{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T03:34:35Z","timestamp":1793763275219,"version":"4.6.1"},"reference-count":75,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T00:00:00Z","timestamp":1744675200000},"content-version":"vor","delay-in-days":14,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["NIH R01AG067103"],"award-info":[{"award-number":["NIH R01AG067103"]}],"id":[{"id":"10.13039\/100000049","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":[[2025,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>INTRODUCTION<\/jats:title>\n                    <jats:p>Previous studies have applied normative modeling on a single neuroimaging modality to investigate Alzheimer disease (AD) heterogeneity. We employed a deep learning\u2010based multimodal normative framework to analyze individual\u2010level variation across ATN (amyloid\u2010tau\u2010neurodegeneration) imaging biomarkers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>\n                      We selected cross\u2010sectional discovery (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a0665) and replication cohorts (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a0430) with available T1\u2010weighted magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). Normative modeling estimated individual\u2010level abnormal deviations in amyloid\u2010positive individuals compared to amyloid\u2010negative controls. Regional abnormality patterns were mapped at different clinical group levels to assess intra\u2010group heterogeneity. An individual\u2010level disease severity index (DSI) was calculated using both the spatial extent and magnitude of abnormal deviations across ATN.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Greater intra\u2010group heterogeneity in ATN abnormality patterns was observed in more severe clinical stages of AD. Higher DSI was associated with worse cognitive function and increased risk of disease progression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>Subject\u2010specific abnormality maps across ATN reveal the heterogeneous impact of AD on the brain.<\/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>Normative modeling examined AD heterogeneity across multimodal imaging biomarkers.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Heterogeneity in spatial patterns of gray matter atrophy, amyloid, and tau burden.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Higher within\u2010group heterogeneity for AD patients at advanced dementia stages.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Patient\u2010specific metric summarized extent of neurodegeneration and neuropathology.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Metric is a marker of poor brain health and can monitor risk of disease progression.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/alz.70143","type":"journal-article","created":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T02:43:57Z","timestamp":1746672237000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Analyzing heterogeneity in Alzheimer disease using multimodal normative modeling on imaging\u2010based ATN biomarkers"],"prefix":"10.1002","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7213-0734","authenticated-orcid":false,"given":"Sayantan","family":"Kumar","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering Washington University in St Louis  Saint Louis Missouri USA"},{"name":"Institute for Informatics Data Science &amp; 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