Integrative functional genomic analysis of human brain development and neuropsychiatric risks

To broaden our understanding of human neurodevelopment, we profiled transcriptomic and epigenomic landscapes across brain regions and/or cell types for the entire span of prenatal and postnatal development. Integrative analysis revealed temporal, regional, sex, and cell type-specific dynamics.We observed a global transcriptomic cup-shaped pattern, characterized by a late fetal transition associated with sharply decreased regional differences and changes in cellular composition and maturation, followed by a reversal in childhood-adolescence, and accompanied by epigenomic reorganizations. Analysis of gene coexpression modules revealed relationships with epigenomic regulation and neurodevelopmental processes. Genes with genetic associations to brain-based traits and neuropsychiatric disorders (including MEF2C, SATB2, SOX5, TCF4, and TSHZ3) converged in a small number of modules and distinct cell types, revealing insights into neurodevelopment and the genomic basis of neuropsychiatric risks

Integrative functional genomic analysis of human brain development and neuropsychiatric risks

To broaden our understanding of human neurodevelopment, we profiled transcriptomic and epigenomic landscapes across brain regions and/or cell types for the entire span of prenatal and postnatal development. Integrative analysis revealed temporal, regional, sex, and cell type-specific dynamics.We observed a global transcriptomic cup-shaped pattern, characterized by a late fetal transition associated with sharply decreased regional differences and changes in cellular composition and maturation, followed by a reversal in childhood-adolescence, and accompanied by epigenomic reorganizations. Analysis of gene coexpression modules revealed relationships with epigenomic regulation and neurodevelopmental processes. Genes with genetic associations to brain-based traits and neuropsychiatric disorders (including MEF2C, SATB2, SOX5, TCF4, and TSHZ3) converged in a small number of modules and distinct cell types, revealing insights into neurodevelopment and the genomic basis of neuropsychiatric risks

Integrative functional genomic analysis of human brain development and neuropsychiatric risks

To broaden our understanding of human neurodevelopment, we profiled transcriptomic and epigenomic landscapes across brain regions and/or cell types for the entire span of prenatal and postnatal development. Integrative analysis revealed temporal, regional, sex, and cell type-specific dynamics.We observed a global transcriptomic cup-shaped pattern, characterized by a late fetal transition associated with sharply decreased regional differences and changes in cellular composition and maturation, followed by a reversal in childhood-adolescence, and accompanied by epigenomic reorganizations. Analysis of gene coexpression modules revealed relationships with epigenomic regulation and neurodevelopmental processes. Genes with genetic associations to brain-based traits and neuropsychiatric disorders (including MEF2C, SATB2, SOX5, TCF4, and TSHZ3) converged in a small number of modules and distinct cell types, revealing insights into neurodevelopment and the genomic basis of neuropsychiatric risks

Integrative functional genomic analysis of human brain development and neuropsychiatric risks

INTRODUCTION The brain is responsible for cognition, behavior, and much of what makes us uniquely human. The development of the brain is a highly complex process, and this process is reliant on precise regulation of molecular and cellular events grounded in the spatiotemporal regulation of the transcriptome. Disruption of this regulation can lead to neuropsychiatric disorders. RATIONALE The regulatory, epigenomic, and transcriptomic features of the human brain have not been comprehensively compiled across time, regions, or cell types. Understanding the etiology of neuropsychiatric disorders requires knowledge not just of endpoint differences between healthy and diseased brains but also of the developmental and cellular contexts in which these differences arise. Moreover, an emerging body of research indicates that many aspects of the development and physiology of the human brain are not well recapitulated in model organisms, and therefore it is necessary that neuropsychiatric disorders be understood in the broader context of the developing and adult human brain. RESULTS Here we describe the generation and analysis of a variety of genomic data modalities at the tissue and single-cell levels, including transcriptome, DNA methylation, and histone modifications across multiple brain regions ranging in age from embryonic development through adulthood. We observed a widespread transcriptomic transition beginning during late fetal development and consisting of sharply decreased regional differences. This reduction coincided with increases in the transcriptional signatures of mature neurons and the expression of genes associated with dendrite development, synapse development, and neuronal activity, all of which were temporally synchronous across neocortical areas, as well as myelination and oligodendrocytes, which were asynchronous. Moreover, genes including MEF2C, SATB2, and TCF4, with genetic associations to multiple brain-related traits and disorders, converged in a small number of modules exhibiting spatial or spatiotemporal specificity. CONCLUSION We generated and applied our dataset to document transcriptomic and epigenetic changes across human development and then related those changes to major neuropsychiatric disorders. These data allowed us to identify genes, cell types, gene coexpression modules, and spatiotemporal loci where disease risk might converge, demonstrating the utility of the dataset and providing new insights into human development and disease

Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

The PsychENCODE project

Recent research on disparate psychiatric disorders has implicated rare variants in genes involved in global gene regulation and chromatin modification, as well as many common variants located primarily in regulatory regions of the genome. Understanding precisely how these variants contribute to disease will require a deeper appreciation for the mechanisms of gene regulation in the developing and adult human brain. The PsychENCODE project aims to produce a public resource of multidimensional genomic data using tissue- and cell type–specific samples from approximately 1,000 phenotypically well-characterized, high-quality healthy and disease-affected human post-mortem brains, as well as functionally characterize disease-associated regulatory elements and variants in model systems. We are beginning with a focus on autism spectrum disorder, bipolar disorder and schizophrenia, and expect that this knowledge will apply to a wide variety of psychiatric disorders. This paper outlines the motivation and design of PsychENCODE

Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders.

Cellular heterogeneity in the human brain obscures the identification of robust cellular regulatory networks, which is necessary to understand the function of non-coding elements and the impact of non-coding genetic variation. Here we integrate genome-wide chromosome conformation data from purified neurons and glia with transcriptomic and enhancer profiles, to characterize the gene regulatory landscape of two major cell classes in the human brain. We then leverage cell-type-specific regulatory landscapes to gain insight into the cellular etiology of several brain disorders. We find that Alzheimer's disease (AD)-associated epigenetic dysregulation is linked to neurons and oligodendrocytes, whereas genetic risk factors for AD highlighted microglia, suggesting that different cell types may contribute to disease risk, via different mechanisms. Moreover, integration of glutamatergic and GABAergic regulatory maps with genetic risk factors for schizophrenia (SCZ) and bipolar disorder (BD) identifies shared (parvalbumin-expressing interneurons) and distinct cellular etiologies (upper layer neurons for BD, and deeper layer projection neurons for SCZ). Collectively, these findings shed new light on cell-type-specific gene regulatory networks in brain disorders

Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap.

The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders-autism, schizophrenia, bipolar disorder, depression, and alcoholism-compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism-based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity