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      PET measurement of longitudinal amyloid load identifies the earliest stages of amyloid-beta accumulation during Alzheimer’s disease progression in Down syndrome

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          Abstract

          Introduction:

          Adults with Down syndrome (DS) are predisposed to Alzheimer’s disease (AD) and reveal early amyloid beta (A β) pathology in the brain. Positron emission tomography (PET) provides an in vivo measure of A β throughout the AD continuum. Due to the high prevalence of AD in DS, there is need for longitudinal imaging studies of A β to better characterize the natural history of A β accumulation, which will aid in the staging of this population for clinical trials aimed at AD treatment and prevention.

          Methods:

          Adults with DS ( N = 79; Mean age (SD) = 42.7 (7.28) years) underwent longitudinal [C-11]Pittsburgh compound B (PiB) PET. Global A β burden was quantified using the amyloid load metric (A β L). Modeled PiB images were generated from the longitudinal A β L data to visualize which regions are most susceptible to A β accumulation in DS. A β L change was evaluated across A β(−), A β-converter, and A β(+) groups to assess longitudinal A β trajectories during different stages of AD-pathology progression. A β L change values were used to identify A β-accumulators within the A β(−) group prior to reaching the A β(+) threshold (previously reported as 20 A β L) which would have resulted in an A β-converter classification. With knowledge of trajectories of A β(−) accumulators, a new cutoff of A β(+) was derived to better identify subthreshold A β accumulation in DS. Estimated sample sizes necessary to detect a 25% reduction in annual A β change with 80% power (alpha 0.01) were determined for different groups of A β-status.

          Results:

          Modeled PiB images revealed the striatum, parietal cortex and precuneus as the regions with earliest detected A β accumulation in DS. The A β(−) group had a mean A β L change of 0.38 (0.58) A β L/year, while the A β-converter and A β(+) groups had change of 2.26 (0.66) and 3.16 (1.34) A β L/year, respectively. Within the A β(−) group, A β-accumulators showed no significant difference in A β L change values when compared to A β-converter and A β(+) groups. An A β(+) cutoff for subthreshold A β accumulation was derived as 13.3 A β L. The estimated sample size necessary to detect a 25% reduction in A β was 79 for A β(−) accumulators and 59 for the A β-converter/A β(+) group in DS.

          Conclusion:

          Longitudinal A β L changes were capable of distinguishing A β accumulators from non-accumulators in DS. Longitudinal imaging allowed for identification of subthreshold A β accumulation in DS during the earliest stages of AD-pathology progression. Detection of active A β deposition evidenced by subthreshold accumulation with longitudinal imaging can identify DS individuals at risk for AD development at an earlier stage.

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          Most cited references50

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          A power primer.

          One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.
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            Index for rating diagnostic tests

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              Clinical and Biomarker Changes in Dominantly Inherited Alzheimer's Disease

              The order and magnitude of pathologic processes in Alzheimer's disease are not well understood, partly because the disease develops over many years. Autosomal dominant Alzheimer's disease has a predictable age at onset and provides an opportunity to determine the sequence and magnitude of pathologic changes that culminate in symptomatic disease. In this prospective, longitudinal study, we analyzed data from 128 participants who underwent baseline clinical and cognitive assessments, brain imaging, and cerebrospinal fluid (CSF) and blood tests. We used the participant's age at baseline assessment and the parent's age at the onset of symptoms of Alzheimer's disease to calculate the estimated years from expected symptom onset (age of the participant minus parent's age at symptom onset). We conducted cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to determine the relative order and magnitude of pathophysiological changes. Concentrations of amyloid-beta (Aβ)(42) in the CSF appeared to decline 25 years before expected symptom onset. Aβ deposition, as measured by positron-emission tomography with the use of Pittsburgh compound B, was detected 15 years before expected symptom onset. Increased concentrations of tau protein in the CSF and an increase in brain atrophy were detected 15 years before expected symptom onset. Cerebral hypometabolism and impaired episodic memory were observed 10 years before expected symptom onset. Global cognitive impairment, as measured by the Mini-Mental State Examination and the Clinical Dementia Rating scale, was detected 5 years before expected symptom onset, and patients met diagnostic criteria for dementia at an average of 3 years after expected symptom onset. We found that autosomal dominant Alzheimer's disease was associated with a series of pathophysiological changes over decades in CSF biochemical markers of Alzheimer's disease, brain amyloid deposition, and brain metabolism as well as progressive cognitive impairment. Our results require confirmation with the use of longitudinal data and may not apply to patients with sporadic Alzheimer's disease. (Funded by the National Institute on Aging and others; DIAN ClinicalTrials.gov number, NCT00869817.).
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                Author and article information

                Journal
                9215515
                20498
                Neuroimage
                Neuroimage
                NeuroImage
                1053-8119
                1095-9572
                28 February 2021
                07 January 2021
                March 2021
                12 March 2021
                : 228
                : 117728
                Affiliations
                [a ]University of Wisconsin-Madison, Waisman Center, 1500 Highland Avenue, Madison, WI 53705, United States
                [b ]University of Pittsburgh, Department of Psychiatry, Pittsburgh, PA, United States
                [c ]University of Pittsburgh, Department of Radiology, Pittsburgh, PA, United States
                [d ]University of Pittsburgh, Department of Bioengineering, Pittsburgh, PA, United States
                [e ]Cambridge Intellectual Disability Research Group, University of Cambridge, Cambridge, United Kingdom
                [f ]Washington University in St. Louis Department of Neurology, St. Louis, MO, United States
                [g ]University of Wisconsin-Madison, Alzheimer’s Disease Research Center, Madison, WI, United States
                [h ]University of Wisconsin-Madison, Department of Medicine, Madison, WI, United States
                Author notes

                Author contributions

                Matthew D. Zammit: Conceptualization, methodology, writing – original draft

                Dana L. Tudorascu: Methodology, writing – review & editing

                Charles L. Laymon: Writing – review & editing

                Sigan L. Hartley: Writing – review & editing

                Shahid H. Zaman: Writing – review & editing

                Beau M. Ances: Writing – review & editing

                Sterling C. Johnson: Methodology, writing – review & editing

                Chales K. Stone: Writing – review & editing

                Chester A. Mathis: Writing – review & editing

                William E. Klunk: Funding acquisition, writing – review & editing

                Ann D. Cohen: Writing – review & editing

                Benjamin L. Handen: Funding acquisition, writing – review & editing

                Bradley T. Christian: Funding acquisition, supervision, conceptualization, writing – review & editing

                [* ]Corresponding author. mzammit@ 123456wisc.edu (M.D. Zammit)
                Article
                NIHMS1677104
                10.1016/j.neuroimage.2021.117728
                7953340
                33421595
                530252c4-e50e-4f0b-822b-dbeb84452ff4

                This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/)

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                Categories
                Article

                Neurosciences
                down syndrome,amyloid pet,alzheimer’s disease,longitudinal,subthreshold amyloid
                Neurosciences
                down syndrome, amyloid pet, alzheimer’s disease, longitudinal, subthreshold amyloid

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