ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

Abstract

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Fig. 1. World Map of ENIGMA’s Working Groups.

The ENIGMA Consortium has grown to include over 1400 participating scientists from over 200 institutions, across 43 countries worldwide. ENIGMA is organized as a set of 50 WGs, studying 26 major brain diseases (see color key). Each group works closely with the others and consists of worldwide teams of experts in each brain disorder as well as experts in the major methods used to study each disorder. The diseases studied include major depressive disorder, bipolar disorder, schizophrenia, substance use disorder, post-traumatic stress disorder, attention-deficit/hyperactivity disorder, obsessive-compulsive disorder, and autism spectrum disorder, and several neurological disorders, including Parkinson’s disease, epilepsy, ataxia, and stroke. In recent years, new WGs were created that grew into worldwide consortia on epilepsy (Whelan et al.), eating disorders (King et al.), anxiety disorders (Groenewold et al.), antisocial behavior, and infant neuroimaging.

Fig. 2. ENIGMA’s Working Group Flowchart.

ENIGMA’s working groups are divided into technical groups that work on testing harmonized methods, and clinical groups that study different disorders and conditions across psychiatry and neurology, as well as some behaviors (e.g., schizotypy and antisocial behaviors). The use of harmonized analysis methods across all the working groups has enabled cross-disorder comparisons (e.g., in the affective/psychosis spectrum of depression to bipolar disorder to schizophrenia), and transdiagnostic analyses of risk factors such as childhood trauma across a number of disorders (such as major depressive disorder (MDD) and post-traumatic stress disorder (PTSD)). Several working groups, such as brain trauma and anxiety, consist of several subgroups examining subtypes (e.g., panic disorder or social anxiety), and allow analyses of overlap and differences (e.g., between military and civilian brain trauma).

Fig. 3. Genetic Influences on brain structure: effects of common and rare genetic variants.

ENIGMA’s large-scale genetic analyses study the effects of both common and rare genetic variants on brain measures. a A series of progressively larger genome-wide association studies have revealed over 45 genetic loci associated with subcortical structure volumes (Hibar et al., Satizabal et al.) and over 200 genetic loci associated with cortical thickness and surface area Grasby et al.. The Manhattan plots here (adapted from Hibar et al., show the genome (on the x-axis) and the evidence for association (as a logarithm of the p-value, on the y-axis) for each common genetic variant (or SNP) with the volume of each brain structure shown. b Genetics of Hippocampal Volume. A subsequent genome-wide association study (GWAS) of 33,536 individuals discovered six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, two lie within key genes involved in neuronal migration and microtubule assembly (ASTN2 and MAST4) (Hibar et al.). An interactive browser, ENIGMA-Vis—http://enigma-brain.org/enigmavis—can be used to navigate ENIGMA’s genomic data. Initially started as a web page to plot ENIGMA summary statistics data for a specific genomic region, ENIGMA-Vis grew over the years into a portal with tools to query, visualize, and navigate the effects, and relate them to other GWAS. c In complementary work on rare variants by the ENIGMA-CNV Working Group, Sønderby and colleagues (2018) examined effects of the 16p11.2 distal CNV that predisposes to psychiatric conditions including autism spectrum disorder and schizophrenia. ENIGMA (including the 16p11.2 European Consortium) and deCODE datasets were combined to discover negative dose-response associations with copy number on intracranial volume and regional caudate, pallidum and putamen volumes—suggesting a neuropathological pattern that may underlie the neurodevelopmental syndromes. The agreement across datasets is apparent in the Forest plots for each brain region. [Data adapted, with permission from the authors and publishers].

Fig. 4. ENIGMA’s large-scale studies of nine brain disorders.

Cortical gray matter thickness abnormalities as Cohen’s d, are mapped for nine different disorders, for which worldwide data were analyzed with the same harmonized methods. Although the cohorts included in the studies differed, as did the scanning sites and age ranges studied, some common and distinct patterns are apparent. Cortical maps for major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia show gradually more extensive profiles of deficits. Across all disorders, the less prevalent disorders tend to show greater effects in the brain: the relatively subtle pattern of hippocampal-limbic deficits in MDD broadens to include frontal deficits in bipolar disorder (consistent with frontal lobe dysfunction and impaired self-control). In schizophrenia, deficits widen to include almost the entire cortex—only the primary visual cortex (specifically the calcarine cortex) failed to show thickness alterations in patients, after meta-analysis. Autism spectrum disorder (ASD) and the 22q deletion syndrome (22q11DS)—a risk condition for ASD—are associated with hypertrophy in frontal brain regions, while patients with obsessive-compulsive disorder (OCD) and alcohol use disorder tend to show deficits in frontal brain regions involved in self-control and inhibition. More refined analyses are now relating symptom domains to these and other brain metrics, within and across these and other disorders.

Fig. 5. Subcortical abnormalities in schizophrenia, bipolar disorder, major depressive disorder, and ADHD.

a ENIGMA’s publications of the three largest neuroimaging papers on schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD), suggested widespread cross-disorder differences in effects (van Erp et al., Hibar et al.). By processing 21,199 people’s brain MRI scans consistently, we found greater brain structural abnormalities in SCZ and BD versus MDD, and a very different pattern in attention-deficit/hyperactivity disorder (ADHD; Hoogman et al.). Subcortically, all three disorders involve hippocampal volume deficits—greatest in SCZ, least in MDD, and intermediate in BD. As a slightly simplified ‘rule of thumb’, the hippocampus, ventricles, thalamus, amygdala and nucleus accumbens show volume reductions in MDD that are around half the magnitude of those seen in BD, which in turn are about half the magnitude of those seen in SCZ. The basal ganglia are an exception to this rule—perhaps because some antipsychotic treatments have hypertrophic effects on the basal ganglia, leading to volume excesses in medicated patients. In ADHD, however, the amygdala, caudate and putamen, and nucleus accumbens all show deficits, as does ICV (ventricular data is not included here for ADHD, as it was not measured in the ADHD study). A web portal, the ENIGMA Viewer, provides access to these summary statistics from ENIGMA’s published studies of psychiatric and neurological disorders (http://enigma-viewer.org/About_the_projects.html). b Independent work by the Japanese Consortium, COCORO, found a very similar set of effect sizes for group differences in subcortical volumes between schizophrenia patients and matched controls.

Fig. 6. White matter microstructure in schizophrenia, major depressive disorder, and 22q11.2 deletion syndrome.

a White matter microstructural abnormalities are shown, by tract, based on the largest-ever diffusion MRI studies of these three disorders. In schizophrenia (SCZ), fractional anisotropy, a measure of white matter microstructure, is lower in almost all individual regions, and in the full skeleton. In major depressive disorder (MDD), a weak pattern of effects is observed, again with MDD patients showing on average lower FA across the full white matter skeleton, when compared to controls. In comparisons between 22q11.2 deletion syndrome (22q11DS) and matched controls, by contrast, the average FA along the full white matter skeleton does not show systematic differences; instead, while some regions do show on average lower FA in affected individuals compared with controls, several white matter regions show higher FA. b Relative to appropriately matched groups of healthy controls (HC), group differences in fractional anisotropy are shown for ENIGMA’s studies of SCZ, MDD (both in adults), and 22q11.2 deletion syndrome. [Data adapted, with permission of the authors and publishers, from Kelly et al., van Velzen et al., and Villalón-Reina et al.; a key to the tract names appears in the original papers; some tracts (i.e. the hippocampal portion of the cingulum) were omitted from the 22q11DS analysis as they were not consistently in the field of view for some cohorts of the working group].

Fig. 7. Topology of large-scale scientific collaboration.

a The topology of scientific collaboration in ENIGMA has some properties that resemble a modular hierarchical network (Ravasz and Barabasi, Slaughter). In this diagram (a), nodes represent individual scientists working on a project, and links denote active scientific collaborations (that might result in co-authored publications, like this review, for example). ENIGMA’s WGs resemble the yellow sets of nodes: guided by a small group of WG chairs, several clusters of scientists coordinate projects applying various methods to the same datasets (e.g., MRI and DTI meta-analysis, machine learning, and modeling of clinical outcomes). WGs study different disorders with the same harmonized methods, enabling to cross-disorder collaborations across WGs. The modular organization allows independent and coordinated projects to proceed in parallel, distributing work and coordination, without requiring a central hub for all communication. Real clusters may differ in their number of members and links [(b) shows a different graph with a similar hierarchical modular form], and may change dynamically over time as new groups and projects form and projects end.