1
|
Rodriguez-Vieitez E, Kumar A, Malarte ML, Ioannou K, Rocha FM, Chiotis K. Imaging Neuroinflammation: Quantification of Astrocytosis in a Multitracer PET Approach. Methods Mol Biol 2024; 2785:195-218. [PMID: 38427196 DOI: 10.1007/978-1-0716-3774-6_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
The recent progress in the development of in vivo biomarkers is rapidly changing how neurodegenerative diseases are conceptualized and diagnosed and how clinical trials are designed today. Alzheimer's disease (AD) - the most common neurodegenerative disorder - is characterized by a complex neuropathology involving the deposition of extracellular amyloid-β (Aβ) plaques and intracellular neurofibrillary tangles (NFTs) of hyperphosphorylated tau proteins, accompanied by the activation of glial cells, i.e., astrocytes and microglia, and neuroinflammatory response, leading to neurodegeneration and cognitive dysfunction. An increasing diversity of positron emission tomography (PET) imaging radiotracers is available to selectively target the different pathophysiological processes of AD. Along with the success of Aβ PET and the more recent tau PET imaging, there is a great interest to develop PET tracers to image glial reactivity and neuroinflammation. While most research to date has focused on imaging microgliosis, there is an upsurge of interest in imaging reactive astrocytes in the AD continuum. There is increasing evidence that reactive astrocytes are morphologically and functionally heterogeneous, with different subtypes that express different markers and display various homeostatic or detrimental roles across disease stages. Therefore, multiple biomarkers are desirable to unravel the complex phenomenon of reactive astrocytosis. In the field of in vivo PET imaging in AD, the research concerning reactive astrocytes has predominantly focused on targeting monoamine oxidase B (MAO-B), most often using either 11C-deuterium-L-deprenyl (11C-DED) or 18F-SMBT-1 PET tracers. Additionally, imidazoline2 binding (I2BS) sites have been imaged using 11C-BU99008 PET. Recent studies in our group using 11C-DED PET imaging suggest that astrocytosis may be present from the early stages of disease development in AD. This chapter provides a detailed description of the practical approach used for the analysis of 11C-DED PET imaging data in a multitracer PET paradigm including 11C-Pittsburgh compound B (11C-PiB) and 18F-fluorodeoxyglucose (18F-FDG). The multitracer PET approach allows investigating the comparative regional and temporal patterns of in vivo brain astrocytosis, fibrillar Aβ deposition, glucose metabolism, and brain structural changes. It may also contribute to understanding the potential role of novel plasma biomarkers of reactive astrocytes, in particular the glial fibrillary acidic protein (GFAP), at different stages of disease progression. This chapter attempts to stimulate further research in the field, including the development of novel PET tracers that may allow visualizing different aspects of the complex astrocytic and microglial response in neurodegenerative diseases. Progress in the field will contribute to the incorporation of PET imaging of glial reactivity and neuroinflammation as biomarkers with clinical application and motivate further investigation on glial cells as therapeutic targets in AD and other neurodegenerative diseases.
Collapse
Affiliation(s)
- Elena Rodriguez-Vieitez
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
- Division of Neurogeriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
| | - Amit Kumar
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Mona-Lisa Malarte
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Ioannou
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Filipa M Rocha
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| |
Collapse
|
2
|
Oeckl P, Bluma M, Bucci M, Halbgebauer S, Chiotis K, Sandebring-Matton A, Ashton NJ, Molfetta GD, Grötschel L, Kivipelto M, Blennow K, Zetterberg H, Savitcheva I, Nordberg A, Otto M. Blood β-synuclein is related to amyloid PET positivity in memory clinic patients. Alzheimers Dement 2023; 19:4896-4907. [PMID: 37052206 DOI: 10.1002/alz.13046] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 01/20/2023] [Accepted: 01/24/2023] [Indexed: 04/14/2023]
Abstract
INTRODUCTION β-synuclein is an emerging blood biomarker to study synaptic degeneration in Alzheimer´s disease (AD), but its relation to amyloid-β (Αβ) pathology is unclear. METHODS We investigated the association of plasma β-synuclein levels with [18F] flutemetamol positron emission tomography (PET) in patients with AD dementia (n = 51), mild cognitive impairment (MCI-Aβ+ n = 18, MCI- Aβ- n = 30), non-AD dementias (n = 22), and non-demented controls (n = 5). RESULTS Plasma β-synuclein levels were higher in Aβ+ (AD dementia, MCI-Aβ+) than in Aβ- subjects (non-AD dementias, MCI-Aβ-) with good discrimination of Aβ+ from Aβ- subjects and prediction of Aβ status in MCI individuals. A positive correlation between plasma β-synuclein and Aβ PET was observed in multiple cortical regions across all lobes. DISCUSSION Plasma β-synuclein demonstrated discriminative properties for Aβ PET positive and negative subjects. Our data underline that β-synuclein is not a direct marker of Aβ pathology and suggest different longitudinal dynamics of synaptic degeneration versus amyloid deposition across the AD continuum. HIGHLIGHTS Blood and CSF β-synuclein levels are higher in Aβ+ than in Aβ- subjects. Blood β-synuclein level correlates with amyloid PET positivity in multiple regions. Blood β-synuclein predicts Aβ status in MCI individuals.
Collapse
Affiliation(s)
- Patrick Oeckl
- German Center for Neurodegenerative Diseases e.V. (DZNE), Ulm, Germany
- Department of Neurology, Ulm University Hospital, Ulm, Germany
| | - Marina Bluma
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
| | - Marco Bucci
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Steffen Halbgebauer
- German Center for Neurodegenerative Diseases e.V. (DZNE), Ulm, Germany
- Department of Neurology, Ulm University Hospital, Ulm, Germany
| | - Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Sandebring-Matton
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Lana Grötschel
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Karolinska University, Stockholm, Sweden
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Markus Otto
- Department of Neurology, Ulm University Hospital, Ulm, Germany
- University Clinic and Polyclinic for Neurology, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| |
Collapse
|
3
|
Chiotis K, Johansson C, Rodriguez-Vieitez E, Ashton NJ, Blennow K, Zetterberg H, Graff C, Nordberg A. Tracking reactive astrogliosis in autosomal dominant and sporadic Alzheimer's disease with multi-modal PET and plasma GFAP. Mol Neurodegener 2023; 18:60. [PMID: 37697307 PMCID: PMC10496408 DOI: 10.1186/s13024-023-00647-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 08/07/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND Plasma assays for the detection of Alzheimer's disease neuropathological changes are receiving ever increasing interest. The concentration of plasma glial fibrillary acidic protein (GFAP) has been suggested as a potential marker of astrocytes or recently, amyloid-β burden, although this hypothesis remains unproven. We compared plasma GFAP levels with the astrocyte tracer 11C-Deuterium-L-Deprenyl (11C-DED) in a multi-modal PET design in participants with sporadic and Autosomal Dominant Alzheimer's disease. METHODS Twenty-four individuals from families with known Autosomal Dominant Alzheimer's Disease mutations (mutation carriers = 10; non-carriers = 14) and fifteen patients with sporadic Alzheimer's disease were included. The individuals underwent PET imaging with 11C-DED, 11C-PIB and 18F-FDG, as markers of reactive astrogliosis, amyloid-β deposition, and glucose metabolism, respectively, and plasma sampling for measuring GFAP concentrations. Twenty-one participants from the Autosomal Dominant Alzheimer's Disease group underwent follow-up plasma sampling and ten of these participants underwent follow-up PET imaging. RESULTS In mutation carriers, plasma GFAP levels and 11C-PIB binding increased, while 11C-DED binding and 18F-FDG uptake significantly decreased across the estimated years to symptom onset. Cross-sectionally, plasma GFAP demonstrated a negative correlation with 11C-DED binding in both mutation carriers and patients with sporadic disease. Plasma GFAP indicated cross-sectionally a significant positive correlation with 11C-PIB binding and a significant negative correlation with 18F-FDG in the whole sample. The longitudinal levels of 11C-DED binding showed a significant negative correlation with longitudinal plasma GFAP concentrations over the follow-up interval. CONCLUSIONS Plasma GFAP concentration and astrocyte 11C-DED brain binding levels followed divergent trajectories and may reflect different underlying processes. The strong negative association between plasma GFAP and 11C-DED binding in Autosomal Dominant and sporadic Alzheimer's disease brains may indicate that if both are markers of reactive astrogliosis, they may detect different states or subtypes of astrogliosis. Increased 11C-DED brain binding seems to be an earlier phenomenon in Alzheimer's disease progression than increased plasma GFAP concentration.
Collapse
Affiliation(s)
- Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Charlotte Johansson
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Elena Rodriguez-Vieitez
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 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
| | - 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
| | - 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 UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, University of Wisconsin-Madison, Madison, WI, USA
| | - Caroline Graff
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
- Unit for Hereditary Dementia, Karolinska University Hospital-Solna, Solna, Sweden
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden.
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden.
| |
Collapse
|
4
|
Bucci M, Bluma M, Savitcheva I, Ashton NJ, Chiotis K, Matton A, Kivipelto M, Di Molfetta G, Blennow K, Zetterberg H, Nordberg A. Profiling of plasma biomarkers in the context of memory assessment in a tertiary memory clinic. Transl Psychiatry 2023; 13:268. [PMID: 37491358 PMCID: PMC10368630 DOI: 10.1038/s41398-023-02558-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 06/24/2023] [Accepted: 07/03/2023] [Indexed: 07/27/2023] Open
Abstract
Plasma biomarkers have shown promising performance in research cohorts in discriminating between different stages of Alzheimer's disease (AD). Studies in clinical populations are necessary to provide insights on the clinical utility of plasma biomarkers before their implementation in real-world settings. Here we investigated plasma biomarkers (glial fibrillary acidic protein (GFAP), tau phosphorylated at 181 and 231 (pTau181, pTau231), amyloid β (Aβ) 42/40 ratio, neurofilament light) in 126 patients (age = 65 ± 8) who were admitted to the Clinic for Cognitive Disorders, at Karolinska University Hospital. After extensive clinical assessment (including CSF analysis), patients were classified as: mild cognitive impairment (MCI) (n = 75), AD (n = 25), non-AD dementia (n = 16), no dementia (n = 9). To refine the diagnosis, patients were examined with [18F]flutemetamol PET (Aβ-PET). Aβ-PET images were visually rated for positivity/negativity and quantified in Centiloid. Accordingly, 68 Aβ+ and 54 Aβ- patients were identified. Plasma biomarkers were measured using single molecule arrays (SIMOA). Receiver-operated curve (ROC) analyses were performed to detect Aβ-PET+ using the different biomarkers. In the whole cohort, the Aβ-PET centiloid values correlated positively with plasma GFAP, pTau231, pTau181, and negatively with Aβ42/40 ratio. While in the whole MCI group, only GFAP was associated with Aβ PET centiloid. In ROC analyses, among the standalone biomarkers, GFAP showed the highest area under the curve discriminating Aβ+ and Aβ- compared to other plasma biomarkers. The combination of plasma biomarkers via regression was the most predictive of Aβ-PET, especially in the MCI group (prior to PET, n = 75) (sensitivity = 100%, specificity = 82%, negative predictive value = 100%). In our cohort of memory clinic patients (mainly MCI), the combination of plasma biomarkers was sensitive in ruling out Aβ-PET negative individuals, thus suggesting a potential role as rule-out tool in clinical practice.
Collapse
Affiliation(s)
- Marco Bucci
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Marina Bluma
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Karolinska University, SE-14186, Stockholm, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
| | - Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Anna Matton
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, SE-43180, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, SE-43180, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1N 3BG, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden.
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden.
| |
Collapse
|
5
|
Fontana IC, Scarpa M, Malarte ML, Rocha FM, Ausellé-Bosch S, Bluma M, Bucci M, Chiotis K, Kumar A, Nordberg A. Astrocyte Signature in Alzheimer's Disease Continuum through a Multi-PET Tracer Imaging Perspective. Cells 2023; 12:1469. [PMID: 37296589 PMCID: PMC10253101 DOI: 10.3390/cells12111469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 05/02/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023] Open
Abstract
Reactive astrogliosis is an early event in the continuum of Alzheimer's disease (AD). Current advances in positron emission tomography (PET) imaging provide ways of assessing reactive astrogliosis in the living brain. In this review, we revisit clinical PET imaging and in vitro findings using the multi-tracer approach, and point out that reactive astrogliosis precedes the deposition of Aβ plaques, tau pathology, and neurodegeneration in AD. Furthermore, considering the current view of reactive astrogliosis heterogeneity-more than one subtype of astrocyte involved-in AD, we discuss how astrocytic body fluid biomarkers might fit into trajectories different from that of astrocytic PET imaging. Future research focusing on the development of innovative astrocytic PET radiotracers and fluid biomarkers may provide further insights into the heterogeneity of reactive astrogliosis and improve the detection of AD in its early stages.
Collapse
Affiliation(s)
- Igor C. Fontana
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Miriam Scarpa
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Mona-Lisa Malarte
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Filipa M. Rocha
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
- Instituto de Ciência Biomédicas Abel Salazar da Universidade do Porto, 4050-313 Porto, Portugal
- Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, Portugal
| | - Sira Ausellé-Bosch
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
- Faculty of Health and Life Sciences, Pompeu Fabra University, 08003 Barcelona, Spain
| | - Marina Bluma
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Marco Bucci
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Amit Kumar
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, 141 57 Stockholm, Sweden
| |
Collapse
|
6
|
Ioannou K, Bucci M, Nordberg AK, Chiotis K. High tau PET binding reveals a constellation of beta‐amyloid positivity and fast cognitive decline. Alzheimers Dement 2022. [DOI: 10.1002/alz.067074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Konstantinos Ioannou
- Nordberg Translational Molecular Imaging Lab, Division of Clinical Geriatrics, Center for Alzheimer’s Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet Stockholm Sweden
| | - Marco Bucci
- Nordberg Translational Molecular Imaging Lab, Division of Clinical Geriatrics, Center for Alzheimer’s Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet Stockholm Sweden
- Theme Inflammation and Aging, Karolinska University Hospital Stockholm Sweden
| | - Agneta K Nordberg
- Nordberg Translational Molecular Imaging Lab, Division of Clinical Geriatrics, Center for Alzheimer’s Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet Stockholm Sweden
- Theme Inflammation and Aging, Karolinska University Hospital Stockholm Sweden
| | - Konstantinos Chiotis
- Nordberg Translational Molecular Imaging Lab, Division of Clinical Geriatrics, Center for Alzheimer’s Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet Stockholm Sweden
- Department of Neurology, Karolinska University Hospital Stockholm Sweden
| |
Collapse
|
7
|
Bucci M, Chiotis K, Nordberg AK. Alzheimer’s disease spectrum profiled by CSF and imaging biomarkers: Tau PET best predicts cognitive decline. Alzheimers Dement 2021. [DOI: 10.1002/alz.056014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
| | - Konstantinos Chiotis
- Karolinska Institutet Stockholm Sweden
- Karolinska University Hospital Solna Sweden
| | - Agneta K Nordberg
- Karolinska Institutet Stockholm Sweden
- Karolinska University Hospital, Theme Aging Stockholm Sweden
| |
Collapse
|
8
|
Boccardi M, Dodich A, Albanese E, Gayet-Ageron A, Festari C, Ashton NJ, Bischof GN, Chiotis K, Leuzy A, Wolters EE, Walter M, Rabinovici GD, Carrillo M, Drzezga A, Hansson O, Nordberg A, Ossenkoppele R, Villemagne VL, Winblad B, Frisoni G, Garibotto V. Correction to: The Strategic Biomarker Roadmap for the validation of Alzheimer's diagnostic biomarkers: methodological update. Eur J Nucl Med Mol Imaging 2021; 48:4525-4531. [PMID: 34546388 DOI: 10.1007/s00259-021-05549-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Marina Boccardi
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany. .,LANVIE, Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland.
| | - Alessandra Dodich
- Center for Neurocognitive Rehabilitation (CeRiN), CIMeC, University of Trento, Trento, Italy.,NIMTlab, Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
| | | | | | - Cristina Festari
- LANE, Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Nicholas J Ashton
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, United Kingdom.,Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Gérard N Bischof
- Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Antoine Leuzy
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Emma E Wolters
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Martin Walter
- Nuclear Medicine and Molecular Division, Geneva Medical Hospital, Geneva, Switzerland
| | - Gil D Rabinovici
- Departments of Neurology, Radiology & Biomedical Imaging, University of California, San Francisco, USA
| | | | - Alexander Drzezga
- University of Cologne, Faculty of Medicine, Cologne, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn/Cologne, Germany.,Institute of Neuroscience and Medicine (INM-2), Molecular Organization of the Brain, Research Center Jülich, Jülich, Germany
| | - Oskar Hansson
- Clinical Memory Rresearch Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Karolinska University Hospital, Theme Aging, Geriatric Clinic, Huddinge, Sweden
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.,Department of Clinical Memory Research, Lund University, Lund, Sweden
| | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, VIC, Australia.,Department of Medicine, Austin Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Bengt Winblad
- Karolinska University Hospital, Theme Aging, Geriatric Clinic, Huddinge, Sweden.,Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Giovanni Frisoni
- LANVIE, Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland.,Memory Clinic, University Hospital, Geneva, Switzerland
| | - Valentina Garibotto
- NIMTlab, Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland.,Nuclear Medicine and Molecular Division, Geneva Medical Hospital, Geneva, Switzerland
| |
Collapse
|
9
|
Colato E, Chiotis K, Ferreira D, Mazrina MS, Lemoine L, Mohanty R, Westman E, Nordberg A, Rodriguez-Vieitez E. Assessment of Tau Pathology as Measured by 18F-THK5317 and 18F-Flortaucipir PET and Their Relation to Brain Atrophy and Cognition in Alzheimer's Disease. J Alzheimers Dis 2021; 84:103-117. [PMID: 34511502 PMCID: PMC8609906 DOI: 10.3233/jad-210614] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND In Alzheimer's disease (AD), the abnormal aggregation of hyperphosphorylated tau leads to synaptic dysfunction and neurodegeneration. Recently developed tau PET imaging tracers are candidate biomarkers for diagnosis and staging of AD. OBJECTIVE We aimed to investigate the discriminative ability of 18F-THK5317 and 18F-flortaucipir tracers and brain atrophy at different stages of AD, and their respective associations with cognition. METHODS Two cohorts, each including 29 participants (healthy controls [HC], prodromal AD, and AD dementia patients), underwent 18F-THK5317 or 18F-flortaucipir PET, T1-weighted MRI, and neuropsychological assessment. For each subject, we quantified regional 18F-THK5317 and 18F-flortaucipir uptake within six bilateral and two composite regions of interest. We assessed global brain atrophy for each individual by quantifying the brain volume index, a measure of brain volume-to-cerebrospinal fluid ratio. We then quantified the discriminative ability of regional 18F-THK5317, 18F-flortaucipir, and brain volume index between diagnostic groups, and their associations with cognition in patients. RESULTS Both 18F-THK5317 and 18F-flortaucipir outperformed global brain atrophy in discriminating between HC and both prodromal AD and AD dementia groups. 18F-THK5317 provided the highest discriminative ability between HC and prodromal AD groups. 18F-flortaucipir performed best at discriminating between prodromal and dementia stages of AD. Across all patients, both tau tracers were predictive of RAVL learning, but only 18F-flortaucipir predicted MMSE. CONCLUSION Our results warrant further in vivo head-to-head and antemortem-postmortem evaluations. These validation studies are needed to select tracers with high clinical validity as biomarkers for early diagnosis, prognosis, and disease staging, which will facilitate their incorporation in clinical practice and therapeutic trials.
Collapse
Affiliation(s)
- Elisa Colato
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Mariam S Mazrina
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Laetitia Lemoine
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Rosaleena Mohanty
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Elena Rodriguez-Vieitez
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | | |
Collapse
|
10
|
Boccardi M, Dodich A, Albanese E, Gayet-Ageron A, Festari C, Ashton NJ, Bischof GN, Chiotis K, Leuzy A, Wolters EE, Walter MA, Rabinovici GD, Carrillo M, Drzezga A, Hansson O, Nordberg A, Ossenkoppele R, Villemagne VL, Winblad B, Frisoni GB, Garibotto V. The strategic biomarker roadmap for the validation of Alzheimer's diagnostic biomarkers: methodological update. Eur J Nucl Med Mol Imaging 2021; 48:2070-2085. [PMID: 33688996 PMCID: PMC8175304 DOI: 10.1007/s00259-020-05120-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 11/15/2020] [Indexed: 12/11/2022]
Abstract
Background The 2017 Alzheimer’s disease (AD) Strategic Biomarker Roadmap (SBR) structured the validation of AD diagnostic biomarkers into 5 phases, systematically assessing analytical validity (Phases 1–2), clinical validity (Phases 3–4), and clinical utility (Phase 5) through primary and secondary Aims. This framework allows to map knowledge gaps and research priorities, accelerating the route towards clinical implementation. Within an initiative aimed to assess the development of biomarkers of tau pathology, we revised this methodology consistently with progress in AD research. Methods We critically appraised the adequacy of the 2017 Biomarker Roadmap within current diagnostic frameworks, discussed updates at a workshop convening the Alzheimer’s Association and 8 leading AD biomarker research groups, and detailed the methods to allow consistent assessment of aims achievement for tau and other AD diagnostic biomarkers. Results The 2020 update applies to all AD diagnostic biomarkers. In Phases 2–3, we admitted a greater variety of study designs (e.g., cross-sectional in addition to longitudinal) and reference standards (e.g., biomarker confirmation in addition to clinical progression) based on construct (in addition to criterion) validity. We structured a systematic data extraction to enable transparent and formal evidence assessment procedures. Finally, we have clarified issues that need to be addressed to generate data eligible to evidence-to-decision procedures. Discussion This revision allows for more versatile and precise assessment of existing evidence, keeps up with theoretical developments, and helps clinical researchers in producing evidence suitable for evidence-to-decision procedures. Compliance with this methodology is essential to implement AD biomarkers efficiently in clinical research and diagnostics.
Collapse
Affiliation(s)
- Marina Boccardi
- German Center for Neurodegenerative Diseases DZNE-Standort Rostock/Greifswald, Gehlsheimer Str. 20, 18147, Rostock, Germany.
- LANVIE - Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland.
| | - Alessandra Dodich
- Center for Neurocognitive Rehabilitation (CeRiN), CIMeC, University of Trento, Trento, Italy
- NIMTlab - Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
| | - Emiliano Albanese
- USI - Università della Svizzera Italiana, Institute of Public Health (IPH), Lugano, Switzerland
| | - Angèle Gayet-Ageron
- Division of Clinical Epidemiology, Department of Health and Community Medicine, University of Geneva & University Hospitals of Geneva, Geneva, Switzerland
| | - Cristina Festari
- LANE - Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Nicholas J Ashton
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at The University of Gothenburg, Molndal, Sweden
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Gérard N Bischof
- Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Antoine Leuzy
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Emma E Wolters
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Martin A Walter
- Nuclear Medicine and Molecular Division, Geneva Medical Hospital, Geneva, Switzerland
| | - Gil D Rabinovici
- Departments of Neurology, Radiology & Biomedical Imaging, University of California, San Francisco, CA, USA
| | | | - Alexander Drzezga
- Faculty of Medicine, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn/Cologne, Germany
- Molecular Organization of the Brain, Research Center Jülich, Institute of Neuroscience and Medicine (INM-2), Julich, Germany
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmo, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Karolinska University Hospital, Theme Aging, Geriatric Clinic, Huddinge, Sweden
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
- Department of Clinical Memory Research, Lund University, Lund, Sweden
| | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, VIC, Australia
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsilvania, USA
| | - Bengt Winblad
- Karolinska University Hospital, Theme Aging, Geriatric Clinic, Huddinge, Sweden
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Giovanni B Frisoni
- LANVIE - Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland
- Memory Clinic, University Hospital, Geneva, Switzerland
| | - Valentina Garibotto
- NIMTlab - Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
- Nuclear Medicine and Molecular Division, Geneva Medical Hospital, Geneva, Switzerland
| |
Collapse
|
11
|
Chiotis K, Savitcheva I, Poulakis K, Saint-Aubert L, Wall A, Antoni G, Nordberg A. [ 18F]THK5317 imaging as a tool for predicting prospective cognitive decline in Alzheimer's disease. Mol Psychiatry 2021; 26:5875-5887. [PMID: 32616831 PMCID: PMC8758479 DOI: 10.1038/s41380-020-0815-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Revised: 05/09/2020] [Accepted: 06/08/2020] [Indexed: 11/09/2022]
Abstract
Cross-sectional studies have indicated potential for positron emission tomography (PET) in imaging tau pathology in Alzheimer's disease (AD); however, its prognostic utility remains unproven. In a longitudinal, multi-modal, prognostic study of cognitive decline, 20 patients with a clinical biomarker-based diagnosis in the AD spectrum (mild cognitive impairment or dementia and a positive amyloid-beta PET scan) were recruited from the Cognitive Clinic at Karolinska University Hospital. The participants underwent baseline neuropsychological assessment, PET imaging with [18F]THK5317, [11C]PIB and [18F]FDG, magnetic resonance imaging, and in a subgroup cerebrospinal fluid (CSF) sampling, with clinical follow-up after a median 48 months (interquartile range = 32:56). In total, 11 patients declined cognitively over time, while 9 remained cognitively stable. The accuracy of baseline [18F]THK5317 binding in temporal areas was excellent at predicting future cognitive decline (area under the receiver operating curve 0.84-1.00) and the biomarker levels were strongly associated with the rate of cognitive decline (β estimate -33.67 to -31.02, p < 0.05). The predictive accuracy of the other baseline biomarkers was poor (area under the receiver operating curve 0.58-0.77) and their levels were not associated with the rate of cognitive decline (β estimate -4.64 to 15.78, p > 0.05). Baseline [18F]THK5317 binding and CSF tau levels were more strongly associated with the MMSE score at follow-up than at baseline (p < 0.05). These findings support a temporal dissociation between tau deposition and cognitive impairment, and suggest that [18F]THK5317 predicts future cognitive decline better than other biomarkers. The use of imaging markers for tau pathology could prove useful for clinical prognostic assessment and screening before inclusion in relevant clinical trials.
Collapse
Affiliation(s)
- Konstantinos Chiotis
- grid.4714.60000 0004 1937 0626Nordberg Translational Molecular Imaging Lab, Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,grid.24381.3c0000 0000 9241 5705Theme Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Irina Savitcheva
- grid.24381.3c0000 0000 9241 5705Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Konstantinos Poulakis
- grid.4714.60000 0004 1937 0626Westman neuroimaging group, Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Laure Saint-Aubert
- grid.4714.60000 0004 1937 0626Nordberg Translational Molecular Imaging Lab, Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,grid.15781.3a0000 0001 0723 035XToulouse NeuroImaging Center, University of Toulouse, Inserm, UPS, Toulouse, France
| | - Anders Wall
- grid.8993.b0000 0004 1936 9457Section for Nuclear Medicine and PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Gunnar Antoni
- grid.8993.b0000 0004 1936 9457Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden
| | - Agneta Nordberg
- Nordberg Translational Molecular Imaging Lab, Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden. .,Theme Aging, Karolinska University Hospital, Stockholm, Sweden.
| |
Collapse
|
12
|
Wolters EE, Chiotis K, Dodich A, Ashton NJ, Barthel H, Bischof GN, Boccardi M, Carrillo MC, Corre J, Démonet J, Drzezga A, Gietl AF, Hansson O, Johnson KA, Leuzy A, Lorenzi M, Rabinovici GD, Ratib O, Sabri O, Treyer V, Unschuld PG, Villemagne VL, Winblad B, Frisoni GB, Garibotto V, Nordberg AK, Ossenkoppele R. Alzheimer’s disease biomarker roadmap 2020: [
18
F]flortaucipir. Alzheimers Dement 2020. [DOI: 10.1002/alz.039550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Emma E. Wolters
- Alzheimer Center Amsterdam Department of Neurology Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam Netherlands
| | | | | | - Nicholas J. Ashton
- Wallenberg Centre for Molecular and Translational Medicine University of Gothenburg Gothenburg Sweden
| | - Henryk Barthel
- Department of Nuclear Medicine University of Leipzig Leipzig Germany
| | | | | | | | - Julie Corre
- Centre National de la Recherche Scientifique Montpellier France
| | - Jean‐François Démonet
- Department of Clinical Neurosciences Leenaards Memory Centre Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne Switzerland
| | | | - Anton F. Gietl
- Institute for Regenerative Medicine University of Zurich Schlieren Switzerland
| | - Oskar Hansson
- Clinical Memory Research Unit Lund University Malmö Sweden
| | - Keith A. Johnson
- Gordon Center for Medical Imaging Massachusetts General Hospital Harvard Medical School Boston MA USA
| | - Antoine Leuzy
- Clinical Memory Research Unit Lund University Malmö Sweden
| | | | - Gil D. Rabinovici
- Memory and Aging Center UCSF Weill Institute for Neurosciences University of California, San Francisco San Francisco CA USA
| | - Osman Ratib
- Geneva University Hospitals Geneva Switzerland
| | - Osama Sabri
- Department of Nuclear Medicine University of Leipzig Leipzig Germany
| | - Valerie Treyer
- Institute for Regenerative Medicine University of Zurich Schlieren Switzerland
| | - Paul G. Unschuld
- Hospital for Psychogeriatric Medicine University of Zurich Zurich Switzerland
| | | | | | | | - Valentina Garibotto
- Division of Nuclear Medicine Geneva University Hospitals and University of Geneva Geneva Switzerland
| | | | - Rik Ossenkoppele
- VU University Medical Center Amsterdam UMC Amsterdam Netherlands
| |
Collapse
|
13
|
Bischof GN, Dodich A, Ashton NJ, Boccardi M, Barthel H, Carrillo MC, Chiotis K, Corre J, Démonet J, Gietl AF, Johnson KA, Hansson O, Leuzy A, Lorenzi M, Nordberg AK, Ossenkoppele R, Rabinovici GD, Ratib O, Sabri O, Treyer V, Unschuld PG, Villemagne VL, Wolters EE, Winblad B, Frisoni GB, Garibotto V, Drzezga A. Alzheimer’s disease biomarker roadmap 2020: Second‐generation tau PET tracers. Alzheimers Dement 2020. [DOI: 10.1002/alz.039556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
| | | | - Nicholas J Ashton
- Wallenberg Centre for Molecular and Translational Medicine University of Gothenburg Gothenburg Sweden
| | | | - Henryk Barthel
- Department of Nuclear Medicine University of Leipzig Leipzig Germany
| | | | | | - Julie Corre
- Centre National de la Recherche Scientifique Montpellier France
| | - Jean‐François Démonet
- Department of Clinical Neurosciences Leenaards Memory Centre Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne Switzerland
| | - Anton F. Gietl
- Institute for Regenerative Medicine University of Zurich Schlieren Switzerland
| | - Keith A. Johnson
- Gordon Center for Medical Imaging Massachusetts General Hospital Harvard Medical School Boston MA USA
| | - Oskar Hansson
- Clinical Memory Research Unit Lund University Malmö Sweden
| | - Antoine Leuzy
- Clinical Memory Research Unit Lund University Malmö Sweden
| | | | | | - Rik Ossenkoppele
- VU University Medical Center Amsterdam UMC Amsterdam Netherlands
| | - Gil D. Rabinovici
- Memory and Aging Center UCSF Weill Institute for Neurosciences University of California, San Francisco San Francisco CA USA
| | - Osman Ratib
- Geneva University Hospitals Geneva Switzerland
| | - Osama Sabri
- Department of Nuclear Medicine University of Leipzig Leipzig Germany
| | - Valerie Treyer
- Institute for Regenerative Medicine University of Zurich Schlieren Switzerland
| | - Paul G. Unschuld
- Hospital for Psychogeriatric Medicine University of Zurich Zurich Switzerland
| | | | - Emma E. Wolters
- Alzheimer Center Amsterdam Department of Neurology Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam Netherlands
| | | | | | - Valentina Garibotto
- Division of Nuclear Medicine Geneva University Hospitals and University of Geneva Geneva Switzerland
| | | |
Collapse
|
14
|
Dodich A, Boccardi M, Ashton NJ, Barthel H, Bischof GN, Carrillo MC, Chiotis K, Corre J, Démonet J, Drzezga A, Gietl AF, Hansson O, Johnson KA, Leuzy A, Lorenzi M, Nordberg AK, Ossenkoppele R, Rabinovici GD, Ratib O, Sabri O, Treyer V, Unschuld PG, Villemagne VL, Winblad B, Wolters EE, Frisoni GB, Garibotto V. Alzheimer’s disease biomarker roadmap 2020: Time for tau. Alzheimers Dement 2020. [DOI: 10.1002/alz.039549] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | - Nicholas J Ashton
- Wallenberg Centre for Molecular and Translational Medicine University of Gothenburg Gothenburg Sweden
| | - Henryk Barthel
- Department of Nuclear Medicine University of Leipzig Leipzig Germany
| | | | | | | | - Julie Corre
- Centre National de la Recherche Scientifique Montpellier France
| | - Jean‐François Démonet
- Department of Clinical Neurosciences Leenaards Memory Centre Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne Switzerland
| | | | - Anton F. Gietl
- Institute for Regenerative Medicine University of Zurich Schlieren Switzerland
| | - Oskar Hansson
- Clinical Memory Research Unit Lund University Malmö Sweden
| | - Keith A. Johnson
- Gordon Center for Medical Imaging Massachusetts General Hospital, Harvard Medical School Boston MA USA
| | - Antoine Leuzy
- Clinical Memory Research Unit Lund University Malmö Sweden
| | | | | | - Rik Ossenkoppele
- VU University Medical Center, Amsterdam UMC Amsterdam Netherlands
| | - Gil D. Rabinovici
- Memory and Aging Center UCSF Weill Institute for Neurosciences University of California, San Francisco San Francisco CA USA
| | - Osman Ratib
- Geneva University Hospitals Geneva Switzerland
| | - Osama Sabri
- Department of Nuclear Medicine University of Leipzig Leipzig Germany
| | - Valerie Treyer
- Institute for Regenerative Medicine University of Zurich Schlieren Switzerland
| | - Paul G. Unschuld
- Hospital for Psychogeriatric Medicine University of Zurich Zurich Switzerland
| | | | | | - Emma E. Wolters
- Alzheimer Center Amsterdam Department of Neurology Amsterdam Neuroscience Vrije Universiteit Amsterdam, Amsterdam UMC Amsterdam Netherlands
| | - Giovanni B. Frisoni
- Memory Clinic and LANVIE‐Laboratory of Neuroimaging of Aging University Hospitals and University of Geneva Geneva Switzerland
| | - Valentina Garibotto
- Geneva University Hospitals Geneva Switzerland
- Division of Nuclear Medicine Geneva University Hospitals and University of Geneva Geneva Switzerland
| |
Collapse
|
15
|
Ashton NJ, Leuzy A, Karikari TK, Dodich A, Boccardi M, Barthel H, Bischof GN, Carrillo MC, Chiotis K, Corre J, Démonet J, Drzezga A, Gietl AF, Johnson KC, Lorenzi M, Nordberg AK, Ossenkoppele R, Rabinovici GD, Ratib O, Sabri O, Treyer V, Unschuld PG, Villemagne VLL, Winblad B, Wolters EE, Frisoni GB, Garibotto V, Mattsson N, Zetterberg H, Blennow K, Hansson O. Alzheimer’s disease biomarker roadmap 2020: Fluid biomarkers. Alzheimers Dement 2020. [DOI: 10.1002/alz.039557] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Nicholas J Ashton
- Wallenberg Centre for Molecular and Translational Medicine University of Gothenburg Gothenburg Sweden
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation London United Kingdom
- Institute of Psychiatry Psychology & Neuroscience King's College London London United Kingdom
- Department of Psychiatry and Neurochemistry Institute of Neuroscience & Physiology the Sahlgrenska Academy at the University of Gothenburg Mölndal Sweden
| | - Antoine Leuzy
- Clinical Memory Research Unit Lund University Malmö Sweden
| | | | | | | | - Henryk Barthel
- Department of Nuclear Medicine University of Leipzig Leipzig Germany
| | - Gerard N Bischof
- Medical Faculty and University Hospital of Cologne Cologne Germany
| | | | | | - Julie Corre
- Centre National de la Recherche Scientifique Montpellier France
| | - Jean‐François Démonet
- Department of Clinical Neurosciences Leenaards Memory Centre Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne Switzerland
| | | | - Anton F. Gietl
- Institute for Regenerative Medicine University of Zurich Schlieren Switzerland
| | - Karen C Johnson
- University of Tennessee Health Science Center Memphis TN USA
| | | | | | - Rik Ossenkoppele
- Alzheimer Center Amsterdam Department of Neurology Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam Netherlands
| | - Gil D Rabinovici
- Memory and Aging Center UCSF Weill Institute for Neurosciences University of California, San Francisco San Francisco CA USA
| | - Osman Ratib
- Geneva University Hospitals Geneva Switzerland
| | - Osama Sabri
- Department of Nuclear Medicine University of Leipzig Leipzig Germany
| | - Valerie Treyer
- Institute for Regenerative Medicine University of Zurich Schlieren Switzerland
| | - Paul G. Unschuld
- Hospital for Psychogeriatric Medicine University of Zurich Zurich Switzerland
| | | | | | - Emma E Wolters
- Alzheimer Center Amsterdam Department of Neurology Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam Netherlands
| | - Giovanni B Frisoni
- Memory Clinic and LANVIE‐Laboratory of Neuroimaging of Aging University Hospitals and University of Geneva Geneva Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine Geneva University Hospitals and University of Geneva Geneva Switzerland
| | | | | | | | - Oskar Hansson
- Clinical Memory Research Unit Lund University Malmö Sweden
| |
Collapse
|
16
|
Smailovic U, Koenig T, Savitcheva I, Chiotis K, Nordberg A, Blennow K, Winblad B, Jelic V. Regional Disconnection in Alzheimer Dementia and Amyloid-Positive Mild Cognitive Impairment: Association Between EEG Functional Connectivity and Brain Glucose Metabolism. Brain Connect 2020; 10:555-565. [PMID: 33073602 PMCID: PMC7757561 DOI: 10.1089/brain.2020.0785] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Introduction: The disconnection hypothesis of Alzheimer's disease (AD) is supported by growing neuroimaging and neurophysiological evidence of altered brain functional connectivity in cognitively impaired individuals. Brain functional modalities such as [18F]fluorodeoxyglucose positron-emission tomography ([18F]FDG-PET) and electroencephalography (EEG) measure different aspects of synaptic functioning, and can contribute to understanding brain connectivity disruptions in AD. Aim: This study investigated the relationship between cortical glucose metabolism and topographical EEG measures of brain functional connectivity in subjects along AD continuum. Methods: Patients diagnosed with mild cognitive impairment (MCI) and AD (n = 67), and stratified into amyloid-positive (n = 32) and negative (n = 10) groups according to cerebrospinal fluid Aβ42/40 ratio, were assessed with [18F]FDG-PET and resting-state EEG recordings. EEG-based neuroimaging analysis involved standardized low-resolution electromagnetic tomography (sLORETA), which estimates functional connectivity from cortical sources of electrical activity in a 3D head model. Results: Glucose hypometabolism in temporoparietal lobes was significantly associated with altered EEG functional connectivity of the same regions of interest in clinically diagnosed MCI and AD patients and in patients with biomarker-verified AD pathology. The correlative pattern of disrupted connectivity in temporoparietal lobes, as detected by EEG sLORETA analysis, included decreased instantaneous linear connectivity in fast frequencies and increased lagged linear connectivity in slow frequencies in relation to the activity of remaining cortex. Conclusions: Topographical EEG measures of functional connectivity detect regional dysfunction of AD-vulnerable brain areas as evidenced by association and spatial overlap with the cortical glucose hypometabolism in MCI and AD patients.
Collapse
Affiliation(s)
- Una Smailovic
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Thomas Koenig
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Clinic for Cognitive Disorders, Karolinska University Hospital-Huddinge, Huddinge, Sweden
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry and Sahlgrenska University Hospital, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Bengt Winblad
- Division of Neurogeriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Geriatrics, Karolinska University Hospital, Huddinge, Sweden
| | - Vesna Jelic
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Clinic for Cognitive Disorders, Karolinska University Hospital-Huddinge, Huddinge, Sweden
| |
Collapse
|
17
|
Mohanty R, Mårtensson G, Poulakis K, Muehlboeck JS, Rodriguez-Vieitez E, Chiotis K, Grothe MJ, Nordberg A, Ferreira D, Westman E. Comparison of subtyping methods for neuroimaging studies in Alzheimer's disease: a call for harmonization. Brain Commun 2020; 2:fcaa192. [PMID: 33305264 PMCID: PMC7713995 DOI: 10.1093/braincomms/fcaa192] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 09/17/2020] [Accepted: 10/05/2020] [Indexed: 01/08/2023] Open
Abstract
Biological subtypes in Alzheimer's disease, originally identified on neuropathological data, have been translated to in vivo biomarkers such as structural magnetic resonance imaging and positron emission tomography, to disentangle the heterogeneity within Alzheimer's disease. Although there is methodological variability across studies, comparable characteristics of subtypes are reported at the group level. In this study, we investigated whether group-level similarities translate to individual-level agreement across subtyping methods, in a head-to-head context. We compared five previously published subtyping methods. Firstly, we validated the subtyping methods in 89 amyloid-beta positive Alzheimer's disease dementia patients (reference group: 70 amyloid-beta negative healthy individuals) using structural magnetic resonance imaging. Secondly, we extended and applied the subtyping methods to 53 amyloid-beta positive prodromal Alzheimer's disease and 30 amyloid-beta positive Alzheimer's disease dementia patients (reference group: 200 amyloid-beta negative healthy individuals) using structural magnetic resonance imaging and tau positron emission tomography. Subtyping methods were implemented as outlined in each original study. Group-level and individual-level comparisons across methods were performed. Each individual subtyping method was replicated, and the proof-of-concept was established. At the group level, all methods captured subtypes with similar patterns of demographic and clinical characteristics, and with similar cortical thinning and tau positron emission tomography uptake patterns. However, at the individual level, large disagreements were found in subtype assignments. Although characteristics of subtypes are comparable at the group level, there is a large disagreement at the individual level across subtyping methods. Therefore, there is an urgent need for consensus and harmonization across subtyping methods. We call for the establishment of an open benchmarking framework to overcome this problem.
Collapse
Affiliation(s)
- Rosaleena Mohanty
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Gustav Mårtensson
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Poulakis
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - J-Sebastian Muehlboeck
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Elena Rodriguez-Vieitez
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain.,Clinical Dementia Research Section, German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| |
Collapse
|
18
|
Lemoine L, Chiotis K, Leuzy A, Nennesmo I, Nordberg AK. P4-599: ANTE-MORTEM BINDING OF 18
F-THK5317 PET IN A CASE OF FTLD AND POST-MORTEM COMPARISON OF TAU BINDING USING 3
H-THK5117 AND 3
H-MK6240. Alzheimers Dement 2019. [DOI: 10.1016/j.jalz.2019.08.147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
| | - Konstantinos Chiotis
- Karolinska Institutet; Stockholm Sweden
- Karolinska University Hospital; Solna Sweden
| | | | | | - Agneta K. Nordberg
- Karolinska Institutet; Stockholm Sweden
- Karolinska University Hospital, Theme Aging; Huddinge Sweden
| |
Collapse
|
19
|
Leuzy A, Savitcheva I, Chiotis K, Lilja J, Andersen P, Bogdanovic N, Jelic V, Nordberg A. Clinical impact of [ 18F]flutemetamol PET among memory clinic patients with an unclear diagnosis. Eur J Nucl Med Mol Imaging 2019; 46:1276-1286. [PMID: 30915522 PMCID: PMC6486908 DOI: 10.1007/s00259-019-04297-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 02/25/2019] [Indexed: 12/11/2022]
Abstract
Purpose To investigate the impact of amyloid PET with [18F]flutemetamol on diagnosis and treatment management in a cohort of patients attending a tertiary memory clinic in whom, despite extensive cognitive assessment including neuropsychological testing, structural imaging, CSF biomarker analysis and in some cases [18F]FDG PET, the diagnosis remained unclear. Methods The study population consisted of 207 patients with a clinical diagnosis prior to [18F]flutemetamol PET including mild cognitive impairment (MCI; n = 131), Alzheimer’s disease (AD; n = 41), non-AD (n = 10), dementia not otherwise specified (dementia NOS; n = 20) and subjective cognitive decline (SCD; n = 5). Results Amyloid positivity was found in 53% of MCI, 68% of AD, 20% of non-AD, 20% of dementia NOS, and 60% of SCD patients. [18F]Flutemetamol PET led, overall, to a change in diagnosis in 92 of the 207 patients (44%). A high percentage of patients with a change in diagnosis was observed in the MCI group (n = 67, 51%) and in the dementia NOS group (n = 11; 55%), followed by the non-AD and AD (30% and 20%, respectively). A significant increase in cholinesterase inhibitor treatment was observed after [18F]flutemetamol PET (+218%, 34 patients before and 108 patients after). Conclusion The present study lends support to the clinical value of amyloid PET in patients with an uncertain diagnosis in the tertiary memory clinic setting.
Collapse
Affiliation(s)
- Antoine Leuzy
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics Center for Alzheimer Research, Karolinska Institutet, Neo, 7th floor, 141 83, Huddinge, Sweden
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics Center for Alzheimer Research, Karolinska Institutet, Neo, 7th floor, 141 83, Huddinge, Sweden
| | - Johan Lilja
- Department of Surgical Sciences, Radiology, Nuclear Medicine and PET, Uppsala University, Uppsala, Sweden.,Hermes Medical Solutions, Stockholm, Sweden
| | - Pia Andersen
- Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Nenad Bogdanovic
- Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Vesna Jelic
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics Center for Alzheimer Research, Karolinska Institutet, Neo, 7th floor, 141 83, Huddinge, Sweden.,Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics Center for Alzheimer Research, Karolinska Institutet, Neo, 7th floor, 141 83, Huddinge, Sweden. .,Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Stockholm, Sweden.
| |
Collapse
|
20
|
Leuzy A, Chiotis K, Lemoine L, Gillberg PG, Almkvist O, Rodriguez-Vieitez E, Nordberg A. Tau PET imaging in neurodegenerative tauopathies-still a challenge. Mol Psychiatry 2019; 24:1112-1134. [PMID: 30635637 PMCID: PMC6756230 DOI: 10.1038/s41380-018-0342-8] [Citation(s) in RCA: 350] [Impact Index Per Article: 70.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Revised: 10/19/2018] [Accepted: 11/26/2018] [Indexed: 12/14/2022]
Abstract
The accumulation of pathological misfolded tau is a feature common to a collective of neurodegenerative disorders known as tauopathies, of which Alzheimer's disease (AD) is the most common. Related tauopathies include progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), Down's syndrome (DS), Parkinson's disease (PD), and dementia with Lewy bodies (DLB). Investigation of the role of tau pathology in the onset and progression of these disorders is now possible due the recent advent of tau-specific ligands for use with positron emission tomography (PET), including first- (e.g., [18F]THK5317, [18F]THK5351, [18F]AV1451, and [11C]PBB3) and second-generation compounds [namely [18F]MK-6240, [18F]RO-948 (previously referred to as [18F]RO69558948), [18F]PI-2620, [18F]GTP1, [18F]PM-PBB3, and [18F]JNJ64349311 ([18F]JNJ311) and its derivative [18F]JNJ-067)]. In this review we describe and discuss findings from in vitro and in vivo studies using both initial and new tau ligands, including their relation to biomarkers for amyloid-β and neurodegeneration, and cognitive findings. Lastly, methodological considerations for the quantification of in vivo ligand binding are addressed, along with potential future applications of tau PET, including therapeutic trials.
Collapse
Affiliation(s)
- Antoine Leuzy
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Chiotis
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,0000 0000 9241 5705grid.24381.3cTheme Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Laetitia Lemoine
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Per-Göran Gillberg
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Ove Almkvist
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,0000 0004 1936 9377grid.10548.38Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Elena Rodriguez-Vieitez
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden. .,Theme Aging, Karolinska University Hospital, Stockholm, Sweden.
| |
Collapse
|
21
|
Leuzy A, Lilja J, Heurling K, Chiotis K, Savitcheva I, Nordberg AK. P1‐473: ESTIMATION OF AMYLOID LOAD USING [
18
F]FLUTEMETAMOL AND A NORMALIZATION‐DERIVED WEIGHTING FACTOR: POTENTIAL APPLICATIONS IN AMYLOID PET. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.06.483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
| | - Johan Lilja
- Hermes Medical SolutionsStockholmSweden
- Uppsala UniversityUppsalaSweden
| | | | | | | | | |
Collapse
|
22
|
Mazrina MS, Chiotis K, Colato E, Nordberg AK, Rodriguez-Vieitez E. P4‐308: MODELLING THE ASSOCIATIONS BETWEEN [18F]AV1451, [18F]FDG PET AND COGNITION IN MILD COGNITIVE IMPAIRMENT AND AD DEMENTIA. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.07.131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
| | | | | | - Agneta K. Nordberg
- Karolinska InstitutetStockholmSweden
- Karolinska University HospitalHuddingeSweden
| | | | | |
Collapse
|
23
|
Leuzy A, Lilja J, Heurling K, Chiotis K, Savitcheva I, Nordberg AK. IC‐P‐016: ESTIMATION OF AMYLOID LOAD USING [
18
F]FLUTEMETAMOL AND A NORMALIZATION DERIVED WEIGHTING FACTOR: POTENTIAL APPLICATIONS IN AMYLOID PET. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.06.2080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
| | - Johan Lilja
- Hermes Medical SolutionsStockholmSweden
- Uppsala UniversityUppsalaSweden
| | | | | | | | | |
Collapse
|
24
|
Chiotis K, Saint-Aubert L, Rodriguez-Vieitez E, Leuzy A, Almkvist O, Savitcheva I, Jonasson M, Lubberink M, Wall A, Antoni G, Nordberg A. Longitudinal changes of tau PET imaging in relation to hypometabolism in prodromal and Alzheimer's disease dementia. Mol Psychiatry 2018; 23:1666-1673. [PMID: 28507319 DOI: 10.1038/mp.2017.108] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Revised: 03/14/2017] [Accepted: 04/04/2017] [Indexed: 12/17/2022]
Abstract
The development of tau-specific positron emission tomography (PET) tracers allows imaging in vivo the regional load of tau pathology in Alzheimer's disease (AD) and other tauopathies. Eighteen patients with baseline investigations enroled in a 17-month follow-up study, including 16 with AD (10 had mild cognitive impairment and a positive amyloid PET scan, that is, prodromal AD, and six had AD dementia) and two with corticobasal syndrome. All patients underwent PET scans with [18F]THK5317 (tau deposition) and [18F]FDG (glucose metabolism) at baseline and follow-up, neuropsychological assessment at baseline and follow-up and a scan with [11C]PIB (amyloid-β deposition) at baseline only. At a group level, patients with AD (prodromal or dementia) showed unchanged [18F]THK5317 retention over time, in contrast to significant decreases in [18F]FDG uptake in temporoparietal areas. The pattern of changes in [18F]THK5317 retention was heterogeneous across all patients, with qualitative differences both between the two AD groups (prodromal and dementia) and among individual patients. High [18F]THK5317 retention was significantly associated over time with low episodic memory encoding scores, while low [18F]FDG uptake was significantly associated over time with both low global cognition and episodic memory encoding scores. Both patients with corticobasal syndrome had a negative [11C]PIB scan, high [18F]THK5317 retention with a different regional distribution from that in AD, and a homogeneous pattern of increased [18F]THK5317 retention in the basal ganglia over time. These findings highlight the heterogeneous propagation of tau pathology among patients with symptomatic AD, in contrast to the homogeneous changes seen in glucose metabolism, which better tracked clinical progression.
Collapse
Affiliation(s)
- K Chiotis
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden
| | - L Saint-Aubert
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden
| | - E Rodriguez-Vieitez
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden
| | - A Leuzy
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden
| | - O Almkvist
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden.,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden.,Department of Psychology, Stockholm University, Stockholm, Sweden
| | - I Savitcheva
- Department of Radiology, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - M Jonasson
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.,Department of Medical Physics, Uppsala University Hospital, Uppsala, Sweden
| | - M Lubberink
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.,Department of Medical Physics, Uppsala University Hospital, Uppsala, Sweden
| | - A Wall
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.,Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden
| | - G Antoni
- Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden
| | - A Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden. .,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden.
| |
Collapse
|
25
|
Lilja J, Leuzy A, Chiotis K, Savitcheva I, Sörensen J, Nordberg A. Spatial Normalization of 18F-Flutemetamol PET Images Using an Adaptive Principal-Component Template. J Nucl Med 2018; 60:285-291. [PMID: 29903930 PMCID: PMC8833851 DOI: 10.2967/jnumed.118.207811] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 06/07/2018] [Indexed: 11/29/2022] Open
Abstract
Though currently approved for visual assessment only, there is evidence to suggest that quantification of amyloid-β (Aβ) PET images may reduce interreader variability and aid in the monitoring of treatment effects in clinical trials. Quantification typically involves a regional atlas in standard space, requiring PET images to be spatially normalized. Different uptake patterns in Aβ-positive and Aβ-negative subjects, however, make spatial normalization challenging. In this study, we proposed a method to spatially normalize 18F-flutemetamol images using a synthetic template based on principal-component images to overcome these challenges. Methods:18F-flutemetamol PET and corresponding MR images from a phase II trial (n = 70), including subjects ranging from Aβ-negative to Aβ-positive, were spatially normalized to standard space using an MR-driven registration method (SPM12). 18F-flutemetamol images were then intensity-normalized using the pons as a reference region. Principal-component images were calculated from the intensity-normalized images. A linear combination of the first 2 principal-component images was then used to model a synthetic template spanning the whole range from Aβ-negative to Aβ-positive. The synthetic template was then incorporated into our registration method, by which the optimal template was calculated as part of the registration process, providing a PET-only–driven registration method. Evaluation of the method was done in 2 steps. First, coregistered gray matter masks generated using SPM12 were spatially normalized using the PET- and MR-driven methods, respectively. The spatially normalized gray matter masks were then visually inspected and quantified. Second, to quantitatively compare the 2 registration methods, additional data from an ongoing study were spatially normalized using both methods, with correlation analysis done on the resulting cortical SUV ratios. Results: All scans were successfully spatially normalized using the proposed method with no manual adjustments performed. Both visual and quantitative comparison between the PET- and MR-driven methods showed high agreement in cortical regions. 18F-flutemetamol quantification showed strong agreement between the SUV ratios for the PET- and MR-driven methods (R2 = 0.996; pons reference region). Conclusion: The principal-component template registration method allows for robust and accurate registration of 18F-flutemetamol images to a standardized template space, without the need for an MR image.
Collapse
|
26
|
Chiotis K, Stenkrona P, Almkvist O, Stepanov V, Ferreira D, Arakawa R, Takano A, Westman E, Varrone A, Okamura N, Shimada H, Higuchi M, Halldin C, Nordberg A. Dual tracer tau PET imaging reveals different molecular targets for 11C-THK5351 and 11C-PBB3 in the Alzheimer brain. Eur J Nucl Med Mol Imaging 2018; 45:1605-1617. [PMID: 29752516 PMCID: PMC6061462 DOI: 10.1007/s00259-018-4012-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2018] [Accepted: 04/06/2018] [Indexed: 12/16/2022]
Abstract
Purpose Several tau PET tracers have been developed, but it remains unclear whether they bind to the same molecular target on the heterogeneous tau pathology. In this study we evaluated the binding of two chemically different tau-specific PET tracers (11C-THK5351 and 11C-PBB3) in a head-to-head, in vivo, multimodal design. Methods Nine patients with a diagnosis of mild cognitive impairment or probable Alzheimer’s disease and cerebrospinal fluid biomarker evidence supportive of the presence of Alzheimer’s disease brain pathology were recruited after thorough clinical assessment. All patients underwent imaging with the tau-specific PET tracers 11C-THK5351 and 11C-PBB3 on the same day, as well as imaging with the amyloid-beta-specific tracer 11C-AZD2184, a T1-MRI sequence, and neuropsychological assessment. Results The load and regional distribution of binding differed between 11C-THK5351 and 11C-PBB3 with no statistically significant regional correlations observed between the tracers. The binding pattern of 11C-PBB3, but not that of 11C-THK5351, in the temporal lobe resembled that of 11C-AZD2184, with strong correlations detected between 11C-PBB3 and 11C-AZD2184 in the temporal and occipital lobes. Global cognition correlated more closely with 11C-THK5351 than with 11C-PBB3 binding. Similarly, cerebrospinal fluid tau measures and entorhinal cortex thickness were more closely correlated with 11C-THK5351 than with 11C-PBB3 binding. Conclusion This research suggests different molecular targets for these tracers; while 11C-PBB3 appeared to preferentially bind to tau deposits with a close spatial relationship to amyloid-beta, the binding pattern of 11C-THK5351 fitted the expected distribution of tau pathology in Alzheimer’s disease better and was more closely related to downstream disease markers. Electronic supplementary material The online version of this article (10.1007/s00259-018-4012-5) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden
| | - Per Stenkrona
- Department of Clinical Neuroscience, Center for Psychiatric Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Ove Almkvist
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden
- Theme Aging, Karolinska University Hospital, Stockholm, Sweden
- Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Vladimir Stepanov
- Department of Clinical Neuroscience, Center for Psychiatric Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Daniel Ferreira
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Ryosuke Arakawa
- Department of Clinical Neuroscience, Center for Psychiatric Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Akihiro Takano
- Department of Clinical Neuroscience, Center for Psychiatric Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Eric Westman
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Andrea Varrone
- Department of Clinical Neuroscience, Center for Psychiatric Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Nobuyuki Okamura
- Cyclotron and Radioisotope Center, Tohoku University, Sendai, Japan
- Division of Pharmacology, Faculty of Medicine, Tohoku Medical and Pharmaceutical University, Sendai, Japan
| | - Hitoshi Shimada
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Makoto Higuchi
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Christer Halldin
- Department of Clinical Neuroscience, Center for Psychiatric Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden.
- Theme Aging, Karolinska University Hospital, Stockholm, Sweden.
| |
Collapse
|
27
|
Iaccarino L, Chiotis K, Alongi P, Almkvist O, Wall A, Cerami C, Bettinardi V, Gianolli L, Nordberg A, Perani D. A Cross-Validation of FDG- and Amyloid-PET Biomarkers in Mild Cognitive Impairment for the Risk Prediction to Dementia due to Alzheimer's Disease in a Clinical Setting. J Alzheimers Dis 2018; 59:603-614. [PMID: 28671117 DOI: 10.3233/jad-170158] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Assessments of brain glucose metabolism (18F-FDG-PET) and cerebral amyloid burden (11C-PiB-PET) in mild cognitive impairment (MCI) have shown highly variable performances when adopted to predict progression to dementia due to Alzheimer's disease (ADD). This study investigates, in a clinical setting, the separate and combined values of 18F-FDG-PET and 11C-PiB-PET in ADD conversion prediction with optimized data analysis procedures. Respectively, we investigate the accuracy of an optimized SPM analysis for 18F-FDG-PET and of standardized uptake value ratio semiquantification for 11C-PiB-PET in predicting ADD conversion in 30 MCI subjects (age 63.57±7.78 years). Fourteen subjects converted to ADD during the follow-up (median 26.5 months, inter-quartile range 30 months). Receiver operating characteristic analyses showed an area under the curve (AUC) of 0.89 and of 0.81 for, respectively, 18F-FDG-PET and 11C-PiB-PET. 18F-FDG-PET, compared to 11C-PiB-PET, showed higher specificity (1.00 versus 0.62, respectively), but lower sensitivity (0.79 versus 1.00). Combining the biomarkers improved classification accuracy (AUC = 0.96). During the follow-up time, all the MCI subjects positive for both PET biomarkers converted to ADD, whereas all the subjects negative for both remained stable. The difference in survival distributions was confirmed by a log-rank test (p = 0.002). These results indicate a very high accuracy in predicting MCI to ADD conversion of both 18F-FDG-PET and 11C-PiB-PET imaging, the former showing optimal performance based on the SPM optimized parametric assessment. Measures of brain glucose metabolism and amyloid load represent extremely powerful diagnostic and prognostic biomarkers with complementary roles in prodromal dementia phase, particularly when tailored to individual cases in clinical settings.
Collapse
Affiliation(s)
- Leonardo Iaccarino
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Konstantinos Chiotis
- Department of NVS, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden
| | - Pierpaolo Alongi
- Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy.,Department of Radiological Sciences, Nuclear Medicine Unit, San Raffaele G.Giglio Institute, Cefalù, Italy
| | - Ove Almkvist
- Department of NVS, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden.,Department of Psychology, Stockholm University, Stockholm, Sweden.,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Anders Wall
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden.,PET Centre, Uppsala University Hospital, Uppsala, Sweden
| | - Chiara Cerami
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Department of Clinical Neurosciences, Neurological Rehabilitation Unit, IRCCS San Raffaele Hospital, Milan, Italy
| | | | - Luigi Gianolli
- Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy
| | - Agneta Nordberg
- Department of NVS, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden.,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy
| |
Collapse
|
28
|
Lemoine L, Leuzy A, Chiotis K, Rodriguez-Vieitez E, Nordberg A. Tau positron emission tomography imaging in tauopathies: The added hurdle of off-target binding. Alzheimers Dement (Amst) 2018; 10:232-236. [PMID: 29780868 PMCID: PMC5956931 DOI: 10.1016/j.dadm.2018.01.007] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Ligands targeting tau for use with positron emission tomography have rapidly been developed during the past several years, enabling the in vivo study of tau pathology in patients with Alzheimer's disease and related non-Alzheimer's disease tauopathies. Several candidate compounds have been developed, showing good in vitro characteristics with respect to their ability to bind tau deposits; off-target binding, however, has also been observed. In this short commentary, we briefly summarize the available in vivo and in vitro evidence pertaining to their off-target binding and discuss the different approaches that are needed for the future development of tau positron emission tomography tracers.
Collapse
Affiliation(s)
- Laetitia Lemoine
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
- Corresponding author. Tel.: +46 8 524 83 527; Fax: +46 8 585 85470 .
| | - Antoine Leuzy
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
| | - Elena Rodriguez-Vieitez
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden
| |
Collapse
|
29
|
Leuzy A, Rodriguez-Vieitez E, Saint-Aubert L, Chiotis K, Almkvist O, Savitcheva I, Jonasson M, Lubberink M, Wall A, Antoni G, Nordberg A. Longitudinal uncoupling of cerebral perfusion, glucose metabolism, and tau deposition in Alzheimer's disease. Alzheimers Dement 2017; 14:652-663. [PMID: 29268078 DOI: 10.1016/j.jalz.2017.11.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2017] [Revised: 11/14/2017] [Accepted: 11/16/2017] [Indexed: 12/01/2022]
Abstract
INTRODUCTION Cross-sectional findings using the tau tracer [18F]THK5317 (THK5317) have shown that [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET) data can be approximated using perfusion measures (early-frame standardized uptake value ratio; ratio of tracer delivery in target to reference regions). In this way, a single PET study can provide both functional and molecular information. METHODS We included 16 patients with Alzheimer's disease who completed follow-up THK5317 and FDG studies 17 months after baseline investigations. Linear mixed-effects models and annual percentage change maps were used to examine longitudinal change. RESULTS Limited spatial overlap was observed between areas showing declines in THK5317 perfusion measures and FDG. Minimal overlap was seen between areas showing functional change and those showing increased retention of THK5317. DISCUSSION Our findings suggest a spatiotemporal offset between functional changes and tau pathology and a partial uncoupling between perfusion and metabolism, possibly as a function of Alzheimer's disease severity.
Collapse
Affiliation(s)
- Antoine Leuzy
- Division of Translational Alzheimer Neurobiology, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
| | - Elena Rodriguez-Vieitez
- Division of Translational Alzheimer Neurobiology, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
| | - Laure Saint-Aubert
- Division of Translational Alzheimer Neurobiology, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Chiotis
- Division of Translational Alzheimer Neurobiology, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
| | - Ove Almkvist
- Division of Translational Alzheimer Neurobiology, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden; Department of Geriatric Medicine, Karolinska University Hospital, Huddinge, Sweden; Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Irina Savitcheva
- Department of Radiology, Karolinska University Hospital, Huddinge, Sweden
| | - My Jonasson
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Department of Medical Physics, Uppsala University Hospital, Uppsala, Sweden
| | - Mark Lubberink
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Department of Medical Physics, Uppsala University Hospital, Uppsala, Sweden
| | - Anders Wall
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden
| | - Gunnar Antoni
- Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden
| | - Agneta Nordberg
- Division of Translational Alzheimer Neurobiology, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden; Department of Geriatric Medicine, Karolinska University Hospital, Huddinge, Sweden.
| |
Collapse
|
30
|
Frisoni GB, Boccardi M, Barkhof F, Blennow K, Cappa S, Chiotis K, Démonet JF, Garibotto V, Giannakopoulos P, Gietl A, Hansson O, Herholz K, Jack CR, Nobili F, Nordberg A, Snyder HM, Ten Kate M, Varrone A, Albanese E, Becker S, Bossuyt P, Carrillo MC, Cerami C, Dubois B, Gallo V, Giacobini E, Gold G, Hurst S, Lönneborg A, Lovblad KO, Mattsson N, Molinuevo JL, Monsch AU, Mosimann U, Padovani A, Picco A, Porteri C, Ratib O, Saint-Aubert L, Scerri C, Scheltens P, Schott JM, Sonni I, Teipel S, Vineis P, Visser PJ, Yasui Y, Winblad B. Strategic roadmap for an early diagnosis of Alzheimer's disease based on biomarkers. Lancet Neurol 2017; 16:661-676. [PMID: 28721928 DOI: 10.1016/s1474-4422(17)30159-x] [Citation(s) in RCA: 379] [Impact Index Per Article: 54.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Revised: 04/27/2017] [Accepted: 04/28/2017] [Indexed: 12/15/2022]
Abstract
The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.
Collapse
Affiliation(s)
- Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University Hospitals and University of Geneva, Geneva, Switzerland; Department of Internal Medicine, University Hospitals and University of Geneva, Geneva, Switzerland.
| | - Marina Boccardi
- Laboratory of Neuroimaging of Aging (LANVIE), University Hospitals and University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer Neuroimaging and Epidemiology (LANE), IRCCS S Giovanni di Dio-Fatebenefratelli, Brescia, Italy
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, Netherlands; Institute of Neurology, University College London, London, UK; Institute of Healthcare Engineering, University College London, London, UK; European Society of Neuroradiology, Zurich, Switzerland
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; International Federation of Clinical Chemistry and Laboratory Medicine Working Group for CSF proteins (IFCC WG-CSF), Gothenburg, Sweden
| | - Stefano Cappa
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, Netherlands; Istituto Universitario di Studi Superiori di Pavia, Pavia, Italy, on behalf of Federation of European Neuropsychological Societies
| | - Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Jean-Francois Démonet
- Leenards Memory Centre, Department of Clinical Neuroscience, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Valentina Garibotto
- Nuclear Medicine and Molecular Imaging Division, University Hospitals and University of Geneva, Geneva, Switzerland
| | | | - Anton Gietl
- Institute for Regenerative Medicine-IREM, University of Zurich Campus Schlieren, Zurich, Switzerland
| | - Oskar Hansson
- Memory Clinic, Skåne University Hospital, Lund, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Karl Herholz
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | | | - Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy; IRCCS AOU San Martino-IST, Genoa, Italy, on behalf of the European Association of Nuclear Medicine
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden; Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | | | - Mara Ten Kate
- Department of Neurology, Alzheimer Centre, VU University Medical Centre, Amsterdam, Netherlands
| | - Andrea Varrone
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Emiliano Albanese
- Department of Psychiatry, University Hospitals and University of Geneva, Geneva, Switzerland
| | | | - Patrick Bossuyt
- Clinical Epidemiology, University of Amsterdam, Amsterdam, Netherlands, on behalf of the European Federation of Laboratory Medicine
| | | | - Chiara Cerami
- Clinical Neuroscience Department, Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Bruno Dubois
- Institut de la Mémoire et de la Maladie d'Alzheimer, Hôpital Pitié Salpêtrière, UPMC University Paris 6, Paris, France
| | - Valentina Gallo
- Centre for Primary Care and Public Health, Barts and The London School of Medicine, Blizard Institute, Queen Mary University of London, London, UK
| | - Ezio Giacobini
- Department of Internal Medicine, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Gabriel Gold
- Service of Geriatrics, Department of Internal Medicine Rehabilitation and Geriatrics, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Samia Hurst
- Institute for Ethics, History, and the Humanities, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Anders Lönneborg
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Karl-Olof Lovblad
- Diagnostic and Interventional Neuroradiology, University Hospital of Geneva, Geneva, Switzerland
| | - Niklas Mattsson
- Memory Clinic, Skåne University Hospital, Lund, Sweden; Department of Neurology, Skåne University Hospital, Lund, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - José-Luis Molinuevo
- Barcelona Beta Brain Research Centre, Pasqual Maragall Foundation, Barcelona, Spain
| | - Andreas U Monsch
- Memory Clinic, University Centre for Medicine of Ageing, Felix Platter Hospital, Basel, Switzerland
| | - Urs Mosimann
- Department of Old Age Psychiatry, University of Bern, Bern, Switzerland
| | - Alessandro Padovani
- Department of Clinical Neurosciences, Faculty of Medicine, University of Brescia, Brescia, Italy
| | - Agnese Picco
- Laboratory of Neuroimaging of Aging (LANVIE), University Hospitals and University of Geneva, Geneva, Switzerland; Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
| | - Corinna Porteri
- Bioethics Unit, IRCCS S Giovanni di Dio-Fatebenefratelli, Brescia, Italy
| | - Osman Ratib
- Department of Radiology, University Hospital of Geneva, Geneva, Switzerland; Division of Nuclear Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Laure Saint-Aubert
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Charles Scerri
- Department of Pathology, Faculty of Medicine and Surgery, University of Malta, Msida, Malta; Alzheimer Europe, Luxembourg, Luxembourg
| | - Philip Scheltens
- Department of Neurology, Alzheimer Centre, VU University Medical Centre, Amsterdam, Netherlands
| | | | - Ida Sonni
- PET Centre, Department of Clinical Neurosciences, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden; Division of Nuclear Medicine and Molecular Imaging, Stanford University, Standford, CA, USA
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE)-Rostock/Greifswald, Rostock, Germany; Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany
| | - Paolo Vineis
- Faculty of Medicine, Imperial College London, London, UK
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU University Medical Centre, Amsterdam, Netherlands; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Yutaka Yasui
- St Jude Children's Research Hospital, Memphis, TN, USA
| | - Bengt Winblad
- Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden; Department of Neurobiology, Care Siences and Society, Centre for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, Huddinge, Sweden; European Alzheimer's Disease Consortium
| |
Collapse
|
31
|
Leuzy A, Chiotis K, Jelic V, Andersen P, Friman J, Lilja J, Savitcheva I, Nordberg A. [P1–357]: INVESTIGATING THE CLINICAL IMPACT OF [
18
F]FLUTEMETAMOL PET IN A TERTIARY MEMORY CLINIC SETTING IN PATIENTS WITH UNCERTAIN DIAGNOSIS. Alzheimers Dement 2017. [DOI: 10.1016/j.jalz.2017.06.373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
| | | | - Vesna Jelic
- Karolinska University HospitalHuddingeSweden
| | | | | | - Johan Lilja
- Uppsala UniversityUppsalaSweden
- Hermes Medical SolutionsStockholmSweden
| | | | - Agneta Nordberg
- Karolinska InstitutetStockholmSweden
- Karolinska University Hospital HuddingeStockholmSweden
| |
Collapse
|
32
|
Chiotis K, Saint-Aubert L, Boccardi M, Gietl A, Picco A, Varrone A, Garibotto V, Herholz K, Nobili F, Nordberg A, Frisoni GB, Winblad B, Jack CR. Clinical validity of increased cortical uptake of amyloid ligands on PET as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework. Neurobiol Aging 2017; 52:214-227. [DOI: 10.1016/j.neurobiolaging.2016.07.012] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Revised: 06/10/2016] [Accepted: 07/06/2016] [Indexed: 12/31/2022]
|
33
|
Saint-Aubert L, Lemoine L, Chiotis K, Leuzy A, Rodriguez-Vieitez E, Nordberg A. Tau PET imaging: present and future directions. Mol Neurodegener 2017; 12:19. [PMID: 28219440 PMCID: PMC5319037 DOI: 10.1186/s13024-017-0162-3] [Citation(s) in RCA: 195] [Impact Index Per Article: 27.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Accepted: 02/15/2017] [Indexed: 12/15/2022] Open
Abstract
Abnormal aggregation of tau in the brain is a major contributing factor in various neurodegenerative diseases. The role of tau phosphorylation in the pathophysiology of tauopathies remains unclear. Consequently, it is important to be able to accurately and specifically target tau deposits in vivo in the brains of patients. The advances of molecular imaging in the recent years have now led to the recent development of promising tau-specific tracers for positron emission tomography (PET), such as THK5317, THK5351, AV-1451, and PBB3. These tracers are now available for clinical assessment in patients with various tauopathies, including Alzheimer's disease, as well as in healthy subjects. Exploring the patterns of tau deposition in vivo for different pathologies will allow discrimination between neurodegenerative diseases, including different tauopathies, and monitoring of disease progression. The variety and complexity of the different types of tau deposits in the different diseases, however, has resulted in quite a challenge for the development of tau PET tracers. Extensive work remains in order to fully characterize the binding properties of the tau PET tracers, and to assess their usefulness as an early biomarker of the underlying pathology. In this review, we summarize recent findings on the most promising tau PET tracers to date, discuss what has been learnt from these findings, and offer some suggestions for the next steps that need to be achieved in a near future.
Collapse
Affiliation(s)
- Laure Saint-Aubert
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Laetitia Lemoine
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Konstantinos Chiotis
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Antoine Leuzy
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Elena Rodriguez-Vieitez
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Agneta Nordberg
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden. .,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden.
| |
Collapse
|
34
|
Rodriguez-Vieitez E, Leuzy A, Chiotis K, Saint-Aubert L, Wall A, Nordberg A. Comparability of [ 18F]THK5317 and [ 11C]PIB blood flow proxy images with [ 18F]FDG positron emission tomography in Alzheimer's disease. J Cereb Blood Flow Metab 2017; 37:740-749. [PMID: 27107028 PMCID: PMC5381463 DOI: 10.1177/0271678x16645593] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
For amyloid positron emission tomography tracers, the simplified reference tissue model derived ratio of influx rate in target relative to reference region (R1) has been shown to serve as a marker of brain perfusion, and, due to the strong coupling between perfusion and metabolism, as a proxy for glucose metabolism. In the present study, 11 prodromal Alzheimer's disease and nine Alzheimer's disease dementia patients underwent [18F]THK5317, carbon-11 Pittsburgh Compound-B ([11C]PIB), and 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography to assess the possible use of early-phase [18F]THK5317 and R1 as proxies for brain perfusion, and thus, for glucose metabolism. Discriminative performance (prodromal vs Alzheimer's disease dementia) of [18F]THK5317 (early-phase SUVr and R1) was compared with that of [11C]PIB (early-phase SUVr and R1) and [18F]FDG. Strong positive correlations were found between [18F]THK5317 (early-phase, R1) and [18F]FDG, particularly in frontal and temporoparietal regions. Differences in correlations between early-phase and R1 ([18F]THK5317 and [11C]PIB) and [18F]FDG, were not statistically significant, nor were differences in area under the curve values in the discriminative analysis. Our findings suggest that early-phase [18F]THK5317 and R1 provide information on brain perfusion, closely related to glucose metabolism. As such, a single positron emission tomography study with [18F]THK5317 may provide information about both tau pathology and brain perfusion in Alzheimer's disease, with potential clinical applications.
Collapse
Affiliation(s)
| | - Antoine Leuzy
- 1 Department NVS, Karolinska Institutet, Stockholm, Sweden
| | | | | | - Anders Wall
- 2 Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Agneta Nordberg
- 1 Department NVS, Karolinska Institutet, Stockholm, Sweden.,3 Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| |
Collapse
|
35
|
Saint-Aubert L, Almkvist O, Chiotis K, Almeida R, Wall A, Nordberg A. Regional tau deposition measured by [ 18F]THK5317 positron emission tomography is associated to cognition via glucose metabolism in Alzheimer's disease. Alzheimers Res Ther 2016; 8:38. [PMID: 27683159 PMCID: PMC5041516 DOI: 10.1186/s13195-016-0204-z] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Accepted: 08/09/2016] [Indexed: 12/15/2022]
Abstract
Background The recent development of tau-specific positron emission tomography (PET) tracers has allowed in vivo quantification of regional tau deposition and offers the opportunity to monitor the progression of tau pathology along with cognitive impairment. In this study, we investigated the relationships of cerebral tau deposition ([18F]THK5317-PET) and metabolism ([18F]FDG-PET) with concomitant cognitive function in patients with probable Alzheimer’s disease (AD). Methods Nine patients diagnosed with AD dementia and 11 with prodromal AD (mild cognitive impairment, amyloid-positive on [11C]PiB-PET) were included in this study. All patients underwent PET scans using each tracer, as well as episodic memory and global cognition assessment. Linear models were used to investigate the association of regional [18F]THK5317 retention and [18F]FDG uptake with cognition. The possible mediating effect of local metabolism on the relationship between tau deposition and cognitive performance was investigated using mediation analyses. Results Significant negative associations were found between [18F]THK5317 regional retention, mainly in temporal regions, and both episodic memory and global cognition. Significant positive associations were found between [18F]FDG regional uptake and cognition. The association of [18F]FDG with global cognition was regionally more extensive than that of [18F]THK5317, while the opposite was observed with episodic memory, suggesting that [18F]THK5317 retention might be more sensitive than [18F]FDG regional uptake to early cognitive impairment. Finally, [18F]FDG uptake had a mediating effect on the relationship between [18F]THK5317 retention in temporal regions and global cognition. Conclusions These findings suggest a mediating role for local glucose metabolism in the observed association between in vivo tau deposition and concomitant cognitive impairment in AD. Electronic supplementary material The online version of this article (doi:10.1186/s13195-016-0204-z) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Laure Saint-Aubert
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Novum 5th floor, Huddinge, 141 57, Sweden
| | - Ove Almkvist
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Novum 5th floor, Huddinge, 141 57, Sweden.,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden.,Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Konstantinos Chiotis
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Novum 5th floor, Huddinge, 141 57, Sweden
| | - Rita Almeida
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Anders Wall
- PET Centre, Uppsala University Hospital, Uppsala, Sweden.,Nuclear medicine and PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Agneta Nordberg
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Novum 5th floor, Huddinge, 141 57, Sweden. .,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden.
| |
Collapse
|
36
|
Leuzy A, Chiotis K, Hasselbalch SG, Rinne JO, de Mendonça A, Otto M, Lleó A, Castelo-Branco M, Santana I, Johansson J, Anderl-Straub S, von Arnim CAF, Beer A, Blesa R, Fortea J, Herukka SK, Portelius E, Pannee J, Zetterberg H, Blennow K, Nordberg A. Pittsburgh compound B imaging and cerebrospinal fluid amyloid-β in a multicentre European memory clinic study. Brain 2016; 139:2540-53. [PMID: 27401520 PMCID: PMC4995359 DOI: 10.1093/brain/aww160] [Citation(s) in RCA: 95] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Revised: 05/02/2016] [Accepted: 05/20/2016] [Indexed: 12/11/2022] Open
Abstract
The aim of this study was to assess the agreement between data on cerebral amyloidosis, derived using Pittsburgh compound B positron emission tomography and (i) multi-laboratory INNOTEST enzyme linked immunosorbent assay derived cerebrospinal fluid concentrations of amyloid-β42; (ii) centrally measured cerebrospinal fluid amyloid-β42 using a Meso Scale Discovery enzyme linked immunosorbent assay; and (iii) cerebrospinal fluid amyloid-β42 centrally measured using an antibody-independent mass spectrometry-based reference method. Moreover, we examined the hypothesis that discordance between amyloid biomarker measurements may be due to interindividual differences in total amyloid-β production, by using the ratio of amyloid-β42 to amyloid-β40 Our study population consisted of 243 subjects from seven centres belonging to the Biomarkers for Alzheimer's and Parkinson's Disease Initiative, and included subjects with normal cognition and patients with mild cognitive impairment, Alzheimer's disease dementia, frontotemporal dementia, and vascular dementia. All had Pittsburgh compound B positron emission tomography data, cerebrospinal fluid INNOTEST amyloid-β42 values, and cerebrospinal fluid samples available for reanalysis. Cerebrospinal fluid samples were reanalysed (amyloid-β42 and amyloid-β40) using Meso Scale Discovery electrochemiluminescence enzyme linked immunosorbent assay technology, and a novel, antibody-independent, mass spectrometry reference method. Pittsburgh compound B standardized uptake value ratio results were scaled using the Centiloid method. Concordance between Meso Scale Discovery/mass spectrometry reference measurement procedure findings and Pittsburgh compound B was high in subjects with mild cognitive impairment and Alzheimer's disease, while more variable results were observed for cognitively normal and non-Alzheimer's disease groups. Agreement between Pittsburgh compound B classification and Meso Scale Discovery/mass spectrometry reference measurement procedure findings was further improved when using amyloid-β42/40 Agreement between Pittsburgh compound B visual ratings and Centiloids was near complete. Despite improved agreement between Pittsburgh compound B and centrally analysed cerebrospinal fluid, a minority of subjects showed discordant findings. While future studies are needed, our results suggest that amyloid biomarker results may not be interchangeable in some individuals.
Collapse
Affiliation(s)
- Antoine Leuzy
- 1 Department of Neurobiology, Care Science, and Society, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Chiotis
- 1 Department of Neurobiology, Care Science, and Society, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden
| | - Steen G Hasselbalch
- 2 Danish Dementia Research Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Juha O Rinne
- 3 Division of Clinical Neurosciences, Turku University Hospital, University of Turku, Turku, Finland 4 Turku PET Centre, University of Turku, Turku, Finland
| | - Alexandre de Mendonça
- 5 Department of Neurology and Laboratory of Neurosciences, Faculty of Medicine, University of Lisbon, Lisbon, Portugal
| | - Markus Otto
- 6 Department of Neurology, Ulm University Hospital, Ulm, Germany
| | - Alberto Lleó
- 7 Department of Neurology, Institut d'Investigacions Biomèdiques, Hospital de Sant Pau, Barcelona, Spain 8 Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Miguel Castelo-Branco
- 9 Institute for Nuclear Sciences Applied to Health (ICNAS), Brain Imaging Network of Portugal, Coimbra, Portugal 10 Institute for Biomedical Imaging and Life Sciences (IBILI) and Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Isabel Santana
- 11 Department of Neurology, Coimbra University Hospital, Coimbra, Portugal 12 Centre for Neuroscience and Cell Biology (CNC), Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | | | | | | | - Ambros Beer
- 13 Department of Nuclear Medicine, Ulm University Hospital, Ulm, Germany
| | - Rafael Blesa
- 7 Department of Neurology, Institut d'Investigacions Biomèdiques, Hospital de Sant Pau, Barcelona, Spain 8 Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Juan Fortea
- 7 Department of Neurology, Institut d'Investigacions Biomèdiques, Hospital de Sant Pau, Barcelona, Spain 8 Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Sanna-Kaisa Herukka
- 14 Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Erik Portelius
- 15 Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Josef Pannee
- 15 Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- 15 Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden 16 Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK
| | - Kaj Blennow
- 15 Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Agneta Nordberg
- 1 Department of Neurobiology, Care Science, and Society, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden 17 Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| |
Collapse
|
37
|
Boccardi M, Yasui Y, Cerami C, Chiotis K, Garibotto V, Mattsson N, Sonni I, Kate MT, Porteri C, Jack CR, Winblad B, Frisoni GB. P2‐167: Roadmap to the Biomarker‐Based Diagnosis of Alzheimer's Disease. Alzheimers Dement 2016. [DOI: 10.1016/j.jalz.2016.06.1334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Marina Boccardi
- IRCCS FatebenefratelliBresciaItaly
- LANVIE-Laboratory of Neuroimaging of Aging, University of GenevaGenevaSwitzerland
| | - Yutaka Yasui
- School of Public Health, University of AlbertaEdmontonAB Canada
- St. Jude Children's Research HospitalMemphisTN USA
| | - Chiara Cerami
- Division of Neuroscience, San Raffaele Scientific InstituteMilanoItaly
- San Raffaele Turro Hospital, Milano, Università Vita-Salute San RaffaeleMilanoItaly
| | | | | | - Niklas Mattsson
- Skåne University Hospital Department of Neurology LundSweden
- Clinical Memory Research Unit, Lund UniversityLundSweden
- Memory Clinic, Skåne University Hospital, Lund UniversityLundSweden
| | - Ida Sonni
- Stanford University Division of Nuclear Medicine and Molecular Imaging StanfordCA USA
- Karolinska Institutet, Center for Psychiatry ResearchStockholmSweden
| | - Mara ten Kate
- Alzheimer Center and Department of Neurology Neuroscience Campus Amsterdam, VU University Medical CenterAmsterdamNetherlands
| | - Corinna Porteri
- Bioethics Unit, IRCCS Centro San Giovanni di DioBresciaItaly
| | | | - Bengt Winblad
- Karolinska Institutet, Center for Alzheimer Research Div. of Neurogeriatrics HuddingeSweden
| | - Giovanni B. Frisoni
- IRCCS Instituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of GenevaGenevaSwitzerland
| | | |
Collapse
|
38
|
Chiotis K, Saint-Aubert L, Savitcheva I, Jelic V, Wall A, Antoni G, Nordberg A. P3‐262: TAU PET Imaging in Non‐Alzheimer’S Disease Dementia: a Multimodal Paradigm. Alzheimers Dement 2016. [DOI: 10.1016/j.jalz.2016.06.1925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
| | | | | | - Vesna Jelic
- Karolinska University HospitalHuddingeSweden
| | | | | | - Agneta Nordberg
- Karolinska InstitutetStockholmSweden
- Karolinska University Hospital HuddingeStockholmSweden
| |
Collapse
|
39
|
Nordberg A, Chiotis K, Saint-Aubert L, Savitcheva I, Jelic V, Andersen P, Almkvist O, Wall A, Antoni G. O4‐07‐03: Longitudinal Changes in Regional Tau Deposition in Alzheimer's Disease and other Tauopathies Measured by [
18
F]‐TKH5317 Pet in a Multi‐Tracer Design. Alzheimers Dement 2016. [DOI: 10.1016/j.jalz.2016.06.645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Agneta Nordberg
- Karolinska University Hospital HuddingeStockholmSweden
- Karolinska InstitutetStockholmSweden
| | | | | | | | - Vesna Jelic
- Department of Geriatric Medicine, Genetics Unit Karolinska University HospitalStockholmSweden
| | - Pia Andersen
- Karolinska University Hospital HuddingeStockholmSweden
| | - Ove Almkvist
- Karolinska InstitutetStockholmSweden
- Stockholm UniversityStockholmSweden
| | | | | |
Collapse
|
40
|
Chiotis K, Saint-Aubert L, Savitcheva I, Jelic V, Wall A, Antoni G, Nordberg A. IC‐P‐189: TAU PET Imaging in Non‐Alzheimer’S Disease Dementia: A Multimodal Paradigm. Alzheimers Dement 2016. [DOI: 10.1016/j.jalz.2016.06.220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
| | | | | | - Vesna Jelic
- Karolinska University HospitalHuddingeSweden
| | | | | | - Agneta Nordberg
- Karolinska InstitutetStockholmSweden
- Karolinska University Hospital HuddingeStockholmSweden
| |
Collapse
|
41
|
Rodriguez-Vieitez E, Leuzy A, Chiotis K, Saint-Aubert L, Almkvist O, Wall A, Nordberg A. P4‐349: EARLY‐PHASE [11C]PIB PET is Comparable to [18F]FDG PET as a Marker of Disease Progression in Alzheimer's Disease. Alzheimers Dement 2016. [DOI: 10.1016/j.jalz.2016.07.094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
| | | | | | | | - Ove Almkvist
- Karolinska InstitutetStockholmSweden
- Stockholm UniversityStockholmSweden
| | | | - Agneta Nordberg
- Karolinska InstitutetStockholmSweden
- Karolinska University Hospital HuddingeStockholmSweden
| |
Collapse
|
42
|
Chiotis K, Saint-Aubert L, Savitcheva I, Jelic V, Andersen P, Jonasson M, Eriksson J, Lubberink M, Almkvist O, Wall A, Antoni G, Nordberg A. Imaging in-vivo tau pathology in Alzheimer's disease with THK5317 PET in a multimodal paradigm. Eur J Nucl Med Mol Imaging 2016; 43:1686-99. [PMID: 26996778 PMCID: PMC4932128 DOI: 10.1007/s00259-016-3363-z] [Citation(s) in RCA: 99] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2015] [Accepted: 03/08/2016] [Indexed: 11/30/2022]
Abstract
Purpose The aim of this study was to explore the cerebral distribution of the tau-specific PET tracer [18F]THK5317 (also known as (S)-[18F]THK5117) retention in different stages of Alzheimer’s disease; and study any associations with markers of hypometabolism and amyloid-beta deposition. Methods Thirty-three individuals were enrolled, including nine patients with Alzheimer’s disease dementia, thirteen with mild cognitive impairment (MCI), two with non-Alzheimer’s disease dementia, and nine healthy controls (five young and four elderly). In a multi-tracer PET design [18F]THK5317, [11C] Pittsburgh compound B ([11C]PIB), and [18F]FDG were used to assess tau pathology, amyloid-beta deposition and cerebral glucose metabolism, respectively. The MCI patients were further divided into MCI [11C]PIB-positive (n = 11) and MCI [11C]PIB-negative (n = 2) groups. Results Test-retest variability for [18F]THK5317-PET was very low (1.17–3.81 %), as shown by retesting five patients. The patients with prodromal (MCI [11C]PIB-positive) and dementia-stage Alzheimer’s disease had significantly higher [18F]THK5317 retention than healthy controls (p = 0.002 and p = 0.001, respectively) in areas exceeding limbic regions, and their discrimination from this control group (using the area under the curve) was >98 %. Focal negative correlations between [18F]THK5317 retention and [18F]FDG uptake were observed mainly in the frontal cortex, and focal positive correlations were found between [18F]THK5317 and [11C]PIB retentions isocortically. One patient with corticobasal degeneration syndrome and one with progressive supranuclear palsy showed no [11C]PIB but high [18F]THK5317 retentions with a different regional distribution from that in Alzheimer’s disease patients. Conclusions The tau-specific PET tracer [18F]THK5317 images in vivo the expected regional distribution of tau pathology. This distribution contrasts with the different patterns of hypometabolism and amyloid-beta deposition. Electronic supplementary material The online version of this article (doi:10.1007/s00259-016-3363-z) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Konstantinos Chiotis
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Laure Saint-Aubert
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Irina Savitcheva
- Department of Radiology, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Vesna Jelic
- Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Pia Andersen
- Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - My Jonasson
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.,Medical Physics, Uppsala University Hospital, Uppsala, Sweden
| | - Jonas Eriksson
- PET Centre, Uppsala University Hospital, Uppsala, Sweden.,Pre-clinical PET Platform, Uppsala University, Uppsala, Sweden
| | - Mark Lubberink
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Ove Almkvist
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden.,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden.,Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Anders Wall
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.,PET Centre, Uppsala University Hospital, Uppsala, Sweden
| | - Gunnar Antoni
- PET Centre, Uppsala University Hospital, Uppsala, Sweden.,Pre-clinical PET Platform, Uppsala University, Uppsala, Sweden
| | - Agneta Nordberg
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden. .,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden.
| |
Collapse
|
43
|
Leuzy A, Carter SF, Chiotis K, Almkvist O, Wall A, Nordberg A. Concordance and Diagnostic Accuracy of [11C]PIB PET and Cerebrospinal Fluid Biomarkers in a Sample of Patients with Mild Cognitive Impairment and Alzheimer's Disease. J Alzheimers Dis 2016; 45:1077-88. [PMID: 25649653 DOI: 10.3233/jad-142952] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) pathology can be quantified in vivo using cerebrospinal fluid (CSF) levels of amyloid-β1-42 (Aβ1-42), total-tau (t-tau), and phosphorylated tau (p-tau181p), as well as with positron emission tomography (PET) using [(11)C]Pittsburgh compound-B ([(11)C]PIB). Studies assessing concordance between these measures, however, have provided conflicting results. Moreover, it has been proposed that [(11)C]PIB PET may be of greater clinical utility in terms of identifying patients with mild cognitive impairment (MCI) who will progress to the dementia phase of AD. OBJECTIVE To determine concordance and classification accuracy of CSF biomarkers and [(11)C]PIB PET in a cohort of patients with MCI and AD. METHODS 68 patients (MCI, n = 33; AD, n = 35) underwent [(11)C]PIB PET and CSF sampling. Cutoffs of >1.41 ([(11)C]PIB), <450 pg/mL-and a more lenient cutoff of 550 pg/mL-(Aβ1-42), <6.5 (Aβ1-42/p-tau181p), and 1.14 (Aβ1-42/t-tau), were used to determine concordance. Logistic regression was used to determine classification accuracy with respect to stable MCI (sMCI) versus MCI who progressed to AD (pMCI). RESULTS Concordance between [(11)C]PIB and Aβ1-42 was highest for sMCI (67%), followed by AD (60%) and pMCI (33%). Agreement was increased across groups using Aβ1-42 <550 pg/mL, or Aβ1-42 to tau ratios. Logistic regression showed that classification accuracy of [(11)C]PIB, between sMCI and pMCI, was superior to Aβ1-42 (73% versus 58%), Aβ1-42/t-tau (63%), and Aβ1-42/p-tau181p (65%). CONCLUSION In the present study, [(11)C]PIB proved a better predictor of progression to AD in patients with MCI, relative to CSF measures of Aβ1-42 or Aβ1-42/tau. Discordance between PET and CSF markers for Aβ1-42 suggests they cannot be used interchangeably, as is currently the case.
Collapse
Affiliation(s)
- Antoine Leuzy
- Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Huddinge, Sweden
| | - Stephen F Carter
- Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Huddinge, Sweden Wolfson Molecular Imaging Centre, University of Manchester, Manchester, United Kingdom
| | - Konstantinos Chiotis
- Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Huddinge, Sweden
| | - Ove Almkvist
- Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Huddinge, Sweden Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Anders Wall
- Section of Nuclear Medicine and PET, Department of Radiology, Oncology and Radiation Sciences, Uppsala University, Uppsala, Sweden
| | - Agneta Nordberg
- Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Huddinge, Sweden Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| |
Collapse
|
44
|
Rodriguez-Vieitez E, Leuzy A, Chiotis K, Saint-Aubert L, Nordberg A. Comparison of Early-Phase (S)-[18F]THK5117 and [11C]PIB PET imaging to assess brain perfusion in Alzheimer’s disease. Neurobiol Aging 2016. [DOI: 10.1016/j.neurobiolaging.2016.01.095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
|
45
|
Rodriguez-Vieitez E, Carter SF, Chiotis K, Saint-Aubert L, Leuzy A, Schöll M, Almkvist O, Wall A, Långström B, Nordberg A. Comparison of Early-Phase 11C-Deuterium-l-Deprenyl and 11C-Pittsburgh Compound B PET for Assessing Brain Perfusion in Alzheimer Disease. J Nucl Med 2016; 57:1071-7. [PMID: 26912447 DOI: 10.2967/jnumed.115.168732] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2015] [Accepted: 01/29/2016] [Indexed: 01/07/2023] Open
Abstract
UNLABELLED The PET tracer (11)C-deuterium-L-deprenyl ((11)C-DED) has been used to visualize activated astrocytes in vivo in patients with Alzheimer disease (AD). In this multitracer PET study, early-phase (11)C-DED and (11)C-Pittsburgh compound B ((11)C-PiB) (eDED and ePiB, respectively) were compared as surrogate markers of brain perfusion, and the extent to which (11)C-DED binding is influenced by brain perfusion was investigated. METHODS (11)C-DED, (11)C-PiB, and (18)F-FDG dynamic PET scans were obtained in age-matched groups comprising AD patients (n = 8), patients with mild cognitive impairment (n = 17), and healthy controls (n = 16). A modified reference Patlak model was used to quantify (11)C-DED binding. A simplified reference tissue model was applied to both (11)C-DED and (11)C-PiB to measure brain perfusion relative to the cerebellar gray matter (R1) and binding potentials. (11)C-PiB retention and (18)F-FDG uptake were also quantified as target-to-pons SUV ratios in 12 regions of interest (ROIs). RESULTS The strongest within-subject correlations with the corresponding R1 values (R1,DED and R1,PiB, respectively) and with (18)F-FDG uptake were obtained when the eDED and ePiB PET data were measured 1-4 min after injection. The optimum eDED/ePiB intervals also showed strong, significant ROI-based intersubject Pearson correlations with R1,DED/R1,PiB and with (18)F-FDG uptake, whereas (11)C-DED binding was largely independent of brain perfusion, as measured by eDED. Corresponding voxelwise correlations confirmed the ROI-based results. Temporoparietal eDED or ePiB brain perfusion measurements were highly discriminative between patient and control groups, with discriminative ability statistically comparable to that of temporoparietal (18)F-FDG glucose metabolism. Hypometabolism extended over wider regions than hypoperfusion in patient groups compared with controls. CONCLUSION The 1- to 4-min early-frame intervals of (11)C-DED or (11)C-PiB are suitable surrogate measures for brain perfusion. (11)C-DED binding is independent of brain perfusion, and thus (11)C-DED PET can provide information on both functional (brain perfusion) and pathologic (astrocytosis) aspects from a single PET scan. In comparison with glucose metabolism, early-phase (11)C-DED and (11)C-PiB perfusion appear to provide complementary rather than redundant information.
Collapse
Affiliation(s)
- Elena Rodriguez-Vieitez
- Division of Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Stephen F Carter
- Division of Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden Wolfson Molecular Imaging Centre, Institute of Brain, Behaviour and Mental Health, University of Manchester, Manchester, United Kingdom
| | - Konstantinos Chiotis
- Division of Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Laure Saint-Aubert
- Division of Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Antoine Leuzy
- Division of Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Michael Schöll
- Division of Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Ove Almkvist
- Division of Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden Department of Psychology, Stockholm University, Stockholm, Sweden Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Anders Wall
- Department of Surgical Sciences, Section of Nuclear Medicine & PET, Uppsala University, Uppsala, Sweden; and
| | | | - Agneta Nordberg
- Division of Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| |
Collapse
|
46
|
Rodriguez-Vieitez E, Saint-Aubert L, Carter SF, Almkvist O, Farid K, Schöll M, Chiotis K, Thordardottir S, Graff C, Wall A, Långström B, Nordberg A. Diverging longitudinal changes in astrocytosis and amyloid PET in autosomal dominant Alzheimer's disease. Brain 2016; 139:922-36. [PMID: 26813969 PMCID: PMC4766380 DOI: 10.1093/brain/awv404] [Citation(s) in RCA: 192] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 11/20/2015] [Indexed: 11/14/2022] Open
Abstract
See Schott and Fox (doi:
10.1093/brain/awv405
) for a scientific commentary on this article.
Alzheimer’s disease is a multifactorial dementia disorder characterized by early amyloid-β, tau deposition, glial activation and neurodegeneration, where the interrelationships between the different pathophysiological events are not yet well characterized. In this study, longitudinal multitracer positron emission tomography imaging of individuals with autosomal dominant or sporadic Alzheimer’s disease was used to quantify the changes in regional distribution of brain astrocytosis (tracer
11
C-deuterium-L-deprenyl), fibrillar amyloid-β plaque deposition (
11
C-Pittsburgh compound B), and glucose metabolism (
18
F-fluorodeoxyglucose) from early presymptomatic stages over an extended period to clinical symptoms. The 52 baseline participants comprised autosomal dominant Alzheimer’s disease mutation carriers (
n =
11; 49.6 ± 10.3 years old) and non-carriers (
n =
16; 51.1 ± 14.2 years old; 10 male), and patients with sporadic mild cognitive impairment (
n =
17; 61.9 ± 6.4 years old; nine male) and sporadic Alzheimer’s disease (
n =
8; 63.0 ± 6.5 years old; five male); for confidentiality reasons, the gender of mutation carriers is not revealed. The autosomal dominant Alzheimer’s disease participants belonged to families with known mutations in either presenilin 1 (
PSEN1
) or amyloid precursor protein (
APPswe
or
APParc
) genes. Sporadic mild cognitive impairment patients were further divided into
11
C-Pittsburgh compound B-positive (
n =
13; 62.0 ± 6.4; seven male) and
11
C-Pittsburgh compound B-negative (
n =
4; 61.8 ± 7.5 years old; two male) groups using a neocortical standardized uptake value ratio cut-off value of 1.41, which was calculated with respect to the cerebellar grey matter. All baseline participants underwent multitracer positron emission tomography scans, cerebrospinal fluid biomarker analysis and neuropsychological assessment. Twenty-six of the participants underwent clinical and imaging follow-up examinations after 2.8 ± 0.6 years. By using linear mixed-effects models, fibrillar amyloid-β plaque deposition was first observed in the striatum of presymptomatic autosomal dominant Alzheimer’s disease carriers from 17 years before expected symptom onset; at about the same time, astrocytosis was significantly elevated and then steadily declined. Diverging from the astrocytosis pattern, amyloid-β plaque deposition increased with disease progression. Glucose metabolism steadily declined from 10 years after initial amyloid-β plaque deposition. Patients with sporadic mild cognitive impairment who were
11
C-Pittsburgh compound B-positive at baseline showed increasing amyloid-β plaque deposition and decreasing glucose metabolism but, in contrast to autosomal dominant Alzheimer’s disease carriers, there was no significant longitudinal decline in astrocytosis over time. The prominent initially high and then declining astrocytosis in autosomal dominant Alzheimer’s disease carriers, contrasting with the increasing amyloid-β plaque load during disease progression, suggests astrocyte activation is implicated in the early stages of Alzheimer’s disease pathology.
Collapse
Affiliation(s)
- Elena Rodriguez-Vieitez
- 1 Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, 141 57 Huddinge, Stockholm, Sweden
| | - Laure Saint-Aubert
- 1 Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, 141 57 Huddinge, Stockholm, Sweden
| | - Stephen F Carter
- 1 Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, 141 57 Huddinge, Stockholm, Sweden
| | - Ove Almkvist
- 1 Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, 141 57 Huddinge, Stockholm, Sweden 2 Department of Psychology, Stockholm University, 106 91 Stockholm, Sweden 3 Department of Geriatric Medicine, Karolinska University Hospital Huddinge, 141 86, Stockholm, Sweden
| | - Karim Farid
- 1 Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, 141 57 Huddinge, Stockholm, Sweden
| | - Michael Schöll
- 1 Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, 141 57 Huddinge, Stockholm, Sweden
| | - Konstantinos Chiotis
- 1 Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, 141 57 Huddinge, Stockholm, Sweden
| | - Steinunn Thordardottir
- 3 Department of Geriatric Medicine, Karolinska University Hospital Huddinge, 141 86, Stockholm, Sweden 4 Department NVS, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, 141 57 Huddinge, Stockholm, Sweden
| | - Caroline Graff
- 3 Department of Geriatric Medicine, Karolinska University Hospital Huddinge, 141 86, Stockholm, Sweden 4 Department NVS, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, 141 57 Huddinge, Stockholm, Sweden
| | - Anders Wall
- 5 Department of Surgical Sciences, Section of Nuclear Medicine & PET, Uppsala University, 751 85 Uppsala, Sweden
| | - Bengt Långström
- 6 Department of Chemistry, Uppsala University, 701 05 Uppsala, Sweden
| | - Agneta Nordberg
- 1 Department NVS, Centre for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, 141 57 Huddinge, Stockholm, Sweden 3 Department of Geriatric Medicine, Karolinska University Hospital Huddinge, 141 86, Stockholm, Sweden
| |
Collapse
|
47
|
Jonasson M, Wall A, Chiotis K, Saint-Aubert L, Wilking H, Sprycha M, Borg B, Thibblin A, Eriksson J, Sörensen J, Antoni G, Nordberg A, Lubberink M. Tracer Kinetic Analysis of (S)-¹⁸F-THK5117 as a PET Tracer for Assessing Tau Pathology. J Nucl Med 2016; 57:574-81. [PMID: 26795290 DOI: 10.2967/jnumed.115.158519] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2015] [Accepted: 11/19/2015] [Indexed: 11/16/2022] Open
Abstract
UNLABELLED Because a correlation between tau pathology and the clinical symptoms of Alzheimer disease (AD) has been hypothesized, there is increasing interest in developing PET tracers that bind specifically to tau protein. The aim of this study was to evaluate tracer kinetic models for quantitative analysis and generation of parametric images for the novel tau ligand (S)-(18)F-THK5117. METHODS Nine subjects (5 with AD, 4 with mild cognitive impairment) received a 90-min dynamic (S)-(18)F-THK5117 PET scan. Arterial blood was sampled for measurement of blood radioactivity and metabolite analysis. Volume-of-interest (VOI)-based analysis was performed using plasma-input models; single-tissue and 2-tissue (2TCM) compartment models and plasma-input Logan and reference tissue models; and simplified reference tissue model (SRTM), reference Logan, and SUV ratio (SUVr). Cerebellum gray matter was used as the reference region. Voxel-level analysis was performed using basis function implementations of SRTM, reference Logan, and SUVr. Regionally averaged voxel values were compared with VOI-based values from the optimal reference tissue model, and simulations were made to assess accuracy and precision. In addition to 90 min, initial 40- and 60-min data were analyzed. RESULTS Plasma-input Logan distribution volume ratio (DVR)-1 values agreed well with 2TCM DVR-1 values (R(2)= 0.99, slope = 0.96). SRTM binding potential (BP(ND)) and reference Logan DVR-1 values were highly correlated with plasma-input Logan DVR-1 (R(2)= 1.00, slope ≈ 1.00) whereas SUVr(70-90)-1 values correlated less well and overestimated binding. Agreement between parametric methods and SRTM was best for reference Logan (R(2)= 0.99, slope = 1.03). SUVr(70-90)-1 values were almost 3 times higher than BP(ND) values in white matter and 1.5 times higher in gray matter. Simulations showed poorer accuracy and precision for SUVr(70-90)-1 values than for the other reference methods. SRTM BP(ND) and reference Logan DVR-1 values were not affected by a shorter scan duration of 60 min. CONCLUSION SRTM BP(ND) and reference Logan DVR-1 values were highly correlated with plasma-input Logan DVR-1 values. VOI-based data analyses indicated robust results for scan durations of 60 min. Reference Logan generated quantitative (S)-(18)F-THK5117 DVR-1 parametric images with the greatest accuracy and precision and with a much lower white-matter signal than seen with SUVr(70-90)-1 images.
Collapse
Affiliation(s)
- My Jonasson
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden Medical Physics, Uppsala University Hospital, Uppsala, Sweden
| | - Anders Wall
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden PET Centre, Uppsala University Hospital, Uppsala, Sweden
| | - Konstantinos Chiotis
- Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
| | - Laure Saint-Aubert
- Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
| | - Helena Wilking
- PET Centre, Uppsala University Hospital, Uppsala, Sweden
| | | | - Beatrice Borg
- PET Centre, Uppsala University Hospital, Uppsala, Sweden
| | - Alf Thibblin
- PET Centre, Uppsala University Hospital, Uppsala, Sweden
| | - Jonas Eriksson
- PET Centre, Uppsala University Hospital, Uppsala, Sweden Pre-clinical PET Platform, Uppsala University, Uppsala, Sweden; and
| | - Jens Sörensen
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden PET Centre, Uppsala University Hospital, Uppsala, Sweden
| | - Gunnar Antoni
- PET Centre, Uppsala University Hospital, Uppsala, Sweden Pre-clinical PET Platform, Uppsala University, Uppsala, Sweden; and
| | - Agneta Nordberg
- Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Mark Lubberink
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden Medical Physics, Uppsala University Hospital, Uppsala, Sweden
| |
Collapse
|
48
|
Rodriguez-Vieitez E, Carter SF, Saint-Aubert L, Almkvist O, Farid K, Schöll M, Chiotis K, Thordardottir S, Wall A, Graff C, Långström B, Nordberg A. IC‐P‐126: Divergent pattern of changes in astrocytosis and fibrillar amyloid plaques as measured by PET in autosomal‐dominant and sporadic Alzheimer's disease. Alzheimers Dement 2015. [DOI: 10.1016/j.jalz.2015.06.148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Stephen F. Carter
- Karolinska InstitutetStockholmSweden
- University of ManchesterManchesterUnited Kingdom
| | | | - Ove Almkvist
- Karolinska InstitutetStockholmSweden
- Stockholm UniversityStockholmSweden
| | | | - Michael Schöll
- Karolinska InstitutetStockholmSweden
- University of GothenburgGothenburgSweden
| | | | | | | | - Caroline Graff
- Karolinska InstitutetDepartment of Neurobiology, Care Sciences and Society (NVS), Center for Alzheimer Research, Division of Neurogeriatrics14157HuddingeSweden
| | | | - Agneta Nordberg
- Karolinska InstitutetStockholmSweden
- Karolinska University Hospital HuddingeStockholmSweden
| |
Collapse
|
49
|
Rodriguez-Vieitez E, Carter SF, Saint-Aubert L, Almkvist O, Farid K, Schöll M, Chiotis K, Thordardottir S, Wall A, Graff C, Långström B, Nordberg A. O1‐02‐03: Divergent pattern of changes in astrocytosis and fibrillar amyloid plaques as measured by PET in autosomal‐dominant and sporadic Alzheimer's disease. Alzheimers Dement 2015. [DOI: 10.1016/j.jalz.2015.07.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Affiliation(s)
| | - Stephen F. Carter
- Karolinska InstitutetStockholmSweden
- University of ManchesterManchesterUnited Kingdom
| | | | - Ove Almkvist
- Karolinska InstitutetStockholmSweden
- Stockholm UniversityStockholmSweden
| | | | - Michael Schöll
- Karolinska InstitutetStockholmSweden
- University of GothenburgGothenburgSweden
| | | | | | | | - Caroline Graff
- Karolinska InstitutetDepartment of Neurobiology, Care Sciences and Society (NVS), Center for Alzheimer Research, Division of NeurogeriatricsHuddingeSweden
| | | | - Agneta Nordberg
- Karolinska InstitutetStockholmSweden
- Karolinska University Hospital HuddingeStockholmSweden
| |
Collapse
|
50
|
Chiotis K, Carter SF, Farid K, Nordberg A. P3‐218: AGE IS A SIGNIFICANT FACTOR IN DETERMINING PATHOLOGICAL POSITIVITY MEASURED WITH [18F]FLORBETAPIR PET. Alzheimers Dement 2014. [DOI: 10.1016/j.jalz.2014.05.1309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
| | - Stephen F. Carter
- Wolfson Molecular Imaging Center, University of ManchesterManchesterUnited Kingdom
| | | | | |
Collapse
|