Population clustering of structural brain aging and its association with brain development

Author:

Duan Haojing12,Shi Runye3,Kang Jujiao12,Banaschewski Tobias4,Bokde Arun L. W.5,Büchel Christian6ORCID,Desrivières Sylvane7,Flor Herta89,Grigis Antoine10,Garavan Hugh11,Gowland Penny A.12,Heinz Andreas13,Brühl Rüdiger14ORCID,Martinot Jean-Luc15,Martinot Marie-Laure Paillère16,Artiges Eric17,Nees Frauke4818,Papadopoulos Orfanos Dimitri10ORCID,Paus Tomáš1920,Poustka Luise21,Hohmann Sarah4,Holz Nathalie4,Fröhner Juliane H.22,Smolka Michael N.22ORCID,Vaidya Nilakshi23,Walter Henrik13,Whelan Robert24,Schumann Gunter1232526,Lin Xiaolei327ORCID,Feng Jianfeng1232829ORCID,

Affiliation:

1. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University

2. Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education

3. School of Data Science, Fudan University

4. Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University

5. Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin

6. University Medical Centre Hamburg-Eppendorf

7. Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London

8. Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University

9. Department of Psychology, School of Social Sciences, University of Mannheim

10. NeuroSpin, CEA, Université Paris-Saclay

11. Departments of Psychiatry and Psychology, University of Vermont

12. Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park

13. Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health

14. Physikalisch-Technische Bundesanstalt (PTB)

15. Institut National de la Santé et de la Recherche Médicale, INSERM U A10 “Trajectoires développementales en psychiatrie”; Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli; Gif-sur-Yvette

16. Institut National de la Santé et de la Recherce Médicale, INSERM U A10 “Trajectoires développementales & psychiatrie”, University Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS; Centre Borelli

17. Institut National de la Santé et de la Recherche Médicale, INSERM U A10 “Trajectoires développementalesen psychiatrie”; Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette; and Psychiatry Department

18. Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein Kiel University

19. Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal

20. Departments of Psychiatry and Psychology, University of Toronto

21. Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen

22. Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden

23. Department of Psychiatry and Neurosciences, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität BerlinHumboldt-Universität zu Berlin, and Berlin Institute of Health

24. School of Psychology and Global Brain Health Institute, Trinity College Dublin

25. Centre for Population Neuroscience and Stratified Medicine (PONS Centre), ISTBI, Fudan University

26. Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin

27. Huashan Institute of Medicine, Huashan Hospital affiliated to Fudan University

28. MOE Frontiers Center for Brain Science, Fudan University

29. Zhangjiang Fudan International Innovation Center

Abstract

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the “last in, first out” mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

Publisher

eLife Sciences Publications, Ltd

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