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Multimodal Image Analysis of Apparent Brain Age Identifies Physical Fitness as Predictor of Brain Maintenance
Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).ORCID iD: 0000-0002-5911-9511
Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.ORCID iD: 0000-0001-6784-1945
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).ORCID iD: 0000-0002-3367-1746
Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, DK-2650 Hvidovre, Denmark; Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital Bispebjerg, DK-2400 Copenhagen, Denmark.ORCID iD: 0000-0002-4458-6475
2021 (English)In: Cerebral Cortex, ISSN 1047-3211, E-ISSN 1460-2199, Vol. 31, no 7, p. 3393-3407Article in journal (Refereed) Published
Abstract [en]

Maintaining a youthful brain structure and function throughout life may be the single most important determinant ofsuccessful cognitive aging. In this study, we addressed heterogeneity in brain aging by making image-based brain agepredictions and relating the brain age prediction gap (BAPG) to cognitive change in aging. Structural, functional, anddiffusion MRI scans from 351 participants were used to train and evaluate 5 single-modal and 4 multimodal predictionmodels, based on 7 regression methods. The models were compared on mean absolute error and whether they were relatedto physical fitness and cognitive ability, measured both currently and longitudinally, as well as study attrition and years ofeducation. Multimodal prediction models performed at a similar level as single-modal models, and the choice of regressionmethod did not significantly affect the results. Correlation with the BAPG was found for current physical fitness, currentcognitive ability, and study attrition. Correlations were also found for retrospective physical fitness, measured 10 years priorto imaging, and slope for cognitive ability during a period of 15 years. The results suggest that maintaining a high physicalfitness throughout life contributes to brain maintenance and preserved cognitive ability.

Place, publisher, year, edition, pages
Oxford University Press, 2021. Vol. 31, no 7, p. 3393-3407
Keywords [en]
age predictions, brain aging, cognition, multimodal MRI, physical fitness
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:umu:diva-181479DOI: 10.1093/cercor/bhab019ISI: 000670805500018PubMedID: 33690853Scopus ID: 2-s2.0-85108304334OAI: oai:DiVA.org:umu-181479DiVA, id: diva2:1536866
Available from: 2021-03-12 Created: 2021-03-12 Last updated: 2023-09-05Bibliographically approved

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Dunås, ToraWåhlin, AndersNyberg, LarsBoraxbekk, Carl-Johan

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Dunås, ToraWåhlin, AndersNyberg, LarsBoraxbekk, Carl-Johan
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Umeå Centre for Functional Brain Imaging (UFBI)Centre for Demographic and Ageing Research (CEDAR)Radiation PhysicsDiagnostic RadiologyDepartment of Integrative Medical Biology (IMB)
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