{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T17:01:58Z","timestamp":1791478918207,"version":"4.3.4"},"reference-count":53,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,1,8]],"date-time":"2025-01-08T00:00:00Z","timestamp":1736294400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2025,1,8]],"date-time":"2025-01-08T00:00:00Z","timestamp":1736294400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R01AG073362"],"award-info":[{"award-number":["R01AG073362"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R21AG073973"],"award-info":[{"award-number":["R21AG073973"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R21AG064263"],"award-info":[{"award-number":["R21AG064263"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R01AG072470"],"award-info":[{"award-number":["R01AG072470"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"National Institute of Mental Health","doi-asserted-by":"publisher","award":["R61MH119289"],"award-info":[{"award-number":["R61MH119289"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"National Institute of Mental Health","doi-asserted-by":"publisher","award":["R21MH123873"],"award-info":[{"award-number":["R21MH123873"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["alz-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Alzheimer's &amp;amp; Dementia"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>INTRODUCTION<\/jats:title>\n                    <jats:p>Amyloid beta (A\u03b2) plaques and hyperphosphorylated tau in the entorhinal regions\u00a0are key Alzheimer's disease (AD) markers, but the spatial A\u03b2 pathways influencing tau pathology remain unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>\n                      We applied predictive modeling to identify A\u03b2 standardized uptake value ratio (SUVR) spatial patterns that predict entorhinal tau levels, future hippocampal volume, and Preclinical Alzheimer's Cognitive Composite (PACC) scores at 5\u2010year follow\u2010up. The model was trained on Alzheimer's Disease Neuroimaging Initiative (ADNI) (\n                      <jats:italic>N<\/jats:italic>\n                      \u00a0=\u00a0237), incorporating amyloid\u2010PET (positron emission tomography), tau\u2010PET, magnetic resonance imaging (MRI), and cognitive data, and validated on Harvard Aging Brain Study (HABS) (\n                      <jats:italic>N<\/jats:italic>\n                      \u00a0=\u00a0276).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>\n                      The model accurately predicted entorhinal tau levels (\n                      <jats:italic>r<\/jats:italic>\n                      \u00a0=\u00a00.48,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a00.0001), future hippocampal volume (\n                      <jats:italic>r<\/jats:italic>\n                      \u00a0=\u00a00.24,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0=\u00a00.002), and PACC scores (\n                      <jats:italic>r<\/jats:italic>\n                      \u00a0=\u00a00.35,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a00.0001) based on regional A\u03b2.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>A\u03b2 in the rostral middle frontal, medial orbitofrontal, and striatal regions predict entorhinal tau levels, future hippocampal volume, and PACC scores, indicating their potential as early biomarkers in AD prediction models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Positron emission tomography (PET) imaging reveals amyloid beta (A\u03b2) patterns predicting entorhinal tau levels in preclinical Alzheimer's disease (AD).<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>A\u03b2 in medial orbitofrontal, rostral middle frontal, and nucleus accumbens best predicts tau.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>A\u03b2 distribution in these regions predicts future hippocampal neurodegeneration and cognitive decline.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Model validated with Alzheimer's Disease Neuroimaging Initiative (ADNI) and Harvard Aging Brain Study (HABS) data sets, showing robustness and reproducibility.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Findings suggest early A\u03b2 patterns can aid in diagnosing AD and guide anti\u2010A\u03b2 therapies<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/alz.14499","type":"journal-article","created":{"date-parts":[[2025,1,8]],"date-time":"2025-01-08T09:34:27Z","timestamp":1736328867000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Mapping amyloid beta predictors of entorhinal tau in preclinical Alzheimer's disease"],"prefix":"10.1002","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1621-3751","authenticated-orcid":false,"given":"Jafar","family":"Zamani","sequence":"first","affiliation":[{"name":"Computational Brain Research and Intervention (C\u2010Brain) Lab 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