The PsychENCODE project

Genetic identification of brain cell types underlying schizophrenia

With few exceptions, the marked advances in knowledge about the genetic basis of schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. By applying knowledge of the cellular taxonomy of the brain from single-cell RNA sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. We found that the common-variant genomic results consistently mapped to pyramidal cells, medium spiny neurons (MSNs) and certain interneurons, but far less consistently to embryonic, progenitor or glial cells. These enrichments were due to sets of genes that were specifically expressed in each of these cell types. We also found that many of the diverse gene sets previously associated with schizophrenia (genes involved in synaptic function, those encoding mRNAs that interact with FMRP, antipsychotic targets, etc.) generally implicated the same brain cell types. Our results suggest a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. The genetic risk associated with MSNs did not overlap with that of glutamatergic pyramidal cells and interneurons, suggesting that different cell types have biologically distinct roles in schizophrenia.

Distinct epigenomic patterns are associated with haploinsufficiency and predict risk genes of developmental disorders

Haploinsufficiency is a major mechanism of genetic risk in developmental disorders. Accurate prediction of haploinsufficient genes is essential for prioritizing and interpreting deleterious variants in genetic studies. Current methods based on mutation intolerance in population data suffer from inadequate power for genes with short transcripts. Here we show haploinsufficiency is strongly associated with epigenomic patterns, and develop a computational method (Episcore) to predict haploinsufficiency leveraging epigenomic data from a broad range of tissue and cell types by machine learning methods. Based on data from recent exome sequencing studies on developmental disorders, Episcore achieves better performance in prioritizing likely-gene-disrupting (LGD) de novo variants than current methods. We further show that Episcore is less-biased by gene size, and complementary to mutation intolerance metrics for prioritizing LGD variants. Our approach enables new applications of epigenomic data and facilitates discovery and interpretation of novel risk variants implicated in developmental disorders.

Predicting haploinsufficient genes helps to understand the genetic risk underlying developmental disorders. Here, the authors develop a Random Forest-based method that uses epigenomic data to predict haploinsufficiency, Episcore, which is complementary to methods based on mutation intolerance scores.

Translating GWAS Findings to Novel Therapeutic Targets for Coronary Artery Disease

The success of genome-wide association studies (GWAS) has significantly advanced our understanding of the etiology of coronary artery disease (CAD) and opens new opportunities to reinvigorate the stalling CAD drug development. However, there exists remarkable disconnection between the CAD GWAS findings and commercialized drugs. While this could implicate major untapped translational and therapeutic potentials in CAD GWAS, it also brings forward extensive technical challenges. In this review we summarize the motivation to leverage GWAS for drug discovery, outline the critical bottlenecks in the field, and highlight several promising strategies such as functional genomics and network-based approaches to enhance the translational value of CAD GWAS findings in driving novel therapeutics

Genomic Approaches to Posttraumatic Stress Disorder: The Psychiatric Genomic Consortium Initiative

Posttraumatic stress disorder (PTSD) after exposure to a traumatic event is a highly prevalent psychiatric disorder. Heritability estimates from twin studies as well as from recent molecular data (single nucleotide polymorphism-based heritability) indicate moderate to high heritability, yet robust genetic variants for PTSD have not yet been identified and the genetic architecture of this polygenic disorder remains largely unknown. To date, fewer than 10 large-scale genome-wide association studies of PTSD have been published, with findings that highlight the unique challenges for PTSD genomics, including a complex diagnostic entity with contingency of PTSD diagnosis on trauma exposure and the large genetic diversity of the study populations. The Psychiatric Genomics Consortium PTSD group has brought together more than 200 scientists with the goal to increase sample size for genome-wide association studies and other genomic analyses to sufficient numbers where robust discoveries of molecular signatures can be achieved. The sample currently includes more than 32,000 PTSD cases and 100,000 trauma-exposed control subjects, and collection is ongoing. The first results found a significant shared genetic risk of PTSD with other psychiatric disorders and sex-biased heritability estimates with higher heritability in female individuals compared with male individuals. This review describes the scope and current focus of the Psychiatric Genomics Consortium PTSD group and its expansion from the initial genome-wide association study group to nine working groups, including epigenetics, gene expression, imaging, and integrative systems biology. We further briefly outline recent findings and future directions of "omics"-based studies of PTSD, with the ultimate goal of elucidating the molecular architecture of this complex disorder to improve prevention and intervention strategies.

Gene regulatory mechanisms underlying sex differences in brain development and psychiatric disease

The sexual differentiation of the mammalian nervous system requires the precise coordination of the temporal and spatial regulation of gene expression in diverse cell types. Sex hormones act at multiple developmental time points to specify sex-typical differentiation during embryonic and early development and to coordinate subsequent responses to gonadal hormones later in life by establishing sex-typical patterns of epigenetic modifications across the genome. Thus, mutations associated with neuropsychiatric conditions may result in sexually dimorphic symptoms by acting on different neural substrates or chromatin landscapes in males and females. Finally, as stress hormone signaling may directly alter the molecular machinery that interacts with sex hormone receptors to regulate gene expression, the contribution of chronic stress to the pathogenesis or presentation of mental illness may be additionally different between the sexes. Here, we review the mechanisms that contribute to sexual differentiation in the mammalian nervous system and consider some of the implications of these processes for sex differences in neuropsychiatric conditions.

Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.

Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights

Genome-wide association studies (GWAS) have identified over 100 risk loci for schizophrenia, but the causal mechanisms remain largely unknown. We performed a transcriptome-wide association study (TWAS) integrating a schizophrenia GWAS of 79,845 individuals from the Psychiatric Genomics Consortium with expression data from brain, blood, and adipose tissues across 3,693 primarily control individuals. We identified 157 TWAS-significant genes, of which 35 did not overlap a known GWAS locus. Of these 157 genes, 42 were associated with specific chromatin features measured in independent samples, thus highlighting potential regulatory targets for follow-up. Suppression of one identified susceptibility gene, mapk3, in zebrafish showed a significant effect on neurodevelopmental phenotypes. Expression and splicing from the brain captured most of the TWAS effect across all genes. This large-scale connection of associations to target genes, tissues, and regulatory features is an essential step in moving toward a mechanistic understanding of GWAS.

Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We applied our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N = 169,331) and found significant tissue-specific enrichments (false discovery rate (FDR) < 5%) for 34 traits. In our analysis of multiple tissues, we detected a broad range of enrichments that recapitulated known biology. In our brain-specific analysis, significant enrichments included an enrichment of inhibitory over excitatory neurons for bipolar disorder, and excitatory over inhibitory neurons for schizophrenia and body mass index. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signals.

Brain Transcriptome Databases: A User's Guide

Transcriptional programs instruct the generation and maintenance of diverse subtypes of neural cells, establishment of distinct brain regions, formation and function of neural circuits, and ultimately behavior. Spatiotemporal and cell type-specific analyses of the transcriptome, the sum total of all RNA transcripts in a cell or an organ, can provide insights into the role of genes in brain development and function, and their potential contribution to disorders of the brain. In the previous decade, advances in sequencing technology and funding from the National Institutes of Health and private foundations for large-scale genomics projects have led to a growing collection of brain transcriptome databases. These valuable resources provide rich and high-quality datasets with spatiotemporal, cell type-specific, and single-cell precision. Most importantly, many of these databases are publicly available via user-friendly web interface, making the information accessible to individual scientists without the need for advanced computational expertise. Here, we highlight key publicly available brain transcriptome databases, summarize the tissue sources and methods used to generate the data, and discuss their utility for neuroscience research.

Untangling Genetic Risk for Alzheimer's Disease

Alzheimer's disease (AD) is a genetically heterogeneous neurodegenerative disorder caused by fully penetrant single gene mutations in a minority of cases, while the majority of cases are sporadic or show modest familial clustering. These cases are of late onset and likely result from the interaction of many genes and the environment. More than 30 loci have been implicated in AD by a combination of linkage, genome-wide association, and whole genome/exome sequencing. We have learned from these studies that perturbations in endolysosomal, lipid metabolism, and immune response pathways substantially contribute to sporadic AD pathogenesis. We review here current knowledge about functions of AD susceptibility genes, highlighting cells of the myeloid lineage as drivers of at least part of the genetic component in late-onset AD. Although targeted resequencing utilized for the identification of causal variants has discovered coding mutations in some AD-associated genes, a lot of risk variants lie in noncoding regions. Here we discuss the use of functional genomics approaches that integrate transcriptomic, epigenetic, and endophenotype traits with systems biology to annotate genetic variants, and to facilitate discovery of AD risk genes. Further validation in cell culture and mouse models will be necessary to establish causality for these genes. This knowledge will allow mechanism-based design of novel therapeutic interventions in AD and promises coherent implementation of treatment in a personalized manner.

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.

DNA methylation and antipsychotic treatment mechanisms in schizophrenia: Progress and future directions

Antipsychotic response in schizophrenia is a complex, multifactorial trait influenced by pharmacogenetic factors. With genetic studies thus far providing little biological insight or clinical utility, the field of pharmacoepigenomics has emerged to tackle the so-called "missing heritability" of drug response in disease. Research on psychiatric disorders has only recently started to assess the link between epigenetic alterations and treatment outcomes. DNA methylation, the best characterised epigenetic mechanism to date, is discussed here in the context of schizophrenia and antipsychotic treatment outcomes. The majority of published studies have assessed the influence of antipsychotics on methylation levels in specific neurotransmitter-associated candidate genes or at the genome-wide level. While these studies illustrate the epigenetic modifications associated with antipsychotics, very few have assessed clinical outcomes and the potential of differential DNA methylation profiles as predictors of antipsychotic response. Results from other psychiatric disorder studies, such as depression and bipolar disorder, provide insight into what may be achieved by schizophrenia pharmacoepigenomics. Other aspects that should be addressed in future research include methodological challenges, such as tissue specificity, and the influence of genetic variation on differential methylation patterns.

Defining Regulatory Elements in the Human Genome Using Nucleosome Occupancy and Methylome Sequencing (NOMe-Seq)

NOMe-seq (nucleosome occupancy and methylome sequencing) identifies nucleosome-depleted regions that correspond to promoters, enhancers, and insulators. The NOMe-seq method is based on the treatment of chromatin with the M.CviPI methyltransferase, which methylates GpC dinucleotides that are not protected by nucleosomes or other proteins that are tightly bound to the chromatin (GpC^m does not occur in the human genome and therefore there is no endogenous background of GpC^m). Following bisulfite treatment of the M.CviPI-methylated chromatin (which converts unmethylated Cs to Ts and thus allows the distinction of GpC from GpC^m) and subsequent genomic sequencing, nucleosome-depleted regions can be ascertained on a genome-wide scale. The bisulfite treatment also allows the distinction of CpG from C^mpG (most endogenous methylation occurs at CpG dinucleotides) and thus the endogenous methylation status of the genome can also be obtained in the same sequencing reaction. Importantly, open chromatin is expected to have high levels of GpC^m but low levels of C^mpG; thus, each of the two separate methylation analyses serve as independent (but opposite) measures which provide matching chromatin designations for each regulatory element.NOMe-seq has advantages over ChIP-seq for identification of regulatory elements because it is not reliant upon knowing the exact modifications on the surrounding nucleosomes. Also, NOMe-seq has advantages over DHS (DNase hypersensitive site)-seq, FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements)-seq, and ATAC (Assay for Transposase-Accessible Chromatin)-seq because it also gives positioning information for several nucleosomes on either side of each open regulatory element. Here, we provide a detailed protocol for NOMe-seq that begins with the isolation of chromatin, followed by methylation of GpCs with M.CviPI and treatment with bisulfite, and ending with the creation of next generation sequencing libraries. We also include sequencing QC analysis metrics and bioinformatics steps that can be used to identify nucleosome-depleted regions throughout the genome.

Psychiatric Genomics: An Update and an Agenda

The Psychiatric Genomics Consortium (PGC) is the largest consortium in the history of psychiatry. This global effort is dedicated to rapid progress and open science, and in the past decade it has delivered an increasing flow of new knowledge about the fundamental basis of common psychiatric disorders. The PGC has recently commenced a program of research designed to deliver "actionable" findings-genomic results that 1) reveal fundamental biology, 2) inform clinical practice, and 3) deliver new therapeutic targets. The central idea of the PGC is to convert the family history risk factor into biologically, clinically, and therapeutically meaningful insights. The emerging findings suggest that we are entering a phase of accelerated genetic discovery for multiple psychiatric disorders. These findings are likely to elucidate the genetic portions of these truly complex traits, and this knowledge can then be mined for its relevance for improved therapeutics and its impact on psychiatric practice within a precision medicine framework. [AJP at 175: Remembering Our Past As We Envision Our Future November 1946: The Genetic Theory of Schizophrenia Franz Kallmann's influential twin study of schizophrenia in 691 twin pairs was the largest in the field for nearly four decades. (Am J Psychiatry 1946; 103:309-322 )].

Genomic resources for the study of neuropsychiatric disorders

The National Institute of Mental Health (NIMH) has made sustained investments in the development of genomic resources over the last two decades. These investments have led to the development of the largest biorepository for psychiatric genetics as a centralized national resource. In the realm of genomic resources, NIMH has been supporting large team science (TS) consortia focused on gene discovery, fine mapping of loci, and functional genomics using state-of-the-art technologies. The scientific output from these efforts has not only begun to transform our understanding of the genetic architecture of neuropsychiatric disorders, but it has also led to a broader cultural change among the investigator community towards deeper collaborations and broad pre-publication sharing of data and resources. The NIMH supported efforts have led to a vast increase in the amount of genetic and genomic resources available to the mental health research community. Here we provide an account of the existing resources and estimates of the scale and scope of what will be available in the near future. All biosamples and data described are intended for broad sharing with researchers worldwide, as allowed by the subject consent and applicable laws.

A multiregional proteomic survey of the postnatal human brain

Detailed observations of transcriptional, translational and post-translational events in the human brain are essential to improving our understanding of its development, function and vulnerability to disease. Here, we exploited label-free quantitative tandem mass-spectrometry to create an in-depth proteomic survey of regions of the postnatal human brain, ranging in age from early infancy to adulthood. Integration of protein data with existing matched whole-transcriptome sequencing (RNA-seq) from the BrainSpan project revealed varied patterns of protein-RNA relationships, with generally increased magnitudes of protein abundance differences between brain regions compared to RNA. Many of the differences amplified in protein data were reflective of cytoarchitectural and functional variation between brain regions. Comparing structurally similar cortical regions revealed significant differences in the abundances of receptor-associated and resident plasma membrane proteins that were not readily observed in the RNA expression data.

Whole genome sequencing in psychiatric disorders: the WGSPD consortium

As technology advances, whole genome sequencing (WGS) is likely to supersede other genotyping technologies. The rate of this change depends on its relative cost and utility. Variants identified uniquely through WGS may reveal novel biological pathways underlying complex disorders and provide high-resolution insight into when, where, and in which cell type these pathways are affected. Alternatively, cheaper and less computationally intensive approaches may yield equivalent insights. Understanding the role of rare variants in the noncoding gene-regulating genome, through pilot WGS projects, will be critical to determine which of these two extremes best represents reality. With large cohorts, well-defined risk loci, and a compelling need to understand the underlying biology, psychiatric disorders have a role to play in this preliminary WGS assessment. The WGSPD consortium will integrate data for 18,000 individuals with psychiatric disorders, beginning with autism spectrum disorder, schizophrenia, bipolar disorder, and major depressive disorder, along with over 150,000 controls.

Genome-wide mapping of genetic determinants influencing DNA methylation and gene expression in human hippocampus

Emerging evidence emphasizes the strong impact of regulatory genomic elements in neurodevelopmental processes and the complex pathways of brain disorders. The present genome-wide quantitative trait loci analyses explore the cis-regulatory effects of single-nucleotide polymorphisms (SNPs) on DNA methylation (meQTL) and gene expression (eQTL) in 110 human hippocampal biopsies. We identify cis-meQTLs at 14,118 CpG methylation sites and cis-eQTLs for 302 3'-mRNA transcripts of 288 genes. Hippocampal cis-meQTL-CpGs are enriched in flanking regions of active promoters, CpG island shores, binding sites of the transcription factor CTCF and brain eQTLs. Cis-acting SNPs of hippocampal meQTLs and eQTLs significantly overlap schizophrenia-associated SNPs. Correlations of CpG methylation and RNA expression are found for 34 genes. Our comprehensive maps of cis-acting hippocampal meQTLs and eQTLs provide a link between disease-associated SNPs and the regulatory genome that will improve the functional interpretation of non-coding genetic variants in the molecular genetic dissection of brain disorders.

Metabotropic glutamate receptors as emerging research targets in bipolar disorder

Glutamatergic dysregulation is implicated in the neuropathology of bipolar disorder (BD). There is increasing interest in investigating the role of metabotropic glutamate receptors (mGluRs) in BD and as a target for treatment intervention. Bipolar mGluR studies (published January 1992-April 2016) were identified via PubMed, Embase, Web of Science, and Scopus. Full-text screening, data extraction, and quality appraisal were conducted in duplicate, with strict inclusion and exclusion criteria. The initial literature search for mGluRs in BD, including non-bipolar mood disorders and primary psychotic disorders, identified 1544 articles. 61 abstracts were selected for relevance, 16 articles met full inclusion criteria, and three additional articles were found via citations. Despite limited literature, studies demonstrated: single nucleotide polymorphisms (SNPs) associated with BD, including a GRM3 SNP associated with greater likelihood of psychosis (rs6465084), mRNA binding protein Fragile X Mental Retardation Protein associated with altered mGluR1/5 activity in BD populations, and lithium decreasing mGluR5 expression and mGluR-mediated intracellular calcium signaling. Limited research has been performed on the role of mGluRs in BD, but results highlight the importance of ongoing study. Future directions for research of mGluRs in BD include GRM polymorphisms, epigenetic regulation, intracellular proteins, and pharmacologic interactions.

Progress in Genetic Studies of Tourette's Syndrome

Tourette's Syndrome (TS) is a complex disorder characterized by repetitive, sudden, and involuntary movements or vocalizations, called tics. Tics usually appear in childhood, and their severity varies over time. In addition to frequent tics, people with TS are at risk for associated problems including attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, depression, and problems with sleep. TS occurs in most populations and ethnic groups worldwide, and it is more common in males than in females. Previous family and twin studies have shown that the majority of cases of TS are inherited. TS was previously thought to have an autosomal dominant pattern of inheritance. However, several decades of research have shown that this is unlikely the case. Instead TS most likely results from a variety of genetic and environmental factors, not changes in a single gene. In the past decade, there has been a rapid development of innovative genetic technologies and methodologies, as well as significant progresses in genetic studies of psychiatric disorders. In this review, we will briefly summarize previous genetic epidemiological studies of TS and related disorders. We will also review previous genetic studies based on genome-wide linkage analyses and candidate gene association studies to comment on problems of previous methodological and strategic issues. Our main purpose for this review will be to summarize the new genetic discoveries of TS based on novel genetic methods and strategies, such as genome-wide association studies (GWASs), whole exome sequencing (WES) and whole genome sequencing (WGS). We will also compare the new genetic discoveries of TS with other major psychiatric disorders in order to understand the current status of TS genetics and its relationship with other psychiatric disorders.

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions

Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular aetiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, which are not enriched in genomic regions identified in genetic studies of schizophrenia and do not reflect direct genetic effects on DNA methylation. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with aetiological variation in complex disease.

The epigenomics of schizophrenia, in the mouse

Large-scale consortia including the Psychiatric Genomics Consortium, the Common Minds Consortium, BrainSeq and PsychENCODE, and many other studies taken together provide increasingly detailed insights into the genetic and epigenetic risk architectures of schizophrenia (SCZ) and offer vast amounts of molecular information, but with largely unexplored therapeutic potential. Here we discuss how epigenomic studies in human brain could guide animal work to test the impact of disease-associated alterations in chromatin structure and function on cognition and behavior. For example, transcription factors such as MYOCYTE-SPECIFIC ENHANCER FACTOR 2C (MEF2C), or multiple regulators of the open chromatin mark, methyl-histone H3-lysine 4, are associated with the genetic risk architectures of common psychiatric disease and alterations in chromatin structure and function in diseased brain tissue. Importantly, these molecules also affect cognition and behavior in genetically engineered mice, including virus-mediated expression changes in prefrontal cortex (PFC) and other key nodes in the circuitry underlying psychosis. Therefore, preclinical and small laboratory animal work could target genomic sequences affected by chromatin alterations in SCZ. To this end, in vivo editing of enhancer and other regulatory non-coding DNA by RNA-guided nucleases including CRISPR-Cas, and designer transcription factors, could be expected to deliver pipelines for novel therapeutic approaches aimed at improving cognitive dysfunction and other core symptoms of SCZ.

Transcriptional Dynamics at Brain Enhancers: from Functional Specialization to Neurodegeneration

Over the last decade, the noncoding part of the genome has been shown to harbour thousands of cis-regulatory elements, such as enhancers, that activate well-defined gene expression programs. Driven by the development of numerous techniques, many of these elements are now identified in multiple tissues and cell types, and their characteristics as well as importance in development and disease are becoming increasingly clear. Here, we provide an overview of the insights that were gained from the analysis of noncoding gene regulatory elements in the brain and describe their potential contribution to cell type specialization, brain function and neurodegenerative disease.

Sequencing on the SOLiD 5500xl System - in-depth characterization of the GC bias

Different types of sequencing biases have been described and subsequently improved for a variety of sequencing systems, mostly focusing on the widely used Illumina systems. Similar studies are missing for the SOLiD 5500xl system, a sequencer which produced many data sets available to researchers today. Describing and understanding the bias is important to accurately interpret and integrate these published data in various ongoing research projects. We report a particularly strong GC bias for this sequencing system when analyzing a defined gDNA mix of 5 microbes with a wide range of different GC contents (20-72%) when comparing to the expected distribution and Illumina MiSeq data from the same DNA pool. Since we observed this bias already under PCR-free conditions, changing the PCR conditions during library preparation - a common strategy to handle bias in the Illumina system - was not relevant. Source of the bias appeared to be an uneven heat distribution during the SOLiD emulsion PCR (ePCR) - for enrichment of libraries prior loading - since ePCR in either small pouches or in 96-well plates improved the GC bias. Sequencing of chromatin immunoprecipitated DNA (ChIP-seq) is a common approach in epigenetics. ChIP-seq of the mixed source histone mark H3K9ac (acetyl Histone H3 lysine 9), typically found on promoter regions and on gene bodies, including CpG islands, performed on a SOLiD 5500xl machine, resulted in major loss of reads at GC rich loci (GC content ≥ 62%), not explained by low sequencing depth. This was improved with adaptations of the ePCR.

Translating genome-wide association findings into new therapeutics for psychiatry

Genome-wide association studies (GWAS) in psychiatry, once they reach sufficient sample size and power, have been enormously successful. The Psychiatric Genomics Consortium (PGC) aims for mega-analyses with sample sizes that will grow to >1 million individuals in the next 5 years. This should lead to hundreds of new findings for common genetic variants across nine psychiatric disorders studied by the PGC. The new targets discovered by GWAS have the potential to restart largely stalled psychiatric drug development pipelines, and the translation of GWAS findings into the clinic is a key aim of the recently funded phase 3 of the PGC. This is not without considerable technical challenges. These approaches complement the other main aim of GWAS studies, risk prediction approaches for improving detection, differential diagnosis, and clinical trial design. This paper outlines the motivations, technical and analytical issues, and the plans for translating PGC phase 3 findings into new therapeutics.

BrainScope: interactive visual exploration of the spatial and temporal human brain transcriptome

Spatial and temporal brain transcriptomics has recently emerged as an invaluable data source for molecular neuroscience. The complexity of such data poses considerable challenges for analysis and visualization. We present BrainScope: a web portal for fast, interactive visual exploration of the Allen Atlases of the adult and developing human brain transcriptome. Through a novel methodology to explore high-dimensional data (dual t-SNE), BrainScope enables the linked, all-in-one visualization of genes and samples across the whole brain and genome, and across developmental stages. We show that densities in t-SNE scatter plots of the spatial samples coincide with anatomical regions, and that densities in t-SNE scatter plots of the genes represent gene co-expression modules that are significantly enriched for biological functions. We also show that the topography of the gene t-SNE maps reflect brain region-specific gene functions, enabling hypothesis and data driven research. We demonstrate the discovery potential of BrainScope through three examples: (i) analysis of cell type specific gene sets, (ii) analysis of a set of stable gene co-expression modules across the adult human donors and (iii) analysis of the evolution of co-expression of oligodendrocyte specific genes over developmental stages. BrainScope is publicly accessible at www.brainscope.nl.

Drug repurposing from the perspective of pharmaceutical companies

Drug repurposing holds the potential to bring medications with known safety profiles to new patient populations. Numerous examples exist for the identification of new indications for existing molecules, most stemming from serendipitous findings or focused recent efforts specifically limited to the mode of action of a specific drug. In recent years, the need for new approaches to drug research and development, combined with the advent of big data repositories and associated analytical methods, has generated interest in developing systematic approaches to drug repurposing. A variety of innovative computational methods to enable systematic repurposing screens, experimental as well as through in silico approaches, have emerged. An efficient drug repurposing pipeline requires the combination of access to molecular data, appropriate analytical expertise to enable robust insights, expertise and experimental set-up for validation and clinical development know-how. In this review, we describe some of the main approaches to systematic repurposing and discuss the various players in this field and the need for strategic collaborations to increase the likelihood of success in bringing existing molecules to new indications, as well as the current advantages, considerations and challenges in repurposing as a drug development strategy pursued by pharmaceutical companies.

LINKED ARTICLES

This article is part of a themed section on Inventing New Therapies Without Reinventing the Wheel: The Power of Drug Repurposing. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.2/issuetoc.

Brain transcriptome atlases: a computational perspective

The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases.

Histone Acetylome-wide Association Study of Autism Spectrum Disorder

The association of histone modification changes with autism spectrum disorder (ASD) has not been systematically examined. We conducted a histone acetylome-wide association study (HAWAS) by performing H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq) on 257 postmortem samples from ASD and matched control brains. Despite etiological heterogeneity, ≥68% of syndromic and idiopathic ASD cases shared a common acetylome signature at >5,000 cis-regulatory elements in prefrontal and temporal cortex. Similarly, multiple genes associated with rare genetic mutations in ASD showed common "epimutations." Acetylome aberrations in ASD were not attributable to genetic differentiation at cis-SNPs and highlighted genes involved in synaptic transmission, ion transport, epilepsy, behavioral abnormality, chemokinesis, histone deacetylation, and immunity. By correlating histone acetylation with genotype, we discovered >2,000 histone acetylation quantitative trait loci (haQTLs) in human brain regions, including four candidate causal variants for psychiatric diseases. Due to the relative stability of histone modifications postmortem, we anticipate that the HAWAS approach will be applicable to multiple diseases.

Molecular mechanisms underlying noncoding risk variations in psychiatric genetic studies

Recent large-scale genetic approaches such as genome-wide association studies have allowed the identification of common genetic variations that contribute to risk architectures of psychiatric disorders. However, most of these susceptibility variants are located in noncoding genomic regions that usually span multiple genes. As a result, pinpointing the precise variant(s) and biological mechanisms accounting for the risk remains challenging. By reviewing recent progresses in genetics, functional genomics and neurobiology of psychiatric disorders, as well as gene expression analyses of brain tissues, here we propose a roadmap to characterize the roles of noncoding risk loci in the pathogenesis of psychiatric illnesses (that is, identifying the underlying molecular mechanisms explaining the genetic risk conferred by those genomic loci, and recognizing putative functional causative variants). This roadmap involves integration of transcriptomic data, epidemiological and bioinformatic methods, as well as in vitro and in vivo experimental approaches. These tools will promote the translation of genetic discoveries to physiological mechanisms, and ultimately guide the development of preventive, therapeutic and prognostic measures for psychiatric disorders.

It's All in the Brain: A Review of Available Functional Genomic Annotations

What makes the molecular study of psychiatric and other neurological conditions particularly challenging compared with other complex traits is the difficulty of accessing the relevant tissue. The Encyclopedia of DNA Elements (ENCODE) project was one of the earliest producers of brain-derived epigenetic functional genomic data, albeit initially from only two cancerous brain cell lines for a limited number of epigenetic marks. It has only been in very recent years that such data from human brain tissue have been made available from various sources. Yet, these data are scattered throughout the literature with no central organization. This review summarizes the availability and accessibility of brain epigenetic and functional genomic data as a single resource to allow investigators to easily access available brain annotations and thus incorporate this wealth of information into their research to make important advances in the field of neuroscience.

Epigenetic Regulation of BDNF Gene during Development and Diseases

Brain-derived neurotrophic factor (BDNF) is required for the development of the nervous system, proper cognitive function and memory formation. While aberrant expression of BDNF has been implicated in neurological disorders, the transcriptional regulation of BDNF remains to be elucidated. In response to different stimuli, BDNF expression can be initiated from different promoters. Several studies have suggested that the expression of BDNF is regulated by promoter methylation. An emerging theme points to the possibility that histone modifications at the BDNF promoters may link to the neurological pathology. Thus, understanding the epigenetic regulation at the BDNF promoters will shed light on future therapies for neurological disorders. The present review summarizes the current knowledge of histone modifications of the BDNF gene in neuronal diseases, as well as the developmental regulation of the BDNF gene based on data from the Encyclopedia of DNA Elements (ENCODE).

Practical Guidelines for High-Resolution Epigenomic Profiling of Nucleosomal Histones in Postmortem Human Brain Tissue

BACKGROUND

The nervous system may include more than 100 residue-specific posttranslational modifications of histones forming the nucleosome core that are often regulated in cell-type-specific manner. On a genome-wide scale, some of the histone posttranslational modification landscapes show significant overlap with the genetic risk architecture for several psychiatric disorders, fueling PsychENCODE and other large-scale efforts to comprehensively map neuronal and nonneuronal epigenomes in hundreds of specimens. However, practical guidelines for efficient generation of histone chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) datasets from postmortem brains are needed.

METHODS

Protocols and quality controls are given for the following: 1) extraction, purification, and NeuN neuronal marker immunotagging of nuclei from adult human cerebral cortex; 2) fluorescence-activated nuclei sorting; 3) preparation of chromatin by micrococcal nuclease digest; 4) ChIP for open chromatin-associated histone methylation and acetylation; and 5) generation and sequencing of ChIP-seq libraries.

RESULTS

We present a ChIP-seq pipeline for epigenome mapping in the neuronal and nonneuronal nuclei from the postmortem brain. This includes a stepwise system of quality controls and user-friendly data presentation platforms.

CONCLUSIONS

Our practical guidelines will be useful for projects aimed at histone posttranslational modification mapping in chromatin extracted from hundreds of postmortem brain samples in cell-type-specific manner.

Transcriptional Gene Silencing of the Autism-Associated Long Noncoding RNA MSNP1AS in Human Neural Progenitor Cells

The long noncoding RNA MSNP1AS (moesin pseudogene 1, antisense) is a functional element that was previously associated with autism spectrum disorder (ASD) with genome-wide significance. Expression of MSNP1AS was increased 12-fold in the cerebral cortex of individuals with ASD and 22-fold in individuals with a genome-wide significantly associated ASD genetic marker on chromosome 5p14.1. Overexpression of MSNP1AS in human neuronal cells caused decreased expression of moesin protein, which is involved in neuronal process stability. In this study, we hypothesize that MSNP1AS knockdown impacts global transcriptome levels. We transfected the human neural progenitor cell line SK- N-SH with constructs that caused a 50% suppression of MSNP1AS expression. After 24 h, cells were harvested for total RNA isolation. Strand-specific RNA sequencing analysis indicated altered expression of 1,352 genes, including altered expression of 318 genes following correction for multiple comparisons. Expression of the OAS2 gene was increased >150-fold, a result that was validated by quantitative PCR. Gene ontology analysis of the 318 genes with altered expression following correction for multiple comparisons indicated that upregulated genes were significantly enriched for genes involved in immune response, and downregulated genes were significantly enriched for genes involved in chromatin remodeling. These data indicate multiple transcriptional and translational functions of MSNP1AS that impact ASD-relevant biological processes. Chromatin remodeling and immune response are biological processes implicated by genes with rare mutations associated with ASD. Our data suggest that the functional elements implicated by association of common genetic variants impact the same biological processes, suggesting a possible shared common molecular pathway of ASD.

Searching for convergent pathways in autism spectrum disorders: insights from human brain transcriptome studies

Autism spectrum disorder (ASD) is one of the most heritable neuropsychiatric conditions. The complex genetic landscape of the disorder includes both common and rare variants at hundreds of genetic loci. This marked heterogeneity has thus far hampered efforts to develop genetic diagnostic panels and targeted pharmacological therapies. Here, we give an overview of the current literature on the genetic basis of ASD, and review recent human brain transcriptome studies and their role in identifying convergent pathways downstream of the heterogeneous genetic variants. We also discuss emerging evidence on the involvement of non-coding genomic regions and non-coding RNAs in ASD.

Genomics implicates adaptive and innate immunity in Alzheimer's and Parkinson's diseases

OBJECTIVES

We assessed the current genetic evidence for the involvement of various cell types and tissue types in the etiology of neurodegenerative diseases, especially in relation to the neuroinflammatory hypothesis of neurodegenerative diseases.

METHODS

We obtained large-scale genome-wide association study (GWAS) summary statistics from Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS). We used multiple sclerosis (MS), an autoimmune disease of the central nervous system, as a positive control. We applied stratified LD score regression to determine if functional marks for cell type and tissue activity, and gene-set lists were enriched for genetic heritability. We compared our results to those from two gene-set enrichment methods (Ingenuity Pathway Analysis and enrichr).

RESULTS

There were no significant heritability enrichments for annotations marking genes active within brain regions, but there were significant heritability enrichments for annotations marking genes active within cell types that form part of both the innate and adaptive immune systems. We found this for MS (as expected) and also for AD and PD. The strongest signals were from the adaptive immune system (e.g., T cells) for PD, and from both the adaptive (e.g., T cells) and innate (e.g., CD14: a marker for monocytes, and CD15: a marker for neutrophils) immune systems for AD. Annotations from the liver were also significant for AD. Pathway analysis provided complementary results.

INTERPRETATION

For AD and PD, we found significant enrichment of heritability in annotations marking gene activity in immune cells.

Toward development of epigenetic drugs for central nervous system disorders: Modulating neuroplasticity via H3K4 methylation

The mammalian brain dynamically activates or silences gene programs in response to environmental input and developmental cues. This neuroplasticity is controlled by signaling pathways that modify the activity, localization, and/or expression of transcriptional-regulatory enzymes in combination with alterations in chromatin structure in the nucleus. Consistent with this key neurobiological role, disruptions in the fine-tuning of epigenetic and transcriptional regulation have emerged as a recurrent theme in studies of the genetics of neurodevelopmental and neuropsychiatric disorders. Furthermore, environmental factors have been implicated in the increased risk of heterogeneous, multifactorial, neuropsychiatric disorders via epigenetic mechanisms. Aberrant epigenetic regulation of gene expression thus provides an attractive unifying model for understanding the complex risk architecture of mental illness. Here, we review emerging genetic evidence implicating dysregulation of histone lysine methylation in neuropsychiatric disease and outline advancements in small-molecule probes targeting this chromatin modification. The emerging field of neuroepigenetic research is poised to provide insight into the biochemical basis of genetic risk for diverse neuropsychiatric disorders and to develop the highly selective chemical tools and imaging agents necessary to dissect dynamic transcriptional-regulatory mechanisms in the nervous system. On the basis of these findings, continued advances may lead to the validation of novel, disease-modifying therapeutic targets for a range of disorders with aberrant chromatin-mediated neuroplasticity.

Understanding the genetic liability to schizophrenia through the neuroepigenome

The Psychiatric Genomics Consortium-Schizophrenia Workgroup (PGC-SCZ) recently identified 108 loci associated with increased risk for schizophrenia (SCZ). The vast majority of these variants reside within non-coding sequences of the genome and are predicted to exert their effects by affecting the mechanism of action of cis regulatory elements (CREs), such as promoters and enhancers. Although a number of large-scale collaborative efforts (e.g. ENCODE) have achieved a comprehensive mapping of CREs in human cell lines or tissue homogenates, it is becoming increasingly evident that many risk-associated variants are enriched for expression Quantitative Trait Loci (eQTLs) and CREs in specific tissues or cells. As such, data derived from previous research endeavors may not capture fully cell-type and/or region specific changes associated with brain diseases. Coupling recent technological advances in genomics with cell-type specific methodologies, we are presented with an unprecedented opportunity to better understand the genetics of normal brain development and function and, in turn, the molecular basis of neuropsychiatric disorders. In this review, we will outline ongoing efforts towards this goal and will discuss approaches with the potential to shed light on the mechanism(s) of action of cell-type specific cis regulatory elements and their putative roles in disease, with particular emphasis on understanding the manner in which the epigenome and CREs influence the etiology of SCZ.

Spatial genome organization and cognition

Nonrandom chromosomal conformations, including promoter-enhancer loopings that bypass kilobases or megabases of linear genome, provide a crucial layer of transcriptional regulation and move vast amounts of non-coding sequence into the physical proximity of genes that are important for neurodevelopment, cognition and behaviour. Activity-regulated changes in the neuronal '3D genome' could govern transcriptional mechanisms associated with learning and plasticity, and loop-bound intergenic and intronic non-coding sequences have been implicated in psychiatric and adult-onset neurodegenerative disease. Recent studies have begun to clarify the roles of spatial genome organization in normal and abnormal cognition.

Impact of the Autism-Associated Long Noncoding RNA MSNP1AS on Neuronal Architecture and Gene Expression in Human Neural Progenitor Cells

We previously identified the long noncoding RNA (lncRNA) MSNP1AS (moesin pseudogene 1, antisense) as a functional element revealed by genome wide significant association with autism spectrum disorder (ASD). MSNP1AS expression was increased in the postmortem cerebral cortex of individuals with ASD and particularly in individuals with the ASD-associated genetic markers on chromosome 5p14.1. Here, we mimicked the overexpression of MSNP1AS observed in postmortem ASD cerebral cortex in human neural progenitor cell lines to determine the impact on neurite complexity and gene expression. ReNcell CX and SK-N-SH were transfected with an overexpression vector containing full-length MSNP1AS. Neuronal complexity was determined by the number and length of neuronal processes. Gene expression was determined by strand-specific RNA sequencing. MSNP1AS overexpression decreased neurite number and neurite length in both human neural progenitor cell lines. RNA sequencing revealed changes in gene expression in proteins involved in two biological processes: protein synthesis and chromatin remodeling. These data indicate that overexpression of the ASD-associated lncRNA MSNP1AS alters the number and length of neuronal processes. The mechanisms by which MSNP1AS overexpression impacts neuronal differentiation may involve protein synthesis and chromatin structure. These same biological processes are also implicated by rare mutations associated with ASD, suggesting convergent mechanisms.

Cross-Disorder Psychiatric Genomics

PURPOSE OF REVIEW

The following review provides some description of the movement in cross-disorder psychiatric genomics toward addressing both comorbidity and polygenicity.

RECENT FINDINGS

We attempt to show how dimensional approaches to the phenotype have led to further addressing the problem of comorbidity of psychiatric diagnoses. And we also attempt to show how a dimensional approach to the genome, with different statistical methods from traditional genome-wide association analyses, has begun to resolve the problem of massive polygenicity.

SUMMARY

Cross-disorder research, of any area in psychiatry, arguably has the most potential to inform clinical diagnosis, early detection and prevention strategies, and pharmacological treatment research. Future research might leverage what we now know to inform developmental studies of risk and resilience.

Genetic variants in Alzheimer disease - molecular and brain network approaches

Genetic studies in late-onset Alzheimer disease (LOAD) are aimed at identifying core disease mechanisms and providing potential biomarkers and drug candidates to improve clinical care of AD. However, owing to the complexity of LOAD, including pathological heterogeneity and disease polygenicity, extraction of actionable guidance from LOAD genetics has been challenging. Past attempts to summarize the effects of LOAD-associated genetic variants have used pathway analysis and collections of small-scale experiments to hypothesize functional convergence across several variants. In this Review, we discuss how the study of molecular, cellular and brain networks provides additional information on the effects of LOAD-associated genetic variants. We then discuss emerging combinations of these omic data sets into multiscale models, which provide a more comprehensive representation of the effects of LOAD-associated genetic variants at multiple biophysical scales. Furthermore, we highlight the clinical potential of mechanistically coupling genetic variants and disease phenotypes with multiscale brain models.

Hypomethylation of FAM63B in bipolar disorder patients

Bipolar disorder (BD) and schizophrenia (SZ) are known to share common genetic and psychosocial risk factors. A recent epigenome-wide association study performed on blood samples from SZ patients found significant hypomethylation of FAM63B in exon 9. Here, we used iPLEX-based methylation analysis to investigate two CpG sites in FAM63B in blood samples from 459 BD cases and 268 controls. Both sites were significantly hypomethylated in BD cases (lowest p value = 3.94 × 10(-8)). The methylation levels at the two sites were correlated, and no strong correlation was found with nearby single nucleotide polymorphisms (SNPs), suggesting that methylation differences at these sites are not readably picked up by genome-wide association studies. Overall, FAM63B hypomethylation was found in BD patients, thus replicating the initial finding in SZ patients. This study suggests that FAM63B is a shared epigenetic risk gene for the two disorders.

Allele-Skewed DNA Modification in the Brain: Relevance to a Schizophrenia GWAS

Numerous recent studies have suggested that phenotypic effects of DNA sequence variants can be mediated or modulated by their epigenetic marks, such as allele-skewed DNA modification (ASM). Using Affymetrix SNP microarrays, we performed a comprehensive search of ASM effects in human post-mortem brain and sperm samples (total n = 256) from individuals with major psychosis and control individuals. Depending on the phenotypic category of the brain samples, 1.4%-7.5% of interrogated SNPs exhibited ASM effects. Next, we investigated ASM in the context of genetic studies of schizophrenia and detected that brain ASM SNPs were significantly overrepresented among sub-threshold SNPs from a schizophrenia genome-wide association study (GWAS). Brain ASM SNPs showed a much stronger enrichment in a schizophrenia GWAS than in 17 large GWASs of non-psychiatric diseases and traits, arguing that ASM effects are at least partially tissue specific. Studies of germline and control brain ASM SNPs supported a causal association between ASM and schizophrenia. Finally, significantly higher proportions of ASM SNPs than of non-ASM SNPs were detected at loci exhibiting epigenetic signatures of enhancers and promoters, and they were overrepresented within transcription factor binding regions and DNase I hypersensitive sites. All of these findings collectively indicate that ASM SNPs should be prioritized in follow-up GWASs.