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IMPORTANCE Adult mood disorders are often preceded by behavioral and emotional problems in childhood. It is yet unclear what explains the associations between childhood psychopathology and adult traits. OBJECTIVE To investigate whether genetic risk for adult mood disorders and associated traits is associated with childhood disorders.

We systematically interrogate the joint genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic, and molecular genetic levels of analysis. We identify four broad factors (Neurodevelopmental, Compulsive, Psychotic, and Internalizing) that underlie genetic correlations among the disorders, and test whether these factors adequately explain their genetic correlations with biobehavioral traits. We introduce Stratified Genomic Structural Equation Modelling, which we use to identify gene sets and genomic regions that disproportionately contribute to pleiotropy, including protein-truncating variant intolerant genes expressed in excitatory and GABAergic brain cells that are enriched for pleiotropy between disorders with psychotic features. Multivariate association analyses detect a total of 152 (20 novel) independent loci which act on the four factors, and identify nine loci that act heterogeneously across disorders within a factor. Despite moderate to high genetic correlations across all 11 disorders, we find very little utility of, or evidence for, a single dimension of genetic risk across psychiatric disorders.

Objective: A systematic review of studies using molecular genetics and statistical approaches to investigate the role of common genetic variation in the development, persistence, and comorbidity of childhood psychiatric traits was conducted. Method: A literature review was performed using the PubMed database, following the Preferred Reporting Items for Meta-Analyses guidelines. There were 131 studies meeting inclusion criteria, having investigated at least one type of childhood-onset or childhood-measured psychiatric disorder or trait with the aim of identifying trait-associated common genetic variants, estimating the contribution of single nucleotide polymorphisms to the amount of variance explained (single nucleotide polymorphism heritability), investigating genetic overlap between psychiatric traits, or investigating whether the stability in traits or the association with adult traits is explained by genetic factors. Results: The first robustly associated genetic variants have started to be identified for childhood psychiatric traits. There were substantial contributions of common genetic variants to many traits, with variation in single nucleotide polymorphism heritability estimates depending on age and raters. Moreover, genetic variants also appeared to explain comorbidity as well as stability across a range of psychiatric traits in childhood and across the life span. Conclusion: Common genetic variation plays a substantial role in childhood psychiatric traits. Increased sample sizes will lead to increased power to identify genetic variants and to understand genetic architecture, which will ultimately be beneficial to targeted and prevention strategies. This can be achieved by harmonizing phenotype measurements, as is already proposed by large international consortia and by including the collection of genetic material in every study.

Both common and rare genetic variants (minor allele frequency >1% and <0.1% respectively) have been implicated in the aetiology of schizophrenia. In this study, we integrate single-cell gene expression data with publicly available Genome-Wide Association Study (GWAS) and exome sequenced data in order to investigate in parallel, the enrichment of common and (ultra-)rare variants related to schizophrenia in several functionally relevant gene-sets. Four types of gene-sets were constructed 1) protein-truncating variant (PTV)-intolerant (PI) genes 2) genes expressed in brain cell types and neurons ascertained from mouse and human brain tissue 3) genes defined by synaptic function and location and 4) intersection genes, i.e., PI genes that are expressed in the human and mouse brain cell gene-sets. We show that common as well as ultra-rare schizophrenia-associated variants are overrepresented in PI genes, in excitatory neurons from the prefrontal cortex and hippocampus, medium spiny neurons, and genes enriched for synaptic processes. We also observed stronger enrichment in the intersection genes. Our findings suggest that across the allele frequency spectrum, genes and genetic variants likely to be under stringent selection, and those expressed in particular brain cell types, are involved in the same biological pathways influencing the risk for schizophrenia.

Both common and rare genetic variants (minor allele frequency > 1% and < 0.1% respectively) have been implicated in the aetiology of schizophrenia. In this study, we integrate single-cell gene expression data with publicly available Genome-Wide Association Study (GWAS) and exome sequenced data in order to investigate in parallel, the enrichment of common and (ultra-)rare variants related to schizophrenia in several functionally relevant gene sets. Four types of gene sets were constructed 1) protein-truncating variant (PTV)-intolerant (PI) genes 2) genes expressed in brain cell types and neurons ascertained from mouse and human brain tissue 3) genes defined by synaptic function and location and 4) intersection genes, i.e., PI genes that are expressed in the human and mouse brain cell gene sets. We show that common as well as (ultra-)rare schizophrenia-associated variants are overrepresented in PI genes, in excitatory neurons from the prefrontal cortex and hippocampus, medium spiny neurons, and genes enriched for synaptic processes. We also observed stronger enrichment in the intersection genes. Our findings suggest that across the allele frequency spectrum, genes and genetic variants likely to be under stringent selection, and those expressed in particular brain cell types, are involved in the same biological pathways influencing the risk for schizophrenia.

The Roadmap for Mental Health and Wellbeing Research in Europe (ROAMER) identified child and adolescent mental illness as a priority area for research. CAPICE (Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe) is a European Union (EU) funded training network aimed at investigating the causes of individual differences in common childhood and adolescent psychopathology, especially depression, anxiety, and attention deficit hyperactivity disorder. CAPICE brings together eight birth and childhood cohorts as well as other cohorts from the EArly Genetics and Life course Epidemiology (EAGLE) consortium, including twin cohorts, with unique longitudinal data on environmental exposures and mental health problems, and genetic data on participants. Here we describe the objectives, summarize the methodological approaches and initial results, and present the dissemination strategy of the CAPICE network. Besides identifying genetic and epigenetic variants associated with these phenotypes, analyses have been performed to shed light on the role of genetic factors and the interplay with the environment in influencing the persistence of symptoms across the lifespan. Data harmonization and building an advanced data catalogue are also part of the work plan. Findings will be disseminated to non-academic parties, in close collaboration with the Global Alliance of Mental Illness Advocacy Networks-Europe (GAMIAN-Europe).

Ubiquitous associations have been detected between different types of childhood psychopathology and polygenic risk scores based on adult psychiatric disorders and related adult outcomes, indicating that genetic factors partly explain the association between childhood psychopathology and adult outcomes. However, these analyses in general do not take into account the correlations between the adult trait and disorder polygenic risk scores. This study aimed to further clarify the influence of genetic factors on associations between childhood psychopathology and adult outcomes by accounting for these correlations. Using a multivariate multivariable regression, we analyzed associations of childhood attention-deficit/hyperactivity disorder (ADHD), internalizing, and social problems, with polygenic scores (PGS) of adult disorders and traits including major depression, bipolar disorder, subjective well-being, neuroticism, insomnia, educational attainment, and body mass index (BMI), derived for 20,539 children aged 8.5-10.5 years. After correcting for correlations between the adult phenotypes, major depression PGS were associated with all three childhood traits,