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Zammit MD, Tudorascu DL, Laymon CM, Hartley SL, Ellison PA, Zaman SH, Ances BM, Johnson SC, Stone CK, Sabbagh MN, Mathis CA, Klunk WE, Cohen AD, Handen BL, Christian BT. Neurofibrillary tau depositions emerge with subthreshold cerebral beta-amyloidosis in down syndrome. NEUROIMAGE-CLINICAL 2021; 31:102740. [PMID: 34182407 PMCID: PMC8252122 DOI: 10.1016/j.nicl.2021.102740] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 05/20/2021] [Accepted: 06/21/2021] [Indexed: 01/04/2023]
Abstract
Neurofibrillary tau deposition in Down syndrome follows the Braak staging pathology. Neurofibrillary tau emerges in individuals with very low amyloid burden. There is a short latency between the onset of amyloid and tau in Down syndrome. Elevated tau was observed in Braak stages I-II with very low amyloid burden, and in stages III-VI with greater amyloid burden.
Introduction Adults with Down syndrome are genetically predisposed to develop Alzheimer’s disease and accumulate beta-amyloid plaques (Aβ) early in life. While Aβ has been heavily studied in Down syndrome, its relationship with neurofibrillary tau is less understood. The aim of this study was to evaluate neurofibrillary tau deposition in individuals with Down syndrome with varying levels of Aβ burden. Methods A total of 161 adults with Down syndrome (mean age = 39.2 (8.50) years) and 40 healthy, non-Down syndrome sibling controls (43.2 (12.6) years) underwent T1w-MRI, [C-11]PiB and [F-18]AV-1451 PET scans. PET images were converted to units of standardized uptake value ratios (SUVrs). Aβ burden was calculated using the amyloid load metric (AβL); a measure of global Aβ burden that improves quantification from SUVrs by suppressing the nonspecific binding signal component and computing the specific Aβ signal from all Aβ-carrying voxels from the image. Regional tau was assessed using control-standardized AV-1451 SUVr. Control-standardized SUVrs were compared across Down syndrome groups of Aβ-negative (A-) (AβL < 13.3), subthreshold A+ (13.3 ≤ AβL < 20) and conventionally A+ (AβL ≥ 20) individuals. The subthreshold A + group was identified as having significantly higher Aβ burden compared to the A- group, but not high enough to satisfy a conventional A + classification. Results A large-sized association that survived adjustment for chronological age, mental age (assessed using the Peabody Picture Vocabulary Test), and imaging site was observed between AβL and AV-1451 within each Braak region (p < .05). The A + group showed significantly higher AV-1451 retention across all Braak regions compared to the A- and subthreshold A + groups (p < .05). The subthreshold A + group showed significantly higher AV-1451 retention in Braak regions I-III compared to an age-matched sample from the A- group (p < .05). Discussion These results show that even the earliest detectable Aβ accumulation in Down syndrome is accompanied by elevated tau in the early Braak stage regions. This early detection of tau can help characterize the tau accumulation phase during preclinical Alzheimer’s disease progression in Down syndrome and suggests that there may be a relatively narrow window after Aβ accumulation begins to prevent the downstream cascade of events that leads to Alzheimer’s disease.
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Affiliation(s)
- Matthew D Zammit
- University of Wisconsin-Madison Waisman Center, Madison, WI, USA; University of Wisconsin-Madison Department of Medical Physics, Madison, WI, USA.
| | - Dana L Tudorascu
- University of Pittsburgh Department of Psychiatry, Pittsburgh, PA, USA
| | - Charles M Laymon
- University of Pittsburgh Department of Radiology, Pittsburgh, PA, USA; University of Pittsburgh Department of Bioengineering, Pittsburgh, PA, USA
| | - Sigan L Hartley
- University of Wisconsin-Madison Waisman Center, Madison, WI, USA
| | - Paul A Ellison
- University of Wisconsin-Madison Department of Medical Physics, Madison, WI, USA
| | - Shahid H Zaman
- Cambridge Intellectual Disability Research Group, University of Cambridge, Cambridge, UK
| | - Beau M Ances
- Washington University in St. Louis Department of Neurology, St. Louis, MO, USA
| | - Sterling C Johnson
- University of Wisconsin-Madison Alzheimer's Disease Research Center, Madison, WI, USA
| | - Charles K Stone
- University of Wisconsin-Madison Department of Medicine, Madison, WI, USA
| | | | - Chester A Mathis
- University of Pittsburgh Department of Psychiatry, Pittsburgh, PA, USA
| | - William E Klunk
- University of Pittsburgh Department of Psychiatry, Pittsburgh, PA, USA
| | - Ann D Cohen
- University of Pittsburgh Department of Psychiatry, Pittsburgh, PA, USA
| | - Benjamin L Handen
- University of Pittsburgh Department of Psychiatry, Pittsburgh, PA, USA
| | - Bradley T Christian
- University of Wisconsin-Madison Waisman Center, Madison, WI, USA; University of Wisconsin-Madison Department of Medical Physics, Madison, WI, USA
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Mayblyum DV, Becker JA, Jacobs HIL, Buckley RF, Schultz AP, Sepulcre J, Sanchez JS, Rubinstein ZB, Katz SR, Moody KA, Vannini P, Papp KV, Rentz DM, Price JC, Sperling RA, Johnson KA, Hanseeuw BJ. Comparing PET and MRI Biomarkers Predicting Cognitive Decline in Preclinical Alzheimer Disease. Neurology 2021; 96:e2933-e2943. [PMID: 33952655 PMCID: PMC8253562 DOI: 10.1212/wnl.0000000000012108] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Accepted: 03/19/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To compare how structural MRI, fluorodeoxyglucose (FDG), and flortaucipir (FTP) PET signals predict cognitive decline in high-amyloid vs low-amyloid participants with the goal of determining which biomarker combination would result in the highest increase of statistical power for prevention trials. METHODS In this prospective cohort study, we analyzed data from clinically normal adults from the Harvard Aging Brain Study with MRI, FDG, FTP, and Pittsburgh compound B (PiB)-PET acquired within a year and prospective cognitive evaluations over a mean 3-year follow-up. We focused analyses on predefined regions of interest: inferior temporal, isthmus cingulate, hippocampus, and entorhinal cortex. Cognition was assessed with the Preclinical Alzheimer's Cognitive Composite. We evaluated the association between biomarkers and cognitive decline using linear mixed-effect models with random intercepts and slopes, adjusting for demographics. We generated power curves simulating prevention trials. RESULTS Data from 131 participants (52 women, age 73.98 ± 8.29 years) were analyzed in the study. In separate models, most biomarkers had a closer association with cognitive decline in the high-PiB compared to the low-PiB participants. A backward stepwise regression including all biomarkers demonstrated that only neocortical PiB, entorhinal FTP, and entorhinal FDG were independent predictors of subsequent cognitive decline. Power analyses revealed that using both high PiB and low entorhinal FDG as inclusion criteria reduced 3-fold the number of participants needed in a hypothetical trial compared to using only high PiB. DISCUSSION In preclinical Alzheimer disease, entorhinal hypometabolism is a strong and independent predictor of subsequent cognitive decline, making FDG a potentially useful biomarker to increase power in clinical trials. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in people with preclinical Alzheimer disease, entorhinal hypometabolism identified by FDG-PET is predictive of subsequent cognitive decline.
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Affiliation(s)
- Danielle V Mayblyum
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - J Alex Becker
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Heidi I L Jacobs
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Rachel F Buckley
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Aaron P Schultz
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Jorge Sepulcre
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Justin S Sanchez
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Zoe B Rubinstein
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Samantha R Katz
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Kirsten A Moody
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Patrizia Vannini
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Kathryn V Papp
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Dorene M Rentz
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Julie C Price
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Reisa A Sperling
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Keith A Johnson
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Bernard J Hanseeuw
- From the Department of Radiology (D.V.M., J.A.B., H.I.L.J., J.S., J.S.S., Z.B.R., S.R.K., K.A.M., J.C.P., K.A.J., B.J.H.), Massachusetts General Hospital, Gordon Center for Medical Imaging and Athinoula A. Martinos Center for Biomedical Imaging, Boston; Faculty of Health, Medicine and Life Sciences (H.I.L.J.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, the Netherlands; Department of Neurology (R.F.B., P.V., K.V.P., D.M.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston; The Florey Institute (R.F.B.) and Melbourne School of Psychological Science (R.F.B.), University of Melbourne, Victoria Australia; Department of Neurology (A.P.S., B.J.H.), Massachusetts General Hospital, Harvard Medical School, Boston; and Department of Neurology (B.J.H.), Cliniques Universitaires Saint-Luc, Brussels, Belgium.
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Cho SH, Choe YS, Kim YJ, Kim HJ, Jang H, Kim Y, Kim SE, Kim SJ, Kim JP, Jung YH, Kim BC, Lockhart SN, Farrar G, Na DL, Moon SH, Seo SW. Head-to-Head Comparison of 18F-Florbetaben and 18F-Flutemetamol in the Cortical and Striatal Regions. J Alzheimers Dis 2021; 76:281-290. [PMID: 32474468 DOI: 10.3233/jad-200079] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) amyloid PET have been developed and approved for clinical use. It is important to understand the distinct features of these ligands to compare and correctly interpret the results of different amyloid PET studies. OBJECTIVE We performed a head-to-head comparison of FBB and FMM to compare with regard to imaging characteristics, including dynamic range of retention, and differences in quantitative measurements between the two ligands in cortical, striatal, and white matter (WM) regions. METHODS Paired FBB and FMM PET images were acquired in 107 participants. Correlations of FBB and FMM amyloid deposition in the cortex, striatum, and WM were investigated and compared in different reference regions (cerebellar gray matter (CG), whole cerebellum (WC), WC with brainstem (WC + B), and pons). RESULTS The cortical SUVR (R2 = 0.97) and striatal SUVR (R2 = 0.95) demonstrated an excellent linear correlation between FBB and FMM using a WC as reference region. There was no difference in the cortical SUVR ratio between the two ligands (p = 0.90), but the striatal SUVR ratio was higher in FMM than in FBB (p < 0.001). Also, the effect size of differences in striatal SUVR seemed to be higher with FMM (2.61) than with FBB (2.34). These trends were similarly observed according to four different reference regions (CG, WC, WC + B, and pons). CONCLUSION Our findings suggest that FMM might be better than FBB to detect amyloid burden in the striatum, although both ligands are comparable for imaging AD pathology in vivo.
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Affiliation(s)
- Soo Hyun Cho
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Department of Neurology, Chonnam National University Medical School, Chonnam National University Hospital, Gwangju, Korea
| | - Yeong Sim Choe
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Young Ju Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Yeshin Kim
- Department of Neurology, Kangwon National University Hospital, Kangwon National University College of Medicine, Chuncheon, Korea
| | - Si Eun Kim
- Departments of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Korea
| | - Seung Joo Kim
- Department of Neurology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Young Hee Jung
- Department of Neurology, Myoungji Hospital, Hanyang University, Goyangsi, Korea
| | - Byeong C Kim
- Department of Neurology, Chonnam National University Medical School, Chonnam National University Hospital, Gwangju, Korea
| | - Samuel N Lockhart
- Internal Medicine - Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Gill Farrar
- Pharmaceutical Diagnostics, GE Healthcare, Chalfont St Giles, UK
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea.,Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, Seoul, Korea
| | - Seung Hwan Moon
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea.,Department of Clinical Research Design & Evaluation, SAIHST, Sungkyunkwan University, Seoul, Korea.,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea.,Center for Clinical Epidemiology, Samsung Medical Center, Seoul, Korea
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54
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Baik K, Yang JJ, Jung JH, Lee YH, Chung SJ, Yoo HS, Sohn YH, Lee PH, Lee JM, Ye BS. Structural connectivity networks in Alzheimer's disease and Lewy body disease. Brain Behav 2021; 11:e02112. [PMID: 33792194 PMCID: PMC8119831 DOI: 10.1002/brb3.2112] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 02/14/2021] [Accepted: 02/17/2021] [Indexed: 01/21/2023] Open
Abstract
OBJECTIVE We evaluated disruption of the white matter (WM) network related with Alzheimer's disease (AD) and Lewy body disease (LBD), which includes Parkinson's disease and dementia with Lewy bodies. METHODS We consecutively recruited 37 controls and 77 patients with AD-related cognitive impairment (ADCI) and/or LBD-related cognitive impairment (LBCI). Diagnoses of ADCI and LBCI were supported by amyloid PET and dopamine transporter PET, respectively. There were 22 patients with ADCI, 19 patients with LBCI, and 36 patients with mixed ADCI/LBCI. We investigated the relationship between ADCI, LBCI, graph theory-based network measures on diffusion tensor images, and cognitive dysfunction using general linear models after controlling for age, sex, education, deep WM hyperintensities (WMH), periventricular WMH, and intracranial volume. RESULTS LBCI, especially mixed with ADCI, was associated with increased normalized path length and decreased normalized global efficiency. LBCI was related to the decreased nodal degree of left caudate, which was further associated with broad cognitive dysfunction. Decreased left caudate nodal degree was associated with decreased fractional anisotropy (FA) in the brain regions vulnerable to LBD. Compared with the control group, the LBCI group had an increased betweenness centrality in the occipital nodes, which was associated with decreased FA in the WM adjacent to the striatum and visuospatial dysfunction. CONCLUSION Concomitant ADCI and LBCI are associated with the accentuation of LBCI-related WM network disruption centered in the left caudate nucleus. The increase of occipital betweenness centrality could be a characteristic biologic change associated with visuospatial dysfunction in LBCI.
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Affiliation(s)
- Kyoungwon Baik
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
| | - Jin-Ju Yang
- Department of Biomedical Engineering, Hanyang University, Seoul, Korea
| | - Jin Ho Jung
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
| | - Yang Hyun Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
| | - Seok Jong Chung
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
| | - Han Soo Yoo
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
| | - Young H Sohn
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
| | - Phil Hyu Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, Seoul, Korea
| | - Byoung Seok Ye
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
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55
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Moscoso A, Grothe MJ, Ashton NJ, Karikari TK, Rodriguez JL, Snellman A, Suárez-Calvet M, Zetterberg H, Blennow K, Schöll M. Time course of phosphorylated-tau181 in blood across the Alzheimer's disease spectrum. Brain 2021; 144:325-339. [PMID: 33257949 PMCID: PMC7880671 DOI: 10.1093/brain/awaa399] [Citation(s) in RCA: 124] [Impact Index Per Article: 41.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 09/15/2020] [Accepted: 09/20/2020] [Indexed: 12/31/2022] Open
Abstract
Tau phosphorylated at threonine 181 (p-tau181) measured in blood plasma has recently been proposed as an accessible, scalable, and highly specific biomarker for Alzheimer’s disease. Longitudinal studies, however, investigating the temporal dynamics of this novel biomarker are lacking. It is therefore unclear when in the disease process plasma p-tau181 increases above physiological levels and how it relates to the spatiotemporal progression of Alzheimer’s disease characteristic pathologies. We aimed to establish the natural time course of plasma p-tau181 across the sporadic Alzheimer’s disease spectrum in comparison to those of established imaging and fluid-derived biomarkers of Alzheimer’s disease. We examined longitudinal data from a large prospective cohort of elderly individuals enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (n = 1067) covering a wide clinical spectrum from normal cognition to dementia, and with measures of plasma p-tau181 and an 18F-florbetapir amyloid-β PET scan at baseline. A subset of participants (n = 864) also had measures of amyloid-β1–42 and p-tau181 levels in CSF, and another subset (n = 298) had undergone an 18F-flortaucipir tau PET scan 6 years later. We performed brain-wide analyses to investigate the associations of plasma p-tau181 baseline levels and longitudinal change with progression of regional amyloid-β pathology and tau burden 6 years later, and estimated the time course of changes in plasma p-tau181 and other Alzheimer’s disease biomarkers using a previously developed method for the construction of long-term biomarker temporal trajectories using shorter-term longitudinal data. Smoothing splines demonstrated that earliest plasma p-tau181 changes occurred even before amyloid-β markers reached abnormal levels, with greater rates of change correlating with increased amyloid-β pathology. Voxel-wise PET analyses yielded relatively weak, yet significant, associations of plasma p-tau181 with amyloid-β pathology in early accumulating brain regions in cognitively healthy individuals, while the strongest associations with amyloid-β were observed in late accumulating regions in patients with mild cognitive impairment. Cross-sectional and particularly longitudinal measures of plasma p-tau181 were associated with widespread cortical tau aggregation 6 years later, covering temporoparietal regions typical for neurofibrillary tangle distribution in Alzheimer’s disease. Finally, we estimated that plasma p-tau181 reaches abnormal levels ∼6.5 and 5.7 years after CSF and PET measures of amyloid-β, respectively, following similar dynamics as CSF p-tau181. Our findings suggest that plasma p-tau181 increases are associated with the presence of widespread cortical amyloid-β pathology and with prospective Alzheimer’s disease typical tau aggregation, providing clear implications for the use of this novel blood biomarker as a diagnostic and screening tool for Alzheimer’s disease.
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Affiliation(s)
- Alexis Moscoso
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Sweden
| | - Michel J Grothe
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Sweden.,Unidad de Trastornos del Movimiento, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Sweden.,King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, UK.,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Juan Lantero Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Anniina Snellman
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden.,Turku PET Centre, University of Turku, FI-20520 Turku, Finland
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Servei de Neurologia, Hospital del Mar, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK.,UK Dementia Research Institute at University College London, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Michael Schöll
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Sweden.,Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
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Li X, Tsolis KC, Koper MJ, Ronisz A, Ospitalieri S, von Arnim CAF, Vandenberghe R, Tousseyn T, Scheuerle A, Economou A, Carpentier S, Otto M, Thal DR. Sequence of proteome profiles in preclinical and symptomatic Alzheimer's disease. Alzheimers Dement 2021; 17:946-958. [PMID: 33871169 DOI: 10.1002/alz.12345] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 03/03/2021] [Accepted: 03/11/2021] [Indexed: 12/15/2022]
Abstract
Proteome profile changes in Alzheimer's disease (AD) brains have been reported. However, it is unclear whether they represent a continuous process, or whether there is a sequential involvement of distinct proteins. To address this question, we used mass spectrometry. We analyzed soluble, dispersible, sodium dodecyl sulfate, and formic acid fractions of neocortex homogenates (mainly Brodmann area 17-19) from 18 pathologically diagnosed preclinical AD, 17 symptomatic AD, and 18 cases without signs of neurodegeneration. By doing so, we identified four groups of AD-related proteins being changed in levels in preclinical and symptomatic AD cases: early-responding, late-responding, gradually-changing, and fraction-shifting proteins. Gene ontology analysis of these proteins and all known AD-risk/causative genes identified vesicle endocytosis and the secretory pathway-related processes as an early-involved AD component. In conclusion, our findings suggest that subtle changes involving the secretory pathway and endocytosis precede severe proteome changes in symptomatic AD as part of the preclinical phase of AD. The respective early-responding proteins may also contribute to synaptic vesicle cycle alterations in symptomatic AD.
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Affiliation(s)
- Xiaohang Li
- Laboratory for Neuropathology, Department of Imaging and Pathology, KU Leuven (University of Leuven), Leuven, Belgium.,Leuven Brain Institute (LBI), KU Leuven (University of Leuven), Leuven, Belgium
| | - Konstantinos C Tsolis
- Laboratory of Molecular Bacteriology, Rega Institute, Department of Microbiology and Immunology, KU Leuven (University of Leuven), Leuven, Belgium
| | - Marta J Koper
- Laboratory for Neuropathology, Department of Imaging and Pathology, KU Leuven (University of Leuven), Leuven, Belgium.,Leuven Brain Institute (LBI), KU Leuven (University of Leuven), Leuven, Belgium.,Laboratory for the Research of Neurodegenerative Diseases, Department of Neurosciences, KU Leuven (University of Leuven), Leuven, Belgium.,Center for Brain and Disease Research, VIB, Leuven, Belgium
| | - Alicja Ronisz
- Laboratory for Neuropathology, Department of Imaging and Pathology, KU Leuven (University of Leuven), Leuven, Belgium.,Leuven Brain Institute (LBI), KU Leuven (University of Leuven), Leuven, Belgium
| | - Simona Ospitalieri
- Laboratory for Neuropathology, Department of Imaging and Pathology, KU Leuven (University of Leuven), Leuven, Belgium.,Leuven Brain Institute (LBI), KU Leuven (University of Leuven), Leuven, Belgium
| | - Christine A F von Arnim
- Department of Neurology, University of Ulm, Ulm, Germany.,Department of Geriatrics, University Medical Center Göttingen, Göttingen, Germany
| | - Rik Vandenberghe
- Department of Neurology, UZ Leuven (University Hospitals Leuven), Leuven, Belgium.,Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven (University of Leuven), Leuven, Belgium
| | - Thomas Tousseyn
- Department of Pathology, UZ Leuven (University Hospitals Leuven), Leuven, Belgium
| | | | - Anastassios Economou
- Laboratory of Molecular Bacteriology, Rega Institute, Department of Microbiology and Immunology, KU Leuven (University of Leuven), Leuven, Belgium
| | - Sebastien Carpentier
- BIOMED facility for SYstems BIOlogy based MAss spectrometry, KU Leuven (University of Leuven), Leuven, Belgium
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Dietmar Rudolf Thal
- Laboratory for Neuropathology, Department of Imaging and Pathology, KU Leuven (University of Leuven), Leuven, Belgium.,Leuven Brain Institute (LBI), KU Leuven (University of Leuven), Leuven, Belgium.,Department of Pathology, UZ Leuven (University Hospitals Leuven), Leuven, Belgium
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57
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Buckley RF. Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease. Neurotherapeutics 2021; 18:709-727. [PMID: 33782864 PMCID: PMC8423933 DOI: 10.1007/s13311-021-01026-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/15/2021] [Indexed: 12/25/2022] Open
Abstract
Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluable opportunities to understand and predict the course of disease. Neuroimaging AD biomarkers also allow for real-time tracking of disease-modifying treatment in clinical trials. With recent neuroimaging advances, along with the burgeoning availability of longitudinal neuroimaging data and big-data harmonization approaches, a more comprehensive evaluation of the disease has shed light on the topographical staging and temporal sequencing of the disease. Multimodal imaging approaches have also promoted the development of data-driven models of AD-associated pathological propagation of tau proteinopathies. Studies of autosomal dominant, early sporadic, and late sporadic courses of the disease have shed unique insights into the AD pathological cascade, particularly with regard to genetic vulnerabilities and the identification of potential drug targets. Further, neuroimaging markers of b-amyloid, tau, and neurodegeneration have provided a powerful tool for validation of novel fluid cerebrospinal and plasma markers. This review highlights some of the latest advances in the field of human neuroimaging in AD across these topics, particularly with respect to positron emission tomography and structural and functional magnetic resonance imaging.
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Affiliation(s)
- Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital & Brigham and Women's, Harvard Medical School, Boston, MA, USA.
- Melbourne School of Psychological Sciences and Florey Institutes, University of Melbourne, Melbourne, VIC, Australia.
- Department of Neurology, Massachusetts General Hospital, 149 13th St, Charlestown, MA, 02129, USA.
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58
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Bullich S, Roé-Vellvé N, Marquié M, Landau SM, Barthel H, Villemagne VL, Sanabria Á, Tartari JP, Sotolongo-Grau O, Doré V, Koglin N, Müller A, Perrotin A, Jovalekic A, De Santi S, Tárraga L, Stephens AW, Rowe CC, Sabri O, Seibyl JP, Boada M. Early detection of amyloid load using 18F-florbetaben PET. ALZHEIMERS RESEARCH & THERAPY 2021; 13:67. [PMID: 33773598 PMCID: PMC8005243 DOI: 10.1186/s13195-021-00807-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 03/10/2021] [Indexed: 03/26/2023]
Abstract
BACKGROUND A low amount and extent of Aβ deposition at early stages of Alzheimer's disease (AD) may limit the use of previously developed pathology-proven composite SUVR cutoffs. This study aims to characterize the population with earliest abnormal Aβ accumulation using 18F-florbetaben PET. Quantitative thresholds for the early (SUVRearly) and established (SUVRestab) Aβ deposition were developed, and the topography of early Aβ deposition was assessed. Subsequently, Aβ accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aβ deposition. METHODS The study population consisted of 686 subjects (n = 287 (cognitively normal healthy controls), n = 166 (subjects with subjective cognitive decline (SCD)), n = 129 (subjects with MCI), and n = 101 (subjects with AD dementia)). Three categories in the Aβ-deposition continuum were defined based on the developed SUVR cutoffs: Aβ-negative subjects, subjects with early Aβ deposition ("gray zone"), and subjects with established Aβ pathology. RESULTS SUVR using the whole cerebellum as the reference region and centiloid (CL) cutoffs for early and established amyloid pathology were 1.10 (13.5 CL) and 1.24 (35.7 CL), respectively. Cingulate cortices and precuneus, frontal, and inferior lateral temporal cortices were the regions showing the initial pathological tracer retention. Subjects in the "gray zone" or with established Aβ pathology accumulated more amyloid over time than Aβ-negative subjects. After a 4-year clinical follow-up, none of the Aβ-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aβ pathology progressed. Tau deposition was infrequent in those subjects without established Aβ pathology. CONCLUSIONS This study supports the utility of using two cutoffs for amyloid PET abnormality defining a "gray zone": a lower cutoff of 13.5 CL indicating emerging Aβ pathology and a higher cutoff of 35.7 CL where amyloid burden levels correspond to established neuropathology findings. These cutoffs define a subset of subjects characterized by pre-AD dementia levels of amyloid burden that precede other biomarkers such as tau deposition or clinical symptoms and accelerated amyloid accumulation. The determination of different amyloid loads, particularly low amyloid levels, is useful in determining who will eventually progress to dementia. Quantitation of amyloid provides a sensitive measure in these low-load cases and may help to identify a group of subjects most likely to benefit from intervention. TRIAL REGISTRATION Data used in this manuscript belong to clinical trials registered in ClinicalTrials.gov ( NCT00928304 , NCT00750282 , NCT01138111 , NCT02854033 ) and EudraCT (2014-000798-38).
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Affiliation(s)
- Santiago Bullich
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany.
| | - Núria Roé-Vellvé
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Marta Marquié
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley and Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Victor L Villemagne
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Ángela Sanabria
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Juan Pablo Tartari
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Oscar Sotolongo-Grau
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Vincent Doré
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia.,The Australian e-Health Research Centre, Health and Biosecurity, CSIRO, Melbourne, Victoria, Australia
| | - Norman Koglin
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Andre Müller
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Audrey Perrotin
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | | | | | - Lluís Tárraga
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Andrew W Stephens
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Christopher C Rowe
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | | | - Mercè Boada
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
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59
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Translating amyloid PET of different radiotracers by a deep generative model for interchangeability. Neuroimage 2021; 232:117890. [PMID: 33617991 DOI: 10.1016/j.neuroimage.2021.117890] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 12/31/2020] [Accepted: 02/15/2021] [Indexed: 11/24/2022] Open
Abstract
It is challenging to compare amyloid PET images obtained with different radiotracers. Here, we introduce a new approach to improve the interchangeability of amyloid PET acquired with different radiotracers through image-level translation. Deep generative networks were developed using unpaired PET datasets, consisting of 203 [11C]PIB and 850 [18F]florbetapir brain PET images. Using 15 paired PET datasets, the standardized uptake value ratio (SUVR) values obtained from pseudo-PIB or pseudo-florbetapir PET images translated using the generative networks was compared to those obtained from the original images. The generated amyloid PET images showed similar distribution patterns with original amyloid PET of different radiotracers. The SUVR obtained from the original [18F]florbetapir PET was lower than those obtained from the original [11C]PIB PET. The translated amyloid PET images reduced the difference in SUVR. The SUVR obtained from the pseudo-PIB PET images generated from [18F]florbetapir PET showed a good agreement with those of the original PIB PET (ICC = 0.87 for global SUVR). The SUVR obtained from the pseudo-florbetapir PET also showed a good agreement with those of the original [18F]florbetapir PET (ICC = 0.85 for global SUVR). The ICC values between the original and generated PET images were higher than those between original [11C]PIB and [18F]florbetapir images (ICC = 0.65 for global SUVR). Our approach provides the image-level translation of amyloid PET images obtained using different radiotracers. It may facilitate the clinical studies designed with variable amyloid PET images due to long-term clinical follow-up as well as multicenter trials by enabling the translation of different types of amyloid PET.
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60
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Sanchez JS, Becker JA, Jacobs HIL, Hanseeuw BJ, Jiang S, Schultz AP, Properzi MJ, Katz SR, Beiser A, Satizabal CL, O'Donnell A, DeCarli C, Killiany R, El Fakhri G, Normandin MD, Gómez-Isla T, Quiroz YT, Rentz DM, Sperling RA, Seshadri S, Augustinack J, Price JC, Johnson KA. The cortical origin and initial spread of medial temporal tauopathy in Alzheimer's disease assessed with positron emission tomography. Sci Transl Med 2021; 13:eabc0655. [PMID: 33472953 PMCID: PMC7978042 DOI: 10.1126/scitranslmed.abc0655] [Citation(s) in RCA: 108] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 09/10/2020] [Indexed: 12/15/2022]
Abstract
Advances in molecular positron emission tomography (PET) have enabled anatomic tracking of brain pathology in longitudinal studies of normal aging and dementia, including assessment of the central model of Alzheimer's disease (AD) pathogenesis, according to which TAU pathology begins focally but expands catastrophically under the influence of amyloid-β (Aβ) pathology to mediate neurodegeneration and cognitive decline. Initial TAU deposition occurs many years before Aβ in a specific area of the medial temporal lobe. Building on recent work that enabled focus of molecular PET measurements on specific TAU-vulnerable convolutional temporal lobe anatomy, we applied an automated anatomic sampling method to quantify TAU PET signal in 443 adult participants from several observational studies of aging and AD, spanning a wide range of ages, Aβ burdens, and degrees of clinical impairment. We detected initial cortical emergence of tauopathy near the rhinal sulcus in clinically normal people and, in a subset with longitudinal 2-year follow-up data (n = 104), tracked Aβ-associated spread of TAU from this site first to nearby neocortex of the temporal lobe and then to extratemporal regions. Greater rate of TAU spread was associated with baseline measures of both global Aβ burden and medial temporal lobe TAU. These findings are consistent with clinicopathological correlation studies of Alzheimer's tauopathy and enable precise tracking of AD-related TAU progression for natural history studies and prevention therapeutic trials.
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Affiliation(s)
- Justin S Sanchez
- Massachusetts General Hospital, Boston, MA 02114, USA.
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - J Alex Becker
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Heidi I L Jacobs
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
- School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, 6211 LK, Netherlands
| | - Bernard J Hanseeuw
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
- Université Catholique de Louvain, Brussels B-1348, Belgium
| | - Shu Jiang
- Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Aaron P Schultz
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Michael J Properzi
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Samantha R Katz
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Alexa Beiser
- Boston University School of Medicine, Boston, MA 02118, USA
- Boston University School of Public Health, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA 01702, USA
| | - Claudia L Satizabal
- Boston University School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA 01702, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 78229, USA
| | - Adrienne O'Donnell
- Boston University School of Public Health, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA 01702, USA
| | | | - Ron Killiany
- Boston University School of Medicine, Boston, MA 02118, USA
- Boston University School of Public Health, Boston, MA 02118, USA
| | - Georges El Fakhri
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Marc D Normandin
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Teresa Gómez-Isla
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Yakeel T Quiroz
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Grupo de Neurociencias, Universidad de Antioquia, Antioquia 050010, Colombia
| | - Dorene M Rentz
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Reisa A Sperling
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Sudha Seshadri
- Boston University School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA 01702, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 78229, USA
| | - Jean Augustinack
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Julie C Price
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Keith A Johnson
- Massachusetts General Hospital, Boston, MA 02114, USA.
- Harvard Medical School, Boston, MA 02115, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
- Brigham and Women's Hospital, Boston, MA 02115, USA
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Teipel SJ, Temp AGM, Levin F, Dyrba M, Grothe MJ. Association of PET-based stages of amyloid deposition with neuropathological markers of Aβ pathology. Ann Clin Transl Neurol 2021; 8:29-42. [PMID: 33137247 PMCID: PMC7818279 DOI: 10.1002/acn3.51238] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 09/22/2020] [Accepted: 10/02/2020] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE To determine if PET-based stages of regional amyloid deposition are associated with neuropathological phases of Aβ pathology. METHODS We applied data-driven regional frequency-based and a-priori striatum-based PET staging approaches to ante-mortem 18F-Florbetapir-PET scans of 30 cases from the Alzheimer's Disease Neuroimaging Initiative autopsy cohort, and used Bayesian regression analysis to study the associations of these in vivo amyloid stages with neuropathological Thal phases of regional Aβ plaque distribution and with semi-quantitative ratings of neocortical and striatal plaque densities. RESULTS Bayesian regression revealed extreme evidence for an association of both PET-based staging approaches with Thal phases, and these associations were about 44 times more likely for frequency-based stages and 89 times more likely for striatum-based stages than for global cortical 18F-Florbetapir-PET signal. Early (i.e., neocortical-only) PET-based amyloid stages also predicted the absence of striatal/diencephalic cored plaques. Receiver operating characteristics curves revealed highly accurate discrimination between low/high Thal phases and the presence/absence of regional plaques. The median areas under the curve were 0.99 for frequency-based staging (95% credibility interval 0.97-1.00), 0.93 for striatum-based staging (0.83-1.00), and 0.87 for global 18F-Florbetapir-PET signal (0.72-0.98). INTERPRETATION Our data indicate that both regional frequency- and striatum-based amyloid-PET staging approaches were superior to standard global amyloid-PET signal for differentiating between low and high degrees of regional amyloid pathology spread. Despite this, we found no evidence for the ability of either staging scheme to differentiate between low and moderate degrees of amyloid pathology which may be particularly relevant for early, preclinical stages of Alzheimer's disease.
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Affiliation(s)
- Stefan J. Teipel
- German Center for Neurodegenerative Diseases (DZNE)RostockGermany
- Department of Psychosomatic MedicineUniversity Medicine RostockRostockGermany
| | - Anna G. M. Temp
- German Center for Neurodegenerative Diseases (DZNE)RostockGermany
| | - Fedor Levin
- German Center for Neurodegenerative Diseases (DZNE)RostockGermany
| | - Martin Dyrba
- German Center for Neurodegenerative Diseases (DZNE)RostockGermany
| | - Michel J. Grothe
- German Center for Neurodegenerative Diseases (DZNE)RostockGermany
- Servicio de Neurología y Neurofisiología ClínicaUnidad de Trastornos del MovimientoInstituto de Biomedicina de SevillaHospital Universitario Virgen del Rocío/CSICUniversidad de SevillaSevilleSpain
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Gonzales MM, Samra J, O’Donnell A, Mackin RS, Salinas J, Jacob M, Satizabal CL, Aparicio HJ, Thibault EG, Sanchez JS, Finney R, Rubinstein ZB, Mayblyum DV, Killiany RJ, Decarli CS, Johnson KA, Beiser AS, Seshadri S. Association of Midlife Depressive Symptoms with Regional Amyloid-β and Tau in the Framingham Heart Study. J Alzheimers Dis 2021; 82:249-260. [PMID: 34024836 PMCID: PMC8900661 DOI: 10.3233/jad-210232] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
BACKGROUND Depressive symptoms predict increased risk for dementia decades before the emergence of cognitive symptoms. Studies in older adults provide preliminary evidence for an association between depressive symptoms and amyloid-β (Aβ) and tau accumulation. It is unknown if similar alterations are observed in midlife when preventive strategies may be most effective. OBJECTIVE The study aim was to evaluate the association between depressive symptoms and cerebral Aβ and tau in a predominately middle-aged cohort with examination of the apolipoprotein (APOE) ɛ4 allele as a moderator. METHODS Participants included 201 adults (mean age 53±8 years) who underwent 11C-Pittsburgh Compound B amyloid and 18F-Flortaucipir tau positron emission tomography (PET) imaging. Depressive symptoms were evaluated with the Center for Epidemiological Studies Depression Scale (CES-D) at the time of PET imaging, as well as eight years prior. Associations between depressive symptoms at both timepoints, as well as depression (CES-D≥16), with regional Aβ and tau PET retention were evaluated with linear regression adjusting for age and sex. Interactions with the APOE ɛ4 allele were explored. RESULTS Depressive symptoms and depression were not associated with PET outcomes in the overall sample. However, among APOE ɛ4 allele carriers, there was a significant cross-sectional association between depressive symptoms and increased tau PET uptake in the entorhinal cortex (β= 0.446, SE = 0.155, p = 0.006) and amygdala (β= 0.350, SE = 0.133, p = 0.012). CONCLUSION Although longitudinal studies are necessary, the results suggest that APOE ɛ4 carriers with depressive symptoms may present with higher susceptibility to early tau accumulation in regions integral to affective regulation and memory consolidation.
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Affiliation(s)
- Mitzi M. Gonzales
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Neurology, University of Texas Health Science Center, San Antonio, TX, USA
| | - Jasmeet Samra
- The Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Adrienne O’Donnell
- The Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - R. Scott Mackin
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
- Center for Imaging of Neurodegenerative Disease, Veteran Affairs Administration, San Francisco, CA, USA
| | - Joel Salinas
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA
| | - Mini Jacob
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- The Framingham Heart Study, Framingham, MA, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- The Framingham Heart Study, Framingham, MA, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Hugo J. Aparicio
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Emma G. Thibault
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Justin S. Sanchez
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Zoe B. Rubinstein
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle V. Mayblyum
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ron J. Killiany
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Charlie S. Decarli
- Department of Neurology, University of California Davis, Davis, CA, USA
- Center for Neuroscience, University of California Davis, Davis, CA, USA
| | - Keith A. Johnson
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Alexa S. Beiser
- The Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Neurology, University of Texas Health Science Center, San Antonio, TX, USA
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
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Lussier FZ, Pascoal TA, Chamoun M, Therriault J, Tissot C, Savard M, Kang MS, Mathotaarachchi S, Benedet AL, Parsons M, Qureshi MNI, Thomas ÉM, Shin M, Dion LA, Massarweh G, Soucy JP, Tsai IH, Vitali P, Ismail Z, Rosa-Neto P, Gauthier S. Mild behavioral impairment is associated with β-amyloid but not tau or neurodegeneration in cognitively intact elderly individuals. Alzheimers Dement 2020; 16:192-199. [PMID: 31914223 PMCID: PMC7041633 DOI: 10.1002/alz.12007] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 11/18/2019] [Indexed: 01/01/2023]
Abstract
INTRODUCTION Mild behavioral impairment (MBI) is characterized by the emergence of neuropsychiatric symptoms in elderly persons. Here, we examine the associations between MBI and Alzheimer's disease (AD) biomarkers in asymptomatic elderly individuals. METHODS Ninety-six cognitively normal elderly individuals underwent MRI, [18 F]AZD4694 β-amyloid-PET, and [18 F]MK6240 tau-PET. MBI was assessed using the MBI Checklist (MBI-C). Pearson's correlations and voxel-based regressions were used to evaluate the relationship between MBI-C score and [18 F]AZD4694 retention, [18 F]MK6240 retention, and gray matter (GM) volume. RESULTS Pearson correlations revealed a positive relationship between MBI-C score and global and striatal [18 F]AZD4694 standardized uptake value ratios (SUVRs). Voxel-based regression analyses revealed a positive correlation between MBI-C score and [18 F]AZD4694 retention. No significant correlations were found between MBI-C score and [18 F]MK6240 retention or GM volume. CONCLUSION We demonstrate for the first time a link between MBI and early AD pathology in a cognitively intact elderly population, supporting the use of the MBI-C as a metric to enhance clinical trial enrolment.
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Affiliation(s)
- Firoza Z Lussier
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Tharick A Pascoal
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Mira Chamoun
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Mélissa Savard
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
| | - Min Su Kang
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.,Montreal Neurological Institute, Montreal, Quebec, Canada
| | - Sulantha Mathotaarachchi
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
| | - Andrea L Benedet
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Marlee Parsons
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Muhammad Naveed Iqbal Qureshi
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Émilie M Thomas
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Monica Shin
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Laurie-Anne Dion
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
| | - Gassan Massarweh
- Montreal Neurological Institute, Montreal, Quebec, Canada.,Department of Radiochemistry, McGill University, Montreal, Quebec, Canada
| | - Jean-Paul Soucy
- Montreal Neurological Institute, Montreal, Quebec, Canada.,Department of Radiochemistry, McGill University, Montreal, Quebec, Canada
| | - I-Huang Tsai
- Montreal Neurological Institute, Montreal, Quebec, Canada
| | - Paolo Vitali
- Alzheimer's Disease Research Unit, The McGill University Research Centre for Studies in Aging, Verdun, Quebec, Canada
| | - Zahinoor Ismail
- Departments of Psychiatry, Clinical Neurosciences, and Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute and O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.,Montreal Neurological Institute, Montreal, Quebec, Canada
| | - Serge Gauthier
- Alzheimer's Disease Research Unit, The McGill University Research Centre for Studies in Aging, Verdun, Quebec, Canada
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Jun S, Kim H, Kim BS, Yoo BG, Lee WG. Quantitative Brain Amyloid Measures Predict Time-to-Progression from Amnestic Mild Cognitive Impairment to Alzheimer's Disease. J Alzheimers Dis 2020; 70:477-486. [PMID: 31256127 DOI: 10.3233/jad-190070] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND This study was designed to investigate factors that predict progression from amnestic mild cognitive impairment (aMCI) to probable Alzheimer's disease (AD). OBJECTIVE We studied the usefulness of quantitative assessment of amyloid burden measured by Florbetapir PET scan. METHODS The study cohort consisted of aMCI participants older than 65 and those with available Florbetapir PET scan at diagnosis from the ADNI database (http://adni.loni.usc.edu). To assess the prognostic impact of amyloid burden, a staging system based on the global SUVr of the PET scan was applied. We defined the stages as: stage I, negative amyloid scan; stage II, positive amyloid in 1st tertile; stage III, positive amyloid in 2nd tertile; and stage IV, positive amyloid in 3rd tertile. RESULTS Of 250 eligible aMCI subjects (age 74.1±5.4, female n = 105), 71 (28.4%) were diagnosed with probable AD within 3 years. Higher amyloid stages showed faster cognitive decline by Kaplan-Meier analysis. In multivariate Cox analysis, with stage I as a reference, the hazard ratio (HR) increased as the stage increased: stage II (HR, 4.509; p = 0.015), stage III (HR, 7.616; p = 0.001), and stage IV (HR, 9.421; p < 0.001). Along with amyloid stage, ApoE ɛ4 (HR, 1.943; p = 0.031), score of CDR-SB (HR, 1.845; p < 0.001) and ADAS 11 (HR, 1.144; p < 0.001), and hippocampal volume (HR, 0.002; p = 0.005) were also identified as predictors of dementia progression in aMCI subjects. CONCLUSIONS Large amyloid burden measured from amyloid PET scan could be a predictor of faster cognitive decline in aMCI patients.
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Affiliation(s)
- Sungmin Jun
- Departement of Nuclear Medicine, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | - Heeyoung Kim
- Departement of Nuclear Medicine, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | - Bum Soo Kim
- Departement of Nuclear Medicine, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | - Bong-Goo Yoo
- Departement of Neurology, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | - Won Gu Lee
- Departement of Neurology, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
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Gonneaud J, Bedetti C, Pichet Binette A, Benzinger TLS, Morris JC, Bateman RJ, Poirier J, Breitner JCS, Villeneuve S. Association of education with Aβ burden in preclinical familial and sporadic Alzheimer disease. Neurology 2020; 95:e1554-e1564. [PMID: 32759192 PMCID: PMC7713743 DOI: 10.1212/wnl.0000000000010314] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 03/23/2020] [Indexed: 02/04/2023] Open
Abstract
OBJECTIVE To determine whether years of education and the ε4 risk allele at APOE influence β-amyloid (Aβ) pathology similarly in asymptomatic individuals with a family history of sporadic Alzheimer disease (AD) and presymptomatic autosomal dominant AD mutation carriers. METHODS We analyzed cross-sectional data from 106 asymptomatic individuals with a parental history of sporadic AD (PREVENT-AD cohort; age 67.28 ± 4.72 years) and 117 presymptomatic autosomal dominant AD mutation carriers (DIAN cohort; age 35.04 ± 9.43 years). All participants underwent structural MRI and Aβ-PET imaging. In each cohort we investigated the influence of years of education, APOE ε4 status, and their interaction on Aβ-PET. RESULTS Asymptomatic individuals with a parental history of sporadic AD showed increased Aβ burden associated with APOE ε4 carriage and lower level of education, but no interaction between these. Presymptomatic mutation carriers of autosomal dominant AD showed no relation between APOE ε4 and Aβ burden, but increasing level of education was associated with reduced Aβ burden. The association between educational attainment and Aβ burden was similar in the 2 cohorts. CONCLUSIONS While the APOE ε4 allele confers increased tendency toward Aβ accumulation in sporadic AD only, protective environmental factors, like increased education, may promote brain resistance against Aβ pathology in both sporadic and autosomal dominant AD.
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Affiliation(s)
- Julie Gonneaud
- From the Department of Psychiatry (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), McGill University; Douglas Mental Health University Institute (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), StoP-AD Centre, Montreal, Canada; Knight Alzheimer's Disease Research Center (T.L.S.B., J.C.M., R.J.B.); and Washington University School of Medicine (T.L.S.B., J.C.M., R.J.B.), St. Louis, MO.
| | - Christophe Bedetti
- From the Department of Psychiatry (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), McGill University; Douglas Mental Health University Institute (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), StoP-AD Centre, Montreal, Canada; Knight Alzheimer's Disease Research Center (T.L.S.B., J.C.M., R.J.B.); and Washington University School of Medicine (T.L.S.B., J.C.M., R.J.B.), St. Louis, MO
| | - Alexa Pichet Binette
- From the Department of Psychiatry (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), McGill University; Douglas Mental Health University Institute (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), StoP-AD Centre, Montreal, Canada; Knight Alzheimer's Disease Research Center (T.L.S.B., J.C.M., R.J.B.); and Washington University School of Medicine (T.L.S.B., J.C.M., R.J.B.), St. Louis, MO
| | - Tammie L S Benzinger
- From the Department of Psychiatry (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), McGill University; Douglas Mental Health University Institute (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), StoP-AD Centre, Montreal, Canada; Knight Alzheimer's Disease Research Center (T.L.S.B., J.C.M., R.J.B.); and Washington University School of Medicine (T.L.S.B., J.C.M., R.J.B.), St. Louis, MO
| | - John C Morris
- From the Department of Psychiatry (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), McGill University; Douglas Mental Health University Institute (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), StoP-AD Centre, Montreal, Canada; Knight Alzheimer's Disease Research Center (T.L.S.B., J.C.M., R.J.B.); and Washington University School of Medicine (T.L.S.B., J.C.M., R.J.B.), St. Louis, MO
| | - Randall J Bateman
- From the Department of Psychiatry (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), McGill University; Douglas Mental Health University Institute (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), StoP-AD Centre, Montreal, Canada; Knight Alzheimer's Disease Research Center (T.L.S.B., J.C.M., R.J.B.); and Washington University School of Medicine (T.L.S.B., J.C.M., R.J.B.), St. Louis, MO
| | - Judes Poirier
- From the Department of Psychiatry (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), McGill University; Douglas Mental Health University Institute (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), StoP-AD Centre, Montreal, Canada; Knight Alzheimer's Disease Research Center (T.L.S.B., J.C.M., R.J.B.); and Washington University School of Medicine (T.L.S.B., J.C.M., R.J.B.), St. Louis, MO
| | - John C S Breitner
- From the Department of Psychiatry (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), McGill University; Douglas Mental Health University Institute (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), StoP-AD Centre, Montreal, Canada; Knight Alzheimer's Disease Research Center (T.L.S.B., J.C.M., R.J.B.); and Washington University School of Medicine (T.L.S.B., J.C.M., R.J.B.), St. Louis, MO
| | - Sylvia Villeneuve
- From the Department of Psychiatry (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), McGill University; Douglas Mental Health University Institute (J.G., C.B., A.P.B., J.P., J.C.S.B., S.V.), StoP-AD Centre, Montreal, Canada; Knight Alzheimer's Disease Research Center (T.L.S.B., J.C.M., R.J.B.); and Washington University School of Medicine (T.L.S.B., J.C.M., R.J.B.), St. Louis, MO.
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Collij LE, Heeman F, Salvadó G, Ingala S, Altomare D, de Wilde A, Konijnenberg E, van Buchem M, Yaqub M, Markiewicz P, Golla SSV, Wottschel V, Wink AM, Visser PJ, Teunissen CE, Lammertsma AA, Scheltens P, van der Flier WM, Boellaard R, van Berckel BNM, Molinuevo JL, Gispert JD, Schmidt ME, Barkhof F, Lopes Alves I. Multitracer model for staging cortical amyloid deposition using PET imaging. Neurology 2020; 95:e1538-e1553. [PMID: 32675080 PMCID: PMC7713745 DOI: 10.1212/wnl.0000000000010256] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Accepted: 03/20/2020] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE To develop and evaluate a model for staging cortical amyloid deposition using PET with high generalizability. METHODS Three thousand twenty-seven individuals (1,763 cognitively unimpaired [CU], 658 impaired, 467 with Alzheimer disease [AD] dementia, 111 with non-AD dementia, and 28 with missing diagnosis) from 6 cohorts (European Medical Information Framework for AD, Alzheimer's and Family, Alzheimer's Biomarkers in Daily Practice, Amsterdam Dementia Cohort, Open Access Series of Imaging Studies [OASIS]-3, Alzheimer's Disease Neuroimaging Initiative [ADNI]) who underwent amyloid PET were retrospectively included; 1,049 individuals had follow-up scans. With application of dataset-specific cutoffs to global standard uptake value ratio (SUVr) values from 27 regions, single-tracer and pooled multitracer regional rankings were constructed from the frequency of abnormality across 400 CU individuals (100 per tracer). The pooled multitracer ranking was used to create a staging model consisting of 4 clusters of regions because it displayed a high and consistent correlation with each single-tracer ranking. Relationships between amyloid stage, clinical variables, and longitudinal cognitive decline were investigated. RESULTS SUVr abnormality was most frequently observed in cingulate, followed by orbitofrontal, precuneal, and insular cortices and then the associative, temporal, and occipital regions. Abnormal amyloid levels based on binary global SUVr classification were observed in 1.0%, 5.5%, 17.9%, 90.0%, and 100.0% of individuals in stage 0 to 4, respectively. Baseline stage predicted decline in Mini-Mental State Examination (MMSE) score (ADNI: n = 867, F = 67.37, p < 0.001; OASIS: n = 475, F = 9.12, p < 0.001) and faster progression toward an MMSE score ≤25 (ADNI: n = 787, hazard ratio [HR]stage1 2.00, HRstage2 3.53, HRstage3 4.55, HRstage4 9.91, p < 0.001; OASIS: n = 469, HRstage4 4.80, p < 0.001). CONCLUSION The pooled multitracer staging model successfully classified the level of amyloid burden in >3,000 individuals across cohorts and radiotracers and detects preglobal amyloid burden and distinct risk profiles of cognitive decline within globally amyloid-positive individuals.
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Affiliation(s)
- Lyduine E Collij
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Fiona Heeman
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Gemma Salvadó
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Silvia Ingala
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Daniele Altomare
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Arno de Wilde
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Elles Konijnenberg
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Marieke van Buchem
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Maqsood Yaqub
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Pawel Markiewicz
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Sandeep S V Golla
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Viktor Wottschel
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Alle Meije Wink
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Pieter Jelle Visser
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Charlotte E Teunissen
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Adriaan A Lammertsma
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Philip Scheltens
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Wiesje M van der Flier
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Ronald Boellaard
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Bart N M van Berckel
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - José Luis Molinuevo
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Juan Domingo Gispert
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Mark E Schmidt
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Frederik Barkhof
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium
| | - Isadora Lopes Alves
- From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium.
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Teipel SJ, Dyrba M, Chiesa PA, Sakr F, Jelistratova I, Lista S, Vergallo A, Lemercier P, Cavedo E, Habert MO, Dubois B, Hampel H, Grothe MJ. In vivo staging of regional amyloid deposition predicts functional conversion in the preclinical and prodromal phases of Alzheimer's disease. Neurobiol Aging 2020; 93:98-108. [DOI: 10.1016/j.neurobiolaging.2020.03.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 03/10/2020] [Accepted: 03/12/2020] [Indexed: 11/24/2022]
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Jelistratova I, Teipel SJ, Grothe MJ. Longitudinal validity of PET-based staging of regional amyloid deposition. Hum Brain Mapp 2020; 41:4219-4231. [PMID: 32648624 PMCID: PMC7502828 DOI: 10.1002/hbm.25121] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 05/29/2020] [Accepted: 06/22/2020] [Indexed: 12/12/2022] Open
Abstract
Positron emission tomography (PET)-based staging of regional amyloid deposition has recently emerged as a promising tool for sensitive detection and stratification of pathology progression in Alzheimer's Disease (AD). Here we present an updated methodological framework for PET-based amyloid staging using region-specific amyloid-positivity thresholds and assess its longitudinal validity using serial PET acquisitions. We defined region-specific thresholds of amyloid-positivity based on Florbetapir-PET data of 13 young healthy individuals (age ≤ 45y), applied these thresholds to Florbetapir-PET data of 179 cognitively normal older individuals to estimate a regional amyloid staging model, and tested this model in a larger sample of patients with mild cognitive impairment (N = 403) and AD dementia (N = 85). 2-year follow-up Florbetapir-PET scans from a subset of this sample (N = 436) were used to assess the longitudinal validity of the cross-sectional model based on individual stage transitions and data-driven longitudinal trajectory modeling. Results show a remarkable congruence between cross-sectionally estimated and longitudinally modeled trajectories of amyloid accumulation, beginning in anterior temporal areas, followed by frontal and medial parietal areas, the remaining associative neocortex, and finally primary sensory-motor areas and subcortical regions. Over 98% of individual amyloid deposition profiles and longitudinal stage transitions adhered to this staging scheme of regional pathology progression, which was further supported by corresponding changes in cerebrospinal fluid biomarkers. In conclusion, we provide a methodological refinement and longitudinal validation of PET-based staging of regional amyloid accumulation, which may help improving early detection and in-vivo stratification of pathologic disease progression in AD.
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Affiliation(s)
| | - Stefan J. Teipel
- German Center for Neurodegenerative Diseases (DZNE)RostockGermany
- Department of Psychosomatic MedicineUniversity of RostockRostockGermany
| | - Michel J. Grothe
- German Center for Neurodegenerative Diseases (DZNE)RostockGermany
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de SevillaHospital Universitario Virgen del Rocío/CSIC/Universidad de SevillaSevilleSpain
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69
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Hanseeuw BJ, Malotaux V, Dricot L, Quenon L, Sznajer Y, Cerman J, Woodard JL, Buckley C, Farrar G, Ivanoiu A, Lhommel R. Defining a Centiloid scale threshold predicting long-term progression to dementia in patients attending the memory clinic: an [ 18F] flutemetamol amyloid PET study. Eur J Nucl Med Mol Imaging 2020; 48:302-310. [PMID: 32601802 PMCID: PMC7835306 DOI: 10.1007/s00259-020-04942-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 06/22/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To evaluate cerebral amyloid-β(Aβ) pathology in older adults with cognitive complaints, visual assessment of PET images is approved as the routine method for image interpretation. In research studies however, Aβ-PET semi-quantitative measures are associated with greater risk of progression to dementia; but until recently, these measures lacked standardization. Therefore, the Centiloid scale, providing standardized Aβ-PET semi-quantitation, was recently validated. We aimed to determine the predictive values of visual assessments and Centiloids in non-demented patients, using long-term progression to dementia as our standard of truth. METHODS One hundred sixty non-demented participants (age, 54-86) were enrolled in a monocentric [18F] flutemetamol Aβ-PET study. Flutemetamol images were interpreted visually following the manufacturers recommendations. SUVr values were converted to the Centiloid scale using the GAAIN guidelines. Ninety-eight persons were followed until dementia diagnosis or were clinically stable for a median of 6 years (min = 4.0; max = 8.0). Twenty-five patients with short follow-up (median = 2.0 years; min = 0.8; max = 3.9) and 37 patients with no follow-up were excluded. We computed ROC curves predicting subsequent dementia using baseline PET data and calculated negative (NPV) and positive (PPV) predictive values. RESULTS In the 98 participants with long follow-up, Centiloid = 26 provided the highest overall predictive value = 87% (NPV = 85%, PPV = 88%). Visual assessment corresponded to Centiloid = 40, which predicted dementia with an overall predictive value = 86% (NPV = 81%, PPV = 92%). Inclusion of the 25 patients who only had a 2-year follow-up decreased the PPV = 67% (NPV = 88%), reflecting the many positive cases that did not progress to dementia after short follow-ups. CONCLUSION A Centiloid threshold = 26 optimally predicts progression to dementia 6 years after PET. Visual assessment provides similar predictive value, with higher specificity and lower sensitivity. TRIAL REGISTRATION Eudra-CT number: 2011-001756-12.
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Affiliation(s)
- Bernard J Hanseeuw
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium. .,Neurology Department, Saint-Luc University Hospital, Av. Hippocrate, 10, 1200, Brussels, Belgium. .,Gordon Center for Medical Imaging, Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Vincent Malotaux
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Laurence Dricot
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Lisa Quenon
- Neurology Department, Saint-Luc University Hospital, Av. Hippocrate, 10, 1200, Brussels, Belgium
| | - Yves Sznajer
- Genetics Department, Saint-Luc University Hospital, Brussels, Belgium
| | - Jiri Cerman
- Department of Neurology, Charles University, 2nd Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
| | - John L Woodard
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium.,Department of Psychology, Wayne State University, Detroit, MI, USA
| | | | | | - Adrian Ivanoiu
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium.,Neurology Department, Saint-Luc University Hospital, Av. Hippocrate, 10, 1200, Brussels, Belgium
| | - Renaud Lhommel
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium.,Nuclear Medicine Department, Saint-Luc University Hospital, Brussels, Belgium.,Institute of Experimental and Clinical Research, Université Catholique de Louvain, Brussels, Belgium
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Hahn A, Strandberg TO, Stomrud E, Nilsson M, van Westen D, Palmqvist S, Ossenkoppele R, Hansson O. Association Between Earliest Amyloid Uptake and Functional Connectivity in Cognitively Unimpaired Elderly. Cereb Cortex 2020; 29:2173-2182. [PMID: 30877785 PMCID: PMC6458901 DOI: 10.1093/cercor/bhz020] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 01/25/2019] [Indexed: 12/19/2022] Open
Abstract
Alterations in cognitive performance have been noted in nondemented subjects with elevated accumulation of amyloid-β (Aβ) fibrils. However, it is not yet understood whether brain function is already influenced by Aβ deposition during the very earliest stages of the disease. We therefore investigated associations between [18F]Flutemetamol PET, resting-state functional connectivity, gray and white matter structure and cognitive performance in 133 cognitively normal elderly that exhibited normal global Aβ PET levels. [18F]Flutemetamol uptake in regions known to accumulate Aβ fibrils early in preclinical AD (i.e., mainly certain parts of the default-mode network) was positively associated with dynamic but not static functional connectivity (r = 0.77). Dynamic functional connectivity was further related to better cognitive performance (r = 0.21–0.72). No significant associations were found for Aβ uptake with gray matter volume or white matter diffusivity. The findings demonstrate that the earliest accumulation of Aβ fibrils is associated with increased functional connectivity, which occurs before any structural alterations. The enhanced functional connectivity may reflect a compensatory mechanism to maintain high cognitive performance in the presence of increasing amyloid accumulation during the earliest phases of AD.
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Affiliation(s)
- Andreas Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Tor O Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Markus Nilsson
- Lund University Bioimaging Center, Lund University, Lund, Sweden
| | - Danielle van Westen
- Department of Clinical Sciences Lund, Diagnostic Radiology, Lund University, Sweden.,Imaging and Function, Skåne University Health Care, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden.,Department of Neurology, Skåne University Hospital, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden.,Department of Neurology and Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, HV, The Netherlands
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
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Lopes Alves I, Collij LE, Altomare D, Frisoni GB, Saint‐Aubert L, Payoux P, Kivipelto M, Jessen F, Drzezga A, Leeuwis A, Wink AM, Visser PJ, van Berckel BN, Scheltens P, Gray KR, Wolz R, Stephens A, Gismondi R, Buckely C, Gispert JD, Schmidt M, Ford L, Ritchie C, Farrar G, Barkhof F, Molinuevo JL. Quantitative amyloid PET in Alzheimer's disease: the AMYPAD prognostic and natural history study. Alzheimers Dement 2020; 16:750-758. [PMID: 32281303 PMCID: PMC7984341 DOI: 10.1002/alz.12069] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 11/12/2019] [Accepted: 12/23/2019] [Indexed: 12/18/2022]
Abstract
INTRODUCTION The Amyloid Imaging to Prevent Alzheimer's Disease (AMYPAD) Prognostic and Natural History Study (PNHS) aims at understanding the role of amyloid imaging in the earliest stages of Alzheimer's disease (AD). AMYPAD PNHS adds (semi-)quantitative amyloid PET imaging to several European parent cohorts (PCs) to predict AD-related progression as well as address methodological challenges in amyloid PET. METHODS AMYPAD PNHS is an open-label, prospective, multi-center, cohort study recruiting from multiple PCs. Around 2000 participants will undergo baseline amyloid positron emission tomography (PET), half of whom will be invited for a follow-up PET 12 at least 12 months later. RESULTS Primary include several amyloid PET measurements (Centiloid, SUVr, BPND , R1 ), and secondary are their changes from baseline, relationship to other amyloid markers (cerebrospinal fluid and visual assessment), and predictive value of AD-related decline. EXPECTED IMPACT Determining the role of amyloid PET for the understanding of this complex disease and potentially improving secondary prevention trials.
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Affiliation(s)
- Isadora Lopes Alves
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Lyduine E. Collij
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
- Memory ClinicUniversity Hospital of GenevaGenevaSwitzerland
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
- Memory ClinicUniversity Hospital of GenevaGenevaSwitzerland
| | - Laure Saint‐Aubert
- Department of Nuclear MedicineImaging PoleToulouse, University HospitalToulouseFrance
- Toulouse NeuroImaging CenterUniversité de Toulouse, Inserm, UPSToulouseFrance
| | - Pierre Payoux
- Department of Nuclear MedicineImaging PoleToulouse, University HospitalToulouseFrance
- Toulouse NeuroImaging CenterUniversité de Toulouse, Inserm, UPSToulouseFrance
| | - Miia Kivipelto
- Department of Geriatric MedicineKarolinska University Hospital HuddingeStockholmSweden
| | - Frank Jessen
- Department of Nuclear MedicineUniversity of CologneCologneGermany
| | | | - Annebet Leeuwis
- Department of Neurology, Amsterdam UMCVrije Universiteit AmsterdamAlzheimercenterAmsterdamthe Netherlands
| | - Alle Meije Wink
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Amsterdam UMCVrije Universiteit AmsterdamAlzheimercenterAmsterdamthe Netherlands
| | - Bart N.M. van Berckel
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Philip Scheltens
- Department of Neurology, Amsterdam UMCVrije Universiteit AmsterdamAlzheimercenterAmsterdamthe Netherlands
| | | | | | | | | | | | - Juan Domingo Gispert
- Barcelona β Brain Research CenterBarcelonaSpain
- Centro de Investigación Biomédica en Red de BioingenieríaBiomateriales y Nanomedicina (CIBER‐BBN)MadridSpain
- Universitat Pompeu FabraBarcelonaSpain
| | | | - Lisa Ford
- Janssen Pharmaceutica RNDTitusvilleNew JerseyUSA
| | - Craig Ritchie
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Gill Farrar
- GE HealthcareLife SciencesAmershamUnited Kingdom
| | - Frederik Barkhof
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
- Centre for Medical Image ComputingMedical Physics and Biomedical Engineering, UCLLondonUnited Kingdom
| | - José Luis Molinuevo
- Barcelona β Brain Research CenterBarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - the AMYPAD Consortium
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
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Rullmann M, McLeod A, Grothe MJ, Sabri O, Barthel H. Reshaping the Amyloid Buildup Curve in Alzheimer Disease? Partial-Volume Effect Correction of Longitudinal Amyloid PET Data. J Nucl Med 2020; 61:1820-1824. [PMID: 32358089 DOI: 10.2967/jnumed.119.238477] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 03/28/2020] [Indexed: 01/27/2023] Open
Abstract
It was hypothesized that the brain β-amyloid buildup curve plateaus at an early symptomatic stage of Alzheimer disease (AD). Atrophy-related partial-volume effects (PVEs) degrade signal in hot-spot imaging techniques such as amyloid PET. The current study, a longitudinal analysis of amyloid-sensitive PET data, investigated the effect on the shape of the β-amyloid curve in AD when PVE correction (PVEC) is applied. Methods: We analyzed baseline and 2-y follow-up data for 216 symptomatic individuals on the AD continuum (positive amyloid status) enrolled in the Alzheimer's Disease Neuroimaging Initiative (17 with AD dementia and 199 with mild cognitive impairment), including 18F-florbetapir PET, MRI, and Mini Mental State Examination scores. For PVEC, the modified Müller-Gärtner method was performed. Results: Compared with non-PVE-corrected data, PVE-corrected data yielded significantly higher changes in regional and composite SUV ratio (SUVR) over time (P = 0.0002 for composite SUVRs). Longitudinal SUVR changes in relation to Mini Mental State Examination decreases showed a significantly higher slope for the regression line in the PVE-corrected than in the non-PVE-corrected PET data (F 1 = 7.1, P = 0.008). Conclusion: These PVEC results indicate that the β-amyloid buildup curve does not plateau at an early symptomatic disease stage. A further evaluation of the impact of PVEC on the in vivo characterization of time-dependent AD pathology, including the reliable assessment and comparison of other amyloid tracers, is warranted.
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Affiliation(s)
- Michael Rullmann
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany; and
| | - Anke McLeod
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany; and
| | - Michel J Grothe
- German Center for Neurodegenerative Diseases-Rostock/Greifswald, Rostock, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany; and
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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.
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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
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74
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d'Oleire Uquillas F, Jacobs HIL, Schultz AP, Hanseeuw BJ, Buckley RF, Sepulcre J, Pascual-Leone A, Donovan NJ, Johnson KA, Sperling RA, Vannini P. Functional and Pathological Correlates of Judgments of Learning in Cognitively Unimpaired Older Adults. Cereb Cortex 2020; 30:1974-1983. [PMID: 31696223 DOI: 10.1093/cercor/bhz217] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Revised: 08/18/2019] [Accepted: 08/20/2019] [Indexed: 11/14/2022] Open
Abstract
Judgments of learning (JOL) pertain to introspective metamemory processes evaluating how well information is learned. Using a functional magnetic resonance imaging (fMRI) task, we investigated the neural substrates of JOL predictions in a group of 105 cognitively unimpaired older adults from the Harvard Aging Brain Study. Associations of JOL performance and its neural correlates with amyloid-β (Aβ) and tau pathology, two proteinopathies associated with Alzheimer's disease (AD) and aging, were also examined. We found that trials judged as learned well relative to trials judged as learned less well (high JOL > low JOL) engaged the ventromedial prefrontal cortex and precuneus, among other midline regions, in addition to bilateral hippocampi. In this cohort of older adults, greater levels of entorhinal tau deposition were associated with overestimation of memory performance and with lower fMRI signal in midline regions during predicted memory success. No associations with Aβ were found. The findings suggest that tau pathology in unimpaired older adults may play a role in altered metamemory processes. We discuss our findings in light of the hypothesis that JOLs are partially dependent on a process involving attempts to retrieve a correct answer from memory, as well as implications for clinical research investigating unawareness of memory performance (i.e., anosognosia) in patients with AD dementia.
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Affiliation(s)
| | - Heidi I L Jacobs
- Division of Nuclear Medicine, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.,School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht 6200 MD, Limburg, The Netherlands
| | - Aaron P Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Bernard J Hanseeuw
- Division of Nuclear Medicine, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.,Department of Neurology, Saint-Luc University Hospital, Institute of Neuroscience, Université Catholique de Louvain, 1200 Brussels, Belgium
| | - Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.,Florey Institutes of Neuroscience and Mental Health, University of Melbourne, 3010 Melbourne, Australia.,Melbourne School of Psychological Science, University of Melbourne, 3010 Melbourne, Australia
| | - Jorge Sepulcre
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA.,Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Alvaro Pascual-Leone
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA.,Hinda and Arthur Marcus Institute for Aging Research and the Center for Memory Health at Hebrew SeniorLife, Boston, MA 02131, USA
| | - Nancy J Donovan
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.,Division of Geriatric Psychiatry, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Keith A Johnson
- Division of Nuclear Medicine, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA.,Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA.,Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Patrizia Vannini
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA.,Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
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Hanseeuw BJ, Scott MR, Sikkes SAM, Properzi M, Gatchel JR, Salmon E, Marshall GA, Vannini P. Evolution of anosognosia in alzheimer's disease and its relationship to amyloid. Ann Neurol 2020; 87:267-280. [PMID: 31750553 PMCID: PMC6980336 DOI: 10.1002/ana.25649] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 11/14/2019] [Accepted: 11/15/2019] [Indexed: 11/09/2022]
Abstract
OBJECTIVE Unawareness, or anosognosia, of memory deficits is a challenging manifestation of Alzheimer's disease (AD) that adversely affects a patient's safety and decision-making. However, there is a lack of consensus regarding the presence, as well as the evolution, of altered awareness of memory function across the preclinical and prodromal stages of AD. Here, we aimed to characterize change in awareness of memory abilities and its relationship to beta-amyloid (Aβ) burden in a large cohort (N = 1,070) of individuals across the disease spectrum. METHODS Memory awareness was longitudinally assessed (average number of visits = 4.3) and operationalized using the discrepancy between mean participant and partner report on the Everyday Cognition scale (memory domain). Aβ deposition was measured at baseline using [18F]florbetapir positron emission tomographic imaging. RESULTS Aβ predicted longitudinal changes in memory awareness, such that awareness decreased faster in participants with increased Aβ burden. Aβ and clinical group interacted to predict change in memory awareness, demonstrating the strongest effect in dementia participants, but could also be found in the cognitively normal (CN) participants. In a subset of CN participants who progressed to mild cognitive impairment (MCI), heightened memory awareness was observed up to 1.6 years before MCI diagnosis, with memory awareness declining until the time of progression to MCI (-0.08 discrepant-points/yr). In a subset of MCI participants who progressed to dementia, awareness was low initially and continued to decline (-0.23 discrepant-points/yr), reaching anosognosia 3.2 years before dementia onset. INTERPRETATION Aβ burden is associated with a progressive decrease in self-awareness of memory deficits, reaching anosognosia approximately 3 years before dementia diagnosis. ANN NEUROL 2020;87:267-280.
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Affiliation(s)
- Bernard J Hanseeuw
- Department of Neurology, Cliniques Universitaires Saint-Luc, and Institute of Neuroscience, Catholic University of Louvain, Brussels, Belgium
- Department of Neurology and Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Matthew R Scott
- Department of Neurology and Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Sietske A M Sikkes
- Department of Neurology and Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical Center, VU University, Amsterdam, the Netherlands
| | - Michael Properzi
- Department of Neurology and Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Jennifer R Gatchel
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Division of Geriatric Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Eric Salmon
- GIGA Cyclotron Research Center-IVI, University of Liege, Quartier Agora, Sart Tilman, Belgium
| | - Gad A Marshall
- Department of Neurology and Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Patrizia Vannini
- Department of Neurology and Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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Kim SE, Lee B, Park S, Cho SH, Kim SJ, Kim Y, Jang H, Jeong JH, Yoon SJ, Park KW, Kim EJ, Jung NY, Yoon B, Jang JW, Hong JY, Hwang J, Na DL, Seo SW, Choi SH, Kim HJ. Clinical significance of focal ß-amyloid deposition measured by 18F-flutemetamol PET. ALZHEIMERS RESEARCH & THERAPY 2020; 12:6. [PMID: 31901233 PMCID: PMC6942396 DOI: 10.1186/s13195-019-0577-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 12/23/2019] [Indexed: 12/14/2022]
Abstract
Background Although amyloid PET of typical Alzheimer’s disease (AD) shows diffuse ß-amyloid (Aß) deposition, some patients show focal deposition. The clinical significance of this focal Aß is not well understood. We examined the clinical significance of focal Aß deposition in terms of cognition as well as Aß and tau cerebrospinal fluid (CSF) levels. We further evaluated the order of Aß accumulation by visual assessment. Methods We included 310 subjects (125 cognitively unimpaired, 125 mild cognitive impairment, and 60 AD dementia) from 9 referral centers. All patients underwent neuropsychological tests and 18F-flutemetamol (FMM) PET. Seventy-seven patients underwent CSF analysis. Each FMM scan was visually assessed in 10 regions (frontal, precuneus and posterior cingulate, lateral temporal, parietal, and striatum of each hemisphere) and was classified into three groups: No-FMM, Focal-FMM (FMM uptake in 1–9 regions), and Diffuse-FMM (FMM uptake in all 10 regions). Results 53/310 (17.1%) subjects were classified as Focal-FMM. The cognitive level of the Focal-FMM group was better than that of Diffuse-FMM group and worse than that of No-FMM group. Among the Focal-FMM group, those who had FMM uptake to a larger extent or in the striatum had worse cognitive levels. Compared to the Diffuse-FMM group, the Focal-FMM group had a less AD-like CSF profile (increased Aß42 and decreased t-tau, t-tau/Aß42). Among the Focal-FMM group, Aß deposition was most frequently observed in the frontal (62.3%) and least frequently observed in the striatum (43.4%) and temporal (39.6%) regions. Conclusions We suggest that focal Aß deposition is an intermediate stage between no Aß and diffuse Aß deposition. Furthermore, among patients with focal Aß deposition, those who have Aß to a larger extent and striatal involvement show clinical features close to diffuse Aß deposition. Further longitudinal studies are needed to evaluate the disease progression of patients with focal Aß deposition. Electronic supplementary material The online version of this article (10.1186/s13195-019-0577-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Si Eun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-ku, Seoul, 135-710, Republic of Korea.,Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Korea
| | - Byungju Lee
- Department of Neurology, Yuseong Geriatric Rehabilitation Hospital, Pohang, Korea
| | - Seongbeom Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-ku, Seoul, 135-710, Republic of Korea.,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Soo Hyun Cho
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-ku, Seoul, 135-710, Republic of Korea.,Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea
| | - Seung Joo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-ku, Seoul, 135-710, Republic of Korea.,Department of Neurology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Korea
| | - Yeshin Kim
- Department of Neurology, Kangwon National University Hospital, Kangwon National University College of Medicine, Chuncheon, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-ku, Seoul, 135-710, Republic of Korea.,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University Mokdong Hospital, Ewha Womans University School of Medicine, Seoul, Korea
| | - Soo Jin Yoon
- Department of Neurology, Eulji University Hospital, Eulji University School of Medicine, Daejeon, Korea
| | - Kyung Won Park
- Department of Neurology, Dong-A Medical Center, Dong-A University College of Medicine, Busan, Korea
| | - Eun-Joo Kim
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Korea
| | - Na Yeon Jung
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Research Institute for Convergence of Biomedical Science and Technology, Yangsan, Korea
| | - Bora Yoon
- Department of Neurology, Konyang University College of Medicine, Daejeon, Korea
| | - Jae-Won Jang
- Department of Neurology, Kangwon National University Hospital, Kangwon National University College of Medicine, Chuncheon, Korea
| | - Jin Yong Hong
- Department of Neurology, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Jihye Hwang
- Department of Neurology, Keimyung University Daegu Dongsan Hospital, Daegu, Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-ku, Seoul, 135-710, Republic of Korea.,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea.,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea.,Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, Seoul, Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-ku, Seoul, 135-710, Republic of Korea.,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea.,Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, Korea.,Center for Clinical Epidemiology, Samsung Medical Center, Seoul, Korea
| | - Seong Hye Choi
- Department of Neurology, Inha University School of Medicine, Incheon, Korea.
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-ku, Seoul, 135-710, Republic of Korea. .,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea. .,Neuroscience Center, Samsung Medical Center, Seoul, Korea.
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Hanseeuw BJ, Jonas V, Jackson J, Betensky RA, Rentz DM, Johnson KA, Sperling RA, Donovan NJ. Association of anxiety with subcortical amyloidosis in cognitively normal older adults. Mol Psychiatry 2020; 25:2599-2607. [PMID: 30116029 PMCID: PMC6377864 DOI: 10.1038/s41380-018-0214-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Revised: 05/30/2018] [Accepted: 06/20/2018] [Indexed: 01/05/2023]
Abstract
Late-life anxiety has been associated with increased progression from normal cognition to amnestic MCI, suggesting that anxiety may be a neuropsychiatric symptom of Alzheimer's disease (AD) pathological changes and a possible marker of anatomical progression in preclinical AD. This study examined whether cortical or subcortical amyloidosis, indicating earlier or later stages of preclinical AD, was associated with greater self-reported anxiety among 118 cognitively normal volunteers, aged 65-90 years, and whether this association was stronger in APOEε4 carriers. Participants underwent Pittsburgh Compound B Positron Emission Tomography (PiB-PET) to assess fibrillar amyloid-β burden in cortical and subcortical regions, and measurement of anxiety using the Hospital Anxiety and Depression Scale-anxiety subscale. Higher PiB-PET measures in the subcortex (striatum, amygdala, and thalamus), but not in the cortex, were associated with greater anxiety, adjusting for demographics, cognition, and depression. Findings were similar using a cortico-striatal staging system and continuous PET measurements. Anxiety was highest in APOEε4 carriers with subcortical amyloidosis. This work supports in vivo staging of amyloid-β deposition in both cortical and subcortical regions as a promising approach to the study of neuropsychiatric symptoms such as anxiety in cognitively normal older individuals. Elevated anxiety symptoms in combination with high-risk biological factors such as APOEε4 and subcortical amyloid-β may identify participants closest to MCI for secondary prevention trials.
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Affiliation(s)
- Bernard J. Hanseeuw
- grid.32224.350000 0004 0386 9924Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA ,grid.32224.350000 0004 0386 9924Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA ,grid.7942.80000 0001 2294 713XDepartment of Neurology, Cliniques Universitaires Saint-Luc, Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
| | - Victoria Jonas
- grid.32224.350000 0004 0386 9924Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Jonathan Jackson
- grid.32224.350000 0004 0386 9924Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Rebecca A. Betensky
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115 USA
| | - Dorene M. Rentz
- grid.32224.350000 0004 0386 9924Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA ,Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA ,Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA ,Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Keith A. Johnson
- grid.32224.350000 0004 0386 9924Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA ,grid.32224.350000 0004 0386 9924Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA ,Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Reisa A. Sperling
- grid.32224.350000 0004 0386 9924Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA ,Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA ,Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Nancy J. Donovan
- Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA ,Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA ,Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA ,grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
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The striatum, the hippocampus, and short-term memory binding: Volumetric analysis of the subcortical grey matter's role in mild cognitive impairment. NEUROIMAGE-CLINICAL 2019; 25:102158. [PMID: 31918064 PMCID: PMC7036699 DOI: 10.1016/j.nicl.2019.102158] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 12/27/2019] [Accepted: 12/28/2019] [Indexed: 12/14/2022]
Abstract
Hippocampal atrophy plays no role in short-term memory binding. The globus pallidus could be part of the brain network supporting binding. Total brain atrophy does not correlate with striatal grey matter atrophy in MCI. Striatal grey matter atrophy reflects in total brain atrophy in controls. Hippocampal and parahippocampal volumes correlate in MCI and controls.
Background Deficits in short-term memory (STM) binding are a distinguishing feature of preclinical stages leading to Alzheimer's disease (AD). However, the neuroanatomical correlates of conjunctive STM binding are largely unexplored. Here we examine the possible association between the volumes of hippocampi, parahippocampal gyri, and grey matter within the subcortical structures – all found to have foci that seemingly correlate with basic daily living activities in AD patients - with cognitive tests related to conjunctive STM binding. Materials and methods Hippocampal, thalamic, parahippocampal and corpus striatum volumes were semi-automatically quantified in brain magnetic resonance images from 25 cognitively normal people and 21 patients with Mild Cognitive Impairment (MCI) at high risk of AD progression, who undertook a battery of cognitive tests and the short-term memory binding test. Associations were assessed using linear regression models and group differences were assessed using the Mann-Whitney U test. Results Hippocampal and parahippocampal gyrus volumes differed between MCI and control groups. Although the grey matter volume in the globus pallidus (r = -0.71, p < 0.001) and parahippocampal gyry (r = -0.63, p < 0.05) correlated with a STM binding task in the MCI group, only the former remained associated with STM binding deficits in MCI patients, after correcting for age, gender and years of education (β = -0.56,P = 0.042) although with borderline significance. Conclusions Loss of hippocampal volume plays no role in the processing of STM binding. Structures within the basal ganglia, namely the globus pallidus, could be part of the extrahippocampal network supporting binding. Replication of this study in large samples is now needed.
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Kim JP, Kim J, Kim Y, Moon SH, Park YH, Yoo S, Jang H, Kim HJ, Na DL, Seo SW, Seong JK. Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes. Eur J Nucl Med Mol Imaging 2019; 47:1971-1983. [PMID: 31884562 PMCID: PMC7299909 DOI: 10.1007/s00259-019-04663-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Accepted: 12/16/2019] [Indexed: 01/18/2023]
Abstract
Purpose We developed a machine learning–based classifier for in vivo amyloid positron emission tomography (PET) staging, quantified cortical uptake of the PET tracer by using a machine learning method, and investigated the impact of these amyloid PET parameters on clinical and structural outcomes. Methods A total of 337 18F-florbetaben PET scans obtained at Samsung Medical Center were assessed. We defined a feature vector representing the change in PET tracer uptake from grey to white matter. Using support vector machine (SVM) regression and SVM classification, we quantified the cortical uptake as predicted regional cortical tracer uptake (pRCTU) and categorised the scans as positive and negative. Positive scans were further classified into two stages according to the striatal uptake. We compared outcome parameters among stages and further assessed the association between the pRCTU and outcome variables. Finally, we performed path analysis to determine mediation effects between PET variables. Results The classification accuracy was 97.3% for cortical amyloid positivity and 91.1% for striatal positivity. The left frontal and precuneus/posterior cingulate regions, as well as the anterior portion of the striatum, were important in determination of stages. The clinical scores and magnetic resonance imaging parameters showed negative associations with PET stage. However, except for the hippocampal volume, most outcomes were associated with the stage through the complete mediation effect of pRCTU. Conclusion Using a machine learning algorithm, we achieved high accuracy for in vivo amyloid PET staging. The in vivo amyloid stage was associated with cognitive function and cerebral atrophy mostly through the mediation effect of cortical amyloid. Electronic supplementary material The online version of this article (10.1007/s00259-019-04663-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Seoul, South Korea.,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Jeonghun Kim
- Department of Bio-convergence Engineering, Korea University, Seoul, South Korea
| | - Yeshin Kim
- Department of Neurology, Kangwon National University Hospital, Chuncheon, South Korea
| | - Seung Hwan Moon
- Department of Nuclear Medicine, Samsung Medical Center, Seoul, South Korea
| | - Yu Hyun Park
- Department of Neurology, Samsung Medical Center, Seoul, South Korea.,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, South Korea
| | - Sole Yoo
- Department of Cognitive Science, Yonsei University, Seoul, South Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Seoul, South Korea.,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Seoul, South Korea.,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Seoul, South Korea.,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea.,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Seoul, South Korea. .,Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, South Korea. .,Neuroscience Center, Samsung Medical Center, Seoul, South Korea. .,Department of Clinical Research Design & Evaluation, SAIHST, Sungkyunkwan University, Seoul, South Korea. .,Center for Clinical Epidemiology, Samsung Medical Center, Seoul, South Korea.
| | - Joon-Kyung Seong
- Department of Bio-convergence Engineering, Korea University, Seoul, South Korea. .,School of Biomedical Engineering, Korea University, Seoul, South Korea. .,Department of Artificial Intelligence, Korea University, Seoul, South Korea.
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80
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Fantoni E, Collij L, Lopes Alves I, Buckley C, Farrar G. The Spatial-Temporal Ordering of Amyloid Pathology and Opportunities for PET Imaging. J Nucl Med 2019; 61:166-171. [PMID: 31836683 DOI: 10.2967/jnumed.119.235879] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 12/03/2019] [Indexed: 12/24/2022] Open
Abstract
Although clinical routine focuses on dichotomous and visual interpretation of amyloid PET, regional image assessment in research settings may yield additional opportunities. Understanding the regional-temporal evolution of amyloid pathology may enable earlier identification of subjects in the Alzheimer Disease pathologic continuum, as well as a finer-grained assessment of pathology beyond traditional dichotomous measures. This review summarizes current research in the detection of regional amyloid deposition patterns and its potential for staging amyloid pathology. Pathology studies, cross-sectional and longitudinal PET-only studies, and comparative PET and autopsy studies are included. Despite certain differences, cortical deposition generally precedes striatal pathology, and in PET-only studies, medial cortical regions are seen to accumulate amyloid earlier than lateral regions. Based on regional amyloid PET, multiple studies have developed and implemented models for staging amyloid pathology that could improve subject selection into secondary prevention trials and visual assessment in clinical routine.
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Affiliation(s)
- Enrico Fantoni
- Pharmaceutical Diagnostics, GE Healthcare, Chalfont St. Giles, Buckinghamshire, United Kingdom; and
| | - Lyduine Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Christopher Buckley
- Pharmaceutical Diagnostics, GE Healthcare, Chalfont St. Giles, Buckinghamshire, United Kingdom; and
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81
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Thal DR, Ronisz A, Tousseyn T, Rijal Upadhaya A, Balakrishnan K, Vandenberghe R, Vandenbulcke M, von Arnim CAF, Otto M, Beach TG, Lilja J, Heurling K, Chakrabarty A, Ismail A, Buckley C, Smith APL, Kumar S, Farrar G, Walter J. Different aspects of Alzheimer's disease-related amyloid β-peptide pathology and their relationship to amyloid positron emission tomography imaging and dementia. Acta Neuropathol Commun 2019; 7:178. [PMID: 31727169 PMCID: PMC6854805 DOI: 10.1186/s40478-019-0837-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 10/28/2019] [Indexed: 11/16/2022] Open
Abstract
Alzheimer’s disease (AD)-related amyloid β-peptide (Aβ) pathology in the form of amyloid plaques and cerebral amyloid angiopathy (CAA) spreads in its topographical distribution, increases in quantity, and undergoes qualitative changes in its composition of modified Aβ species throughout the pathogenesis of AD. It is not clear which of these aspects of Aβ pathology contribute to AD progression and to what extent amyloid positron emission tomography (PET) reflects each of these aspects. To address these questions three cohorts of human autopsy cases (in total n = 271) were neuropathologically and biochemically examined for the topographical distribution of Aβ pathology (plaques and CAA), its quantity and its composition. These parameters were compared with neurofibrillary tangle (NFT) and neuritic plaque pathology, the degree of dementia and the results from [18F]flutemetamol amyloid PET imaging in cohort 3. All three aspects of Aβ pathology correlated with one another, the estimation of Aβ pathology by [18F]flutemetamol PET, AD-related NFT pathology, neuritic plaques, and with the degree of dementia. These results show that one aspect of Aβ pathology can be used to predict the other two, and correlates well with the development of dementia, advancing NFT and neuritic plaque pathology. Moreover, amyloid PET estimates all three aspects of Aβ pathology in-vivo. Accordingly, amyloid PET-based estimates for staging of amyloid pathology indicate the progression status of amyloid pathology in general and, in doing so, also of AD pathology. Only 7.75% of our cases deviated from this general association.
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82
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Matsuda H, Shigemoto Y, Sato N. Neuroimaging of Alzheimer's disease: focus on amyloid and tau PET. Jpn J Radiol 2019; 37:735-749. [PMID: 31493197 DOI: 10.1007/s11604-019-00867-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 08/28/2019] [Indexed: 12/14/2022]
Abstract
Although the diagnosis of dementia is still largely a clinical one, based on history and disease course, neuroimaging has dramatically increased our ability to accurately diagnose it. Neuroimaging modalities now play a wider role in dementia beyond their traditional role of excluding neurosurgical lesions and are recommended in most clinical guidelines for dementia. In addition, new neuroimaging methods facilitate the diagnosis of most neurodegenerative conditions after symptom onset and show diagnostic promise even in the very early or presymptomatic phases of some diseases. In the case of Alzheimer's disease (AD), extracellular amyloid-β (Aβ) aggregates and intracellular tau neurofibrillary tangles are the two neuropathological hallmarks of the disease. Recent molecular imaging techniques using amyloid and tau PET ligands have led to preclinical diagnosis and improved differential diagnosis as well as narrowed subject selection and treatment monitoring in clinical trials aimed at delaying or preventing the symptomatic phase of AD. This review discusses the recent progress in amyloid and tau PET imaging and the key findings achieved by the use of this molecular imaging modality related to the respective roles of Aβ and tau in AD, as well as its specific limitations.
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Affiliation(s)
- Hiroshi Matsuda
- Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi, Kodaira, Tokyo, 187-8551, Japan.
| | - Yoko Shigemoto
- Department of Radiology, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi, Kodaira, Tokyo, 187-8551, Japan
| | - Noriko Sato
- Department of Radiology, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi, Kodaira, Tokyo, 187-8551, Japan
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83
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Spallazzi M, Barocco F, Michelini G, Immovilli P, Taga A, Morelli N, Ruffini L, Caffarra P. CSF biomarkers and amyloid PET: concordance and diagnostic accuracy in a MCI cohort. Acta Neurol Belg 2019; 119:445-452. [PMID: 30847669 DOI: 10.1007/s13760-019-01112-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 02/27/2019] [Indexed: 02/07/2023]
Abstract
Brain amyloid deposition is one of the main hallmarks of Alzheimer's disease (AD) and two approaches are available for assessing amyloid pathology in vivo: cerebrospinal fluid (CSF) biomarkers levels and amyloid load visualized by amyloid beta positron emission tomography imaging (Amy-PET) probes. We aimed to investigate the concordance between CSF biomarkers and Amy-PET in a memory clinic cohort. Moreover, using a proper clinical follow-up, we wanted to assess the diagnostic accuracy of CSF and PET biomarkers in predicting the progression of patients with mild cognitive impairment (MCI) to AD dementia. We included 31 MCI patients who underwent [18F]florbetaben PET and CSF sampling (Aβ1-42, t-Tau, p-Tau). A semiquantitative visual scan assessment was used to quantify amyloid deposition in 5 brain regions, rating from 1 (negative), to 2 and 3 (positive). CSF biomarkers were considered abnormal if: Aβ1-42 < 600 pg/ml, p-Tau/Aβ1-42 > 0.08 and t-Tau/Aβ1-42 > 0.52. We also applied less lenient cutoffs of 550 pg/ml and 450 pg/ml for Aβ1-42. The concordance rate was 77% between Amy-PET and CSF Aβ1-42 levels, and 89% between Amy-PET and p-Tau/Aβ1-42 and t-Tau/Aβ1-42. According to the clinical follow-up, Amy-PET (sensitivity [SE] 93.7%, specificity [SP] 80%) exhibited the best diagnostic accuracy in discriminating AD from non-AD, followed by p-Tau/Aβ1-42 ratio and t-Tau/Aβ1-42 ratio (SE 93.7%, SP 66.6%), and Aβ1-42 levels (SE 81%, SP 60%). The regional uptake of [18F]florbetaben PET in the precuneus and the striatum showed the best SP (86.6%). In discordant cases, the clinical diagnosis was most often in agreement with PET results. In general, concordance between CSF biomarkers and Amy-PET was good, especially when the ratios between CSF amyloid and Tau biomarkers were used. However, Amy-PET proved to be superior to CSF Aβ1-42 in terms of diagnostic accuracy for AD, with the possibility to further increase its specificity by focusing the analysis in specific areas such as the precuneus/posterior cingulate cortex and the striatum.
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Affiliation(s)
- Marco Spallazzi
- Department of Medicine and Surgery, Section of Neurology, Azienda Ospedaliero-Universitaria, Via Gramsci, 14, 43126, Parma, Italy.
| | | | | | - Paolo Immovilli
- Department of Neurology, Guglielmo da Saliceto Hospital, Piacenza, Italy
| | - Arens Taga
- Department of Medicine and Surgery, Section of Neurology, Azienda Ospedaliero-Universitaria, Via Gramsci, 14, 43126, Parma, Italy
| | - Nicola Morelli
- Department of Neurology, Guglielmo da Saliceto Hospital, Piacenza, Italy
| | - Livia Ruffini
- Nuclear Medicine Department, Azienda Ospedaliero-Universitaria, Parma, Italy
| | - Paolo Caffarra
- Department of Medicine and Surgery, Section of Neurology, Azienda Ospedaliero-Universitaria, Via Gramsci, 14, 43126, Parma, Italy
- Alzheimer Center, Briolini Hospital, Gazzaniga, Bergamo, Italy
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84
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Subcortical amyloid relates to cortical morphology in cognitively normal individuals. Eur J Nucl Med Mol Imaging 2019; 46:2358-2369. [DOI: 10.1007/s00259-019-04446-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Accepted: 07/16/2019] [Indexed: 11/25/2022]
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85
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Meyer PF, McSweeney M, Gonneaud J, Villeneuve S. AD molecular: PET amyloid imaging across the Alzheimer's disease spectrum: From disease mechanisms to prevention. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2019; 165:63-106. [PMID: 31481172 DOI: 10.1016/bs.pmbts.2019.05.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The advent of amyloid-beta (Aβ) positron emission tomography (PET) imaging has transformed the field of Alzheimer's disease (AD) by enabling the quantification of cortical Aβ accumulation and propagation in vivo. This revolutionary tool has made it possible to measure direct associations between Aβ and other AD biomarkers, to identify factors that influence Aβ accumulation and to redefine entry criteria into clinical trials as well as measure drug target engagement. This chapter summarizes the main findings on the associations of Aβ with other biomarkers of disease progression across the AD spectrum. It discusses investigations of the timing at which Aβ pathology starts to accumulate, demonstrates the clinical utility of Aβ PET imaging and discusses some ethical implications. Finally, it presents genetic and potentially modifiable lifestyle factors that might influence Aβ accumulation and therefore be targets for AD prevention.
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Affiliation(s)
- Pierre-François Meyer
- Centre for Studies on the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montréal, Canada; McGill University, Montréal, Canada
| | - Melissa McSweeney
- Centre for Studies on the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montréal, Canada; McGill University, Montréal, Canada
| | - Julie Gonneaud
- Centre for Studies on the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montréal, Canada; McGill University, Montréal, Canada
| | - Sylvia Villeneuve
- Centre for Studies on the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montréal, Canada; McGill University, Montréal, Canada.
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86
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Rahayel S, Bocti C, Sévigny Dupont P, Joannette M, Lavallée MM, Nikelski J, Chertkow H, Joubert S. Subcortical amyloid load is associated with shape and volume in cognitively normal individuals. Hum Brain Mapp 2019; 40:3951-3965. [PMID: 31148327 DOI: 10.1002/hbm.24680] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 05/09/2019] [Accepted: 05/21/2019] [Indexed: 01/18/2023] Open
Abstract
Amyloid-beta (Aβ) deposition is one of the main hallmarks of Alzheimer's disease. The study assessed the associations between cortical and subcortical 11 C-Pittsburgh Compound B (PiB) retention, namely, in the hippocampus, amygdala, putamen, caudate, pallidum, and thalamus, and subcortical morphology in cognitively normal individuals. We recruited 104 cognitive normal individuals who underwent extensive neuropsychological assessment, PiB-positron emission tomography (PET) scan, and 3-T magnetic resonance imaging (MRI) acquisition of T1-weighted images. Global, cortical, and subcortical regional PiB retention values were derived from each scan and subcortical morphology analyses were performed to investigate vertex-wise local surface and global volumes, including the hippocampal subfields volumes. We found that subcortical regional Aβ was associated with the surface of the hippocampus, thalamus, and pallidum, with changes being due to volume and shape. Hippocampal Aβ was marginally associated with volume of the whole hippocampus as well as with the CA1 subfield, subiculum, and molecular layer. Participants showing higher subcortical Aβ also showed worse cognitive performance and smaller hippocampal volumes. In contrast, global and cortical PiB uptake did not associate with any subcortical metrics. This study shows that subcortical Aβ is associated with subcortical surface morphology in cognitively normal individuals. This study highlights the importance of quantifying subcortical regional PiB retention values in these individuals.
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Affiliation(s)
- Shady Rahayel
- Department of Psychology, Université de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
| | - Christian Bocti
- Department of Neurology, Université de Sherbrooke, Sherbrooke, Canada
| | - Pénélope Sévigny Dupont
- Department of Psychology, Université de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
| | - Maude Joannette
- Department of Psychology, Université de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
| | - Marie Maxime Lavallée
- Department of Psychology, Université de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
| | - Jim Nikelski
- Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Canada
| | - Howard Chertkow
- Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Sven Joubert
- Department of Psychology, Université de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
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87
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Farrar G, Molinuevo JL, Zanette M. Is there a difference in regional read [ 18F]flutemetamol amyloid patterns between end-of-life subjects and those with amnestic mild cognitive impairment? Eur J Nucl Med Mol Imaging 2019; 46:1299-1308. [PMID: 30863934 PMCID: PMC6486895 DOI: 10.1007/s00259-019-04282-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 02/04/2019] [Indexed: 02/04/2023]
Abstract
PURPOSE Visual interpretation of PET [18F]flutemetamol images relies on systematic review of five brain regions and is considered positive when an elevated signal is observed in at least one region. Amnestic mild cognitive impairment (aMCI) is an early clinical presentation of Alzheimer's disease (AD); hence it is of interest to determine if the pattern of visually read regional positivity between end-of-life (EoL) patients with and without dementia and aMCI patients is different. METHODS A total of 180 EoL patients with and without dementia (mean age 81 years, range 59 to 95 years) and 232 aMCI patients (mean age 71 years, range 53 to 91 years) were scanned following intravenous administration of 185-370 MBq [18F]flutemetamol. Images from both studies were read by two groups of five blinded readers who independently classified each of the five regions as either positive or negative. The majority interpretation made by at least three of the five readers was used as the imaging endpoint and compared with a composite standardized uptake value ratio (SUVR) analysis using a predetermined threshold. RESULTS Amyloid-positive images from 71 of 106 EoL patients coming to autopsy and from 97 aMCI patients were included. In the images from the EoL patients widespread deposition of amyloid was observed, with 76% of the images positive in all five regions and a further 20% positive in four regions. In the images from the aMCI patients, similar results were observed with 87% of the images positive in five regions and a further 5% positive in four regions. The mean SUVR of these positively read images was 2.24 (range 1.48 to 3.14) and 2.08 (range 1.28 to 3.04) in the autopsy and aMCI groups, respectively. There was 95.3% agreement between the visual reading and SUVR quantitation in the aMCI group and 90.4% agreement in the autopsy group. CONCLUSION Patients with aMCI showed a similar distribution of amyloid deposition determined by both visual reading and SUVR to that observed in patients with and without dementia coming to autopsy. Most of the aMCI patients, who are already within the AD continuum, had widespread amyloid deposition in terms of amount and topographical progression. Attempts to observe potential initial signs of amyloid deposition should focus on populations earlier in the dementia spectrum such as patients with subjective cognitive decline or even at-risk subjects with earlier stages of disease.
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Affiliation(s)
| | - José Luis Molinuevo
- Barcelona Beta Brain Research Center, Pasqual Maragall Foundation and Hospital Clinic I Universitari, IDIBAPS, Barcelona, Spain
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88
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Striatal amyloid is associated with tauopathy and memory decline in familial Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2019; 11:17. [PMID: 30717814 PMCID: PMC6362587 DOI: 10.1186/s13195-019-0468-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 01/14/2019] [Indexed: 01/15/2023]
Abstract
Background Autosomal dominant Alzheimer’s disease (ADAD) is distinguished from late-onset AD by early striatal amyloid-β deposition. To determine whether striatal Pittsburgh compound B (PiB)-PET measurements of amyloid-β can help predict disease severity in ADAD, we compared relationships of striatal and neocortical PiB-PET to age, tau-PET, and memory performance in the Colombian Presenilin 1 E280A kindred. Methods Fourteen carriers (age = 28–42, Mini-Mental State Examination = 26–30) and 20 age-matched non-carriers were evaluated using PiB, flortaucipir (FTP; tau), and memory testing (CERAD Word List Learning). PiB-PET signal was measured in neocortical and striatal aggregates. FTP-PET signal was measured in entorhinal cortex. Results Compared to non-carriers, mutation carriers had age-related elevations in both neocortical and striatal PiB binding. The PiB elevation in carriers was significantly greater in the striatum than in the neocortex. In mutation carriers, PiB binding in both the neocortex and the striatum is related to entorhinal FTP; however, the association was stronger with the striatum. Only striatal PiB was associated with worse memory. Remarkably, PiB binding in the striatum, but not in the neocortex, predicted entorhinal FTP and lower memory scores after adjusting for age, indicating that striatal PiB identified the carriers with the most severe disease. Conclusions Based on these preliminary cross-sectional findings, striatal PiB-PET measurements may offer particular value in the detection and tracking of preclinical ADAD, informing a mutation carrier’s prognosis and evaluating amyloid-β-modifying ADAD treatments.
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89
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Thal DR, Beach TG, Zanette M, Lilja J, Heurling K, Chakrabarty A, Ismail A, Farrar G, Buckley C, Smith APL. Estimation of amyloid distribution by [ 18F]flutemetamol PET predicts the neuropathological phase of amyloid β-protein deposition. Acta Neuropathol 2018; 136:557-567. [PMID: 30123935 PMCID: PMC6132944 DOI: 10.1007/s00401-018-1897-9] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 08/08/2018] [Accepted: 08/09/2018] [Indexed: 10/28/2022]
Abstract
The deposition of the amyloid β-protein (Aβ) in senile plaques is one of the histopathological hallmarks of Alzheimer's disease (AD). Aβ-plaques arise first in neocortical areas and, then, expand into further brain regions in a process described by 5 phases. Since it is possible to identify amyloid pathology with radioactive-labeled tracers by positron emission tomography (PET) the question arises whether it is possible to distinguish the neuropathological Aβ-phases with amyloid PET imaging. To address this question we reassessed 97 cases of the end-of-life study cohort of the phase 3 [18F]flutemetamol trial (ClinicalTrials.gov identifiers NCT01165554, and NCT02090855) by combining the standardized uptake value ratios (SUVRs) with pons as reference region for cortical and caudate nucleus-related [18F]flutemetamol-retention. We tested them for their prediction of the neuropathological pattern found at autopsy. By defining threshold levels for cortical and caudate nucleus SUVRs we could distinguish different levels of [18F]flutemetamol uptake termed PET-Aβ phase estimates. When comparing these PET-Aβ phase estimates with the neuropathological Aβ-phases we found that PET-Aβ phase estimate 0 corresponded with Aβ-phases 0-2, 1 with Aβ-phase 3, 2 with Aβ-phase 4, and 3 with Aβ-phase 5. Classification using the PET-Aβ phase estimates predicted the correct Aβ-phase in 72.16% of the cases studied here. Bootstrap analysis was used to confirm the robustness of the estimates around this association. When allowing a range of ± 1 phase for a given Aβ-phase correct classification was given in 96.91% of the cases. In doing so, we provide a novel method to convert SUVR-levels into PET-Aβ phase estimates that can be easily translated into neuropathological phases of Aβ-deposition. This method allows direct conclusions about the pathological distribution of amyloid plaques (Aβ-phases) in vivo. Accordingly, this method may be ideally suited to detect early preclinical AD-patients, to follow them with disease progression, and to provide a more precise prognosis for them based on the knowledge about the underlying pathological phase of the disease.
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90
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Van Hooren RWE, Riphagen JM, Jacobs HIL. Inter-network connectivity and amyloid-beta linked to cognitive decline in preclinical Alzheimer's disease: a longitudinal cohort study. Alzheimers Res Ther 2018; 10:88. [PMID: 30153858 PMCID: PMC6114059 DOI: 10.1186/s13195-018-0420-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Accepted: 08/07/2018] [Indexed: 02/07/2023]
Abstract
BACKGROUND Amyloid-beta (Aβ) has a dose-response relationship with cognition in healthy adults. Additionally, the levels of functional connectivity within and between brain networks have been associated with cognitive performance in healthy adults. Aiming to explore potential synergistic effects, we investigated the relationship of inter-network functional connectivity, Aβ burden, and memory decline among healthy individuals and individuals with preclinical, prodromal, or clinical Alzheimer's disease. METHODS In this longitudinal cohort study (ADNI2), participants (55-88 years) were followed for a maximum of 5 years. We included cognitively healthy participants and patients with mild cognitive impairment (with or without elevated Aβ) or Alzheimer's disease. Associations between memory decline, Aβ burden, and connectivity between networks across the groups were investigated using linear and curvilinear mixed-effects models. RESULTS We found a synergistic relationships between inter-network functional connectivity and Aβ burden on memory decline. Dose-response relationships between Aβ and memory decline varied as a function of directionality of inter-network connectivity across groups. When inter-network correlations were negative, the curvilinear mixed-effects models revealed that higher Aβ burden was associated with greater memory decline in cognitively normal participants, but when inter-network correlations were positive, there was no association between the magnitude of Aβ burden and memory decline. Opposite patterns were observed in patients with mild cognitive impairment. Combining negative inter-network correlations with Aβ burden can reduce the required sample size by 88% for clinical trials aiming to slow down memory decline. CONCLUSIONS The direction of inter-network connectivity provides additional information about Aβ burden on the rate of expected memory decline, especially in the preclinical phase. These results may be valuable for optimizing patient selection and decreasing study times to assess efficacy in clinical trials.
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Affiliation(s)
- Roy W. E. Van Hooren
- Faculty of Health, Medicine and Life Sciences; School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Alzheimer Center Limburg, Maastricht University, Dr. Tanslaan 12, 6229 ET Maastricht, the Netherlands
| | - Joost M. Riphagen
- Faculty of Health, Medicine and Life Sciences; School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Alzheimer Center Limburg, Maastricht University, Dr. Tanslaan 12, 6229 ET Maastricht, the Netherlands
- Department of Anesthesiology, Sankt-Willibrord Spital, Emmerich, Germany
| | - Heidi I. L. Jacobs
- Faculty of Health, Medicine and Life Sciences; School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Alzheimer Center Limburg, Maastricht University, Dr. Tanslaan 12, 6229 ET Maastricht, the Netherlands
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA USA
| | - For the Alzheimer’s Disease Neuroimaging Initiative
- Faculty of Health, Medicine and Life Sciences; School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Alzheimer Center Limburg, Maastricht University, Dr. Tanslaan 12, 6229 ET Maastricht, the Netherlands
- Department of Anesthesiology, Sankt-Willibrord Spital, Emmerich, Germany
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA USA
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Cho SH, Shin JH, Jang H, Park S, Kim HJ, Kim SE, Kim SJ, Kim Y, Lee JS, Na DL, Lockhart SN, Rabinovici GD, Seong JK, Seo SW. Amyloid involvement in subcortical regions predicts cognitive decline. Eur J Nucl Med Mol Imaging 2018; 45:2368-2376. [PMID: 29980831 DOI: 10.1007/s00259-018-4081-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2018] [Accepted: 06/25/2018] [Indexed: 01/31/2023]
Abstract
PURPOSE We estimated whether amyloid involvement in subcortical regions may predict cognitive impairment, and established an amyloid staging scheme based on degree of subcortical amyloid involvement. METHODS Data from 240 cognitively normal older individuals, 393 participants with mild cognitive impairment, and 126 participants with Alzheimer disease were acquired at Alzheimer's Disease Neuroimaging Initiative sites. To assess subcortical involvement, we analyzed amyloid deposition in amygdala, putamen, and caudate nucleus. We staged participants into a 3-stage model based on cortical and subcortical amyloid involvement: 382 with no cortical or subcortical involvement as stage 0, 165 with cortical but no subcortical involvement as stage 1, and 203 with both cortical and subcortical involvement as stage 2. RESULTS Amyloid accumulation was first observed in cortical regions and spread down to the putamen, caudate nucleus, and amygdala. In longitudinal analysis, changes in MMSE, ADAS-cog 13, FDG PET SUVR, and hippocampal volumes were steepest in stage 2 followed by stage 1 then stage 0 (p value <0.001). Stage 2 showed steeper changes in MMSE score (β [SE] = -0.02 [0.004], p < 0.001), ADAS-cog 13 (0.05 [0.01], p < 0.001), FDG PET SUVR (-0.0008 [0.0003], p = 0.004), and hippocampal volumes (-4.46 [0.65], p < 0.001) compared to stage 1. CONCLUSIONS We demonstrated a downward spreading pattern of amyloid, suggesting that amyloid accumulates first in neocortex followed by subcortical structures. Furthermore, our new finding suggested that an amyloid staging scheme based on subcortical involvement might reveal how differential regional accumulation of amyloid affects cognitive decline through functional and structural changes of the brain.
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Affiliation(s)
- Soo Hyun Cho
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Jeong-Hyeon Shin
- School of Biomedical Engineering, Korea University, Seoul, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Seongbeom Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Si Eun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Seung Joo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Yeshin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Jin San Lee
- Department of Neurology, Kyung Hee University Hospital, Seoul, South Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea.,Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, Seoul, South Korea.,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Samuel N Lockhart
- Internal Medicine - Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, 27101, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Joon-Kyung Seong
- School of Biomedical Engineering, Korea University, Seoul, Republic of Korea.
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea. .,Neuroscience Center, Samsung Medical Center, Seoul, South Korea. .,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea. .,Department of Clinical Research Design & Evaluation, SAIHST, Sungkyunkwan University, Seoul, South Korea.
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