ABSTRACT
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.
Subject(s)
Biological Variation, Population/physiology , Brain/anatomy & histology , Brain/diagnostic imaging , Human Development/physiology , Magnetic Resonance Imaging , Neuroimaging , Sex Characteristics , Brain Cortical Thickness , Cerebral Cortex/anatomy & histology , Cerebral Cortex/diagnostic imaging , Female , Humans , MaleABSTRACT
Copy Number Variants (CNVs) are associated with elevated rates of neuropsychiatric disorders. A 'genetics-first' approach, involving the CNV effects on the brain, irrespective of clinical symptomatology, allows investigation of mechanisms underlying neuropsychiatric disorders in the general population. Recent years have seen an increasing number of larger multisite neuroimaging studies investigating the effect of CNVs on structural and functional brain endophenotypes. Alterations overlap with those found in idiopathic psychiatric conditions but effect sizes are twofold to fivefold larger. Here we review new CNV-associated structural and functional brain alterations and outline the future of neuroimaging genomics research, with particular emphasis on developing new resources for the study of high-risk CNVs and rare genomic variants.
