A cross-cohort replicable and heritable latent dimension linking behaviour to multi-featured brain structure.

Autor: Nicolaisen-Sobesky E; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany. elinicolaisen@gmail.com., Mihalik A; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.; Department of Psychiatry, University of Cambridge, Cambridge, UK., Kharabian-Masouleh S; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.; Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany., Ferreira FS; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK., Hoffstaedter F; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.; Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany., Schwender H; Mathematical Institute, Heinrich Heine University Düsseldorf, Düsseldorf, Germany., Maleki Balajoo S; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.; Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany., Valk SL; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.; Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.; Otto Hahn Research Group 'Cognitive Neurogenetics', Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany., Eickhoff SB; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.; Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany., Yeo BTT; Department of Electrical and Computer Engineering, Centre for Translational MR Research, Centre for Sleep & Cognition, N.1 Institute for Health, Institute for Digital Medicine, National University of Singapore, Singapore, Singapore., Mourao-Miranda J; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK., Genon S; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany. s.genon@fz-juelich.de.; Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany. s.genon@fz-juelich.de.
Jazyk: angličtina
Zdroj: Communications biology [Commun Biol] 2022 Nov 26; Vol. 5 (1), pp. 1297. Date of Electronic Publication: 2022 Nov 26.
DOI: 10.1038/s42003-022-04244-5
Abstrakt: Identifying associations between interindividual variability in brain structure and behaviour requires large cohorts, multivariate methods, out-of-sample validation and, ideally, out-of-cohort replication. Moreover, the influence of nature vs nurture on brain-behaviour associations should be analysed. We analysed associations between brain structure (grey matter volume, cortical thickness, and surface area) and behaviour (spanning cognition, emotion, and alertness) using regularized canonical correlation analysis and a machine learning framework that tests the generalisability and stability of such associations. The replicability of brain-behaviour associations was assessed in two large, independent cohorts. The load of genetic factors on these associations was analysed with heritability and genetic correlation. We found one heritable and replicable latent dimension linking cognitive-control/executive-functions and positive affect to brain structural variability in areas typically associated with higher cognitive functions, and with areas typically associated with sensorimotor functions. These results revealed a major axis of interindividual behavioural variability linking to a whole-brain structural pattern.
(© 2022. The Author(s).)
Databáze: MEDLINE
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