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Walhovd KB, Krogsrud SK, Amlien IK, Sørensen Ø, Wang Y, Bråthen ACS, Overbye K, Kransberg J, Mowinckel AM, Magnussen F, Herud M, Håberg AK, Fjell AM, Vidal-Pineiro D. Fetal influence on the human brain through the lifespan. eLife 2024; 12:RP86812. [PMID: 38602745 PMCID: PMC11008813 DOI: 10.7554/elife.86812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2024] Open
Abstract
Human fetal development has been associated with brain health at later stages. It is unknown whether growth in utero, as indexed by birth weight (BW), relates consistently to lifespan brain characteristics and changes, and to what extent these influences are of a genetic or environmental nature. Here we show remarkably stable and lifelong positive associations between BW and cortical surface area and volume across and within developmental, aging and lifespan longitudinal samples (N = 5794, 4-82 y of age, w/386 monozygotic twins, followed for up to 8.3 y w/12,088 brain MRIs). In contrast, no consistent effect of BW on brain changes was observed. Partly environmental effects were indicated by analysis of twin BW discordance. In conclusion, the influence of prenatal growth on cortical topography is stable and reliable through the lifespan. This early-life factor appears to influence the brain by association of brain reserve, rather than brain maintenance. Thus, fetal influences appear omnipresent in the spacetime of the human brain throughout the human lifespan. Optimizing fetal growth may increase brain reserve for life, also in aging.
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Affiliation(s)
- Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University HospitalOsloNorway
| | - Stine K Krogsrud
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | | | - Knut Overbye
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Jonas Kransberg
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | | | - Fredrik Magnussen
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Martine Herud
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
| | - Asta K Håberg
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and TechnologyOsloNorway
| | - Anders Martin Fjell
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University HospitalOsloNorway
| | - Didac Vidal-Pineiro
- Center for Lifespan Changes in Brain and Cognition, University of OsloOsloNorway
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de Chastelaine M, Srokova S, Hou M, Kidwai A, Kafafi SS, Racenstein ML, Rugg MD. Cortical thickness, gray matter volume, and cognitive performance: a crosssectional study of the moderating effects of age on their interrelationships. Cereb Cortex 2023; 33:6474-6485. [PMID: 36627250 PMCID: PMC10183746 DOI: 10.1093/cercor/bhac518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 12/05/2022] [Accepted: 12/06/2022] [Indexed: 01/12/2023] Open
Abstract
In a sample comprising younger, middle-aged, and older cognitively healthy adults (N = 375), we examined associations between mean cortical thickness, gray matter volume (GMV), and performance in 4 cognitive domains-memory, speed, fluency, and crystallized intelligence. In almost all cases, the associations were moderated significantly by age, with the strongest associations in the older age group. An exception to this pattern was identified in a younger adult subgroup aged <23 years when a negative association between cognitive performance and cortical thickness was identified. Other than for speed, all associations between structural metrics and performance in specific cognitive domains were fully mediated by mean cognitive ability. Cortical thickness and GMV explained unique fractions of the variance in mean cognitive ability, speed, and fluency. In no case, however, did the amount of variance jointly explained by the 2 metrics exceed 7% of the total variance. These findings suggest that cortical thickness and GMV are distinct correlates of domain-general cognitive ability, that the strength and, for cortical thickness, the direction of these associations are moderated by age, and that these structural metrics offer only limited insights into the determinants of individual differences in cognitive performance across the adult lifespan.
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Affiliation(s)
- Marianne de Chastelaine
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, 1600, Viceroy Drive, Suite 800, Dallas, TX 75235, United States
| | - Sabina Srokova
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, 1600, Viceroy Drive, Suite 800, Dallas, TX 75235, United States
| | - Mingzhu Hou
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, 1600, Viceroy Drive, Suite 800, Dallas, TX 75235, United States
| | - Ambereen Kidwai
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, 1600, Viceroy Drive, Suite 800, Dallas, TX 75235, United States
| | - Seham S Kafafi
- Department of Psychology, University of Notre Dame, Notre Dame, IN 46556, United States
| | - Melanie L Racenstein
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, 1600, Viceroy Drive, Suite 800, Dallas, TX 75235, United States
| | - Michael D Rugg
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, 1600, Viceroy Drive, Suite 800, Dallas, TX 75235, United States
- School of Psychology, University of East Anglia, Norwich NR4 7TJ, United Kingdom
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Nicolaisen-Sobesky E, Mihalik A, Kharabian-Masouleh S, Ferreira FS, Hoffstaedter F, Schwender H, Maleki Balajoo S, Valk SL, Eickhoff SB, Yeo BTT, Mourao-Miranda J, Genon S. A cross-cohort replicable and heritable latent dimension linking behaviour to multi-featured brain structure. Commun Biol 2022; 5:1297. [PMID: 36435870 PMCID: PMC9701210 DOI: 10.1038/s42003-022-04244-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 11/09/2022] [Indexed: 11/28/2022] Open
Abstract
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.
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Affiliation(s)
- Eliana Nicolaisen-Sobesky
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.
| | - Agoston Mihalik
- 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
| | - Shahrzad Kharabian-Masouleh
- 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
| | - Fabio S Ferreira
- 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
| | - Felix Hoffstaedter
- 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
| | - Holger Schwender
- Mathematical Institute, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Somayeh Maleki Balajoo
- 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
| | - Sofie L Valk
- 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
| | - Simon B Eickhoff
- 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
| | - B T Thomas Yeo
- 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
| | - Janaina Mourao-Miranda
- 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
| | - Sarah Genon
- 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.
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