Significant concordance of genetic variation that increases both the risk for obsessive-compulsive disorder and the volumes of the nucleus accumbens and putamen

Opening new vistas on obsessive-compulsive disorder with the observing response task

Obsessive-compulsive disorder (OCD), a highly prevalent and debilitating disorder, is incompletely understood in terms of underpinning behavioural, psychological, and neural mechanisms. This is attributable to high symptomatic heterogeneity; cardinal features comprise obsessions and compulsions, including clinical subcategories. While obsessive and intrusive thoughts are arguably unique to humans, dysfunctional behaviours analogous to those seen in clinical OCD have been examined in nonhuman animals. Genetic, ethological, pharmacological, and neurobehavioural approaches all contribute to understanding the emergence and persistence of compulsive behaviour. One behaviour of particular interest is maladaptive checking, whereby human patients excessively perform checking rituals despite these serving no purpose. Dysfunctional and excessive checking is the most common symptom associated with OCD and can be readily operationalised in rodents. This review considers animal models of OCD, the neural circuitries associated with impairments in habit-based and goal-directed behaviour, and how these may link to the compulsions observed in OCD. We further review the Observing Response Task (ORT), an appetitive instrumental learning procedure that distinguishes between functional and dysfunctional checking, with translational application in humans and rodents. By shedding light on the psychological and neural bases of compulsive-like checking, the ORT has potential to offer translational insights into the underlying mechanisms of OCD, in addition to being a platform for testing psychological and neurochemical treatment approaches.

Disclosing common biological signatures and predicting new therapeutic targets in schizophrenia and obsessive-compulsive disorder by integrated bioinformatics analysis

Schizophrenia (SCZ) is a severe mental illness mainly characterized by a number of psychiatric symptoms. Obsessive-compulsive disorder (OCD) is a long-lasting and devastating mental disorder. SCZ has high co-occurrence with OCD resulting in the emergence of a concept entitled "schizo-obsessive disorder" as a new specific clinical entity with more severe psychiatric symptoms. Many studies have been done on SCZ and OCD, but the common pathogenesis between them is not clear yet. Therefore, this study aimed to identify shared genetic basis, potential biomarkers and therapeutic targets between these two disorders. Gene sets were extracted from the Geneweaver and Harmonizome databases for each disorder. Interestingly, the combination of both sets revealed 89 common genes between SCZ and OCD, the most important of which were BDNF, SLC6A4, GAD1, HTR2A, GRIN2B, DRD2, SLC6A3, COMT, TH and DLG4. Then, we conducted a comprehensive bioinformatics analysis of the common genes. Receptor activity as the molecular functions, neuron projection and synapse as the cellular components as well as serotonergic synapse, dopaminergic synapse and alcoholism as the pathways were the most significant commonalities in enrichment analyses. In addition, transcription factor (TFs) analysis predicted significant TFs such as HMGA1, MAPK14, HINFP and TEAD2. Hsa-miR-3121-3p and hsa-miR-495-3p were the most important microRNAs (miRNAs) associated with both disorders. Finally, our study predicted 19 existing drugs (importantly, Haloperidol, Fluoxetine and Melatonin) that may have a potential influence on this co-occurrence. To summarize, this study may help us to better understand and handle the co-occurrence of SCZ and OCD by identifying potential biomarkers and therapeutic targets.

Correlations between single nucleotide polymorphisms in obsessive-compulsive disorder with the clinical features or response to therapy

Obsessive-compulsive disorder (OCD) is a debilitating neuropsychiatric disorder, in which the patient endures intrusive thoughts or is compelled to perform repetitive or ritualized actions. Many cases of OCD are considered to be familial or heritable in nature. It has been shown that a variety of internal and external risk factors are involved in the pathogenesis of OCD. Among the internal factors, genetic modifications play a critical role in the pathophysiological process. Despite many investigations performed to determine the candidate genes, the precise genetic factors involved in the disease remain largely undetermined. The present review summarizes the single nucleotide polymorphisms that have been proposed to be associated with OCD symptoms, early onset disease, neuroimaging results, and response to therapy. This information could help us to draw connections between genetics and OCD symptoms, better characterize OCD in individual patients, understand OCD prognosis, and design more targeted personalized treatment approaches.

Early intervention in obsessive-compulsive disorder: From theory to practice

Obsessive-compulsive disorder (OCD) is frequent and often disabling. Yet, correct diagnosis and appropriate treatment implementation are usually delayed, with undesirable consequences. In this paper we review the rationale for early intervention in OCD and provide recommendations for early intervention services. Two scenarios are discussed, i.e., subclinical (prodromal) obsessive-compulsive symptoms (OCS) and full-blown OCD. Although the typical patient with OCD reports a long history of subclinical OCS, longitudinal studies suggest most individuals with OCS in the community do not convert to full-blown OCD. Thus, research on "at risk" phenotypes for OCD and how they should incorporate different risk factors (e.g., polygenic risk scores) are badly needed. For this specific scenario, preventative treatments that are cheap, well tolerated and highly scalable (e.g., lifestyle interventions) are of major interest. On the other hand, increasing evidence suggests OCD to be a progressive disorder and the severity and duration of illness to be associated with both biological changes and increased clinical complexity, including greater number of physical and psychiatric comorbidities, increased family accommodation and worse treatment response. Therefore, prompt identification and early treatment implementation for full-blown OCD are also critical for ethical, clinical and therapeutic reasons. Based on the existing findings, we argue that, regardless of focusing on subclinical OCS or clinical OCD, early intervention services need to target a childhood age group. In addition to delivering well established treatments to people with full-blown OCD early on their illness, early intervention services also need to provide psychoeducation for patients, families and teachers.

Subcortical shape in pediatric and adult obsessive-compulsive disorder

BACKGROUND

Obsessive-compulsive disorder (OCD) implicates alterations in cortico-striato-thalamo-cortical and fronto-limbic circuits. Building on prior structural findings, this is the largest study to date examining subcortical surface morphometry in OCD.

METHODS

Structural magnetic resonance imaging data were collected from 200 participants across development (5-55 years): 28 youth and 75 adults with OCD and 27 psychiatrically healthy youth and 70 adults. General linear models were used to assess group differences and group-by-age interactions on subcortical shape (FSL FIRST).

RESULTS

Compared to healthy participants, those with OCD exhibited surface expansions on the right nucleus accumbens and inward left amygdala deformations, which were associated with greater OCD symptom severity ([Children's] Yale-Brown Obsessive-Compulsive Scale). Group-by-age interactions indicated that accumbens group differences were driven by younger participants and that right pallidum shape was associated inversely with age in healthy participants, but not in participants with OCD. No differences in the shape of other subcortical regions or in volumes (FreeSurfer) were detected in supplementary analyses.

CONCLUSIONS

This study is the largest to date examining subcortical shape in OCD and the first to do so across the developmental spectrum. NAcc and amygdala shape deformation builds on extant neuroimaging findings and suggests subtle, subregional alterations beyond volumetric findings. Results shed light on morphometric alterations in OCD, informing current pathophysiological models.

Symptom provocation in obsessive-compulsive disorder: A voxel-based meta-analysis and meta-analytic connectivity modeling

BACKGROUND

Obsessive-compulsive disorder (OCD) is a heterogeneous psychiatric illness with a complex array of symptoms and potentially distinct neural underpinnings. We employed meta-analysis and connectivity modeling of symptom dimensions to delineate the circuit mechanisms of OCD.

METHODS

With the activation likelihood estimation (ALE) algorithm we performed meta-analysis of whole-brain functional magnetic resonance imaging (fMRI) studies of symptom provocation. We contrasted all OCD patients and controls in a primary analysis and divided the studies according to clinical symptoms in secondary meta-analyses. Finally, we employed meta-analytic connectivity modeling analyses (MACMs) to examine co-activation patterns of the brain regions revealed in the primary meta-analysis.

RESULTS

A total of 14 experiments from 12 eligible studies with a total of 238 OCD patients (124 men) and 219 healthy controls (120 men) were included in the primary analysis. OCD patients showed higher activation in the right caudate body/putamen/insula and lower activation in the left orbitofrontal cortex (OFC), left inferior frontal gyrus (IFG), left caudate body/middle cingulate cortex (MCC), right middle temporal gyrus (MTG), middle occipital gyrus (MOG) and right lateral occipital gyrus (LOG). MACMs revealed significant co-activation between left IFG and left caudate body/MCC, left MOG and right LOG, right LOG and MTG. In the secondary meta-analyses, the washing subgroup showed higher activation in the right OFC, bilateral ACC, left MOG and right caudate body.

CONCLUSION

OCD patients showed elevated dorsal striatal activation during symptom provocation. In contrast, the washing subgroup engaged higher activation in frontal, temporal and posterior cortical structures as well as right caudate body. Broadly consistent with the proposition of cortico-striatal-thalamic-cortical circuit dysfunction, these findings highlight potentially distinct neural circuits that may underlie the symptoms and potentially etiological subtypes of OCD.

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.

Classification of Obsessive-Compulsive Disorder Using Distance Correlation on Resting-State Functional MRI Images

Both the Pearson correlation and partial correlation methods have been widely used in the resting-state functional MRI (rs-fMRI) studies. However, they can only measure linear relationship, although partial correlation excludes some indirect effects. Recent distance correlation can discover both the linear and non-linear dependencies. Our goal was to use the multivariate pattern analysis to compare the ability of such three correlation methods to distinguish between the patients with obsessive-compulsive disorder (OCD) and healthy control subjects (HCSs), so as to find optimal correlation method. The main process includes four steps. First, the regions of interest are defined by automated anatomical labeling (AAL). Second, functional connectivity (FC) matrices are constructed by the three correlation methods. Third, the best discriminative features are selected by support vector machine recursive feature elimination (SVM-RFE) with a stratified N-fold cross-validation strategy. Finally, these discriminative features are used to train a classifier. We had a total of 128 subjects out of which 61 subjects had OCD and 67 subjects were normal. All the three correlation methods with SVM have achieved good results, among which distance correlation is the best [accuracy = 93.01%, specificity = 89.71%, sensitivity = 95.08%, and area under the receiver-operating characteristic curve (AUC) = 0.94], followed by Pearson correlation and partial correlation is the last. The most discriminative regions of the brain for distance correlation are right dorsolateral superior frontal gyrus, orbital part of left superior frontal gyrus, orbital part of right middle frontal gyrus, right anterior cingulate and paracingulate gyri, left the supplementary motor area, and right precuneus, which are the promising biomarkers of OCD.

Genomics of Obsessive-Compulsive Disorder-Toward Personalized Medicine in the Era of Big Data

Pathogenesis of obsessive-compulsive disorder (OCD) mainly involves dysregulation of serotonergic neurotransmission, but a number of other factors are involved. Genetic underprints of OCD fall under the category of "common disease common variant hypothesis," that suggests that if a disease that is heritable is common in the population (a prevalence >1-5%), then the genetic contributors-specific variations in the genetic code-will also be common in the population. Therefore, the genetic contribution in OCD is believed to come from multiple genes simultaneously and it is considered a polygenic disorder. Genomics offers a number of advanced tools to determine causal relationship between the exposure and the outcome of interest. Particularly, methods such as polygenic risk score (PRS) or Mendelian Randomization (MR) enable investigation of new pathways involved in OCD pathogenesis. This premise is also facilitated by the existence of publicly available databases that include vast study samples. Examples include population-based studies such as UK Biobank, China Kadoorie Biobank, Qatar Biobank, All of US Program sponsored by National Institute of Health or Generations launched by Yale University, as well as disease-specific databases, that include patients with OCD and co-existing pathologies, with the following examples: Psychiatric Genomics Consortium (PGC), ENIGMA OCD, The International OCD Foundation Genetics Collaborative (IOCDF-GC) or OCD Collaborative Genetic Association Study. The aim of this review is to present a comprehensive overview of the available Big Data resources for the study of OCD pathogenesis in the context of genomics and demonstrate that OCD should be considered a disorder which requires the approaches offered by personalized medicine.

Polygenic risk for obsessive-compulsive disorder (OCD) predicts brain response during working memory task in OCD, unaffected relatives, and healthy controls

Alterations in frontal and parietal neural activations during working memory task performance have been suggested as a candidate endophenotype of obsessive-compulsive disorder (OCD) in studies involving first-degree relatives. However, the direct link between genetic risk for OCD and neuro-functional alterations during working memory performance has not been investigated to date. Thus, the aim of the current functional magnetic resonance imaging (fMRI) study was to test the direct association between polygenic risk for OCD and neural activity during the performance of a numeric n-back task with four working memory load conditions in 128 participants, including patients with OCD, unaffected first-degree relatives of OCD patients, and healthy controls. Behavioral results show a significant performance deficit at high working memory load in both patients with OCD and first-degree relatives (p < 0.05). A whole-brain analysis of the fMRI data indicated decreased neural activity in bilateral inferior parietal lobule and dorsolateral prefrontal cortex in both patients and relatives. Most importantly, OCD polygenic risk scores predicted neural activity in orbitofrontal cortex. Results indicate that genetic risk for OCD can partly explain alterations in brain response during working memory performance, supporting the notion of a neuro-functional endophenotype for OCD.

Disrupted pathways from frontal-parietal cortex to basal ganglia and cerebellum in patients with unmedicated obsessive compulsive disorder as observed by whole-brain resting-state effective connectivity analysis - a small sample pilot study

OBJECTIVE

To date, a systematic characterization of abnormalities in resting-state effective connectivity (rsEC) in obsessive-compulsive disorder (OCD) is lacking. The present study aimed to systematically characterize whole-brain rsEC in OCD patients as compared to healthy controls.

METHODS

Using resting-state fMRI data of 50 unmedicated patients with OCD and 50 healthy participants, we constructed whole-brain rsEC networks using Granger causality analysis followed by univariate and multivariate comparisons between patients and controls. Similar analyses were performed for resting-state functional connectivity (rsFC) networks to examine how rsFC and rsEC differentially capture abnormal brain connectivity in OCD.

RESULTS

Univariate comparisons identified 10 rsEC networks that were significantly disrupted in patients, and which were mainly associated with frontal-parietal cortex, basal ganglia, and cerebellum. Conversely, abnormal rsFC networks were widely distributed throughout the whole brain. Multivariate pattern analysis revealed a classification accuracy as high as 80.5% for distinguishing patients from controls using combined whole-brain rsEC and rsFC.

CONCLUSIONS

The results of the present study suggest disrupted communication of information from frontal-parietal cortex to basal ganglia and cerebellum in OCD patients. Using combined whole-brain rsEC and rsFC, multivariate pattern analysis revealed a classification accuracy as high as 80.5% for distinguishing patients from controls. The alterations observed in OCD patients could aid in identifying treatment mechanisms for OCD.

Overlap in genetic risk for cross-disorder vulnerability to mental disorders and genetic risk for altered subcortical brain volumes

BACKGROUND

There have been considerable recent advances in understanding the genetic architecture of psychiatric disorders as well as the underlying neurocircuitry. However, there is little work on the concordance of genetic variations that increase risk for cross-disorder vulnerability, and those that influence subcortical brain structures. We undertook a genome-wide investigation of the genetic overlap between cross-disorder vulnerability to psychiatric disorders (p-factor) and subcortical brain structures.

METHODS

Summary statistics were obtained from the PGC cross-disorder genome-wide association study (GWAS) (N_case= 232,964, N_control= 494,162) and the CHARGE-ENIGMA subcortical brain volumes GWAS (N=38,851). SNP effect concordance analysis (SECA) was used to assess pleiotropy and concordance. Linkage Disequilibrium (LD) Score Regression and ρ-HESS were used to assess genetic correlation and conditional false discovery (cFDR) was used to identify variants associated with p-factor, conditional on the variants association with subcortical brain volumes.

RESULTS

Evidence of global pleiotropy between p-factor and all subcortical brain regions was observed. Risk variants for p-factor correlated negatively with brainstem. A total of 787 LD-independent variants were significantly associated with p-factor when conditioned on the subcortical GWAS results. Gene set enrichment analysis of these variants implicated actin binding and neuronal regulation.

LIMITATIONS

SECA could be biased due to the potential presence of overlapping study participants in the p-factor and subcortical GWASs.

CONCLUSION

Findings of genome-wide pleiotropy and possible concordance between genetic variants that contribute to p-factor and smaller brainstem volumes, are consistent with previous work. cFDR results highlight actin binding and neuron regulation as key underlying mechanisms. Further fine-grained delineation of these mechanisms is needed to advance the field.

Cutting-edge genetics in obsessive-compulsive disorder

This article reviews recent advances in the genetics of obsessive-compulsive disorder (OCD). We cover work on the following: genome-wide association studies, whole-exome sequencing studies, copy number variation studies, gene expression, polygenic risk scores, gene–environment interaction, experimental animal systems, human cell models, imaging genetics, pharmacogenetics, and studies of endophenotypes. Findings from this work underscore the notion that the genetic architecture of OCD is highly complex and shared with other neuropsychiatric disorders. Also, the latest evidence points to the participation of gene networks involved in synaptic transmission, neurodevelopment, and the immune and inflammatory systems in this disorder. We conclude by highlighting that further study of the genetic architecture of OCD, a great part of which remains to be elucidated, could benefit the development of diagnostic and therapeutic approaches based on the biological basis of the disorder. Studies to date revealed that OCD is not a simple homogeneous entity, but rather that the underlying biological pathways are variable and heterogenous. We can expect that translation from bench to bedside, through continuous effort and collaborative work, will ultimately transform our understanding of what causes OCD and thus how best to treat it.

Targeting presynaptic H3 heteroreceptor in nucleus accumbens to improve anxiety and obsessive-compulsive-like behaviors

Anxiety commonly co-occurs with obsessive-compulsive disorder (OCD). Both of them are closely related to stress. However, the shared neurobiological substrates and therapeutic targets remain unclear. Here we report an amelioration of both anxiety and OCD via the histamine presynaptic H3 heteroreceptor on glutamatergic afferent terminals from the prelimbic prefrontal cortex (PrL) to the nucleus accumbens (NAc) core, a vital node in the limbic loop. The NAc core receives direct hypothalamic histaminergic projections, and optogenetic activation of hypothalamic NAc core histaminergic afferents selectively suppresses glutamatergic rather than GABAergic synaptic transmission in the NAc core via the H3 receptor and thus produces an anxiolytic effect and improves anxiety- and obsessive-compulsive-like behaviors induced by restraint stress. Although the H3 receptor is expressed in glutamatergic afferent terminals from the PrL, basolateral amygdala (BLA), and ventral hippocampus (vHipp), rather than the thalamus, only the PrL- and not BLA- and vHipp-NAc core glutamatergic pathways among the glutamatergic afferent inputs to the NAc core is responsible for co-occurrence of anxiety- and obsessive-compulsive-like behaviors. Furthermore, activation of the H3 receptor ameliorates anxiety and obsessive-compulsive-like behaviors induced by optogenetic excitation of the PrL-NAc glutamatergic afferents. These results demonstrate a common mechanism regulating anxiety- and obsessive-compulsive-like behaviors and provide insight into the clinical treatment strategy for OCD with comorbid anxiety by targeting the histamine H3 receptor in the NAc core.

Disrupted pathways from the frontal-parietal cortices to basal nuclei and the cerebellum are a feature of the obsessive-compulsive disorder spectrum and can be used to aid in early differential diagnosis

A marker for distinguishing patients with obsessive-compulsive disorder (OCD) spectrum has not yet been identified. Whole-brain resting-state effective and functional connectivity (rsEC and rsFC, respectively) networks were constructed for 50 unmedicated OCD (U-OCD) patients, 45 OCD patients in clinical remission (COCD), 47 treatment-resistant OCD (T-OCD) patients, 42 chronic schizophrenia patients who exhibit OCD symptoms (SCHOCD), and 50 healthy controls (HCs). Multivariate pattern analysis (MVPA) was performed to investigate the accuracy of using connectivity alterations to distinguished among the aforementioned groups. Compared to HCs, rsEC connections were significantly disrupted in the U-OCD (n = 15), COCD (n = 8), and T-OCD (n = 19) groups. Additionally, 21 rsEC connections were significantly disrupted in the T-OCD group compared to the SCHOCD group. The disrupted rsEC networks were associated mainly with the frontal-parietal cortex, basal ganglia, limbic regions, and the cerebellum. Classification accuracies for distinguishing OCD patients from HCs and SCHOCD patients ranged from 66.6% to 98.0%. In conclusion, disrupted communication from the frontal-parietal cortices to subcortical basal nuclei and the cerebellum may represent a functional pathological feature of the OCD spectrum. MVPA based on both abnormal rsEC and rsFC patterns may aid in early differential diagnosis of OCD.

Mapping Cortical and Subcortical Asymmetry in Obsessive-Compulsive Disorder: Findings From the ENIGMA Consortium

BACKGROUND

Lateralized dysfunction has been suggested in obsessive-compulsive disorder (OCD). However, it is currently unclear whether OCD is characterized by abnormal patterns of brain structural asymmetry. Here we carried out what is by far the largest study of brain structural asymmetry in OCD.

METHODS

We studied a collection of 16 pediatric datasets (501 patients with OCD and 439 healthy control subjects), as well as 30 adult datasets (1777 patients and 1654 control subjects) from the OCD Working Group within the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium. Asymmetries of the volumes of subcortical structures, and of measures of regional cortical thickness and surface areas, were assessed based on T1-weighted magnetic resonance imaging scans, using harmonized image analysis and quality control protocols. We investigated possible alterations of brain asymmetry in patients with OCD. We also explored potential associations of asymmetry with specific aspects of the disorder and medication status.

RESULTS

In the pediatric datasets, the largest case-control differences were observed for volume asymmetry of the thalamus (more leftward; Cohen's d = 0.19) and the pallidum (less leftward; d = -0.21). Additional analyses suggested putative links between these asymmetry patterns and medication status, OCD severity, or anxiety and depression comorbidities. No significant case-control differences were found in the adult datasets.

CONCLUSIONS

The results suggest subtle changes of the average asymmetry of subcortical structures in pediatric OCD, which are not detectable in adults with the disorder. These findings may reflect altered neurodevelopmental processes in OCD.

Neuroimaging studies within Cognitive Genetics Collaborative Research Organization aiming to replicate and extend works of ENIGMA

Reproducibility is one of the most important issues for generalizing the results of clinical research; however, low reproducibility in neuroimaging studies is well known. To overcome this problem, the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) consortium, an international neuroimaging consortium, established standard protocols for imaging analysis and employs either meta‐ and mega‐analyses of psychiatric disorders with large sample sizes. The Cognitive Genetics Collaborative Research Organization (COCORO) in Japan promotes neurobiological studies in psychiatry and has successfully replicated and extended works of ENIGMA especially for neuroimaging studies. For example, (a) the ENIGMA consortium showed subcortical regional volume alterations in patients with schizophrenia (n = 2,028) compared to controls (n = 2,540) across 15 cohorts using meta‐analysis. COCORO replicated the volumetric changes in patients with schizophrenia (n = 884) compared to controls (n = 1,680) using the ENIGMA imaging analysis protocol and mega‐analysis. Furthermore, a schizophrenia‐specific leftward asymmetry for the pallidum volume was demonstrated; and (b) the ENIGMA consortium identified white matter microstructural alterations in patients with schizophrenia (n = 1,963) compared to controls (n = 2,359) across 29 cohorts. Using the ENIGMA protocol, a study from COCORO showed similar results in patients with schizophrenia (n = 696) compared to controls (n = 1,506) from 12 sites using mega‐analysis. Moreover, the COCORO study found that schizophrenia, bipolar disorder (n = 211) and autism spectrum disorder (n = 126), but not major depressive disorder (n = 398), share similar white matter microstructural alterations, compared to controls. Further replication and harmonization of the ENIGMA consortium and COCORO will contribute to the generalization of their research findings.

Genetic meta-analysis of obsessive-compulsive disorder and self-report compulsive symptoms

We investigated whether obsessive-compulsive (OC) symptoms from a population-based sample could be analyzed to detect genetic variants influencing obsessive-compulsive disorder (OCD). We performed a genome-wide association studies (GWAS) on the obsession (rumination and impulsions) and compulsion (checking, washing, and ordering/precision) subscales of an abbreviated version of the Padua Inventory (N = 8,267 with genome-wide genotyping and phenotyping). The compulsion subscale showed a substantial and significant positive genetic correlation with an OCD case-control GWAS (r _G = 0.61, p = .017) previously published by the Psychiatric Genomics Consortium (PGC-OCD). The obsession subscale and the total Padua score showed no significant genetic correlations (r _G = -0.02 and r _G = 0.42, respectively). A meta-analysis of the compulsive symptoms GWAS with the PGC-OCD revealed no genome-wide significant Single-Nucleotide Polymorphisms (SNPs combined N = 17,992, indicating that the power is still low for individual SNP effects). A gene-based association analysis, however, yielded two novel genes (WDR7 and ADCK1). The top 250 genes in the gene-based test also showed a significant increase in enrichment for psychiatric and brain-expressed genes. S-Predixcan testing showed that for genes expressed in hippocampus, amygdala, and caudate nucleus significance increased in the meta-analysis with compulsive symptoms compared to the original PGC-OCD GWAS. Thus, the inclusion of dimensional symptom data in genome-wide association on clinical case-control GWAS of OCD may be useful to find genes for OCD if the data are based on quantitative indices of compulsive behavior. SNP-level power increases were limited, but aggregate, gene-level analyses showed increased enrichment for brain-expressed genes related to psychiatric disorders, and increased association with gene expression in brain tissues with known emotional, reward processing, memory, and fear-formation functions.

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

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.

Brain Imaging Genomics: Integrated Analysis and Machine Learning

Brain imaging genomics is an emerging data science field, where integrated analysis of brain imaging and genomics data, often combined with other biomarker, clinical and environmental data, is performed to gain new insights into the phenotypic, genetic and molecular characteristics of the brain as well as their impact on normal and disordered brain function and behavior. It has enormous potential to contribute significantly to biomedical discoveries in brain science. Given the increasingly important role of statistical and machine learning in biomedicine and rapidly growing literature in brain imaging genomics, we provide an up-to-date and comprehensive review of statistical and machine learning methods for brain imaging genomics, as well as a practical discussion on method selection for various biomedical applications.

Putamen gray matter volumes in neuropsychiatric and neurodegenerative disorders

Putamen is enriched with dopamine and associated with dopamine-related phenotypes including many neuropsychiatric and neurodegenerative disorders that manifest with motor impairment, impulsive behavior, and cognitive deficits. The gray matter volume of the putamen is age-dependent and genetically controlled. In most neuropsychiatric and neurodegenerative disorders, including Parkinson's spectrum disorders, Huntington's disease, dementia with Lewy bodies, Alzheimer's disease, multiple sclerosis, attention deficit hyperactivity disorder, developmental dyslexia, and major depression, the putamen volume is significantly reduced. On the other hand, in individuals with bipolar disorder, schizophrenia spectrum disorders, especially neuroleptics-medicated patients with schizophrenia, autism spectrum disorders, obsessive-compulsive spectrum disorders, and cocaine/amphetamine dependence, the putamen volume is significantly enlarged. Therefore, the putamen volume may serve as a structural neural marker for many neuropsychiatric and neurodegenerative disorders and a predictor of treatment outcomes in individuals afflicted with these conditions. We provided an overview of the genetic bases of putamen volume and explored potential mechanisms whereby altered putamen volume manifests in these neuropsychiatric and neurodegenerative conditions, with a specific focus on dopaminergic processes.

Concordance of genetic variation that increases risk for tourette syndrome and that influences its underlying neurocircuitry

There have been considerable recent advances in understanding the genetic architecture of Tourette syndrome (TS) as well as its underlying neurocircuitry. However, the mechanisms by which genetic variation that increases risk for TS-and its main symptom dimensions-influence relevant brain regions are poorly understood. Here we undertook a genome-wide investigation of the overlap between TS genetic risk and genetic influences on the volume of specific subcortical brain structures that have been implicated in TS. We obtained summary statistics for the most recent TS genome-wide association study (GWAS) from the TS Psychiatric Genomics Consortium Working Group (4644 cases and 8695 controls) and GWAS of subcortical volumes from the ENIGMA consortium (30,717 individuals). We also undertook analyses using GWAS summary statistics of key symptom factors in TS, namely social disinhibition and symmetry behaviour. SNP effect concordance analysis (SECA) was used to examine genetic pleiotropy-the same SNP affecting two traits-and concordance-the agreement in single nucelotide polymorphism (SNP) effect directions across these two traits. In addition, a conditional false discovery rate (FDR) analysis was performed, conditioning the TS risk variants on each of the seven subcortical and the intracranial brain volume GWAS. Linkage disequilibrium score regression (LDSR) was used as validation of the SECA method. SECA revealed significant pleiotropy between TS and putamen (p = 2 × 10^-4) and caudate (p = 4 × 10^-4) volumes, independent of direction of effect, and significant concordance between TS and lower thalamic volume (p = 1 × 10^-3). LDSR lent additional support for the association between TS and thalamus volume (p = 5.85 × 10^-2). Furthermore, SECA revealed significant evidence of concordance between the social disinhibition symptom dimension and lower thalamus volume (p = 1 × 10^-3), as well as concordance between symmetry behaviour and greater putamen volume (p = 7 × 10^-4). Conditional FDR analysis further revealed novel variants significantly associated with TS (p < 8 × 10^-7) when conditioning on intracranial (rs2708146, q = 0.046; and rs72853320, q = 0.035) and hippocampal (rs1922786, q = 0.001) volumes, respectively. These data indicate concordance for genetic variation involved in disorder risk and subcortical brain volumes in TS. Further work with larger samples is needed to fully delineate the genetic architecture of these disorders and their underlying neurocircuitry.

Concordance of genetic variation that increases risk for anxiety disorders and posttraumatic stress disorders and that influences their underlying neurocircuitry

BACKGROUND

There have been considerable recent advances in understanding the genetic architecture of anxiety disorders and posttraumatic stress disorder (PTSD), as well as the underlying neurocircuitry of these disorders. However, there is little work on the concordance of genetic variations that increase risk for these conditions, and that influence subcortical brain structures. We undertook a genome-wide investigation of the overlap between the genetic influences from single nucleotide polymorphisms (SNPs) on volumes of subcortical brain structures and genetic risk for anxiety disorders and PTSD.

METHOD

We obtained summary statistics of genome-wide association studies (GWAS) of anxiety disorders (N_cases= 7016, N_controls= 14,745), PTSD (European sample; N_cases= 2424, N_controls= 7113) and of subcortical brain structures (N = 13,171). SNP Effect Concordance Analysis (SECA) and Linkage Disequilibrium (LD) Score Regression were used to examine genetic pleiotropy, concordance, and genome-wide correlations respectively. SECAs conditional false discovery was used to identify specific risk variants associated with anxiety disorders or PTSD when conditioning on brain related traits.

RESULTS

For anxiety disorders, we found evidence of significant concordance between increased anxiety risk variants and variants associated with smaller amygdala volume. Further, by conditioning on brain volume GWAS, we identified novel variants that associate with smaller brain volumes and increase risk for disorders: rs56242606 was found to increase risk for anxiety disorders, while two variants (rs6470292 and rs683250) increase risk for PTSD, when conditioning on the GWAS of putamen volume.

LIMITATIONS

Despite using the largest available GWAS summary statistics, the analyses were limited by sample size.

CONCLUSIONS

These preliminary data indicate that there is genome wide concordance between genetic risk factors for anxiety disorders and those for smaller amygdala volume, which is consistent with research that supports the involvement of the amygdala in anxiety disorders. It is notable that a genetic variant that contributes to both reduced putamen volume and PTSD plays a key role in the glutamatergic system. Further work with GWAS summary statistics from larger samples, and a more extensive look at the genetics underlying brain circuits, is needed to fully delineate the genetic architecture of these disorders and their underlying neurocircuitry.

Imaging genetics in neurodevelopmental psychopathology

Neurodevelopmental disorders are defined by highly heritable problems during development and brain growth. Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASDs), and intellectual disability (ID) are frequent neurodevelopmental disorders, with common comorbidity among them. Imaging genetics studies on the role of disease-linked genetic variants on brain structure and function have been performed to unravel the etiology of these disorders. Here, we reviewed imaging genetics literature on these disorders attempting to understand the mechanisms of individual disorders and their clinical overlap. For ADHD and ASD, we selected replicated candidate genes implicated through common genetic variants. For ID, which is mainly caused by rare variants, we included genes for relatively frequent forms of ID occurring comorbid with ADHD or ASD. We reviewed case-control studies and studies of risk variants in healthy individuals. Imaging genetics studies for ADHD were retrieved for SLC6A3/DAT1, DRD2, DRD4, NOS1, and SLC6A4/5HTT. For ASD, studies on CNTNAP2, MET, OXTR, and SLC6A4/5HTT were found. For ID, we reviewed the genes FMR1, TSC1 and TSC2, NF1, and MECP2. Alterations in brain volume, activity, and connectivity were observed. Several findings were consistent across studies, implicating, for example, SLC6A4/5HTT in brain activation and functional connectivity related to emotion regulation. However, many studies had small sample sizes, and hypothesis-based, brain region-specific studies were common. Results from available studies confirm that imaging genetics can provide insight into the link between genes, disease-related behavior, and the brain. However, the field is still in its early stages, and conclusions about shared mechanisms cannot yet be drawn.

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.