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Only a small number of studies have assessed structural differences between the two hemispheres during childhood and adolescence. However, the existing findings lack consistency or are restricted to a particular brain region, a specific brain feature, or a relatively narrow age range. Here, we investigated associations between brain asymmetry and age as well as sex in one of the largest pediatric samples to date (n = 4265), aged 1-18 years, scanned at 69 sites participating in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our study revealed that significant brain asymmetries already exist in childhood, but their magnitude and direction depend on the brain region examined and the morphometric measurement used (cortical volume or thickness, regional surface area, or subcortical volume). With respect to effects of age, some asymmetries became weaker over time while others became stronger; sometimes they even reversed direction. With respect to sex differences, the total number of regions exhibiting significant asymmetries was larger in females than in males, while the total number of measurements indicating significant asymmetries was larger in males (as we obtained more than one measurement per cortical region). The magnitude of the significant asymmetries was also greater in males. However, effect sizes for both age effects and sex differences were small. Taken together, these findings suggest that cerebral asymmetries are an inherent organizational pattern of the brain that manifests early in life. Overall, brain asymmetry appears to be relatively stable throughout childhood and adolescence, with some differential effects in males and females., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

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., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Left-right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures are asymmetrical on average in the healthy population, and how variability in brain asymmetry relates to basic biological variables such as age and sex. Over the last 4 years, the ENIGMA-Laterality Working Group has published six studies of gray matter morphological asymmetry based on total sample sizes from roughly 3,500 to 17,000 individuals, which were between one and two orders of magnitude larger than those published in previous decades. A population-level mapping of average asymmetry was achieved, including an intriguing fronto-occipital gradient of cortical thickness asymmetry in healthy brains. ENIGMA's multi-dataset approach also supported an empirical illustration of reproducibility of hemispheric differences across datasets. Effect sizes were estimated for gray matter asymmetry based on large, international, samples in relation to age, sex, handedness, and brain volume, as well as for three psychiatric disorders: autism spectrum disorder was associated with subtly reduced asymmetry of cortical thickness at regions spread widely over the cortex; pediatric obsessive-compulsive disorder was associated with altered subcortical asymmetry; major depressive disorder was not significantly associated with changes of asymmetry. Ongoing studies are examining brain asymmetry in other disorders. Moreover, a groundwork has been laid for possibly identifying shared genetic contributions to brain asymmetry and disorders., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Here we review the motivation for creating the enhancing neuroimaging genetics through meta-analysis (ENIGMA) Consortium and the genetic analyses undertaken by the consortium so far. We discuss the methodological challenges, findings, and future directions of the genetics working group. A major goal of the working group is tackling the reproducibility crisis affecting "candidate gene" and genome-wide association analyses in neuroimaging. To address this, we developed harmonized analytic methods, and support their use in coordinated analyses across sites worldwide, which also makes it possible to understand heterogeneity in results across sites. These efforts have resulted in the identification of hundreds of common genomic loci robustly associated with brain structure. We have found both pleiotropic and specific genetic effects associated with brain structures, as well as genetic correlations with psychiatric and neurological diseases., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Previous studies have linked the low expression variant of a variable number of tandem repeat polymorphism in the monoamine oxidase A gene (MAOA-L) to the risk for impulsivity and aggression, brain developmental abnormalities, altered cortico-limbic circuit function, and an exaggerated neural serotonergic tone. However, the neurobiological effects of this variant on human brain network architecture are incompletely understood. We studied healthy individuals and used multimodal neuroimaging (sample size range: 219-284 across modalities) and network-based statistics (NBS) to probe the specificity of MAOA-L-related connectomic alterations to cortical-limbic circuits and the emotion processing domain. We assessed the spatial distribution of affected links across several neuroimaging tasks and data modalities to identify potential alterations in network architecture. Our results revealed a distributed network of node links with a significantly increased connectivity in MAOA-L carriers compared to the carriers of the high expression (H) variant. The hyperconnectivity phenotype primarily consisted of between-lobe ("anisocoupled") network links and showed a pronounced involvement of frontal-temporal connections. Hyperconnectivity was observed across functional magnetic resonance imaging (fMRI) of implicit emotion processing (p FWE = .037), resting-state fMRI (p FWE = .022), and diffusion tensor imaging (p FWE = .044) data, while no effects were seen in fMRI data of another cognitive domain, that is, spatial working memory (p FWE = .540). These observations are in line with prior research on the MAOA-L variant and complement these existing data by novel insights into the specificity and spatial distribution of the neurogenetic effects. Our work highlights the value of multimodal network connectomic approaches for imaging genetics., (© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Introduction: Reward processing is a key aspect of cognitive control processes, putatively instantiated by mesolimbic and mesocortical brain circuits. Deficient signaling within these circuits has been associated with psychopathology. We applied a network discovery approach to assess specific functional networks associated with reward processing in participants with attention-deficit/hyperactivity disorder (ADHD)., Methods: To describe task-related processes in terms of integrated functional networks, we applied independent component analysis (ICA) to task response maps of 60 healthy participants who performed a monetary incentive delay (MID) task. The resulting components were interpreted on the basis of their similarity with group-level task responses as well as their similarity with brain networks derived from resting state fMRI analyses. ADHD-related effects on network characteristics including functional connectivity and communication between networks were examined in an independent sample comprising 150 participants with ADHD and 48 healthy controls., Results: We identified 23 components to be associated with 4 large-scale functional networks: the default-mode, visual, executive control, and salience networks. The salience network showed a specific association with reward processing as well as the highest degree of within-network integration. ADHD was associated with decreased functional connectivity between the salience and executive control networks as well as with peripheral brain regions., Conclusions: Reward processing as measured with the MID task involves one reward-specific and three general functional networks. Participants with ADHD exhibited alterations in connectivity of both the salience and executive control networks and associated brain regions during task performance. Hum Brain Mapp 38:2359-2369, 2017. © 2017 Wiley Periodicals, Inc., (© 2017 Wiley Periodicals, Inc.)

Genome-wide association screens aim to identify common genetic variants contributing to the phenotypic variability of complex traits, such as human height or brain morphology. The identified genetic variants are mostly within noncoding genomic regions and the biology of the genotype-phenotype association typically remains unclear. In this article, we propose a complementary targeted strategy to reveal the genetic underpinnings of variability in subcortical brain volumes, by specifically selecting genomic loci that are experimentally validated forebrain enhancers, active in early embryonic development. We hypothesized that genetic variation within these enhancers may affect the development and ultimately the structure of subcortical brain regions in adults. We tested whether variants in forebrain enhancer regions showed an overall enrichment of association with volumetric variation in subcortical structures of >13,000 healthy adults. We observed significant enrichment of genomic loci that affect the volume of the hippocampus within forebrain enhancers (empirical P = 0.0015), a finding which robustly passed the adjusted threshold for testing of multiple brain phenotypes (cutoff of P < 0.0083 at an alpha of 0.05). In analyses of individual single nucleotide polymorphisms (SNPs), we identified an association upstream of the ID2 gene with rs7588305 and variation in hippocampal volume. This SNP-based association survived multiple-testing correction for the number of SNPs analyzed but not for the number of subcortical structures. Targeting known regulatory regions offers a way to understand the underlying biology that connects genotypes to phenotypes, particularly in the context of neuroimaging genetics. This biology-driven approach generates testable hypotheses regarding the functional biology of identified associations. Hum Brain Mapp 37:1788-1800, 2016. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

While detecting genetic variations underlying brain structures helps reveal mechanisms of neural disorders, high data dimensionality poses a major challenge for imaging genomic association studies. In this work, we present the application of a recently proposed approach, parallel independent component analysis with reference (pICA-R), to investigate genomic factors potentially regulating gray matter variation in a healthy population. This approach simultaneously assesses many variables for an aggregate effect and helps to elicit particular features in the data. We applied pICA-R to analyze gray matter density (GMD) images (274,131 voxels) in conjunction with single nucleotide polymorphism (SNP) data (666,019 markers) collected from 1,256 healthy individuals of the Brain Imaging Genetics (BIG) study. Guided by a genetic reference derived from the gene GNA14, pICA-R identified a significant SNP-GMD association (r=-0.16, P=2.34×10(-8)), implying that subjects with specific genotypes have lower localized GMD. The identified components were then projected to an independent dataset from the Mind Clinical Imaging Consortium (MCIC) including 89 healthy individuals, and the obtained loadings again yielded a significant SNP-GMD association (r=-0.25, P=0.02). The imaging component reflected GMD variations in frontal, precuneus, and cingulate regions. The SNP component was enriched in genes with neuronal functions, including synaptic plasticity, axon guidance, molecular signal transduction via PKA and CREB, highlighting the GRM1, PRKCH, GNA12, and CAMK2B genes. Collectively, our findings suggest that GNA12 and GNA14 play a key role in the genetic architecture underlying normal GMD variation in frontal and parietal regions., (© 2015 Wiley Periodicals, Inc.)

Brain white matter (WM) tracts, playing a vital role in the communication between brain regions, undergo important maturational changes during adolescence and young adulthood, a critical period for the development of nicotine dependence. Attention-deficit/hyperactivity disorder (ADHD) is associated with increased smoking and widespread WM abnormalities, suggesting that the developing ADHD brain might be especially vulnerable to effects of smoking. This study aims to investigate the effect of smoking on (WM) microstructure in adolescents and young adults with and without ADHD. Diffusion tensor imaging was performed in an extensively phenotyped sample of nonsmokers (n = 95, 50.5% ADHD), irregular smokers (n = 41, 58.5% ADHD), and regular smokers (n = 50, 82.5% ADHD), aged 14-24 years. A whole-brain voxelwise approach investigated associations of smoking, ADHD and their interaction, with WM microstructure as measured by fractional anisotropy (FA) and mean diffusivity (MD). Widespread alterations in FA and MD were found for regular smokers compared to irregular and nonsmokers, mainly located in the corpus callosum and WM tracts surrounding the basal ganglia. Several regions overlapped with regions of altered FA for ADHD versus controls, albeit in different directions. Irregular and nonsmokers did not differ, and ADHD and smoking did not interact. Results implicate that smoking and ADHD have independent effects on WM microstructure, and possibly do not share underlying mechanisms. Two mechanisms may play a role in the current results. First, smoking may cause alterations in WM microstructure in the maturing brain. Second, pre-existing WM microstructure differences possibly reflect a risk factor for development of a smoking addiction., (© 2014 Wiley Periodicals, Inc.)

Functional and anatomical asymmetries are prevalent features of the human brain, linked to gender, handedness, and cognition. However, little is known about the neurodevelopmental processes involved. In zebrafish, asymmetries arise in the diencephalon before extending within the central nervous system. We aimed to identify genes involved in the development of subtle, left-right volumetric asymmetries of human subcortical structures using large datasets. We first tested the feasibility of measuring left-right volume differences in such large-scale samples, as assessed by two automated methods of subcortical segmentation (FSL|FIRST and FreeSurfer), using data from 235 subjects who had undergone MRI twice. We tested the agreement between the first and second scan, and the agreement between the segmentation methods, for measures of bilateral volumes of six subcortical structures and the hippocampus, and their volumetric asymmetries. We also tested whether there were biases introduced by left-right differences in the regional atlases used by the methods, by analyzing left-right flipped images. While many bilateral volumes were measured well (scan-rescan r = 0.6-0.8), most asymmetries, with the exception of the caudate nucleus, showed lower repeatabilites. We meta-analyzed genome-wide association scan results for caudate nucleus asymmetry in a combined sample of 3,028 adult subjects but did not detect associations at genome-wide significance (P < 5 × 10(-8) ). There was no enrichment of genetic association in genes involved in left-right patterning of the viscera. Our results provide important information for researchers who are currently aiming to carry out large-scale genome-wide studies of subcortical and hippocampal volumes, and their asymmetries., (Copyright © 2013 Wiley Periodicals, Inc.)

Male and female brains differ in both structure and function. Investigating this sexual dimorphism in healthy subjects is an important first step to ultimately gain insight into sex-specific differences in behavior and risk for neuropsychiatric disorders. The basal ganglia are among the main regions containing sex steroid receptors in the brain and play a central role in cognitive (dys)functioning. However, little is known about sexual dimorphism of different basal ganglia nuclei. The aim of the present study was to investigate sex-specific differences in basal ganglia morphology using MRI. We applied automatic volumetry on anatomical MRI data of two large cohorts of healthy young adults (n = 463 and n = 541) and assessed the volume of four major nuclei of the basal ganglia: caudate nucleus, globus pallidus, nucleus accumbens, and putamen, while controlling for total gray matter volume, total white matter volume, and age of the participant. No significant sex differences were found for caudate nucleus and nucleus accumbens, but males showed significantly larger volumes for globus pallidus and putamen, as confirmed in both cohorts. These results show that sexual dimorphism is neither a general effect in the basal ganglia nor confined to just one specific nucleus, and will aid the interpretation of differences in basal ganglia (dys)function between males and females., (Copyright © 2011 Wiley-Liss, Inc.)

Objective: Enhanced memory for emotionally charged events helps us to remember potentially vital information. There are large interindividual differences in emotional-memory enhancement, but little is known about their neurobiological basis. Recently, a functional deletion variant of the gene that codes for the α2b-adrenoceptor (ADRA2B) has been shown to affect memory for emotional experiences. Initial neuroimaging evidence linked this behavioral effect to increased amygdala activity, but its influence on successful memory processing remains unknown. Therefore, the aim of this study was to investigate the effect of the common deletion in the ADRA2B gene on neural activity related to specific mnemonic processing, successful memory formation, and retrieval., Methods: Twenty-three noncarriers (10 males) and 28 deletion carriers (13 males) with a mean age of 24 years were investigated while performing an emotional-learning task with sad and happy scenes. Functional magnetic resonance imaging was acquired both during memory formation and retrieval., Results: Although there were no differences in memory performance between groups, the common deletion variant of ADRA2B was related to enhanced activity in the amygdala and inferior frontal gyrus during successful emotional memory formation, but not retrieval. Deletion carriers showed a larger differential response in these brain regions between later-remembered and later-forgotten stimuli than nondeletion carriers did., Conclusion: Our results demonstrate that the ADRA2B polymorphism influences emotional memory formation but not memory retrieval in the amygdala and left inferior frontal gyrus., (Copyright © 2011 Wiley Periodicals, Inc.)