Genome-wide association studies have identified hundreds of genetic associations for complex psychiatric disorders and cognitive traits. However, interpretation of most of these findings is complicated by the presence of many significant and highly correlated genetic variants located in noncoding regions. Here, we address this issue by creating a high-resolution map of the three-dimensional (3D) genome organization by applying Hi-C to adult and fetal brain cortex with concomitant RNA-seq, open chromatin (ATAC-seq), and ChIP-seq data (H3K27ac, H3K4me3, and CTCF). Extensive analyses established the quality, information content, and salience of these new Hi-C data. We used these data to connect 938 significant genetic loci for schizophrenia, intelligence, ADHD, alcohol dependence, Page 2 Alzheimer's disease, anorexia nervosa, autism spectrum disorder, bipolar disorder, major depression, and educational attainment to 8,595 genes (with 42.1% of these genes implicated more than once). We show that assigning genes to traits based on proximity provides a limited view of the complexity of GWAS findings and that gene set analyses based on functional genomic data provide an expanded view of the biological processes involved in the etiology of schizophrenia and other complex brain traits.URLs 1000 Genomes Selection Browser,

Despite considerable progress in schizophrenia genetics, most findings have been for large rare structural variants and common variants in well-imputed regions with few genes implicated from exome sequencing. Whole genome sequencing (WGS) can potentially provide a more complete enumeration of etiological genetic variation apart from the exome and regions of high linkage disequilibrium. We analyze high-coverage WGS data from 1162 Swedish schizophrenia cases and 936 ancestry-matched population controls. Our main objective is to evaluate the contribution to schizophrenia etiology from a variety of genetic variants accessible to WGS but not by previous technologies. Our results suggest that ultrarare structural variants that affect the boundaries of topologically associated domains (TADs) increase risk for schizophrenia. Alterations in TAD boundaries may lead to dysregulation of gene expression. Future mechanistic studies will be needed to determine the precise functional effects of these variants on biology.

Anorexia nervosa (AN) is a serious and heritable psychiatric disorder. To date, studies of copy number variants (CNVs) have been limited and inconclusive because of small sample size. We conducted a case-only genome-wide CNV survey in 1,983 female AN cases included in the Genetic Consortium for Anorexia Nervosa (GCAN). Following stringent quality control procedures, we investigated whether pathogenic CNVs in regions previously implicated in psychiatric and neurodevelopmental disorders were present in AN cases. We observed two instances of the well-established pathogenic CNVs in AN cases. Additionally, one case had a deletion in the 13q12 region, overlapping with a deletion previously reported in two AN cases. As a secondary aim, we also examined our sample for CNVs over 1 Mb in size. Out of the 40 instances of such large CNVs which were not previously implicated for AN or neuropsychiatric phenotypes, two of them contained genes with previous neuropsychiatric associations, and only five of them had no associated reports associated in public CNV databases. Although ours is the largest study of its kind in AN, larger datasets are needed to comprehensively assess the role of CNVs in the etiology of AN.

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Background: Genetic studies of schizophrenia have implicated numerous risk loci including several copy number variants (CNVs) of large effect and hundreds of loci of small effect. In only a few cases has a specific gene been clearly identified. Rare CNVs affecting a single gene offer a potential avenue to discovering schizophrenia risk genes. Methods: CNVs were generated from exome-sequencing of 4,913 schizophrenia cases and 6,188 controls from Sweden. We integrated multiple CNV calling methods (XHMM and ExomeDepth) to expand our set of single-gene CNVs and leveraged two different approaches for validating these variants (qPCR and Nanostring). Results: We found a significant excess of all rare CNVs (deletions p=0.0004, duplications p=0.0006) and single-gene CNVs (deletions p=0.04, duplications p=0.03) in schizophrenia cases compared to controls. An expanded set of CNVs generated from integrating multiple approaches showed a significant burden of deletions in 11/21 gene-sets previously implicated in schizophrenia and across all genes in those sets (p=0.008), although no tests survived correction. We performed an extensive validation of all deletions in the significant set of voltage-gated calcium channels among CNVs called from both exome-sequencing and genotyping arrays. In total, 4 exonic, singlegene deletions validated in cases and none in controls (p=0.039), of which all were identified by exome-sequencing. Conclusions: These results point to the potential contribution of single-gene CNVs to schizophrenia, that the utility of exome-sequencing for CNV calling has yet to be maximized and single-gene CNVs should be included in gene focused studies using other classes of variation.