Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17–29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn’s disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

Highlights d Three groups of highly genetically-related disorders among 8 psychiatric disorders d Identified 109 pleiotropic loci affecting more than one disorder d Pleiotropic genes show heightened expression beginning in 2 nd prenatal trimester d Pleiotropic genes play prominent roles in neurodevelopmental processes Authors Cross-Disorder Group of the Psychiatric Genomics Consortium

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

This large cross-sectional study examined the impact of COVID-19 emergency measures on child/adolescent mental health for children/adolescents with and without pre-existing psychiatric diagnoses. Using adapted measures from the CRISIS questionnaire, parents of children aged 6–18 ( N = 1013; 56% male; 62% pre-existing psychiatric diagnosis) and self-reporting children/adolescents aged 10–18 ( N = 385) indicated changes in mental health across six domains: depression, anxiety, irritability, attention, hyperactivity, and obsessions/compulsions. Changes in anxiety, irritability, and hyperactivity were calculated for children aged 2–5 years using the Strengths and Difficulties Questionnaire. COVID-19 exposure, compliance with emergency measures, COVID-19 economic concerns, and stress from social isolation were measured with the CRISIS questionnaire. Prevalence of change in mental health status was estimated for each domain; multinomial logistic regression was used to determine variables associated with mental health status change in each domain. Depending on the age group, 67–70% of children/adolescents experienced deterioration in at least one mental health domain; however, 19–31% of children/adolescents experienced improvement in at least one domain. Children/adolescents without and with psychiatric diagnoses tended to experience deterioration during the first wave of COVID-19. Rates of deterioration were higher in those with a pre-exiting diagnosis. The rate of deterioration was variable across different age groups and pre-existing psychiatric diagnostic groups: depression 37–56%, anxiety 31–50%, irritability 40–66%, attention 40–56%, hyperactivity 23–56%, obsessions/compulsions 13–30%. Greater stress from social isolation was associated with deterioration in all mental health domains (all ORs 11.12–55.24). The impact of pre-existing psychiatric diagnosis was heterogenous, associated with deterioration in depression, irritability, hyperactivity, obsession/compulsions for some children (ORs 1.96–2.23) but also with improvement in depression, anxiety, and irritability for other children (ORs 2.13–3.12). Economic concerns were associated with improvement in anxiety, attention, and obsessions/compulsions (ORs 3.97–5.57). Children/adolescents with and without pre-existing psychiatric diagnoses reported deterioration. Deterioration was associated with increased stress from social isolation. Enhancing social interactions for children/adolescents will be an important mitigation strategy for current and future COVID-19 waves. Supplementary Information The online version contains supplementary material available at 10.1007/s00787-021-01744-3.

Attention deficit hyperactivity disorder (ADHD) is a common and persistent condition characterized by developmentally atypical and impairing inattention, hyperactivity, and impulsiveness. We identified de novo and rare copy number variations (CNVs) in 248 unrelated ADHD patients using million-feature genotyping arrays. We found de novo CNVs in 3 of 173 (1.7%) ADHD patients for whom we had DNA from both parents. These CNVs affected brain-expressed genes: DCLK2, SORCS1, SORCS3, and MACROD2. We also detected rare inherited CNVs in 19 of 248 (7.7%) ADHD probands, which were absent in 2357 controls and which either overlapped previously implicated ADHD loci (for example, DRD5 and 15q13 microduplication) or identified new candidate susceptibility genes (ASTN2, CPLX2, ZBBX, and PTPRN2). Among these de novo and rare inherited CNVs, there were also examples of genes (ASTN2, GABRG1, and CNTN5) previously implicated by rare CNVs in other neurodevelopmental conditions including autism spectrum disorder (ASD). To further explore the overlap of risks in ADHD and ASD, we used the same microarrays to test for rare CNVs in an independent, newly collected cohort of 349 unrelated individuals with a primary diagnosis of ASD. Deletions of the neuronal ASTN2 and the ASTN2-intronic TRIM32 genes yielded the strongest association with ADHD and ASD, but numerous other shared candidate genes (such as CHCHD3, MACROD2, and the 16p11.2 region) were also revealed. Our results provide support for a role for rare CNVs in ADHD risk and reinforce evidence for the existence of common underlying susceptibility genes for ADHD, ASD, and other neuropsychiatric disorders.

The Behavior Rating Inventory of Executive Function (BRIEF) is commonly used in the assessment of children and adolescents presenting with a wide range of concerns. It is unclear, however, whether the questionnaire is more closely related to general measures of behavioral disruption and impairment or to specific measures of executive function. In the present study, associations between the Behavioral Regulation Index and Metacognition Index of the BRIEF and cognitive, behavioral, and academic measures were examined in a sample of clinic-referred youth (n = 60) and healthy youth (n = 37) 6-15 years of age. Measures included ratings of inattentive and hyperactive-impulsive symptoms in youth, ratings of how well youth functioned in their everyday environments, youth's scores on measures of reading and math, and youth's scores on measures of inhibition, performance monitoring, and working memory. Although both BRIEF indices were strongly related to parent and teacher ratings of behavioral disruption and impairment, neither was associated with youth's scores on the performance-based tasks of executive function. These findings support the use of the BRIEF as a clinical tool for assessing a broad range of concerns, but raise questions about the relation of the BRIEF to performance-based tasks that are commonly used to assess executive function.