Search

Genetic studies of schizophrenia (SCZ) reveal a complex polygenic risk architecture comprised of hundreds of risk variants, the majority of which are common in the population at-large and confer only modest increases in disorder risk. Precisely how genetic variants with individually small predicted effects on gene expression combine to yield substantial clinical impacts in aggregate is unclear. Towards this, we previously reported that the combinatorial perturbation of four SCZ risk genes (“eGenes”, whose expression is regulated by common variants) resulted in gene expression changes that were not predicted by individual perturbations, being most non-additive among genes associated with synaptic function and SCZ risk. Now, across fifteen SCZ eGenes, we demonstrate that non-additive effects are greatest within groups of functionally similar eGenes. Individual eGene perturbations reveal common downstream transcriptomic effects (“convergence”), while combinatorial eGene perturbations result in changes that are smaller than predicted by summing individual eGene effects (“sub-additive effects”). Unexpectedly, these convergent and sub-additive downstream transcriptomic effects overlap and constitute a large proportion of the genome-wide polygenic risk score, suggesting that functional redundancy of eGenes may be a major mechanism underlying non-additivity. Single eGene perturbations likewise fail to predict the magnitude or directionality of cellular phenotypes resulting from combinatorial perturbations. Overall, our results indicate that polygenic risk cannot be extrapolated from experiments testing one risk gene at a time and must instead be empirically measured. By unravelling the interactions between complex risk variants, it may be possible to improve the clinical utility of polygenic risk scores through more powerful prediction of symptom onset, clinical trajectory, and treatment response, or to identify novel targets for therapeutic intervention.

Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder characterized by deficits in social interactions and communication. Protein-altering variants in many genes have been shown to contribute to ASD; however, understanding the convergence across many genes remains a challenge. We demonstrate that coexpression patterns from 993 human postmortem brains are significantly correlated with the transcriptional consequences of CRISPR perturbations in human neurons. Across 71 ASD risk genes, there was significant tissue-specific convergence implicating synaptic pathways. Tissue-specific convergence was further demonstrated across schizophrenia and atrial fibrillation risk genes. The degree of ASD convergence was significantly correlated with ASD association from rare variation and differential expression in ASD brains. Positively convergent genes showed intolerance to functional mutations and had shorter coding lengths than known risk genes even after removing association with ASD. These results indicate that convergent coexpression can identify potentially novel genes that are unlikely to be discovered by sequencing studies.

A key challenge in psychiatry research is the development of high-fidelity model systems that can be experimentally manipulated to explore and test pathophysiological mechanisms of illness. In this respect, the emerging capacity to derive neural cells and circuits from human induced pluripotent stem cells (iPSCs) has generated significant excitement. This review aims to provide a critical appraisal of the potential for iPSCs in illuminating pathophysiological mechanisms in the context of other available technical approaches. We discuss the selection of iPSC phenotypes relevant to psychiatry, the information that researchers can draw on to help guide these decisions, and how researchers choose between the use of 2-dimensional cultures and the use of more complex 3-dimensional model systems. We discuss the strengths and limitations of current models and the challenges and opportunities that they present. Finally, we discuss the potential of iPSC-based model systems for clarifying the mechanisms underlying genetic risk for psychiatry and the steps that will be needed to ensure that robust and reliable conclusions can be drawn. We argue that while iPSC-based models are ideally placed to study fundamental processes occurring within and between neural cells, they are often less well suited for case-control studies, given issues relating to statistical power and the challenges in identifying which cellular phenotypes are meaningful at the level of the whole individual. Our aim is to highlight the importance of considering the hypotheses of a given study to guide decisions about which, if any, iPSC-based system is most appropriate to address it.

To characterize the dysregulation of chromatin accessibility in Alzheimer’s disease (AD), we generated 636 ATAC-seq libraries from neuronal and nonneuronal nuclei isolated from the superior temporal gyrus and entorhinal cortex of 153 AD cases and 56 controls. By analyzing a total of ~20 billion read pairs, we expanded the repertoire of known open chromatin regions (OCRs) in the human brain and identified cell-type-specific enhancer–promoter interactions. We show that interindividual variability in OCRs can be leveraged to identify cis-regulatory domains (CRDs) that capture the three-dimensional structure of the genome (3D genome). We identified AD-associated effects on chromatin accessibility, the 3D genome and transcription factor (TF) regulatory networks. For one of the most AD-perturbed TFs, USF2, we validated its regulatory effect on lysosomal genes. Overall, we applied a systematic approach to understanding the role of the 3D genome in AD. We provide all data as an online resource for widespread community-based analysis.

Lack of FMR1 protein results in fragile X syndrome (FXS), which is the most common inherited intellectual disability syndrome and serves as an excellent model disease to study molecular mechanisms resulting in neuropsychiatric comorbidities. We compared the transcriptomes of human neural progenitors (NPCs) generated from patient-derived induced pluripotent stem cells (iPSCs) of three FXS and three control male donors. Altered expression of

Schizophrenia is a highly heritable, polygenic disorder. A growing list of common genetic variants have been associated with schizophrenia; there is a clear need to understand the role of these risk factors in the etiology of disease. The majority of these variants occur in noncoding regions of the genome and are thought to regulate the expression of one or more genes in a cell type–specific fashion. Recent advances in stem cell biology and molecular genetics have resulted in two invaluable advances: hiPSC technology makes possible the generation of donor-specific disease-relevant neural cell types, whereas CRISPR-based techniques can be applied to manipulate individual variants and/or their gene targets. New multiplexed gene manipulation and CRISPR screening techniques show great promise toward dissecting the complex interactions between the myriad disease-associated variants. This review outlines key advances in hiPSC and CRISPR technology, describing their applications and future potential in the field of schizophrenia research.

De novo, heterozygous, loss of function variants were identified in Pou domain, class 4, transcription factor 1 (POU4F1) via whole exome sequencing in four independent probands presenting with ataxia, intention tremor, and hypotonia. POU4F1 is expressed in the developing nervous system, and mice homozygous for null alleles of Pou4f1 exhibit uncoordinated movements with newborns being unable to successfully right themselves to feed. Head magnetic resonance imaging of the four probands was reviewed and multiple abnormalities were noted including significant cerebellar vermian atrophy and hypertrophic olivary degeneration in one proband. Transcriptional activation of the POU4F1 p.Gln306Arg protein was noted to be decreased when compared to wild-type. These findings suggest that heterozygous, loss-of-function variants in POU4F1 are causative of a novel ataxia syndrome. This article is protected by copyright. All rights reserved.

Bipolar disorder (BD) is a neuropsychiatric illness defined by recurrent episodes of mania/hypomania, depression and circadian rhythm abnormalities. Lithium is an effective drug for BD, but 30-40% of patients fail to respond adequately to treatment. Previous work has demonstrated that lithium affects the expression of "clock genes" and that lithium responders (Li-R) can be distinguished from non-responders (Li-NR) by differences in circadian rhythms. However, circadian rhythms have not been evaluated in BD patient neurons from Li-R and Li-NR. We used induced pluripotent stem cells (iPSCs) to culture neuronal precursor cells (NPC) and glutamatergic neurons from BD patients characterized for lithium responsiveness and matched controls. We identified strong circadian rhythms in Per2-luc expression in NPCs and neurons from controls and Li-R, but NPC rhythms in Li-R had a shorter circadian period. Li-NR rhythms were low amplitude and profoundly weakened. In NPCs and neurons, expression of PER2 was higher in both BD groups compared to controls. In neurons, PER2 protein levels were higher in BD than controls, especially in Li-NR samples. In single cells, NPC and neuron rhythms in both BD groups were desynchronized compared to controls. Lithium lengthened period in Li-R and control neurons but failed to alter rhythms in Li-NR. In contrast, temperature entrainment increased amplitude across all groups, and partly restored rhythms in Li-NR neurons. We conclude that neuronal circadian rhythm abnormalities are present in BD and most pronounced in Li-NR. Rhythm deficits in BD may be partly reversible through stimulation of entrainment pathways.

The mechanisms by which genetic risk variants interact with each other, as well as environmental factors, to contribute to complex genetic disorders remain unclear. We describe in detail our recently published approach to resolve distinct additive and synergistic transcriptomic effects after combinatorial manipulation of genetic variants and/or chemical perturbagens. Although first developed for CRISPR-based perturbation studies of isogenic human induced pluripotent stem cell-derived neurons, our methodology can be broadly applied to any RNA sequencing dataset, provided that raw read counts are available. Whereas other differential expression analyses reveal the effect of individual perturbations, here we specifically query interactions between two or more perturbagens, resolving the extent of non-additive (synergistic) interactions between perturbations. We discuss the careful experimental design required to resolve synergistic effects and considerations of statistical power and how to quantify observed synergy between experiments. Additionally, we speculate on potential future applications and explore the obvious limitations of this approach. Overall, by interrogating the effect of independent factors, alone and in combination, our analytic framework and experimental design facilitate the discovery of convergence and synergy downstream of gene and/or treatment perturbations hypothesized to contribute to complex diseases. We think that this protocol can be successfully applied by any scientist with bioinformatic skills and basic proficiency in the R programming language. Our computational pipeline ( https://github.com/nadschro/synergy-analysis ) is straightforward, does not require supercomputing support and can be conducted in a single day upon completion of RNA sequencing experiments.

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 over-representation of risk variants among gene-regulatory 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 (CNNs) 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 non-coding variants in the context of large population-level ‘genome and phenome’ databases.

Most risk variants for brain disorders identified by genome-wide association studies reside in the noncoding genome, which makes deciphering biological mechanisms difficult. A commonly used tool, multimarker analysis of genomic annotation (MAGMA), addresses this issue by aggregating single nucleotide polymorphism associations to nearest genes. Here we developed a platform, Hi-C-coupled MAGMA (H-MAGMA), that advances MAGMA by incorporating chromatin interaction profiles from human brain tissue across two developmental epochs and two brain cell types. By analyzing gene regulatory relationships in the disease-relevant tissue, H-MAGMA identified neurobiologically relevant target genes. We applied H-MAGMA to five psychiatric disorders and four neurodegenerative disorders to interrogate biological pathways, developmental windows and cell types implicated for each disorder. Psychiatric-disorder risk genes tended to be expressed during mid-gestation and in excitatory neurons, whereas neurodegenerative-disorder risk genes showed increasing expression over time and more diverse cell-type specificities. H-MAGMA adds to existing analytic frameworks to help identify the neurobiological principles of brain disorders.

As expanding genetic and genomic studies continue to implicate a growing list of variants contributing risk to neuropsychiatric disease, an important next step is to understand the functional impact and points of convergence of these risk factors. Here, with a focus on schizophrenia, we survey the most recent findings of the rare and common variants underlying genetic risk for schizophrenia. We discuss the ongoing efforts to validate these variants in post-mortem brain tissue, as well as new approaches to combine CRISPR-based genome engineering with patient-specific human induced pluripotent stem cell (hiPSC)-based models, in order to identify putative causal schizophrenia loci that regulate gene expression and cellular function. We consider the current limitations of hiPSC-based approaches as well as the future advances necessary to improve the fidelity of this human model. With the objective of utilizing patient genotype data to improve diagnosis and predict treatment response, the integration of CRISPR-genome engineering and hiPSC-based models represent an important strategy with which to systematically demonstrate the cell-type-specific effects of schizophrenia-associated variants.

Although circular RNAs (circRNAs) are enriched in the mammalian brain, very little is known about their potential involvement in brain function and psychiatric disease. Here, we show that circHomer1a, a neuronal-enriched circRNA abundantly expressed in the frontal cortex, derived from Homer protein homolog 1 (HOMER1), is significantly reduced in both the prefrontal cortex (PFC) and induced pluripotent stem cell-derived neuronal cultures from patients with schizophrenia (SCZ) and bipolar disorder (BD). Moreover, alterations in circHomer1a were positively associated with the age of onset of SCZ in both the dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC). No correlations between the age of onset of SCZ and linear HOMER1 mRNA were observed, whose expression was mostly unaltered in BD and SCZ postmortem brain. Using in vivo circRNA-specific knockdown of circHomer1a in mouse PFC, we show that it modulates the expression of numerous alternative mRNA transcripts from genes involved in synaptic plasticity and psychiatric disease. Intriguingly, in vivo circHomer1a knockdown in mouse OFC resulted in specific deficits in OFC-mediated cognitive flexibility. Lastly, we demonstrate that the neuronal RNA-binding protein HuD binds to circHomer1a and can influence its synaptic expression in the frontal cortex. Collectively, our data uncover a novel psychiatric disease-associated circRNA that regulates synaptic gene expression and cognitive flexibility.

Aberrant migration of GABAergic interneurons during cortical neurodevelopment is implicated in Timothy Syndrome, yet the underlying mechanisms remain elusive. In this issue of Cell Stem Cell, Birey et al. model developing brain circuitry using "assembloids" from patients, characterizing a bimodal mechanism of mechano-chemically driven interneuron migration inefficiencies.

The ‘non-linear’ genome, or the spatial proximity of non-contiguous sequences, emerges as an important regulatory layer for genome organization and function, including transcriptional regulation. Here, we review recent genome-scale chromosome conformation mappings (‘Hi-C’) in developing and adult human and mouse brain. Neural differentiation is associated with widespread remodeling of the chromosomal contact map, reflecting dynamic changes in cell-type-specific gene expression programs, with a massive (estimated 20–50%) net loss of chromosomal contacts that is specific for the neuronal lineage. Hi-C datasets provided an unexpected link between locus-specific abnormal expansion of repeat sequences positioned at the boundaries of self-associating topological chromatin domains and associated with monogenic neurodevelopmental and neurodegenerative disease. Furthermore, integrative analyses of cell-type-specific Hi-C and transcriptomes uncovered an expanded genomic risk space interacting with sequences conferring liability for schizophrenia and other cognitive disease. We predict that spatial genome exploration will deliver radically new insights into the brain’s nucleomes in health and disease.

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.

BackgroundRecent efforts have identified genetic loci that are associated with coronavirus disease 2019 (COVID-19) infection rates and disease outcome severity. Translating these genetic findings into druggable genes and readily available compounds that reduce COVID-19 host susceptibility is a critical next step.MethodsWe integrate COVID-19 genetic susceptibility variants, multi-tissue genetically regulated gene expression (GReX) and perturbargen signatures to identify candidate genes and compounds that reverse the predicted gene expression dysregulation associated with COVID-19 susceptibility. The top candidate gene is validated by testing both its GReX and observed blood transcriptome association with COVID-19 severity, as well as by in vitro perturbation to quantify effects on viral load and molecular pathway dysregulation. We validate the in silico drug repositioning analysis by examining whether the top candidate compounds decrease COVID-19 incidence based on epidemiological evidence.ResultsWe identify IL10RB as the top key regulator of COVID-19 host susceptibility. Predicted GReX up-regulation of IL10RB and higher IL10RB expression in COVID-19 patient blood is associated with worse COVID-19 outcomes. In vitro IL10RB overexpression is associated with increased viral load and activation of immune-related molecular pathways. Azathioprine and retinol are prioritized as candidate compounds to reduce the likelihood of testing positive for COVID-19.ConclusionsWe establish an integrative data-driven approach for gene target prioritization. We identify and validate IL10RB as a suitable molecular target for modulation of COVID-19 host susceptibility. Finally, we provide evidence for a few readily available medications that would warrant further investigation as drug repositioning candidates.

The mechanisms by which common risk variants of small effect interact to contribute to complex genetic disorders remain unclear. Here, we apply a genetic approach, using isogenic human induced pluripotent stem cells (hiPSCs), to evaluate the effects of schizophrenia-associated common variants predicted to function as brain expression quantitative trait loci (SZ-eQTLs). By integrating CRISPR-mediated gene editing, activation and repression technologies to study one putative SZ-eQTL (FURIN rs4702) and four top-ranked SZ-eQTL genes (FURIN, SNAP91, TSNARE1, CLCN3), our platform resolves pre- and post-synaptic neuronal deficits, recapitulates genotype-dependent gene expression differences, and identifies convergence downstream of SZ-eQTL gene perturbations. Our observations highlight the cell-type-specific effects of common variants and demonstrate a synergistic effect between SZ-eQTL genes that converges on synaptic function. We propose that the links between rare and common variants implicated in psychiatric disease risk constitute a potentially generalizable phenomenon occurring more widely in complex genetic disorders.

Significance Unlike all differentiated cells, pluripotent stem cells do not elicit a productive antiviral response when infected by a pathogen. This observation seems at odds with the importance of pluripotent stem cells given their absolute requirement for the development of life. Here we investigate why this antiviral response is not utilized in these unique cells. We find that the factors required to maintain pluripotency are incompatible with those involved in eliciting the canonical interferon-based response to virus infection., Upon virus infection, pluripotent stem cells neither induce nor respond to canonical type I interferons (IFN-I). To better understand this biology, we characterized induced pluripotent stem cells (iPSCs) as well as their differentiated parental or rederived counterparts. We confirmed that only iPSCs failed to respond to viral RNA, IFN-I, or viral infection. This lack of response could be phenocopied in fibroblasts with the expression of a reprogramming factor which repressed the capacity to induce canonical antiviral pathways. To ascertain the consequences of restoring the antiviral response in the context of pluripotency, we engineered a system to engage these defenses in iPSCs. Inducible expression of a recombinant virus-activated transcription factor resulted in the successful reconstitution of antiviral defenses through the direct up-regulation of IFN-I–stimulated genes. Induction of the antiviral signature in iPSCs, even for a short duration, resulted in the dysregulation of genes associated with all three germ layers despite maintaining pluripotency markers. Trilineage differentiation of these same cells showed that engagement of the antiviral defenses compromised ectoderm and endoderm formation and dysregulated the development of mesodermal sublineages. In all, these data suggest that the temporal induction of the antiviral response primes iPSCs away from pluripotency and induces numerous aberrant gene products upon differentiation. Together these results suggest that the IFN-I system and pluripotency may be incompatible with each other and thus explain why stem cells do not utilize the canonical antiviral system.

Identification of risk variants for neuropsychiatric diseases within enhancers underscores the importance of understanding the population-level variation of enhancers in the human brain. Besides regulating tissue- and cell-type-specific transcription of target genes, enhancers themselves can be transcribed. We expanded the catalog of known human brain transcribed enhancers by an order of magnitude by generating and jointly analyzing large-scale cell-type-specific transcriptome and regulome data. Examination of the transcriptome in 1,382 brain samples in two independent cohorts identified robust expression of transcribed enhancers. We explored gene-enhancer coordination and found that enhancer-linked genes are strongly implicated in neuropsychiatric disease. We identified significant expression quantitative trait loci (eQTL) for 25,958 enhancers which mediate 6.8% of schizophrenia heritability, mostly independent from standard gene eQTL. Inclusion of enhancer eQTL in transcriptome-wide association studies enhanced functional interpretation of disease loci. Overall, our study characterizes the enhancer-gene regulome and genetic mechanisms in the human cortex in both healthy and disease states.

Post-traumatic stress disorder (PTSD) results from severe trauma exposure, but the extent to which genetic and epigenetic risk factors impact individual clinical outcomes is unknown. We assessed the impact of genomic differences following glucocorticoid administration by examining the transcriptional profile of human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons and live cultured peripheral blood mononuclear cells from combat veterans with PTSD (n=5) and without PTSD (n=5). This parallel examination in baseline and glucocorticoid-treated conditions resolves cell-type specific and diagnosis-dependent elements of stress response, and permits discrimination of gene expression signals associated with PTSD risk from those induced by stress. Computational analyses revealed neuron-specific glucocorticoid-response expression patterns that were enriched for transcriptomic patterns observed in clinical PTSD samples. PTSD-specific signatures, albeit underpowered, accurately stratify veterans with PTSD relative to combat-exposed controls. Overall, in vitro PTSD and glucocorticoid response signatures in blood and brain cells represent exciting new platforms with which to test the genetic and epigenetic mechanisms underlying PTSD, identify biomarkers of PTSD risk and onset, and conduct drug-screening to identify novel therapeutics to prevent or ameliorate clinical phenotypes.