A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons

SATB2 organizes the 3D genome architecture of cognition in cortical neurons

The DNA-binding protein SATB2 is genetically linked to human intelligence. We studied its influence on the three-dimensional (3D) epigenome by mapping chromatin interactions and accessibility in control versus SATB2-deficient cortical neurons. We find that SATB2 affects the chromatin looping between enhancers and promoters of neuronal-activity-regulated genes, thus influencing their expression. It also alters A/B compartments, topologically associating domains, and frequently interacting regions. Genes linked to SATB2-dependent 3D genome changes are implicated in highly specialized neuronal functions and contribute to cognitive ability and risk for neuropsychiatric and neurodevelopmental disorders. Non-coding DNA regions with a SATB2-dependent structure are enriched for common variants associated with educational attainment, intelligence, and schizophrenia. Our data establish SATB2 as a cell-type-specific 3D genome modulator, which operates both independently and in cooperation with CCCTC-binding factor (CTCF) to set up the chromatin landscape of pyramidal neurons for cognitive processes.

Dopaminergic dysfunction: Role for genetic & epigenetic testing in the new psychiatry

Reward Deficiency Syndrome (RDS), particularly linked to addictive disorders, costs billions of dollars globally and has resulted in over one million deaths in the United States (US). Illicit substance use has been steadily rising and in 2021 approximately 21.9% (61.2 million) of individuals living in the US aged 12 or older had used illicit drugs in the past year. However, only 1.5% (4.1 million) of these individuals had received any substance use treatment. This increase in use and failure to adequately treat or provide treatment to these individuals resulted in 106,699 overdose deaths in 2021 and increased in 2022. This article presents an alternative non-pharmaceutical treatment approach tied to gene-guided therapy, the subject of many decades of research. The cornerstone of this paradigm shift is the brain reward circuitry, brain stem physiology, and neurotransmitter deficits due to the effects of genetic and epigenetic insults on the interrelated cascade of neurotransmission and the net release of dopamine at the Ventral Tegmental Area -Nucleus Accumbens (VTA-NAc) reward site. The Genetic Addiction Risk Severity (GARS) test and pro-dopamine regulator nutraceutical KB220 were combined to induce "dopamine homeostasis" across the brain reward circuitry. This article aims to encourage four future actionable items: 1) the neurophysiologically accurate designation of, for example, "Hyperdopameism /Hyperdopameism" to replace the blaming nomenclature like alcoholism; 2) encouraging continued research into the nature of dysfunctional brainstem neurotransmitters across the brain reward circuitry; 3) early identification of people at risk for all RDS behaviors as a brain check (cognitive testing); 4) induction of dopamine homeostasis using "precision behavioral management" along with the coupling of GARS and precision Kb220 variants; 5) utilization of promising potential treatments include neuromodulating modalities such as Transmagnetic stimulation (TMS) and Deep Brain Stimulation(DBS), which target different areas of the neural circuitry involved in addiction and even neuroimmune agents like N-acetyl-cysteine.

Invited Expert Opinion- Bioinformatic and Limitation Directives to Help Adopt Genetic Addiction Risk Screening and Identify Preaddictive Reward Dysregulation: Required Analytic Evidence to Induce Dopamine Homeostatsis

Addiction, albeit some disbelievers like Mark Lewis [1], is a chronic, relapsing brain disease, resulting in unwanted loss of control over both substance and non- substance behavioral addictions leading to serious adverse consequences [2]. Addiction scientists and clinicians face an incredible challenge in combatting the current opioid and alcohol use disorder (AUD) pandemic throughout the world. Provisional data from the Centers for Disease Control and Prevention (CDC) shows that from July 2021-2022, over 100,000 individuals living in the United States (US) died from a drug overdose, and 77,237 of those deaths were related to opioid use [3]. This number is expected to rise, and according to the US Surgeon General it is highly conceivable that by 2025 approximately 165,000 Americans will die from an opioid overdose. Alcohol abuse, according to data from the World Health Organization (WHO), results in 3 million deaths worldwide every year, which represents 5.3% of all deaths globally [4].

Single nucleus transcriptomics of ventral midbrain identifies glial activation associated with chronic opioid use disorder

Dynamic interactions of neurons and glia in the ventral midbrain mediate reward and addiction behavior. We studied gene expression in 212,713 ventral midbrain single nuclei from 95 individuals with history of opioid misuse, and individuals without drug exposure. Chronic exposure to opioids was not associated with change in proportions of glial and neuronal subtypes, however glial transcriptomes were broadly altered, involving 9.5 - 6.2% of expressed genes within microglia, oligodendrocytes, and astrocytes. Genes associated with activation of the immune response including interferon, NFkB signaling, and cell motility pathways were upregulated, contrasting with down-regulated expression of synaptic signaling and plasticity genes in ventral midbrain non-dopaminergic neurons. Ventral midbrain transcriptomic reprogramming in the context of chronic opioid exposure included 325 genes that previous genome-wide studies had linked to risk of substance use traits in the broader population, thereby pointing to heritable risk architectures in the genomic organization of the brain's reward circuitry.

Schizophrenia Risk Mapping and Functional Engineering of the 3D Genome in Three Neuronal Subtypes

Common variants associated with schizophrenia are concentrated in non-coding regulatory sequences, but their precise target genes are context-dependent and impacted by cell-type-specific three-dimensional spatial chromatin organization. Here, we map long-range chromosomal conformations in isogenic human dopaminergic, GABAergic, and glutamatergic neurons to track developmentally programmed shifts in the regulatory activity of schizophrenia risk loci. Massive repressive compartmentalization, concomitant with the emergence of hundreds of neuron-specific multi-valent chromatin architectural stripes, occurs during neuronal differentiation, with genes interconnected to genetic risk loci through these long-range chromatin structures differing in their biological roles from genes more proximal to sequences conferring heritable risk. Chemically induced CRISPR-guided chromosomal loop-engineering for the proximal risk gene SNAP91 and distal risk gene BHLHE22 profoundly alters synaptic development and functional activity. Our findings highlight the large-scale cell-type-specific reorganization of chromosomal conformations at schizophrenia risk loci during neurodevelopment and establish a causal link between risk-associated gene-regulatory loop structures and neuronal function.

Network models of chromatin structure

Increasing numbers of datasets and experimental assays that capture the organization of chromatin inside the nucleus warrant an effort to develop tools to visualize and analyze these structures. Alongside polymer physics or constraint-based modeling, network theory approaches to describe 3D epigenome organization have gained in popularity. Representing genomic regions as nodes in a network enables visualization of 1D epigenomics datasets in the context of chromatin structure maps, while network theory metrics can be used to describe 3D epigenome organization and dynamics. In this review, we summarize the most salient applications of network theory to the study of chromatin contact maps, demonstrating its potential in revealing epigenomic patterns and relating them to cellular phenotypes.

Induction of dopaminergic neurons for neuronal subtype-specific modeling of psychiatric disease risk

Dopaminergic neurons are critical to movement, mood, addiction, and stress. Current techniques for generating dopaminergic neurons from human induced pluripotent stem cells (hiPSCs) yield heterogenous cell populations with variable purity and inconsistent reproducibility between donors, hiPSC clones, and experiments. Here, we report the rapid (5 weeks) and efficient (~90%) induction of induced dopaminergic neurons (iDANs) through transient overexpression of lineage-promoting transcription factors combined with stringent selection across five donors. We observe maturation-dependent increase in dopamine synthesis and electrophysiological properties consistent with midbrain dopaminergic neuron identity, such as slow-rising after- hyperpolarization potentials, an action potential duration of ~3 ms, tonic sub-threshold oscillatory activity, and spontaneous burst firing at a frequency of ~1.0-1.75 Hz. Transcriptome analysis reveals robust expression of genes involved in fetal midbrain dopaminergic neuron identity. Specifically expressed genes in iDANs, as well as those from isogenic induced GABAergic and glutamatergic neurons, were enriched in loci conferring heritability for cannabis use disorder, schizophrenia, and bipolar disorder; however, each neuronal subtype demonstrated subtype-specific heritability enrichments in biologically relevant pathways, and iDANs alone were uniquely enriched in autism spectrum disorder risk loci. Therefore, iDANs provide a critical tool for modeling midbrain dopaminergic neuron development and dysfunction in psychiatric disease.

Single Nucleus Transcriptomics Reveals Pervasive Glial Activation in Opioid Overdose Cases

Dynamic interactions of neurons and glia in the ventral midbrain (VM) mediate reward and addiction behavior. We studied gene expression in 212,713 VM single nuclei from 95 human opioid overdose cases and drug-free controls. Chronic exposure to opioids left numerical proportions of VM glial and neuronal subtypes unaltered, while broadly affecting glial transcriptomes, involving 9.5 - 6.2% of expressed genes within microglia, oligodendrocytes, and astrocytes, with prominent activation of the immune response including interferon, NFkB signaling, and cell motility pathways, sharply contrasting with down-regulated expression of synaptic signaling and plasticity genes in VM non-dopaminergic neurons. VM transcriptomic reprogramming in the context of opioid exposure and overdose included 325 genes with genetic variation linked to substance use traits in the broader population, thereby pointing to heritable risk architectures in the genomic organization of the brain's reward circuitry.

Why haven't we solved the addiction crisis?

The current addiction crisis has destroyed a multitude of lives, leaving millions of fatalities worldwide in its wake. At the same time, various governmental agencies dedicated to solving this seemingly never-ending dilemma have not yet succeeded or delivered on their promises. We understand that addictive behavioral seeking is a multi-faceted neurobiological and spiritually complicated phenomenon. However, although the substitution replacement approach, especially to treat Opioid Use Disorder (OUD), has importance for harm reduction in the short term, it does not bring about a harm-free recovery or prevention. Instead, we propose a promising novel approach that uses genetic risk testing with induction of dopamine homeostasis and an objective Brain Health Check during youth. Our model involves a six-hit approach known as the "Reward Dysregulation Syndrome Solution System," which can identify addiction risk and target the root cause of addiction, dopamine dysregulation. While we applaud all past sophisticated neurogenetic and neuropharmacological research, our opinion is that in the long term, addiction scientists and clinicians might characterize preaddiction using tests; for example, administering the validated RDSQuestionarre29, genetic risk assessment, a modified brain health check, or diagnostic framing of mild to moderate Substance Use Disorder (SUD). The preaddiction concept could incentivize the development of interventions to prevent addiction from developing in the first place and target and treat neurotransmitter imbalances and other early indications of addiction. WC 222.

3D Genome Plasticity in Normal and Diseased Neurodevelopment

Non-random spatial organization of the chromosomal material inside the nuclei of brain cells emerges as an important regulatory layer of genome organization and function in health and disease. Here, we discuss how integrative approaches assessing chromatin in context of the 3D genome is providing new insights into normal and diseased neurodevelopment. Studies in primate (incl. human) and rodent brain have confirmed that chromosomal organization in neurons and glia undergoes highly dynamic changes during pre- and early postnatal development, with potential for plasticity across a much wider age window. For example, neuronal 3D genomes from juvenile and adult cerebral cortex and hippocampus undergo chromosomal conformation changes at hundreds of loci in the context of learning and environmental enrichment, viral infection, and neuroinflammation. Furthermore, locus-specific structural DNA variations, such as micro-deletions, duplications, repeat expansions, and retroelement insertions carry the potential to disrupt the broader epigenomic and transcriptional landscape far beyond the boundaries of the site-specific variation, highlighting the critical importance of long-range intra- and inter-chromosomal contacts for neuronal and glial function.

High-resolution genome topology of human retina uncovers super enhancer-promoter interactions at tissue-specific and multifactorial disease loci

Chromatin organization and enhancer-promoter contacts establish unique spatiotemporal gene expression patterns in distinct cell types. Non-coding genetic variants can influence cellular phenotypes by modifying higher-order transcriptional hubs and consequently gene expression. To elucidate genomic regulation in human retina, we mapped chromatin contacts at high resolution and integrated with super-enhancers (SEs), histone marks, binding of CTCF and select transcription factors. We show that topologically associated domains (TADs) with central SEs exhibit stronger insulation and augmented contact with retinal genes relative to TADs with edge SEs. Merging genome-wide expression quantitative trait loci (eQTLs) with topology map reveals physical links between 100 eQTLs and corresponding eGenes associated with retinal neurodegeneration. Additionally, we uncover candidate genes for susceptibility variants linked to age-related macular degeneration and glaucoma. Our study of high-resolution genomic architecture of human retina provides insights into genetic control of tissue-specific functions, suggests paradigms for missing heritability, and enables the dissection of common blinding disease phenotypes.

Chromatin architecture in addiction circuitry identifies risk genes and potential biological mechanisms underlying cigarette smoking and alcohol use traits

Cigarette smoking and alcohol use are among the most prevalent substances used worldwide and account for a substantial proportion of preventable morbidity and mortality, underscoring the public health significance of understanding their etiology. Genome-wide association studies (GWAS) have successfully identified genetic variants associated with cigarette smoking and alcohol use traits. However, the vast majority of risk variants reside in non-coding regions of the genome, and their target genes and neurobiological mechanisms are unknown. Chromosomal conformation mappings can address this knowledge gap by charting the interaction profiles of risk-associated regulatory variants with target genes. To investigate the functional impact of common variants associated with cigarette smoking and alcohol use traits, we applied Hi-C coupled MAGMA (H-MAGMA) built upon cortical and newly generated midbrain dopaminergic neuronal Hi-C datasets to GWAS summary statistics of nicotine dependence, cigarettes per day, problematic alcohol use, and drinks per week. The identified risk genes mapped to key pathways associated with cigarette smoking and alcohol use traits, including drug metabolic processes and neuronal apoptosis. Risk genes were highly expressed in cortical glutamatergic, midbrain dopaminergic, GABAergic, and serotonergic neurons, suggesting them as relevant cell types in understanding the mechanisms by which genetic risk factors influence cigarette smoking and alcohol use. Lastly, we identified pleiotropic genes between cigarette smoking and alcohol use traits under the assumption that they may reveal substance-agnostic, shared neurobiological mechanisms of addiction. The number of pleiotropic genes was ~26-fold higher in dopaminergic neurons than in cortical neurons, emphasizing the critical role of ascending dopaminergic pathways in mediating general addiction phenotypes. Collectively, brain region- and neuronal subtype-specific 3D genome architecture helps refine neurobiological hypotheses for smoking, alcohol, and general addiction phenotypes by linking genetic risk factors to their target genes.

Understanding Regulatory Mechanisms of Brain Function and Disease through 3D Genome Organization

The human genome has a complex and dynamic three-dimensional (3D) organization, which plays a critical role for gene regulation and genome function. The importance of 3D genome organization in brain development and function has been well characterized in a region- and cell-type-specific fashion. Recent technological advances in chromosome conformation capture (3C)-based techniques, imaging approaches, and ligation-free methods, along with computational methods to analyze the data generated, have revealed 3D genome features at different scales in the brain that contribute to our understanding of genetic mechanisms underlying neuropsychiatric diseases and other brain-related traits. In this review, we discuss how these advances aid in the genetic dissection of brain-related traits.

Clinical Characterization of Copy Number Variants Associated With Neurodevelopmental Disorders in a Large-scale Multiancestry Biobank

IMPORTANCE

Past studies identified rare copy number variants (CNVs) as risk factors for neurodevelopmental disorders (NDDs), including autism spectrum disorder and schizophrenia. However, the clinical characterization of NDD CNVs is understudied in population cohorts unselected for neuropsychiatric disorders and in cohorts of diverse ancestry.

OBJECTIVE

To identify individuals harboring NDD CNVs in a multiancestry biobank and to query their enrichment for select neuropsychiatric disorders as well as association with multiple medical disorders.

DESIGN, SETTINGS, AND PARTICIPANTS

In a series of phenotypic enrichment and association analyses, NDD CNVs were clinically characterized among 24 877 participants in the BioMe biobank, an electronic health record-linked biobank derived from the Mount Sinai Health System, New York, New York. Participants were recruited into the biobank since September 2007 across diverse ancestry and medical and neuropsychiatric specialties. For the current analyses, electronic health record data were analyzed from May 2004 through May 2019.

MAIN OUTCOMES AND MEASURES

NDD CNVs were identified using a consensus of 2 CNV calling algorithms, based on whole-exome sequencing and genotype array data, followed by novel in-silico clinical assessments.

RESULTS

Of 24 877 participants, 14 586 (58.7%) were female; self-reported ancestry categories included 5965 (24.0%) who were of African ancestry, 7892 (31.7%) who were of European ancestry, and 8536 (34.3%) who were of Hispanic ancestry; and the mean (SD) age was 50.5 (17.3) years. Among 24 877 individuals, the prevalence of 64 NDD CNVs was 2.5% (n = 627), with prevalence varying by locus, corroborating the presence of some relatively highly prevalent NDD CNVs (eg, 15q11.2 deletion/duplication). An aggregate set of NDD CNVs were enriched for congenital disorders (odds ratio, 2.0; 95% CI, 1.1-3.5; P = .01) and major depressive disorder (odds ratio, 1.5; 95% CI, 1.1-2.0; P = .01). In a meta-analysis of medical diagnoses (n = 195 hierarchically clustered diagnostic codes), NDD CNVs were significantly associated with several medical outcomes, including essential hypertension (z score = 3.6; P = 2.8 × 10-4), kidney failure (z score = 3.3; P = 1.1 × 10-3), and obstructive sleep apnea (z score = 3.4; P = 8.1 × 10-4) and, in another analysis, morbid obesity (z score = 3.8; P = 1.3 × 10-4). Further, NDD CNVs were associated with increased body mass index in a multiancestry analysis (β = 0.19; 95% CI, 0.10-0.31; P = .003). For 36 common serum tests, there was no association with NDD CNVs.

CONCLUSIONS AND RELEVANCE

Clinical features of individuals harboring NDD CNVs were elucidated in a large-scale, multiancestry biobank, identifying enrichments for congenital disorders and major depressive disorder as well as associations with several medical outcomes, including hypertension, kidney failure, and obesity and obesity-related phenotypes, specifically obstructive sleep apnea and increased body mass index. The association between NDD CNVs and obesity outcomes indicate further potential pleiotropy of NDD CNVs beyond neurodevelopmental outcomes previously reported. Future clinical genetic investigations may lead to insights of at-risk individuals and therapeutic strategies targeting specific genetic variants. The importance of diverse inclusion within biobanks and considering the effect of rare genetic variants in a multiancestry context is evident.

Reward Deficiency Syndrome (RDS) Surprisingly Is Evolutionary and Found Everywhere: Is It "Blowin' in the Wind"?

Reward Deficiency Syndrome (RDS) encompasses many mental health disorders, including a wide range of addictions and compulsive and impulsive behaviors. Described as an octopus of behavioral dysfunction, RDS refers to abnormal behavior caused by a breakdown of the cascade of reward in neurotransmission due to genetic and epigenetic influences. The resultant reward neurotransmission deficiencies interfere with the pleasure derived from satisfying powerful human physiological drives. Epigenetic repair may be possible with precision gene-guided therapy using formulations of KB220, a nutraceutical that has demonstrated pro-dopamine regulatory function in animal and human neuroimaging and clinical trials. Recently, large GWAS studies have revealed a significant dopaminergic gene risk polymorphic allele overlap between depressed and schizophrenic cohorts. A large volume of literature has also identified ADHD, PTSD, and spectrum disorders as having the known neurogenetic and psychological underpinnings of RDS. The hypothesis is that the true phenotype is RDS, and behavioral disorders are endophenotypes. Is it logical to wonder if RDS exists everywhere? Although complex, “the answer is blowin’ in the wind,” and rather than intangible, RDS may be foundational in species evolution and survival, with an array of many neurotransmitters and polymorphic loci influencing behavioral functionality.

Cis-regulatory hubs: a new 3D model of complex disease genetics with an application to schizophrenia

Genes and their regulatory elements are organized in neurons within 3D networks which model functional structures and explain schizophrenia genetic etiology.

The 3D conformation of the chromatin creates complex networks of noncoding regulatory regions (distal elements) and promoters impacting gene regulation. Despite the importance of the role of noncoding regions in complex diseases, little is known about their interplay within regulatory hubs and implication in multigenic diseases such as schizophrenia. Here we show that cis-regulatory hubs (CRHs) in neurons highlight functional interactions between distal elements and promoters, providing a model to explain epigenetic mechanisms involved in complex diseases. CRHs represent a new 3D model, where distal elements interact to create a complex network of active genes. In a disease context, CRHs highlighted strong enrichments in schizophrenia-associated genes, schizophrenia-associated SNPs, and schizophrenia heritability compared with equivalent structures. Finally, CRHs exhibit larger proportions of genes differentially expressed in schizophrenia compared with promoter-distal element pairs or TADs. CRHs thus capture causal regulatory processes improving the understanding of complex disease etiology such as schizophrenia. These multiple lines of genetic and statistical evidence support CRHs as 3D models to study dysregulation of gene expression in complex diseases more generally.

Advances in profiling chromatin architecture shed light on the regulatory dynamics underlying brain disorders

Understanding the exquisitely complex nature of the three-dimensional organization of the genome and how it affects gene regulation remains a central question in biology. Recent advances in sequencing- and imaging-based approaches in decoding the three-dimensional chromatin landscape have enabled a systematic characterization of gene regulatory architecture. In this review, we outline how chromatin architecture provides a reference atlas to predict the functional consequences of non-coding variants associated with human traits and disease. High-throughput perturbation assays such as massively parallel reporter assays (MPRA) and CRISPR-based genome engineering in combination with a reference atlas opened an avenue for going beyond observational studies to experimentally validating the regulatory principles of the genome. We conclude by providing a suggested path forward by calling attention to barriers that can be addressed for a more complete understanding of the regulatory landscape of the human brain.

Loop Interrupted: Dysfunctional Chromatin Relations in Neurological Diseases

The majority of genetic variants for psychiatric disorders have been found within non-coding genomic regions. Physical interactions of gene promoters with distant regulatory elements carrying risk alleles may explain how the latter affect gene expression. Recently, whole genome maps of long-range chromosomal contacts from human postmortem brains have been integrated with gene sequence and chromatin accessibility data to decipher disease-specific alterations in chromatin architecture. Cell culture and rodent models provide a causal link between chromatin conformation, long-range chromosomal contacts, gene expression, and disease phenotype. Here, we give an overview of the techniques used to study chromatin contacts and their limitations in brain research. We present evidence for three-dimensional genome changes in physiological brain function and assess how its disturbance contributes to psychiatric disorders. Lastly, we discuss remaining questions and future research directions with a focus on clinical applications.

Three-dimensional genome organization in the central nervous system, implications for neuropsychological disorders

Chromosomes in eukaryotic cell nuclei are highly compacted and finely organized into hierarchical three-dimensional (3D) configuration. In recent years, scientists have gained deeper understandings of 3D genome structures and revealed novel evidence linking 3D genome organization to various important cell events on the molecular level. Most importantly, alteration of 3D genome architecture has emerged as an intriguing higher order mechanism that connects disease-related genetic variants in multiple heterogenous and polygenic neuropsychological disorders, delivering novel insights into the etiology. In this review, we provide a brief overview of the hierarchical structures of 3D genome and two proposed regulatory models, loop extrusion and phase separation. We then focus on recent Hi-C data in the central nervous system and discuss 3D genome alterations during normal brain development and in mature neurons. Most importantly, we make a comprehensive review on current knowledge and discuss the role of 3D genome in multiple neuropsychological disorders, including schizophrenia, repeat expansion disorders, 22q11 deletion syndrome, and others.

Chromatin Profiling Techniques: Exploring the Chromatin Environment and Its Contributions to Complex Traits

The genetic architecture of complex traits is multifactorial. Genome-wide association studies (GWASs) have identified risk loci for complex traits and diseases that are disproportionately located at the non-coding regions of the genome. On the other hand, we have just begun to understand the regulatory roles of the non-coding genome, making it challenging to precisely interpret the functions of non-coding variants associated with complex diseases. Additionally, the epigenome plays an active role in mediating cellular responses to fluctuations of sensory or environmental stimuli. However, it remains unclear how exactly non-coding elements associate with epigenetic modifications to regulate gene expression changes and mediate phenotypic outcomes. Therefore, finer interrogations of the human epigenomic landscape in associating with non-coding variants are warranted. Recently, chromatin-profiling techniques have vastly improved our understanding of the numerous functions mediated by the epigenome and DNA structure. Here, we review various chromatin-profiling techniques, such as assays of chromatin accessibility, nucleosome distribution, histone modifications, and chromatin topology, and discuss their applications in unraveling the brain epigenome and etiology of complex traits at tissue homogenate and single-cell resolution. These techniques have elucidated compositional and structural organizing principles of the chromatin environment. Taken together, we believe that high-resolution epigenomic and DNA structure profiling will be one of the best ways to elucidate how non-coding genetic variations impact complex diseases, ultimately allowing us to pinpoint cell-type targets with therapeutic potential.

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.

Parsing the Functional Impact of Noncoding Genetic Variants in the Brain Epigenome

The heritability of common psychiatric disorders has motivated global efforts to identify risk-associated genetic variants and elucidate molecular pathways connecting DNA sequence to disease-associated brain dysfunction. The overrepresentation of risk variants among gene regulatory loci instead of protein-coding loci, however, poses a unique challenge in discerning which among the many thousands of variants identified contribute functionally to disease etiology. Defined broadly, psychiatric epigenomics seeks to understand the effects of disease-associated genetic variation on functional readouts of chromatin in an effort to prioritize variants in terms of their impact on gene expression in the brain. Here, we provide an overview of epigenomic mapping in the human brain and highlight findings of particular relevance to psychiatric genetics. Computational methods, including convolutional neuronal networks, and other machine learning approaches hold great promise for elucidating the functional impact of both common and rare genetic variants, thereby refining the epigenomic architecture of psychiatric disorders and enabling integrative analyses of regulatory noncoding variants in the context of large population-level genome and phenome databases.

Down Syndrome Is a Metabolic Disease: Altered Insulin Signaling Mediates Peripheral and Brain Dysfunctions

Down syndrome (DS) is the most frequent chromosomal abnormality that causes intellectual disability, resulting from the presence of an extra complete or segment of chromosome 21 (HSA21). In addition, trisomy of HSA21 contributes to altered energy metabolism that appears to be a strong determinant in the development of pathological phenotypes associated with DS. Alterations include, among others, mitochondrial defects, increased oxidative stress levels, impaired glucose, and lipid metabolism, finally resulting in reduced energy production and cellular dysfunctions. These molecular defects seem to account for a high incidence of metabolic disorders, i.e., diabetes and/or obesity, as well as a higher risk of developing Alzheimer’s disease (AD) in DS. A dysregulation of the insulin signaling with reduced downstream pathways represents a common pathophysiological aspect in the development of both peripheral and central alterations leading to diabetes/obesity and AD. This is further strengthened by evidence showing that the molecular mechanisms responsible for such alterations appear to be similar between peripheral organs and brain. Considering that DS subjects are at high risk to develop either peripheral or brain metabolic defects, this review will discuss current knowledge about the link between trisomy of HSA21 and defects of insulin and insulin-related pathways in DS. Drawing the molecular signature underlying these processes in DS is a key challenge to identify novel drug targets and set up new prevention strategies aimed to reduce the impact of metabolic disorders and cognitive decline.

Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective

Genome-wide association studies (GWAS) have been performed for many psychiatric disorders and revealed a complex polygenic architecture linking mental and physical health phenotypes. Psychiatric diagnoses are often heterogeneous, and several layers of trait heterogeneity may contribute to detection of genetic risks per disorder or across multiple disorders. In this review, we discuss these heterogeneities and their consequences on the discovery of risk loci using large-scale genetic data. We primarily highlight the ways in which sex and diagnostic complexity contribute to risk locus discovery in schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorder, posttraumatic stress disorder, major depressive disorder, obsessive-compulsive disorder, Tourette’s syndrome and chronic tic disorder, anxiety disorders, suicidality, feeding and eating disorders, and substance use disorders. Genetic data also have facilitated discovery of clinically relevant subphenotypes also described here. Collectively, GWAS of psychiatric disorders revealed that the understanding of heterogeneity, polygenicity, and pleiotropy is critical to translate genetic findings into treatment strategies.