12The cerebral cortex underlies our complex cognitive capabilities, yet we know little about the specific genetic loci influencing human cortical structure. To identify genetic variants, including structural variants, impacting cortical structure, we conducted a genome-wide association meta-analysis of brain MRI data from 51,662 individuals. We analysed the surface area and average thickness of the whole cortex and 34 regions with known functional specialisations. We identified 255 nominally significant loci (P ≤ 5 x 10 -8 ); 199 survived multiple testing correction (P ≤ 8.3 x 10 -10 ; 187 surface area; 12 thickness). We found significant enrichment for loci influencing total surface area within regulatory elements active during prenatal cortical development, supporting the radial unit hypothesis. Loci impacting regional surface area cluster near genes in Wnt signalling pathways, known to influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression and ADHD.One Sentence Summary: Common genetic variation is associated with inter-individual variation in the structure of the human cortex, both globally and within specific regions, and is shared with genetic risk factors for some neuropsychiatric disorders.The human cerebral cortex is the outer grey matter layer of the brain, which is implicated in multiple aspects of higher cognitive function. Its distinct folding pattern is characterised by convex (gyral) and concave (sulcal) regions. Computational brain mapping approaches use the consistent folding patterns across individual cortices to label brain regions(1). During fetal development excitatory neurons, the predominant neuronal cell-type in the cortex, are generated from neural progenitor cells in the developing germinal zone(2). The radial unit hypothesis(3) posits that the expansion of cortical surface area (SA) is driven by the proliferation of these neural progenitor cells, whereas thickness (TH) is determined by the number of neurogenic divisions. Variation in global and regional measures of cortical SA and TH are associated with neuropsychiatric disorders and psychological traits(4) ( Table S1). Twin and family-based brain imaging studies show that SA and TH measurements are highly heritable and are largely influenced by independent genetic factors(5). Despite extensive studies of genes impacting cortical structure in model organisms (6), our current understanding of genetic variation impacting human cortical size and patterning is limited to rare, highly penetrant variants (7,8). These variants often disrupt cortical development, leading to altered post-natal structure. However, little is known about how common genetic variants impact human cortical SA and TH.To address this, we conducted genome-wide association meta-analyses of cortical SA and TH measures in 51,662 individuals from 60 cohorts from around the world (Tables S2-S4). Cortical measures were extracted from structural brain MRI scan...

Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here the ENIGMA consortium presents the largest ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and brain size (indexed by intracranial volume). Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (N = 1,443 and 1,113, respectively), we found several asymmetries showing modest but highly reliable heritability. The structural asymmetries identified, and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.Significance StatementLeft-right asymmetry is a key feature of the human brain's structure and function. It remains unclear which cortical regions are asymmetrical on average in the population, and how biological factors such as age, sex and genetic variation affect these asymmetries. Here we describe by far the largest ever study of cerebral cortical brain asymmetry, based on data from 17,141 participants. We found a global anterior-posterior 'torque' pattern in cortical thickness, together with various regional asymmetries at the population level, which have not been previously described, as well as effects of age, sex, and heritability estimates. From these data, we have created an on-line resource that will serve future studies of human brain anatomy in health and disease.

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA WIERENGA ET AL.

1Pregnancy and childbirth involve maternal brain adaptations that promote attachment to and protection 2 of the newborn. Using brain imaging and machine learning, we provide evidence for a positive relation-3 ship between number of childbirths and a 'younger-looking' brain in 12,021 women, which could not be 4 explained by common genetic variation. The findings demonstrate that parity can be linked to brain 5 health later in life. 6 Page 2 of 23Population-based neuroimaging reveals traces of childbirth in the maternal brain -de Lange et. al., 2019 During pregnancy and postpartum, fundamental biological processes are instigated to support maternal 7 adaptation and ensure protection of the offspring [1]. In rodents, brain adaptations across pregnancy 8 and postpartum include altered neurogenesis in the dentate gyrus [2], and changes in volume, dendritic 9 morphology, and cell proliferation in the hippocampus [1,3]. In humans, reduction in total brain vol-10 ume has been observed during pregnancy, with reversion occurring within six months of parturition [4]. 11Regional changes in brain structure are evident during the postpartum period, with effects depending 12 on region and time since delivery [5][6][7][8]. While some maternal brain changes revert postpartum, others 13 extend well beyond this phase [1,[7][8][9] and may influence the course of neurobiological aging later in 14 life. Some regional grey matter changes have been found to endure for at least 2 years post-pregnancy 15 in humans [1], and aged parous rats have increased hippocampal long-term potentiation and show fewer 16 signs of brain aging [1,10]. In addition to the direct and indirect bodily and environmental adaptations 17 in response to pregnancy and child-rearing, such long-lasting effects on brain health in humans could 18 also reflect genetic pleiotropy, as reproductive behaviors are complex, heritable traits with a polygenic 19 architecture that partly overlaps with a range of other traits that influence brain-health trajectories [11]. 20Based on the evidence of long-lasting effects of parity on the maternal brain, we investigated struc-21 tural brain characteristics in 12,021 women from the UK Biobank, hypothesizing that women who had 22 given (live) birth (n = 9568) would show less evidence of brain aging compared to their nulliparous peers 23 (n = 2453). We used machine learning and brain age prediction to test I) if a classifier could identify 24 women as parous or nulliparous based on morphometric brain characteristics, and II) whether brain age 25 gap (estimated brain age − chronological age) differed between parous and nulliparous women. Mean 26 age (± SD) was 54.72 (7.29) years for the full sample; 55.23 (7.22) years for parous and 52.79 (7.23) 27 years for nulliparous women. To investigate the impact of number of childbirths, we tested for associa-28 tions between number of births and the probabilistic scores from the group classification and brain age 29 gap, respectively, in addition to comparing women who had given 1-2 births, 3-...