Greater male than female variability in regional brain structure across the lifespan
Publication year
2022Author(s)
Source
Human Brain Mapping, 43, 1, (2022), pp. 470-499ISSN
Publication type
Article / Letter to editor

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Organization
PI Group Memory & Emotion
Cognitive Neuroscience
Neuroinformatics
Human Genetics
Psychiatry
PI Group Motivational & Cognitive Control
Journal title
Human Brain Mapping
Volume
vol. 43
Issue
iss. 1
Page start
p. 470
Page end
p. 499
Subject
130 000 Cognitive Neurology & Memory; 170 000 Motivational & Cognitive Control; Neuroinformatics; Radboudumc 7: Neurodevelopmental disorders DCMN: Donders Center for Medical NeuroscienceAbstract
For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.
This item appears in the following Collection(s)
- Academic publications [234108]
- Donders Centre for Cognitive Neuroimaging [3707]
- Electronic publications [116863]
- Faculty of Medical Sciences [89175]
- Faculty of Science [34556]
- Open Access publications [83955]
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