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Scheijbeler EP, de Haan W, Coomans EM, den Braber A, Tomassen J, ten Kate M, Konijnenberg E, Collij LE, van de Giessen E, Barkhof F, Visser PJ, Stam CJ, Gouw AA. Amyloid-β deposition predicts oscillatory slowing of magnetoencephalography signals and a reduction of functional connectivity over time in cognitively unimpaired adults. Brain Commun 2025; 7:fcaf018. [PMID: 40008329 PMCID: PMC11851009 DOI: 10.1093/braincomms/fcaf018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 12/11/2024] [Accepted: 01/17/2025] [Indexed: 02/27/2025] Open
Abstract
With the ongoing developments in the field of anti-amyloid therapy for Alzheimer's disease, it is crucial to better understand the longitudinal associations between amyloid-β deposition and altered network activity in the living human brain. We included 110 cognitively unimpaired individuals (67.9 ± 5.7 years), who underwent [18F]flutemetamol (amyloid-β)-PET imaging and resting-state magnetoencephalography (MEG) recording at baseline and 4-year follow-up. We tested associations between baseline amyloid-β deposition and MEG measures (oscillatory power and functional connectivity). Next, we examined the relationship between baseline amyloid-β deposition and longitudinal MEG measures, as well as between baseline MEG measures and longitudinal amyloid-β deposition. Finally, we assessed associations between longitudinal changes in both amyloid-β deposition and MEG measures. Analyses were performed using linear mixed models corrected for age, sex and family. At baseline, amyloid-β deposition in orbitofrontal-posterior cingulate regions (i.e. early Alzheimer's disease regions) was associated with higher theta (4-8 Hz) power (β = 0.17, P < 0.01) in- and lower functional connectivity [inverted Joint Permutation Entropy (JPEinv) theta, β = -0.24, P < 0.001] of these regions, lower whole-brain beta (13-30 Hz) power (β = -0.13, P < 0.05) and lower whole-brain functional connectivity (JPEinv theta, β = -0.18, P < 0.001). Whole-brain amyloid-β deposition was associated with higher whole-brain theta power (β = 0.17, P < 0.05), lower whole-brain beta power (β = -0.13, P < 0.05) and lower whole-brain functional connectivity (JPEinv theta, β = -0.21, P < 0.001). Baseline amyloid-β deposition in early Alzheimer's disease regions also predicted future oscillatory slowing, reflected by increased theta power over time in early Alzheimer's disease regions and across the whole brain (β = 0.11, β = 0.08, P < 0.001), as well as decreased whole-brain beta power over time (β = -0.04, P < 0.05). Baseline amyloid-β deposition in early Alzheimer's disease regions also predicted a reduction in functional connectivity between these regions and the rest of the brain over time (JPEinv theta, β = -0.07, P < 0.05). Baseline whole-brain amyloid-β deposition was associated with increased whole-brain theta power over time (β = 0.08, P < 0.01). Baseline MEG measures were not associated with longitudinal amyloid-β deposition. Longitudinal changes in amyloid-β deposition in early Alzheimer's disease regions were associated with longitudinal changes in functional connectivity of early Alzheimer's disease regions (JPEinv theta, β = -0.19, P < 0.05) and the whole brain [corrected amplitude envelope correlations alpha (8-13 Hz), β = -0.22, P < 0.05]. Finally, longitudinal changes in whole-brain amyloid-β deposition were associated with longitudinal changes in whole-brain relative theta power (β = 0.21, P < 0.05). Disruptions of oscillatory power and functional connectivity appear to represent early functional consequences of emerging amyloid-β deposition in cognitively unimpaired individuals. These findings suggest a role for neurophysiology in monitoring disease progression and potential treatment effects in pre-clinical Alzheimer's disease.
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Affiliation(s)
- Elliz P Scheijbeler
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Department of Clinical Neurophysiology & MEG Center, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
| | - Willem de Haan
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Emma M Coomans
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Mara ten Kate
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Elles Konijnenberg
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, 202 13 Malmö, Sweden
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, WC1N 3BG London, UK
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, 6229 ET Maastricht, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology & MEG Center, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
| | - Alida A Gouw
- Department of Clinical Neurophysiology & MEG Center, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
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2
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Zarovniaeva V, Anwar S, Kazmi S, Cortez Perez K, Sandhu S, Mohammed L. The Role of PET Detection of Biomarkers in Early Diagnosis, Progression, and Prognosis of Alzheimer's Disease: A Systematic Review. Cureus 2025; 17:e77781. [PMID: 39981456 PMCID: PMC11841692 DOI: 10.7759/cureus.77781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/21/2025] [Indexed: 02/22/2025] Open
Abstract
Alzheimer's disease (AD) is a chronic neurologic disease characterized by the deposition of Aβ amyloid and tau protein in the neural tissue, which leads to gradual and irreversible deterioration of memory. Positron emission tomography (PET) showed high potential in diagnosing AD. It provided a unique opportunity to assess cerebral amyloid plaques and tau neurofibrillary tangle deposits in the brain tissue without invasive procedures in vivo. Many studies have been focused on PET diagnosis of AD in recent years, which has significantly improved diagnosis and treatment strategies. This review study aims to summarize the role and emphasize the benefits of PET detection of AD biomarkers in early stages, clinical and histological progression assessment, and predicting AD outcomes. Relevant articles published in the last five years, from September 1, 2019, to October 30, 2024, were searched through authentic databases such as PubMed, PubMed Central, Europe PubMed Central, Science Direct, Cochrane Library, and Google Scholar. In this systematic review, we included articles published in English, with available full text, based on human trials, with relevant information regarding participants who underwent PET of the brain to diagnose AD biomarkers. The study strictly followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines and recommendations. The Joanna Briggs Institute (JBI) critical appraisal methods were used to evaluate all selected cross-sectional research, and the Newcastle-Ottawa Scale (NOS) was used to assess the cohort and longitudinal studies. Eleven relevant articles were included in this systematic review, and 2,203 males and females participated. The study revealed that the detection of beta-amyloid PET showed high-precious results in early diagnosis of AD. The detection of tau protein showed a high potential for estimation of the clinical and histological progression and prognosis of AD in longitudinal studies. Identifying amyloid and tau protein accumulation and glucose metabolism alterations is highly predictive of neurodegeneration in preclinical and mild cognitive impairment stages.
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Affiliation(s)
- Viktoriia Zarovniaeva
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Summayya Anwar
- Biosciences, COMSATS University Islamabad, Islamabad, PAK
| | - Saba Kazmi
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Kimberly Cortez Perez
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Sehej Sandhu
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Lubna Mohammed
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
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Bao YW, Wang ZJ, Shea YF, Chiu PKC, Kwan JS, Chan FHW, Mak HKF. Combined Quantitative amyloid-β PET and Structural MRI Features Improve Alzheimer's Disease Classification in Random Forest Model - A Multicenter Study. Acad Radiol 2024; 31:5154-5163. [PMID: 39003227 DOI: 10.1016/j.acra.2024.06.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 04/18/2024] [Accepted: 06/24/2024] [Indexed: 07/15/2024]
Abstract
RATIONALE AND OBJECTIVES Prior to clinical presentations of Alzheimer's Disease (AD), neuropathological changes, such as amyloid-β and brain atrophy, have accumulated at the earlier stages of the disease. The combination of such biomarkers assessed by multiple modalities commonly improves the likelihood of AD etiology. We aimed to explore the discriminative ability of Aβ PET features and whether combining Aβ PET and structural MRI features can improve the classification performance of the machine learning model in older healthy control (OHC) and mild cognitive impairment (MCI) from AD. MATERIAL AND METHODS We collected 94 AD patients, 82 MCI patients, and 85 OHC from three different cohorts. 17 global/regional Aβ features in Centiloid, 122 regional volume, and 68 regional cortical thickness were extracted as imaging features. Single or combined modality features were used to train the random forest model on the testing set. The top 10 features were sorted based on the Gini index in each binary classification. RESULTS The results showed that AUC scores were 0.81/0.86 and 0.69/0.68 using sMRI/Aβ PET features on the testing set in differentiating OHC and MCI from AD. The performance was improved while combining two-modality features with an AUC of 0.89 and an AUC of 0.71 in two classifications. Compared to sMRI features, particular Aβ PET features contributed more to differentiating AD from others. CONCLUSION Our study demonstrated the discriminative ability of Aβ PET features in differentiating AD from OHC and MCI. A combination of Aβ PET and structural MRI features can improve the RF model performance.
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Affiliation(s)
- Yi-Wen Bao
- Department of Medical Imaging Center, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, China (Y-W.B.)
| | - Zuo-Jun Wang
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China (Z-J.W., H.K-F.M.)
| | - Yat-Fung Shea
- Department of Medicine, Queen Mary Hospital, Hong Kong SAR, China (Y-F.S., P.K-C.C., J.S.K., F.H-W.C.)
| | - Patrick Ka-Chun Chiu
- Department of Medicine, Queen Mary Hospital, Hong Kong SAR, China (Y-F.S., P.K-C.C., J.S.K., F.H-W.C.)
| | - Joseph Sk Kwan
- Department of Medicine, Queen Mary Hospital, Hong Kong SAR, China (Y-F.S., P.K-C.C., J.S.K., F.H-W.C.)
| | - Felix Hon-Wai Chan
- Department of Medicine, Queen Mary Hospital, Hong Kong SAR, China (Y-F.S., P.K-C.C., J.S.K., F.H-W.C.)
| | - Henry Ka-Fung Mak
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China (Z-J.W., H.K-F.M.).
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Kim GH, Kim BR, Yoon HJ, Jeong JH. Elevated cerebral blood flow proxy with increased beta-amyloid burden in Alzheimer's disease preclinical phase evaluated by dual-phase 18F-florbetaben positron emission tomography. Sci Rep 2024; 14:18480. [PMID: 39122860 PMCID: PMC11315901 DOI: 10.1038/s41598-024-68916-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 07/30/2024] [Indexed: 08/12/2024] Open
Abstract
This study investigated the earliest change of cerebral blood flow (CBF) and its relationship with β-amyloid (Aβ) burden in preclinical Alzheimer's disease (AD) employing dual-phase 18F-florbetaben (FBB) PET. Seventy-one cognitively normal (NC) individuals were classified as Aβ negative (Aβ-NC) or positive (Aβ+NC) based on two different cutoff values: an SUVR of > 1.08 and a Centiloid scale of > 20. The PET scans were acquired in two phases: an early phase (0-10 min, eFBB) and a delayed phase (90-110 min, dFBB), which were averaged to generate single-frame images for each phase. Furthermore, an R1 parametric map was generated from the early phase data using a simplified reference tissue model. We conducted regional and voxel-based analyses to compare the eFBB, dFBB, and R1 images between the Aβ positive and negative groups. In addition, the correlations between the CBF proxy R1 and the dFBB SUVR were analyzed. The Aβ+NC group showed significantly higher dFBB SUVR in both the global cerebral cortex and target regions compared to the Aβ-NC group, while no significant differences were observed in eFBB SUVR between the two groups. Furthermore, the Aβ+NC group exhibited significantly higher R1 values, a proxy for cerebral perfusion, in both the global cerebral cortex and target regions compared to the Aβ-NC group. Significant positive correlations were observed between R1 and dFBB SUVR in both the global cerebral cortex and target regions, which remained significant after controlling for demographics and cognitive profiles, except for the medial temporal and occipital cortices. The findings reveal increased CBF in preclinical AD and a positive correlation between CBF and amyloid pathology. The positive correlation between R1 and amyloid burden may indicate a compensatory mechanism in the preclinical stage of Alzheimer's disease, but to elucidate this hypothesis, further longitudinal observational studies are necessary.
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Affiliation(s)
- Geon Ha Kim
- Department of Neurology, Ewha Womans University College of Medicine, Seoul, Republic of Korea
| | - Bori R Kim
- Department of Neurology, Ewha Womans University College of Medicine, Seoul, Republic of Korea
- Ewha Medical Research Institute, Ewha Womans University, Seoul, Republic of Korea
| | - Hai-Jeon Yoon
- Department of Nuclear Medicine, Ewha Womans University, College of Medicine, Seoul, Republic of Korea.
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University College of Medicine, Seoul, Republic of Korea.
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5
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van den Berg RL, de Boer C, Zwan MD, Jutten RJ, van Liere M, van de Glind MCABJ, Dubbelman MA, Schlüter LM, van Harten AC, Teunissen CE, van de Giessen E, Barkhof F, Collij LE, Robin J, Simpson W, Harrison JE, van der Flier WM, Sikkes SAM. Digital remote assessment of speech acoustics in cognitively unimpaired adults: feasibility, reliability and associations with amyloid pathology. Alzheimers Res Ther 2024; 16:176. [PMID: 39090738 PMCID: PMC11293000 DOI: 10.1186/s13195-024-01543-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Accepted: 07/24/2024] [Indexed: 08/04/2024]
Abstract
BACKGROUND Digital speech assessment has potential relevance in the earliest, preclinical stages of Alzheimer's disease (AD). We evaluated the feasibility, test-retest reliability, and association with AD-related amyloid-beta (Aβ) pathology of speech acoustics measured over multiple assessments in a remote setting. METHODS Fifty cognitively unimpaired adults (Age 68 ± 6.2 years, 58% female, 46% Aβ-positive) completed remote, tablet-based speech assessments (i.e., picture description, journal-prompt storytelling, verbal fluency tasks) for five days. The testing paradigm was repeated after 2-3 weeks. Acoustic speech features were automatically extracted from the voice recordings, and mean scores were calculated over the 5-day period. We assessed feasibility by adherence rates and usability ratings on the System Usability Scale (SUS) questionnaire. Test-retest reliability was examined with intraclass correlation coefficients (ICCs). We investigated the associations between acoustic features and Aβ-pathology, using linear regression models, adjusted for age, sex and education. RESULTS The speech assessment was feasible, indicated by 91.6% adherence and usability scores of 86.0 ± 9.9. High reliability (ICC ≥ 0.75) was found across averaged speech samples. Aβ-positive individuals displayed a higher pause-to-word ratio in picture description (B = -0.05, p = 0.040) and journal-prompt storytelling (B = -0.07, p = 0.032) than Aβ-negative individuals, although this effect lost significance after correction for multiple testing. CONCLUSION Our findings support the feasibility and reliability of multi-day remote assessment of speech acoustics in cognitively unimpaired individuals with and without Aβ-pathology, which lays the foundation for the use of speech biomarkers in the context of early AD.
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Affiliation(s)
- Rosanne L van den Berg
- Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Department of Clinical, Neuro and Developmental Psychology, Faculty of Movement and Behavioral Sciences, VU University, Amsterdam, The Netherlands.
| | - Casper de Boer
- Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Marissa D Zwan
- Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Roos J Jutten
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Mariska van Liere
- Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Marie-Christine A B J van de Glind
- Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center Groningen, Department of Neurology, Department of Neuropsychology and Department of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands
- Alzheimer Center Erasmus MC and Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Mark A Dubbelman
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Lisa Marie Schlüter
- Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Argonde C van Harten
- Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Neurochemistry Laboratory and Biobank, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands
| | - Elsmarieke van de Giessen
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Lyduine E Collij
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Malmö, Lund, Sweden
| | | | | | - John E Harrison
- Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands
- Scottish Brain Sciences, Edinburgh, UK
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Sietske A M Sikkes
- Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Clinical, Neuro and Developmental Psychology, Faculty of Movement and Behavioral Sciences, VU University, Amsterdam, The Netherlands
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6
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Mastenbroek SE, Sala A, Vállez García D, Shekari M, Salvadó G, Lorenzini L, Pieperhoff L, Wink AM, Lopes Alves I, Wolz R, Ritchie C, Boada M, Visser PJ, Bucci M, Farrar G, Hansson O, Nordberg AK, Ossenkoppele R, Barkhof F, Gispert JD, Rodriguez-Vieitez E, Collij LE. Continuous β-Amyloid CSF/PET Imbalance Model to Capture Alzheimer Disease Heterogeneity. Neurology 2024; 103:e209419. [PMID: 38862136 PMCID: PMC11244744 DOI: 10.1212/wnl.0000000000209419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 03/29/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Discordance between CSF and PET biomarkers of β-amyloid (Aβ) might reflect an imbalance between soluble and aggregated species, possibly reflecting disease heterogeneity. Previous studies generally used binary cutoffs to assess discrepancies in CSF/PET biomarkers, resulting in a loss of information on the extent of discordance. In this study, we (1) jointly modeled Aβ-CSF/PET data to derive a continuous measure of the imbalance between soluble and fibrillar pools of Aβ, (2) investigated factors contributing to this imbalance, and (3) examined associations with cognitive trajectories. METHODS Across 822 cognitively unimpaired (n = 261) and cognitively impaired (n = 561) Alzheimer's Disease Neuroimaging Initiative individuals (384 [46.7%] females, mean age 73.0 ± 7.4 years), we fitted baseline CSF-Aβ42 and global Aβ-PET to a hyperbolic regression model, deriving a participant-specific Aβ-aggregation score (standardized residuals); negative values represent more soluble relative to aggregated Aβ and positive values more aggregated relative to soluble Aβ. Using linear models, we investigated whether methodological factors, demographics, CSF biomarkers, and vascular burden contributed to Aβ-aggregation scores. With linear mixed models, we assessed whether Aβ-aggregation scores were predictive of cognitive functioning. Analyses were repeated in an early independent validation cohort of 383 Amyloid Imaging to Prevent Alzheimer's Disease Prognostic and Natural History Study individuals (224 [58.5%] females, mean age 65.2 ± 6.9 years). RESULTS The imbalance model could be fit (pseudo-R2 = 0.94) in both cohorts, across CSF kits and PET tracers. Although no associations were observed with the main methodological factors, lower Aβ-aggregation scores were associated with larger ventricular volume (β = 0.13, p < 0.001), male sex (β = -0.18, p = 0.019), and homozygous APOE-ε4 carriership (β = -0.56, p < 0.001), whereas higher scores were associated with increased uncorrected CSF p-tau (β = 0.17, p < 0.001) and t-tau (β = 0.16, p < 0.001), better baseline executive functioning (β = 0.12, p < 0.001), and slower global cognitive decline (β = 0.14, p = 0.006). In the validation cohort, we replicated the associations with APOE-ε4, CSF t-tau, and, although modestly, with cognition. DISCUSSION We propose a novel continuous model of Aβ CSF/PET biomarker imbalance, accurately describing heterogeneity in soluble vs aggregated Aβ pools in 2 independent cohorts across the full Aβ continuum. Aβ-aggregation scores were consistently associated with genetic and AD-associated CSF biomarkers, possibly reflecting disease heterogeneity beyond methodological influences.
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Affiliation(s)
- Sophie E Mastenbroek
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Arianna Sala
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - David Vállez García
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Mahnaz Shekari
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Gemma Salvadó
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Luigi Lorenzini
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Leonard Pieperhoff
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Alle Meije Wink
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Isadora Lopes Alves
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Robin Wolz
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Craig Ritchie
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Mercè Boada
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Pieter Jelle Visser
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Marco Bucci
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Gill Farrar
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Oskar Hansson
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Agneta K Nordberg
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Rik Ossenkoppele
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Frederik Barkhof
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Juan Domingo Gispert
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Elena Rodriguez-Vieitez
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Lyduine E Collij
- From the Department of Radiology and Nuclear Medicine (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc; Amsterdam Neuroscience (S.E.M., D.V.G., L.L., L.P., A.M.W., F.B., L.E.C.), Brain Imaging, the Netherlands; Clinical Memory Research Unit (S.E.M., G.S., O.H., R.O., L.E.C.), Department of Clinical Sciences Malmö, Lund University; Division of Clinical Geriatrics (A.S., M. Bucci, A.K.N., E.R.-V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Coma Science Group (A.S.), GIGA-Consciousness, University of Liège; Centre du Cerveau2 (A.S.), University Hospital of Liège, Belgium; Barcelonaβeta Brain Research Center (BBRC) (M.S., G.S., J.D.G.), Pasqual Maragall Foundation; IMIM (Hospital del Mar Medical Research Institute) (M.S., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (M.S., J.D.G.), Instituto de Salud Carlos III, Madrid; Universitat Pompeu Fabra (M.S.), Barcelona, Spain; Brain Research Center (I.L.A.), Amsterdam, the Netherlands; IXICO (R.W.), London; Centre for Clinical Brain Sciences (C.R.), University of Edinburgh, United Kingdom; Ace Alzheimer Center Barcelona (M. Boada), Universitat Internacional de Catalunya, Spain; Networking Research Center on Neurodegenerative Diseases (CIBERNED) (M. Boada), Instituto de Salud Carlos III, Madrid, Spain; Alzheimer Center Amsterdam (P.J.V., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Amsterdam Neuroscience (P.J.V.), Neurodegeneration; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging (M. Bucci, A.K.N.), Karolinska University Hospital, Stockholm, Sweden; GE Healthcare (G.F.), Amersham, United Kingdom; Memory Clinic (O.H.), Skåne University Hospital, Malmö, Sweden; and Centre for Medical Image Computing (F.B.), and Queen Square Institute of Neurology, UCL, London, United Kingdom
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Quenon L, Collij LE, Garcia DV, Lopes Alves I, Gérard T, Malotaux V, Huyghe L, Gispert JD, Jessen F, Visser PJ, den Braber A, Ritchie CW, Boada M, Marquié M, Vandenberghe R, Luckett ES, Schöll M, Frisoni GB, Buckley C, Stephens A, Altomare D, Ford L, Birck C, Mett A, Gismondi R, Wolz R, Grootoonk S, Manber R, Shekari M, Lhommel R, Dricot L, Ivanoiu A, Farrar G, Barkhof F, Hanseeuw BJ. Amyloid-PET imaging predicts functional decline in clinically normal individuals. Alzheimers Res Ther 2024; 16:130. [PMID: 38886831 PMCID: PMC11181677 DOI: 10.1186/s13195-024-01494-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 06/09/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND There is good evidence that elevated amyloid-β (Aβ) positron emission tomography (PET) signal is associated with cognitive decline in clinically normal (CN) individuals. However, it is less well established whether there is an association between the Aβ burden and decline in daily living activities in this population. Moreover, Aβ-PET Centiloids (CL) thresholds that can optimally predict functional decline have not yet been established. METHODS Cross-sectional and longitudinal analyses over a mean three-year timeframe were performed on the European amyloid-PET imaging AMYPAD-PNHS dataset that phenotypes 1260 individuals, including 1032 CN individuals and 228 participants with questionable functional impairment. Amyloid-PET was assessed continuously on the Centiloid (CL) scale and using Aβ groups (CL < 12 = Aβ-, 12 ≤ CL ≤ 50 = Aβ-intermediate/Aβ± , CL > 50 = Aβ+). Functional abilities were longitudinally assessed using the Clinical Dementia Rating (Global-CDR, CDR-SOB) and the Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). The Global-CDR was available for the 1260 participants at baseline, while baseline CDR-SOB and A-IADL-Q scores and longitudinal functional data were available for different subsamples that had similar characteristics to those of the entire sample. RESULTS Participants included 765 Aβ- (61%, Mdnage = 66.0, IQRage = 61.0-71.0; 59% women), 301 Aβ± (24%; Mdnage = 69.0, IQRage = 64.0-75.0; 53% women) and 194 Aβ+ individuals (15%, Mdnage = 73.0, IQRage = 68.0-78.0; 53% women). Cross-sectionally, CL values were associated with CDR outcomes. Longitudinally, baseline CL values predicted prospective changes in the CDR-SOB (bCL*Time = 0.001/CL/year, 95% CI [0.0005,0.0024], p = .003) and A-IADL-Q (bCL*Time = -0.010/CL/year, 95% CI [-0.016,-0.004], p = .002) scores in initially CN participants. Increased clinical progression (Global-CDR > 0) was mainly observed in Aβ+ CN individuals (HRAβ+ vs Aβ- = 2.55, 95% CI [1.16,5.60], p = .020). Optimal thresholds for predicting decline were found at 41 CL using the CDR-SOB (bAβ+ vs Aβ- = 0.137/year, 95% CI [0.069,0.206], p < .001) and 28 CL using the A-IADL-Q (bAβ+ vs Aβ- = -0.693/year, 95% CI [-1.179,-0.208], p = .005). CONCLUSIONS Amyloid-PET quantification supports the identification of CN individuals at risk of functional decline. TRIAL REGISTRATION The AMYPAD PNHS is registered at www.clinicaltrialsregister.eu with the EudraCT Number: 2018-002277-22.
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Affiliation(s)
- Lisa Quenon
- Institute of Neuroscience, UCLouvain, Brussels, Belgium.
- Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium.
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - David Vállez Garcia
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Brain Research Center, Amsterdam, The Netherlands
| | - Thomas Gérard
- Institute of Neuroscience, UCLouvain, Brussels, Belgium
- Department of Nuclear Medicine, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Vincent Malotaux
- Institute of Neuroscience, UCLouvain, Brussels, Belgium
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Lara Huyghe
- Institute of Neuroscience, UCLouvain, Brussels, Belgium
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
| | - Anouk den Braber
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Craig W Ritchie
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Mercè Boada
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center for Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Marta Marquié
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center for Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Louvain, Belgium
- Neurology Service, University Hospital Leuven, Louvain, Belgium
| | - Emma S Luckett
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Louvain, Belgium
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Göteborg, Sweden
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Mölndal, Sweden
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, University Hospital of Geneva, Geneva, Switzerland
| | | | | | - Daniele Altomare
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Lisa Ford
- Johnson & Johnson Innovative Medicine, Titusville, NJ, USA
| | | | - Anja Mett
- GE HealthCare, Glattbrugg, Switzerland
| | | | | | | | | | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Renaud Lhommel
- Institute of Neuroscience, UCLouvain, Brussels, Belgium
- Department of Nuclear Medicine, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | | | - Adrian Ivanoiu
- Institute of Neuroscience, UCLouvain, Brussels, Belgium
- Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Bernard J Hanseeuw
- Institute of Neuroscience, UCLouvain, Brussels, Belgium
- Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
- Gordon Center for Medical Imaging, Department of Radiology, Mass General Brigham, Boston, MA, USA
- WELBIO Department, WEL Research Institute, Wavre, Belgium
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Paprzycka O, Wieczorek J, Nowak I, Madej M, Strzalka-Mrozik B. Potential Application of MicroRNAs and Some Other Molecular Biomarkers in Alzheimer's Disease. Curr Issues Mol Biol 2024; 46:5066-5084. [PMID: 38920976 PMCID: PMC11202417 DOI: 10.3390/cimb46060304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 05/05/2024] [Accepted: 05/21/2024] [Indexed: 06/27/2024] Open
Abstract
Alzheimer's disease (AD) is the world's most common neurodegenerative disease, expected to affect up to one-third of the elderly population in the near future. Among the major challenges in combating AD are the inability to reverse the damage caused by the disease, expensive diagnostic tools, and the lack of specific markers for the early detection of AD. This paper highlights promising research directions for molecular markers in AD diagnosis, including the diagnostic potential of microRNAs. The latest molecular methods for diagnosing AD are discussed, with particular emphasis on diagnostic techniques prior to the appearance of full AD symptoms and markers detectable in human body fluids. A collection of recent studies demonstrates the promising potential of molecular methods in AD diagnosis, using miRNAs as biomarkers. Up- or downregulation in neurodegenerative diseases may not only provide a new diagnostic tool but also serve as a marker for differentiating neurodegenerative diseases. However, further research in this direction is needed.
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Affiliation(s)
- Olga Paprzycka
- Department of Molecular Biology, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, 40-055 Katowice, Poland; (O.P.); (J.W.); (M.M.)
| | - Jan Wieczorek
- Department of Molecular Biology, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, 40-055 Katowice, Poland; (O.P.); (J.W.); (M.M.)
| | - Ilona Nowak
- Silesia LabMed, Centre for Research and Implementation, Medical University of Silesia, 40-752 Katowice, Poland;
| | - Marcel Madej
- Department of Molecular Biology, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, 40-055 Katowice, Poland; (O.P.); (J.W.); (M.M.)
- Silesia LabMed, Centre for Research and Implementation, Medical University of Silesia, 40-752 Katowice, Poland;
| | - Barbara Strzalka-Mrozik
- Department of Molecular Biology, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, 40-055 Katowice, Poland; (O.P.); (J.W.); (M.M.)
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Jagust WJ, Mattay VS, Krainak DM, Wang SJ, Weidner LD, Hofling AA, Koo H, Hsieh P, Kuo PH, Farrar G, Marzella L. Quantitative Brain Amyloid PET. J Nucl Med 2024; 65:670-678. [PMID: 38514082 PMCID: PMC11064834 DOI: 10.2967/jnumed.123.265766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 02/13/2024] [Indexed: 03/23/2024] Open
Abstract
Since the development of amyloid tracers for PET imaging, there has been interest in quantifying amyloid burden in the brains of patients with Alzheimer disease. Quantitative amyloid PET imaging is poised to become a valuable approach in disease staging, theranostics, monitoring, and as an outcome measure for interventional studies. Yet, there are significant challenges and hurdles to overcome before it can be implemented into widespread clinical practice. On November 17, 2022, the U.S. Food and Drug Administration, Society of Nuclear Medicine and Molecular Imaging, and Medical Imaging and Technology Alliance cosponsored a public workshop comprising experts from academia, industry, and government agencies to discuss the role of quantitative brain amyloid PET imaging in staging, prognosis, and longitudinal assessment of Alzheimer disease. The workshop discussed a range of topics, including available radiopharmaceuticals for amyloid imaging; the methodology, metrics, and analytic validity of quantitative amyloid PET imaging; its use in disease staging, prognosis, and monitoring of progression; and challenges facing the field. This report provides a high-level summary of the presentations and the discussion.
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Affiliation(s)
| | - Venkata S Mattay
- Division of Imaging and Radiation Medicine, Office of Specialty Medicine, Office of New Drugs, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland;
| | - Daniel M Krainak
- Division of Radiological Imaging and Radiation Therapy Devices, Office of Radiological Health, Office of Product Evaluation and Quality, Centers for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland
| | - Sue-Jane Wang
- Division of Biometrics I, Office of Biostatistics, Office of Translational Sciences, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland
| | - Lora D Weidner
- Division of Radiological Imaging and Radiation Therapy Devices, Office of Radiological Health, Office of Product Evaluation and Quality, Centers for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland
| | - A Alex Hofling
- Division of Imaging and Radiation Medicine, Office of Specialty Medicine, Office of New Drugs, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland
| | - Hayoung Koo
- Division of Imaging and Radiation Medicine, Office of Specialty Medicine, Office of New Drugs, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland
| | | | | | | | - Libero Marzella
- Division of Imaging and Radiation Medicine, Office of Specialty Medicine, Office of New Drugs, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland
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Bollack A, Collij LE, García DV, Shekari M, Altomare D, Payoux P, Dubois B, Grau‐Rivera O, Boada M, Marquié M, Nordberg A, Walker Z, Scheltens P, Schöll M, Wolz R, Schott JM, Gismondi R, Stephens A, Buckley C, Frisoni GB, Hanseeuw B, Visser PJ, Vandenberghe R, Drzezga A, Yaqub M, Boellaard R, Gispert JD, Markiewicz P, Cash DM, Farrar G, Barkhof F. Investigating reliable amyloid accumulation in Centiloids: Results from the AMYPAD Prognostic and Natural History Study. Alzheimers Dement 2024; 20:3429-3441. [PMID: 38574374 PMCID: PMC11095430 DOI: 10.1002/alz.13761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 04/06/2024]
Abstract
INTRODUCTION To support clinical trial designs focused on early interventions, our study determined reliable early amyloid-β (Aβ) accumulation based on Centiloids (CL) in pre-dementia populations. METHODS A total of 1032 participants from the Amyloid Imaging to Prevent Alzheimer's Disease-Prognostic and Natural History Study (AMYPAD-PNHS) and Insight46 who underwent [18F]flutemetamol, [18F]florbetaben or [18F]florbetapir amyloid-PET were included. A normative strategy was used to define reliable accumulation by estimating the 95th percentile of longitudinal measurements in sub-populations (NPNHS = 101/750, NInsight46 = 35/382) expected to remain stable over time. The baseline CL threshold that optimally predicts future accumulation was investigated using precision-recall analyses. Accumulation rates were examined using linear mixed-effect models. RESULTS Reliable accumulation in the PNHS was estimated to occur at >3.0 CL/year. Baseline CL of 16 [12,19] best predicted future Aβ-accumulators. Rates of amyloid accumulation were tracer-independent, lower for APOE ε4 non-carriers, and for subjects with higher levels of education. DISCUSSION Our results support a 12-20 CL window for inclusion into early secondary prevention studies. Reliable accumulation definition warrants further investigations.
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Affiliation(s)
- Ariane Bollack
- Centre for Medical Image Computing (CMIC)Department of Medical Physics and BioengineeringUniversity College LondonLondonLondonUK
| | - Lyduine E. Collij
- Department of Radiology and Nuclear MedicineAmsterdam UMCAmsterdamThe Netherlands
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
- Amsterdam Neuroscience, Brain ImagingVU University AmsterdamAmsterdamThe Netherlands
| | - David Vállez García
- Department of Radiology and Nuclear MedicineAmsterdam UMCAmsterdamThe Netherlands
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- Instituto de investigaciones médicas Hospital del Mar (IMIM)BarcelonaSpain
| | - Daniele Altomare
- Neurology UnitDepartment of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
| | - Pierre Payoux
- Department of Nuclear MedicineImaging PoleToulouse University HospitalToulouseFrance
- Toulouse NeuroImaging CenterUniversité de ToulouseInsermUPSCHU PurpanPavillon BaudotPlace du Docteur Joseph BaylacToulouseFrance
| | - Bruno Dubois
- Department of NeurologySalpêtrière HospitalAP‐HPSorbonne UniversityParisFrance
| | - Oriol Grau‐Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
| | - Mercè Boada
- Ace Alzheimer Center Barcelona – Universitat Internacional de CatalunyaBarcelonaSpain
- CIBERNEDNetwork Center for Biomedical Research in Neurodegenerative DiseasesNational Institute of Health Carlos IIIMadridSpain
| | - Marta Marquié
- Ace Alzheimer Center Barcelona – Universitat Internacional de CatalunyaBarcelonaSpain
- CIBERNEDNetwork Center for Biomedical Research in Neurodegenerative DiseasesNational Institute of Health Carlos IIIMadridSpain
| | - Agneta Nordberg
- Department of NeurobiologyCare Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
- Theme Inflammation and Aging, Karolinska University Hospital, Karolinska InstitutetStockholmSweden
| | - Zuzana Walker
- Division of PsychiatryUniversity College LondonLondonUK
- Essex Partnership University NHS Foundation Trust, The LodgeWickfordUK
| | - Philip Scheltens
- Alzheimer Center and Department of NeurologyAmsterdam Neuroscience, VU University Medical Center, Alzheimercentrum AmsterdamAmsterdamThe Netherlands
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, The University of GothenburgGothenburgSweden
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sahlgrenska University HospitalGothenburgSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
| | | | - Jonathan M. Schott
- Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | | | | | | | - Giovanni B. Frisoni
- Neurology UnitDepartment of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
| | - Bernard Hanseeuw
- Department of NeurologyInstitute of Neuroscience, Université Catholique de Louvain, Cliniques Universitaires Saint‐LucBrusselsBelgium
- Gordon Center for Medical ImagingDepartment of RadiologyMassachusetts General HospitalBostonMassachusettsUSA
- WELBIO DepartmentWEL Research InstituteWavreBelgium
| | - Pieter Jelle Visser
- Department of Radiology and Nuclear MedicineAmsterdam UMCAmsterdamThe Netherlands
- Department of NeurobiologyCare Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht UniversityMaastrichtThe Netherlands
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, LBI – KU Leuven Brain InstituteLeuvenBelgium
| | - Alexander Drzezga
- Department of Nuclear MedicineUniversity Hospital Cologne, Universitätsklinikums KölnKölnGermany
- Molecular Organization of the Brain, Institute for Neuroscience and Medicine, INM‐2), Forschungszentrum Jülich GmbHJülichGermany
- German Center for Neurodegenerative Diseases (DZNE)BonnGermany
| | - Maqsood Yaqub
- Department of Radiology and Nuclear MedicineAmsterdam UMCAmsterdamThe Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear MedicineAmsterdam UMCAmsterdamThe Netherlands
- Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of GroningenGroningenThe Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos IIIMadridSpain
| | - Pawel Markiewicz
- Centre for Medical Image Computing (CMIC)Department of Medical Physics and BioengineeringUniversity College LondonLondonLondonUK
- Computer Science and Informatics, School of Engineering, London South Bank UniversityLondonUK
| | - David M. Cash
- Queen Square Institute of Neurology, University College LondonLondonUK
- UK Dementia Research Institute at University College LondonLondonUK
| | | | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC)Department of Medical Physics and BioengineeringUniversity College LondonLondonLondonUK
- Department of Radiology and Nuclear MedicineAmsterdam UMCAmsterdamThe Netherlands
- Queen Square Institute of Neurology, University College LondonLondonUK
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Liu Z, Shi D, Cai Y, Li A, Lan G, Sun P, Liu L, Zhu Y, Yang J, Zhou Y, Guo L, Zhang L, Deng S, Chen S, Yu X, Chen X, Zhao R, Wang Q, Ran P, Xu L, Zhou L, Sun K, Wang X, Peng Q, Han Y, Guo T. Pathophysiology characterization of Alzheimer's disease in South China's aging population: for the Greater-Bay-Area Healthy Aging Brain Study (GHABS). Alzheimers Res Ther 2024; 16:84. [PMID: 38627753 PMCID: PMC11020808 DOI: 10.1186/s13195-024-01458-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Accepted: 04/12/2024] [Indexed: 04/19/2024]
Abstract
INTRODUCTION The Guangdong-Hong Kong-Macao Greater-Bay-Area of South China has an 86 million population and faces a significant challenge of Alzheimer's disease (AD). However, the characteristics and prevalence of AD in this area are still unclear due to the rarely available community-based neuroimaging AD cohort. METHODS Following the standard protocols of the Alzheimer's Disease Neuroimaging Initiative, the Greater-Bay-Area Healthy Aging Brain Study (GHABS) was initiated in 2021. GHABS participants completed clinical assessments, plasma biomarkers, genotyping, magnetic resonance imaging (MRI), β-amyloid (Aβ) positron emission tomography (PET) imaging, and tau PET imaging. The GHABS cohort focuses on pathophysiology characterization and early AD detection in the Guangdong-Hong Kong-Macao Greater Bay Area. In this study, we analyzed plasma Aβ42/Aβ40 (A), p-Tau181 (T), neurofilament light, and GFAP by Simoa in 470 Chinese older adults, and 301, 195, and 70 had MRI, Aβ PET, and tau PET, respectively. Plasma biomarkers, Aβ PET, tau PET, hippocampal volume, and temporal-metaROI cortical thickness were compared between normal control (NC), subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia groups, controlling for age, sex, and APOE-ε4. The prevalence of plasma A/T profiles and Aβ PET positivity were also determined in different diagnostic groups. RESULTS The aims, study design, data collection, and potential applications of GHABS are summarized. SCD individuals had significantly higher plasma p-Tau181 and plasma GFAP than the NC individuals. MCI and dementia patients showed more abnormal changes in all the plasma and neuroimaging biomarkers than NC and SCD individuals. The frequencies of plasma A+/T+ (NC; 5.9%, SCD: 8.2%, MCI: 25.3%, dementia: 64.9%) and Aβ PET positivity (NC: 25.6%, SCD: 22.5%, MCI: 47.7%, dementia: 89.3%) were reported. DISCUSSION The GHABS cohort may provide helpful guidance toward designing standard AD community cohorts in South China. This study, for the first time, reported the pathophysiology characterization of plasma biomarkers, Aβ PET, tau PET, hippocampal atrophy, and AD-signature cortical thinning, as well as the prevalence of Aβ PET positivity in the Guangdong-Hong Kong-Macao Greater Bay Area of China. These findings provide novel insights into understanding the characteristics of abnormal AD pathological changes in South China's older population.
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Affiliation(s)
- Zhen Liu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Dai Shi
- Neurology Medicine Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518000, China
| | - Yue Cai
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Anqi Li
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Guoyu Lan
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Pan Sun
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Lin Liu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Yalin Zhu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Jie Yang
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Yajing Zhou
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Lizhi Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Laihong Zhang
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Shuqing Deng
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Shuda Chen
- Neurology Medicine Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518000, China
| | - Xianfeng Yu
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Xuhui Chen
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
- Department of Neurology, Peking University Shenzhen Hospital, Shenzhen, 518000, China
| | - Ruiyue Zhao
- Department of Nuclear Medicine, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510120, China
| | - Qingyong Wang
- Department of Neurology, University of Chinese Academy of Sciences-Shenzhen Hospital, Shenzhen, 518107, China
| | - Pengcheng Ran
- Department of Nuclear Medicine, Guangdong Hospital of Traditional Chinese Medicine, Guangzhou, 510120, China
| | - Linsen Xu
- Department of Medical Imaging, University of Chinese Academy of Sciences-Shenzhen Hospital, Shenzhen, 518106, China
| | - Liemin Zhou
- Neurology Medicine Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518000, China
| | - Kun Sun
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China
| | - Xinlu Wang
- Department of Nuclear Medicine, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510120, China
| | - Qiyu Peng
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Ying Han
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China
- National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China.
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, 518055, China.
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Vilor‐Tejedor N, Genius P, Rodríguez‐Fernández B, Minguillón C, Sadeghi I, González‐Escalante A, Crous‐Bou M, Suárez‐Calvet M, Grau‐Rivera O, Brugulat‐Serrat A, Sánchez‐Benavides G, Esteller M, Fauria K, Molinuevo JL, Navarro A, Gispert JD. Genetic characterization of the ALFA study: Uncovering genetic profiles in the Alzheimer's continuum. Alzheimers Dement 2024; 20:1703-1715. [PMID: 38088508 PMCID: PMC10984507 DOI: 10.1002/alz.13537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 09/12/2023] [Accepted: 10/11/2023] [Indexed: 03/16/2024]
Abstract
INTRODUCTION In 2013, the ALzheimer's and FAmilies (ALFA) project was established to investigate pathophysiological changes in preclinical Alzheimer's disease (AD), and to foster research on early detection and preventive interventions. METHODS We conducted a comprehensive genetic characterization of ALFA participants with respect to neurodegenerative/cerebrovascular diseases, AD biomarkers, brain endophenotypes, risk factors and aging biomarkers. We placed particular emphasis on amyloid/tau status and assessed gender differences. Multiple polygenic risk scores were computed to capture different aspects of genetic predisposition. We additionally compared AD risk in ALFA to that across the full disease spectrum from the Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS Results show that the ALFA project has been successful at establishing a cohort of cognitively unimpaired individuals at high genetic predisposition of AD. DISCUSSION It is, therefore, well-suited to study early pathophysiological changes in the preclinical AD continuum. Highlights Prevalence of ε4 carriers in ALzheimer and FAmilies (ALFA) is higher than in the general European population The ALFA study is highly enriched in Alzheimer's disease (AD) genetic risk factors beyond APOE AD genetic profiles in ALFA are similar to clinical groups along the continuum ALFA has succeeded in establishing a cohort of cognitively unimpaired individuals at high genetic AD risk ALFA is well suited to study pathogenic events/early pathophysiological changes in AD.
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Affiliation(s)
- Natalia Vilor‐Tejedor
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Centre for Genomic Regulation (CRG)The Barcelona Institute for Science and TechnologyBarcelonaSpain
- Department of Clinical GeneticsErasmus University Medical CenterRotterdamNetherlands
- Neurosciences Programme, IMIM ‐ Hospital del Mar Medical Research InstituteBarcelonaSpain
| | - Patricia Genius
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Centre for Genomic Regulation (CRG)The Barcelona Institute for Science and TechnologyBarcelonaSpain
- Neurosciences Programme, IMIM ‐ Hospital del Mar Medical Research InstituteBarcelonaSpain
| | - Blanca Rodríguez‐Fernández
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Centre for Genomic Regulation (CRG)The Barcelona Institute for Science and TechnologyBarcelonaSpain
- Neurosciences Programme, IMIM ‐ Hospital del Mar Medical Research InstituteBarcelonaSpain
| | - Carolina Minguillón
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Neurosciences Programme, IMIM ‐ Hospital del Mar Medical Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBER‐FES)Instituto de Salud Carlos IIIMadridSpain
| | - Iman Sadeghi
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Centre for Genomic Regulation (CRG)The Barcelona Institute for Science and TechnologyBarcelonaSpain
| | - Armand González‐Escalante
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Neurosciences Programme, IMIM ‐ Hospital del Mar Medical Research InstituteBarcelonaSpain
- Department of Medicine and Life SciencesUniversitat Pompeu FabraBarcelonaSpain
| | - Marta Crous‐Bou
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Department of EpidemiologyHarvard T.H. Chan School of Public Health. School of Public Health 2BostonMassachusettsUSA
- Catalan Institute of Oncology (ICO)‐Bellvitge Biomedical Research Center (IDIBELL)Hospital Duran i ReynalsBarcelonaSpain
| | - Marc Suárez‐Calvet
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Neurosciences Programme, IMIM ‐ Hospital del Mar Medical Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBER‐FES)Instituto de Salud Carlos IIIMadridSpain
- Servei de NeurologiaHospital del MarBarcelonaSpain
| | - Oriol Grau‐Rivera
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Neurosciences Programme, IMIM ‐ Hospital del Mar Medical Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBER‐FES)Instituto de Salud Carlos IIIMadridSpain
- Servei de NeurologiaHospital del MarBarcelonaSpain
| | - Anna Brugulat‐Serrat
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Neurosciences Programme, IMIM ‐ Hospital del Mar Medical Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBER‐FES)Instituto de Salud Carlos IIIMadridSpain
- Global Brain Health InstituteSan FranciscoCaliforniaUSA
| | - Gonzalo Sánchez‐Benavides
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Neurosciences Programme, IMIM ‐ Hospital del Mar Medical Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBER‐FES)Instituto de Salud Carlos IIIMadridSpain
| | - Manel Esteller
- Cancer Epigenetics, Josep Carreras Leukaemia Research Institute (IJC)BarcelonaSpain
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos IIIMadridSpain
- Integrated Pharmacology and Systems NeurosciencesIMIM‐Hospital del Mar Medical Research InstituteBarcelonaSpain
- Institució Catalana de Recerca i Estudis Avançats (ICREA)BarcelonaSpain
- Physiological Sciences DepartmentSchool of Medicine and Health SciencesUniversity of Barcelona (UB)BarcelonaSpain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBER‐FES)Instituto de Salud Carlos IIIMadridSpain
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Experimental Medicine, H. Lundbeck A/SKøbenhavnDenmark
| | - Arcadi Navarro
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Centre for Genomic Regulation (CRG)The Barcelona Institute for Science and TechnologyBarcelonaSpain
- Department of Medicine and Life SciencesUniversitat Pompeu FabraBarcelonaSpain
- Institució Catalana de Recerca i Estudis Avançats (ICREA)BarcelonaSpain
- Department of Experimental and Health SciencesInstitute of Evolutionary Biology (CSIC‐UPF)BarcelonaSpain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Neurosciences Programme, IMIM ‐ Hospital del Mar Medical Research InstituteBarcelonaSpain
- Department of Medicine and Life SciencesUniversitat Pompeu FabraBarcelonaSpain
- Centro de Investigación Biomédica en Red BioingenieríaBiomateriales y Nanomedicina. Instituto de Salud carlos IIIMadridSpain
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)MadridSpain
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13
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Young P, Heeman F, Axelsson J, Collij LE, Hitzel A, Sanaat A, Niñerola-Baizan A, Perissinotti A, Lubberink M, Frisoni GB, Zaidi H, Barkhof F, Farrar G, Baker S, Gispert JD, Garibotto V, Rieckmann A, Schöll M. Impact of simulated reduced injected dose on the assessment of amyloid PET scans. Eur J Nucl Med Mol Imaging 2024; 51:734-748. [PMID: 37897616 PMCID: PMC10796642 DOI: 10.1007/s00259-023-06481-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 10/15/2023] [Indexed: 10/30/2023]
Abstract
PURPOSE To investigate the impact of reduced injected doses on the quantitative and qualitative assessment of the amyloid PET tracers [18F]flutemetamol and [18F]florbetaben. METHODS Cognitively impaired and unimpaired individuals (N = 250, 36% Aβ-positive) were included and injected with [18F]flutemetamol (N = 175) or [18F]florbetaben (N = 75). PET scans were acquired in list-mode (90-110 min post-injection) and reduced-dose images were simulated to generate images of 75, 50, 25, 12.5 and 5% of the original injected dose. Images were reconstructed using vendor-provided reconstruction tools and visually assessed for Aβ-pathology. SUVRs were calculated for a global cortical and three smaller regions using a cerebellar cortex reference tissue, and Centiloid was computed. Absolute and percentage differences in SUVR and CL were calculated between dose levels, and the ability to discriminate between Aβ- and Aβ + scans was evaluated using ROC analyses. Finally, intra-reader agreement between the reduced dose and 100% images was evaluated. RESULTS At 5% injected dose, change in SUVR was 3.72% and 3.12%, with absolute change in Centiloid 3.35CL and 4.62CL, for [18F]flutemetamol and [18F]florbetaben, respectively. At 12.5% injected dose, percentage change in SUVR and absolute change in Centiloid were < 1.5%. AUCs for discriminating Aβ- from Aβ + scans were high (AUC ≥ 0.94) across dose levels, and visual assessment showed intra-reader agreement of > 80% for both tracers. CONCLUSION This proof-of-concept study showed that for both [18F]flutemetamol and [18F]florbetaben, adequate quantitative and qualitative assessments can be obtained at 12.5% of the original injected dose. However, decisions to reduce the injected dose should be made considering the specific clinical or research circumstances.
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Affiliation(s)
- Peter Young
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden
| | - Fiona Heeman
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Jan Axelsson
- Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå, Sweden
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Anne Hitzel
- Department of Nuclear Medicine, Toulouse University Hospital, Toulouse, France
| | - Amirhossein Sanaat
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
| | - Aida Niñerola-Baizan
- Nuclear Medicine Department, Hospital Clínic Barcelona, Barcelona, Spain
- Biomedical Research Networking Centre of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), ISCIII, Barcelona, Spain
| | - Andrés Perissinotti
- Nuclear Medicine Department, Hospital Clínic Barcelona, Barcelona, Spain
- Biomedical Research Networking Centre of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), ISCIII, Barcelona, Spain
| | - Mark Lubberink
- Nuclear Medicine and PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
| | - Habib Zaidi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
- Geneva University Neurocenter, Geneva University, Geneva, Switzerland
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- UCL Institute of Neurology, London, UK
| | | | - Suzanne Baker
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, United States
| | - Juan Domingo Gispert
- Barcelona βeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva; NIMTLab; Center for Biomedical Imaging (CIBM), University of Geneva, Geneva, Switzerland
| | - Anna Rieckmann
- Institute for Psychology, Universität Der Bundeswehr München, Neubiberg, Germany
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.
- Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden.
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK.
- Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg, Sweden.
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14
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Bader I, Bader I, Lopes Alves I, Vállez García D, Vellas B, Dubois B, Boada M, Marquié M, Altomare D, Scheltens P, Vandenberghe R, Hanseeuw B, Schöll M, Frisoni GB, Jessen F, Nordberg A, Kivipelto M, Ritchie CW, Grau-Rivera O, Molinuevo JL, Ford L, Stephens A, Gismondi R, Gispert JD, Farrar G, Barkhof F, Visser PJ, Collij LE. Recruitment of pre-dementia participants: main enrollment barriers in a longitudinal amyloid-PET study. Alzheimers Res Ther 2023; 15:189. [PMID: 37919783 PMCID: PMC10621165 DOI: 10.1186/s13195-023-01332-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 10/13/2023] [Indexed: 11/04/2023]
Abstract
BACKGROUND The mismatch between the limited availability versus the high demand of participants who are in the pre-dementia phase of Alzheimer's disease (AD) is a bottleneck for clinical studies in AD. Nevertheless, potential enrollment barriers in the pre-dementia population are relatively under-reported. In a large European longitudinal biomarker study (the AMYPAD-PNHS), we investigated main enrollment barriers in individuals with no or mild symptoms recruited from research and clinical parent cohorts (PCs) of ongoing observational studies. METHODS Logistic regression was used to predict study refusal based on sex, age, education, global cognition (MMSE), family history of dementia, and number of prior study visits. Study refusal rates and categorized enrollment barriers were compared between PCs using chi-squared tests. RESULTS 535/1856 (28.8%) of the participants recruited from ongoing studies declined participation in the AMYPAD-PNHS. Only for participants recruited from clinical PCs (n = 243), a higher MMSE-score (β = - 0.22, OR = 0.80, p < .05), more prior study visits (β = - 0.93, OR = 0.40, p < .001), and positive family history of dementia (β = 2.08, OR = 8.02, p < .01) resulted in lower odds on study refusal. General study burden was the main enrollment barrier (36.1%), followed by amyloid-PET related burden (PCresearch = 27.4%, PCclinical = 9.0%, X2 = 10.56, p = .001), and loss of research interest (PCclinical = 46.3%, PCresearch = 16.5%, X2 = 32.34, p < .001). CONCLUSIONS The enrollment rate for the AMYPAD-PNHS was relatively high, suggesting an advantage of recruitment via ongoing studies. In this observational cohort, study burden reduction and tailored strategies may potentially improve participant enrollment into trial readiness cohorts such as for phase-3 early anti-amyloid intervention trials. The AMYPAD-PNHS (EudraCT: 2018-002277-22) was approved by the ethical review board of the VU Medical Center (VUmc) as the Sponsor site and in every affiliated site.
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Affiliation(s)
- Ilse Bader
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV, Amsterdam, The Netherlands.
| | - Ilona Bader
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, 1081 HZ, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, 1081 HV, The Netherlands
| | - Isadora Lopes Alves
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, 1081 HZ, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, 1081 HV, The Netherlands
- Brain Research Center, 1081 GN, Amsterdam, The Netherlands
| | - David Vállez García
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, 1081 HZ, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, 1081 HV, The Netherlands
| | - Bruno Vellas
- Gérontopole of Toulouse, University Hospital of Toulouse (CHU-Toulouse), 31300, Toulouse, France
- UMR INSERM 1027, University of Toulouse III, 31062, Toulouse, France
| | - Bruno Dubois
- Institute of Memory and Alzheimer's Disease (IM2A) and Brain Institute, Salpetriere Hospital, Sorbonne University, 75013, Paris, France
| | - Mercè Boada
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Networking Research Center On Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - Marta Marquié
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Networking Research Center On Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - Daniele Altomare
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, 25123, Brescia, Italy
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV, Amsterdam, The Netherlands
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Leuven Brain Institute, KU Leuven, 3001, Louvain, Belgium
| | - Bernard Hanseeuw
- Institute of Neuroscience, Université Catholique de Louvain, 1200, Brussels, Belgium
- Department of Neurology, Clinique Universitaires Saint-Luc, 1200, Brussels, Belgium
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, 02155, USA
- WELBIO Department, WEL Research Institute, Avenue Pasteur, 6, 1300, Wavre, Belgium
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 405 30, Gothenburg, Sweden
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 405 30, Gothenburg, Sweden
- Dementia Research Centre, Queen Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, 1205, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, 1205, Geneva, Switzerland
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), 53127, Bonn, Germany
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences, and Society (NVS), Karolinska Institutet, 171 77, Stockholm, Sweden
- Theme Inflammation, Karolinska University Hospital, Stockholm, 171 77, Sweden
- Theme Aging, Karolinska University Hospital, Stockholm, 171 77, Sweden
| | - Miia Kivipelto
- Kuopio University Hospital, 70210, Kuopio, Finland
- Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences, and Society (NVS), Karolinska Institutet, 171 77, Stockholm, Sweden
- Imperial College London, London, SW7 2AZ, UK
| | | | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, 08005, Barcelona, Spain
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, 08005, Barcelona, Spain
- H. Lundbeck A/S, 2500, Copenhagen, Denmark
| | - Lisa Ford
- Janssen Research and Development, Titusville, NJ, 08560, USA
| | | | | | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, 08005, Barcelona, Spain
| | - Gill Farrar
- GE Healthcare, Pharmaceutical Diagnostics, Amersham, HP7 9LL, UK
| | - Frederik Barkhof
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, 1081 HZ, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, 1081 HV, The Netherlands
- Institutes of Neurology and Healthcare Engineering, UCL, London, WC1N 3BG, UK
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV, Amsterdam, The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, 6229 ER, The Netherlands
| | - Lyduine E Collij
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, 1081 HZ, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, 1081 HV, The Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, 221 00, Malmö, Sweden
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15
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Shekari M, Verwer EE, Yaqub M, Daamen M, Buckley C, Frisoni GB, Visser PJ, Farrar G, Barkhof F, Gispert JD, Boellaard R. Harmonization of brain PET images in multi-center PET studies using Hoffman phantom scan. EJNMMI Phys 2023; 10:68. [PMID: 37906338 PMCID: PMC10618151 DOI: 10.1186/s40658-023-00588-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 10/12/2023] [Indexed: 11/02/2023] Open
Abstract
BACKGROUND Image harmonization has been proposed to minimize heterogeneity in brain PET scans acquired in multi-center studies. However, standard validated methods and software tools are lacking. Here, we assessed the performance of a framework for the harmonization of brain PET scans in a multi-center European clinical trial. METHOD Hoffman 3D brain phantoms were acquired in 28 PET systems and reconstructed using site-specific settings. Full Width at Half Maximum (FWHM) of the Effective Image Resolution (EIR) and harmonization kernels were estimated for each scan. The target EIR was selected as the coarsest EIR in the imaging network. Using "Hoffman 3D brain Analysis tool," indicators of image quality were calculated before and after the harmonization: The Coefficient of Variance (COV%), Gray Matter Recovery Coefficient (GMRC), Contrast, Cold-Spot RC, and left-to-right GMRC ratio. A COV% ≤ 15% and Contrast ≥ 2.2 were set as acceptance criteria. The procedure was repeated to achieve a 6-mm target EIR in a subset of scans. The method's robustness against typical dose-calibrator-based errors was assessed. RESULTS The EIR across systems ranged from 3.3 to 8.1 mm, and an EIR of 8 mm was selected as the target resolution. After harmonization, all scans met acceptable image quality criteria, while only 13 (39.4%) did before. The harmonization procedure resulted in lower inter-system variability indicators: Mean ± SD COV% (from 16.97 ± 6.03 to 7.86 ± 1.47%), GMRC Inter-Quartile Range (0.040-0.012), and Contrast SD (0.14-0.05). Similar results were obtained with a 6-mm FWHM target EIR. Errors of ± 10% in the DRO activity resulted in differences below 1 mm in the estimated EIR. CONCLUSION Harmonizing the EIR of brain PET scans significantly reduced image quality variability while minimally affecting quantitative accuracy. This method can be used prospectively for harmonizing scans to target sharper resolutions and is robust against dose-calibrator errors. Comparable image quality is attainable in brain PET multi-center studies while maintaining quantitative accuracy.
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Affiliation(s)
- Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Eline E Verwer
- Department of Radiology and Nuclear Medicine, Amsterdam, University Medical Centers, Location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam, University Medical Centers, Location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Marcel Daamen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | | | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Center, Department of Rehabilitation and Geriatrics, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam, University Medical Centers, Location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
- Queen Square Institute of Neurology, University College London, London, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
- Universitat Pompeu Fabra, Barcelona, Spain.
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain.
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam, University Medical Centers, Location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
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16
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Bollack A, Markiewicz PJ, Wink AM, Prosser L, Lilja J, Bourgeat P, Schott JM, Coath W, Collij LE, Pemberton HG, Farrar G, Barkhof F, Cash DM. Evaluation of novel data-driven metrics of amyloid β deposition for longitudinal PET studies. Neuroimage 2023; 280:120313. [PMID: 37595816 DOI: 10.1016/j.neuroimage.2023.120313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 05/29/2023] [Accepted: 08/04/2023] [Indexed: 08/20/2023] Open
Abstract
PURPOSE Positron emission tomography (PET) provides in vivo quantification of amyloid-β (Aβ) pathology. Established methods for assessing Aβ burden can be affected by physiological and technical factors. Novel, data-driven metrics have been developed to account for these sources of variability. We aimed to evaluate the performance of four of these amyloid PET metrics against conventional techniques, using a common set of criteria. METHODS Three cohorts were used for evaluation: Insight 46 (N=464, [18F]florbetapir), AIBL (N=277, [18F]flutemetamol), and an independent test-retest data (N=10, [18F]flutemetamol). Established metrics of amyloid tracer uptake included the Centiloid (CL) and where dynamic data was available, the non-displaceable binding potential (BPND). The four data-driven metrics computed were the amyloid load (Aβ load), the Aβ-PET pathology accumulation index (Aβ index), the Centiloid derived from non-negative matrix factorisation (CLNMF), and the amyloid pattern similarity score (AMPSS). These metrics were evaluated using reliability and repeatability in test-retest data, associations with BPND and CL, variability of the rate of change and sample size estimates to detect a 25% slowing in Aβ accumulation. RESULTS All metrics showed good reliability. Aβ load, Aβ index and CLNMF were strong associated with the BPND. The associations with CL suggest that cross-sectional measures of CLNMF, Aβ index and Aβ load are robust across studies. Sample size estimates for secondary prevention trial scenarios were the lowest for CLNMF and Aβ load compared to the CL. CONCLUSION Among the novel data-driven metrics evaluated, the Aβ load, the Aβ index and the CLNMF can provide comparable performance to more established quantification methods of Aβ PET tracer uptake. The CLNMF and Aβ load could offer a more precise alternative to CL, although further studies in larger cohorts should be conducted.
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Affiliation(s)
- Ariane Bollack
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK.
| | - Pawel J Markiewicz
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Alle Meije Wink
- Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands
| | - Lloyd Prosser
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | | | | | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Lyduine E Collij
- Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands; Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Hugh G Pemberton
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK; GE HealthCare, Amersham, UK; Queen Square Institute of Neurology, University College London, UK
| | | | - Frederik Barkhof
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK; Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands; Queen Square Institute of Neurology, University College London, UK
| | - David M Cash
- Queen Square Institute of Neurology, University College London, UK; UK Dementia Research Institute at University College London, London, UK
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17
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Padrela BE, Lorenzini L, Collij LE, García DV, Coomans E, Ingala S, Tomassen J, Deckers Q, Shekari M, de Geus EJC, van de Giessen E, Kate MT, Visser PJ, Barkhof F, Petr J, den Braber A, Mutsaerts HJMM. Genetic, vascular and amyloid components of cerebral blood flow in a preclinical population. J Cereb Blood Flow Metab 2023; 43:1726-1736. [PMID: 37231665 PMCID: PMC10581242 DOI: 10.1177/0271678x231178993] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 04/05/2023] [Accepted: 04/09/2023] [Indexed: 05/27/2023]
Abstract
Aging-related cognitive decline can be accelerated by a combination of genetic factors, cardiovascular and cerebrovascular dysfunction, and amyloid-β burden. Whereas cerebral blood flow (CBF) has been studied as a potential early biomarker of cognitive decline, its normal variability in healthy elderly is less known. In this study, we investigated the contribution of genetic, vascular, and amyloid-β components of CBF in a cognitively unimpaired (CU) population of monozygotic older twins. We included 134 participants who underwent arterial spin labeling (ASL) MRI and [18F]flutemetamol amyloid-PET imaging at baseline and after a four-year follow-up. Generalized estimating equations were used to investigate the associations of amyloid burden and white matter hyperintensities with CBF. We showed that, in CU individuals, CBF: 1) has a genetic component, as within-pair similarities in CBF values were moderate and significant (ICC > 0.40); 2) is negatively associated with cerebrovascular damage; and 3) is positively associated with the interaction between cardiovascular risk scores and early amyloid-β burden, which may reflect a vascular compensatory response of CBF to early amyloid-β accumulation. These findings encourage future studies to account for multiple interactions with CBF in disease trajectory analyses.
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Affiliation(s)
- Beatriz E Padrela
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Luigi Lorenzini
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - David Vállez García
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Emma Coomans
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Quinten Deckers
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Mahnaz Shekari
- BBRC: Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Eco JC de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Mara ten Kate
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Jan Petr
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Henk JMM Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
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18
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Jovalekic A, Roé-Vellvé N, Koglin N, Quintana ML, Nelson A, Diemling M, Lilja J, Gómez-González JP, Doré V, Bourgeat P, Whittington A, Gunn R, Stephens AW, Bullich S. Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods. Eur J Nucl Med Mol Imaging 2023; 50:3276-3289. [PMID: 37300571 PMCID: PMC10542295 DOI: 10.1007/s00259-023-06279-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023]
Abstract
PURPOSE Amyloid positron emission tomography (PET) with [18F]florbetaben (FBB) is an established tool for detecting Aβ deposition in the brain in vivo based on visual assessment of PET scans. Quantitative measures are commonly used in the research context and allow continuous measurement of amyloid burden. The aim of this study was to demonstrate the robustness of FBB PET quantification. METHODS This is a retrospective analysis of FBB PET images from 589 subjects. PET scans were quantified with 15 analytical methods using nine software packages (MIMneuro, Hermes BRASS, Neurocloud, Neurology Toolkit, statistical parametric mapping (SPM8), PMOD Neuro, CapAIBL, non-negative matrix factorization (NMF), AmyloidIQ) that used several metrics to estimate Aβ load (SUVR, centiloid, amyloid load, and amyloid index). Six analytical methods reported centiloid (MIMneuro, standard centiloid, Neurology Toolkit, SPM8 (PET only), CapAIBL, NMF). All results were quality controlled. RESULTS The mean sensitivity, specificity, and accuracy were 96.1 ± 1.6%, 96.9 ± 1.0%, and 96.4 ± 1.1%, respectively, for all quantitative methods tested when compared to histopathology, where available. The mean percentage of agreement between binary quantitative assessment across all 15 methods and visual majority assessment was 92.4 ± 1.5%. Assessments of reliability, correlation analyses, and comparisons across software packages showed excellent performance and consistent results between analytical methods. CONCLUSION This study demonstrated that quantitative methods using both CE marked software and other widely available processing tools provided comparable results to visual assessments of FBB PET scans. Software quantification methods, such as centiloid analysis, can complement visual assessment of FBB PET images and could be used in the future for identification of early amyloid deposition, monitoring disease progression and treatment effectiveness.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Vincent Doré
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, Australia
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19
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Bradshaw A, Hughes N, Vallez-Garcia D, Chokoshvili D, Owens A, Hansen C, Emmert K, Maetzler W, Killin L, Barnes R, Brookes AJ, Visser PJ, Hofmann-Apitius M, Diaz C, Steukers L. Data sharing in neurodegenerative disease research: challenges and learnings from the innovative medicines initiative public-private partnership model. Front Neurol 2023; 14:1187095. [PMID: 37545729 PMCID: PMC10397390 DOI: 10.3389/fneur.2023.1187095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 06/02/2023] [Indexed: 08/08/2023] Open
Abstract
Efficient data sharing is hampered by an array of organizational, ethical, behavioral, and technical challenges, slowing research progress and reducing the utility of data generated by clinical research studies on neurodegenerative diseases. There is a particular need to address differences between public and private sector environments for research and data sharing, which have varying standards, expectations, motivations, and interests. The Neuronet data sharing Working Group was set up to understand the existing barriers to data sharing in public-private partnership projects, and to provide guidance to overcome these barriers, by convening data sharing experts from diverse projects in the IMI neurodegeneration portfolio. In this policy and practice review, we outline the challenges and learnings of the WG, providing the neurodegeneration community with examples of good practices and recommendations on how to overcome obstacles to data sharing. These obstacles span organizational issues linked to the unique structure of cross-sectoral, collaborative research initiatives, to technical issues that affect the storage, structure and annotations of individual datasets. We also identify sociotechnical hurdles, such as academic recognition and reward systems that disincentivise data sharing, and legal challenges linked to heightened perceptions of data privacy risk, compounded by a lack of clear guidance on GDPR compliance mechanisms for public-private research. Focusing on real-world, neuroimaging and digital biomarker data, we highlight particular challenges and learnings for data sharing, such as data management planning, development of ethical codes of conduct, and harmonization of protocols and curation processes. Cross-cutting solutions and enablers include the principles of transparency, standardization and co-design - from open, accessible metadata catalogs that enhance findability of data, to measures that increase visibility and trust in data reuse.
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Affiliation(s)
| | | | - David Vallez-Garcia
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | | | - Andrew Owens
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Clint Hansen
- Department of Neurology, University Hospital Schleswig-Holstein, Campus Kiel and Kiel University, Kiel, Germany
| | - Kirsten Emmert
- Department of Neurology, University Hospital Schleswig-Holstein, Campus Kiel and Kiel University, Kiel, Germany
| | - Walter Maetzler
- Department of Neurology, University Hospital Schleswig-Holstein, Campus Kiel and Kiel University, Kiel, Germany
| | - Lewis Killin
- Synapse Research Management Partners, Barcelona, Spain
| | | | - Anthony J. Brookes
- Department of Genetics and Genome Biology, University of Leicester, Leicester, United Kingdom
| | - Pieter Jelle Visser
- Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, University of Maastricht, Maastricht, Netherlands
| | | | - Carlos Diaz
- Synapse Research Management Partners, Barcelona, Spain
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20
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Brugulat-Serrat A, Sánchez-Benavides G, Cacciaglia R, Salvadó G, Shekari M, Collij LE, Buckley C, van Berckel BNM, Perissinotti A, Niñerola-Baizán A, Milà-Alomà M, Vilor-Tejedor N, Operto G, Falcon C, Grau-Rivera O, Arenaza-Urquijo EM, Minguillón C, Fauria K, Molinuevo JL, Suárez-Calvet M, Gispert JD. APOE-ε4 modulates the association between regional amyloid deposition and cognitive performance in cognitively unimpaired middle-aged individuals. EJNMMI Res 2023; 13:18. [PMID: 36856866 PMCID: PMC9978048 DOI: 10.1186/s13550-023-00967-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 02/10/2023] [Indexed: 03/02/2023] Open
Abstract
PURPOSE To determine whether the APOE-ε4 allele modulates the relationship between regional β-amyloid (Aβ) accumulation and cognitive change in middle-aged cognitively unimpaired (CU) participants. METHODS The 352 CU participants (mean aged 61.1 [4.7] years) included completed two cognitive assessments (average interval 3.34 years), underwent [18F]flutemetamol Aβ positron emission tomography (PET), T1w magnetic resonance imaging (MRI), as well as APOE genotyping. Global and regional Aβ PET positivity was assessed across five regions-of-interest by visual reading (VR) and regional Centiloids. Linear regression models were developed to examine the interaction between regional and global Aβ PET positivity and APOE-ε4 status on longitudinal cognitive change assessed with the Preclinical Alzheimer's Cognitive Composite (PACC), episodic memory, and executive function, after controlling for age, sex, education, cognitive baseline scores, and hippocampal volume. RESULTS In total, 57 participants (16.2%) were VR+ of whom 41 (71.9%) were APOE-ε4 carriers. No significant APOE-ε4*global Aβ PET interactions were associated with cognitive change for any cognitive test. However, APOE-ε4 carriers who were VR+ in temporal areas (n = 19 [9.81%], p = 0.04) and in the striatum (n = 8 [4.14%], p = 0.01) exhibited a higher decline in the PACC. The temporal areas findings were replicated when regional PET positivity was determined with Centiloid values. Regionally, VR+ in the striatum was associated with higher memory decline. As for executive function, interactions between APOE-ε4 and regional VR+ were found in temporal and parietal regions, and in the striatum. CONCLUSION CU APOE-ε4 carriers with a positive Aβ PET VR in regions known to accumulate amyloid at later stages of the Alzheimer's disease (AD) continuum exhibited a steeper cognitive decline. This work supports the contention that regional VR of Aβ PET might convey prognostic information about future cognitive decline in individuals at higher risk of developing AD. CLINICALTRIALS gov Identifier: NCT02485730. Registered 20 June 2015 https://clinicaltrials.gov/ct2/show/NCT02485730 and ClinicalTrials.gov Identifier:NCT02685969. Registered 19 February 2016 https://clinicaltrials.gov/ct2/show/NCT02685969 .
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Affiliation(s)
- Anna Brugulat-Serrat
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain ,grid.512357.7Global Brain Health Institute, San Francisco, CA USA
| | - Gonzalo Sánchez-Benavides
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Raffaele Cacciaglia
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Gemma Salvadó
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.4514.40000 0001 0930 2361Department of Clinical Sciences, Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Mahnaz Shekari
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.5612.00000 0001 2172 2676Universitat Pompeu Fabra, Barcelona, Spain
| | - Lyduine E. Collij
- grid.12380.380000 0004 1754 9227Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, Amsterdam, The Netherlands
| | - Christopher Buckley
- grid.83440.3b0000000121901201Center for Medical Image Computing, and Queen Square Institute of Neurology, UCL, London, UK
| | - Bart N. M. van Berckel
- grid.12380.380000 0004 1754 9227Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, Amsterdam, The Netherlands
| | - Andrés Perissinotti
- grid.410458.c0000 0000 9635 9413Nuclear Medicine Department, Hospital Clínic, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Aida Niñerola-Baizán
- grid.410458.c0000 0000 9635 9413Nuclear Medicine Department, Hospital Clínic, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Marta Milà-Alomà
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain ,grid.5612.00000 0001 2172 2676Universitat Pompeu Fabra, Barcelona, Spain
| | - Natàlia Vilor-Tejedor
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.5612.00000 0001 2172 2676Universitat Pompeu Fabra, Barcelona, Spain ,grid.473715.30000 0004 6475 7299Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain
| | - Grégory Operto
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Carles Falcon
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.411142.30000 0004 1767 8811Neurologia Department, Hospital del Mar, Barcelona, Spain
| | - Oriol Grau-Rivera
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain ,grid.411142.30000 0004 1767 8811Neurologia Department, Hospital del Mar, Barcelona, Spain
| | - Eider M. Arenaza-Urquijo
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Carolina Minguillón
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Karine Fauria
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - José Luis Molinuevo
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.424580.f0000 0004 0476 7612H. Lundbeck A/S, Copenhagen, Denmark
| | - Marc Suárez-Calvet
- grid.430077.7Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain ,grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain ,grid.411142.30000 0004 1767 8811Neurologia Department, Hospital del Mar, Barcelona, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain. .,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain. .,Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain.
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21
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Impact of Nut Consumption on Cognition across the Lifespan. Nutrients 2023; 15:nu15041000. [PMID: 36839359 PMCID: PMC9965316 DOI: 10.3390/nu15041000] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 02/13/2023] [Accepted: 02/14/2023] [Indexed: 02/19/2023] Open
Abstract
Cognitive health is a life-long concern affected by modifiable risk factors, including lifestyle choices, such as dietary intake, with serious implications for quality of life, morbidity, and mortality worldwide. In addition, nuts are a nutrient-dense food that contain a number of potentially neuroprotective components, including monounsaturated and polyunsaturated fatty acids, fiber, B-vitamins, non-sodium minerals, and highly bioactive polyphenols. However, increased nut consumption relates to a lower cardiovascular risk and a lower burden of cardiovascular risk factors that are shared with neurodegenerative disorders, which is why nuts have been hypothesized to be beneficial for brain health. The present narrative review discusses up-to-date epidemiological, clinical trial, and mechanistic evidence of the effect of exposure to nuts on cognitive performance. While limited and inconclusive, available evidence suggests a possible role for nuts in the maintenance of cognitive health and prevention of cognitive decline in individuals across the lifespan, particularly in older adults and those at higher risk. Walnuts, as a rich source of the plant-based polyunsaturated omega-3 fatty acid alpha-linolenic acid, are the nut type most promising for cognitive health. Given the limited definitive evidence available to date, especially regarding cognitive health biomarkers and hard outcomes, future studies are needed to better elucidate the impact of nuts on the maintenance of cognitive health, as well as the prevention and management of cognitive decline and dementia, including Alzheimer disease.
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Collij LE, Farrar G, Valléz García D, Bader I, Shekari M, Lorenzini L, Pemberton H, Altomare D, Pla S, Loor M, Markiewicz P, Yaqub M, Buckley C, Frisoni GB, Nordberg A, Payoux P, Stephens A, Gismondi R, Visser PJ, Ford L, Schmidt M, Birck C, Georges J, Mett A, Walker Z, Boada M, Drzezga A, Vandenberghe R, Hanseeuw B, Jessen F, Schöll M, Ritchie C, Lopes Alves I, Gispert JD, Barkhof F. The amyloid imaging for the prevention of Alzheimer's disease consortium: A European collaboration with global impact. Front Neurol 2023; 13:1063598. [PMID: 36761917 PMCID: PMC9907029 DOI: 10.3389/fneur.2022.1063598] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 12/08/2022] [Indexed: 01/22/2023] Open
Abstract
Background Amyloid-β (Aβ) accumulation is considered the earliest pathological change in Alzheimer's disease (AD). The Amyloid Imaging to Prevent Alzheimer's Disease (AMYPAD) consortium is a collaborative European framework across European Federation of Pharmaceutical Industries Associations (EFPIA), academic, and 'Small and Medium-sized enterprises' (SME) partners aiming to provide evidence on the clinical utility and cost-effectiveness of Positron Emission Tomography (PET) imaging in diagnostic work-up of AD and to support clinical trial design by developing optimal quantitative methodology in an early AD population. The AMYPAD studies In the Diagnostic and Patient Management Study (DPMS), 844 participants from eight centres across three clinical subgroups (245 subjective cognitive decline, 342 mild cognitive impairment, and 258 dementia) were included. The Prognostic and Natural History Study (PNHS) recruited pre-dementia subjects across 11 European parent cohorts (PCs). Approximately 1600 unique subjects with historical and prospective data were collected within this study. PET acquisition with [18F]flutemetamol or [18F]florbetaben radiotracers was performed and quantified using the Centiloid (CL) method. Results AMYPAD has significantly contributed to the AD field by furthering our understanding of amyloid deposition in the brain and the optimal methodology to measure this process. Main contributions so far include the validation of the dual-time window acquisition protocol to derive the fully quantitative non-displaceable binding potential (BP ND ), assess the value of this metric in the context of clinical trials, improve PET-sensitivity to emerging Aβ burden and utilize its available regional information, establish the quantitative accuracy of the Centiloid method across tracers and support implementation of quantitative amyloid-PET measures in the clinical routine. Future steps The AMYPAD consortium has succeeded in recruiting and following a large number of prospective subjects and setting up a collaborative framework to integrate data across European PCs. Efforts are currently ongoing in collaboration with ARIDHIA and ADDI to harmonize, integrate, and curate all available clinical data from the PNHS PCs, which will become openly accessible to the wider scientific community.
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Affiliation(s)
- Lyduine E. Collij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, location VUmc, Amsterdam, Netherlands,Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands,*Correspondence: Lyduine E. Collij ✉
| | | | - David Valléz García
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, location VUmc, Amsterdam, Netherlands,Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Ilona Bader
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, location VUmc, Amsterdam, Netherlands,Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | | | - Luigi Lorenzini
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, location VUmc, Amsterdam, Netherlands,Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Hugh Pemberton
- Centre for Medical Image Computing, and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), Université de Genève, Geneva, Switzerland
| | - Sandra Pla
- Synapse Research Management Partners, Barcelona, Spain
| | - Mery Loor
- Synapse Research Management Partners, Barcelona, Spain
| | - Pawel Markiewicz
- Centre for Medical Image Computing, and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, location VUmc, Amsterdam, Netherlands
| | | | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), Université de Genève, Geneva, Switzerland
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center of Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
| | - Pierre Payoux
- Department of Nuclear Medicine, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Andrew Stephens
- Life Molecular Imaging GmbH, Berlin, Baden-Württemberg, Germany
| | | | - Pieter Jelle Visser
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, location VUmc, Amsterdam, Netherlands
| | - Lisa Ford
- Janssen Pharmaceutica NV, Beerse, Belgium
| | | | | | | | - Anja Mett
- GE Healthcare, Amersham, United Kingdom
| | - Zuzana Walker
- Centre for Medical Image Computing, and Queen Square Institute of Neurology, UCL, London, United Kingdom
| | - Mercé Boada
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Alexander Drzezga
- Department of Psychiatry, University Hospital of Cologne, Cologne, North Rhine-Westphalia, Germany
| | - Rik Vandenberghe
- Faculty of Medicine, University Hospitals Leuven, Leuven, Brussels, Belgium
| | - Bernard Hanseeuw
- Institute of Neuroscience (IONS), Université Catholique de Louvain, Brussels, Belgium
| | - Frank Jessen
- Department of Psychiatry, University Hospital of Cologne, Cologne, North Rhine-Westphalia, Germany
| | - Michael Schöll
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Craig Ritchie
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | | | - Juan Domingo Gispert
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, location VUmc, Amsterdam, Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, location VUmc, Amsterdam, Netherlands,Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands,Centre for Medical Image Computing, and Queen Square Institute of Neurology, UCL, London, United Kingdom
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23
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Saunders S, Gregory S, Clement MHS, Birck C, van der Geyten S, Ritchie CW. The European Prevention of Alzheimer's Dementia Programme: An Innovative Medicines Initiative-funded partnership to facilitate secondary prevention of Alzheimer's disease dementia. Front Neurol 2022; 13:1051543. [PMID: 36484017 PMCID: PMC9723139 DOI: 10.3389/fneur.2022.1051543] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 10/28/2022] [Indexed: 08/08/2023] Open
Abstract
INTRODUCTION Tens of millions of people worldwide will develop Alzheimer's disease (AD), and only by intervening early in the preclinical disease can we make a fundamental difference to the rates of late-stage disease where clinical symptoms and societal burden manifest. However, collectively utilizing data, samples, and knowledge amassed by large-scale projects such as the Innovative Medicines Initiative (IMI)-funded European Prevention of Alzheimer's Dementia (EPAD) program will enable the research community to learn, adapt, and implement change. METHOD In the current article, we define and discuss the substantial assets of the EPAD project for the scientific community, patient population, and industry, describe the EPAD structure with a focus on how the public and private sector interacted and collaborated within the project, reflect how IMI specifically supported the achievements of the above, and conclude with a view for future. RESULTS The EPAD project was a €64-million investment to facilitate secondary prevention of AD dementia research. The project recruited over 2,000 research participants into the EPAD longitudinal cohort study (LCS) and included over 400 researchers from 39 partners. The EPAD LCS data and biobank are freely available and easily accessible via the Alzheimer's Disease Data Initiative's (ADDI) AD Workbench platform and the University of Edinburgh's Sample Access Committee. The trial delivery network established within the EPAD program is being incorporated into the truly global offering from the Global Alzheimer's Platform (GAP) for trial delivery, and the almost 100 early-career researchers who were part of the EPAD Academy will take forward their experience and learning from EPAD to the next stage of their careers. DISCUSSION Through GAP, IMI-Neuronet, and follow-on funding from the Alzheimer's Association for the data and sample access systems, the EPAD assets will be maintained and, as and when sponsors seek a new platform trial to be established, the learnings from EPAD will ensure that this can be developed to be even more successful than this first pan-European attempt.
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Affiliation(s)
- Stina Saunders
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Sarah Gregory
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | | | | | - Serge van der Geyten
- Janssen Research and Development, Division of Janssen Pharmaceutica NV, Beerse, Belgium
| | - Craig W. Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Brain Health Scotland, Edinburgh, United Kingdom
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24
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Pemberton HG, Collij LE, Heeman F, Bollack A, Shekari M, Salvadó G, Alves IL, Garcia DV, Battle M, Buckley C, Stephens AW, Bullich S, Garibotto V, Barkhof F, Gispert JD, Farrar G. Quantification of amyloid PET for future clinical use: a state-of-the-art review. Eur J Nucl Med Mol Imaging 2022; 49:3508-3528. [PMID: 35389071 PMCID: PMC9308604 DOI: 10.1007/s00259-022-05784-y] [Citation(s) in RCA: 85] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 03/25/2022] [Indexed: 12/15/2022]
Abstract
Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.
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Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Amersham, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Brain Research Center, Amsterdam, The Netherlands
| | - David Vallez Garcia
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mark Battle
- GE Healthcare, Amersham, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | | | | | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva, Geneva, Switzerland
- NIMTLab, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
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25
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Imabayashi E, Tamamura N, Yamaguchi Y, Kamitaka Y, Sakata M, Ishii K. Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer's disease. Ann Nucl Med 2022; 36:865-875. [PMID: 35821311 PMCID: PMC9515054 DOI: 10.1007/s12149-022-01769-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 06/19/2022] [Indexed: 11/11/2022]
Abstract
Objective Although beta-amyloid (Aβ) positron emission tomography (PET) images are interpreted visually as positive or negative, approximately 10% are judged as equivocal in Alzheimer’s disease. Therefore, we aimed to develop an automated semi-quantitative analysis technique using 18F-flutemetamol PET images without anatomical images. Methods Overall, 136 cases of patients administered 18F-flutemetamol were enrolled. Of 136 cases, five PET images each with the highest and lowest values of standardized uptake value ratio (SUVr) of cerebral cortex-to-pons were used to create positive and negative templates. Using these templates, PET images of the remaining 126 cases were standardized, and SUVr images were produced with the pons as a reference region. The mean of SUVr values in the volume of interest delineated on the cerebral cortex was compared to those in the CortexID Suite (GE Healthcare). Furthermore, centiloid (CL) values were calculated for the 126 cases using data from the Centiloid Project (http://www.gaain.org/centiloid-project) and both templates. 18F-flutemetamol-PET was interpreted visually as positive/negative based on Aβ deposition in the cortex. However, the criterion "equivocal" was added for cases with focal or mild Aβ accumulation that were difficult to categorize. Optimal cutoff values of SUVr and CL maximizing sensitivity and specificity for Aβ detection were determined by receiver operating characteristic (ROC) analysis using the visual evaluation as a standard of truth. Results SUVr calculated by our method and CortexID were highly correlated (R2 = 0.9657). The 126 PET images comprised 84 negative and 42 positive cases of Aβ deposition by visual evaluation, of which 11 and 10 were classified as equivocal, respectively. ROC analyses determined the optimal cutoff values, sensitivity, and specificity for SUVr as 0.544, 89.3%, and 92.9%, respectively, and for CL as 12.400, 94.0%, and 92.9%, respectively. Both semi-quantitative analyses showed that 12 and 9 of the 21 equivocal cases were negative and positive, respectively, under the optimal cutoff values. Conclusions This semi-quantitative analysis technique using 18F-flutemetamol-PET calculated SUVr and CL automatically without anatomical images. Moreover, it objectively and homogeneously interpreted positive or negative Aβ burden in the brain as a supplemental tool for the visual reading of equivocal cases in routine clinical practice. Supplementary Information The online version contains supplementary material available at 10.1007/s12149-022-01769-x.
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Affiliation(s)
- Etsuko Imabayashi
- Research Team for Neuroimaging, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, 35-2 Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan.,Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), 4-9-1 Anagawa, Inage, Chiba, 263-8555, Japan
| | - Naoyuki Tamamura
- Nihon Medi-Physics Co., Ltd., 3-4-10 Shinsuna, Koto-ku, Tokyo, 136-0075, Japan
| | - Yuzuho Yamaguchi
- Nihon Medi-Physics Co., Ltd., 3-4-10 Shinsuna, Koto-ku, Tokyo, 136-0075, Japan
| | - Yuto Kamitaka
- Research Team for Neuroimaging, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, 35-2 Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan
| | - Muneyuki Sakata
- Research Team for Neuroimaging, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, 35-2 Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan
| | - Kenji Ishii
- Research Team for Neuroimaging, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, 35-2 Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan.
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26
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Lorenzini L, Ansems LT, Lopes Alves I, Ingala S, Vállez García D, Tomassen J, Sudre C, Salvadó G, Shekari M, Operto G, Brugulat-Serrat A, Sánchez-Benavides G, ten Kate M, Tijms B, Wink AM, Mutsaerts HJMM, den Braber A, Visser PJ, van Berckel BNM, Gispert JD, Barkhof F, Collij LE. Regional associations of white matter hyperintensities and early cortical amyloid pathology. Brain Commun 2022; 4:fcac150. [PMID: 35783557 PMCID: PMC9246276 DOI: 10.1093/braincomms/fcac150] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 04/11/2022] [Accepted: 06/09/2022] [Indexed: 11/13/2022] Open
Abstract
White matter hyperintensities (WMHs) have a heterogeneous aetiology, associated with both vascular risk factors and amyloidosis due to Alzheimer's disease. While spatial distribution of both amyloid and WM lesions carry important information for the underlying pathogenic mechanisms, the regional relationship between these two pathologies and their joint contribution to early cognitive deterioration remains largely unexplored. We included 662 non-demented participants from three Amyloid Imaging to Prevent Alzheimer's disease (AMYPAD)-affiliated cohorts: EPAD-LCS (N = 176), ALFA+ (N = 310), and EMIF-AD PreclinAD Twin60++ (N = 176). Using PET imaging, cortical amyloid burden was assessed regionally within early accumulating regions (medial orbitofrontal, precuneus, and cuneus) and globally, using the Centiloid method. Regional WMH volume was computed using Bayesian Model Selection. Global associations between WMH, amyloid, and cardiovascular risk scores (Framingham and CAIDE) were assessed using linear models. Partial least square (PLS) regression was used to identify regional associations. Models were adjusted for age, sex, and APOE-e4 status. Individual PLS scores were then related to cognitive performance in 4 domains (attention, memory, executive functioning, and language). While no significant global association was found, the PLS model yielded two components of interest. In the first PLS component, a fronto-parietal WMH pattern was associated with medial orbitofrontal-precuneal amyloid, vascular risk, and age. Component 2 showed a posterior WMH pattern associated with precuneus-cuneus amyloid, less related to age or vascular risk. Component 1 was associated with lower performance in all cognitive domains, while component 2 only with worse memory. In a large pre-dementia population, we observed two distinct patterns of regional associations between WMH and amyloid burden, and demonstrated their joint influence on cognitive processes. These two components could reflect the existence of vascular-dependent and -independent manifestations of WMH-amyloid regional association that might be related to distinct primary pathophysiology.
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Affiliation(s)
- Luigi Lorenzini
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Loes T Ansems
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Isadora Lopes Alves
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Silvia Ingala
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - David Vállez García
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jori Tomassen
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Carole Sudre
- Centre for Medical Image Computing (CMIC), Departments of Medical Physics & Biomedical Engineering and Computer Science, University College London, UK
- MRC Unit for Lifelong Health and Ageing - University CollegeLondon, UK
- School of Biomedical Engineering, King’s College LondonUK
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Gregory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Anna Brugulat-Serrat
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Madrid, Spain
- Atlantic Fellow for Equity in Brain Health at the University of California San Francisco, SanFrancisco, California, USA
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Mara ten Kate
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Betty Tijms
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Alle Meije Wink
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Henk J M M Mutsaerts
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Anouk den Braber
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department. of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Bart N M van Berckel
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales Y Nanomedicina, Madrid, Spain
| | - Frederik Barkhof
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Lyduine E Collij
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
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27
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Heeman F, Yaqub M, Hendriks J, van Berckel BNM, Collij LE, Gray KR, Manber R, Wolz R, Garibotto V, Wimberley C, Ritchie C, Barkhof F, Gispert JD, Vállez García D, Lopes Alves I, Lammertsma AA. Impact of cerebral blood flow and amyloid load on SUVR bias. EJNMMI Res 2022; 12:29. [PMID: 35553267 PMCID: PMC9098761 DOI: 10.1186/s13550-022-00898-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 04/25/2022] [Indexed: 11/17/2022] Open
Abstract
Background Despite its widespread use, the semi-quantitative standardized uptake value ratio (SUVR) may be biased compared with the distribution volume ratio (DVR). This bias may be partially explained by changes in cerebral blood flow (CBF) and is likely to be also dependent on the extent of the underlying amyloid-β (Aβ) burden. This study aimed to compare SUVR with DVR and to evaluate the effects of underlying Aβ burden and CBF on bias in SUVR in mainly cognitively unimpaired participants. Participants were scanned according to a dual-time window protocol, with either [18F]flutemetamol (N = 90) or [18F]florbetaben (N = 31). The validated basisfunction-based implementation of the two-step simplified reference tissue model was used to derive DVR and R1 parametric images, and SUVR was calculated from 90 to 110 min post-injection, all with the cerebellar grey matter as reference tissue. First, linear regression and Bland–Altman analyses were used to compare (regional) SUVR with DVR. Then, generalized linear models were applied to evaluate whether (bias in) SUVR relative to DVR could be explained by R1 for the global cortical average (GCA), precuneus, posterior cingulate, and orbitofrontal region. Results Despite high correlations (GCA: R2 ≥ 0.85), large overestimation and proportional bias of SUVR relative to DVR was observed. Negative associations were observed between both SUVR or SUVRbias and R1, albeit non-significant. Conclusion The present findings demonstrate that bias in SUVR relative to DVR is strongly related to underlying Aβ burden. Furthermore, in a cohort consisting mainly of cognitively unimpaired individuals, the effect of relative CBF on bias in SUVR appears limited. EudraCT Number: 2018-002277-22, registered on: 25-06-2018. Supplementary Information The online version contains supplementary material available at 10.1186/s13550-022-00898-8.
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Affiliation(s)
- Fiona Heeman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
| | - Maqsood Yaqub
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Janine Hendriks
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Lyduine E Collij
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | | | | | | | - Valentina Garibotto
- NIMTLab, Faculty of Medicine, Geneva University, Geneva, Switzerland.,Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
| | - Catriona Wimberley
- Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Craig Ritchie
- Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Frederik Barkhof
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.,UCL, Institutes of Neurology and Healthcare Engineering, London, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Centre, Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain.,Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - David Vállez García
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Isadora Lopes Alves
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
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Reward System Dysfunction and the Motoric-Cognitive Risk Syndrome in Older Persons. Biomedicines 2022; 10:biomedicines10040808. [PMID: 35453558 PMCID: PMC9029623 DOI: 10.3390/biomedicines10040808] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 03/27/2022] [Accepted: 03/28/2022] [Indexed: 02/04/2023] Open
Abstract
During aging, many physiological systems spontaneously change independent of the presence of chronic diseases. The reward system is not an exception and its dysfunction generally includes a reduction in dopamine and glutamate activities and the loss of neurons of the ventral tegmental area (VTA). These impairments are even more pronounced in older persons who have neurodegenerative diseases and/or are affected by cognitive and motoric frailty. All these changes may result in the occurrence of cognitive and motoric frailty and accelerated progression of neurodegenerative diseases, such as Alzheimer’s and Parkinson’s diseases. In particular, the loss of neurons in VTA may determine an acceleration of depressive symptoms and cognitive and motor frailty trajectory, producing an increased risk of disability and mortality. Thus, we hypothesize the existence of a loop between reward system dysfunction, depression, and neurodegenerative diseases in older persons. Longitudinal studies are needed to evaluate the determinant role of the reward system in the onset of motoric-cognitive risk syndrome.
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de Souza GS, Andrade MA, Borelli WV, Schilling LP, Matushita CS, Portuguez MW, da Costa JC, Marques da Silva AM. Amyloid-β PET Classification on Cognitive Aging Stages Using the Centiloid Scale. Mol Imaging Biol 2021; 24:394-403. [PMID: 34611766 DOI: 10.1007/s11307-021-01660-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 09/22/2021] [Accepted: 09/27/2021] [Indexed: 11/25/2022]
Abstract
PROPOSE This study aims to explore the use of the Centiloid (CL) method in amyloid-β PET quantification to evaluate distinct cognitive aging stages, investigating subjects' mismatch classification using different cut-points for amyloid-β positivity. PROCEDURES The CL equation was applied in four groups of individuals: SuperAgers (SA), healthy age-matched controls (AC), healthy middle-aged controls (MC), and Alzheimer's disease (AD). The amyloid-β burden was calculated and compared between groups and quantitative variables. Three different cut-points (Jack CR, Wiste HJ, Weigand SD, et al., Alzheimer's Dement 13:205-216, 2017; Salvadó G, Molinuevo JL, Brugulat-Serrat A, et al., Alzheimer's Res Ther 11:27, 2019; and Amadoru S, Doré V, McLean CA, et al., Alzheimer's Res Ther 12:22, 2020) were applied in CL values to differentiate the earliest abnormal pathophysiological accumulation of Aβ and the established Aβ pathology. RESULTS The AD group exhibited a significantly increased Aβ burden compared to the MC, but not AC groups. Both healthy control (MC and AC) groups were not significantly different. Visually, the SA group showed a diverse distribution of CL values compared with MC; however, the difference was not significant. The CL values have a moderate and significant relationship between Aβ visual read, RAVLT DR and MMSE. Depending on the cut-point used, 10 CL, 19 CL, or 30 CL, 7.5% of our individuals had a different classification in the Aβ positivity. For the AC group, we obtained about 40 to 60% of the individuals classified as positive. CONCLUSION SuperAgers exhibited a similar Aβ load to AC and MC, differing in cognitive performance. Independently of cut-point used (10 CL, 19 CL, or 30 CL), three SA individuals were classified as Aβ positive, showing the duality between the individual's clinics and the biological definition of Alzheimer's. Different cut-points lead to Aβ positivity classification mismatch in individuals, and an extra care is needed for individuals who have a CL value between 10 and 30 CL.
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Affiliation(s)
- Giordana Salvi de Souza
- School of Medicine, PUCRS, Porto Alegre, Brazil.
- Medical Image Computing Laboratory, School of Technology, PUCRS, Porto Alegre, Brazil.
| | - Michele Alberton Andrade
- School of Medicine, PUCRS, Porto Alegre, Brazil
- Medical Image Computing Laboratory, School of Technology, PUCRS, Porto Alegre, Brazil
- Brain Institute of Rio Grande Do Sul (BraIns), PUCRS, Porto Alegre, Brazil
| | | | | | | | - Mirna Wetters Portuguez
- School of Medicine, PUCRS, Porto Alegre, Brazil
- Brain Institute of Rio Grande Do Sul (BraIns), PUCRS, Porto Alegre, Brazil
| | - Jaderson Costa da Costa
- School of Medicine, PUCRS, Porto Alegre, Brazil
- Brain Institute of Rio Grande Do Sul (BraIns), PUCRS, Porto Alegre, Brazil
| | - Ana Maria Marques da Silva
- School of Medicine, PUCRS, Porto Alegre, Brazil
- Medical Image Computing Laboratory, School of Technology, PUCRS, Porto Alegre, Brazil
- Brain Institute of Rio Grande Do Sul (BraIns), PUCRS, Porto Alegre, Brazil
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30
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Collij LE, Mastenbroek SE, Salvadó G, Wink AM, Visser PJ, Barkhof F, van Berckel BN, Lopes Alves I. Regional amyloid accumulation predicts memory decline in initially cognitively unimpaired individuals. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12216. [PMID: 34368416 PMCID: PMC8327468 DOI: 10.1002/dad2.12216] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 05/04/2021] [Accepted: 06/04/2021] [Indexed: 01/02/2023]
Abstract
INTRODUCTION The value of quantitative longitudinal and regional amyloid beta (Aβ) measurements in predicting cognitive decline in initially cognitively unimpaired (CU) individuals remains to be determined. METHODS We selected 133 CU individuals with two or more [11C]Pittsburgh compound B ([11C]PiB) scans and neuropsychological data from Open Access Series of Imaging Studies (OASIS-3). Baseline and annualized distribution volume ratios were computed for a global composite and four regional clusters. The predictive value of Aβ measurements (baseline, slope, and interaction) on longitudinal cognitive performance was examined. RESULTS Global performance could only be predicted by Aβ burden in an early cluster (precuneus, lateral orbitofrontal, and insula) and the precuneus region of interest (ROI) by itself significantly improved the model. Precuneal Aβ burden was also predictive of immediate and delayed episodic memory performance. In Aβ subjects at baseline (N = 93), lateral orbitofrontal Aβ burden predicted working and semantic memory performance. DISCUSSION Quantifying longitudinal and regional changes in Aβ can improve the prediction of cognitive functioning in initially CU individuals.
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Affiliation(s)
- Lyduine E. Collij
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Sophie E. Mastenbroek
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
| | - Alle Meije Wink
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Pieter Jelle Visser
- Amsterdam UMCAlzheimer Center and department of NeurologyVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Frederik Barkhof
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
- Medical Physics and Biomedical EngineeringCentre for Medical Image ComputingUCLLondonUK
| | - Bart. N.M. van Berckel
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Isadora Lopes Alves
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
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31
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Lopes Alves I, Heeman F, Collij LE, Salvadó G, Tolboom N, Vilor-Tejedor N, Markiewicz P, Yaqub M, Cash D, Mormino EC, Insel PS, Boellaard R, van Berckel BNM, Lammertsma AA, Barkhof F, Gispert JD. Strategies to reduce sample sizes in Alzheimer's disease primary and secondary prevention trials using longitudinal amyloid PET imaging. Alzheimers Res Ther 2021; 13:82. [PMID: 33875021 PMCID: PMC8056524 DOI: 10.1186/s13195-021-00819-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 03/26/2021] [Indexed: 01/07/2023]
Abstract
BACKGROUND Detecting subtle-to-moderate biomarker changes such as those in amyloid PET imaging becomes increasingly relevant in the context of primary and secondary prevention of Alzheimer's disease (AD). This work aimed to determine if and when distribution volume ratio (DVR; derived from dynamic imaging) and regional quantitative values could improve statistical power in AD prevention trials. METHODS Baseline and annualized % change in [11C]PIB SUVR and DVR were computed for a global (cortical) and regional (early) composite from scans of 237 cognitively unimpaired subjects from the OASIS-3 database ( www.oasis-brains.org ). Bland-Altman and correlation analyses were used to assess the relationship between SUVR and DVR. General linear models and linear mixed effects models were used to determine effects of age, sex, and APOE-ε4 carriership on baseline and longitudinal amyloid burden. Finally, differences in statistical power of SUVR and DVR (cortical or early composite) were assessed considering three anti-amyloid trial scenarios: secondary prevention trials including subjects with (1) intermediate-to-high (Centiloid > 20.1), or (2) intermediate (20.1 < Centiloid ≤ 49.4) amyloid burden, and (3) a primary prevention trial focusing on subjects with low amyloid burden (Centiloid ≤ 20.1). Trial scenarios were set to detect 20% reduction in accumulation rates across the whole population and in APOE-ε4 carriers only. RESULTS Although highly correlated to DVR (ρ = .96), cortical SUVR overestimated DVR cross-sectionally and in annual % change. In secondary prevention trials, DVR required 143 subjects per arm, compared with 176 for SUVR. Both restricting inclusion to individuals with intermediate amyloid burden levels or to APOE-ε4 carriers alone further reduced sample sizes. For primary prevention, SUVR required less subjects per arm (n = 855) compared with DVR (n = 1508) and the early composite also provided considerable sample size reductions (n = 855 to n = 509 for SUVR, n = 1508 to n = 734 for DVR). CONCLUSION Sample sizes in AD secondary prevention trials can be reduced by the acquisition of dynamic PET scans and/or by restricting inclusion to subjects with intermediate amyloid burden or to APOE-ε4 carriers only. Using a targeted early composite only leads to reductions of sample size requirements in primary prevention trials. These findings support strategies to enable smaller Proof-of-Concept Phase II clinical trials to better streamline drug development.
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Affiliation(s)
- Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Nelleke Tolboom
- Imaging Division, Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Natàlia Vilor-Tejedor
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain
- Department of Clinical Genetics, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Pawel Markiewicz
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - David Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Philip S Insel
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain.
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
- Universitat Pompeu Fabra, Barcelona, Spain.
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain.
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Bullich S, Roé-Vellvé N, Marquié M, Landau SM, Barthel H, Villemagne VL, Sanabria Á, Tartari JP, Sotolongo-Grau O, Doré V, Koglin N, Müller A, Perrotin A, Jovalekic A, De Santi S, Tárraga L, Stephens AW, Rowe CC, Sabri O, Seibyl JP, Boada M. Early detection of amyloid load using 18F-florbetaben PET. ALZHEIMERS RESEARCH & THERAPY 2021; 13:67. [PMID: 33773598 PMCID: PMC8005243 DOI: 10.1186/s13195-021-00807-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 03/10/2021] [Indexed: 03/26/2023]
Abstract
BACKGROUND A low amount and extent of Aβ deposition at early stages of Alzheimer's disease (AD) may limit the use of previously developed pathology-proven composite SUVR cutoffs. This study aims to characterize the population with earliest abnormal Aβ accumulation using 18F-florbetaben PET. Quantitative thresholds for the early (SUVRearly) and established (SUVRestab) Aβ deposition were developed, and the topography of early Aβ deposition was assessed. Subsequently, Aβ accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aβ deposition. METHODS The study population consisted of 686 subjects (n = 287 (cognitively normal healthy controls), n = 166 (subjects with subjective cognitive decline (SCD)), n = 129 (subjects with MCI), and n = 101 (subjects with AD dementia)). Three categories in the Aβ-deposition continuum were defined based on the developed SUVR cutoffs: Aβ-negative subjects, subjects with early Aβ deposition ("gray zone"), and subjects with established Aβ pathology. RESULTS SUVR using the whole cerebellum as the reference region and centiloid (CL) cutoffs for early and established amyloid pathology were 1.10 (13.5 CL) and 1.24 (35.7 CL), respectively. Cingulate cortices and precuneus, frontal, and inferior lateral temporal cortices were the regions showing the initial pathological tracer retention. Subjects in the "gray zone" or with established Aβ pathology accumulated more amyloid over time than Aβ-negative subjects. After a 4-year clinical follow-up, none of the Aβ-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aβ pathology progressed. Tau deposition was infrequent in those subjects without established Aβ pathology. CONCLUSIONS This study supports the utility of using two cutoffs for amyloid PET abnormality defining a "gray zone": a lower cutoff of 13.5 CL indicating emerging Aβ pathology and a higher cutoff of 35.7 CL where amyloid burden levels correspond to established neuropathology findings. These cutoffs define a subset of subjects characterized by pre-AD dementia levels of amyloid burden that precede other biomarkers such as tau deposition or clinical symptoms and accelerated amyloid accumulation. The determination of different amyloid loads, particularly low amyloid levels, is useful in determining who will eventually progress to dementia. Quantitation of amyloid provides a sensitive measure in these low-load cases and may help to identify a group of subjects most likely to benefit from intervention. TRIAL REGISTRATION Data used in this manuscript belong to clinical trials registered in ClinicalTrials.gov ( NCT00928304 , NCT00750282 , NCT01138111 , NCT02854033 ) and EudraCT (2014-000798-38).
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Affiliation(s)
- Santiago Bullich
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany.
| | - Núria Roé-Vellvé
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Marta Marquié
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley and Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Victor L Villemagne
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Ángela Sanabria
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Juan Pablo Tartari
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Oscar Sotolongo-Grau
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Vincent Doré
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia.,The Australian e-Health Research Centre, Health and Biosecurity, CSIRO, Melbourne, Victoria, Australia
| | - Norman Koglin
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Andre Müller
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Audrey Perrotin
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | | | | | - Lluís Tárraga
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Andrew W Stephens
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Christopher C Rowe
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | | | - Mercè Boada
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
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Heeman F, Yaqub M, Hendriks J, Bader I, Barkhof F, Gispert JD, van Berckel BNM, Lopes Alves I, Lammertsma AA. Parametric imaging of dual-time window [ 18F]flutemetamol and [ 18F]florbetaben studies. Neuroimage 2021; 234:117953. [PMID: 33762215 DOI: 10.1016/j.neuroimage.2021.117953] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 01/12/2021] [Accepted: 03/05/2021] [Indexed: 11/15/2022] Open
Abstract
Optimal pharmacokinetic models for quantifying amyloid beta (Aβ) burden using both [18F]flutemetamol and [18F]florbetaben scans have previously been identified at a region of interest (ROI) level. The purpose of this study was to determine optimal quantitative methods for parametric analyses of [18F]flutemetamol and [18F]florbetaben scans. Forty-six participants were scanned on a PET/MR scanner using a dual-time window protocol and either [18F]flutemetamol (N=24) or [18F]florbetaben (N=22). The following parametric approaches were used to derive DVR estimates: reference Logan (RLogan), receptor parametric mapping (RPM), two-step simplified reference tissue model (SRTM2) and multilinear reference tissue models (MRTM0, MRTM1, MRTM2), all with cerebellar grey matter as reference tissue. In addition, a standardized uptake value ratio (SUVR) was calculated for the 90-110 min post injection interval. All parametric images were assessed visually. Regional outcome measures were compared with those from a validated ROI method, i.e. DVR derived using RLogan. Visually, RPM, and SRTM2 performed best across tracers and, in addition to SUVR, provided highest AUC values for differentiating between Aβ-positive vs Aβ-negative scans ([18F]flutemetamol: range AUC=0.96-0.97 [18F]florbetaben: range AUC=0.83-0.85). Outcome parameters of most methods were highly correlated with the reference method (R2≥0.87), while lowest correlation were observed for MRTM2 (R2=0.71-0.80). Furthermore, bias was low (≤5%) and independent of underlying amyloid burden for MRTM0 and MRTM1. The optimal parametric method differed per evaluated aspect; however, the best compromise across aspects was found for MRTM0 followed by SRTM2, for both tracers. SRTM2 is the preferred method for parametric imaging because, in addition to its good performance, it has the advantage of providing a measure of relative perfusion (R1), which is useful for measuring disease progression.
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Affiliation(s)
- Fiona Heeman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands.
| | - Maqsood Yaqub
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Janine Hendriks
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Ilona Bader
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; UCL, Institutes of Neurology and Healthcare Engineering, London, United Kingdom
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Centre, Pasqual Maragall Foundation, Barcelona, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Bart N M van Berckel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Isadora Lopes Alves
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Adriaan A Lammertsma
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
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Peng S, Tang C, Schindlbeck K, Rydzinski Y, Dhawan V, Spetsieris PG, Ma Y, Eidelberg D. Dynamic 18F-FPCIT PET: Quantification of Parkinson's disease metabolic networks and nigrostriatal dopaminergic dysfunction in a single imaging session. J Nucl Med 2021; 62:jnumed.120.257345. [PMID: 33741649 PMCID: PMC8612203 DOI: 10.2967/jnumed.120.257345] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 03/09/2021] [Accepted: 03/09/2021] [Indexed: 11/16/2022] Open
Abstract
Previous multi-center imaging studies with 18F-FDG PET have established the presence of Parkinson's disease motor- and cognition-related metabolic patterns termed PDRP and PDCP in patients with this disorder. Given that in PD cerebral perfusion and glucose metabolism are typically coupled in the absence of medication, we determined whether subject expression of these disease networks can be quantified in early-phase images from dynamic 18F-FPCIT PET scans acquired to assess striatal dopamine transporter (DAT) binding. Methods: We studied a cohort of early-stage PD patients and age-matched healthy control subjects who underwent 18F-FPCIT at baseline; scans were repeated 4 years later in a smaller subset of patients. The early 18F-FPCIT frames, which reflect cerebral perfusion, were used to compute PDRP and PDCP expression (subject scores) in each subject, and compared to analogous measures computed based on 18F-FDG PET scan when additionally available. The late 18F-FPCIT frames were used to measure caudate and putamen DAT binding in the same individuals. Results: PDRP subject scores from early-phase 18F-FPCIT and 18F-FDG scans were elevated and striatal DAT binding reduced in PD versus healthy subjects. The PDRP scores from 18F-FPCIT correlated with clinical motor ratings, disease duration, and with corresponding measures from 18F-FDG PET. In addition to correlating with disease duration and analogous 18F-FDG PET values, PDCP scores correlated with DAT binding in the caudate/anterior putamen. PDRP and PDCP subject scores using either method rose over 4 years whereas striatal DAT binding declined over the same time period. Conclusion: Early-phase images obtained with 18F-FPCIT PET can provide an alternative to 18F-FDG PET for PD network quantification. This technique therefore allows PDRP/PDCP expression and caudate/putamen DAT binding to be evaluated with a single tracer in one scanning session.
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Affiliation(s)
- Shichun Peng
- Center for Neurosciences, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York; and
| | - Chris Tang
- Center for Neurosciences, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York; and
| | - Katharina Schindlbeck
- Center for Neurosciences, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York; and
| | - Yaacov Rydzinski
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Vijay Dhawan
- Center for Neurosciences, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York; and
| | - Phoebe G. Spetsieris
- Center for Neurosciences, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York; and
| | - Yilong Ma
- Center for Neurosciences, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York; and
| | - David Eidelberg
- Center for Neurosciences, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York; and
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Collij LE, Salvadó G, Shekari M, Lopes Alves I, Reimand J, Wink AM, Zwan M, Niñerola-Baizán A, Perissinotti A, Scheltens P, Ikonomovic MD, Smith APL, Farrar G, Molinuevo JL, Barkhof F, Buckley CJ, van Berckel BNM, Gispert JD. Visual assessment of [ 18F]flutemetamol PET images can detect early amyloid pathology and grade its extent. Eur J Nucl Med Mol Imaging 2021; 48:2169-2182. [PMID: 33615397 PMCID: PMC8175297 DOI: 10.1007/s00259-020-05174-2] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 12/20/2020] [Indexed: 11/08/2022]
Abstract
Purpose To investigate the sensitivity of visual read (VR) to detect early amyloid pathology and the overall utility of regional VR. Methods [18F]Flutemetamol PET images of 497 subjects (ALFA+ N = 352; ADC N = 145) were included. Scans were visually assessed according to product guidelines, recording the number of positive regions (0–5) and a final negative/positive classification. Scans were quantified using the standard and regional Centiloid (CL) method. The agreement between VR-based classification and published CL-based cut-offs for early (CL = 12) and established (CL = 30) pathology was determined. An optimal CL cut-off maximizing Youden’s index was derived. Global and regional CL quantification was compared to VR. Finally, 28 post-mortem cases from the [18F]flutemetamol phase III trial were included to assess the percentage agreement between VR and neuropathological classification of neuritic plaque density. Results VR showed excellent agreement against CL = 12 (κ = .89, 95.2%) and CL = 30 (κ = .88, 95.4%) cut-offs. ROC analysis resulted in an optimal CL = 17 cut-off against VR (sensitivity = 97.9%, specificity = 97.8%). Each additional positive VR region corresponded to a clear increase in global CL. Regional VR was also associated with regional CL quantification. Compared to mCERADSOT-based classification (i.e., any region mCERADSOT > 1.5), VR was in agreement in 89.3% of cases, with 13 true negatives, 12 true positives, and 3 false positives (FP). Regional sparse-to-moderate neuritic and substantial diffuse Aβ plaque was observed in all FP cases. Regional VR was also associated with regional plaque density. Conclusion VR is an appropriate method for assessing early amyloid pathology and that grading the extent of visual amyloid positivity could present clinical value. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-020-05174-2.
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Affiliation(s)
- Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Juhan Reimand
- Alzheimer Center and department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands.,Department of Health Technologies, Tallinn University of Technology, Tallinn, Estonia.,Radiology Centre, North Estonia Medical Centre, Tallinn, Estonia
| | - Alle Meije Wink
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Marissa Zwan
- Alzheimer Center and department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Aida Niñerola-Baizán
- Nuclear Medicine Department, Hospital Clínic Barcelona & Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Andrés Perissinotti
- Nuclear Medicine Department, Hospital Clínic Barcelona & Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Philip Scheltens
- Alzheimer Center and department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Milos D Ikonomovic
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Geriatric Research Education and Clinical Center, VA Pittsburgh HS, Pittsburgh, PA, USA
| | | | | | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Universitat Pompeu Fabra, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands.,Centre for Medical Image Computing, and Queen Square Institute of Neurology, UCL, London, UK
| | | | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands. .,Department of Radiology and Nuclear Medicine, VU University Medical Center, De Boelelaan 1117, 1108 HV, Amsterdam, The Netherlands.
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain. .,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain. .,Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA. .,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain. .,Alzheimer Prevention Program, BarcelonaBeta Brain Research Center (BBRC), C/ Wellington, 30, 08005, Barcelona, Spain.
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Lopes Alves I, Collij LE, Altomare D, Frisoni GB, Saint‐Aubert L, Payoux P, Kivipelto M, Jessen F, Drzezga A, Leeuwis A, Wink AM, Visser PJ, van Berckel BN, Scheltens P, Gray KR, Wolz R, Stephens A, Gismondi R, Buckely C, Gispert JD, Schmidt M, Ford L, Ritchie C, Farrar G, Barkhof F, Molinuevo JL. Quantitative amyloid PET in Alzheimer's disease: the AMYPAD prognostic and natural history study. Alzheimers Dement 2020; 16:750-758. [PMID: 32281303 PMCID: PMC7984341 DOI: 10.1002/alz.12069] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 11/12/2019] [Accepted: 12/23/2019] [Indexed: 12/18/2022]
Abstract
INTRODUCTION The Amyloid Imaging to Prevent Alzheimer's Disease (AMYPAD) Prognostic and Natural History Study (PNHS) aims at understanding the role of amyloid imaging in the earliest stages of Alzheimer's disease (AD). AMYPAD PNHS adds (semi-)quantitative amyloid PET imaging to several European parent cohorts (PCs) to predict AD-related progression as well as address methodological challenges in amyloid PET. METHODS AMYPAD PNHS is an open-label, prospective, multi-center, cohort study recruiting from multiple PCs. Around 2000 participants will undergo baseline amyloid positron emission tomography (PET), half of whom will be invited for a follow-up PET 12 at least 12 months later. RESULTS Primary include several amyloid PET measurements (Centiloid, SUVr, BPND , R1 ), and secondary are their changes from baseline, relationship to other amyloid markers (cerebrospinal fluid and visual assessment), and predictive value of AD-related decline. EXPECTED IMPACT Determining the role of amyloid PET for the understanding of this complex disease and potentially improving secondary prevention trials.
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Affiliation(s)
- Isadora Lopes Alves
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Lyduine E. Collij
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
- Memory ClinicUniversity Hospital of GenevaGenevaSwitzerland
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
- Memory ClinicUniversity Hospital of GenevaGenevaSwitzerland
| | - Laure Saint‐Aubert
- Department of Nuclear MedicineImaging PoleToulouse, University HospitalToulouseFrance
- Toulouse NeuroImaging CenterUniversité de Toulouse, Inserm, UPSToulouseFrance
| | - Pierre Payoux
- Department of Nuclear MedicineImaging PoleToulouse, University HospitalToulouseFrance
- Toulouse NeuroImaging CenterUniversité de Toulouse, Inserm, UPSToulouseFrance
| | - Miia Kivipelto
- Department of Geriatric MedicineKarolinska University Hospital HuddingeStockholmSweden
| | - Frank Jessen
- Department of Nuclear MedicineUniversity of CologneCologneGermany
| | | | - Annebet Leeuwis
- Department of Neurology, Amsterdam UMCVrije Universiteit AmsterdamAlzheimercenterAmsterdamthe Netherlands
| | - Alle Meije Wink
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Amsterdam UMCVrije Universiteit AmsterdamAlzheimercenterAmsterdamthe Netherlands
| | - Bart N.M. van Berckel
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Philip Scheltens
- Department of Neurology, Amsterdam UMCVrije Universiteit AmsterdamAlzheimercenterAmsterdamthe Netherlands
| | | | | | | | | | | | - Juan Domingo Gispert
- Barcelona β Brain Research CenterBarcelonaSpain
- Centro de Investigación Biomédica en Red de BioingenieríaBiomateriales y Nanomedicina (CIBER‐BBN)MadridSpain
- Universitat Pompeu FabraBarcelonaSpain
| | | | - Lisa Ford
- Janssen Pharmaceutica RNDTitusvilleNew JerseyUSA
| | - Craig Ritchie
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Gill Farrar
- GE HealthcareLife SciencesAmershamUnited Kingdom
| | - Frederik Barkhof
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
- Centre for Medical Image ComputingMedical Physics and Biomedical Engineering, UCLLondonUnited Kingdom
| | - José Luis Molinuevo
- Barcelona β Brain Research CenterBarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - the AMYPAD Consortium
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
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