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      Longitudinal tau PET in ageing and Alzheimer’s disease

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          Abstract

          See Hansson and Mormino (doi: [Related article:]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.

          Abstract

          See Hansson and Mormino (doi: [Related article:]10.1093/brain/awy065) for a scientific commentary on this article.

          Our objective was to compare different whole-brain and region-specific measurements of within-person change on serial tau PET and evaluate its utility for clinical trials. We studied 126 individuals: 59 cognitively unimpaired with normal amyloid, 37 cognitively unimpaired with abnormal amyloid, and 30 cognitively impaired with an amnestic phenotype and abnormal amyloid. All had baseline amyloid PET and two tau PET, MRI, and clinical assessments. We compared the topography across all cortical regions of interest of tau PET accumulation rates and the rates of four different whole-brain or region-specific meta-regions of interest among the three clinical groups. We computed sample size estimates for change in tau PET, cortical volume, and memory/mental status indices for use as outcome measures in clinical trials. The cognitively unimpaired normal amyloid group had no observable tau accumulation throughout the brain. Tau accumulation rates in cognitively unimpaired abnormal amyloid were low [0.006 standardized uptake value ratio (SUVR), 0.5%, per year] but greater than rates in the cognitively unimpaired normal amyloid group in the basal and mid-temporal, retrosplenial, posterior cingulate, and entorhinal regions of interest. Thus, the earliest elevation in accumulation rates was widespread and not confined to the entorhinal cortex. Tau accumulation rates in the cognitively impaired abnormal amyloid group were 0.053 SUVR (3%) per year and greater than rates in cognitively unimpaired abnormal amyloid in all cortical areas except medial temporal. Rates of accumulation in the four meta-regions of interest differed but only slightly from one another. Among all tau PET meta-regions of interest, sample size estimates were smallest for a temporal lobe composite within cognitively unimpaired abnormal amyloid and for the late Alzheimer’s disease meta-region of interest within cognitively impaired abnormal amyloid. The ordering of the sample size estimates by outcome measure was MRI < tau PET < cognitive measures. At a group-wise level, observable rates of short-term serial tau accumulation were only seen in the presence of abnormal amyloid. As disease progressed to clinically symptomatic stages (cognitively impaired abnormal amyloid), observable rates of tau accumulation were seen uniformly throughout the brain providing evidence that tau does not accumulate in one area at a time or in start-stop, stepwise sequence. The information captured by rate measures in different meta-regions of interest, even those with little topographic overlap, was similar. The implication is that rate measurements from simple meta-regions of interest, without the need for Braak-like staging, may be sufficient to capture progressive within-person accumulation of pathologic tau. Tau PET SUVR measures should be an efficient outcome measure in disease-modifying clinical trials.

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          Most cited references21

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          The Mayo Clinic Study of Aging: Design and Sampling, Participation, Baseline Measures and Sample Characteristics

          Background: The objective of this study was to establish a prospective population-based cohort to investigate the prevalence, incidence and risk factors for mild cognitive impairment (MCI) and dementia. Methods: The Olmsted County, Minn., population, aged 70–89 years on October 1, 2004, was enumerated using the Rochester Epidemiology Project. Eligible subjects were randomly selected and invited to participate. Participants underwent a comprehensive in-person evaluation including the Clinical Dementia Rating Scale, a neurological evaluation and neuropsychological testing. A consensus diagnosis of normal cognition, MCI or dementia was made by a panel using previously published criteria. A subsample of subjects was studied via telephone interview. Results: Four hundred and two subjects with dementia were identified from a detailed review of their medical records but were not contacted. At baseline, we successfully evaluated 703 women aged 70–79 years, 769 women aged 80–89 years, 730 men aged 70–79 years and 517 men aged 80–89 years (total n = 2,719). Among the participants, 2,050 subjects were evaluated in person and 669 via telephone. Conclusions: Strengths of the study are that the subjects were randomly selected from a defined population, the majority of the subjects were examined in person, and MCI was defined using published criteria. Here, we report the design and sampling, participation, baseline measures and sample characteristics.
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            Longitudinal change in CSF biomarkers in autosomal-dominant Alzheimer's disease.

            Clinicopathological evidence suggests that the pathology of Alzheimer's disease (AD) begins many years before the appearance of cognitive symptoms. Biomarkers are required to identify affected individuals during this asymptomatic ("preclinical") stage to permit intervention with potential disease-modifying therapies designed to preserve normal brain function. Studies of families with autosomal-dominant AD (ADAD) mutations provide a unique and powerful means to investigate AD biomarker changes during the asymptomatic period. In this biomarker study, we collected cerebrospinal fluid (CSF), plasma, and in vivo amyloid imaging cross-sectional data at baseline in individuals from ADAD families enrolled in the Dominantly Inherited Alzheimer Network. Our study revealed reduced concentrations of CSF amyloid-β1-42 (Aβ1-42) associated with the presence of Aβ plaques, and elevated concentrations of CSF tau, ptau181 (phosphorylated tau181), and VILIP-1 (visinin-like protein-1), markers of neurofibrillary tangles and neuronal injury/death, in asymptomatic mutation carriers 10 to 20 years before their estimated age at symptom onset (EAO) and before the detection of cognitive deficits. When compared longitudinally, however, the concentrations of CSF biomarkers of neuronal injury/death within individuals decreased after their EAO, suggesting a slowing of acute neurodegenerative processes with symptomatic disease progression. These results emphasize the importance of longitudinal, within-person assessment when modeling biomarker trajectories across the course of the disease. If corroborated, this pattern may influence the definition of a positive neurodegenerative biomarker outcome in clinical trials.
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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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                Author and article information

                Journal
                Brain
                Brain
                brainj
                Brain
                Oxford University Press
                0006-8950
                1460-2156
                May 2018
                12 March 2018
                12 March 2018
                : 141
                : 5
                : 1517-1528
                Affiliations
                [1 ]Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
                [2 ]Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
                [3 ]Department of Nuclear Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
                [4 ]Department of Information Technology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
                [5 ]Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
                [6 ]Department of Psychiatry and Psychology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
                Author notes
                Correspondence to: Clifford R. Jack, Jr 200 First St. SW Rochester, MN 55905, USA E-mail: Jack.clifford@ 123456mayo.edu

                See Hansson and Mormino (doi: [Related article:]10.1093/brain/awy065) for a scientific commentary on this article.

                Article
                awy059
                10.1093/brain/awy059
                5917767
                29538647
                042f9543-1829-4f7b-991e-66aecb5e4b71
                © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 27 November 2017
                : 8 January 2018
                : 14 January 2018
                Page count
                Pages: 12
                Funding
                Funded by: NIH 10.13039/100000002
                Award ID: R01 AG011378
                Award ID: R01 AG041851
                Award ID: U01 AG006786
                Award ID: R01 AG034676
                Award ID: R01 NS097495
                Award ID: P50 AG016574
                Categories
                Original Articles

                Neurosciences
                tau pet,brain ageing,alzheimer’s disease,alzheimer’s biomarkers,amyloid pet
                Neurosciences
                tau pet, brain ageing, alzheimer’s disease, alzheimer’s biomarkers, amyloid pet

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