The neocortical infrastructure for language involves region-specific patterns of laminar gene expression.

The language network of the human brain has core components in the inferior frontal cortex and superior/middle temporal cortex, with left-hemisphere dominance in most people. Functional specialization and interconnectivity of these neocortical regions is likely to be reflected in their molecular and cellular profiles. Excitatory connections between cortical regions arise and innervate according to layer-specific patterns. Here, we generated a gene expression dataset from human postmortem cortical tissue samples from core language network regions, using spatial transcriptomics to discriminate gene expression across cortical layers. Integration of these data with existing single-cell expression data identified 56 genes that showed differences in laminar expression profiles between the frontal and temporal language cortex together with upregulation in layer II/III and/or layer V/VI excitatory neurons. Based on data from large-scale genome-wide screening in the population, DNA variants within these 56 genes showed set-level associations with interindividual variation in structural connectivity between the left-hemisphere frontal and temporal language cortex, and with the brain-related disorders dyslexia and schizophrenia which often involve affected language. These findings identify region-specific patterns of laminar gene expression as a feature of the brain's language network.

The universe is asymmetric, the mouse brain too.

Hemispheric brain asymmetry is a basic organizational principle of the human brain and has been implicated in various psychiatric conditions, including autism spectrum disorder. Brain asymmetry is not a uniquely human feature and is observed in other species such as the mouse. Yet, asymmetry patterns are generally nuanced, and substantial sample sizes are required to detect these patterns. In this pre-registered study, we use a mouse dataset from the Province of Ontario Neurodevelopmental Network, which comprises structural MRI data from over 2000 mice, including genetic models for autism spectrum disorder, to reveal the scope and magnitude of hemispheric asymmetry in the mouse. Our findings demonstrate the presence of robust hemispheric asymmetry in the mouse brain, such as larger right hemispheric volumes towards the anterior pole and larger left hemispheric volumes toward the posterior pole, opposite to what has been shown in humans. This suggests the existence of species-specific traits. Further clustering analysis identified distinct asymmetry patterns in autism spectrum disorder models, a phenomenon that is also seen in atypically developing participants. Our study shows potential for the use of mouse models to understand the biological bases of typical and atypical brain asymmetry but also warrants caution as asymmetry patterns seem to differ between humans and mice.

Using neuroimaging genomics to investigate the evolution of human brain structure.

Alterations in brain size and organization represent some of the most distinctive changes in the emergence of our species. Yet, there is limited understanding of how genetic factors contributed to altered neuroanatomy during human evolution. Here, we analyze neuroimaging and genetic data from up to 30,000 people in the UK Biobank and integrate with genomic annotations for different aspects of human evolution, including those based on ancient DNA and comparative genomics. We show that previously reported signals of recent polygenic selection for cortical anatomy are not replicable in a more ancestrally homogeneous sample. We then investigate relationships between evolutionary annotations and common genetic variants shaping cortical surface area and white-matter connectivity for each hemisphere. Our analyses identify single-nucleotide polymorphism heritability enrichment in human-gained regulatory elements that are active in early brain development, affecting surface areas of several parts of the cortex, including left-hemispheric speech-associated regions. We also detect heritability depletion in genomic regions with Neanderthal ancestry for connectivity of the uncinate fasciculus; this is a white-matter tract involved in memory, language, and socioemotional processing with relevance to neuropsychiatric disorders. Finally, we show that common genetic loci associated with left-hemispheric pars triangularis surface area overlap with a human-gained enhancer and affect regulation of ZIC4, a gene implicated in neurogenesis. This work demonstrates how genomic investigations of present-day neuroanatomical variation can help shed light on the complexities of our evolutionary past.

Handedness and its genetic influences are associated with structural asymmetries of the cerebral cortex in 31,864 individuals.

Roughly 10% of the human population is left-handed, and this rate is increased in some brain-related disorders. The neuroanatomical correlates of hand preference have remained equivocal. We resampled structural brain image data from 28,802 right-handers and 3,062 left-handers (UK Biobank population dataset) to a symmetrical surface template, and mapped asymmetries for each of 8,681 vertices across the cerebral cortex in each individual. Left-handers compared to right-handers showed average differences of surface area asymmetry within the fusiform cortex, the anterior insula, the anterior middle cingulate cortex, and the precentral cortex. Meta-analyzed functional imaging data implicated these regions in executive functions and language. Polygenic disposition to left-handedness was associated with two of these regional asymmetries, and 18 loci previously linked with left-handedness by genome-wide screening showed associations with one or more of these asymmetries. Implicated genes included six encoding microtubule-related proteins: TUBB, TUBA1B, TUBB3, TUBB4A, MAP2, and NME7-mutations in the latter can cause left to right reversal of the visceral organs. There were also two cortical regions where average thickness asymmetry was altered in left-handedness: on the postcentral gyrus and the inferior occipital cortex, functionally annotated with hand sensorimotor and visual roles. These cortical thickness asymmetries were not heritable. Heritable surface area asymmetries of language-related regions may link the etiologies of hand preference and language, whereas nonheritable asymmetries of sensorimotor cortex may manifest as consequences of hand preference.

Machine learning of large-scale multimodal brain imaging data reveals neural correlates of hand preference.

Lateralization is a fundamental characteristic of many behaviors and the organization of the brain, and atypical lateralization has been suggested to be linked to various brain-related disorders such as autism and schizophrenia. Right-handedness is one of the most prominent markers of human behavioural lateralization, yet its neurobiological basis remains to be determined. Here, we present a large-scale analysis of handedness, as measured by self-reported direction of hand preference, and its variability related to brain structural and functional organization in the UK Biobank (N = 36,024). A multivariate machine learning approach with multi-modalities of brain imaging data was adopted, to reveal how well brain imaging features could predict individual's handedness (i.e., right-handedness vs. non-right-handedness) and further identify the top brain signatures that contributed to the prediction. Overall, the results showed a good prediction performance, with an area under the receiver operating characteristic curve (AUROC) score of up to 0.72, driven largely by resting-state functional measures. Virtual lesion analysis and large-scale decoding analysis suggested that the brain networks with the highest importance in the prediction showed functional relevance to hand movement and several higher-level cognitive functions including language, arithmetic, and social interaction. Genetic analyses of contributions of common DNA polymorphisms to the imaging-derived handedness prediction score showed a significant heritability (h2=7.55%, p <0.001) that was similar to and slightly higher than that for the behavioural measure itself (h2=6.74%, p <0.001). The genetic correlation between the two was high (rg=0.71), suggesting that the imaging-derived score could be used as a surrogate in genetic studies where the behavioural measure is not available. This large-scale study using multimodal brain imaging and multivariate machine learning has shed new light on the neural correlates of human handedness.

Reproducibility in the absence of selective reporting: An illustration from large-scale brain asymmetry research.

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes.

Mapping brain asymmetry in health and disease through the ENIGMA consortium.

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.

An overview of the first 5 years of the ENIGMA obsessive-compulsive disorder working group: The power of worldwide collaboration.

Neuroimaging has played an important part in advancing our understanding of the neurobiology of obsessive-compulsive disorder (OCD). At the same time, neuroimaging studies of OCD have had notable limitations, including reliance on relatively small samples. International collaborative efforts to increase statistical power by combining samples from across sites have been bolstered by the ENIGMA consortium; this provides specific technical expertise for conducting multi-site analyses, as well as access to a collaborative community of neuroimaging scientists. In this article, we outline the background to, development of, and initial findings from ENIGMA's OCD working group, which currently consists of 47 samples from 34 institutes in 15 countries on 5 continents, with a total sample of 2,323 OCD patients and 2,325 healthy controls. Initial work has focused on studies of cortical thickness and subcortical volumes, structural connectivity, and brain lateralization in children, adolescents and adults with OCD, also including the study on the commonalities and distinctions across different neurodevelopment disorders. Additional work is ongoing, employing machine learning techniques. Findings to date have contributed to the development of neurobiological models of OCD, have provided an important model of global scientific collaboration, and have had a number of clinical implications. Importantly, our work has shed new light on questions about whether structural and functional alterations found in OCD reflect neurodevelopmental changes, effects of the disease process, or medication impacts. We conclude with a summary of ongoing work by ENIGMA-OCD, and a consideration of future directions for neuroimaging research on OCD within and beyond ENIGMA.

Inherited variants in CHD3 show variable expressivity in Snijders Blok-Campeau syndrome.

PURPOSE: Common diagnostic next-generation sequencing strategies are not optimized to identify inherited variants in genes associated with dominant neurodevelopmental disorders as causal when the transmitting parent is clinically unaffected, leaving a significant number of cases with neurodevelopmental disorders undiagnosed. METHODS: We characterized 21 families with inherited heterozygous missense or protein-truncating variants in CHD3, a gene in which de novo variants cause Snijders Blok-Campeau syndrome. RESULTS: Computational facial and Human Phenotype Ontology-based comparisons showed that the phenotype of probands with inherited CHD3 variants overlaps with the phenotype previously associated with de novo CHD3 variants, whereas heterozygote parents are mildly or not affected, suggesting variable expressivity. In addition, similarly reduced expression levels of CHD3 protein in cells of an affected proband and of healthy family members with a CHD3 protein-truncating variant suggested that compensation of expression from the wild-type allele is unlikely to be an underlying mechanism. Notably, most inherited CHD3 variants were maternally transmitted. CONCLUSION: Our results point to a significant role of inherited variation in Snijders Blok-Campeau syndrome, a finding that is critical for correct variant interpretation and genetic counseling and warrants further investigation toward understanding the broader contributions of such variation to the landscape of human disease.

Patterns of brain asymmetry associated with polygenic risks for autism and schizophrenia implicate language and executive functions but not brain masculinization.

Autism spectrum disorder (ASD) and schizophrenia have been conceived as partly opposing disorders in terms of systemizing vs. empathizing cognitive styles, with resemblances to male vs. female average sex differences. Left-right asymmetry of the brain is an important aspect of its organization that shows average differences between the sexes and can be altered in both ASD and schizophrenia. Here we mapped multivariate associations of polygenic risk scores for ASD and schizophrenia with asymmetries of regional cerebral cortical surface area, thickness, and subcortical volume measures in 32,256 participants from the UK Biobank. Polygenic risks for the two disorders were positively correlated (r = 0.08, p = 7.13 × 10-50) and both were higher in females compared to males, consistent with biased participation against higher-risk males. Each polygenic risk score was associated with multivariate brain asymmetry after adjusting for sex, ASD r = 0.03, p = 2.17 × 10-9, and schizophrenia r = 0.04, p = 2.61 × 10-11, but the multivariate patterns were mostly distinct for the two polygenic risks and neither resembled average sex differences. Annotation based on meta-analyzed functional imaging data showed that both polygenic risks were associated with asymmetries of regions important for language and executive functions, consistent with behavioral associations that arose in phenome-wide association analysis. Overall, the results indicate that distinct patterns of subtly altered brain asymmetry may be functionally relevant manifestations of polygenic risks for ASD and schizophrenia, but do not support brain masculinization or feminization in their etiologies.

Genome-wide association study reveals new insights into the heritability and genetic correlates of developmental dyslexia.

Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40-60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p < 2.8 × 10-6) enrichment of associations at the gene level, for LOC388780 (20p13; uncharacterized gene), and for VEPH1 (3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20-25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (at pT = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase; p = 8 × 10-13), bipolar disorder (1.53[1.44; 1.63]; p = 1 × 10-43), schizophrenia (1.36[1.28; 1.45]; p = 4 × 10-22), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30]; p = 3 × 10-12), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96]; p = 5 × 10-4), educational attainment (0.86[0.82; 0.91]; p = 2 × 10-7), and intelligence (0.72[0.68; 0.76]; p = 9 × 10-29). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence.

Interhemispheric Relationship of Genetic Influence on Human Brain Connectivity.

To understand the origins of interhemispheric differences and commonalities/coupling in human brain wiring, it is crucial to determine how homologous interregional connectivities of the left and right hemispheres are genetically determined and related. To address this, in the present study, we analyzed human twin and pedigree samples with high-quality diffusion magnetic resonance imaging tractography and estimated the heritability and genetic correlation of homologous left and right white matter (WM) connections. The results showed that the heritability of WM connectivity was similar and coupled between the 2 hemispheres and that the degree of overlap in genetic factors underlying homologous WM connectivity (i.e., interhemispheric genetic correlation) varied substantially across the human brain: from complete overlap to complete nonoverlap. Particularly, the heritability was significantly stronger and the chance of interhemispheric complete overlap in genetic factors was higher in subcortical WM connections than in cortical WM connections. In addition, the heritability and interhemispheric genetic correlations were stronger for long-range connections than for short-range connections. These findings highlight the determinants of the genetics underlying WM connectivity and its interhemispheric relationships, and provide insight into genetic basis of WM connectivity asymmetries in both healthy and disease states.

Large-Scale Phenomic and Genomic Analysis of Brain Asymmetrical Skew.

The human cerebral hemispheres show a left-right asymmetrical torque pattern, which has been claimed to be absent in chimpanzees. The functional significance and developmental mechanisms are unknown. Here, we carried out the largest-ever analysis of global brain shape asymmetry in magnetic resonance imaging data. Three population datasets were used, UK Biobank (N = 39 678), Human Connectome Project (N = 1113), and BIL&GIN (N = 453). At the population level, there was an anterior and dorsal skew of the right hemisphere, relative to the left. Both skews were associated independently with handedness, and various regional gray and white matter metrics oppositely in the two hemispheres, as well as other variables related to cognitive functions, sociodemographic factors, and physical and mental health. The two skews showed single nucleotide polymorphisms-based heritabilities of 4-13%, but also substantial polygenicity in causal mixture model analysis, and no individually significant loci were found in genome-wide association studies for either skew. There was evidence for a significant genetic correlation between horizontal brain skew and autism, which requires future replication. These results provide the first large-scale description of population-average brain skews and their inter-individual variations, their replicable associations with handedness, and insights into biological and other factors which associate with human brain asymmetry.

Whole-genome sequencing identifies functional noncoding variation in SEMA3C that cosegregates with dyslexia in a multigenerational family.

Dyslexia is a common heritable developmental disorder involving impaired reading abilities. Its genetic underpinnings are thought to be complex and heterogeneous, involving common and rare genetic variation. Multigenerational families segregating apparent monogenic forms of language-related disorders can provide useful entrypoints into biological pathways. In the present study, we performed a genome-wide linkage scan in a three-generational family in which dyslexia affects 14 of its 30 members and seems to be transmitted with an autosomal dominant pattern of inheritance. We identified a locus on chromosome 7q21.11 which cosegregated with dyslexia status, with the exception of two cases of phenocopy (LOD = 2.83). Whole-genome sequencing of key individuals enabled the assessment of coding and noncoding variation in the family. Two rare single-nucleotide variants (rs144517871 and rs143835534) within the first intron of the SEMA3C gene cosegregated with the 7q21.11 risk haplotype. In silico characterization of these two variants predicted effects on gene regulation, which we functionally validated for rs144517871 in human cell lines using luciferase reporter assays. SEMA3C encodes a secreted protein that acts as a guidance cue in several processes, including cortical neuronal migration and cellular polarization. We hypothesize that these intronic variants could have a cis-regulatory effect on SEMA3C expression, making a contribution to dyslexia susceptibility in this family.

Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium.

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 (Enhancing NeuroImaging Genetics through Meta-Analysis) 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 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 significant, replicable 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.

A set of regulatory genes co-expressed in embryonic human brain is implicated in disrupted speech development.

Genetic investigations of people with impaired development of spoken language provide windows into key aspects of human biology. Over 15 years after FOXP2 was identified, most speech and language impairments remain unexplained at the molecular level. We sequenced whole genomes of nineteen unrelated individuals diagnosed with childhood apraxia of speech, a rare disorder enriched for causative mutations of large effect. Where DNA was available from unaffected parents, we discovered de novo mutations, implicating genes, including CHD3, SETD1A and WDR5. In other probands, we identified novel loss-of-function variants affecting KAT6A, SETBP1, ZFHX4, TNRC6B and MKL2, regulatory genes with links to neurodevelopment. Several of the new candidates interact with each other or with known speech-related genes. Moreover, they show significant clustering within a single co-expression module of genes highly expressed during early human brain development. This study highlights gene regulatory pathways in the developing brain that may contribute to acquisition of proficient speech.

Multivariate genome-wide association study of rapid automatised naming and rapid alternating stimulus in Hispanic American and African-American youth.

BACKGROUND: Rapid automatised naming (RAN) and rapid alternating stimulus (RAS) are reliable predictors of reading disability. The underlying biology of reading disability is poorly understood. However, the high correlation among RAN, RAS and reading could be attributable to shared genetic factors that contribute to common biological mechanisms. OBJECTIVE: To identify shared genetic factors that contribute to RAN and RAS performance using a multivariate approach. METHODS: We conducted a multivariate genome-wide association analysis of RAN Objects, RAN Letters and RAS Letters/Numbers in a sample of 1331 Hispanic American and African-American youth. Follow-up neuroimaging genetic analysis of cortical regions associated with reading ability in an independent sample and epigenetic examination of extant data predicting tissue-specific functionality in the brain were also conducted. RESULTS: Genome-wide significant effects were observed at rs1555839 (p=4.03×10-8) and replicated in an independent sample of 318 children of European ancestry. Epigenetic analysis and chromatin state models of the implicated 70 kb region of 10q23.31 support active transcription of the gene RNLS in the brain, which encodes a catecholamine metabolising protein. Chromatin contact maps of adult hippocampal tissue indicate a potential enhancer-promoter interaction regulating RNLS expression. Neuroimaging genetic analysis in an independent, multiethnic sample (n=690) showed that rs1555839 is associated with structural variation in the right inferior parietal lobule. CONCLUSION: This study provides support for a novel trait locus at chromosome 10q23.31 and proposes a potential gene-brain-behaviour relationship for targeted future functional analysis to understand underlying biological mechanisms for reading disability.

On the other hand: including left-handers in cognitive neuroscience and neurogenetics.

Left-handers are often excluded from study cohorts in neuroscience and neurogenetics in order to reduce variance in the data. However, recent investigations have shown that the inclusion or targeted recruitment of left-handers can be informative in studies on a range of topics, such as cerebral lateralization and the genetic underpinning of asymmetrical brain development. Left-handed individuals represent a substantial portion of the human population and therefore left-handedness falls within the normal range of human diversity; thus, it is important to account for this variation in our understanding of brain functioning. We call for neuroscientists and neurogeneticists to recognize the potential of studying this often-discarded group of research subjects.

Exome sequencing in an admixed isolated population indicates NFXL1 variants confer a risk for specific language impairment.

Children affected by Specific Language Impairment (SLI) fail to acquire age appropriate language skills despite adequate intelligence and opportunity. SLI is highly heritable, but the understanding of underlying genetic mechanisms has proved challenging. In this study, we use molecular genetic techniques to investigate an admixed isolated founder population from the Robinson Crusoe Island (Chile), who are affected by a high incidence of SLI, increasing the power to discover contributory genetic factors. We utilize exome sequencing in selected individuals from this population to identify eight coding variants that are of putative significance. We then apply association analyses across the wider population to highlight a single rare coding variant (rs144169475, Minor Allele Frequency of 4.1% in admixed South American populations) in the NFXL1 gene that confers a nonsynonymous change (N150K) and is significantly associated with language impairment in the Robinson Crusoe population (p = 2.04 × 10-4, 8 variants tested). Subsequent sequencing of NFXL1 in 117 UK SLI cases identified four individuals with heterozygous variants predicted to be of functional consequence. We conclude that coding variants within NFXL1 confer an increased risk of SLI within a complex genetic model.

ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide.

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others1, ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.