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Background Cannabis remains one of the most widely abused drugs during pregnancy. In utero exposure to its principal psychoactive component, Δ9-tetrahydrocannabinol (THC), can result in long-term neuropsychiatric risk for the progeny. The current study investigated epigenetic signatures underlying these enduring consequences. Methods Rat dams were exposed daily to THC (0.15mg/kg) during pregnancy and adult male offspring were examined for reward and depressive-like behavioral endophenotypes. Using unbiased sequencing approaches, we explored transcriptional and epigenetic profiles in the nucleus accumbens (NAc), a brain area central to reward and emotional processing. An in vitro CRISPRa model coupled with RNA-sequencing was also applied to study specific consequences of epigenetic dysregulation and altered molecular signatures were compared to human major depressive disorder (MDD) transcriptome datasets. Results Prenatal THC-exposure induced increased motivation for food, heightened learned helplessness and anhedonia, and altered stress sensitivity. We identified a robust increase specific to males in the expression of Histone-Lysine N-Methyltransferase 2A (Kmt2a) that targets lysine 4 on histone H3 (H3K4me) in cellular chromatin. Normalizing Kmt2a in the NAc restored the motivational phenotype of prenatally THC-exposed animals. Comparison of RNA and H3K4me3 sequencing datasets from the NAc of rat offspring with the in vitro model of Kmt2a upregulation revealed overlapping, significant disturbances in pathways that mediate synaptic plasticity. Similar epigenetic alterations were detected in human MDD. Conclusions These studies provide direct evidence for the persistent effects of prenatal cannabis exposure on transcriptional and epigenetic deviations in the NAc via Kmt2a dysregulation and associated psychiatric vulnerability.

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.

The cellular complexity of the human brain is established via dynamic changes in gene expression throughout development that is mediated, in part, by the spatiotemporal activity of cis-regulatory elements. We simultaneously profiled gene expression and chromatin accessibility in 45,549 cortical nuclei across 6 broad developmental time-points from fetus to adult. We identified cell-type specific domains in which chromatin accessibility is highly correlated with gene expression. Differentiation pseudotime trajectory analysis indicates that chromatin accessibility at cis-regulatory elements precedes transcription and that dynamic changes in chromatin structure play a critical role in neuronal lineage commitment. In addition, we mapped cell-type and temporally specific genetic loci implicated in neuropsychiatric traits, including schizophrenia and bipolar disorder. Together, our results describe the complex regulation of cell composition at critical stages in lineage determination, serve as a developmental blueprint of the human brain and shed light on the impact of spatiotemporal alterations in gene expression on neuropsychiatric disease.One-Sentence SummarySimultaneous profiling of gene expression and chromatin accessibility in single nuclei from 6 developmental time-points sheds light on cell fate determination in the human cerebral cortex and on the molecular basis of neuropsychiatric disease.

Amyloid deposits in Alzheimer’s disease (AD) are surrounded by large numbers of plaque-associated axonal spheroids (PAAS). PAAS disrupt axonal electrical conduction and neuronal network function, and correlate with AD severity. However, the mechanisms that govern their formation remain unknown. To uncover the molecular architecture of PAAS, we applied proximity labeling proteomics of spheroids in human AD postmortem brains and mice. We then implemented a human iPSC-derived AD model recapitulating PAAS pathology for mechanistic studies. Using this strategy, we uncovered hundreds of previously unknown PAAS-enriched proteins and signaling pathways, including PI3K/AKT/mTOR. Phosphorylated mTOR was highly enriched in PAAS and strongly correlated with disease severity in humans. Importantly, pharmacological mTOR inhibition in iPSC-derived human neurons or AAV-mediated knockdown in mice, led to a marked reduction of PAAS pathology. Altogether, our study provides a novel platform to examine mechanisms of axonal pathology in neurodegeneration and to evaluate the therapeutic potential of novel targets.

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.

Schizophrenia affects approximately 1% of the world population. Genetics, epigenetics, and environmental factors are known to play a role in this psychiatric disorder. While there is a high concordance in monozygotic twins, about half of twin pairs are discordant for schizophrenia. We characterized human-induced pluripotent stem cell (iPSC)-derived hippocampal neurons from two pairs of monozygotic twins that are discordant for a schizophrenia diagnosis. We compared the affected and the non-affected siblings and compared all of them to twin sets where none of the siblings suffered from schizophrenia. We found that the neurons derived from the schizophrenia patients were less arborized, were hypoexcitable with immature spike features, and exhibited a significant reduction in synaptic activity with dysregulation in synapse-related genes. Interestingly, the neurons derived from the co-twin siblings who did not have schizophrenia formed another distinct group that was different from the neurons in the group of the affected twin siblings but also different from the neurons in the group of the control twins. The neurons in the unaffected co-twin group were also less arborized than the neurons from controls but more arborized than those from affected siblings. Some of their spike features were immature (but less immature than neurons derived from the affected siblings). Importantly, their synaptic activity was not affected. Since schizophrenia is a genetically complex disorder, our twin study allows the measurement of neuronal phenotypes with a similar genetic background. The differences between the siblings may arise due to changes that occurred after the split of the egg into twins. Therefore, our study confirms that dysregulation of synaptic pathways, as well as changes in the rate of synaptic events, distinguishes between individuals affected with schizophrenia and unaffected individuals, even in those having a very similar genetic background.

Genetic liability associated with schizophrenia most frequently arises from common genetic variation that confers small individual effects and contributes to phenotypes only when considered in aggregate. These risk variants are typically non-coding and act by genetically regulating the expression of one or more gene targets (eGenes), but the mechanisms by which unlinked eGenes interact to contribute to complex genetic risk remains unclear. Here we apply a pooled CRISPR approach to evaluate in parallel ten schizophrenia eGenes in human glutamatergic neurons. Querying the shared neuronal impacts across eGenes reveals shared downstream transcriptomic impacts (“convergence”) concentrated on pathways of brain development and synaptic signaling. The composition and strength of convergent networks is influenced by both the similarity of eGene functional annotation and the strength of eGene co-expression in human postmortem brain tissue. Convergent networks resolve distinct patterns of eGene up-regulation associated with individual-level risk in the post-mortem dorsolateral prefrontal cortex that are broadly enriched for neuropsychiatric disorder risk genes and may represent molecular subtypes of schizophrenia. Convergent gene targets are druggable as novel points of therapeutic intervention. Overall, convergence suggests a model to explain how non-additive interactions arise between risk genes and may explain cross-disorder pleiotropy of genetic risk for psychiatric disorders.

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.