Mapping human brain charts cross-sectionally and longitudinally
Brain scans acquired across large, age-diverse cohorts have facilitated recent progress in establishing normative brain aging charts. Here, we ask the critical question of whether cross-sectional estimates of age-related brain trajectories resemble those directly measured from longitudinal data. We...
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| Veröffentlicht in: | Proceedings of the National Academy of Sciences - PNAS 2023-05, Vol.120 (20), p.e2216798120-e2216798120 |
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| container_title | Proceedings of the National Academy of Sciences - PNAS |
| container_volume | 120 |
| creator | Di Biase, Maria A Tian, Ye Ella Bethlehem, Richard A I Seidlitz, Jakob Alexander-Bloch, Aaron F Yeo, B T Thomas Zalesky, Andrew |
| description | Brain scans acquired across large, age-diverse cohorts have facilitated recent progress in establishing normative brain aging charts. Here, we ask the critical question of whether cross-sectional estimates of age-related brain trajectories resemble those directly measured from longitudinal data. We show that age-related brain changes inferred from cross-sectionally mapped brain charts can substantially underestimate actual changes measured longitudinally. We further find that brain aging trajectories vary markedly between individuals and are difficult to predict with population-level age trends estimated cross-sectionally. Prediction errors relate modestly to neuroimaging confounds and lifestyle factors. Our findings provide explicit evidence for the importance of longitudinal measurements in ascertaining brain development and aging trajectories. |
| doi_str_mv | 10.1073/pnas.2216798120 |
| format | Article |
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Here, we ask the critical question of whether cross-sectional estimates of age-related brain trajectories resemble those directly measured from longitudinal data. We show that age-related brain changes inferred from cross-sectionally mapped brain charts can substantially underestimate actual changes measured longitudinally. We further find that brain aging trajectories vary markedly between individuals and are difficult to predict with population-level age trends estimated cross-sectionally. Prediction errors relate modestly to neuroimaging confounds and lifestyle factors. 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| source | MEDLINE; PubMed Central; Alma/SFX Local Collection; Free Full-Text Journals in Chemistry |
| subjects | Age Aging Biological Sciences Brain Brain - diagnostic imaging Brain mapping Charts Cross-Sectional Studies Humans Longitudinal Studies Magnetic Resonance Imaging Medical imaging Neuroimaging Trajectory measurement |
| title | Mapping human brain charts cross-sectionally and longitudinally |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-19T05%3A10%3A57IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Mapping%20human%20brain%20charts%20cross-sectionally%20and%20longitudinally&rft.jtitle=Proceedings%20of%20the%20National%20Academy%20of%20Sciences%20-%20PNAS&rft.au=Di%20Biase,%20Maria%20A&rft.date=2023-05-16&rft.volume=120&rft.issue=20&rft.spage=e2216798120&rft.epage=e2216798120&rft.pages=e2216798120-e2216798120&rft.issn=0027-8424&rft.eissn=1091-6490&rft_id=info:doi/10.1073/pnas.2216798120&rft_dat=%3Cproquest_pubme%3E2811569885%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2816132048&rft_id=info:pmid/37155868&rfr_iscdi=true |