tau accumulation. Here, we studied cerebrospinal fluid (CSF) biomarkers and plasma phosphorylated tau (p-tau)181 as predictors of tau accumulation on positron emission tomography (PET) to evaluate implications for trial designs. METHODS We included older individuals who had serial tau-PET scans, baseline amyloid beta (Aβ)-PET, and baseline CSF biomarkers (n = 163) or plasma p-tau181 (n = 74). We studied fluid biomarker associations with tau accumulation and estimated trial sample sizes and screening failure reductions by implementing these markers into participant selection for trials. RESULTS P-tau181 in CSF and plasma predicted tau accumulation (r > 0.36, P < .001), even in AD-continuum individuals with normal baseline tau-PET (A+T-; r > 0.37, P < .05). Recruitment based on CSF biomarkers yielded comparable sample sizes to Aβ-PET. Prescreening with plasma p-tau181 reduced up to ≈50% of screening failures. DISCUSSION Clinical trials testing tau-targeting therapies may benefit from using fluid biomarkers to recruit individuals at risk of tau aggregation.
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Affiliation(s)
- Alexis Moscoso
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Michel J Grothe
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.,Unidad de Trastornos del Movimiento, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.,King's College London, Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, UK.,NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anniina Snellman
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Turku PET Centre, University of Turku, Turku, Finland
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK.,UK Dementia Research Institute at University College London, London, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Michael Schöll
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.,Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
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42
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Josephs KA, Tosakulwong N, Gatto RG, Weigand SD, Ali F, Botha H, Graff‐Radford J, Machulda MM, Savica R, Schwarz CG, Senjem ML, Boeve BF, Kantarci K, Jones DT, Ramanan VK, Fields JA, Reichard RR, Dickson DW, Petersen RC, Jack CR, Lowe VJ, Whitwell JL. Optimum Differentiation of Frontotemporal Lobar Degeneration from Alzheimer Disease Achieved with Cross-Sectional Tau Positron Emission Tomography. Ann Neurol 2022; 92:1016-1029. [PMID: 36054427 PMCID: PMC9804568 DOI: 10.1002/ana.26479] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 08/10/2022] [Accepted: 08/12/2022] [Indexed: 01/25/2023]
Abstract
OBJECTIVE This study was undertaken to assess cross-sectional and longitudinal [18 F]-flortaucipir positron emission tomography (PET) uptake in pathologically confirmed frontotemporal lobar degeneration (FTLD) and to compare FTLD to cases with high and low levels of Alzheimer disease (AD) neuropathologic changes (ADNC). METHODS One hundred forty-three participants who had completed at least one flortaucipir PET and had autopsy-confirmed FTLD (n = 52) or high (n = 58) or low ADNC (n = 33) based on Braak neurofibrillary tangle stages 0-IV versus V-VI were included. Flortaucipir standard uptake value ratios (SUVRs) were calculated for 9 regions of interest (ROIs): an FTLD meta-ROI, midbrain, globus pallidum, an AD meta-ROI, entorhinal, inferior temporal, orbitofrontal, precentral, and medial parietal. Linear mixed effects models were used to compare mean baseline SUVRs and annual rate of change in SUVR by group. Sensitivity and specificity to distinguish FTLD from high and low ADNC were calculated. RESULTS Baseline uptake in the FTLD meta-ROI, midbrain, and globus pallidus was greater in FTLD than high and low ADNC. No region showed a greater rate of flortaucipir accumulation in FTLD. Baseline uptake in the AD-related regions and orbitofrontal and precentral cortices was greater in high ADNC, and all showed greater rates of accumulation compared to FTLD. Baseline differences were superior to longitudinal rates in differentiating FTLD from high and low ADNC. A simple baseline metric of midbrain/inferior temporal ratio of flortaucipir uptake provided good to excellent differentiation between FTLD and high and low ADNC (sensitivities/specificities = 94%/95% and 71%/70%). INTERPRETATION There are cross-sectional and longitudinal differences in flortaucipir uptake between FTLD and high and low ADNC. However, optimum differentiation between FTLD and ADNC was achieved with baseline uptake rather than longitudinal rates. ANN NEUROL 2022;92:1016-1029.
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Affiliation(s)
| | | | | | | | - Farwa Ali
- Department of NeurologyMayo ClinicRochesterMNUSA
| | - Hugo Botha
- Department of NeurologyMayo ClinicRochesterMNUSA
| | | | - Mary M. Machulda
- Department of Psychiatry and PsychologyMayo ClinicRochesterMNUSA
| | | | | | - Matthew L. Senjem
- Department of RadiologyMayo ClinicRochesterMNUSA,Department of Information TechnologyMayo ClinicRochesterMNUSA
| | | | | | | | | | - Julie A. Fields
- Department of Psychiatry and PsychologyMayo ClinicRochesterMNUSA
| | - Ross R. Reichard
- Department of Laboratory Medicine and PathologyMayo ClinicRochesterMNUSA
| | - Dennis W. Dickson
- Department of Neuroscience (Neurogenetics)Mayo ClinicJacksonvilleFLUSA
| | | | | | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMNUSA
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Weigand AJ, Edwards L, Thomas KR, Bangen KJ, Bondi MW. Comprehensive characterization of elevated tau PET signal in the absence of amyloid-beta. Brain Commun 2022; 4:fcac272. [PMID: 36382220 PMCID: PMC9651027 DOI: 10.1093/braincomms/fcac272] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 07/07/2022] [Accepted: 10/24/2022] [Indexed: 02/03/2023] Open
Abstract
Recently proposed biomarker-only diagnostic frameworks propose that amyloid-beta is necessary for placement on the Alzheimer's disease continuum, whereas tau in the absence of amyloid-beta is considered to be a non-Alzheimer's disease pathologic change. Similarly, the pathologic designation of tau in the absence of amyloid-beta is characterized as primary age-related tauopathy and separable from Alzheimer's disease. Our study sought to identify an early-to-moderate tau stage with minimal amyloid-beta using PET imaging and characterize these individuals in terms of clinical, cognitive and biological features. Seven hundred and three participants from the Alzheimer's Disease Neuroimaging Initiative were classified into one of the four groups (A-/T-, A-/T+, A+/T- and A+/T+) based on PET positivity or negativity for cortical amyloid-beta (A-/A+) and early-to-moderate stage (i.e. meta-temporal) tau (T-/T+). These groups were then compared on demographic and clinical features, vascular risk, multi-domain neuropsychological performance, multi-domain subjective cognitive complaints, apolipoprotein E epsilon-4 carrier status and cortical thickness across Alzheimer's disease-vulnerable regions. The proportion of participants classified in each group was as follows: 47.23% A-/T-, 13.51% A-/T+, 12.23% A+/T- and 27.03% A+/T+. Results indicated that the A-/T+ and A+/T+ groups did not statistically differ on age, sex, depression levels, vascular risk and cortical thickness across temporal and parietal regions. Additionally, both A-/T+ and A+/T+ groups showed significant associations between memory performance and cortical thickness of temporal regions. Despite the different pathologic terminology used for A-/T+ and A+/T+, these groups did not statistically differ on a number of clinical, cognitive and biomarker features. Although it remains unclear whether A-/T+ reflects a pathologic construct separable from Alzheimer's disease, our results provide evidence that this group typically characterized as 'non-Alzheimer's pathologic change' or 'primary age-related tauopathy' should be given increased attention, given some similarities in cognitive and biomarker characteristics to groups traditionally considered to be on the Alzheimer's continuum.
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Affiliation(s)
- Alexandra J Weigand
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, CA 92120, USA
| | - Lauren Edwards
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, CA 92120, USA
| | - Kelsey R Thomas
- VA San Diego Healthcare System, San Diego, CA 92161, USA,Department of Psychiatry, University of California San Diego, San Diego, CA 92093, USA
| | - Katherine J Bangen
- VA San Diego Healthcare System, San Diego, CA 92161, USA,Department of Psychiatry, University of California San Diego, San Diego, CA 92093, USA
| | - Mark W Bondi
- Correspondence to: Mark W. Bondi, PhD ABPP-CN, VA San Diego Healthcare System (116B) 3350 La Jolla Village Drive, San Diego, CA 92161, USA E-mail:
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Wang R, Gao H, Xie H, Jia Z, Chen Q. Molecular imaging biomarkers in familial frontotemporal lobar degeneration: Progress and prospects. Front Neurol 2022; 13:933217. [PMID: 36051222 PMCID: PMC9424494 DOI: 10.3389/fneur.2022.933217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 07/25/2022] [Indexed: 12/01/2022] Open
Abstract
Familial frontotemporal lobar degeneration (FTLD) is a pathologically heterogeneous group of neurodegenerative diseases with diverse genotypes and clinical phenotypes. Three major mutations were reported in patients with familial FTLD, namely, progranulin (GRN), microtubule-associated protein tau (MAPT), and the chromosome 9 open reading frame 72 (C9orf72) repeat expansion, which could cause neurodegenerative pathological changes years before symptom onset. Noninvasive quantitative molecular imaging with PET or single-photon emission CT (SPECT) allows for selective visualization of the molecular targets in vivo to investigate brain metabolism, perfusion, neuroinflammation, and pathophysiological changes. There was increasing evidence that several molecular imaging biomarkers tend to serve as biomarkers to reveal the early brain abnormalities in familial FTLD. Tau-PET with 18F-flortaucipir and 11C-PBB3 demonstrated the elevated tau position in patients with FTLD and also showed the ability to differentiate patterns among the different subtypes of the mutations in familial FTLD. Furthermore, dopamine transporter imaging with the 11C-DOPA and 11C-CFT in PET and the 123I-FP-CIT in SPECT revealed the loss of dopaminergic neurons in the asymptomatic and symptomatic patients of familial FTLD. In addition, PET imaging with the 11C-MP4A has demonstrated reduced acetylcholinesterase (AChE) activity in patients with FTLD, while PET with the 11C-DAA1106 and 11C-PK11195 revealed an increased level of microglial activation associated with neuroinflammation even before the onset of symptoms in familial FTLD. 18F-fluorodeoxyglucose (FDG)-PET indicated hypometabolism in FTLD with different mutations preceded the atrophy on MRI. Identifying molecular imaging biomarkers for familial FTLD is important for the in-vivo assessment of underlying pathophysiological changes with disease progression and future disease-modifying therapy. We review the recent progress of molecular imaging in familial FTLD with focused on the possible implication of these techniques and their prospects in specific mutation types.
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Affiliation(s)
- Ruihan Wang
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, China
| | - Hui Gao
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, China
| | - Hongsheng Xie
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Zhiyun Jia
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Qin Chen
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, China
- *Correspondence: Qin Chen
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Focal amyloid and asymmetric tau in an imaging-to-autopsy case of clinical primary progressive aphasia with Alzheimer disease neuropathology. Acta Neuropathol Commun 2022; 10:111. [PMID: 35945628 PMCID: PMC9361632 DOI: 10.1186/s40478-022-01412-w] [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] [Received: 05/24/2022] [Accepted: 07/17/2022] [Indexed: 01/21/2023] Open
Abstract
Quantification of in vivo amyloid and tau PET imaging relationships with postmortem measurements are critical for validating the sensitivity and specificity imaging biomarkers across clinical phenotypes with Alzheimer disease neuropathologic change (ADNC). This study examined the quantitative relationship between regional binding of in vivo 18F-florbetapir amyloid PET and 18F-flortaucipir tau PET with postmortem stereological counts of amyloid plaques and neurofibrillary tangles (NFT) in a case of primary progressive aphasia (PPA) with ADNC, where neurodegeneration asymmetrically targets the left hemisphere. Beginning 2 years prior to death, a 63-year-old right-handed man presenting with agrammatic variant PPA underwent a florbetapir and flortaucpir PET scan, and neuropsychological assessments and magnetic resonance imaging sessions every 6 months. Florbetapir and flortaucpir PET standard uptake value ratios (SUVRs) were quantified from 8 left and right hemisphere brain regions with stereological quantification of amyloid plaques and NFTs from corresponding postmortem sections. Pearson's correlations and measures of asymmetry were used to examine relationships between imaging and autopsy measurements. The three visits prior to death revealed decline of language measures, with marked progression of atrophy. Florbetapir PET presented with an atypical focal pattern of uptake and showed a significant positive correlation with postmortem amyloid plaque density across the 8 regions (r = 0.92; p = 0.001). Flortaucipir PET had a left-lateralized distribution and showed a significant positive correlation with NFT density (r = 0.78; p = 0.023). Flortaucipir PET and NFT density indicated a medial temporal lobe sparing presentation of ADNC, demonstrating that AD does not always target the medial temporal lobe. This study adds additional evidence, in a non-amnestic phenotype of ADNC, that there is a strong correlation between AD PET biomarkers, florbetapir and flortaucipir, with quantitative neuropathology. The atypical and focal presentation of plaque density and florbetapir PET uptake suggests not all amyloid pathology presents as diffuse across neocortex.
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Asken BM, Tanner JA, VandeVrede L, Mantyh WG, Casaletto KB, Staffaroni AM, La Joie R, Iaccarino L, Soleimani-Meigooni D, Rojas JC, Gardner RC, Miller BL, Grinberg LT, Boxer AL, Kramer JH, Rabinovici GD. Plasma P-tau181 and P-tau217 in Patients With Traumatic Encephalopathy Syndrome With and Without Evidence of Alzheimer Disease Pathology. Neurology 2022; 99:e594-e604. [PMID: 35577574 PMCID: PMC9442622 DOI: 10.1212/wnl.0000000000200678] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 03/18/2022] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Traumatic encephalopathy syndrome (TES) has overlapping clinical symptoms with Alzheimer disease (AD). AD pathology commonly co-occurs with chronic traumatic encephalopathy (CTE) pathology. There are currently no validated CTE biomarkers. AD-specific biomarkers such as plasma P-tau181 and P-tau217 may help to identify patients with TES who have AD pathology. METHODS We measured plasma P-tau181 and P-tau217 (Meso Scale Discovery electrochemiluminescence) in patients with TES, mild cognitive impairment/dementia with biomarker-confirmed AD ("AD"), and healthy controls ("HC"). Patients underwent amyloid-beta (Aβ)-PET and a subset underwent tau-PET using [18F]Flortaucipir. We compared plasma P-tau levels controlling for age and sex and also performed AUC analyses to evaluate the accuracy of group differentiation. In patients with TES, we evaluated associations between plasma P-tau, years of repetitive head impact exposure, and tau-PET. Four TES patients with autopsy-confirmed CTE were described qualitatively. RESULTS The sample included 131 participants (TES, N = 18; AD, N = 65; HC, N = 48). Aβ(+) patients with TES (N = 10), but not Aβ(-) TES, had significantly higher plasma P-tau levels than HC (P-tau181: p < 0.001, d = 1.34; P-tau217: p < 0.001, d = 1.59). There was a trend for Aβ(+) TES having higher plasma P-tau than Aβ(-) TES (P-tau181: p = 0.06, d = 1.06; P-tau217: p = 0.09, d = 0.93). AUC analyses showed good classification of Aβ(+) TES from HC for P-tau181 (AUC = 0.87 [0.71-1.00]) and P-tau217 (AUC = 0.93 [0.86-1.00]). Plasma P-tau217 showed fair differentiation of Aβ(+) TES from Aβ(-) TES (AUC = 0.79 [0.54-1.00], p = 0.04), whereas classification accuracy of P-tau181 was slightly lower and not statistically significant (AUC = 0.71 [0.46-0.96], p = 0.13). Patients with AD had higher tau-PET tracer uptake than Aβ(+) TES and were well differentiated using P-tau181 (AUC = 0.81 [0.68-0.94]) and P-tau217 (AUC = 0.86 [0.73-0.98]). Plasma P-tau correlated with the tau-PET signal in Aβ(+) TES but not in Aβ(-) TES, and there was no association between plasma P-tau and years of repetitive head impact exposure. TES patients with severe CTE and no AD at autopsy had low P-tau181 and P-tau217 levels. DISCUSSION Measuring P-tau181 and P-tau217 in plasma may be a feasible and scalable fluid biomarker for identifying AD pathology in TES. Low plasma P-tau levels may be used to increase clinical suspicion of CTE over AD as a primary pathology in TES. Currently, there is no support for P-tau181 or P-tau217 as in vivo biomarkers of CTE tau. Larger studies of patients with pathologically confirmed CTE are needed. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that (1) among patients with TES and abnormal Aβ-PET scans, elevated plasma P-tau can differentiate between affected individuals and HCs; (2) low plasma P-tau may help identify patients with TES who do not have Alzheimer; and (3) plasma P-tau181 and P-tau217 are not useful biomarkers of patients with TES who do not have AD.
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Affiliation(s)
- Breton M Asken
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco.
| | - Jeremy A Tanner
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Lawren VandeVrede
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - William G Mantyh
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Kaitlin B Casaletto
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Adam M Staffaroni
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Renaud La Joie
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Leonardo Iaccarino
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - David Soleimani-Meigooni
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Julio C Rojas
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Raquel C Gardner
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Bruce L Miller
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Lea T Grinberg
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Adam L Boxer
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Joel H Kramer
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
| | - Gil D Rabinovici
- From the Memory and Aging Center (B.M.A.T.C., J.A.T., L.V., W.G.M., K.B.C., A.M.S., R.L.J., L.I., D.S.-M., J.C.R., R.C.G., B.L.M., L.T.G., A.L.B., J.H.K., G.D.R.), Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; Department of Neurology (W.G.M.), University of Minnesota, Minneapolis; San Francisco Veterans Affairs Medical Center (R.C.G.); and Department of Radiology & Biomedical Imaging, University of California (G.D.R.), San Francisco
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Malpetti M, Kaalund SS, Tsvetanov KA, Rittman T, Briggs M, Allinson KSJ, Passamonti L, Holland N, Jones PS, Fryer TD, Hong YT, Kouli A, Bevan-Jones WR, Mak E, Savulich G, Spillantini MG, Aigbirhio FI, Williams-Gray CH, O'Brien JT, Rowe JB. In Vivo 18F-Flortaucipir PET Does Not Accurately Support the Staging of Progressive Supranuclear Palsy. J Nucl Med 2022; 63:1052-1057. [PMID: 34795013 PMCID: PMC7612961 DOI: 10.2967/jnumed.121.262985] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 10/08/2021] [Indexed: 02/02/2023] Open
Abstract
Progressive supranuclear palsy (PSP) is a neurodegenerative disorder characterized by neuroglial tau pathology. A new staging system for PSP pathology postmortem has been described and validated. We used a data-driven approach to test whether postmortem pathologic staging in PSP can be reproduced in vivo with 18F-flortaucipir PET. Methods: Forty-two patients with probable PSP and 39 controls underwent 18F-flortaucipir PET. Conditional inference tree analyses on regional binding potential values identified absent/present pathology thresholds to define in vivo staging. Following the postmortem staging approach for PSP pathology, we evaluated the combinations of absent/present pathology (or abnormal/normal PET signal) across all regions to assign each participant to in vivo stages. ANOVA was applied to analyze differences among means of disease severity between stages. In vivo staging was compared with postmortem staging in 9 patients who also had postmortem confirmation of the diagnosis and stage. Results: Stage assignment was estimable in 41 patients: 10, 26, and 5 patients were classified in stage I/II, stage III/IV, and stage V/VI, respectively, whereas 1 patient was not classifiable. Explorative substaging identified 2 patients in stage I, 8 in stage II, 9 in stage III, 17 in stage IV, and 5 in stage V. However, the nominal 18F-flortaucipir--derived stage was not associated with clinical severity and was not indicative of pathology staging postmortem. Conclusion:18F-flortaucipir PET in vivo does not correspond to neuropathologic staging in PSP. This analytic approach, seeking to mirror in vivo neuropathology staging with PET-to-autopsy correlational analyses, might enable in vivo staging with next-generation tau PET tracers; however, further evidence and comparisons with postmortem data are needed.
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Affiliation(s)
- Maura Malpetti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom;
| | - Sanne S Kaalund
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Kamen A Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Timothy Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Mayen Briggs
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Cambridge University Brain Bank, Cambridge, United Kingdom
| | - Kieren S J Allinson
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Cambridge University Brain Bank, Cambridge, United Kingdom
| | - Luca Passamonti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Istituto di Bioimmagini e Fisiologia Molecolare (IBFM), Consiglio Nazionale delle Ricerche (CNR), Milano, Italy
| | - Negin Holland
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - P Simon Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Tim D Fryer
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, United Kingdom
| | - Young T Hong
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, United Kingdom
| | - Antonina Kouli
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - W Richard Bevan-Jones
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; and
| | - Elijah Mak
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; and
| | - George Savulich
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; and
| | | | - Franklin I Aigbirhio
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, United Kingdom
| | - Caroline H Williams-Gray
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - John T O'Brien
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; and
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
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Laforce RJ, Dallaire-Théroux C, Racine AM, Dent G, Salinas-Valenzuela C, Poulin E, Cayer AM, Bédard-Tremblay D, Rouleau-Bonenfant T, St-Onge F, Schraen-Maschke S, Beauregard JM, Sergeant N, Puymirat J. Tau positron emission tomography, cerebrospinal fluid and plasma biomarkers of neurodegeneration, and neurocognitive testing: an exploratory study of participants with myotonic dystrophy type 1. J Neurol 2022; 269:3579-3587. [PMID: 35103843 PMCID: PMC9217820 DOI: 10.1007/s00415-022-10970-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 01/11/2022] [Accepted: 01/11/2022] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To investigate Tau pathology using multimodal biomarkers of neurodegeneration and neurocognition in participants with myotonic dystrophy type 1 (DM1). METHODS We recruited twelve participants with DM1 and, for comparison, two participants with Alzheimer's Disease (AD). Participants underwent cognitive screening and social cognition testing using the Dépistage Cognitif de Québec (DCQ), among other tests. Biomarkers included Tau PET with [18F]-AV-1451, CSF (Aβ, Tau, phospho-Tau), and plasma (Aβ, Tau, Nf-L, GFAP) studies. RESULTS Of the twelve DM1 participants, seven completed the full protocol (Neurocognition 11/12; PET 7/12, CSF 9/12, plasma 12/12). Three DM1 participants were cognitively impaired (CI). On average, CI DM1 participants had lower scores on the DCQ compared to cognitively unimpaired (CU) DM1 participants (75.5/100 vs. 91.4/100) and were older (54 vs. 44 years old) but did not differ in years of education (11.3 vs. 11.1). The majority (6/7) of DM1 participants had no appreciable PET signal. Only one of the CI participants presented with elevated Tau PET SUVR in bilateral medial temporal lobes. This participant was the eldest and most cognitively impaired, and had the lowest CSF Aβ 1-42 and the highest CSF Tau levels, all suggestive of co-existing AD. CSF Tau and phospho-Tau levels were higher in the 3 CI compared to CU DM1 participants, but with a mean value lower than that typically observed in AD. Nf-L and GFAP were elevated in most DM1 participants (9/11 and 8/11, respectively). Finally, CSF phospho-Tau was significantly correlated with plasma Nf-L concentrations. CONCLUSIONS AND RELEVANCE We observed heterogenous cognitive and biomarker profiles in individuals with DM1. While some participants presented with abnormal PET and/or CSF Tau, these patterns were highly variable and only present in a small subset. Although DM1 may indeed represent a non-AD Tauopathy, the Tau-PET tracer used in this study was unable to detect an in vivo Tau DM1 signature in this small cohort. Interestingly, most DM1 participants presented with elevated plasma Nf-L and GFAP levels, suggestive of other, possibly related, central brain alterations which motivate further research. This pioneering study provides novel insights towards the potential relationship between biomarkers and neurocognitive deficits commonly seen in DM1.
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Affiliation(s)
- Robert Jr Laforce
- Clinique Interdisciplinaire de Mémoire, CHU de Québec, Québec, QC, Canada.
| | | | | | | | | | - Elizabeth Poulin
- Clinique Interdisciplinaire de Mémoire, CHU de Québec, Québec, QC, Canada
| | - Anne-Marie Cayer
- Clinique Interdisciplinaire de Mémoire, CHU de Québec, Québec, QC, Canada
| | | | | | - Frédéric St-Onge
- Clinique Interdisciplinaire de Mémoire, CHU de Québec, Québec, QC, Canada
| | - Susanna Schraen-Maschke
- Université de Lille, Inserm UMRS1172, CHU Lille, Lille, France
- Alzheimer & Tauopathies, LabEx DISTALZ, Lille, France
| | | | - Nicolas Sergeant
- Université de Lille, Inserm UMRS1172, CHU Lille, Lille, France
- Alzheimer & Tauopathies, LabEx DISTALZ, Lille, France
| | - Jack Puymirat
- Clinique Interdisciplinaire de Mémoire, CHU de Québec, Québec, QC, Canada
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Koga S, Josephs KA, Aiba I, Yoshida M, Dickson DW. Neuropathology and emerging biomarkers in corticobasal syndrome. J Neurol Neurosurg Psychiatry 2022; 93:jnnp-2021-328586. [PMID: 35697501 PMCID: PMC9380481 DOI: 10.1136/jnnp-2021-328586] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 05/18/2022] [Indexed: 11/05/2022]
Abstract
Corticobasal syndrome (CBS) is a clinical syndrome characterised by progressive asymmetric limb rigidity and apraxia with dystonia, myoclonus, cortical sensory loss and alien limb phenomenon. Corticobasal degeneration (CBD) is one of the most common underlying pathologies of CBS, but other disorders, such as progressive supranuclear palsy (PSP), Alzheimer's disease (AD) and frontotemporal lobar degeneration with TDP-43 inclusions, are also associated with this syndrome.In this review, we describe common and rare neuropathological findings in CBS, including tauopathies, synucleinopathies, TDP-43 proteinopathies, fused in sarcoma proteinopathy, prion disease (Creutzfeldt-Jakob disease) and cerebrovascular disease, based on a narrative review of the literature and clinicopathological studies from two brain banks. Genetic mutations associated with CBS, including GRN and MAPT, are also reviewed. Clinicopathological studies on neurodegenerative disorders associated with CBS have shown that regardless of the underlying pathology, frontoparietal, as well as motor and premotor pathology is associated with CBS. Clinical features that can predict the underlying pathology of CBS remain unclear. Using AD-related biomarkers (ie, amyloid and tau positron emission tomography (PET) and fluid biomarkers), CBS caused by AD often can be differentiated from other causes of CBS. Tau PET may help distinguish AD from other tauopathies and non-tauopathies, but it remains challenging to differentiate non-AD tauopathies, especially PSP and CBD. Although the current clinical diagnostic criteria for CBS have suboptimal sensitivity and specificity, emerging biomarkers hold promise for future improvements in the diagnosis of underlying pathology in patients with CBS.
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Affiliation(s)
- Shunsuke Koga
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Ikuko Aiba
- Department of Neurology, National Hospital Organization Higashinagoya National Hospital, Nagoya, Aichi, Japan
| | - Mari Yoshida
- Institute for Medical Science of Aging, Aichi Medical University, Nagakute, Aichi, Japan
| | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
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50
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Wu Y, Wu X, Gao L, Yan Y, Geng Z, Zhou S, Zhu W, Tian Y, Yu Y, Wei L, Wang K. Abnormal Functional Connectivity of Thalamic Subdivisions in Alzheimer's Disease: A Functional Magnetic Resonance Imaging Study. Neuroscience 2022; 496:73-82. [PMID: 35690336 DOI: 10.1016/j.neuroscience.2022.06.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 04/23/2022] [Accepted: 06/02/2022] [Indexed: 12/01/2022]
Abstract
Alzheimer's disease (AD) is characterized by global cognitive impairment in multiple cognitive domains. Thalamic dysfunction during AD progression has been reported. However, there are limited studies regarding dysfunction in the functional connectivity (FC) of thalamic subdivisions and the relationship between such dysfunction and clinical assessments. This study examined dysfunction in the FC of thalamic subdivisions and determined the relationship between such dysfunction and clinical assessments. Forty-eight patients with AD and 47 matched healthy controls were recruited and assessed with scales for multiple cognitive domains. Group-wise comparisons of FC with thalamic subdivisions as seed points were conducted to identify abnormal cerebral regions. Moreover, correlation analysis was conducted to evaluate the relationship between abnormal FC and cognitive performance. Decreased FC of the intralaminar and medial nuclei with the left precuneus was observed in patients but not in heathy controls. The abnormal FC of the medial nuclei with the left precuneus was correlated with the Mini Mental State Examination score in the patient group. Using the FC values showing between-group differences, the linear support vector machine classifier achieved quite good in accuracy, sensitivity, specificity and area under the curve. Dysfunction in the FC of the intralaminar and medial thalamus with the precuneus may comprise a potential neural substrate for cognitive impairment during AD progression, which in turn may provide new treatment targets.
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Affiliation(s)
- Yue Wu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui 230022, China
| | - Xingqi Wu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui 230022, China
| | - Liying Gao
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui 230022, China
| | - Yibing Yan
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui 230022, China
| | - Zhi Geng
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui 230022, China; Department of Neurology, Second People's Hospital of Hefei City, The Hefei Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China
| | - Shanshan Zhou
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui 230022, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province 230022, China
| | - Wanqiu Zhu
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui 230022, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, Anhui 230088, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province 230022, China
| | - Yongqiang Yu
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China.
| | - Ling Wei
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui 230022, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province 230022, China.
| | - Kai Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui 230022, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, Anhui 230088, China; The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui Province 230032, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province 230022, China.
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