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      Association of Amyloid and Tau With Cognition in Preclinical Alzheimer Disease : A Longitudinal Study

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Key Points

          Question

          Is cognitive decline associated with amyloid-β or tau tangles accumulation?

          Findings

          In this cohort study that included 60 normal older adults with repeated positron emission tomography measures, the rate of tau accumulation in the inferior temporal neocortex was associated with the rate of cognitive decline. Amyloid accumulation was associated with subsequent tau accumulation, and this sequence of successive amyloid and tau changes in neocortex was found to mediate the association of initial amyloid with final cognition, measured 7 years later.

          Meaning

          Amyloid positron emission tomography is useful to detect early Alzheimer pathology; repeated tau positron emission tomography is useful to track disease progression.

          Abstract

          Importance

          Positron emission tomography (PET) imaging now allows in vivo visualization of both neuropathologic hallmarks of Alzheimer disease (AD): amyloid-β (Aβ) plaques and tau neurofibrillary tangles. Observing their progressive accumulation in the brains of clinically normal older adults is critically important to understand the pathophysiologic cascade leading to AD and to inform the choice of outcome measures in prevention trials.

          Objective

          To assess the associations among Aβ, tau, and cognition, measured during different observation periods for 7 years.

          Design, Setting, and Participants

          Prospective cohort study conducted between 2010 and 2017 at the Harvard Aging Brain Study, Boston, Massachusetts. The study enrolled 279 clinically normal participants. An additional 90 individuals were approached but declined the study or did not meet the inclusion criteria. In this report, we analyzed data from 60 participants who had multiple Aβ and tau PET observations available on October 31, 2017.

          Main Outcomes and Measures

          A median of 3 Pittsburgh compound B–PET (Aβ, 2010-2017) and 2 flortaucipir-PET (tau, 2013-2017) images were collected. We used initial PET and slope data, assessing the rates of change in Aβ and tau, to measure cognitive changes. Cognition was evaluated annually using the Preclinical Alzheimer Cognitive Composite (2010-2017). Annual consensus meetings evaluated progression to mild cognitive impairment.

          Results

          Of the 60 participants, 35 were women (58%) and 25 were men (42%); median age at inclusion was 73 years (range, 65-85 years). Seventeen participants (28%) exhibited an initial high Aβ burden. An antecedent rise in Aβ was associated with subsequent changes in tau (1.07 flortaucipir standardized uptake value ratios [SUVr]/PiB-SUVr; 95% CI, 0.13-3.46; P = .02). Tau changes were associated with cognitive changes (−3.28 z scores/SUVR; 95% CI, −6.67 to −0.91; P = .001), covarying baseline Aβ and tau. Tau changes were greater in the participants who progressed to mild cognitive impairment (n = 6) than in those who did not (n = 11; 0.05 SUVr per year; 95% CI, 0.03-0.07; P = .001). A serial mediation model demonstrated that the association between initial Aβ and final cognition, measured 7 years later, was mediated by successive changes in Aβ and tau.

          Conclusions and Relevance

          We identified sequential changes in normal older adults, from Aβ to tau to cognition, after which the participants with high Aβ with greater tau increase met clinical criteria for mild cognitive impairment. These findings highlight the importance of repeated tau-PET observations to track disease progression and the importance of repeated amyloid-PET observations to detect the earliest AD pathologic changes.

          Abstract

          This cohort study assesses the associations among amyloid-β, tau, and cognition, measured during different observation periods for 7 years.

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          Most cited references19

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          Longitudinal tau PET in ageing and Alzheimer’s disease

          See Hansson and Mormino (doi:10.1093/brain/awy065) for a scientific commentary on this article. Where should measurements be taken to best capture tau accumulation in ageing and Alzheimer’s disease? Jack et al. report that in clinically symptomatic stages of Alzheimer’s disease, tau accumulation occurs throughout the brain, rather than only in specific areas. Rate measurements from simple meta-regions of interest may be sufficient to capture progressive within-person tau accumulation.
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            Measurement of longitudinal β-amyloid change with 18F-florbetapir PET and standardized uptake value ratios.

            The accurate measurement of β-amyloid (Aβ) change using amyloid PET imaging is important for Alzheimer disease research and clinical trials but poses several unique challenges. In particular, reference region measurement instability may lead to spurious changes in cortical regions of interest. To optimize our ability to measure (18)F-florbetapir longitudinal change, we evaluated several candidate regions of interest and their influence on cortical florbetapir change over a 2-y period in participants from the Alzheimer Disease Neuroimaging Initiative (ADNI).
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              Phases of Hyperconnectivity and Hypoconnectivity in the Default Mode and Salience Networks Track with Amyloid and Tau in Clinically Normal Individuals.

              Alzheimer's disease (AD) is characterized by two hallmark molecular pathologies: amyloid aβ1-42 and Tau neurofibrillary tangles. To date, studies of functional connectivity MRI (fcMRI) in individuals with preclinical AD have relied on associations with in vivo measures of amyloid pathology. With the recent advent of in vivo Tau-PET tracers it is now possible to extend investigations on fcMRI in a sample of cognitively normal elderly humans to regional measures of Tau. We modeled fcMRI measures across four major cortical association networks [default-mode network (DMN), salience network (SAL), dorsal attention network, and frontoparietal control network] as a function of global cortical amyloid [Pittsburgh Compound B (PiB)-PET] and regional Tau (AV1451-PET) in entorhinal, inferior temporal (IT), and inferior parietal cortex. Results showed that the interaction term between PiB and IT AV1451 was significantly associated with connectivity in the DMN and salience. The interaction revealed that amyloid-positive (aβ(+)) individuals show increased connectivity in the DMN and salience when neocortical Tau levels are low, whereas aβ(+) individuals demonstrate decreased connectivity in these networks as a function of elevated Tau-PET signal. This pattern suggests a hyperconnectivity phase followed by a hypoconnectivity phase in the course of preclinical AD.SIGNIFICANCE STATEMENT This article offers a first look at the relationship between Tau-PET imaging with F(18)-AV1451 and functional connectivity MRI (fcMRI) in the context of amyloid-PET imaging. The results suggest a nonlinear relationship between fcMRI and both Tau-PET and amyloid-PET imaging. The pattern supports recent conjecture that the AD fcMRI trajectory is characterized by periods of both hyperconnectivity and hypoconnectivity. Furthermore, this nonlinear pattern can account for the sometimes conflicting reports of associations between amyloid and fcMRI in individuals with preclinical Alzheimer's disease.
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                Author and article information

                Journal
                JAMA Neurol
                JAMA Neurol
                JAMA Neurol
                JAMA Neurology
                American Medical Association
                2168-6149
                2168-6157
                3 June 2019
                August 2019
                12 August 2019
                3 June 2019
                : 76
                : 8
                : 915-924
                Affiliations
                [1 ]Department of Radiology, Massachusetts General Hospital, the Gordon Center for Medical Imaging and the Athinoula A. Martinos Center for Biomedical Imaging, Boston
                [2 ]Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
                [3 ]Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
                [4 ]Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
                [5 ]Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, the Netherlands
                [6 ]Department of Neurology and Neurological Sciences, Stanford University, California
                [7 ]Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
                [8 ]The Florey Institute, The University of Melbourne, Victoria, Australia; Melbourne School of Psychological Science, University of Melbourne, Victoria, Australia
                [9 ]Dementia Research Group, BioMedical Research Institute, Hasselt University, Hasselt, Belgium
                [10 ]Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
                [11 ]Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, the Netherlands
                Author notes
                Article Information
                Corresponding Author: Keith Johnson, MD, Massachusetts General Hospital, 55 Fruit St S, Boston, MA 02114 ( kjohnson@ 123456mgh.harvard.edu ).
                Accepted for Publication: April 11, 2019.
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Hanseeuw BJ et al. JAMA Neurology.
                Published Online: June 3, 2019. doi:10.1001/jamaneurol.2019.1424
                Correction: This article was corrected on August 12, 2019, to fix an error in Figure 3.
                Author Contributions: Drs Hanseeuw and Johnson had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Hanseeuw, Betensky, Jacobs, Schultz, Sepulcre, Mormino, Papp, Johnson.
                Acquisition, analysis, or interpretation of data: Hanseeuw, Betensky, Jacobs, Schultz, Sepulcre, Becker, Orozco Cosio, Farrell, Quiroz, Buckley, Amariglio, Dewachter, Ivanoiu, Huijbers, Hedden, Marshall, Chhatwal, Rentz, Sperling, Johnson.
                Drafting of the manuscript: Hanseeuw, Betensky, Mormino, Johnson.
                Critical revision of the manuscript for important intellectual content: Betensky, Jacobs, Schultz, Sepulcre, Becker, Orozco Cosio, Farrell, Quiroz, Buckley, Papp, Amariglio, Dewachter, Ivanoiu, Huijbers, Hedden, Marshall, Chhatwal, Rentz, Sperling, Johnson.
                Statistical analysis: Hanseeuw, Betensky, Jacobs, Schultz, Becker, Mormino, Sperling, Johnson.
                Obtained funding: Hedden, Johnson.
                Administrative, technical, or material support: Becker, Orozco Cosio, Papp, Huijbers, Chhatwal, Sperling, Johnson.
                Supervision: Betensky, Sepulcre, Hedden, Rentz, Sperling, Johnson.
                Conflict of Interest Disclosures: Dr Hanseeuw reported grants from the Belgian National Fund for Scientific Research and the Belgian Foundation for Alzheimer Research during the conduct of the study and personal fees from GE Healthcare outside the submitted work. Dr Jacobs reported funding from the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant agreement (IF-2015-GF, 706714). Dr Becker reported grants from the National Institutes of Health during the conduct of the study. Dr Quiroz reported grants from the National Institutes of Health and the National Institute on Aging during the conduct of the study. Dr Hedden reported grants from the National Institutes of Health during the conduct of the study. Dr Rentz reported other support from Eli Lilly, Neurotrack, and Biogen outside the submitted work. Dr Sperling reported grants from Janssen during the conduct of the study and personal fees from AC Immune, Biogen, and Roche outside the submitted work. Dr Johnson reported grants from the National Institutes of Health; personal fees from Biogen, Lilly/Avid, Merck, Novartis, Takeda, Roche/Genentech, and Janssen; and grants from Alzheimer’s Association and from Alzheimer’s Drug Discovery Foundation during the conduct of the study. No other disclosures were reported.
                Funding/Support: This work was supported with funding from National Institutes of Health grants P01 AG036694 (Drs Sperling and Johnson), R01 AG046396 (Dr Johnson), R01 AG053509 (Dr Hedden), and K23 EB019023 (Dr Sepulcre); the Belgian Fund for Scientific Research (FNRS #SPD 28094292; DrHanseeuw); and the Belgian Foundation for Alzheimer Research (SAO-FRA #P16.008, Hanseeuw). This research was carried out in part at the Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital, using resources provided by Center for Functional Neuroimaging Technologies grant P41EB015896, a P41 Biotechnology Resource Grant supported by the National Institute of Biomedical Imaging and Bioengineering. This work also involved the use of instrumentation supported by the National Institutes of Health Shared Instrumentation Grant Program; specifically, grant numbers S10RR021110, S10RR023401, and S10RR023043.
                Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Article
                noi190037
                10.1001/jamaneurol.2019.1424
                6547132
                31157827
                56d7433a-1743-4bfd-9048-d052561c1456
                Copyright 2019 Hanseeuw BJ et al. JAMA Neurology.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 14 January 2019
                : 11 April 2019
                Funding
                Funded by: National Institutes of Health
                Funded by: Belgian Fund for Scientific Research
                Funded by: Belgian Foundation for Alzheimer Research
                Funded by: Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital
                Funded by: Center for Functional Neuroimaging Technologies
                Funded by: National Institute of Biomedical Imaging and Bioengineering
                Funded by: National Institutes of Health Shared Instrumentation Grant Program
                Categories
                Research
                Research
                Original Investigation
                Online First

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