{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T15:01:15Z","timestamp":1790348475588,"version":"4.1.0"},"reference-count":60,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T00:00:00Z","timestamp":1766534400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T00:00:00Z","timestamp":1766534400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["606650"],"award-info":[{"award-number":["606650"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005725","name":"CHDI Foundation","doi-asserted-by":"publisher","award":["A\u20103433"],"award-info":[{"award-number":["A\u20103433"]}],"id":[{"id":"10.13039\/100005725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001779","name":"Monash University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001779","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["movementdisorders.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Movement Disorders"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Huntington's disease (HD) is a progressive neurodegenerative disorder. Models of brain biological age have shown evidence of accelerated aging relative to chronological age, but they typically rely on a single whole\u2010brain measure. While studies in other neurodegenerative diseases suggest region\u2010specific brain age models can provide deeper insights, this approach remains underexplored in HD. Such regional models could benefit clinical trials, which depend on sensitive biomarkers to monitor therapeutic effects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>This study aimed to characterize region\u2010specific patterns of brain aging across Huntington's Disease Integrated Staging System (HD\u2010ISS) stages and evaluate their associations with cognitive, motor, and functional scores.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We employed machine learning to train brain age models on structural magnetic resonance imaging data from 1936 controls. These models were applied to 531 persons with HD. Associations between regional brain age gap, HD\u2010ISS stages, and clinical scores were assessed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Whole\u2010brain aging increased progressively at HD\u2010ISS stages 2 and 3. Region\u2010specific analyses revealed the dominance of subcortical, temporal, and parietal aging trajectories, which exhibited significant stage\u2010wise increases in brain age gap. A higher brain age gap in these regions was associated with declines in cognitive, motor, and functional performance. In contrast, insular and frontal regions showed flatter patterns and no significant associations with clinical measures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      This study highlights distinct region\u2010specific components of brain aging in HD. Regional analysis provides deeper insights into HD progression and could be employed as a sensitive biomarker for monitoring therapeutic effects in clinical trials. Future work should explore these findings in younger cohorts and investigate network\u2010specific aging with multimodal imaging. \u00a9 2025 The Author(s).\n                      <jats:italic>Movement Disorders<\/jats:italic>\n                      published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mds.70160","type":"journal-article","created":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T12:16:53Z","timestamp":1766578613000},"page":"881-888","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Mapping Regional Brain Aging in Huntington's Disease Using Structural Magnetic Resonance Imaging and Machine Learning"],"prefix":"10.1002","volume":"41","author":[{"given":"Mohsen","family":"Ghofrani\u2010Jahromi","sequence":"first","affiliation":[{"name":"Turner Institute for Brain and 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