Abstract
Personality has recently emerged as a critical determinant for multiple health outcomes. However, the evidence is less established for brain health, and the underlying mechanisms remain unclear. Here, utilizing data of 298,259 participants from the UK Biobank, five personality traits, including warmth, diligence, nervousness, sociability and curiosity, were constructed, and their relationships with brain disorders were examined with Cox regression and Mendelian randomization analyses. The results revealed consistent deleterious roles of nervousness, while the protective roles of warmth, diligence, sociability and curiosity in brain disorders were emphasized. Neuroimaging analyses highlighted the associations of personality traits with critical brain regions including the frontal cortex, temporal cortex and thalamus. Exploratory analyses revealed the mediating effects of neutrophil and high-density lipoprotein, indicating the contribution of inflammation and lipid metabolism to the associations between personality and brain health. This study provides a foundation for personality-oriented interventions in brain health, and it is necessary to validate our findings in other populations.
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Data availability
The main data used in this study were accessed from the publicly available UK Biobank Resource under application number 19542, which cannot be shared with other investigators. The GWAS data of brain disorders were retrieved from the exogenous population which is publicly available (dementia: https://gwas.mrcieu.ac.uk/datasets/finn-b-F5_DEMENTIA/, PD: https://gwas.mrcieu.ac.uk/datasets/ieu-a-812/, stroke: http://megastroke.org/download.html, schizophrenia: https://pgc.unc.edu/for-researchers/download-results/, bipolar affective disorder: https://pgc.unc.edu/for-researchers, and MDD: https://pgc.unc.edu/for-researchers/download-results/).
Code availability
Packages including survival 3.2, TwoSampleMR and lavaan 0.8 in R version 4.0.0 were used to perform Cox proportional hazards regression model, MR study and structural equation model, respectively. PLINK 2.0 was used to perform genome-wide association analysis and PRSice2 was used to calculate the PRS. Freesurfer v6.0 and FSL 6.0 were used to process the imaging data, and MATLAB 2018b was used to perform corresponding linear association analysis. Scripts used to perform the analyses are available at https://github.com/yuzhulineu/UKB_personality.
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Acknowledgements
This study was supported by grants from the STI2030-Major Projects (2022ZD0211600), National Natural Science Foundation of China (82071201, 82071997), Shanghai Municipal Science and Technology Major Project (2018SHZDZX01), Research Start-up Fund of Huashan Hospital (2022QD002), Excellence 2025 Talent Cultivation Program at Fudan University (3030277001), Shanghai Talent Development Funding for The Project (2019074), Shanghai Rising-Star Program (21QA1408700), 111 Project (B18015), ZHANGJIANG LAB, Tianqiao and Chrissy Chen Institute, the State Key Laboratory of Neurobiology and Frontiers Center for Brain Science of Ministry of Education, and Shanghai Center for Brain Science and Brain-Inspired Technology, Fudan University. We want to thank all the participants and researchers from the cohorts, including UKB, FinnGen, IPDGC, MEGASTROKE, PGC and CLOZUK.
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All authors had full access to the data in the study and accepted responsibility to submit them for publication. J.-T.Y. designed the study. Y.-R.Z. and Y.-T.D. conducted the primary analyses and drafted the manuscript. Y.-Z.L., R.-Q.Z., Y.-J.G., B.-S.W., W.Z. and K.K. contributed to imaging, SEM and genetic data analyses. J.-T.Y., W.C., J.-F.F., B.J.S., J.S. and A.D.S. critically revised the manuscript, and all authors approved the final version.
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Zhang, YR., Deng, YT., Li, YZ. et al. Personality traits and brain health: a large prospective cohort study. Nat. Mental Health 1, 722–735 (2023). https://doi.org/10.1038/s44220-023-00119-8
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DOI: https://doi.org/10.1038/s44220-023-00119-8