1
|
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.
Collapse
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
| |
Collapse
|
2
|
Sánchez-Soblechero A, López-García S, Lage C, Fernández-Matarrubia M, Irure J, López-Hoyos M, Jiménez-Bonilla J, Quirce R, de Arcocha-Torres M, Cuenca-Vera O, Martín-Arroyo J, Martínez-Dubarbie F, Pozueta A, García-Martínez M, Infante J, Sánchez-Juan P, Rodríguez-Rodríguez E. Where Should I Draw the Line: PET-Driven, Data-Driven, or Manufacturer Cut-Off? J Alzheimers Dis 2024; 98:957-967. [PMID: 38489172 DOI: 10.3233/jad-230678] [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] [Indexed: 03/17/2024]
Abstract
Background The optimal cut-off for Alzheimer's disease (AD) CSF biomarkers remains controversial. Objective To analyze the performance of cut-off points standardized by three methods: one that optimized the agreement between 11C-Pittsburgh compound B PET (a-PET) and CSF biomarkers (Aβ1-42, pTau, tTau, and Aβ1-42/Aβ1-40 ratio) in our population, called PET-driven; an unbiased cut-off using data from a healthy research cohort, called data-driven, and that provided by the manufacturer. We also compare changes in ATN classification. Methods CSF biomarkers measured by the LUMIPULSE G600II platform and qualitative visualization of amyloid positron emission tomography (a-PET) were performed in all the patients. We established a cut-off for each single biomarker and Aβ1-42/Aβ1-40 ratio that optimized their agreement with a-PET using ROC curves. Sensitivity, Specificity, and Overall Percent of Agreement are assessed using a-PET or clinical diagnosis as gold standard for every cut-off. Also, we established a data-driven cut-off from our cognitively unimpaired cohort. We then analyzed changes in ATN classification. Results One hundred and ten patients were recruited. Sixty-six (60%) were a-PET positive. PET-driven cut-offs were: pTau > 57, tTau > 362.62, Aβ1-42/Aβ1-40 < 0.069. For a single biomarker, pTau showed the highest accuracy (AUC 0.926). New PET-driven cut-offs classified patients similarly to manufacturer cut-offs (only two patients changed). However, 20 patients (18%) changed when data-driven cut-offs were used. Conclusions We established our sample's best CSF biomarkers cut-offs using a-PET as the gold standard. These cut-offs categorize better symptomatic subjects than data-driven in ATN classification, but they are very similar to the manufacturer's.
Collapse
Affiliation(s)
| | - Sara López-García
- Neurology Department, Cognitive Impairment Unit, 'Marqués de Valdecilla' University Hospital, Santander, Spain
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Carmen Lage
- Neurology Department, Cognitive Impairment Unit, 'Marqués de Valdecilla' University Hospital, Santander, Spain
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Marta Fernández-Matarrubia
- Neurology Department, Cognitive Impairment Unit, 'Marqués de Valdecilla' University Hospital, Santander, Spain
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Juan Irure
- Immunology Department, 'Marqués de Valdecilla' University Hospital, Santander, Spain
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Department of Medicine and Psychiatry, University of Cantabria, Santander, Spain
| | - Marcos López-Hoyos
- Immunology Department, 'Marqués de Valdecilla' University Hospital, Santander, Spain
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Department of Medicine and Psychiatry, University of Cantabria, Santander, Spain
| | - Julio Jiménez-Bonilla
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Nuclear Medicine Department, 'Marqués de Valdecilla' University Hospital, Santander, Spain
| | - Remedios Quirce
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Nuclear Medicine Department, 'Marqués de Valdecilla' University Hospital, Santander, Spain
| | - María de Arcocha-Torres
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Nuclear Medicine Department, 'Marqués de Valdecilla' University Hospital, Santander, Spain
| | - Oriana Cuenca-Vera
- Nuclear Medicine Department, 'Marqués de Valdecilla' University Hospital, Santander, Spain
| | - Juan Martín-Arroyo
- Neurology Department, Cognitive Impairment Unit, 'Marqués de Valdecilla' University Hospital, Santander, Spain
| | - Francisco Martínez-Dubarbie
- Neurology Department, Cognitive Impairment Unit, 'Marqués de Valdecilla' University Hospital, Santander, Spain
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Ana Pozueta
- Neurology Department, Cognitive Impairment Unit, 'Marqués de Valdecilla' University Hospital, Santander, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - María García-Martínez
- Neurology Department, Cognitive Impairment Unit, 'Marqués de Valdecilla' University Hospital, Santander, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Jon Infante
- Neurology Department, Cognitive Impairment Unit, 'Marqués de Valdecilla' University Hospital, Santander, Spain
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
- Department of Medicine and Psychiatry, University of Cantabria, Santander, Spain
| | - Pascual Sánchez-Juan
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
- Alzheimer's Centre Reina Sofia-CIEN Foundation-ISCIII, Madrid, Spain
| | - Eloy Rodríguez-Rodríguez
- Neurology Department, Cognitive Impairment Unit, 'Marqués de Valdecilla' University Hospital, Santander, Spain
- Institute for Research 'Marqués de Valdecilla' (IDIVAL), Santander, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
- Department of Medicine and Psychiatry, University of Cantabria, Santander, Spain
| |
Collapse
|
3
|
Guillén N, Contador J, Buongiorno M, Álvarez I, Culell N, Alcolea D, Lleó A, Fortea J, Piñol-Ripoll G, Carnes-Vendrell A, Lourdes Ispierto M, Vilas D, Puig-Pijoan A, Fernández-Lebrero A, Balasa M, Sánchez-Valle R, Lladó A. Agreement of cerebrospinal fluid biomarkers and amyloid-PET in a multicenter study. Eur Arch Psychiatry Clin Neurosci 2023:10.1007/s00406-023-01701-y. [PMID: 37898567 DOI: 10.1007/s00406-023-01701-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 10/02/2023] [Indexed: 10/30/2023]
Abstract
Core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers have shown incomplete agreement with amyloid-positron emission tomography (PET). Our goal was to analyze the agreement between AD CSF biomarkers and amyloid-PET in a multicenter study. Retrospective multicenter study (5 centers). Participants who underwent both CSF biomarkers and amyloid-PET scan within 18 months were included. Clinical diagnoses were made according to latest diagnostic criteria by the attending clinicians. CSF Amyloid Beta1-42 (Aβ1-42, A), phosphorliated tau 181 (pTau181, T) and total tau (tTau, N) biomarkers were considered normal (-) or abnormal ( +) according to cutoffs of each center. Amyloid-PET was visually classified as positive/negative. Agreement between CSF biomarkers and amyloid-PET was analyzed by overall percent agreement (OPA). 236 participants were included (mean age 67.9 years (SD 9.1), MMSE score 24.5 (SD 4.1)). Diagnoses were mild cognitive impairment or dementia due to AD (49%), Lewy body dementia (22%), frontotemporal dementia (10%) and others (19%). Mean time between tests was 5.1 months (SD 4.1). OPA between single CSF biomarkers and amyloid-PET was 74% for Aβ1-42, 75% for pTau181, 73% for tTau. The use of biomarker ratios improved OPA: 87% for Aβ1-42/Aβ1-40 (n = 155), 88% for pTau181/Aβ1-42 (n = 94) and 82% for tTau/Aβ1-42 (n = 160). A + T + N + cases showed the highest agreement between CSF biomarkers and amyloid-PET (96%), followed by A-T-N- cases (89%). Aβ1-42/Aβ1-40 was a better marker of cerebral amyloid deposition, as identified by amyloid tracers, than Aβ1-42 alone. Combined biomarkers in CSF predicted amyloid-PET result better than single biomarkers.
Collapse
Affiliation(s)
- Núria Guillén
- Alzheimer's Disease and Other Cognitive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Hospital Clínic de Barcelona, Carrer Villarroel, 170, 08036, Barcelona, Spain
| | - José Contador
- Alzheimer's Disease and Other Cognitive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Hospital Clínic de Barcelona, Carrer Villarroel, 170, 08036, Barcelona, Spain
| | - Mariateresa Buongiorno
- Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Terrassa, Spain
- Fundació Docència i Recerca Mútua Terrassa, Terrassa, Spain
| | - Ignacio Álvarez
- Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Terrassa, Spain
- Fundació Docència i Recerca Mútua Terrassa, Terrassa, Spain
| | - Natalia Culell
- Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Terrassa, Spain
- Fundació Docència i Recerca Mútua Terrassa, Terrassa, Spain
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau-Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas. CIBERNED, Madrid, Spain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau-Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas. CIBERNED, Madrid, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau-Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas. CIBERNED, Madrid, Spain
| | - Gerard Piñol-Ripoll
- Clinical Neuroscience Research, Unitat Trastorns Cognitius, IRBLleida, Santa Maria University Hospital, Lleida, Spain
| | - Anna Carnes-Vendrell
- Clinical Neuroscience Research, Unitat Trastorns Cognitius, IRBLleida, Santa Maria University Hospital, Lleida, Spain
| | - María Lourdes Ispierto
- Neurodegenerative Diseases Unit, Neurology Service and Neurosciences Department, University Hospital Germans Trias i Pujol (HUGTP), Badalona, Spain
| | - Dolores Vilas
- Neurodegenerative Diseases Unit, Neurology Service and Neurosciences Department, University Hospital Germans Trias i Pujol (HUGTP), Badalona, Spain
| | - Albert Puig-Pijoan
- Cognitive Decline and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Aida Fernández-Lebrero
- Cognitive Decline and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Hospital Clínic de Barcelona, Carrer Villarroel, 170, 08036, Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Hospital Clínic de Barcelona, Carrer Villarroel, 170, 08036, Barcelona, Spain
- Institute of Neurosciences, Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Hospital Clínic de Barcelona, Carrer Villarroel, 170, 08036, Barcelona, Spain.
- Institute of Neurosciences, Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain.
| |
Collapse
|
4
|
Toledo JB, Abdelnour C, Weil RS, Ferreira D, Rodriguez-Porcel F, Pilotto A, Wyman-Chick KA, Grothe MJ, Kane JPM, Taylor A, Rongve A, Scholz S, Leverenz JB, Boeve BF, Aarsland D, McKeith IG, Lewis S, Leroi I, Taylor JP. Dementia with Lewy bodies: Impact of co-pathologies and implications for clinical trial design. Alzheimers Dement 2023; 19:318-332. [PMID: 36239924 PMCID: PMC9881193 DOI: 10.1002/alz.12814] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 08/29/2022] [Accepted: 09/09/2022] [Indexed: 02/01/2023]
Abstract
Dementia with Lewy bodies (DLB) is clinically defined by the presence of visual hallucinations, fluctuations, rapid eye movement (REM) sleep behavioral disorder, and parkinsonism. Neuropathologically, it is characterized by the presence of Lewy pathology. However, neuropathological studies have demonstrated the high prevalence of coexistent Alzheimer's disease, TAR DNA-binding protein 43 (TDP-43), and cerebrovascular pathologic cases. Due to their high prevalence and clinical impact on DLB individuals, clinical trials should account for these co-pathologies in their design and selection and the interpretation of biomarkers values and outcomes. Here we discuss the frequency of the different co-pathologies in DLB and their cross-sectional and longitudinal clinical impact. We then evaluate the utility and possible applications of disease-specific and disease-nonspecific biomarkers and how co-pathologies can impact these biomarkers. We propose a framework for integrating multi-modal biomarker fingerprints and step-wise selection and assessment of DLB individuals for clinical trials, monitoring target engagement, and interpreting outcomes in the setting of co-pathologies.
Collapse
Affiliation(s)
- Jon B Toledo
- Nantz National Alzheimer Center, Stanley H. Appel Department of Neurology, Houston Methodist Hospital, Houston, Texas, USA
| | - Carla Abdelnour
- Fundació ACE. Barcelona Alzheimer Treatment and Research Center, Universitat Autónoma de Barcelona, Barcelona, Spain
| | - Rimona S Weil
- Dementia Research Centre, Wellcome Centre for Human Neuroimaging, Movement Disorders Consortium, National Hospital for Neurology and Neurosurgery, University College London, London, UK
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer's Research, Karolinska Institutet, Stockholm, Sweden
| | | | - Andrea Pilotto
- Department of Clinical and Experimental Sciences, University of Brescia, Parkinson's Disease Rehabilitation Centre, FERB ONLUS-S, Isidoro Hospital, Trescore Balneario (BG), Italy
| | - Kathryn A Wyman-Chick
- HealthPartners Center for Memory and Aging and Struthers Parkinson's Center, Saint Paul, Minnesota, USA
| | - Michel J Grothe
- Instituto de Biomedicina de Sevilla (IBiS), Unidad de Trastornos del Movimiento, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Joseph P M Kane
- Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Angela Taylor
- Lewy Body Dementia Association, Lilburn, Georgia, USA
| | - Arvid Rongve
- Department of Research and Innovation, Institute of Clinical Medicine (K1), Haugesund Hospital, Norway and The University of Bergen, Bergen, Norway
| | - Sonja Scholz
- Department of Neurology, National Institute of Neurological Disorders and Stroke, Neurodegenerative Diseases Research Unit, Johns Hopkins University Medical Center, Baltimore, Maryland, USA
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, Ohio, USA
| | - Bradley F Boeve
- Department of Neurology and Center for Sleep Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Dag Aarsland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Ian G McKeith
- Newcastle University Translational and Clinical Research Institute (NUTCRI, Newcastle upon Tyne, UK
| | - Simon Lewis
- ForeFront Parkinson's Disease Research Clinic, School of Medical Sciences, Brain and Mind Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Iracema Leroi
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - John P Taylor
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| |
Collapse
|
5
|
Wisch JK, Gordon BA, Boerwinkle AH, Luckett PH, Bollinger JG, Ovod V, Li Y, Henson RL, West T, Meyer MR, Kirmess KM, Benzinger TL, Fagan AM, Morris JC, Bateman RJ, Ances BM, Schindler SE. Predicting continuous amyloid PET values with CSF and plasma Aβ42/Aβ40. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12405. [PMID: 36874595 PMCID: PMC9980305 DOI: 10.1002/dad2.12405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 12/14/2022] [Accepted: 01/19/2023] [Indexed: 03/06/2023]
Abstract
Introduction Continuous measures of amyloid burden as measured by positron emission tomography (PET) are being used increasingly to stage Alzheimer's disease (AD). This study examined whether cerebrospinal fluid (CSF) and plasma amyloid beta (Aβ)42/Aβ40 could predict continuous values for amyloid PET. Methods CSF Aβ42 and Aβ40 were measured with automated immunoassays. Plasma Aβ42 and Aβ40 were measured with an immunoprecipitation-mass spectrometry assay. Amyloid PET was performed with Pittsburgh compound B (PiB). The continuous relationships of CSF and plasma Aβ42/Aβ40 with amyloid PET burden were modeled. Results Most participants were cognitively normal (427 of 491 [87%]) and the mean age was 69.0 ± 8.8 years. CSF Aβ42/Aβ40 predicted amyloid PET burden until a relatively high level of amyloid accumulation (69.8 Centiloids), whereas plasma Aβ42/Aβ40 predicted amyloid PET burden until a lower level (33.4 Centiloids). Discussion CSF Aβ42/Aβ40 predicts the continuous level of amyloid plaque burden over a wider range than plasma Aβ42/Aβ40 and may be useful in AD staging. Highlights Cerebrospinal fluid (CSF) amyloid beta (Aβ)42/Aβ40 predicts continuous amyloid positron emission tomography (PET) values up to a relatively high burden.Plasma Aβ42/Aβ40 is a comparatively dichotomous measure of brain amyloidosis.Models can predict regional amyloid PET burden based on CSF Aβ42/Aβ40.CSF Aβ42/Aβ40 may be useful in staging AD.
Collapse
Affiliation(s)
- Julie K. Wisch
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
| | - Brian A. Gordon
- Department of RadiologyWashington University in Saint LouisSt. LouisMissouriUSA
- Hope CenterWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| | - Anna H. Boerwinkle
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
| | - Patrick H. Luckett
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
| | - James G. Bollinger
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- The Tracy Family SILQ Center for Neurodegenerative BiologySt. LouisMissouriUSA
| | - Vitaliy Ovod
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- The Tracy Family SILQ Center for Neurodegenerative BiologySt. LouisMissouriUSA
| | - Yan Li
- Department of RadiologyWashington University in Saint LouisSt. LouisMissouriUSA
| | - Rachel L. Henson
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
| | - Tim West
- C2N DiagnosticsSt. LouisMissouriUSA
| | | | | | - Tammie L.S. Benzinger
- Department of RadiologyWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| | - Anne M. Fagan
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| | - John C. Morris
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| | - Randall J. Bateman
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- The Tracy Family SILQ Center for Neurodegenerative BiologySt. LouisMissouriUSA
| | - Beau M. Ances
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- Department of RadiologyWashington University in Saint LouisSt. LouisMissouriUSA
- Hope CenterWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| | - Suzanne E. Schindler
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| |
Collapse
|
6
|
Nordengen K, Pålhaugen L, Bettella F, Bahrami S, Selnes P, Jarholm J, Athanasiu L, Shadrin A, Andreassen OA, Fladby T. Phenotype-informed polygenic risk scores are associated with worse outcome in individuals at risk of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12350. [PMID: 35991219 PMCID: PMC9376972 DOI: 10.1002/dad2.12350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 06/30/2022] [Accepted: 07/07/2022] [Indexed: 11/11/2022]
Abstract
Introduction Patients with predementia Alzheimer's disease (AD) and at-risk subjects are targets for promising disease-modifying treatments, and improved polygenic risk scores (PRSs) could improve early-stage case selection. Methods Phenotype-informed PRSs were developed by selecting AD-associated variants conditional on relevant inflammatory or cardiovascular traits. The primary outcome was longitudinal changes in measures of AD pathology, namely development of pathological amyloid deposition, medial temporal lobe atrophy, and cognitive decline in a prospective cohort study including 394 adults without AD dementia. Results High-risk groups defined by phenotype-informed AD PRSs had significantly steeper volume decline in medial temporal cortices, and the high-risk group defined by the cardiovascular-informed AD PRS had significantly increased hazard ratio of pathological amyloid deposition, compared to low-risk groups. Discussion AD PRSs informed by inflammatory disorders or cardiovascular risk factors and diseases are associated with development of AD pathology markers and may improve identification of subjects at risk for progression of AD.
Collapse
Affiliation(s)
- Kaja Nordengen
- Department of NeurologyAkershus University HospitalLørenskogNorway
- Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Lene Pålhaugen
- Department of NeurologyAkershus University HospitalLørenskogNorway
- Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Francesco Bettella
- Norwegian Centre for Mental Disorders Research (NORMENT)Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Shahram Bahrami
- Norwegian Centre for Mental Disorders Research (NORMENT)Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Per Selnes
- Department of NeurologyAkershus University HospitalLørenskogNorway
- Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Jonas Jarholm
- Department of NeurologyAkershus University HospitalLørenskogNorway
- Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Lavinia Athanasiu
- Norwegian Centre for Mental Disorders Research (NORMENT)Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Alexey Shadrin
- Norwegian Centre for Mental Disorders Research (NORMENT)Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Ole A. Andreassen
- Institute of Clinical MedicineUniversity of OsloOsloNorway
- Norwegian Centre for Mental Disorders Research (NORMENT)Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Tormod Fladby
- Department of NeurologyAkershus University HospitalLørenskogNorway
- Institute of Clinical MedicineUniversity of OsloOsloNorway
| |
Collapse
|
7
|
Tideman P, Stomrud E, Leuzy A, Mattsson-Carlgren N, Palmqvist S, Hansson O. Association of β-Amyloid Accumulation With Executive Function in Adults With Unimpaired Cognition. Neurology 2022; 98:e1525-e1533. [PMID: 35022305 PMCID: PMC9012270 DOI: 10.1212/wnl.0000000000013299] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 12/27/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The neuropathologic changes underlying Alzheimer disease (AD) start before overt cognitive symptoms arise, but it is not well-known how they relate to the first subtle cognitive changes. The objective for this study was to examine the independent associations of the AD hallmarks β-amyloid (Aβ), tau, and neurodegeneration with different cognitive domains in cognitively unimpaired (CU) individuals. METHODS In this cross-sectional study, CU participants from the prospective BioFINDER-2 study were included. All had CSF biomarkers (Aβ42 and phosphorylated tau [p-tau]181), MRI (cortical thickness of AD-susceptible regions), Aβ-PET (neocortical uptake), tau-PET (entorhinal uptake), and cognitive test data for memory, executive function, verbal function, and visuospatial function. Multivariable linear regression models were performed using either CSF Aβ42, p-tau181, and cortical thickness or Aβ-PET, tau-PET, and cortical thickness as predictors of cognitive function. The results were validated in an independent cohort (Alzheimer's Disease Neuroimaging Initiative [ADNI]). RESULTS A total of 316 CU participants were included from the BioFINDER-2 study. Abnormal Aβ status was independently associated with the executive measure, regardless of modality (CSF Aβ42, β = 0.128, p = 0.024; Aβ-PET, β = 0.124, p = 0.049), while tau was independently associated with memory (CSF p-tau181, β = 0.132, p = 0.018; tau-PET, β = 0.189, p = 0.002). Cortical thickness was independently associated with the executive measure and verbal fluency in both models (p = 0.005-0.018). To examine the relationships in the earliest stage of preclinical AD, only participants with normal biomarkers of tau and neurodegeneration were included (n = 217 CSF-based; n = 246 PET-based). Again, Aβ status was associated with executive function (CSF Aβ42, β = 0.189, p = 0.005; Aβ-PET, β = 0.146, p = 0.023), but not with other cognitive domains. The results were overall replicated in the ADNI cohort (n = 361). DISCUSSION These findings suggest that Aβ is independently associated with worse performance on an executive measure but not with memory performance, which instead is associated with tau pathology. This may have implications for early preclinical AD screening and outcome measures in AD trials targeting Aβ pathology.
Collapse
Affiliation(s)
- Pontus Tideman
- From the Clinical Memory Research Unit, Department of Clinical Sciences (P.T., E.S., A.L., N.M.-C., S.P., O.H.), and Wallenberg Center for Molecular Medicine (N.M.-C.), Lund University; and Memory Clinic (P.T., E.S., S.P., O.H.) and Department of Neurology (N.M.-C.), Skåne University Hospital, Sweden
| | - Erik Stomrud
- From the Clinical Memory Research Unit, Department of Clinical Sciences (P.T., E.S., A.L., N.M.-C., S.P., O.H.), and Wallenberg Center for Molecular Medicine (N.M.-C.), Lund University; and Memory Clinic (P.T., E.S., S.P., O.H.) and Department of Neurology (N.M.-C.), Skåne University Hospital, Sweden
| | - Antoine Leuzy
- From the Clinical Memory Research Unit, Department of Clinical Sciences (P.T., E.S., A.L., N.M.-C., S.P., O.H.), and Wallenberg Center for Molecular Medicine (N.M.-C.), Lund University; and Memory Clinic (P.T., E.S., S.P., O.H.) and Department of Neurology (N.M.-C.), Skåne University Hospital, Sweden
| | - Niklas Mattsson-Carlgren
- From the Clinical Memory Research Unit, Department of Clinical Sciences (P.T., E.S., A.L., N.M.-C., S.P., O.H.), and Wallenberg Center for Molecular Medicine (N.M.-C.), Lund University; and Memory Clinic (P.T., E.S., S.P., O.H.) and Department of Neurology (N.M.-C.), Skåne University Hospital, Sweden
| | - Sebastian Palmqvist
- From the Clinical Memory Research Unit, Department of Clinical Sciences (P.T., E.S., A.L., N.M.-C., S.P., O.H.), and Wallenberg Center for Molecular Medicine (N.M.-C.), Lund University; and Memory Clinic (P.T., E.S., S.P., O.H.) and Department of Neurology (N.M.-C.), Skåne University Hospital, Sweden
| | - Oskar Hansson
- From the Clinical Memory Research Unit, Department of Clinical Sciences (P.T., E.S., A.L., N.M.-C., S.P., O.H.), and Wallenberg Center for Molecular Medicine (N.M.-C.), Lund University; and Memory Clinic (P.T., E.S., S.P., O.H.) and Department of Neurology (N.M.-C.), Skåne University Hospital, Sweden.
| |
Collapse
|
8
|
Morenas-Rodríguez E, Li Y, Nuscher B, Franzmeier N, Xiong C, Suárez-Calvet M, Fagan AM, Schultz S, Gordon BA, Benzinger TLS, Hassenstab J, McDade E, Feederle R, Karch CM, Schlepckow K, Morris JC, Kleinberger G, Nellgard B, Vöglein J, Blennow K, Zetterberg H, Ewers M, Jucker M, Levin J, Bateman RJ, Haass C. Soluble TREM2 in CSF and its association with other biomarkers and cognition in autosomal-dominant Alzheimer's disease: a longitudinal observational study. Lancet Neurol 2022; 21:329-341. [PMID: 35305339 PMCID: PMC8926925 DOI: 10.1016/s1474-4422(22)00027-8] [Citation(s) in RCA: 79] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 01/05/2022] [Accepted: 01/10/2022] [Indexed: 02/08/2023]
Abstract
BACKGROUND Therapeutic modulation of TREM2-dependent microglial function might provide an additional strategy to slow the progression of Alzheimer's disease. Although studies in animal models suggest that TREM2 is protective against Alzheimer's pathology, its effect on tau pathology and its potential beneficial role in people with Alzheimer's disease is still unclear. Our aim was to study associations between the dynamics of soluble TREM2, as a biomarker of TREM2 signalling, and amyloid β (Aβ) deposition, tau-related pathology, neuroimaging markers, and cognitive decline, during the progression of autosomal dominant Alzheimer's disease. METHODS We did a longitudinal analysis of data from the Dominantly Inherited Alzheimer Network (DIAN) observational study, which includes families with a history of autosomal dominant Alzheimer's disease. Participants aged over 18 years who were enrolled in DIAN between Jan 1, 2009, and July 31, 2019, were categorised as either carriers of pathogenic variants in PSEN1, PSEN2, and APP genes (n=155) or non-carriers (n=93). We measured amounts of cleaved soluble TREM2 using a novel immunoassay in CSF samples obtained every 2 years from participants who were asymptomatic (Clinical Dementia Rating [CDR]=0) and annually for those who were symptomatic (CDR>0). CSF concentrations of Aβ40, Aβ42, total tau (t-tau), and tau phosphorylated on threonine 181 (p-tau) were measured by validated immunoassays. Predefined neuroimaging measurements were total cortical uptake of Pittsburgh compound B PET (PiB-PET), cortical thickness in the precuneus ascertained by MRI, and hippocampal volume determined by MRI. Cognition was measured using a validated cognitive composite (including DIAN word list test, logical memory delayed recall, digit symbol coding test [total score], and minimental status examination). We based our statistical analysis on univariate and bivariate linear mixed effects models. FINDINGS In carriers of pathogenic variants, a high amyloid burden at baseline, represented by low CSF Aβ42 (β=-4·28 × 10-2 [SE 0·013], p=0·0012), but not high cortical uptake in PiB-PET (β=-5·51 × 10-3 [0·011], p=0·63), was the only predictor of an augmented annual rate of subsequent increase in soluble TREM2. Augmented annual rates of increase in soluble TREM2 were associated with a diminished rate of decrease in amyloid deposition, as measured by Aβ42 in CSF (r=0·56 [0·22], p=0·011), in presymptomatic carriers of pathogenic variants, and with diminished annual rate of increase in PiB-PET (r=-0·67 [0·25], p=0·0060) in symptomatic carriers of pathogenic variants. Presymptomatic carriers of pathogenic variants with annual rates of increase in soluble TREM2 lower than the median showed a correlation between enhanced annual rates of increase in p-tau in CSF and augmented annual rates of increase in PiB-PET signal (r=0·45 [0·21], p=0·035), that was not observed in those with rates of increase in soluble TREM2 higher than the median. Furthermore, presymptomatic carriers of pathogenic variants with rates of increase in soluble TREM2 above or below the median had opposite associations between Aβ42 in CSF and PiB-PET uptake when assessed longitudinally. Augmented annual rates of increase in soluble TREM2 in presymptomatic carriers of pathogenic variants correlated with decreased cortical shrinkage in the precuneus (r=0·46 [0·22]), p=0·040) and diminished cognitive decline (r=0·67 [0·22], p=0·0020). INTERPRETATION Our findings in autosomal dominant Alzheimer's disease position the TREM2 response within the amyloid cascade immediately after the first pathological changes in Aβ aggregation and further support the role of TREM2 on Aβ plaque deposition and compaction. Furthermore, these findings underpin a beneficial effect of TREM2 on Aβ deposition, Aβ-dependent tau pathology, cortical shrinkage, and cognitive decline. Soluble TREM2 could, therefore, be a key marker for clinical trial design and interpretation. Efforts to develop TREM2-boosting therapies are ongoing. FUNDING German Research Foundation, US National Institutes of Health.
Collapse
Affiliation(s)
- Estrella Morenas-Rodríguez
- German Center for Neurodegenerative Diseases, Munich, Germany; Metabolic Biochemistry, Biomedical Center, Faculty of Medicine, Ludwig-Maximilians University, Munich, Germany.
| | - Yan Li
- Division of Biostatistics, Washington University School of Medicine, St Louis, MO, USA
| | - Brigitte Nuscher
- German Center for Neurodegenerative Diseases, Munich, Germany; Metabolic Biochemistry, Biomedical Center, Faculty of Medicine, Ludwig-Maximilians University, Munich, Germany
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians University, Munich, Germany
| | - Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine, St Louis, MO, USA
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Servei de Neurologia, Hospital del Mar Medical Research Institute, Barcelona, Spain; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable, Madrid, Spain
| | - Anne M Fagan
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Stephanie Schultz
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Brian A Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Eric McDade
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Regina Feederle
- German Center for Neurodegenerative Diseases, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; Institute for Diabetes and Obesity, Monoclonal Antibody Core Facility, Helmholtz Center, Munich, Germany; German Research Center for Environmental Health, Neuherberg, Germany
| | - Celeste M Karch
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Kai Schlepckow
- German Center for Neurodegenerative Diseases, Munich, Germany; Metabolic Biochemistry, Biomedical Center, Faculty of Medicine, Ludwig-Maximilians University, Munich, Germany
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Gernot Kleinberger
- German Center for Neurodegenerative Diseases, Munich, Germany; Metabolic Biochemistry, Biomedical Center, Faculty of Medicine, Ludwig-Maximilians University, Munich, Germany
| | - Bengt Nellgard
- Department of Anesthesiology and Intensive Care, Sahlgrenska University Hospital, Mölndal, Sweden; Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Jonathan Vöglein
- German Center for Neurodegenerative Diseases, Munich, Germany; Department of Neurology, University Hospital of Munich, Ludwig-Maximilians University, Munich, Germany
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Queens Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute, University College London, London, UK; Hong Kong Center for Neurodegenerative Diseases, Hong Kong Special Administrative Region, China
| | - Michael Ewers
- German Center for Neurodegenerative Diseases, Munich, Germany; Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians University, Munich, Germany
| | - Mathias Jucker
- German Center for Neurodegenerative Diseases, Tübingen, Germany; Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Johannes Levin
- German Center for Neurodegenerative Diseases, Munich, Germany; Department of Neurology, University Hospital of Munich, Ludwig-Maximilians University, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Christian Haass
- German Center for Neurodegenerative Diseases, Munich, Germany; Metabolic Biochemistry, Biomedical Center, Faculty of Medicine, Ludwig-Maximilians University, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| |
Collapse
|
9
|
Teipel SJ, Dyrba M, Vergallo A, Lista S, Habert MO, Potier MC, Lamari F, Dubois B, Hampel H, Grothe MJ. Partial Volume Correction Increases the Sensitivity of 18F-Florbetapir-Positron Emission Tomography for the Detection of Early Stage Amyloidosis. Front Aging Neurosci 2022; 13:748198. [PMID: 35002673 PMCID: PMC8729321 DOI: 10.3389/fnagi.2021.748198] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 11/05/2021] [Indexed: 11/25/2022] Open
Abstract
Purpose: To test whether correcting for unspecific signal from the cerebral white matter increases the sensitivity of amyloid-PET for early stages of cerebral amyloidosis. Methods: We analyzed 18F-Florbetapir-PET and cerebrospinal fluid (CSF) Aβ42 data from 600 older individuals enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), including people with normal cognition, mild cognitive impairment (MCI), and Alzheimer’s disease (AD) dementia. We determined whether three compartmental partial volume correction (PVC-3), explicitly modeling signal spill-in from white matter, significantly improved the association of CSF Aβ42 levels with global 18F-Florbetapir-PET values compared with standard processing without PVC (non-PVC) and a widely used two-compartmental PVC method (PVC-2). In additional voxel-wise analyses, we determined the sensitivity of PVC-3 compared with non-PVC and PVC-2 for detecting early regional amyloid build-up as modeled by decreasing CSF Aβ42 levels. For replication, we included an independent sample of 43 older individuals with subjective memory complaints from the INveStIGation of AlzHeimer’s PredicTors cohort (INSIGHT-preAD study). Results: In the ADNI sample, PVC-3 18F-Florbetapir-PET values normalized to whole cerebellum signal showed significantly stronger associations with CSF Aβ42 levels than non-PVC or PVC-2, particularly in the lower range of amyloid levels. These effects were replicated in the INSIGHT-preAD sample. PVC-3 18F-Florbetapir-PET data detected regional amyloid build-up already at higher (less abnormal) CSF Aβ42 levels than non-PVC or PVC-2 data. Conclusion: A PVC approach that explicitly models unspecific white matter binding improves the sensitivity of amyloid-PET for identifying the earliest stages of cerebral amyloid pathology which has implications for future primary prevention trials.
Collapse
Affiliation(s)
- Stefan J Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany
| | - Martin Dyrba
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Andrea Vergallo
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'Hôpital, Paris, France
| | - Simone Lista
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'Hôpital, Paris, France.,Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'Hôpital, Paris, France.,Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'Hôpital, Paris, France
| | - Marie Odile Habert
- Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, LIB, Sorbonne University, Paris, France.,Department of Nuclear Medicine, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.,Centre d'Acquisition et Traitement des Images (CATI platform), Paris, France
| | - Marie-Claude Potier
- ICM Institut du Cerveau et de la Moelle Épinière, CNRS UMR 7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, 47 Bd de l'Hôpital, Paris, France
| | - Foudil Lamari
- UF Biochimie des Maladies Neurométaboliques, Service de Biochimie Métabolique, Hôpital Pitié-Salpêtrière, Paris, France
| | - Bruno Dubois
- Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'Hôpital, Paris, France
| | - Harald Hampel
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'Hôpital, Paris, France
| | - Michel J Grothe
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| |
Collapse
|
10
|
Jiang C, Wang Q, Xie S, Chen Z, Fu L, Peng Q, Liang Y, Guo H, Guo T. OUP accepted manuscript. Brain Commun 2022; 4:fcac084. [PMID: 35441134 PMCID: PMC9014538 DOI: 10.1093/braincomms/fcac084] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 12/21/2021] [Accepted: 03/29/2022] [Indexed: 11/14/2022] Open
Affiliation(s)
- Chenyang Jiang
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Qingyong Wang
- Department of Neurology, University of Chinese Academy of Sciences-Shenzhen Hospital, Shenzhen 518107, China
| | - Siwei Xie
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Zhicheng Chen
- Institute of Chemical Biology, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Liping Fu
- Department of Nuclear Medicine, China-Japan Friendship Hospital, 2 Yinghuayuan Dongjie, Beijing 100029, China
| | - Qiyu Peng
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Ying Liang
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - Hongbo Guo
- Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- Correspondence to: Tengfei Guo, PhD Institute of Biomedical Engineering Shenzhen Bay Laboratory, No.5 Kelian Road Shenzhen 518132, China E-mail:
| | | |
Collapse
|
11
|
Sacchi L, Carandini T, Fumagalli GG, Pietroboni AM, Contarino VE, Siggillino S, Arcaro M, Fenoglio C, Zito F, Marotta G, Castellani M, Triulzi F, Galimberti D, Scarpini E, Arighi A. Unravelling the Association Between Amyloid-PET and Cerebrospinal Fluid Biomarkers in the Alzheimer's Disease Spectrum: Who Really Deserves an A+? J Alzheimers Dis 2021; 85:1009-1020. [PMID: 34897084 DOI: 10.3233/jad-210593] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Association between cerebrospinal fluid (CSF)-amyloid-β (Aβ)42 and amyloid-PET measures is inconstant across the Alzheimer's disease (AD) spectrum. However, they are considered interchangeable, along with Aβ 42/40 ratio, for defining 'Alzheimer's Disease pathologic change' (A+). OBJECTIVE Herein, we further characterized the association between amyloid-PET and CSF biomarkers and tested their agreement in a cohort of AD spectrum patients. METHODS We include ed 23 patients who underwent amyloid-PET, MRI, and CSF analysis showing reduced levels of Aβ 42 within a 365-days interval. Thresholds used for dichotomization were: Aβ 42 < 640 pg/mL (Aβ 42+); pTau > 61 pg/mL (pTau+); and Aβ 42/40 < 0.069 (ADratio+). Amyloid-PET scans were visually assessed and processed by four pipelines (SPMCL, SPMAAL, FSGM, FSWC). RESULTS Different pipelines gave highly inter-correlated standardized uptake value ratios (SUVRs) (rho = 0.93-0.99). The most significant findings were: pTau positive correlation with SPMCL SUVR (rho = 0.56, p = 0.0063) and Aβ 42/40 negative correlation with SPMCL and SPMAAL SUVRs (rho = -0.56, p = 0.0058; rho = -0.52, p = 0.0117 respectively). No correlations between CSF-Aβ 42 and global SUVRs were observed. In subregion analysis, both pTau and Aβ 42/40 values significantly correlated with cingulate SUVRs from any pipeline (R2 = 0.55-0.59, p < 0.0083), with the strongest associations observed for the posterior/isthmus cingulate areas. However, only associations observed for Aβ 42/40 ratio were still significant in linear regression models. Moreover, combining pTau with Aβ 42 or using Aβ 42/40, instead of Aβ 42 alone, increased concordance with amyloid-PET status from 74% to 91% based on visual reads and from 78% to 96% based on Centiloids. CONCLUSION We confirmed that, in the AD spectrum, amyloid-PET measures show a stronger association and a better agreement with CSF-Aβ 42/40 and secondarily pTau rather than Aβ 42 levels.
Collapse
Affiliation(s)
- Luca Sacchi
- University of Milan, Milan, Italy.,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Tiziana Carandini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | | | - Anna Margherita Pietroboni
- University of Milan, Milan, Italy.,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | | | - Silvia Siggillino
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Marina Arcaro
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Chiara Fenoglio
- University of Milan, Milan, Italy.,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Felicia Zito
- University of Milan, Milan, Italy.,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Giorgio Marotta
- University of Milan, Milan, Italy.,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Massimo Castellani
- University of Milan, Milan, Italy.,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Fabio Triulzi
- University of Milan, Milan, Italy.,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Daniela Galimberti
- University of Milan, Milan, Italy.,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Elio Scarpini
- University of Milan, Milan, Italy.,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Andrea Arighi
- University of Milan, Milan, Italy.,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| |
Collapse
|
12
|
Hampel H, Hardy J, Blennow K, Chen C, Perry G, Kim SH, Villemagne VL, Aisen P, Vendruscolo M, Iwatsubo T, Masters CL, Cho M, Lannfelt L, Cummings JL, Vergallo A. The Amyloid-β Pathway in Alzheimer's Disease. Mol Psychiatry 2021; 26:5481-5503. [PMID: 34456336 PMCID: PMC8758495 DOI: 10.1038/s41380-021-01249-0] [Citation(s) in RCA: 595] [Impact Index Per Article: 198.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 07/19/2021] [Accepted: 07/28/2021] [Indexed: 02/06/2023]
Abstract
Breakthroughs in molecular medicine have positioned the amyloid-β (Aβ) pathway at the center of Alzheimer's disease (AD) pathophysiology. While the detailed molecular mechanisms of the pathway and the spatial-temporal dynamics leading to synaptic failure, neurodegeneration, and clinical onset are still under intense investigation, the established biochemical alterations of the Aβ cycle remain the core biological hallmark of AD and are promising targets for the development of disease-modifying therapies. Here, we systematically review and update the vast state-of-the-art literature of Aβ science with evidence from basic research studies to human genetic and multi-modal biomarker investigations, which supports a crucial role of Aβ pathway dyshomeostasis in AD pathophysiological dynamics. We discuss the evidence highlighting a differentiated interaction of distinct Aβ species with other AD-related biological mechanisms, such as tau-mediated, neuroimmune and inflammatory changes, as well as a neurochemical imbalance. Through the lens of the latest development of multimodal in vivo biomarkers of AD, this cross-disciplinary review examines the compelling hypothesis- and data-driven rationale for Aβ-targeting therapeutic strategies in development for the early treatment of AD.
Collapse
Affiliation(s)
- Harald Hampel
- Eisai Inc., Neurology Business Group, Woodcliff Lake, NJ, USA.
| | - John Hardy
- UK Dementia Research Institute at UCL and Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Christopher Chen
- Memory Aging and Cognition Centre, Departments of Pharmacology and Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - George Perry
- Department of Biology and Neurosciences Institute, University of Texas at San Antonio (UTSA), San Antonio, TX, USA
| | - Seung Hyun Kim
- Department of Neurology, College of Medicine, Hanyang University, Seoul, Republic of Korea; Cell Therapy Center, Hanyang University Hospital, Seoul, Republic of Korea
| | - Victor L Villemagne
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
| | - Paul Aisen
- USC Alzheimer's Therapeutic Research Institute, San Diego, CA, USA
| | - Michele Vendruscolo
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge, UK
| | - Takeshi Iwatsubo
- Department of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Colin L Masters
- Laureate Professor of Dementia Research, Florey Institute and The University of Melbourne, Parkville, VIC, Australia
| | - Min Cho
- Eisai Inc., Neurology Business Group, Woodcliff Lake, NJ, USA
| | - Lars Lannfelt
- Uppsala University, Department of of Public Health/Geriatrics, Uppsala, Sweden
- BioArctic AB, Stockholm, Sweden
| | - Jeffrey L Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV), Las Vegas, NV, USA
| | - Andrea Vergallo
- Eisai Inc., Neurology Business Group, Woodcliff Lake, NJ, USA.
| |
Collapse
|
13
|
Aksnes M, Müller EG, Tiiman A, Edwin TH, Terenius L, Revheim ME, Vukojević V, Bogdanović N, Knapskog AB. Amyloidogenic Nanoplaques in Cerebrospinal Fluid: Relationship to Amyloid Brain Uptake and Clinical Alzheimer's Disease in a Memory Clinic Cohort. J Alzheimers Dis 2021; 77:831-842. [PMID: 32741818 PMCID: PMC7592690 DOI: 10.3233/jad-200237] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Aggregation of amyloid-β (Aβ) is an early pathological event in Alzheimer's disease (AD). Consequently, measures of pathogenic aggregated Aβ are attractive biomarkers for AD. Here, we use a recently developed Thioflavin-T-Fluorescence Correlation Spectroscopy (ThT-FCS) assay to quantify structured ThT-responsive protein aggregates, so-called nanoplaques, in the cerebrospinal fluid (CSF). OBJECTIVE The overall aim of this work was to assess whether ThT-FCS determined CSF nanoplaque levels could predict amyloid brain uptake as determined by 18F-Flutemetamol PET analysis. Further, we assess whether nanoplaque levels could predict clinical AD. METHODS Nanoplaque levels in the CSF from 54 memory clinic patients were compared between sub-groups classified by 18F-Flutemetamol PET as amyloid-positive or amyloid-negative, and by clinical assessment as AD or non-AD. RESULTS Nanoplaque levels did not differ between amyloid groups and could not predict brain amyloid uptake. However, nanoplaque levels were significantly increased in patients with clinical AD, and were significant predictors for AD when adjusting for age, sex, cognitive function, and apolipoprotein E (APOE) genotype. CONCLUSION The concentration of nanoplaques in the CSF differentiates patients with clinical AD from non-AD patients.
Collapse
Affiliation(s)
- Mari Aksnes
- Department of Geriatric Medicine, University of Oslo, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ebba Glersen Müller
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Nuclear Medicine, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Ann Tiiman
- Department of Clinical Neurosciences (CNS), Center for Molecular Medicine CMM L8: 01, Karolinska Institutet, Stockholm, Sweden
| | - Trine Holt Edwin
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway.,Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Vestfold, Norway
| | - Lars Terenius
- Department of Clinical Neurosciences (CNS), Center for Molecular Medicine CMM L8: 01, Karolinska Institutet, Stockholm, Sweden
| | - Mona-Elisabeth Revheim
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Nuclear Medicine, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Vladana Vukojević
- Department of Clinical Neurosciences (CNS), Center for Molecular Medicine CMM L8: 01, Karolinska Institutet, Stockholm, Sweden
| | - Nenad Bogdanović
- Department of Geriatric Medicine, University of Oslo, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Neurobiology, Care Science and Society (NVS), Division of Clinical Geriatrics, Karolinska Institutet, Huddinge, Sweden
| | - Anne-Brita Knapskog
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| |
Collapse
|
14
|
Lombardi G, Pupi A, Bessi V, Polito C, Padiglioni S, Ferrari C, Lucidi G, Berti V, De Cristofaro MT, Piaceri I, Bagnoli S, Nacmias B, Sorbi S. Challenges in Alzheimer's Disease Diagnostic Work-Up: Amyloid Biomarker Incongruences. J Alzheimers Dis 2021; 77:203-217. [PMID: 32716357 DOI: 10.3233/jad-200119] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Discordance among amyloid biomarkers is a challenge to overcome in order to increase diagnostic accuracy in dementia. OBJECTIVES 1) To verify that cerebrospinal fluid (CSF) Aβ42/Aβ40 ratio (AβR) better agrees with Amyloid PET (Amy-PET) results compared to CSF Aβ42; 2) to detect differences among concordant positive, concordant negative, and discordant cases, basing the concordance definition on the agreement between CSF AβR and Amy-PET results; 3) to define the suspected underlying pathology of discordant cases using in vivo biomarkers. METHOD We retrospectively enrolled 39 cognitively impaired participants in which neuropsychological tests, apolipoprotein E genotype determination, TC/MRI, FDG-PET, Amy-PET, and CSF analysis had been performed. In all cases, CSF analysis was repeated using the automated Lumipulse method. In discordant cases, FDG-PET scans were evaluated visually and using automated classifiers. RESULTS CSF AβR better agreed with Amy-PET compared to CSF Aβ42 (Cohen's K 0.431 versus 0.05). Comparisons among groups did not show any difference in clinical characteristics except for age at symptoms onset that was higher in the 6 discordant cases with abnormal CSF AβR values and negative Amy-PET (CSF AβR+/AmyPET-). FDG-PET and all CSF markers (Aβ42, AβR, p-Tau, t-Tau) were suggestive of Alzheimer's disease (AD) in 5 of these 6 cases. CONCLUSION 1) CSF AβR is the CSF amyloid marker that shows the better level of agreement with Amy-PET results; 2) The use of FDG-PET and CSF-Tau markers in CSFAβR+/Amy-PET-discordant cases can support AD diagnosis; 3) Disagreement between positive CSF AβR and negative Amy-PET in symptomatic aged AD patients could be due to the variability in plaques conformation and a negative Amy-PET scan cannot be always sufficient to rule out AD.
Collapse
Affiliation(s)
- Gemma Lombardi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.,Fondazione Filippo Turati, Pistoia, Italy
| | | | | | - Cristina Polito
- Department of Biomedical, Experimental and Clinical Sciences "Mario Serio", Nuclear Medicine Unit, University of Florence, Florence, Italy
| | - Sonia Padiglioni
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Camilla Ferrari
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | | | - Valentina Berti
- Department of Biomedical, Experimental and Clinical Sciences "Mario Serio", Nuclear Medicine Unit, University of Florence, Florence, Italy
| | | | - Irene Piaceri
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.,Fondazione IRCCS Don Carlo Gnocchi, Florence, Italy
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.,Fondazione IRCCS Don Carlo Gnocchi, Florence, Italy
| |
Collapse
|
15
|
Reijntjes RH, Potters WV, Kerkhof FI, van Zwet E, van Rossum IA, Verhamme C, Tannemaat MR. Deriving reference values for nerve conduction studies from existing data using mixture model clustering. Clin Neurophysiol 2021; 132:1820-1829. [PMID: 34130250 DOI: 10.1016/j.clinph.2021.04.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 03/23/2021] [Accepted: 04/10/2021] [Indexed: 11/19/2022]
Abstract
OBJECTIVE to obtain locally valid reference values (RVs) from existing nerve conduction study (NCS) data. METHODS we used age, sex, height and limb temperature-based mixture model clustering (MMC) to identify normal and abnormal measurements on NCS data from two university hospitals. We compared MMC-derived RVs to published data; examined the effect of using different variables; validated MMC-derived RVs using independent data from 26 healthy control subjects and investigated their clinical applicability for the diagnosis of polyneuropathy. RESULTS MMC-derived RVs were similar to published RVs. Clustering can be achieved using only sex and age as variables. MMC is likely to yield reliable results with fewer abnormal than normal measurements and when the total number of measurements is at least 300. Measurements from healthy controls fell within the 95% MMC-derived prediction interval in 97.4% of cases. CONCLUSIONS MMC can be used to obtain RVs from existing data, providing a locally valid, accurate reflection of the (ab)normality of an NCS result. SIGNIFICANCE MMC can be used to generate locally valid RVs for any test for which sufficient data are available.1.
Collapse
Affiliation(s)
- R H Reijntjes
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands.
| | - W V Potters
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - F I Kerkhof
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands.
| | - E van Zwet
- Department of Biostatistics, Leiden University Medical Center, Leiden, the Netherlands.
| | - I A van Rossum
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands.
| | - C Verhamme
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - M R Tannemaat
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands.
| |
Collapse
|
16
|
Jung NY, Kim ES, Kim HS, Jeon S, Lee MJ, Pak K, Lee JH, Lee YM, Lee K, Shin JH, Ko JK, Lee JM, Yoon JA, Hwang C, Choi KU, Lee EC, Seong JK, Huh GY, Kim DS, Kim EJ. Comparison of Diagnostic Performances Between Cerebrospinal Fluid Biomarkers and Amyloid PET in a Clinical Setting. J Alzheimers Dis 2021; 74:473-490. [PMID: 32039853 DOI: 10.3233/jad-191109] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The diagnostic performances of cerebrospinal fluid (CSF) biomarkers and amyloid positron emission tomography (PET) were compared by examining the association and concordance or discordance between CSF Aβ1-42 and amyloid PET, after determining our own cut-off values for CSF Alzheimer's disease (AD) biomarkers. Furthermore, we evaluated the ability of CSF biomarkers and amyloid PET to predict clinical progression. CSF Aβ1-42, t-tau, and p-tau levels were analyzed in 203 individuals [27 normal controls, 38 mild cognitive impairment (MCI), 62 AD dementia, and 76 patients with other neurodegenerative diseases] consecutively recruited from two dementia clinics. We used both visual and standardized uptake value ratio (SUVR)-based amyloid PET assessments for analyses. The association of CSF biomarkers with amyloid PET SUVR, hippocampal atrophy, and cognitive function were investigated by linear regression analysis, and the risk of conversion from MCI to AD dementia was assessed using a Cox proportional hazards model. CSF p-tau/Aβ1-42 and t-tau/Aβ1-42 exhibited the best diagnostic accuracies among the CSF AD biomarkers examined. Correlations were observed between CSF biomarkers and global SUVR, hippocampal volume, and cognitive function. Overall concordance and discordance between CSF Aβ1-42 and amyloid PET was 77% and 23%, respectively. Baseline positive CSF Aβ1-42 for MCI demonstrated a 5.6-fold greater conversion risk than negative CSF Aβ1-42 . However, amyloid PET findings failed to exhibit significant prognostic value. Therefore, despite presence of a significant correlation between the CSF Aβ1-42 level and SUVR of amyloid PET, and a relevant concordance between CSF Aβ1-42 and amyloid PET, baseline CSF Aβ1-42 better predicted AD conversion.
Collapse
Affiliation(s)
- Na-Yeon Jung
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Eun Soo Kim
- Department of Anesthesia and Pain Medicine, Pusan National University Hospital, School of Medicine, Pusan National University, Busan, Republic of Korea
| | - Hyang-Sook Kim
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Sumin Jeon
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| | - Myung Jun Lee
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| | - Kyoungjune Pak
- Department of Nuclear Medicine, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Jae-Hyeok Lee
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Young Min Lee
- Department of Psychiatry, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Kangyoon Lee
- Department of Psychiatry, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Jin-Hong Shin
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Jun Kyeung Ko
- Department of Neurosurgery, Medical Research Institute, Pusan National University Hospital, Busan, Republic of Korea
| | - Jae Meen Lee
- Department of Neurosurgery, Medical Research Institute, Pusan National University Hospital, Busan, Republic of Korea
| | - Jin A Yoon
- Department of Rehabilitation Medicine, Pusan National University School of Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea
| | - Chungsu Hwang
- Department of Pathology, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Kyung-Un Choi
- Department of Pathology, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Eun Chong Lee
- School of Biomedical Engineering, Korea University, Seoul, Republic of Korea
| | - Joon-Kyung Seong
- School of Biomedical Engineering, Korea University, Seoul, Republic of Korea
| | - Gi Yeong Huh
- Department of Forensic Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Dae-Seong Kim
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Eun-Joo Kim
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| |
Collapse
|
17
|
Sala A, Nordberg A, Rodriguez-Vieitez E. Longitudinal pathways of cerebrospinal fluid and positron emission tomography biomarkers of amyloid-β positivity. Mol Psychiatry 2021; 26:5864-5874. [PMID: 33303945 PMCID: PMC8758501 DOI: 10.1038/s41380-020-00950-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Revised: 10/09/2020] [Accepted: 11/02/2020] [Indexed: 01/20/2023]
Abstract
Mismatch between CSF and PET amyloid-β biomarkers occurs in up to ≈20% of preclinical/prodromal Alzheimer's disease individuals. Factors underlying mismatching results remain unclear. In this study we hypothesized that CSF/PET discordance provides unique biological/clinical information. To test this hypothesis, we investigated non-demented and demented participants with CSF amyloid-β42 and [18F]Florbetapir PET assessments at baseline (n = 867) and at 2-year follow-up (n = 289). Longitudinal trajectories of amyloid-β positivity were tracked simultaneously for CSF and PET biomarkers. In the longitudinal cohort (n = 289), we found that participants with normal CSF/PET amyloid-β biomarkers progressed more frequently toward CSF/PET discordance than to full CSF/PET positivity (χ2(1) = 5.40; p < 0.05). Progression to CSF+/PET+ status was ten times more frequent in cases with discordant biomarkers, as compared to csf-/pet- cases (χ2(1) = 18.86; p < 0.001). Compared to the CSF+/pet- group, the csf-/PET+ group had lower APOE-ε4ε4 prevalence (χ2(6) = 197; p < 0.001; n = 867) and slower rate of brain amyloid-β accumulation (F(3,600) = 12.76; p < 0.001; n = 608). These results demonstrate that biomarker discordance is a typical stage in the natural history of amyloid-β accumulation, with CSF or PET becoming abnormal first and not concurrently. Therefore, biomarker discordance allows for identification of individuals with elevated risk of progression toward fully abnormal amyloid-β biomarkers, with subsequent risk of neurodegeneration and cognitive decline. Our results also suggest that there are two alternative pathways ("CSF-first" vs. "PET-first") toward established amyloid-β pathology, characterized by different genetic profiles and rates of amyloid-β accumulation. In conclusion, CSF and PET amyloid-β biomarkers provide distinct information, with potential implications for their use as biomarkers in clinical trials.
Collapse
Affiliation(s)
- Arianna Sala
- grid.4714.60000 0004 1937 0626Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,grid.15496.3f0000 0001 0439 0892Vita-Salute San Raffaele University, Milan, Italy ,grid.18887.3e0000000417581884In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Agneta Nordberg
- grid.4714.60000 0004 1937 0626Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,grid.24381.3c0000 0000 9241 5705Theme Aging, The Aging Brain, Karolinska University Hospital, Stockholm, Sweden
| | - Elena Rodriguez-Vieitez
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
| | | |
Collapse
|
18
|
Bubu OM, Umasabor-Bubu OQ, Turner AD, Parekh A, Mullins A, Kam K, Birckbichler M, Fahad M, Mbah AK, Williams NJ, Rapoport DM, de Leon M, Jean-Louis G, Ayappa I, Varga AW, Osorio RS. Self-reported obstructive sleep apnea, amyloid and tau burden, and Alzheimer's disease time-dependent progression. Alzheimers Dement 2020; 17:10.1002/alz.12184. [PMID: 33090679 PMCID: PMC8026765 DOI: 10.1002/alz.12184] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 07/19/2020] [Accepted: 08/11/2020] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Obstructive sleep apnea (OSA) is associated with Alzheimer's disease (AD) biomarkers in cognitively normal (CN) and mild cognitive impaired (MCI) participants. However, independent and combined effects of OSA, amyloid beta (Aβ) and tau-accumulation on AD time-dependent progression risk is unclear. METHODS Study participants grouped by biomarker profile, as described by the A/T/N scheme, where "A" refers to aggregated Aβ, "T" aggregated tau, and "N" to neurodegeneration, included 258 CN (OSA-positive [OSA+] [A+TN+ n = 10, A+/TN- n = 6, A-/TN+ n = 10, A-/TN- n = 6 and OSA-negative [OSA-] [A+TN+ n = 84, A+/TN- n = 11, A-/TN+ n = 96, A-/TN- n = 36]) and 785 MCI (OSA+ [A+TN+ n = 35, A+/TN- n = 15, A-/TN+ n = 25, A-/TN- n = 16] and OSA- [A+TN+ n = 388, A+/TN- n = 28, A-/TN+ n = 164, A-/TN- n = 114]) older-adults from the Alzheimer's Disease Neuroimaging Initiative cohort. Cox proportional hazards regression models estimated the relative hazard of progression from CN-to-MCI and MCI-to-AD, among baseline OSA CN and MCI patients, respectively. Multi-level logistic mixed-effects models with random intercept and slope investigated the synergistic associations of self-reported OSA, Aβ, and tau burden with prospective cognitive decline. RESULTS Independent of TN-status (CN and MCI), OSA+/Aβ+ participants were approximately two to four times more likely to progress to MCI/AD (P < .001) and progressed 6 to 18 months earlier (P < .001), compared to other participants combined (ie, OSA+/Aβ-, OSA-/Aβ+, and OSA-/Aβ-). Notably, OSA+/Aβ- versus OSA-/Aβ- (CN and MCI) and OSA+/TN- versus OSA-/TN- (CN) participants showed no difference in the risk and time-to-MCI/AD progression. Mixed effects models demonstrated OSA synergism with Aβ (CN and MCI [β = 1.13, 95% confidence interval (CI), 0.74 to 1.52, and β = 1.18, 95%CI, 0.82 to 1.54]) respectively, and with tau (MCI [β = 1.31, 95% CI, 0.87 to 1.47]), P < .001 for all. DISCUSSION OSA acts in synergism with Aβ and with tau, and all three acting together result in synergistic neurodegenerative mechanisms especially as Aβ and tau accumulation becomes increasingly abnormal, thus leading to shorter progression time to MCI/AD in CN and MCI-OSA patients, respectively.
Collapse
Affiliation(s)
- Omonigho M. Bubu
- Center for Sleep and Brain Health, Department of
Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
- Center for Healthful Behavior Change, Department of
Population Health, New York Grossman School of Medicine, New York, USA
| | - Ogie Q. Umasabor-Bubu
- Department of Epidemiology and Infection Control, State
University New York Downstate Medical Center, Brooklyn, NY, USA
| | - Arlener D Turner
- Center for Sleep and Brain Health, Department of
Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Ankit Parekh
- Division of Pulmonary, Critical Care and Sleep Medicine at
the Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anna Mullins
- Division of Pulmonary, Critical Care and Sleep Medicine at
the Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Korey Kam
- Division of Pulmonary, Critical Care and Sleep Medicine at
the Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Mukhtar Fahad
- Department of Epidemiology and Biostatistics, College of
Public Health, University of South Florida, Tampa, FL, USA
| | - Alfred K Mbah
- Department of Epidemiology and Biostatistics, College of
Public Health, University of South Florida, Tampa, FL, USA
| | - Natasha J. Williams
- Center for Healthful Behavior Change, Department of
Population Health, New York Grossman School of Medicine, New York, USA
| | - David M. Rapoport
- Division of Pulmonary, Critical Care and Sleep Medicine at
the Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mony de Leon
- Brain Health Imaging Institute, Department of Radiology,
Weill Cornell Medicine, New York, NY, USA
| | - Girardin Jean-Louis
- Center for Healthful Behavior Change, Department of
Population Health, New York Grossman School of Medicine, New York, USA
| | - Indu Ayappa
- Division of Pulmonary, Critical Care and Sleep Medicine at
the Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrew W. Varga
- Division of Pulmonary, Critical Care and Sleep Medicine at
the Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ricardo S. Osorio
- Center for Sleep and Brain Health, Department of
Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
- Nathan S. Kline Institute for Psychiatric Research,
Orangeburg, New York, USA
| |
Collapse
|
19
|
Toledo JB, Habes M, Sotiras A, Bjerke M, Fan Y, Weiner MW, Shaw LM, Davatzikos C, Trojanowski JQ. APOE Effect on Amyloid-β PET Spatial Distribution, Deposition Rate, and Cut-Points. J Alzheimers Dis 2020; 69:783-793. [PMID: 31127775 DOI: 10.3233/jad-181282] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
There are conflicting results regarding how APOE genotype, the strongest genetic risk factor for Alzheimer's disease (AD), influences spatial and longitudinal amyloid-β (Aβ) deposition and its impact on the selection of biomarker cut-points. In our study, we sought to determine the impact of APOE genotype on cross-sectional and longitudinal florbetapir positron emission tomography (PET) amyloid measures and its impact in classification of patients and interpretation of clinical cohort results. We included 1,019 and 1,072 Alzheimer's Disease Neuroimaging Initiative participants with cerebrospinal fluid Aβ1 - 42 and florbetapir PET values, respectively. 623 of these subjects had a second florbetapir PET scans two years after the baseline visit. We evaluated the effect of APOE genotype on Aβ distribution pattern, pathological biomarker cut-points, cross-sectional clinical associations with Aβ load, and longitudinal Aβ deposition rate measured using florbetapir PET scans. 1) APOEɛ4 genotype influences brain amyloid deposition pattern; 2) APOEɛ4 genotype does not modify Aβ biomarker cut-points estimated using unsupervised mixture modeling methods if white matter and brainstem references are used (but not when cerebellum is used as a reference); 3) findings of large differences in Aβ biomarker value differences based on APOE genotype are due to increased probability of having AD neuropathology and are most significant in mild cognitive impairment subjects; and 4) APOE genotype and age (but not gender) were associated with increased Aβ deposition rate. APOEɛ4 carrier status affects rate and location of brain Aβ deposition but does not affect choice of biomarker cut-points if adequate references are selected for florbetapir PET processing.
Collapse
Affiliation(s)
- Jon B Toledo
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Neurology, Houston Methodist Hospital, Houston, TX, USA
| | - Mohamad Habes
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Aristeidis Sotiras
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.,Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Maria Bjerke
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Yong Fan
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael W Weiner
- Department of Radiology, Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco, San Francisco, CA, USA
| | - Leslie M Shaw
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | |
Collapse
|
20
|
Bjorkli C, Sandvig A, Sandvig I. Bridging the Gap Between Fluid Biomarkers for Alzheimer's Disease, Model Systems, and Patients. Front Aging Neurosci 2020; 12:272. [PMID: 32982716 PMCID: PMC7492751 DOI: 10.3389/fnagi.2020.00272] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Accepted: 08/06/2020] [Indexed: 12/12/2022] Open
Abstract
Alzheimer’s disease (AD) is a debilitating neurodegenerative disease characterized by the accumulation of two proteins in fibrillar form: amyloid-β (Aβ) and tau. Despite decades of intensive research, we cannot yet pinpoint the exact cause of the disease or unequivocally determine the exact mechanism(s) underlying its progression. This confounds early diagnosis and treatment of the disease. Cerebrospinal fluid (CSF) biomarkers, which can reveal ongoing biochemical changes in the brain, can help monitor developing AD pathology prior to clinical diagnosis. Here we review preclinical and clinical investigations of commonly used biomarkers in animals and patients with AD, which can bridge translation from model systems into the clinic. The core AD biomarkers have been found to translate well across species, whereas biomarkers of neuroinflammation translate to a lesser extent. Nevertheless, there is no absolute equivalence between biomarkers in human AD patients and those examined in preclinical models in terms of revealing key pathological hallmarks of the disease. In this review, we provide an overview of current but also novel AD biomarkers and how they relate to key constituents of the pathological cascade, highlighting confounding factors and pitfalls in interpretation, and also provide recommendations for standardized procedures during sample collection to enhance the translational validity of preclinical AD models.
Collapse
Affiliation(s)
- Christiana Bjorkli
- Sandvig Group, Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Axel Sandvig
- Sandvig Group, Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway.,Institute of Neuromedicine and Movement Science, Department of Neurology, St. Olavs Hospital, Trondheim, Norway.,Department of Pharmacology and Clinical Neurosciences, Division of Neuro, Head, and Neck, University Hospital of Umeå, Umeå, Sweden
| | - Ioanna Sandvig
- Sandvig Group, Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| |
Collapse
|
21
|
Guo T, Korman D, La Joie R, Shaw LM, Trojanowski JQ, Jagust WJ, Landau SM. Normalization of CSF pTau measurement by Aβ 40 improves its performance as a biomarker of Alzheimer's disease. Alzheimers Res Ther 2020; 12:97. [PMID: 32799929 PMCID: PMC7429887 DOI: 10.1186/s13195-020-00665-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 08/04/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Alzheimer's disease (AD)-related tauopathy can be measured with CSF phosphorylated tau (pTau) and tau PET. We aim to investigate the associations between these measurements and their relative ability to predict subsequent disease progression. METHODS In 219 cognitively unimpaired and 122 impaired Alzheimer's Disease Neuroimaging Initiative participants with concurrent amyloid-β (Aβ) PET (18F-florbetapir or 18F-florbetaben), 18F-flortaucipir (FTP) PET, CSF measurements, structural MRI, and cognition, we examined inter-relationships between these biomarkers and their predictions of subsequent FTP and cognition changes. RESULTS The use of a CSF pTau/Aβ40 ratio eliminated positive associations we observed between CSF pTau alone and CSF Aβ42 in the normal Aβ range likely reflecting individual differences in CSF production rather than pathology. Use of the CSF pTau/Aβ40 ratio also increased expected associations with Aβ PET, FTP PET, hippocampal volume, and cognitive decline compared to pTau alone. In Aβ+ individuals, abnormal CSF pTau/Aβ40 only individuals (26.7%) were 4 times more prevalent (p < 0.001) than abnormal FTP only individuals (6.8%). Furthermore, among individuals on the AD pathway, CSF pTau/Aβ40 mediates the association between Aβ PET and FTP PET accumulation, but FTP PET is more closely linked to subsequent cognitive decline than CSF pTau/Aβ40. CONCLUSIONS Together, these findings suggest that CSF pTau/Aβ40 may be a superior measure of tauopathy compared to CSF pTau alone, and CSF pTau/Aβ40 enables detection of tau accumulation at an earlier stage than FTP among Aβ+ individuals.
Collapse
Affiliation(s)
- Tengfei Guo
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA.
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
| | - Deniz Korman
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
| | - Renaud La Joie
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| |
Collapse
|
22
|
Guo T, Shaw LM, Trojanowski JQ, Jagust WJ, Landau SM. Association of CSF Aβ, amyloid PET, and cognition in cognitively unimpaired elderly adults. Neurology 2020; 95:e2075-e2085. [PMID: 32759202 DOI: 10.1212/wnl.0000000000010596] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 04/28/2020] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE To compare CSF β-amyloid (Aβ) and florbetapir PET measurements in cognitively unimpaired (CU) elderly adults in order to detect the earliest abnormalities and compare their predictive effect for cognitive decline. METHODS A total of 259 CU individuals were categorized as abnormal (+) or normal (-) on CSF Aβ1-42/Aβ1-40 analyzed with mass spectrometry and Aβ PET measured with 18F-florbetapir. Simultaneous longitudinal measurements of CSF and PET were compared for 39 individuals who were unambiguously Aβ-negative at baseline (CSF-/PET-). We also examined the relationship between baseline CSF/PET group membership and longitudinal changes in CSF Aβ, Aβ PET, and cognition. RESULTS The proportions of individuals in each discordant group were similar (8.1% CSF+/PET- and 7.7% CSF-/PET+). Among baseline Aβ-negative (CSF-/PET-) individuals with longitudinal CSF and PET measurements, a larger proportion subsequently worsened on CSF Aβ (odds ratio 4 [95% confidence interval (CI) 1.1, 22.1], p = 0.035) than Aβ PET over 3.5 ± 1.0 years. Compared to CSF-/PET- individuals, CSF+/PET- individuals had faster (estimate 0.009 [95% CI 0.005, 0.013], p < 0.001) rates of Aβ PET accumulation over 4.4 ± 1.7 years, while CSF-/PET+ individuals had faster (estimate -0.492 [95% CI -0.861, -0.123], p = 0.01) rates of cognitive decline over 4.5 ± 1.9 years. CONCLUSIONS The proportions of discordant PET and CSF Aβ-positive individuals were similar cross-sectionally. However, unambiguously Aβ-negative (CSF-/PET-) individuals are more likely to show subsequent worsening on CSF than PET, supporting the idea that CSF detects the earliest Aβ changes. In discordant cases, only PET abnormality predicted cognitive decline, suggesting that abnormal Aβ PET changes are a later phenomenon in cognitively normal individuals.
Collapse
Affiliation(s)
- Tengfei Guo
- From the Helen Wills Neuroscience Institute (T.G., W.J.J., S.M.L.), University of California; Molecular Biophysics and Integrated Bioimaging (T.G., W.J.J., S.M.L.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia.
| | - Leslie M Shaw
- From the Helen Wills Neuroscience Institute (T.G., W.J.J., S.M.L.), University of California; Molecular Biophysics and Integrated Bioimaging (T.G., W.J.J., S.M.L.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - John Q Trojanowski
- From the Helen Wills Neuroscience Institute (T.G., W.J.J., S.M.L.), University of California; Molecular Biophysics and Integrated Bioimaging (T.G., W.J.J., S.M.L.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - William J Jagust
- From the Helen Wills Neuroscience Institute (T.G., W.J.J., S.M.L.), University of California; Molecular Biophysics and Integrated Bioimaging (T.G., W.J.J., S.M.L.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Susan M Landau
- From the Helen Wills Neuroscience Institute (T.G., W.J.J., S.M.L.), University of California; Molecular Biophysics and Integrated Bioimaging (T.G., W.J.J., S.M.L.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | | |
Collapse
|
23
|
Yu H, Wang Y, Zeng D. Sparse Nonparametric Regression With Regularized Tensor Product Kernel. Stat (Int Stat Inst) 2020; 9:e300. [PMID: 33824723 PMCID: PMC8021131 DOI: 10.1002/sta4.300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 06/23/2020] [Indexed: 11/09/2022]
Abstract
With growing interest to use black-box machine learning for complex data with many feature variables, it is critical to obtain a prediction model that only depends on a small set of features to maximize generalizability. Therefore, feature selection remains to be an important and challenging problem in modern applications. Most of existing methods for feature selection are based on either parametric or semiparametric models, so the resulting performance can severely suffer from model misspecification when high-order nonlinear interactions among the features are present. A very limited number of approaches for nonparametric feature selection were proposed, but they are computationally intensive and may not even converge. In this paper, we propose a novel and computationally efficient approach for nonparametric feature selection in regression field based on a tensor-product kernel function over the feature space. The importance of each feature is governed by a parameter in the kernel function which can be efficiently computed iteratively from a modified alternating direction method of multipliers (ADMM) algorithm. We prove the oracle selection property of the proposed method. Finally, we demonstrate the superior performance of our approach compared to existing methods via simulation studies and application to the prediction of Alzheimer's disease.
Collapse
Affiliation(s)
- Hang Yu
- Department of Statistics and Operation Research, University of North Carolina at Chapel Hill, North Carolina, United State
| | - Yuanjia Wang
- Department of Biostatistics, Mailman School of Public Health, Columbia University, United State
| | - Donglin Zeng
- Department of Biostatistics, University of North Carolina at Chapel Hill, North Carolina, United State
| |
Collapse
|
24
|
Guo T, Landau SM, Jagust WJ. Detecting earlier stages of amyloid deposition using PET in cognitively normal elderly adults. Neurology 2020; 94:e1512-e1524. [PMID: 32188766 PMCID: PMC7251521 DOI: 10.1212/wnl.0000000000009216] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 11/14/2019] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To examine the feasibility of using cross-sectional PET to identify cognitive decliners among β-amyloid (Aβ)-negative cognitively normal (CN) elderly adults. METHODS We determined the highest Aβ-affected region by ranking baseline and accumulation rates of florbetapir-PET regions in 355 CN elderly adults using 18F-florbetapir-PET from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The banks of the superior temporal sulcus (BANKSSTS) were found as the highest Aβ-affected region, and Aβ positivity in this region was defined as above the lowest boundary of BANKSSTS standardized uptake value ratio of Aβ+ (ADNI-defined COMPOSITE region) CN individuals. The entire CN cohort was divided as follows: stage 0, BANKSSTS-COMPOSITE-; stage 1, BANKSSTS+COMPOSITE-; and stage 2, BANKSSTS+COMPOSITE+. Linear mixed-effect (LME) models investigated subsequent longitudinal cognitive change, and 18F-flortaucipir (FTP)-PET was measured 4.8 ± 1.6 years later to track tau deposition. RESULTS LME analysis revealed that individuals in stage 1 (n = 64) and stage 2 (n = 99) showed 2.5 (p < 0.05) and 4.8 (p < 0.001) times faster memory decline, respectively, than those in stage 0 (n = 191) over >4 years of mean follow-up. Compared to stage 0, both stage 1 (p < 0.05) and stage 2 (p < 0.001) predicted higher FTP in entorhinal cortex. CONCLUSIONS Nominally Aβ- CN individuals with high Aβ in BANKSSTS are at increased risk of cognitive decline, probably showing an earlier stage of Aβ deposition. Our findings may help elucidate the association between brain Aβ accumulation and cognition in Aβ- CN cohorts. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in elderly CN individuals those with high PET-identified superior temporal sulcus Aβ burden have an increased risk of cognitive decline.
Collapse
Affiliation(s)
- Tengfei Guo
- From the Helen Wills Neuroscience Institute (T.G., S.M.L., W.J.J.), University of California; and Molecular Biophysics and Integrated Bioimaging (T.G., S.M.L., W.J.J.), Lawrence Berkeley National Laboratory, CA.
| | - Susan M Landau
- From the Helen Wills Neuroscience Institute (T.G., S.M.L., W.J.J.), University of California; and Molecular Biophysics and Integrated Bioimaging (T.G., S.M.L., W.J.J.), Lawrence Berkeley National Laboratory, CA
| | - William J Jagust
- From the Helen Wills Neuroscience Institute (T.G., S.M.L., W.J.J.), University of California; and Molecular Biophysics and Integrated Bioimaging (T.G., S.M.L., W.J.J.), Lawrence Berkeley National Laboratory, CA
| |
Collapse
|
25
|
Lin SY, Lin KJ, Lin PC, Huang CC, Chang CC, Lee YC, Hsiao IT, Yen TC, Huang WS, Yang BH, Wang PN. Plasma amyloid assay as a pre-screening tool for amyloid positron emission tomography imaging in early stage Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2019; 11:111. [PMID: 31881963 PMCID: PMC6933740 DOI: 10.1186/s13195-019-0566-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Accepted: 12/05/2019] [Indexed: 11/10/2022]
Abstract
INTRODUCTION Due to the high cost and high failure rate of ascertaining amyloid positron emission tomography positivity (PET+) in patients with earlier stage Alzheimer's disease (AD), an effective pre-screening tool for amyloid PET scans is needed. METHODS Patients with mild cognitive impairment (n = 33, 24.2% PET+, 42% females, age 74.4 ± 7.5, MMSE 26.8 ± 1.9) and mild dementia (n = 19, 63.6% PET+, 36.3% females, age 73.0 ± 9.3, MMSE 22.6 ± 2.0) were recruited. Amyloid PET imaging, Apolipoprotein E (APOE) genotyping, and plasma amyloid β (Aβ)1-40, Aβ1-42, and total tau protein quantification by immunomagnetic reduction (IMR) method were performed. Receiver operating characteristics (ROC) analysis and Youden's index were performed to identify possible cut-off points, clinical sensitivities/specificities, and areas under the curve (AUCs). RESULTS Amyloid PET+ participants had lower plasma Aβ1-42 levels than amyloid PET-negative (PET-) subjects. APOE ε4 carriers had higher plasma Aβ1-42 than non-carriers. We developed an algorithm involving the combination of plasma Aβ1-42 and APOE genotyping. The success rate for detecting amyloid PET+ patients effectively increased from 42.3 to 70.4% among clinically suspected MCI and mild dementia patients. CONCLUSIONS Our results demonstrate the possibility of utilizing APOE genotypes in combination with plasma Aβ1-42 levels as a pre-screening tool for predicting the positivity of amyloid PET findings in early stage dementia patients.
Collapse
Affiliation(s)
- Szu-Ying Lin
- Department of Neurology, Taipei Municipal Gan-Dau Hospital, Taipei, Taiwan
| | - Kun-Ju Lin
- Department of Nuclear Medicine and Molecular Imaging Center, Linkou Chang Gung Memorial Hospital, Tao-Yuan, Taiwan. .,Healthy Aging Research Center and Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Tao-Yuan, Taiwan.
| | - Po-Chen Lin
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chin-Chang Huang
- Department of Neurology, Linkou Chang Gung Memorial Hospital and University, Tao-Yuan, Taiwan
| | - Chiung-Chih Chang
- Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Yi-Chung Lee
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan.,Brain Research Center, National Yang-Ming University, Taipei, Taiwan
| | - Ing-Tsung Hsiao
- Department of Nuclear Medicine and Molecular Imaging Center, Linkou Chang Gung Memorial Hospital, Tao-Yuan, Taiwan.,Healthy Aging Research Center and Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Tao-Yuan, Taiwan
| | - Tzu-Chen Yen
- Department of Nuclear Medicine and Molecular Imaging Center, Linkou Chang Gung Memorial Hospital, Tao-Yuan, Taiwan.,Healthy Aging Research Center and Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Tao-Yuan, Taiwan
| | - Wen-Sheng Huang
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Bang-Hung Yang
- Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Pei-Ning Wang
- Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan. .,Brain Research Center, National Yang-Ming University, Taipei, Taiwan. .,Aging and Health Research Center, National Yang-Ming University, Taipei, Taiwan. .,Division of General Neurology, Department of Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.
| |
Collapse
|
26
|
Carandini T, Arighi A, Sacchi L, Fumagalli GG, Pietroboni AM, Ghezzi L, Colombi A, Scarioni M, Fenoglio C, De Riz MA, Marotta G, Scarpini E, Galimberti D. Testing the 2018 NIA-AA research framework in a retrospective large cohort of patients with cognitive impairment: from biological biomarkers to clinical syndromes. ALZHEIMERS RESEARCH & THERAPY 2019; 11:84. [PMID: 31615545 PMCID: PMC6794758 DOI: 10.1186/s13195-019-0543-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 09/27/2019] [Indexed: 12/29/2022]
Abstract
Background According to the 2018 NIA-AA research framework, Alzheimer’s disease (AD) is not defined by the clinical consequences of the disease, but by its underlying pathology, measured by biomarkers. Evidence of both amyloid-β (Aβ) and phosphorylated tau protein (p-tau) deposition—assessed interchangeably with amyloid-positron emission tomography (PET) and/or cerebrospinal fluid (CSF) analysis—is needed to diagnose AD in a living person. Our aim was to test the new NIA-AA research framework in a large cohort of cognitively impaired patients to evaluate correspondence between the clinical syndromes and the underlying pathologic process testified by biomarkers. Methods We retrospectively analysed 628 subjects referred to our centre in suspicion of dementia, who underwent CSF analysis, together with neuropsychological assessment and neuroimaging, and were diagnosed with different neurodegenerative dementias according to current criteria, or as cognitively unimpaired. Subjects were classified considering CSF biomarkers, and the prevalence of normal, AD-continuum and non-AD profiles in each clinical syndrome was calculated. The positivity threshold of each CSF biomarker was first assessed by receiver operating characteristic analysis, using Aβ-positive/negative status as determined by amyloid-PET visual reads. The agreement between CSF and amyloid-PET data was also evaluated. Results Among patients with a clinical diagnosis of AD, 94.1% were in the AD-continuum, whereas 5.5% were classified as non-AD and 0.4% were normal. The AD-continuum profile was found also in 26.2% of frontotemporal dementia, 48.6% of Lewy body dementia, 25% of atypical parkinsonism and 44.7% of vascular dementia. Biomarkers’ profile did not differ in amnestic and not amnestic mild cognitive impairment. CSF Aβ levels and amyloid-PET tracer binding negatively correlated, and the concordance between the two Aβ biomarkers was 89%. Conclusions The examination of the 2018 NIA-AA research framework in our clinical setting revealed a good, but incomplete, correspondence between the clinical syndromes and the underlying pathologic process measured by CSF biomarkers. The AD-continuum profile resulted to be a sensitive, but non-specific biomarker with regard to the clinical AD diagnosis. CSF and PET Aβ biomarkers were found to be not perfectly interchangeable to quantify the Aβ burden, possibly because they measure different aspects of AD pathology.
Collapse
Affiliation(s)
- Tiziana Carandini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy. .,Dino Ferrari Center, University of Milan, Milan, Italy.
| | - Andrea Arighi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Luca Sacchi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Giorgio G Fumagalli
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy.,Department of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, Florence, Italy
| | - Anna M Pietroboni
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Laura Ghezzi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Annalisa Colombi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Marta Scarioni
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | | | - Milena A De Riz
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Giorgio Marotta
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy
| | - Elio Scarpini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| |
Collapse
|
27
|
Alcolea D, Pegueroles J, Muñoz L, Camacho V, López-Mora D, Fernández-León A, Le Bastard N, Huyck E, Nadal A, Olmedo V, Sampedro F, Montal V, Vilaplana E, Clarimón J, Blesa R, Fortea J, Lleó A. Agreement of amyloid PET and CSF biomarkers for Alzheimer's disease on Lumipulse. Ann Clin Transl Neurol 2019; 6:1815-1824. [PMID: 31464088 PMCID: PMC6764494 DOI: 10.1002/acn3.50873] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 07/26/2019] [Accepted: 08/02/2019] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE To determine the cutoffs that optimized the agreement between 18 F-Florbetapir positron emission tomography (PET) and Aβ1-42, Aβ1-40, tTau, pTau and their ratios measured in cerebrospinal fluid (CSF) on the LUMIPULSE G600II instrument, we quantified the levels of these four biomarkers in 94 CSF samples from participants of the Sant Pau Initiative on Neurodegeneration (SPIN cohort) using the Lumipulse G System with available 18 F-Florbetapir imaging. METHODS Participants had mild cognitive impairment (n = 35), AD dementia (n = 12), other dementias or neurodegenerative diseases (n = 41), or were cognitively normal controls (n = 6). Levels of Aβ1-42 were standardized to certified reference material. Amyloid scans were assessed visually and through automated quantification. We determined the cutoffs of CSF biomarkers that optimized their agreement with 18 F-Florbetapir PET and evaluated concordance between markers of the amyloid category. RESULTS Aβ1-42, tTau and pTau (but not Aβ1-40) and the ratios with Aβ1-42 had good diagnostic agreement with 18 F-Florbetapir PET. As a marker of amyloid pathology, the Aβ1-42/Aβ1-40 ratio had higher agreement and better correlation with amyloid PET than Aβ1-42 alone. INTERPRETATION CSF biomarkers measured with the Lumipulse G System show good agreement with amyloid imaging in a clinical setting with heterogeneous presentations of neurological disorders. Combination of Aβ1-42 with Aβ1-40 increases the agreement between markers of amyloid pathology.
Collapse
Affiliation(s)
- Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Jordi Pegueroles
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Laia Muñoz
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Valle Camacho
- Nuclear Medicine Department, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau,, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Diego López-Mora
- Nuclear Medicine Department, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau,, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Alejandro Fernández-León
- Nuclear Medicine Department, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau,, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Els Huyck
- Fujirebio Europe N.V., Gent, Belgium
| | | | | | - Frederic Sampedro
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Eduard Vilaplana
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Jordi Clarimón
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Rafael Blesa
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| |
Collapse
|
28
|
Müller EG, Edwin TH, Stokke C, Navelsaker SS, Babovic A, Bogdanovic N, Knapskog AB, Revheim ME. Amyloid-β PET-Correlation with cerebrospinal fluid biomarkers and prediction of Alzheimer´s disease diagnosis in a memory clinic. PLoS One 2019; 14:e0221365. [PMID: 31430334 PMCID: PMC6701762 DOI: 10.1371/journal.pone.0221365] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 08/05/2019] [Indexed: 01/11/2023] Open
Abstract
Background Alzheimer’s disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD. Objective To compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting. Methods We included 64 patients who had lumbar puncture and Aβ PET with 18F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ42), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results. Results Thirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ42 showed the highest correlation with 18F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. 18F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis. Conclusions The present study showed an excellent correlation of Aβ42 in CSF and 18F-Flutemetamol PET and the presented cut-off value for Aβ42 yields high sensitivity and specificity for 18F-Flutemetamol PET. 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis.
Collapse
Affiliation(s)
- Ebba Gløersen Müller
- Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- * E-mail:
| | - Trine Holt Edwin
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Caroline Stokke
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway
- Department of Life Science and Health, Oslo Metropolitan University, Oslo, Norway
| | | | - Almira Babovic
- Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Nenad Bogdanovic
- Department for Neurobiology, Caring Science and Society, Division of Clinical Geriatrics, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Anne Brita Knapskog
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Mona Elisabeth Revheim
- Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| |
Collapse
|
29
|
Bjerke M, Engelborghs S. Cerebrospinal Fluid Biomarkers for Early and Differential Alzheimer's Disease Diagnosis. J Alzheimers Dis 2019; 62:1199-1209. [PMID: 29562530 PMCID: PMC5870045 DOI: 10.3233/jad-170680] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
An accurate and early diagnosis of Alzheimer’s disease (AD) is important to select optimal patient care and is critical in current clinical trials targeting core AD neuropathological features. The past decades, much progress has been made in the development and validation of cerebrospinal fluid (CSF) biomarkers for the biochemical diagnosis of AD, including standardization and harmonization of (pre-) analytical procedures. This has resulted in three core CSF biomarkers for AD diagnostics, namely the 42 amino acid long amyloid-beta peptide (Aβ1-42), total tau protein (T-tau), and tau phosphorylated at threonine 181 (P-tau181). These biomarkers have been incorporated into research diagnostic criteria for AD and have an added value in the (differential) diagnosis of AD and related disorders, including mixed pathologies, atypical presentations, and in case of ambiguous clinical dementia diagnoses. The implementation of the CSF Aβ1-42/Aβ1-40 ratio in the core biomarker panel will improve the biomarker analytical variability, and will also improve early and differential AD diagnosis through a more accurate reflection of pathology. Numerous biomarkers are being investigated for their added value to the core AD biomarkers, aiming at the AD core pathological features like the amyloid mismetabolism, tau pathology, or synaptic or neuronal degeneration. Others aim at non-AD neurodegenerative, vascular or inflammatory hallmarks. Biomarkers are essential for an accurate identification of preclinical AD in the context of clinical trials with potentially disease-modifying drugs. Therefore, a biomarker-based early diagnosis of AD offers great opportunities for preventive treatment development in the near future.
Collapse
Affiliation(s)
- Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| |
Collapse
|
30
|
Timmers M, Tesseur I, Bogert J, Zetterberg H, Blennow K, Börjesson-Hanson A, Baquero M, Boada M, Randolph C, Tritsmans L, Van Nueten L, Engelborghs S, Streffer JR. Relevance of the interplay between amyloid and tau for cognitive impairment in early Alzheimer's disease. Neurobiol Aging 2019; 79:131-141. [PMID: 31055223 DOI: 10.1016/j.neurobiolaging.2019.03.016] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Revised: 03/08/2019] [Accepted: 03/25/2019] [Indexed: 01/23/2023]
Abstract
Amyloid β (Aβ) and tau are key hallmark features of Alzheimer's disease (AD) neuropathology. The interplay of Aβ and tau for cognitive impairment in early AD was examined with cross-sectional analysis, measured by cerebrospinal fluid biomarkers (Aβ1-42, total tau [t-tau], and phosphorylated tau [p-tau181P]), and on cognitive performance by the repeatable battery for assessment of neuropsychological status (RBANS). Participants (n = 246) included cognitively normal (Aβ-), mild cognitively impaired (Aβ-), preclinical AD (Aβ+), and prodromal AD (Aβ+). Overall, cognitive scores (RBANS total scale score) had a moderate negative correlation to t-tau (n = 246; r = -0.434; p < 0.001) and p-tau181P (r = -0.389; p < 0.001). When classified by Aβ status, this correlation to t-tau was applicable only in Aβ+ participants (n = 139; r = -0.451, p < 0.001) but not Aβ- participants (n = 107; r = 0.137, p = 0.16), with identical findings for p-tau. Both tau (p < 0.0001) and interaction of Aβ1-42 with tau (p = 0.006) affected RBANS, but not Aβ1-42 alone. Cognitive/memory performance correlated well with cerebrospinal fluid tau levels across early stages of AD, although the correlation is Aβ dependent.
Collapse
Affiliation(s)
- Maarten Timmers
- Janssen Research and Development, A Division of Janssen Pharmaceutica N.V., Beerse, Belgium; Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.
| | - Ina Tesseur
- Janssen Research and Development, A Division of Janssen Pharmaceutica N.V., Beerse, Belgium
| | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistery Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistery Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Anne Börjesson-Hanson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Sahlgrenska University Hospital, Mölndal, Sweden; Clinical Trials, Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Miquel Baquero
- Neurology Department, Hospital Universitari I Politecnic La Fe, Valencia, Spain
| | - Mercè Boada
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Christopher Randolph
- MedAvante-ProPhase, Hamilton, NJ, USA; Department of Neurology, Loyola University Medical Center, Maywood, IL, USA
| | - Luc Tritsmans
- Janssen Research and Development, A Division of Janssen Pharmaceutica N.V., Beerse, Belgium
| | - Luc Van Nueten
- Janssen Research and Development, A Division of Janssen Pharmaceutica N.V., Beerse, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium; Department of Neurology and Center for Neurosciences, UZ Brussel and Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Johannes Rolf Streffer
- Janssen Research and Development, A Division of Janssen Pharmaceutica N.V., Beerse, Belgium; Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| |
Collapse
|
31
|
Salvadó G, Molinuevo JL, Brugulat-Serrat A, Falcon C, Grau-Rivera O, Suárez-Calvet M, Pavia J, Niñerola-Baizán A, Perissinotti A, Lomeña F, Minguillon C, Fauria K, Zetterberg H, Blennow K, Gispert JD. Centiloid cut-off values for optimal agreement between PET and CSF core AD biomarkers. Alzheimers Res Ther 2019; 11:27. [PMID: 30902090 PMCID: PMC6429814 DOI: 10.1186/s13195-019-0478-z] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 02/27/2019] [Indexed: 01/22/2023]
Abstract
BACKGROUND The Centiloid scale has been developed to standardize measurements of amyloid PET imaging. Reference cut-off values of this continuous measurement enable the consistent operationalization of decision-making for multicentre research studies and clinical trials. In this study, we aimed at deriving reference Centiloid thresholds that maximize the agreement against core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers in two large independent cohorts. METHODS A total of 516 participants of the ALFA+ Study (N = 205) and ADNI (N = 311) underwent amyloid PET imaging ([18F]flutemetamol and [18F]florbetapir, respectively) and core AD CSF biomarker determination using Elecsys® tests. Tracer uptake was quantified in Centiloid units (CL). Optimal Centiloid cut-offs were sought that maximize the agreement between PET and dichotomous determinations based on CSF levels of Aβ42, tTau, pTau, and their ratios, using pre-established reference cut-off values. To this end, a receiver operating characteristic analysis (ROC) was conducted, and Centiloid cut-offs were calculated as those that maximized the Youden's J Index or the overall percentage agreement recorded. RESULTS All Centiloid cut-offs fell within the range of 25-35, except for CSF Aβ42 that rendered an optimal cut-off value of 12 CL. As expected, the agreement of tau/Aβ42 ratios was higher than that of CSF Aβ42. Centiloid cut-off robustness was confirmed even when established in an independent cohort and against variations of CSF cut-offs. CONCLUSIONS A cut-off of 12 CL matches previously reported values derived against postmortem measures of AD neuropathology. Together with these previous findings, our results flag two relevant inflection points that would serve as boundary of different stages of amyloid pathology: one around 12 CL that marks the transition from the absence of pathology to subtle pathology and another one around 30 CL indicating the presence of established pathology. The derivation of robust and generalizable cut-offs for core AD biomarkers requires cohorts with adequate representation of intermediate levels. TRIAL REGISTRATION ALFA+ Study, NCT02485730 ALFA PET Sub-study, NCT02685969.
Collapse
Affiliation(s)
- Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Anna Brugulat-Serrat
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER de Bioengeniería, Biomateriales y Nanomedicina, Madrid, Spain
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - Javier Pavia
- CIBER de Bioengeniería, Biomateriales y Nanomedicina, Madrid, Spain
- Nuclear Medicine Department, Hospital Clínic, Barcelona, Spain
- Instititut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | | | | | | | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER de Bioengeniería, Biomateriales y Nanomedicina, Madrid, Spain
| |
Collapse
|
32
|
Amyloid beta in nasal secretions may be a potential biomarker of Alzheimer's disease. Sci Rep 2019; 9:4966. [PMID: 30899050 PMCID: PMC6428828 DOI: 10.1038/s41598-019-41429-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Accepted: 03/08/2019] [Indexed: 12/31/2022] Open
Abstract
We investigated the level of amyloid beta (Aβ) in nasal secretions of patients with Alzheimer’s disease dementia (ADD) using interdigitated microelectrode (IME) biosensors and determined the predictive value of Aβ in nasal secretions for ADD diagnosis. Nasal secretions were obtained from 35 patients with ADD, 18 with cognitive decline associated with other neurological disorders (OND), and 26 cognitively unimpaired (CU) participants. Capacitance changes in IMEs were measured by capturing total Aβ (ΔCtAβ). After 4-(2-hydroxyethyl)-1-piperazinepropanesulfonic acid (EPPS) was injected, additional capacitance changes due to the smaller molecular weight Aβ oligomers disassembled from the higher molecular weight oligomeric Aβ were determined (ΔCoAβ). By dividing two values, the capacitance ratio (ΔCoAβ/ΔCtAβ) was determined and then normalized to the capacitance change index (CCI). The CCI was higher in the ADD group than in the OND (p = 0.040) and CU groups (p = 0.007). The accuracy of the CCI was fair in separating into the ADD and CU groups (area under the receiver operating characteristic curve = 0.718, 95% confidence interval = 0.591–0.845). These results demonstrate that the level of Aβ in nasal secretions increases in ADD and the detection of Aβ in nasal secretions using IME biosensors may be possible in predicting ADD.
Collapse
|
33
|
Perez SE, Miguel JC, He B, Malek-Ahmadi M, Abrahamson EE, Ikonomovic MD, Lott I, Doran E, Alldred MJ, Ginsberg SD, Mufson EJ. Frontal cortex and striatal cellular and molecular pathobiology in individuals with Down syndrome with and without dementia. Acta Neuropathol 2019; 137:413-436. [PMID: 30734106 PMCID: PMC6541490 DOI: 10.1007/s00401-019-01965-6] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 01/18/2019] [Accepted: 01/22/2019] [Indexed: 02/06/2023]
Abstract
Although, by age 40, individuals with Down syndrome (DS) develop amyloid-β (Aβ) plaques and tau-containing neurofibrillary tangles (NFTs) linked to cognitive impairment in Alzheimer's disease (AD), not all people with DS develop dementia. Whether Aβ plaques and NFTs are associated with individuals with DS with (DSD +) and without dementia (DSD -) is under-investigated. Here, we applied quantitative immunocytochemistry and fluorescent procedures to characterize NFT pathology using antibodies specific for tau phosphorylation (pS422, AT8), truncation (TauC3, MN423), and conformational (Alz50, MC1) epitopes, as well as Aβ and its precursor protein (APP) to frontal cortex (FC) and striatal tissue from DSD + to DSD - cases. Expression profiling of single pS422 labeled FC layer V and VI neurons was also determined using laser capture microdissection and custom-designed microarray analysis. Analysis revealed that cortical and striatal Aβ plaque burdens were similar in DSD + and DSD - cases. In both groups, most FC plaques were neuritic, while striatal plaques were diffuse. By contrast, FC AT8-positive NFTs and neuropil thread densities were significantly greater in DSD + compared to DSD -, while striatal NFT densities were similar between groups. FC pS422-positive and TauC3 NFT densities were significantly greater than Alz50-labeled NFTs in DSD + , but not DSD - cases. Putaminal, but not caudate pS422-positive NFT density, was significantly greater than TauC3-positive NFTs. In the FC, AT8 + pS422 + Alz50, TauC3 + pS422 + Alz50, pS422 + Alz50, and TauC3 + pS422 positive NFTs were more frequent in DSD + compared to DSD- cases. Single gene-array profiling of FC pS422 positive neurons revealed downregulation of 63 of a total of 864 transcripts related to Aβ/tau biology, glutamatergic, cholinergic, and monoaminergic metabolism, intracellular signaling, cell homeostasis, and cell death in DSD + compared DSD - cases. These observations suggest that abnormal tau aggregation plays a critical role in the development of dementia in DS.
Collapse
Affiliation(s)
- Sylvia E Perez
- Department of Neurobiology and Neurology, Barrow Neurological Institute, 350 W. Thomas St, Phoenix, AZ, 85013, USA
- School of Life Sciences, College of Liberal Arts and Sciences, Arizona State University, Tempe, AZ, 85287, USA
| | - Jennifer C Miguel
- Department of Neurobiology and Neurology, Barrow Neurological Institute, 350 W. Thomas St, Phoenix, AZ, 85013, USA
| | - Bin He
- Department of Neurobiology and Neurology, Barrow Neurological Institute, 350 W. Thomas St, Phoenix, AZ, 85013, USA
| | | | - Eric E Abrahamson
- Geriatric Research Education and Clinical Center, VA Pittsburgh Healthcare System, Pittsburgh, PA, 15213, USA
- Departments of Neurology and Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Milos D Ikonomovic
- Geriatric Research Education and Clinical Center, VA Pittsburgh Healthcare System, Pittsburgh, PA, 15213, USA
- Departments of Neurology and Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Ira Lott
- Departments of Pediatrics and Neurology, University of California, Irvine, CA, 92697, USA
| | - Eric Doran
- Departments of Pediatrics and Neurology, University of California, Irvine, CA, 92697, USA
| | - Melissa J Alldred
- Center for Dementia Research, Nathan Kline Institute, Orangeburg, NY, 10962, USA
- Departments of Psychiatry, NYU Neuroscience Institute, NYU Langone Medical Center, New York, NY, 10021, USA
| | - Stephen D Ginsberg
- Center for Dementia Research, Nathan Kline Institute, Orangeburg, NY, 10962, USA
- Departments of Psychiatry, NYU Neuroscience Institute, NYU Langone Medical Center, New York, NY, 10021, USA
- Departments of Neuroscience and Physiology, The NYU Neuroscience Institute, NYU Langone Medical Center, New York, NY, 10021, USA
| | - Elliott J Mufson
- Department of Neurobiology and Neurology, Barrow Neurological Institute, 350 W. Thomas St, Phoenix, AZ, 85013, USA.
| |
Collapse
|
34
|
Kim HJ, Lim TS, Lee SM, Kim TS, Kim Y, An YS, Youn YC, Park SA, Chang J, Moon SY. Cerebrospinal Fluid Levels of β-Amyloid 40 and β-Amyloid 42 are Proportionately Decreased in Amyloid Positron-Emission Tomography Negative Idiopathic Normal-Pressure Hydrocephalus Patients. J Clin Neurol 2019; 15:353-359. [PMID: 31286708 PMCID: PMC6620439 DOI: 10.3988/jcn.2019.15.3.353] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Revised: 02/14/2019] [Accepted: 02/14/2019] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND AND PURPOSE Cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) could be misleading in idiopathic normal-pressure hydrocephalus (iNPH). We therefore investigated the CSF biomarkers in 18F-florbetaben amyloid-negative positron-emission tomography (PET) [amyloid PET(-)] iNPH, amyloid-positive PET [amyloid PET(+)] AD, and cognitively normal (CN) subjects. METHODS Ten amyloid PET(+) AD patients (56.7±5.6 years old, mean±standard deviation), 10 amyloid PET(-) iNPH patients (72.8±4.5 years old), and 8 CN subjects (61.2±6.5 years old) were included. We measured the levels of β-amyloid (Aβ)40, Aβ42, total tau (t-tau) protein, and phosphorylated tau (p-tau) protein in the CSF using enzyme-linked immunosorbent assays. RESULTS The level of Aβ42 and the Aβ42/Aβ40 ratio in the CSF were significantly lower in AD than in iNPH or CN subjects. The Aβ40 level did not differ significantly between AD and iNPH (p=1.000), but it did between AD and CN subjects (p=0.032). The levels of both t-tau and p-tau were higher in AD than in iNPH or CN subjects. The levels of Aβ42, Aβ40, t-tau, and p-tau were lower in iNPH than in CN subjects, but there was no significant difference after controlling for age. CONCLUSIONS Our results suggest that the mechanism underlying low CSF Aβ levels differs between amyloid PET(-) iNPH and amyloid PET(+) AD subjects. The lower levels of all CSF biomarkers in iNPH patients might be due to reduced clearances from extracellular fluid and decreased brain metabolism of the periventricular zone in iNPH resulting from glymphatic dysfunction.
Collapse
Affiliation(s)
- Hyun Jae Kim
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea
| | - Tae Sung Lim
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea
| | - Sun Min Lee
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea
| | - Tae Sung Kim
- Department of Brain Science, Ajou University School of Medicine, Suwon, Korea
| | - Youngbin Kim
- Department of Biomedical Sciences, Ajou University School of Medicine, Suwon, Korea
| | - Young Sil An
- Department of Nuclear Medicine and Molecular Imaging, Ajou University School of Medicine, Suwon, Korea
| | - Young Chul Youn
- Department of Neurology, Chung-Ang University College of Medicine, Seoul, Korea
| | - Sun Ah Park
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea.,Department of Anatomy, Ajou University School of Medicine, Suwon, Korea
| | - Jaerak Chang
- Department of Brain Science, Ajou University School of Medicine, Suwon, Korea.,Department of Biomedical Sciences, Ajou University School of Medicine, Suwon, Korea.
| | - So Young Moon
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea.
| |
Collapse
|
35
|
Westwood S, Baird AL, Hye A, Ashton NJ, Nevado-Holgado AJ, Anand SN, Liu B, Newby D, Bazenet C, Kiddle SJ, Ward M, Newton B, Desai K, Tan Hehir C, Zanette M, Galimberti D, Parnetti L, Lleó A, Baker S, Narayan VA, van der Flier WM, Scheltens P, Teunissen CE, Visser PJ, Lovestone S. Plasma Protein Biomarkers for the Prediction of CSF Amyloid and Tau and [ 18F]-Flutemetamol PET Scan Result. Front Aging Neurosci 2018; 10:409. [PMID: 30618716 PMCID: PMC6297196 DOI: 10.3389/fnagi.2018.00409] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 11/28/2018] [Indexed: 01/01/2023] Open
Abstract
Background: Blood biomarkers may aid in recruitment to clinical trials of Alzheimer's disease (AD) modifying therapeutics by triaging potential trials participants for amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) Aβ and tau tests. Objective: To discover a plasma proteomic signature associated with CSF and PET measures of AD pathology. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics were performed in plasma from participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD, recruited to the Amsterdam Dementia Cohort, stratified by CSF Tau/Aβ42 (n = 50). Technical replication and independent validation were performed by immunoassay in plasma from SCD, MCI, and AD participants recruited to the Amsterdam Dementia Cohort with CSF measures (n = 100), MCI participants enrolled in the GE067-005 study with [18F]-Flutemetamol PET amyloid measures (n = 173), and AD, MCI and cognitively healthy participants from the EMIF 500 study with CSF Aβ42 measurements (n = 494). Results: 25 discovery proteins were nominally associated with CSF Tau/Aβ42 (P < 0.05) with associations of ficolin-2 (FCN2), apolipoprotein C-IV and fibrinogen β chain confirmed by immunoassay (P < 0.05). In the GE067-005 cohort, FCN2 was nominally associated with PET amyloid (P < 0.05) replicating the association with CSF Tau/Aβ42. There were nominally significant associations of complement component 3 with PET amyloid, and apolipoprotein(a), apolipoprotein A-I, ceruloplasmin, and PPY with MCI conversion to AD (all P < 0.05). In the EMIF 500 cohort FCN2 was trending toward a significant relationship with CSF Aβ42 (P ≈ 0.05), while both A1AT and clusterin were nominally significantly associated with CSF Aβ42 (both P < 0.05). Conclusion: Associations of plasma proteins with multiple measures of AD pathology and progression are demonstrated. To our knowledge this is the first study to report an association of FCN2 with AD pathology. Further testing of the proteins in larger independent cohorts will be important.
Collapse
Affiliation(s)
- Sarah Westwood
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Alison L. Baird
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Abdul Hye
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kigndom
- Biomedical Research Unit for Dementia, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Nicholas J. Ashton
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kigndom
- Biomedical Research Unit for Dementia, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London, United Kingdom
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | | | - Sneha N. Anand
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Benjamine Liu
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Danielle Newby
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Chantal Bazenet
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kigndom
| | - Steven J. Kiddle
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, University of Cambridge, Cambridge, United Kingdom
| | - Malcolm Ward
- Proteomics Facility, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Ben Newton
- GE Healthcare Life Sciences Core Imaging, London, United Kingdom
| | - Keyur Desai
- Biosciences, GE Global Research, Niskayuna, NY, United States
| | | | - Michelle Zanette
- GE Healthcare Life Sciences Core Imaging, Marlborough, MA, United States
| | - Daniela Galimberti
- Neurodegenerative Diseases Unit, Centro Dino Ferrari, University of Milan, Milan, Italy
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Lucilla Parnetti
- Center for Memory Disorders and Laboratory of Clinical Neurochemistry, Neurology Clinic, University of Perugia, Perugia, Italy
| | - Alberto Lleó
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Susan Baker
- Janssen Neuroscience Research & Development, Titusville, NJ, United States
| | - Vaibhav A. Narayan
- Janssen Neuroscience Research & Development, Titusville, NJ, United States
| | - Wiesje M. van der Flier
- Department of Neurology, Alzheimer Centre, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, Netherlands
| | - Philip Scheltens
- Department of Neurology, Alzheimer Centre, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
| | - Charlotte E. Teunissen
- Department of Clinical Chemistry, Neurochemistry Lab and Biobank, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Simon Lovestone
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| |
Collapse
|
36
|
Avants BB, Hutchison RM, Mikulskis A, Salinas-Valenzuela C, Hargreaves R, Beaver J, Chiao P. Amyloid beta-positive subjects exhibit longitudinal network-specific reductions in spontaneous brain activity. Neurobiol Aging 2018; 74:191-201. [PMID: 30471630 DOI: 10.1016/j.neurobiolaging.2018.10.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 09/06/2018] [Accepted: 10/02/2018] [Indexed: 12/20/2022]
Abstract
Amyloid beta (Aβ) deposition and cognitive decline are key features of Alzheimer's disease. The relationship between Aβ status and changes in neuronal function over time, however, remains unclear. We evaluated the effect of baseline Aβ status on reference region spontaneous brain activity (SBA-rr) using resting-state functional magnetic resonance imaging and fluorodeoxyglucose positron emission tomography in patients with mild cognitive impairment. Patients (N = 62, [43 Aβ-positive]) from the Alzheimer's Disease Neuroimaging Initiative were divided into Aβ-positive and Aβ-negative groups via prespecified cerebrospinal fluid Aβ42 or 18F-florbetapir positron emission tomography standardized uptake value ratio cutoffs measured at baseline. We analyzed interaction of biomarker-confirmed Aβ status with SBA-rr change over a 2-year period using mixed-effects modeling. SBA-rr differences between Aβ-positive and Aβ-negative subjects increased significantly over time within subsystems of the default and visual networks. Changes exhibit an interaction with memory performance over time but were independent of glucose metabolism. Results reinforce the value of resting-state functional magnetic resonance imaging in evaluating Alzheimer''s disease progression and suggest spontaneous neuronal activity changes are concomitant with cognitive decline.
Collapse
Affiliation(s)
- Brian B Avants
- Biogen employee while completing work, 225 Binney Street, Cambridge, Massachusetts, 02142, USA.
| | | | - Alvydas Mikulskis
- Biogen employee while completing work, 225 Binney Street, Cambridge, Massachusetts, 02142, USA
| | | | | | - John Beaver
- Biogen, 225 Binney Street, Cambridge, Massachusetts, 02142, USA
| | - Ping Chiao
- Biogen, 225 Binney Street, Cambridge, Massachusetts, 02142, USA
| |
Collapse
|
37
|
Palmqvist S, Insel PS, Zetterberg H, Blennow K, Brix B, Stomrud E, Mattsson N, Hansson O. Accurate risk estimation of β-amyloid positivity to identify prodromal Alzheimer's disease: Cross-validation study of practical algorithms. Alzheimers Dement 2018; 15:194-204. [PMID: 30365928 PMCID: PMC6374284 DOI: 10.1016/j.jalz.2018.08.014] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 06/14/2018] [Accepted: 08/21/2018] [Indexed: 12/21/2022]
Abstract
INTRODUCTION The aim was to create readily available algorithms that estimate the individual risk of β-amyloid (Aβ) positivity. METHODS The algorithms were tested in BioFINDER (n = 391, subjective cognitive decline or mild cognitive impairment) and validated in Alzheimer's Disease Neuroimaging Initiative (n = 661, subjective cognitive decline or mild cognitive impairment). The examined predictors of Aβ status were demographics; cognitive tests; white matter lesions; apolipoprotein E (APOE); and plasma Aβ42/Aβ40, tau, and neurofilament light. RESULTS Aβ status was accurately estimated in BioFINDER using age, 10-word delayed recall or Mini-Mental State Examination, and APOE (area under the receiver operating characteristics curve = 0.81 [0.77-0.85] to 0.83 [0.79-0.87]). When validated, the models performed almost identical in Alzheimer's Disease Neuroimaging Initiative (area under the receiver operating characteristics curve = 0.80-0.82) and within different age, subjective cognitive decline, and mild cognitive impairment populations. Plasma Aβ42/Aβ40 improved the models slightly. DISCUSSION The algorithms are implemented on http://amyloidrisk.com where the individual probability of being Aβ positive can be calculated. This is useful in the workup of prodromal Alzheimer's disease and can reduce the number needed to screen in Alzheimer's disease trials.
Collapse
Affiliation(s)
- Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Neurology, Skåne University Hospital, Lund, Sweden.
| | - Philip S Insel
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, United Kingdom; UK Dementia Research Institute at UCL, London, United Kingdom
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | | | | | - Niklas Mattsson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden.
| |
Collapse
|
38
|
Ashton NJ, Schöll M, Heurling K, Gkanatsiou E, Portelius E, Höglund K, Brinkmalm G, Hye A, Blennow K, Zetterberg H. Update on biomarkers for amyloid pathology in Alzheimer's disease. Biomark Med 2018; 12:799-812. [DOI: 10.2217/bmm-2017-0433] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
At the center of Alzheimer's disease pathogenesis is the aberrant aggregation of amyloid-β (Aβ) into oligomers, fibrils and plaques. Effective monitoring of Aβ deposition directly in patients is essential to assist anti-Aβ therapeutics in target engagement and participant selection. In the advent of approved anti-Aβ therapeutics, biomarkers will become of fundamental importance in initiating treatments having disease modifying effects at the earliest stage. Two well-established Aβ biomarkers are widely utilized: Aβ-binding ligands for positron emission tomography and immunoassays to measure Aβ42 in cerebrospinal fluid. In this review, we will discuss the current clinical, diagnostic and research state of biomarkers for Aβ pathology. Furthermore, we will explore the current application of blood-based markers to assess Aβ pathology.
Collapse
Affiliation(s)
- Nicholas J Ashton
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK
- Wallenberg Centre for Molecular & Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry & Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Michael Schöll
- Wallenberg Centre for Molecular & Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Kerstin Heurling
- Wallenberg Centre for Molecular & Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Eleni Gkanatsiou
- Department of Psychiatry & Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Erik Portelius
- Department of Psychiatry & Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kina Höglund
- Department of Psychiatry & Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Gunnar Brinkmalm
- Department of Psychiatry & Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Abdul Hye
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK
| | - Kaj Blennow
- Department of Psychiatry & Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry & Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| |
Collapse
|
39
|
Abstract
PURPOSE OF REVIEW To present the new PET markers that could become in the coming years, relevant to advanced clinical approaches to dementia diagnosis, drug trials, and treatment strategies and discuss their advantages and limitations. RECENT FINDINGS The most advanced new PET tracers are the markers of the amyloid plaques, the τ compounds and the tracers of the translocator protein as markers of neuroinflammation. The main advantages but also the weaknesses of each of these markers are discussed. The main pitfall remains the heterogeneity of the available results that cast doubt to a rapid introduction of these new ligands in clinical practice. SUMMARY With the advent of biomarkers in clinical management and findings of molecular neuroimaging studies in the evaluation of patients with suspected dementia, the impact of functional neuroimaging has increased considerably these last years and has been integrated into many clinical guidelines in the field of dementia. In addition to conventional single PET brain perfusion and dopaminergic neurotransmission, 18F-fluorodeoxyglucose (18F-FDG) PET is used in advanced diagnosis procedures. Furthermore, new tracers are being developed to quantify key neuropathological features in the brain tissue as highly specific diagnosis is crucial to comply with the global medical and public health objectives in this domain. A strategic road map for further developments, adapted from the approach to cancer biomarkers, should be proposed so as to optimize the rationale of the PET-based molecular diagnosis of Alzheimer's disease and related disorders.
Collapse
|
40
|
Nobili F, Cagnin A, Calcagni ML, Chincarini A, Guerra UP, Morbelli S, Padovani A, Paghera B, Pappatà S, Parnetti L, Sestini S, Schillaci O. Emerging topics and practical aspects for an appropriate use of amyloid PET in the current Italian context. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF RADIOPHARMACEUTICAL CHEMISTRY AND BIOLOGY 2018; 63:83-92. [PMID: 29697220 DOI: 10.23736/s1824-4785.18.03069-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
In May 2017 some representatives of the Italian nuclear medicine and neurological communities spontaneously met to discuss the issues emerged during the first two years of routine application of amyloid PET with fluorinated radiopharmaceuticals in the real world. The limitations of a binary classification of scans, the possibility to obtain early images as a surrogate marker of regional cerebral bloos flow, the need for (semi-)quantification and, thus, the opportunity of ranking brain amyloidosis, the correlation with Aβ42 levels in the cerebrospinal fluid, the occurrence and biological meaning of uncertain/boderline scans, the issue of incidental amyloidosis, the technical pittfalls leading to false negative/positive results, the position of the tool in the diagnostic flow-chart in the national reality, are the main topics that have been discussed. Also, a card to justify the examination to be filled by the dementia specialist and a card for the nuclear medicine physician to report the exam in detail have been approved and are available in the web, which should facilitate the creation of a national register, as previewed by the 2015 intersocietal recommendation on the use of amyloid PET in Italy. The content of this discussion could stimulate both public institutions and companies to support further research on these topics.
Collapse
Affiliation(s)
- Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa and Neurology Clinic, San Martino Polyclinic Hospital, Genoa, Italy -
| | - Annachiara Cagnin
- Department of Neurosciences (DNS), University of Padua, Padua, Italy.,San Camillo IRCCS Hospital, Venice, Italy
| | - Maria L Calcagni
- Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.,Università Cattolica del Sacro Cuore, Rome, Italy
| | - Andrea Chincarini
- National Institute for Nuclear Physics (INFN), Genoa Section, Genoa, Italy
| | - Ugo P Guerra
- Unit of Nuclear Medicine, Poliambulanza Fundation, Brescia, Italy
| | - Silvia Morbelli
- Unit of Nuclear Medicine, Department of Health Sciences (DISSAL), Polyclinic San Martino Hospital, University of Genoa, Genoa, Italy
| | - Alessandro Padovani
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.,Neurology Clinic, Spedali Civili, Brescia, Italy
| | - Barbara Paghera
- Unit of Nuclear Medicine, ASST-Spedali Civili, University of Brescia, Brescia, Italy
| | - Sabina Pappatà
- Institute of Biostructure and Bioimaging, National Research Council, Naples, Italy
| | - Lucilla Parnetti
- Center for Memory Disorders, Laboratory of Clinical Neurochemistry, Neurology Clinic, University of Perugia, Perugia, Italy
| | - Stelvio Sestini
- Unit of Nuclear Medicine, Department of Diagnostic Imaging, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy
| | - Orazio Schillaci
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.,IRCCS Neuromed, Rome, Italy
| |
Collapse
|
41
|
Illán-Gala I, Pegueroles J, Montal V, Vilaplana E, Carmona-Iragui M, Alcolea D, Dickerson BC, Sánchez-Valle R, de Leon MJ, Blesa R, Lleó A, Fortea J. Challenges associated with biomarker-based classification systems for Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2018; 10:346-357. [PMID: 30175226 PMCID: PMC6114028 DOI: 10.1016/j.dadm.2018.03.004] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
INTRODUCTION We aimed to evaluate the consistency of the A/T/N classification system. METHODS We included healthy controls, mild cognitive impairment, and dementia patients from Alzheimer's disease Neuroimaging Initiative. We assessed subject classification consistency with different biomarker combinations and the agreement and correlation between biomarkers. RESULTS Subject classification discordance ranged from 12.2% to 44.5% in the whole sample; 17.3%-46.4% in healthy controls; 11.9%-46.5% in mild cognitive impairment, and 1%-35.7% in dementia patients. Amyloid, but not neurodegeneration biomarkers, showed good agreement both in the whole sample and in the clinical subgroups. Amyloid biomarkers were correlated in the whole sample, but not along the Alzheimer's disease continuum (as defined by a positive amyloid positron emission tomography). Neurodegeneration biomarkers were poorly correlated both in the whole sample and along the Alzheimer's disease continuum. The relationship between biomarkers was stage-dependent. DISCUSSION Our findings suggest that the current A/T/N classification system does not achieve the required consistency to be used in the clinical setting.
Collapse
Affiliation(s)
- Ignacio Illán-Gala
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Jordi Pegueroles
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Victor Montal
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Eduard Vilaplana
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - María Carmona-Iragui
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Daniel Alcolea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Bradford C. Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Massachusetts Alzheimer's Disease Research Center, Boston, MA, USA
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Department of Neurology, Hospital Clínic, Institut d'Investigació Biomèdica August Pi i Sunyer, Barcelona, Spain
| | - Mony J. de Leon
- Centre for Brain Health, Department of Psychiatry, New York University School of Medicine, New York, NY, USA
| | - Rafael Blesa
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Alberto Lleó
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Juan Fortea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| |
Collapse
|
42
|
Shimizu S, Hirose D, Hatanaka H, Takenoshita N, Kaneko Y, Ogawa Y, Sakurai H, Hanyu H. Role of Neuroimaging as a Biomarker for Neurodegenerative Diseases. Front Neurol 2018; 9:265. [PMID: 29720959 PMCID: PMC5915477 DOI: 10.3389/fneur.2018.00265] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 04/04/2018] [Indexed: 12/03/2022] Open
Abstract
It has recently been recognized that neurodegenerative diseases are caused by common cellular and molecular mechanisms including protein aggregation and inclusion body formation. Each type of neurodegenerative disease is characterized by the specific protein that aggregates. In these days, the pathway involved in protein aggregation has been elucidated. These are leading to approaches toward disease-modifying therapies. Neurodegenerative diseases are fundamentally diagnosed pathologically. Therefore, autopsy is essential for a definitive diagnosis of a neurodegenerative disease. However, recently, the development of various molecular brain imaging techniques have enabled pathological changes in the brain to be inferred even without autopsy. Some molecular imaging techniques are described as biomarker in diagnostic criteria of neurodegenerative disease. Magnetic resonance imaging (MRI), single photon emission computed tomography (SPECT), positron emission tomography (PET), and amyloid imaging are described in the diagnostic guidelines for Alzheimer’s disease in the National Institute on Aging-Alzheimer’s Association. MRI, dopamine transporter (DAT) imaging, and 123I-metaiodobenzyl-guanidine (MIBG) myocardial scintigraphy listed in the guidelines for consensus clinical diagnostic criteria for dementia with Lewy bodies are described as potential biomarkers. The Movement Disorder Society Progressive Supranuclear Palsy Study Group defined MRI, SPECT/PET, DAT imaging, and tau imaging as biomarkers. Other diagnostic criteria for neurodegenerative disease described neuroimaging findings as only characteristic finding, not as biomarker. In this review, we describe the role of neuroimaging as a potential biomarker for neurodegenerative diseases.
Collapse
Affiliation(s)
- Soichiro Shimizu
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Daisuke Hirose
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Hirokuni Hatanaka
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Naoto Takenoshita
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Yoshitsugu Kaneko
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Yusuke Ogawa
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Hirofumi Sakurai
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Haruo Hanyu
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| |
Collapse
|
43
|
Lawrence E, Vegvari C, Ower A, Hadjichrysanthou C, De Wolf F, Anderson RM. A Systematic Review of Longitudinal Studies Which Measure Alzheimer's Disease Biomarkers. J Alzheimers Dis 2018; 59:1359-1379. [PMID: 28759968 PMCID: PMC5611893 DOI: 10.3233/jad-170261] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Alzheimer’s disease (AD) is a progressive and fatal neurodegenerative disease, with no effective treatment or cure. A gold standard therapy would be treatment to slow or halt disease progression; however, knowledge of causation in the early stages of AD is very limited. In order to determine effective endpoints for possible therapies, a number of quantitative surrogate markers of disease progression have been suggested, including biochemical and imaging biomarkers. The dynamics of these various surrogate markers over time, particularly in relation to disease development, are, however, not well characterized. We reviewed the literature for studies that measured cerebrospinal fluid or plasma amyloid-β and tau, or took magnetic resonance image or fluorodeoxyglucose/Pittsburgh compound B-positron electron tomography scans, in longitudinal cohort studies. We summarized the properties of the major cohort studies in various countries, commonly used diagnosis methods and study designs. We have concluded that additional studies with repeat measures over time in a representative population cohort are needed to address the gap in knowledge of AD progression. Based on our analysis, we suggest directions in which research could move in order to advance our understanding of this complex disease, including repeat biomarker measurements, standardization and increased sample sizes.
Collapse
Affiliation(s)
- Emma Lawrence
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Carolin Vegvari
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Alison Ower
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | | | - Frank De Wolf
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.,Janssen Prevention Center, Leiden, The Netherlands
| | - Roy M Anderson
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| |
Collapse
|
44
|
Abstract
Alzheimer's disease (AD), the main form of dementia in the elderly, is the most common progressive neurodegenerative disease characterized by rapidly progressive cognitive dysfunction and behavior impairment. AD exhibits a considerable heritability and great advances have been made in approaches to searching the genetic etiology of AD. In AD genetic studies, methods have developed from classic linkage-based and candidate-gene-based association studies to genome-wide association studies (GWAS) and next generation sequencing (NGS). The identification of new susceptibility genes has provided deeper insights to understand the mechanisms underlying AD. In addition to searching novel genes associated with AD in large samples, the NGS technologies can also be used to shed light on the 'black matter' discovery even in smaller samples. The shift in AD genetics between traditional studies and individual sequencing will allow biomaterials of each patient as the central unit of genetic studies. This review will cover genetic findings in AD and consequences of AD genetic findings. Firstly, we will discuss the discovery of mutations in APP, PSEN1, PSEN2, APOE, and ADAM10. Then we will summarize and evaluate the information obtained from GWAS of AD. Finally, we will outline the efforts to identify rare variants associated with AD using NGS.
Collapse
|
45
|
Hansson O, Seibyl J, Stomrud E, Zetterberg H, Trojanowski JQ, Bittner T, Lifke V, Corradini V, Eichenlaub U, Batrla R, Buck K, Zink K, Rabe C, Blennow K, Shaw LM. CSF biomarkers of Alzheimer's disease concord with amyloid-β PET and predict clinical progression: A study of fully automated immunoassays in BioFINDER and ADNI cohorts. Alzheimers Dement 2018; 14:1470-1481. [PMID: 29499171 PMCID: PMC6119541 DOI: 10.1016/j.jalz.2018.01.010] [Citation(s) in RCA: 472] [Impact Index Per Article: 78.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 01/12/2018] [Accepted: 01/15/2018] [Indexed: 12/11/2022]
Abstract
Introduction We studied whether fully automated Elecsys cerebrospinal fluid (CSF) immunoassay results were concordant with positron emission tomography (PET) and predicted clinical progression, even with cutoffs established in an independent cohort. Methods Cutoffs for Elecsys amyloid-β1–42 (Aβ), total tau/Aβ(1–42), and phosphorylated tau/Aβ(1–42) were defined against [18F]flutemetamol PET in Swedish BioFINDER (n = 277) and validated against [18F]florbetapir PET in Alzheimer’s Disease Neuroimaging Initiative (n = 646). Clinical progression in patients with mild cognitive impairment (n = 619) was studied. Results CSF total tau/Aβ(1–42) and phosphorylated tau/Aβ(1–42) ratios were highly concordant with PET classification in BioFINDER (overall percent agreement: 90%; area under the curve: 94%). The CSF biomarker statuses established by predefined cutoffs were highly concordant with PET classification in Alzheimer’s Disease Neuroimaging Initiative (overall percent agreement: 89%–90%; area under the curves: 96%) and predicted greater 2-year clinical decline in patients with mild cognitive impairment. Strikingly, tau/Aβ ratios were as accurate as semiquantitative PET image assessment in predicting visual read–based outcomes. Discussion Elecsys CSF biomarker assays may provide reliable alternatives to PET in Alzheimer’s disease diagnosis.
Collapse
Affiliation(s)
- Oskar Hansson
- Clinical Memory Research Unit, Lund University, Malmö, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden.
| | - John Seibyl
- Institute for Neurodegenerative Disorders, New Haven, CT, USA
| | - Erik Stomrud
- Clinical Memory Research Unit, Lund University, Malmö, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute, London, UK
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Institute on Aging and Department of Pathology and Laboratory Medicine, Philadelphia, PA, USA
| | - Tobias Bittner
- Former Employee of Roche Diagnostics GmbH, Penzberg, Germany
| | | | | | | | | | | | | | - Christina Rabe
- Former Employee of Roche Diagnostics GmbH, Penzberg, Germany
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden.
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| |
Collapse
|
46
|
Villemagne VL, Doré V, Burnham SC, Masters CL, Rowe CC. Imaging tau and amyloid-β proteinopathies in Alzheimer disease and other conditions. Nat Rev Neurol 2018; 14:225-236. [DOI: 10.1038/nrneurol.2018.9] [Citation(s) in RCA: 230] [Impact Index Per Article: 38.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
|
47
|
Fantoni ER, Chalkidou A, O’ Brien JT, Farrar G, Hammers A. A Systematic Review and Aggregated Analysis on the Impact of Amyloid PET Brain Imaging on the Diagnosis, Diagnostic Confidence, and Management of Patients being Evaluated for Alzheimer's Disease. J Alzheimers Dis 2018; 63:783-796. [PMID: 29689725 PMCID: PMC5929301 DOI: 10.3233/jad-171093] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/26/2018] [Indexed: 12/20/2022]
Abstract
BACKGROUND Amyloid PET (aPET) imaging could improve patient outcomes in clinical practice, but the extent of impact needs quantification. OBJECTIVE To provide an aggregated quantitative analysis of the value added by aPET in cognitively impaired subjects. METHODS Systematic literature searches were performed in Embase and Medline until January 2017. 1,531 cases over 12 studies were included (1,142 cases over seven studies in the primary analysis where aPET was the key biomarker; the remaining cases included as defined groups in the secondary analysis). Data was abstracted by consensus among two observers and assessed for bias. Clinical utility was measured by diagnostic change, diagnostic confidence, and patient management before and after aPET. Three groups were further analyzed: control patients for whom feedback of aPET scan results was delayed; aPET Appropriate Use Criteria (AUC+) cases; and patients undergoing additional FDG/CSF testing. RESULTS For 1,142 cases with only aPET, 31.3% of diagnoses were revised, whereas 3.2% of diagnoses changed in the delayed aPET control group (p < 0.0001). Increased diagnostic confidence following aPET was found for 62.1% of 870 patients. Management changes with aPET were found in 72.2% of 740 cases and in 55.5% of 299 cases in the control group (p < 0.0001). The diagnostic value of aPET in AUC+ patients or when FDG/CSF were additionally available did not substantially differ from the value of aPET alone in the wider population. CONCLUSIONS Amyloid PET contributed to diagnostic revision in almost a third of cases and demonstrated value in increasing diagnostic confidence and refining management plans.
Collapse
Affiliation(s)
| | - Anastasia Chalkidou
- King’s Technology Evaluation Centre (KiTEC), London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK; King’s College London and Guy’s and St Thomas’ PET Centre, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, UK
| | | | | | - Alexander Hammers
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK; King’s College London and Guy’s and St Thomas’ PET Centre, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, UK
| |
Collapse
|
48
|
La Joie R, Bejanin A, Fagan AM, Ayakta N, Baker SL, Bourakova V, Boxer AL, Cha J, Karydas A, Jerome G, Maass A, Mensing A, Miller ZA, O'Neil JP, Pham J, Rosen HJ, Tsai R, Visani AV, Miller BL, Jagust WJ, Rabinovici GD. Associations between [ 18F]AV1451 tau PET and CSF measures of tau pathology in a clinical sample. Neurology 2017; 90:e282-e290. [PMID: 29282337 DOI: 10.1212/wnl.0000000000004860] [Citation(s) in RCA: 104] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Accepted: 10/04/2017] [Indexed: 01/26/2023] Open
Abstract
OBJECTIVE To assess the relationships between fluid and imaging biomarkers of tau pathology and compare their diagnostic utility in a clinically heterogeneous sample. METHODS Fifty-three patients (28 with clinical Alzheimer disease [AD] and 25 with non-AD clinical neurodegenerative diagnoses) underwent β-amyloid (Aβ) and tau ([18F]AV1451) PET and lumbar puncture. CSF biomarkers (Aβ42, total tau [t-tau], and phosphorylated tau [p-tau]) were measured by multianalyte immunoassay (AlzBio3). Receiver operator characteristic analyses were performed to compare discrimination of Aβ-positive AD from non-AD conditions across biomarkers. Correlations between CSF biomarkers and PET standardized uptake value ratios (SUVR) were assessed using skipped Pearson correlation coefficients. Voxelwise analyses were run to assess regional CSF-PET associations. RESULTS [18F]AV1451-PET cortical SUVR and p-tau showed excellent discrimination between Aβ-positive AD and non-AD conditions (area under the curve 0.92-0.94; ≤0.83 for other CSF measures), and reached 83% classification agreement. In the full sample, cortical [18F]AV1451 was associated with all CSF biomarkers, most strongly with p-tau (r = 0.75 vs 0.57 for t-tau and -0.49 for Aβ42). When restricted to Aβ-positive patients with AD, [18F]AV1451 SUVR correlated modestly with p-tau and t-tau (both r = 0.46) but not Aβ42 (r = 0.02). On voxelwise analysis, [18F]AV1451 correlated with CSF p-tau in temporoparietal cortices and with t-tau in medial prefrontal regions. Within AD, Mini-Mental State Examination scores were associated with [18F]AV1451-PET, but not CSF biomarkers. CONCLUSION [18F]AV1451-PET and CSF p-tau had comparable value for differential diagnosis. Correlations were robust in a heterogeneous clinical group but attenuated (although significant) in AD, suggesting that fluid and imaging biomarkers capture different aspects of tau pathology. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that, in a clinical sample of patients with a variety of suspected neurodegenerative diseases, both CSF p-tau and [18F]AV1451 distinguish AD from non-AD conditions.
Collapse
Affiliation(s)
- Renaud La Joie
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley.
| | - Alexandre Bejanin
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Anne M Fagan
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Nagehan Ayakta
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Suzanne L Baker
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Viktoriya Bourakova
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Adam L Boxer
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Jungho Cha
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Anna Karydas
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Gina Jerome
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Anne Maass
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Ashley Mensing
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Zachary A Miller
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - James P O'Neil
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Julie Pham
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Howard J Rosen
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Richard Tsai
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Adrienne V Visani
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Bruce L Miller
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - William J Jagust
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Gil D Rabinovici
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| |
Collapse
|
49
|
Martínez G, Vernooij RWM, Fuentes Padilla P, Zamora J, Bonfill Cosp X, Flicker L. 18F PET with florbetapir for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev 2017; 11:CD012216. [PMID: 29164603 PMCID: PMC6486090 DOI: 10.1002/14651858.cd012216.pub2] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND 18F-florbetapir uptake by brain tissue measured by positron emission tomography (PET) is accepted by regulatory agencies like the Food and Drug Administration (FDA) and the European Medicine Agencies (EMA) for assessing amyloid load in people with dementia. Its added value is mainly demonstrated by excluding Alzheimer's pathology in an established dementia diagnosis. However, the National Institute on Aging and Alzheimer's Association (NIA-AA) revised the diagnostic criteria for Alzheimer's disease and confidence in the diagnosis of mild cognitive impairment (MCI) due to Alzheimer's disease may be increased when using amyloid biomarkers tests like 18F-florbetapir. These tests, added to the MCI core clinical criteria, might increase the diagnostic test accuracy (DTA) of a testing strategy. However, the DTA of 18F-florbetapir to predict the progression from MCI to Alzheimer's disease dementia (ADD) or other dementias has not yet been systematically evaluated. OBJECTIVES To determine the DTA of the 18F-florbetapir PET scan for detecting people with MCI at time of performing the test who will clinically progress to ADD, other forms of dementia (non-ADD), or any form of dementia at follow-up. SEARCH METHODS This review is current to May 2017. We searched MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), BIOSIS Citation Index (Thomson Reuters Web of Science), Web of Science Core Collection, including the Science Citation Index (Thomson Reuters Web of Science) and the Conference Proceedings Citation Index (Thomson Reuters Web of Science), LILACS (BIREME), CINAHL (EBSCOhost), ClinicalTrials.gov (https://clinicaltrials.gov), and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (http://www.who.int/ictrp/search/en/). We also searched ALOIS, the Cochrane Dementia & Cognitive Improvement Group's specialised register of dementia studies (http://www.medicine.ox.ac.uk/alois/). We checked the reference lists of any relevant studies and systematic reviews, and performed citation tracking using the Science Citation Index to identify any additional relevant studies. No language or date restrictions were applied to the electronic searches. SELECTION CRITERIA We included studies that had prospectively defined cohorts with any accepted definition of MCI at time of performing the test and the use of 18F-florbetapir scan to evaluate the DTA of the progression from MCI to ADD or other forms of dementia. In addition, we only selected studies that applied a reference standard for Alzheimer's dementia diagnosis, for example, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) or Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria. DATA COLLECTION AND ANALYSIS We screened all titles and abstracts identified in electronic-database searches. Two review authors independently selected studies for inclusion and extracted data to create two-by-two tables, showing the binary test results cross-classified with the binary reference standard. We used these data to calculate sensitivities, specificities, and their 95% confidence intervals. Two independent assessors performed quality assessment using the QUADAS-2 tool plus some additional items to assess the methodological quality of the included studies. MAIN RESULTS We included three studies, two of which evaluated the progression from MCI to ADD, and one evaluated the progression from MCI to any form of dementia.Progression from MCI to ADD was evaluated in 448 participants. The studies reported data on 401 participants with 1.6 years of follow-up and in 47 participants with three years of follow-up. Sixty-one (15.2%) participants converted at 1.6 years follow-up; nine (19.1%) participants converted at three years of follow-up.Progression from MCI to any form of dementia was evaluated in five participants with 1.5 years of follow-up, with three (60%) participants converting to any form of dementia.There were concerns regarding applicability in the reference standard in all three studies. Regarding the domain of flow and timing, two studies were considered at high risk of bias. MCI to ADD;Progression from MCI to ADD in those with a follow-up between two to less than four years had a sensitivity of 67% (95% CI 30 to 93) and a specificity of 71% (95% CI 54 to 85) by visual assessment (n = 47, 1 study).Progression from MCI to ADD in those with a follow-up between one to less than two years had a sensitivity of 89% (95% CI 78 to 95) and a specificity of 58% (95% CI 53 to 64) by visual assessment, and a sensitivity of 87% (95% CI 76 to 94) and a specificity of 51% (95% CI 45 to 56) by quantitative assessment by the standardised uptake value ratio (SUVR)(n = 401, 1 study). MCI to any form of dementia;Progression from MCI to any form of dementia in those with a follow-up between one to less than two years had a sensitivity of 67% (95% CI 9 to 99) and a specificity of 50% (95% CI 1 to 99) by visual assessment (n = 5, 1 study). MCI to any other forms of dementia (non-ADD);There was no information regarding the progression from MCI to any other form of dementia (non-ADD). AUTHORS' CONCLUSIONS Although sensitivity was good in one included study, considering the poor specificity and the limited data available in the literature, we cannot recommend routine use of 18F-florbetapir PET in clinical practice to predict the progression from MCI to ADD.Because of the poor sensitivity and specificity, limited number of included participants, and the limited data available in the literature, we cannot recommend its routine use in clinical practice to predict the progression from MCI to any form of dementia.Because of the high financial costs of 18F-florbetapir, clearly demonstrating the DTA and standardising the process of this modality are important prior to its wider use.
Collapse
Affiliation(s)
- Gabriel Martínez
- Iberoamerican Cochrane CentreC/ Sant Antoni Maria Claret 167Pavelló 18 Planta 0BarcelonaBarcelonaSpain08025
- Universidad de AntofagastaFaculty of Medicine and DentistryAntofagastaChile
- Institut Català de Neurociències AplicadesAlzheimer Research Center and Memory Clinic of Fundació ACEBarcelonaSpain
| | - Robin WM Vernooij
- Iberoamerican Cochrane CentreC/ Sant Antoni Maria Claret 167Pavelló 18 Planta 0BarcelonaBarcelonaSpain08025
| | - Paulina Fuentes Padilla
- Iberoamerican Cochrane CentreC/ Sant Antoni Maria Claret 167Pavelló 18 Planta 0BarcelonaBarcelonaSpain08025
- Universidad de AntofagastaFaculty of Medicine and DentistryAntofagastaChile
| | - Javier Zamora
- Ramon y Cajal Institute for Health Research (IRYCIS), CIBER Epidemiology and Public Health (CIBERESP), Madrid (Spain) and Women's Health Research Unit, Centre for Primary Care and Public Health, Queen Mary University of LondonClinical Biostatistics UnitLondonMadridUK
| | - Xavier Bonfill Cosp
- CIBER Epidemiología y Salud Pública (CIBERESP)Iberoamerican Cochrane Centre, Biomedical Research Institute Sant Pau (IIB Sant Pau)Sant Antoni Maria Claret 167Pavilion 18BarcelonaCatalunyaSpain08025
- Universitat Autònoma de BarcelonaSant Antoni Maria Claret, 167Pavilion 18 (D‐13)BarcelonaCatalunyaSpain08025
| | - Leon Flicker
- University of Western AustraliaWestern Australian Centre for Health & Ageing ‐ WACHACrawleyPerthWestern AustraliaAustralia6014
| | | |
Collapse
|
50
|
Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity. Nat Commun 2017; 8:1214. [PMID: 29089479 PMCID: PMC5663717 DOI: 10.1038/s41467-017-01150-x] [Citation(s) in RCA: 547] [Impact Index Per Article: 78.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2017] [Accepted: 08/23/2017] [Indexed: 01/22/2023] Open
Abstract
It is not known exactly where amyloid-β (Aβ) fibrils begin to accumulate in individuals with Alzheimer’s disease (AD). Recently, we showed that abnormal levels of Aβ42 in cerebrospinal fluid (CSF) can be detected before abnormal amyloid can be detected using PET in individuals with preclinical AD. Using these approaches, here we identify the earliest preclinical AD stage in subjects from the ADNI and BioFINDER cohorts. We show that Aβ accumulation preferentially starts in the precuneus, medial orbitofrontal, and posterior cingulate cortices, i.e., several of the core regions of the default mode network (DMN). This early pattern of Aβ accumulation is already evident in individuals with normal Aβ42 in the CSF and normal amyloid PET who subsequently convert to having abnormal CSF Aβ42. The earliest Aβ accumulation is further associated with hypoconnectivity within the DMN and between the DMN and the frontoparietal network, but not with brain atrophy or glucose hypometabolism. Our results suggest that Aβ fibrils start to accumulate predominantly within certain parts of the DMN in preclinical AD and already then affect brain connectivity. Abnormal levels of Aβ42 in the cerebrospinal fluid occur prior to a positive amyloid PET scan in the brain of individuals with Alzheimer’s disease and here the authors use this temporal pattern to identify individuals with very early stage AD. They show that Aβ fibrils start to accumulate in some of the regions of the default mode network and affect brain connectivity before neurodegeneration occurs.
Collapse
|