{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T19:10:53Z","timestamp":1790363453288,"version":"4.1.0"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2020,2,6]],"date-time":"2020-02-06T00:00:00Z","timestamp":1580947200000},"content-version":"vor","delay-in-days":36,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["P30 AG010129"],"award-info":[{"award-number":["P30 AG010129"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["K01 AG030514"],"award-info":[{"award-number":["K01 AG030514"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["R01 AG049750"],"award-info":[{"award-number":["R01 AG049750"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>With recent advances in our understanding of the continuous pathophysiological changes that begin many years prior to symptom onset, it is now apparent that Alzheimer\u2019s disease cannot be adequately described by discrete clinical stages, but should also incorporate the continuum of biological changes that precede and underlie the clinical representation of the disease. By jointly considering longitudinal changes of all available biomarkers and clinical assessments, variation within individuals can be integrated into a single continuous measure of disease progression and used to identify the earliest pathophysiological changes. Disease time, a measure of disease severity, was estimated using a Bayesian latent time joint mixed-effects model applied to an array of imaging, biomarker and neuropsychological data. Trajectories of regional amyloid \u03b2 and tau PET uptake were estimated as a function of disease time. Regions with early signs of elevated amyloid \u03b2 uptake were used to form an early, focal composite and compared to a commonly used global composite, in a separate validation sample. Disease time was estimated in 279 participants (183 cognitively unimpaired individuals, 61 mild cognitive impairment and 35 Alzheimer\u2019s disease dementia patients) with available amyloid \u03b2 and tau PET data. Amyloid \u03b2 PET uptake levels in the posterior cingulate and precuneus start high and immediately increase with small increases of disease time. Early elevation in tau PET uptake was found in the inferior temporal lobe, amygdala, banks of the superior temporal sulcus, entorhinal cortex, middle temporal lobe, inferior parietal lobe and the fusiform gyrus. In a separate validation sample of 188 cognitively unimpaired individuals, the early, focal amyloid \u03b2 PET composite showed a 120% increase in the accumulation rate of amyloid \u03b2 compared to the global composite (P\u2009&amp;lt;\u20090.001), resulting in a 60% increase in the power to detect a treatment effect in a primary prevention trial design. Ordering participants on a continuous disease time scale facilitates the inspection of the earliest signs of amyloid \u03b2 and tau pathology. To detect early changes in amyloid \u03b2 pathology, focusing on the earliest sites of amyloid \u03b2 accumulation results in more powerful and efficient study designs in early Alzheimer\u2019s disease. Targeted composites could be used to re-examine the thresholds for amyloid \u03b2-related study inclusion, especially as the field shifts to focus on primary and secondary prevention. Clinical trials of anti-amyloid \u03b2 treatments may benefit from the use of focal composites when estimating drug effects on amyloid \u03b2 and tau changes in populations with minimal amyloid \u03b2 and tau pathology and limited expected short-term accumulation.<\/jats:p>","DOI":"10.1093\/braincomms\/fcaa007","type":"journal-article","created":{"date-parts":[[2020,2,6]],"date-time":"2020-02-06T13:33:06Z","timestamp":1580995986000},"source":"Crossref","is-referenced-by-count":113,"title":["Neuroanatomical spread of amyloid \u03b2 and tau in Alzheimer\u2019s disease: implications for primary prevention"],"prefix":"10.1093","volume":"2","author":[{"given":"Philip S","family":"Insel","sequence":"first","affiliation":[{"name":"Department of Psychiatry, University of California, San Francisco, CA, USA"},{"name":"Clinical Memory Research Unit, Department of Clinical Sciences Malm\u00f6, Lund University, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth C","family":"Mormino","sequence":"additional","affiliation":[{"name":"Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul S","family":"Aisen","sequence":"additional","affiliation":[{"name":"Alzheimer\u2019s Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wesley K","family":"Thompson","sequence":"additional","affiliation":[{"name":"Department of Family Medicine and Public Health, University of California, San Diego, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael C","family":"Donohue","sequence":"additional","affiliation":[{"name":"Alzheimer\u2019s Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2020,2,6]]},"reference":[{"key":"2020081109065400800_fcaa007-B1","first-page":"1","article-title":"On the path to 2025: understanding the Alzheimer\u2019s disease continuum","volume":"9","author":"Aisen","year":"2017","journal-title":"Alzheimer\u2019s Res Ther"},{"key":"2020081109065400800_fcaa007-B2","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1002\/ana.24711","article-title":"In vivo cortical spreading pattern of tau and amyloid in the Alzheimer disease spectrum","volume":"80","author":"Cho","year":"2016","journal-title":"Ann Neurol"},{"key":"2020081109065400800_fcaa007-B3","doi-asserted-by":"crossref","first-page":"S400","DOI":"10.1016\/j.jalz.2013.10.003","article-title":"Estimating long-term multivariate progression from short-term data","volume":"10","author":"Donohue","year":"2014","journal-title":"Alzheimer\u2019s Dement"},{"key":"2020081109065400800_fcaa007-B4","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1002\/ana.24546","article-title":"Tau positron emission tomographic imaging in aging and early Alzheimer disease","volume":"79","author":"Johnson","year":"2016","journal-title":"Ann Neurol"},{"key":"2020081109065400800_fcaa007-B5","doi-asserted-by":"crossref","first-page":"378","DOI":"10.2967\/jnumed.111.090340","article-title":"Performance characteristics of amyloid PET with florbetapir F 18 in patients with Alzheimer\u2019s disease and cognitively normal subjects","volume":"53","author":"Joshi","year":"2012","journal-title":"J Nucl Med"},{"key":"2020081109065400800_fcaa007-B6","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1002\/ana.23650","article-title":"Amyloid deposition, hypometabolism, and longitudinal cognitive decline","volume":"72","author":"Landau","year":"2012","journal-title":"Ann Neurol"},{"key":"2020081109065400800_fcaa007-B7","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1177\/0962280217737566","article-title":"Bayesian latent time joint mixed effect models for multicohort longitudinal data","volume":"28","author":"Li","year":"2017","journal-title":"Stat Methods Med Res"},{"key":"2020081109065400800_fcaa007-B8","first-page":"657","article-title":"Bayesian latent time joint mixed-effects model of progression in the Alzheimer\u2019s Disease Neuroimaging Initiative. 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