Profiling gene expression in the human dentate gyrus granule cell layer reveals insights into schizophrenia and its genetic risk

Transcriptomic analysis of the human habenula in schizophrenia

Pathophysiology of many neuropsychiatric disorders, including schizophrenia (SCZD), is linked to habenula (Hb) function. While pharmacotherapies and deep brain stimulation targeting the Hb are emerging as promising therapeutic treatments, little is known about the cell type-specific transcriptomic organization of the human Hb or how it is altered in SCZD. Here we define the molecular neuroanatomy of the human Hb and identify transcriptomic changes in individuals with SCZD compared to neurotypical controls. Utilizing Hb-enriched postmortem human brain tissue, we performed single nucleus RNA-sequencing (snRNA-seq; n=7 neurotypical donors) and identified 17 molecularly defined Hb cell types across 16,437 nuclei, including 3 medial and 7 lateral Hb populations, several of which were conserved between rodents and humans. Single molecule fluorescent in situ hybridization (smFISH; n=3 neurotypical donors) validated snRNA-seq Hb cell types and mapped their spatial locations. Bulk RNA-sequencing and cell type deconvolution in Hb-enriched tissue from 35 individuals with SCZD and 33 neurotypical controls yielded 45 SCZD-associated differentially expressed genes (DEGs, FDR < 0.05), with 32 (71%) unique to Hb-enriched tissue. eQTL analysis identified 717 independent SNP-gene pairs (FDR < 0.05), where either the SNP is a SCZD risk variant (16 pairs) or the gene is a SCZD DEG (7 pairs). eQTL and SCZD risk colocalization analysis identified 16 colocalized genes. These results identify topographically organized cell types with distinct molecular signatures in the human Hb and demonstrate unique genetic changes associated with SCZD, thereby providing novel molecular insights into the role of Hb in neuropsychiatric disorders.

One Sentence Summary

Transcriptomic analysis of the human habenula and identification of molecular changes associated with schizophrenia risk and illness state.

Analysis of gene expression in the postmortem brain of neurotypical Black Americans reveals contributions of genetic ancestry

Ancestral differences in genomic variation affect the regulation of gene expression; however, most gene expression studies have been limited to European ancestry samples or adjusted to identify ancestry-independent associations. Here, we instead examined the impact of genetic ancestry on gene expression and DNA methylation in the postmortem brain tissue of admixed Black American neurotypical individuals to identify ancestry-dependent and ancestry-independent contributions. Ancestry-associated differentially expressed genes (DEGs), transcripts and gene networks, while notably not implicating neurons, are enriched for genes related to the immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinson disease and 30% of heritability for Alzheimer's disease. Ancestry-associated DEGs also show general enrichment for the heritability of diverse immune-related traits but depletion for psychiatric-related traits. We also compared Black and non-Hispanic white Americans, confirming most ancestry-associated DEGs. Our results delineate the extent to which genetic ancestry affects differences in gene expression in the human brain and the implications for brain illness risk.

Single-cell multi-cohort dissection of the schizophrenia transcriptome

The complexity and heterogeneity of schizophrenia have hindered mechanistic elucidation and the development of more effective therapies. Here, we performed single-cell dissection of schizophrenia-associated transcriptomic changes in the human prefrontal cortex across 140 individuals in two independent cohorts. Excitatory neurons were the most affected cell group, with transcriptional changes converging on neurodevelopment and synapse-related molecular pathways. Transcriptional alterations included known genetic risk factors, suggesting convergence of rare and common genomic variants on neuronal population-specific alterations in schizophrenia. Based on the magnitude of schizophrenia-associated transcriptional change, we identified two populations of individuals with schizophrenia marked by expression of specific excitatory and inhibitory neuronal cell states. This single-cell atlas links transcriptomic changes to etiological genetic risk factors, contextualizing established knowledge within the human cortical cytoarchitecture and facilitating mechanistic understanding of schizophrenia pathophysiology and heterogeneity.

Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood

The molecular pathology of stress-related disorders remains elusive. Our brain multiregion, multiomic study of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) included the central nucleus of the amygdala, hippocampal dentate gyrus, and medial prefrontal cortex (mPFC). Genes and exons within the mPFC carried most disease signals replicated across two independent cohorts. Pathways pointed to immune function, neuronal and synaptic regulation, and stress hormones. Multiomic factor and gene network analyses provided the underlying genomic structure. Single nucleus RNA sequencing in dorsolateral PFC revealed dysregulated (stress-related) signals in neuronal and non-neuronal cell types. Analyses of brain-blood intersections in >50,000 UK Biobank participants were conducted along with fine-mapping of the results of PTSD and MDD genome-wide association studies to distinguish risk from disease processes. Our data suggest shared and distinct molecular pathology in both disorders and propose potential therapeutic targets and biomarkers.

Spatiotemporal analysis of gene expression in the human dentate gyrus reveals age-associated changes in cellular maturation and neuroinflammation

The dentate gyrus of the hippocampus is important for many cognitive functions, including learning, memory, and mood. Here, we investigated age-associated changes in transcriptome-wide spatial gene expression in the human dentate gyrus across the lifespan. Genes associated with neurogenesis and the extracellular matrix were enriched in infants, while gene markers of inhibitory neurons and cell proliferation showed increases and decreases in post-infancy, respectively. While we did not find evidence for neural proliferation post-infancy, we did identify molecular signatures supporting protracted maturation of granule cells. We also identified a wide-spread hippocampal aging signature and an age-associated increase in genes related to neuroinflammation. Our findings suggest major changes to the putative neurogenic niche after infancy and identify molecular foci of brain aging in glial and neuropil enriched tissue.

Monozygotic twins discordant for schizophrenia differ in maturation and synaptic transmission

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. To address the question of how and when concordance in monozygotic twins occur, we have obtained fibroblasts from two pairs of schizophrenia discordant twins (one sibling with schizophrenia while the second one is unaffected by schizophrenia) and three pairs of healthy twins (both of the siblings are healthy). We have prepared iPSC models for these 3 groups of patients with schizophrenia, unaffected co-twins, and the healthy twins. When the study started the co-twins were considered healthy and unaffected but both the co-twins were later diagnosed with a depressive disorder. The reprogrammed iPSCs were differentiated into hippocampal neurons to measure the neurophysiological abnormalities in the patients. 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. Importantly, their synaptic activity was not affected. Our measurements that were obtained from schizophrenia patients and their monozygotic twin and compared also to control healthy twins point to hippocampal synaptic deficits as a central mechanism in schizophrenia.

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus

The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial topography, morphology, physiology, and connectivity, highlighting the need for transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus across ten adult neurotypical donors. We defined molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization and transfer learning, we integrated these data to define gene expression patterns within the snRNA-seq data and infer the expression of these patterns in the SRT data. With this approach, we leveraged existing rodent datasets that feature information on circuit connectivity and neural activity induction to make predictions about axonal projection targets and likelihood of ensemble recruitment in spatially-defined cellular populations of the human hippocampus. Finally, we integrated genome-wide association studies with transcriptomic data to identify enrichment of genetic components for neurodevelopmental, neuropsychiatric, and neurodegenerative disorders across cell types, spatial domains, and gene expression patterns of the human hippocampus. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

Central neurocytoma exhibits radial glial cell signatures with FGFR3 hypomethylation and overexpression

We explored the genomic events underlying central neurocytoma (CN), a rare neoplasm of the central nervous system, via multiomics approaches, including whole-exome sequencing, bulk and single-nuclei RNA sequencing, and methylation sequencing. We identified FGFR3 hypomethylation leading to FGFR3 overexpression as a major event in the ontogeny of CN that affects crucial downstream events, such as aberrant PI3K-AKT activity and neuronal development pathways. Furthermore, we found similarities between CN and radial glial cells based on analyses of gene markers and CN tumor cells and postulate that CN tumorigenesis is due to dysregulation of radial glial cell differentiation into neurons. Our data demonstrate the potential role of FGFR3 as one of the leading drivers of tumorigenesis in CN.

Spatial omics: An innovative frontier in aging research

Disentangling the impact of aging on health and disease has become critical as population aging progresses rapidly. Studying aging at the molecular level is complicated by the diverse aging profiles and dynamics. However, the examination of cellular states within aging tissues in situ is hampered by the lack of high-resolution spatial data. Emerging spatial omics technologies facilitate molecular and spatial analysis of tissues, providing direct access to precise information on various functional regions and serving as a favorable tool for unraveling the heterogeneity of aging. In this review, we summarize the recent advances in spatial omics application in multi-organ aging research, which has enhanced the understanding of aging mechanisms from multiple standpoints. We also discuss the main challenges in spatial omics research to date, the opportunities for further developing the technology, and the potential applications of spatial omics in aging and aging-related diseases.

The role of cell adhesion molecule IgSF9b at the inhibitory synapse and psychiatric disease

Understanding perturbations in synaptic function between health and disease states is crucial to the treatment of neuropsychiatric illness. While genome-wide association studies have identified several genetic loci implicated in synaptic dysfunction in disorders such as autism and schizophrenia, many have not been rigorously characterized. Here, we highlight immunoglobulin superfamily member 9b (IgSF9b), a cell adhesion molecule thought to localize exclusively to inhibitory synapses in the brain. While both pre-clinical and clinical studies suggest its association with psychiatric diseases, our understanding of IgSF9b in synaptic maintenance, neural circuits, and behavioral phenotypes remains rudimentary. Moreover, these functions wield undiscovered influences on neurodevelopment. This review evaluates current literature and publicly available gene expression databases to explore the implications of IgSF9b dysfunction in rodents and humans. Through a focused analysis of one high-risk gene locus, we identify areas requiring further investigation and unearth clues related to broader mechanisms contributing to the synaptic etiology of psychiatric disorders.

Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain

Methods integrating genetics with transcriptomic reference panels prioritize risk genes and mechanisms at only a fraction of trait-associated genetic loci, due in part to an overreliance on total gene expression as a molecular outcome measure. This challenge is particularly relevant for the brain, in which extensive splicing generates multiple distinct transcript-isoforms per gene. Due to complex correlation structures, isoform-level modeling from cis-window variants requires methodological innovation. Here we introduce isoTWAS, a multivariate, stepwise framework integrating genetics, isoform-level expression and phenotypic associations. Compared to gene-level methods, isoTWAS improves both isoform and gene expression prediction, yielding more testable genes, and increased power for discovery of trait associations within genome-wide association study loci across 15 neuropsychiatric traits. We illustrate multiple isoTWAS associations undetectable at the gene-level, prioritizing isoforms of AKT3, CUL3 and HSPD1 in schizophrenia and PCLO with multiple disorders. Results highlight the importance of incorporating isoform-level resolution within integrative approaches to increase discovery of trait associations, especially for brain-relevant traits.

Genetic and environmental contributions to ancestry differences in gene expression in the human brain

Ancestral differences in genomic variation are determining factors in gene regulation; however, most gene expression studies have been limited to European ancestry samples or adjusted for ancestry to identify ancestry-independent associations. We instead examined the impact of genetic ancestry on gene expression and DNA methylation (DNAm) in admixed African/Black American neurotypical individuals to untangle effects of genetic and environmental factors. Ancestry-associated differentially expressed genes (DEGs), transcripts, and gene networks, while notably not implicating neurons, are enriched for genes related to immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinson's disease, and 30% of heritability for Alzhemier's disease. Ancestry-associated DEGs also show general enrichment for heritability of diverse immune-related traits but depletion for psychiatric-related traits. The cell-type enrichments and direction of effects vary by brain region. These DEGs are less evolutionarily constrained and are largely explained by genetic variations; roughly 15% are predicted by DNAm variation implicating environmental exposures. We also compared Black and White Americans, confirming most of these ancestry-associated DEGs. Our results highlight how environment and genetic background affect genetic ancestry differences in gene expression in the human brain and affect risk for brain illness.

Human-genome single nucleotide polymorphisms affecting transcription factor binding and their role in pathogenesis

Single nucleotide polymorphisms (SNPs) are the most common type of variation in the human genome. The vast majority of SNPs identified in the human genome do not have any effect on the phenotype; however, some can lead to changes in the function of a gene or the level of its expression. Most SNPs associated with certain traits or pathologies are mapped to regulatory regions of the genome and affect gene expression by changing transcription factor binding sites. In recent decades, substantial effort has been invested in searching for such regulatory SNPs (rSNPs) and understanding the mechanisms by which they lead to phenotypic differences, primarily to individual differences in susceptibility to diseases and in sensitivity to drugs. The development of the NGS (next-generation sequencing) technology has contributed not only to the identification of a huge number of SNPs and to the search for their association (genome-wide association studies, GWASs) with certain diseases or phenotypic manifestations, but also to the development of more productive approaches to their functional annotation. It should be noted that the presence of an association does not allow one to identify a functional, truly disease-associated DNA sequence variant among multiple marker SNPs that are detected due to linkage disequilibrium. Moreover, determination of associations of genetic variants with a disease does not provide information about the functionality of these variants, which is necessary to elucidate the molecular mechanisms of the development of pathology and to design effective methods for its treatment and prevention. In this regard, the functional analysis of SNPs annotated in the GWAS catalog, both at the genome-wide level and at the level of individual SNPs, became especially relevant in recent years. A genome-wide search for potential rSNPs is possible without any prior knowledge of their association with a trait. Thus, mapping expression quantitative trait loci (eQTLs) makes it possible to identify an SNP for which - among transcriptomes of homozygotes and heterozygotes for its various alleles - there are differences in the expression level of certain genes, which can be located at various distances from the SNP. To predict rSNPs, approaches based on searches for allele-specific events in RNA-seq, ChIP-seq, DNase-seq, ATAC-seq, MPRA, and other data are also used. Nonetheless, for a more complete functional annotation of such rSNPs, it is necessary to establish their association with a trait, in particular, with a predisposition to a certain pathology or sensitivity to drugs. Thus, approaches to finding SNPs important for the development of a trait can be categorized into two groups: (1) starting from data on an association of SNPs with a certain trait, (2) starting from the determination of allele-specific changes at the molecular level (in a transcriptome or regulome). Only comprehensive use of strategically different approaches can considerably enrich our knowledge about the role of genetic determinants in the molecular mechanisms of trait formation, including predisposition to multifactorial diseases.

Sex Significantly Impacts the Function of Major Depression-Linked Variants In Vivo

BACKGROUND

Genome-wide association studies have discovered blocks of common variants-likely transcriptional-regulatory-associated with major depressive disorder (MDD), though the functional subset and their biological impacts remain unknown. Likewise, why depression occurs in females more frequently than males is unclear. We therefore tested the hypothesis that risk-associated functional variants interact with sex and produce greater impact in female brains.

METHODS

We developed techniques to directly measure regulatory variant activity and sex interactions using massively parallel reporter assays in the mouse brain in vivo, in a cell type-specific manner, and applied these approaches to measure activity of >1000 variants from >30 MDD loci.

RESULTS

We identified extensive sex-by-allele effects in mature hippocampal neurons, suggesting that sex-differentiated impacts of genetic risk may underlie sex bias in disease. Unbiased informatics approaches indicated that functional MDD variants recurrently disrupt a number of transcription factor binding motifs, including those of sex hormone receptors. We confirmed a role for the latter by performing massively parallel reporter assays in neonatal mice on the day of birth (during a sex-differentiating hormone surge) and hormonally quiescent juveniles.

CONCLUSIONS

Our study provides novel insights into the influence of age, biological sex, and cell type on regulatory variant function and provides a framework for in vivo parallel assays to functionally define interactions between organismal variables such as sex and regulatory variation. Moreover, we experimentally demonstrate that a portion of the sex differences seen in MDD occurrence may be a product of sex-differentiated effects at associated regulatory variants.

Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations

Single-cell transcriptomics are powerful tools to define neuronal cell types based on co-expressed gene clusters. Limited RNA input in these technologies necessarily compromises transcriptome coverage and accuracy of differential expression analysis. We propose that bulk RNA-Seq of neuronal pools defined by spatial position offers an alternative strategy to overcome these technical limitations. We report a laser-capture microdissection (LCM)-Seq method which allows deep transcriptome profiling of fluorescently tagged neuron populations isolated with LCM from histological sections of transgenic mice. Mild formaldehyde fixation of ZsGreen marker protein, LCM sampling of ∼300 pooled neurons, followed by RNA isolation, library preparation and RNA-Seq with methods optimized for nanogram amounts of moderately degraded RNA enabled us to detect ∼15,000 different transcripts in fluorescently labeled cholinergic neuron populations. The LCM-Seq approach showed excellent accuracy in quantitative studies, allowing us to detect 2891 transcripts expressed differentially between the spatially defined and clinically relevant cholinergic neuron populations of the dorsal caudate-putamen and medial septum. In summary, the LCM-Seq method we report in this study is a versatile, sensitive, and accurate bulk sequencing approach to study the transcriptome profile and differential gene expression of fluorescently tagged neuronal populations isolated from transgenic mice with high spatial precision.

Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease

In the past decade, single-cell technologies have proliferated and improved from their technically challenging beginnings to become common laboratory methods capable of determining the expression of thousands of genes in thousands of cells simultaneously. The field has progressed by taking the CNS as a primary research subject - the cellular complexity and multiplicity of neuronal cell types provide fertile ground for the increasing power of single-cell methods. Current single-cell RNA sequencing methods can quantify gene expression with sufficient accuracy to finely resolve even subtle differences between cell types and states, thus providing a great tool for studying the molecular and cellular repertoire of the CNS and its disorders. However, single-cell RNA sequencing requires the dissociation of tissue samples, which means that the interrelationships between cells are lost. Spatial transcriptomic methods bypass tissue dissociation and retain this spatial information, thereby allowing gene expression to be assessed across thousands of cells within the context of tissue structural organization. Here, we discuss how single-cell and spatially resolved transcriptomics have been contributing to unravelling the pathomechanisms underlying brain disorders. We focus on three areas where we feel these new technologies have provided particularly useful insights: selective neuronal vulnerability, neuroimmune dysfunction and cell-type-specific treatment response. We also discuss the limitations and future directions of single-cell and spatial RNA sequencing technologies.

Prioritization of potential causative genes for schizophrenia in placenta

Our earlier work has shown that genomic risk for schizophrenia converges with early life complications in affecting risk for the disorder and sex-biased neurodevelopmental trajectories. Here, we identify specific genes and potential mechanisms that, in placenta, may mediate such outcomes. We performed TWAS in healthy term placentae (N = 147) to derive candidate placental causal genes that we confirmed with SMR; to search for placenta and schizophrenia-specific associations, we performed an analogous analysis in fetal brain (N = 166) and additional placenta TWAS for other disorders/traits. The analyses in the whole sample and stratifying by sex ultimately highlight 139 placenta and schizophrenia-specific risk genes, many being sex-biased; the candidate molecular mechanisms converge on the nutrient-sensing capabilities of placenta and trophoblast invasiveness. These genes also implicate the Coronavirus-pathogenesis pathway and showed increased expression in placentae from a small sample of SARS-CoV-2-positive pregnancies. Investigating placental risk genes for schizophrenia and candidate mechanisms may lead to opportunities for prevention that would not be suggested by study of the brain alone.

Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings

Major depressive disorder (MDD) is a complex and heterogeneous psychiatric syndrome with genetic and environmental influences. In addition to neuroanatomical and circuit-level disturbances, dysregulation of the brain transcriptome is a key phenotypic signature of MDD. Postmortem brain gene expression data are uniquely valuable resources for identifying this signature and key genomic drivers in human depression; however, the scarcity of brain tissue limits our capacity to observe the dynamic transcriptional landscape of MDD. It is therefore crucial to explore and integrate depression and stress transcriptomic data from numerous, complementary perspectives to construct a richer understanding of the pathophysiology of depression. In this review, we discuss multiple approaches for exploring the brain transcriptome reflecting dynamic stages of MDD: predisposition, onset, and illness. We next highlight bioinformatic approaches for hypothesis-free, genome-wide analyses of genomic and transcriptomic data and their integration. Last, we summarize the findings of recent genetic and transcriptomic studies within this conceptual framework.

Consensus molecular environment of schizophrenia risk genes in coexpression networks shifting across age and brain regions

Schizophrenia is a neurodevelopmental brain disorder whose genetic risk is associated with shifting clinical phenomena across the life span. We investigated the convergence of putative schizophrenia risk genes in brain coexpression networks in postmortem human prefrontal cortex (DLPFC), hippocampus, caudate nucleus, and dentate gyrus granule cells, parsed by specific age periods (total N = 833). The results support an early prefrontal involvement in the biology underlying schizophrenia and reveal a dynamic interplay of regions in which age parsing explains more variance in schizophrenia risk compared to lumping all age periods together. Across multiple data sources and publications, we identify 28 genes that are the most consistently found partners in modules enriched for schizophrenia risk genes in DLPFC; twenty-three are previously unidentified associations with schizophrenia. In iPSC-derived neurons, the relationship of these genes with schizophrenia risk genes is maintained. The genetic architecture of schizophrenia is embedded in shifting coexpression patterns across brain regions and time, potentially underwriting its shifting clinical presentation.

The gene expression patterns as surrogate indices of pH in the brain

Hydrogen ion (H⁺) is one of the most potent intrinsic neuromodulators in the brain in terms of concentration. Changes in H⁺ concentration, expressed as pH, are thought to be associated with various biological processes, such as gene expression, in the brain. Accumulating evidence suggests that decreased brain pH is a common feature of several neuropsychiatric disorders, including schizophrenia, bipolar disorder, autism spectrum disorder, and Alzheimer's disease. However, it remains unclear whether gene expression patterns can be used as surrogates for pH changes in the brain. In this study, we performed meta-analyses using publicly available gene expression datasets to profile the expression patterns of pH-associated genes, whose expression levels were correlated with brain pH, in human patients and mouse models of major central nervous system (CNS) diseases, as well as in mouse cell-type datasets. Comprehensive analysis of 281 human datasets from 11 CNS disorders revealed that gene expression associated with decreased pH was over-represented in disorders including schizophrenia, bipolar disorder, autism spectrum disorders, Alzheimer's disease, Huntington's disease, Parkinson's disease, and brain tumors. Expression patterns of pH-associated genes in mouse models of neurodegenerative disease showed a common time course trend toward lower pH over time. Furthermore, cell type analysis identified astrocytes as the cell type with the most acidity-related gene expression, consistent with previous experimental measurements showing a lower intracellular pH in astrocytes than in neurons. These results suggest that the expression pattern of pH-associated genes may be a surrogate for the state- and trait-related changes in pH in brain cells. Altered expression of pH-associated genes may serve as a novel molecular mechanism for a more complete understanding of the transdiagnostic pathophysiology of neuropsychiatric and neurodegenerative disorders.

Application of spatial transcriptome technologies to neurological diseases

Spatial transcriptome technology acquires gene expression profiles while retaining spatial location information, it displays the gene expression properties of cells in situ. Through the investigation of cell heterogeneity, microenvironment, function, and cellular interactions, spatial transcriptome technology can deeply explore the pathogenic mechanisms of cell-type-specific responses and spatial localization in neurological diseases. The present article overviews spatial transcriptome technologies based on microdissection, in situ hybridization, in situ sequencing, in situ capture, and live cell labeling. Each technology is described along with its methods, detection throughput, spatial resolution, benefits, and drawbacks. Furthermore, their applications in neurodegenerative disease, neuropsychiatric illness, stroke and epilepsy are outlined. This information can be used to understand disease mechanisms, pick therapeutic targets, and establish biomarkers.

An optimized method for high-quality RNA extraction from distinctive intrinsic laryngeal muscles in the rat model

Challenges related to high-quality RNA extraction from post-mortem tissue have limited RNA-sequencing (RNA-seq) application in certain skeletal muscle groups, including the intrinsic laryngeal muscles (ILMs). The present study identified critical factors contributing to substandard RNA extraction from the ILMs and established a suitable method that permitted high-throughput analysis. Here, standard techniques for tissue processing were adapted, and an effective means to control confounding effects during specimen preparation was determined. The experimental procedure consistently provided sufficient intact total RNA (N = 68) and RIN ranging between 7.0 and 8.6, which was unprecedented using standard RNA purification protocols. This study confirmed the reproducibility of the workflow through repeated trials at different postnatal time points and across the distinctive ILMs. High-throughput diagnostics from 90 RNA samples indicated no sequencing alignment scores below 70%, validating the extraction strategy. Significant differences between the standard and experimental conditions suggest circumvented challenges and broad applicability to other skeletal muscles. This investigation remains ongoing given the prospect of therapeutic insights to voice, swallowing, and airway disorders. The present methodology supports pioneering global transcriptome investigations in the larynx previously unfounded in literature.

Brain single cell transcriptomic profiles in episodic memory phenotypes associated with temporal lobe epilepsy

Memory dysfunction is prevalent in temporal lobe epilepsy (TLE), but little is known about the underlying molecular etiologies. Single-nucleus RNA sequencing technology was used to examine differences in cellular heterogeneity among left (language-dominant) temporal neocortical tissues from patients with TLE with (n = 4) or without (n = 2) impairment in verbal episodic memory. We observed marked cell heterogeneity between memory phenotypes and identified numerous differentially expressed genes across all brain cell types. The most notable differences were observed in glutamatergic (excitatory) and GABAergic (inhibitory) neurons with an overrepresentation of genes associated with long-term potentiation, long-term depression, and MAPK signaling, processes known to be essential for episodic memory formation.

RNA-seq profiling reveals different pathways between remodeled vessels and myocardium in hypertrophic cardiomyopathy

OBJECTIVE

Coronary microvascular dysfunction (CMD) is a key pathophysiological feature of hypertrophic cardiomyopathy (HCM), contributing to myocardial ischemia and representing a critical determinant of patients' adverse outcome. The molecular mechanisms underlying the morphological and functional changes of CMD are still unknown. Aim of this study was to obtain insights on the molecular pathways associated with microvessel remodeling in HCM.

METHODS

Interventricular septum myectomies from patients with obstructive HCM (n = 20) and donors' hearts (CTRL, discarded for technical reasons, n = 7) were collected. Remodeled intramyocardial arterioles and cardiomyocytes were microdissected by laser capture and next-generation sequencing was used to delineate the transcriptome profile.

RESULTS

We identified 720 exclusive differentially expressed genes (DEGs) in cardiomyocytes and 1315 exclusive DEGs in remodeled arterioles of HCM. Performing gene ontology and pathway enrichment analyses, we identified selectively altered pathways between remodeled arterioles and cardiomyocytes in HCM patients and controls.

CONCLUSIONS

We demonstrate the existence of distinctive pathways between remodeled arterioles and cardiomyocytes in HCM patients and controls at the transcriptome level.

CACNA1C (CaV1.2) and other L-type calcium channels in the pathophysiology and treatment of psychiatric disorders: Advances from functional genomics and pharmacoepidemiology

A role for voltage-gated calcium channels (VGCCs) in psychiatric disorders has long been postulated as part of a broader involvement of intracellular calcium signalling. However, the data were inconclusive and hard to interpret. We review three areas of research that have markedly advanced the field. First, there is now robust genomic evidence that common variants in VGCC subunit genes, notably CACNA1C which encodes the L-type calcium channel (LTCC) Ca_V1.2 subunit, are trans-diagnostically associated with psychiatric disorders including schizophrenia and bipolar disorder. Rare variants in these genes also contribute to the risk. Second, pharmacoepidemiological evidence supports the possibility that calcium channel blockers, which target LTCCs, might have beneficial effects on the onset or course of these disorders. This is especially true for calcium channel blockers that are brain penetrant. Third, long-range sequencing is revealing the repertoire of full-length LTCC transcript isoforms. Many novel and abundant CACNA1C isoforms have been identified in human and mouse brain, including some which are enriched compared to heart or aorta, and predicted to encode channels with differing functional and pharmacological properties. These isoforms may contribute to the molecular mechanisms of genetic association to psychiatric disorders. They may also enable development of therapeutic agents that can preferentially target brain LTCC isoforms and be of potential value for psychiatric indications.

Profiling cell-type specific gene expression in post-mortem human brain samples through laser capture microdissection

The transcriptome of a cell constitutes an essential piece of cellular identity and contributes to the multifaceted complexity and heterogeneity of cell-types within the mammalian brain. Thus, while a wealth of studies have investigated transcriptomic alterations underlying the pathophysiology of diseases of the brain, their use of bulk-tissue homogenates makes it difficult to tease apart whether observed differences are explained by disease state or cellular composition. Cell-type-specific enrichment strategies are, therefore, crucial in the context of gene expression profiling. Laser capture microdissection (LCM) is one such strategy that allows for the capture of specific cell-types, or regions of interest, under microscopic visualization. In this review, we focus on using LCM for cell-type specific gene expression profiling in post-mortem human brain samples. We begin with a discussion of various LCM systems, followed by a walk-through of each step in the LCM to gene expression profiling workflow and a description of some of the limitations associated with LCM. Throughout the review, we highlight important considerations when using LCM with post-mortem human brain samples. Whenever applicable, commercially available kits that have proven successful in the context of LCM with post-mortem human brain samples are described.

Structural and Functional Deviations of the Hippocampus in Schizophrenia and Schizophrenia Animal Models

Schizophrenia is a grave neuropsychiatric disease which frequently onsets between the end of adolescence and the beginning of adulthood. It is characterized by a variety of neuropsychiatric abnormalities which are categorized into positive, negative and cognitive symptoms. Most therapeutical strategies address the positive symptoms by antagonizing D2-dopamine-receptors (DR). However, negative and cognitive symptoms persist and highly impair the life quality of patients due to their disabling effects. Interestingly, hippocampal deviations are a hallmark of schizophrenia and can be observed in early as well as advanced phases of the disease progression. These alterations are commonly accompanied by a rise in neuronal activity. Therefore, hippocampal formation plays an important role in the manifestation of schizophrenia. Furthermore, studies with animal models revealed a link between environmental risk factors and morphological as well as electrophysiological abnormalities in the hippocampus. Here, we review recent findings on structural and functional hippocampal abnormalities in schizophrenic patients and in schizophrenia animal models, and we give an overview on current experimental approaches that especially target the hippocampus. A better understanding of hippocampal aberrations in schizophrenia might clarify their impact on the manifestation and on the outcome of this severe disease.

Schizophrenia Genomics: Convergence on Synaptic Development, Adult Synaptic Plasticity, or Both?

Large-scale genomic studies of schizophrenia have identified hundreds of genetic loci conferring risk to the disorder. This progress offers an important route toward defining the biological basis of the condition and potentially developing new treatments. In this review, we discuss insights from recent genome-wide association study, copy number variant, and exome sequencing analyses of schizophrenia, together with functional genomics data from the pre- and postnatal brain, in relation to synaptic development and function. These data provide strong support for the view that synaptic dysfunction within glutamatergic and GABAergic (gamma-aminobutyric acidergic) neurons of the cerebral cortex, hippocampus, and other limbic structures is a central component of schizophrenia pathophysiology. Implicated genes and functional genomic data suggest that disturbances in synaptic connectivity associated with susceptibility to schizophrenia begin in utero but continue throughout development, with some alleles conferring risk to the disorder through direct effects on synaptic function in adulthood. This model implies that novel interventions for schizophrenia could include broad preventive approaches aimed at enhancing synaptic health during development as well as more targeted treatments aimed at correcting synaptic function in affected adults.

Schizophrenia-associated SAP97 mutations increase glutamatergic synapse strength in the dentate gyrus and impair contextual episodic memory in rats

Mutations in the putative glutamatergic synapse scaffolding protein SAP97 are associated with the development of schizophrenia in humans. However, the role of SAP97 in synaptic regulation is unclear. Here we show that SAP97 is expressed in the dendrites of granule neurons in the dentate gyrus but not in the dendrites of other hippocampal neurons. Schizophrenia-related perturbations of SAP97 did not affect CA1 pyramidal neuron synapse function. Conversely, these perturbations produce dramatic augmentation of glutamatergic neurotransmission in granule neurons that can be attributed to a release of perisynaptic GluA1-containing AMPA receptors into the postsynaptic densities of perforant pathway synapses. Furthermore, inhibiting SAP97 function in the dentate gyrus was sufficient to impair contextual episodic memory. Together, our results identify a cell-type-specific synaptic regulatory mechanism in the dentate gyrus that, when disrupted, impairs contextual information processing in rats.

The effects of SAP97 mutations associated with schizophrenia on synaptic function are unclear. Here, the authors show that schizophrenia-related SAP97 mutations enhance glutamatergic synapse strength in the dentate gyrus, impairing contextual episodic memory in rats.

Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits

While large-scale, genome-wide association studies (GWAS) have identified hundreds of loci associated with brain-related traits, identification of the variants, genes and molecular mechanisms underlying these traits remains challenging. Integration of GWAS with expression quantitative trait loci (eQTLs) and identification of shared genetic architecture have been widely adopted to nominate genes and candidate causal variants. However, this approach is limited by sample size, statistical power and linkage disequilibrium. We developed the multivariate multiple QTL approach and performed a large-scale, multi-ancestry eQTL meta-analysis to increase power and fine-mapping resolution. Analysis of 3,983 RNA-sequenced samples from 2,119 donors, including 474 non-European individuals, yielded an effective sample size of 3,154. Joint statistical fine-mapping of eQTL and GWAS identified 329 variant-trait pairs for 24 brain-related traits driven by 204 unique candidate causal variants for 189 unique genes. This integrative analysis identifies candidate causal variants and elucidates potential regulatory mechanisms for genes underlying schizophrenia, bipolar disorder and Alzheimer's disease.

Neuropsychiatric disorders: An immunological perspective

Neuropsychiatric diseases have traditionally been studied from brain, and mind-centric perspectives. However, mounting epidemiological and clinical evidence shows a strong correlation of neuropsychiatric manifestations with immune system activation, suggesting a likely mechanistic interaction between the immune and nervous systems in mediating neuropsychiatric disease. Indeed, immune mediators such as cytokines, antibodies, and complement proteins have been shown to affect various cellular members of the central nervous system in multitudinous ways, such as by modulating neuronal firing rates, inducing cellular apoptosis, or triggering synaptic pruning. These observations have in turn led to the exciting development of clinical therapies aiming to harness this neuro-immune interaction for the treatment of neuropsychiatric disease and symptoms. Besides the clinic, important theoretical fundamentals can be drawn from the immune system and applied to our understanding of the brain and neuropsychiatric disease. These new frameworks could lead to novel insights in the field and further potentiate the development of future therapies to treat neuropsychiatric disease.

Transcriptomics of the depressed and PTSD brain

Stress is the response of an organism to demands for change, yet excessive or chronic stress contributes to nearly all psychiatric disorders. The advent of high-throughput transcriptomic methods such as single cell RNA sequencing poses new opportunities to understand the neurobiology of stress, yet substantial barriers to understanding stress remain. Stress adaptation is an organismal survival mechanism conserved across all organisms, yet there is an infinity of potential stressful experiences. Unraveling shared and separate transcriptional programs for adapting to stressful experience remains a challenge, despite methodological and analytic advances. Here we review the state of the field focusing on the technologies used to study the transcriptome for the stress neurobiologist, and also attempt to identify central questions about the heterogeneity of stress for those applying transcriptomic approaches. We further explore how postmortem transcriptome studies aided by preclinical animal models are converging on common molecular pathways for adaptation to aversive experience. Finally, we discuss approaches to integrate large genomic datasets with human neuroimaging and other datasets.

webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study

The development of transcriptome-wide association studies (TWAS) has enabled researchers to better identify and interpret causal genes in many diseases. However, there are currently no resources providing a comprehensive listing of gene-disease associations discovered by TWAS from published GWAS summary statistics. TWAS analyses are also difficult to conduct due to the complexity of TWAS software pipelines. To address these issues, we introduce a new resource called webTWAS, which integrates a database of the most comprehensive disease GWAS datasets currently available with credible sets of potential causal genes identified by multiple TWAS software packages. Specifically, a total of 235 064 gene-diseases associations for a wide range of human diseases are prioritized from 1298 high-quality downloadable European GWAS summary statistics. Associations are calculated with seven different statistical models based on three popular and representative TWAS software packages. Users can explore associations at the gene or disease level, and easily search for related studies or diseases using the MeSH disease tree. Since the effects of diseases are highly tissue-specific, webTWAS applies tissue-specific enrichment analysis to identify significant tissues. A user-friendly web server is also available to run custom TWAS analyses on user-provided GWAS summary statistics data. webTWAS is freely available at http://www.webtwas.net.

Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain

Single-cell gene expression technologies are powerful tools to study cell types in the human brain, but efforts have largely focused on cortical brain regions. We therefore created a single-nucleus RNA-sequencing resource of 70,615 high-quality nuclei to generate a molecular taxonomy of cell types across five human brain regions that serve as key nodes of the human brain reward circuitry: nucleus accumbens, amygdala, subgenual anterior cingulate cortex, hippocampus, and dorsolateral prefrontal cortex. We first identified novel subpopulations of interneurons and medium spiny neurons (MSNs) in the nucleus accumbens and further characterized robust GABAergic inhibitory cell populations in the amygdala. Joint analyses across the 107 reported cell classes revealed cell-type substructure and unique patterns of transcriptomic dynamics. We identified discrete subpopulations of D1- and D2-expressing MSNs in the nucleus accumbens to which we mapped cell-type-specific enrichment for genetic risk associated with both psychiatric disease and addiction.

Molecular signatures from multi-omics of autism spectrum disorders and schizophrenia

The genetic and phenotypic heterogeneity of autism spectrum disorder (ASD) impedes the unification of multiple biological hypotheses in an attempt to explain the complex features of ASD, such as impaired social communication, social interaction deficits, and restricted and repetitive patterns of behavior. However, recent psychiatric genetic studies have identified numerous risk genes and chromosome loci (copy number variation: CNV) which enable us to analyze at the single gene level and utilize system-level approaches. In this review, we focus on ASD as a major neurodevelopmental disorder and review recent findings mainly from the bioinformatics of omics studies. Additionally, by comparing these data with other major psychiatric disorders, including schizophrenia (SCZ), we identify unique characteristics of both diseases from multiple enrichment, pathway, and protein-protein interaction networks (PPIs) analyses using susceptible genes found in recent large-scale genetic studies. These unified, systematic approaches highlight unique characteristics of both disorders from multiple aspects and demonstrate how convergent pathways can contribute to an understanding of the complex etiology of such neurodevelopmental and neuropsychiatric disorders.

Induced Pluripotent Stem Cells in Psychiatry: An Overview and Critical Perspective

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.

Genomics at cellular resolution: insights into cognitive disorders and their evolution

High-throughput genomic sequencing approaches have held the promise of understanding and ultimately leading to treatments for cognitive disorders such as autism spectrum disorders, schizophrenia and Alzheimer's disease. Although significant progress has been made into identifying genetic variants associated with these diseases, these studies have also uncovered that these disorders are mostly genetically complex and thus challenging to model in non-human systems. Improvements in such models might benefit from understanding the evolution of the human genome and how such modifications have affected brain development and function. The intersection of genome-wide variant information with cell-type-specific expression and epigenetic information will further assist in resolving the contribution of particular cell types in evolution or disease. For example, the role of non-neuronal cells in brain evolution and cognitive disorders has gone mostly underappreciated until the recent availability of single-cell transcriptomic approaches. In this review, we discuss recent studies that carry out cell-type-specific assessments of gene expression in brain tissue across primates and between healthy and disease populations. The emerging results from these studies are beginning to elucidate how specific cell types in the evolved human brain are contributing to cognitive disorders.

Targeting synaptic plasticity in schizophrenia: insights from genomic studies

Patients with schizophrenia experience cognitive dysfunction and negative symptoms that do not respond to current drug treatments. Historical evidence is consistent with the hypothesis that these deficits are due, at least in part, to altered cortical synaptic plasticity (the ability of synapses to strengthen or weaken their activity), making this an attractive pathway for therapeutic intervention. However, while synaptic transmission and plasticity is well understood in model systems, it has been challenging to identify specific therapeutic targets for schizophrenia. New information is emerging from genomic findings, which converge on synaptic plasticity and provide a new window on the neurobiology of schizophrenia. Translating this information into therapeutic advances will require a multidisciplinary and collaborative approach.

Investigation of genetic loci shared between bipolar disorder and risk-taking propensity: potential implications for pharmacological interventions

Patients with bipolar disorder (BD) often show increased risk-taking propensity, which may contribute to poor clinical outcome. While these two phenotypes are genetically correlated, there is scarce knowledge on the shared genetic determinants. Using GWAS datasets on BD (41,917 BD cases and 371,549 controls) and risk-taking (n = 466,571), we dissected shared genetic determinants using conjunctional false discovery rate (conjFDR) and local genetic covariance analysis. We investigated specificity of identified targets using GWAS datasets on schizophrenia (SCZ) and attention-deficit hyperactivity disorder (ADHD). The putative functional role of identified targets was evaluated using different tools and GTEx v. 8. Target druggability was evaluated using DGIdb and enrichment for drug targets with genome for REPositioning drugs (GREP). Among 102 loci shared between BD and risk-taking, 87% showed the same direction of effect. Sixty-two were specifically shared between risk-taking propensity and BD, while the others were also shared between risk-taking propensity and either SCZ or ADHD. By leveraging pleiotropic enrichment, we reported 15 novel and specific loci associated with BD and 22 with risk-taking. Among cross-disorder genes, CACNA1C (a known target of calcium channel blockers) was significantly associated with risk-taking propensity and both BD and SCZ using conjFDR (p = 0.001 for both) as well as local genetic covariance analysis, and predicted to be differentially expressed in the cerebellar hemisphere in an eQTL-informed gene-based analysis (BD, Z = 7.48, p = 3.8E-14; risk-taking: Z = 4.66, p = 1.6E-06). We reported for the first time shared genetic determinants between BD and risk-taking propensity. Further investigation into calcium channel blockers or development of innovative ligands of calcium channels might form the basis for innovative pharmacotherapy in patients with BD with increased risk-taking propensity.

Review of multi-omics data resources and integrative analysis for human brain disorders

In the last decade, massive omics datasets have been generated for human brain research. It is evolving so fast that a timely update is urgently needed. In this review, we summarize the main multi-omics data resources for the human brains of both healthy controls and neuropsychiatric disorders, including schizophrenia, autism, bipolar disorder, Alzheimer's disease, Parkinson's disease, progressive supranuclear palsy, etc. We also review the recent development of single-cell omics in brain research, such as single-nucleus RNA-seq, single-cell ATAC-seq and spatial transcriptomics. We further investigate the integrative multi-omics analysis methods for both tissue and single-cell data. Finally, we discuss the limitations and future directions of the multi-omics study of human brain disorders.

Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases

The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.

Social Behavior and Ultrasonic Vocalizations in a Genetic Rat Model Haploinsufficient for the Cross-Disorder Risk Gene Cacna1c

The top-ranked cross-disorder risk gene CACNA1C is strongly associated with multiple neuropsychiatric dysfunctions. In a recent series of studies, we applied a genomically informed approach and contributed extensively to the behavioral characterization of a genetic rat model haploinsufficient for the cross-disorder risk gene Cacna1c. Because deficits in processing social signals are associated with reduced social functioning as commonly seen in neuropsychiatric disorders, we focused on socio-affective communication through 22-kHz and 50-kHz ultrasonic vocalizations (USV). Specifically, we applied a reciprocal approach for studying socio-affective communication in sender and receiver by including rough-and-tumble play and playback of 22-kHz and 50-kHz USV. Here, we review the findings obtained in this recent series of studies and link them to the key features of 50-kHz USV emission during rough-and-tumble play and social approach behavior evoked by playback of 22-kHz and 50-kHz USV. We conclude that Cacna1c haploinsufficiency in rats leads to robust deficits in socio-affective communication through 22-kHz and 50-kHz USV and associated alterations in social behavior, such as rough-and-tumble play behavior.

SPEAQeasy: a scalable pipeline for expression analysis and quantification for R/bioconductor-powered RNA-seq analyses

BACKGROUND

RNA sequencing (RNA-seq) is a common and widespread biological assay, and an increasing amount of data is generated with it. In practice, there are a large number of individual steps a researcher must perform before raw RNA-seq reads yield directly valuable information, such as differential gene expression data. Existing software tools are typically specialized, only performing one step-such as alignment of reads to a reference genome-of a larger workflow. The demand for a more comprehensive and reproducible workflow has led to the production of a number of publicly available RNA-seq pipelines. However, we have found that most require computational expertise to set up or share among several users, are not actively maintained, or lack features we have found to be important in our own analyses.

RESULTS

In response to these concerns, we have developed a Scalable Pipeline for Expression Analysis and Quantification (SPEAQeasy), which is easy to install and share, and provides a bridge towards R/Bioconductor downstream analysis solutions. SPEAQeasy is portable across computational frameworks (SGE, SLURM, local, docker integration) and different configuration files are provided ( http://research.libd.org/SPEAQeasy/ ).

CONCLUSIONS

SPEAQeasy is user-friendly and lowers the computational-domain entry barrier for biologists and clinicians to RNA-seq data processing as the main input file is a table with sample names and their corresponding FASTQ files. The goal is to provide a flexible pipeline that is immediately usable by researchers, regardless of their technical background or computing environment.

Human brain region-specific variably methylated regions are enriched for heritability of distinct neuropsychiatric traits

BACKGROUND

DNA methylation dynamics in the brain are associated with normal development and neuropsychiatric disease and differ across functionally distinct brain regions. Previous studies of genome-wide methylation differences among human brain regions focus on limited numbers of individuals and one to two brain regions.

RESULTS

Using GTEx samples, we generate a resource of DNA methylation in purified neuronal nuclei from 8 brain regions as well as lung and thyroid tissues from 12 to 23 donors. We identify differentially methylated regions between brain regions among neuronal nuclei in both CpG (181,146) and non-CpG (264,868) contexts, few of which were unique to a single pairwise comparison. This significantly expands the knowledge of differential methylation across the brain by 10-fold. In addition, we present the first differential methylation analysis among neuronal nuclei from basal ganglia tissues and identify unique CpG differentially methylated regions, many associated with ion transport. We also identify 81,130 regions of variably CpG methylated regions, i.e., variable methylation among individuals in the same brain region, which are enriched in regulatory regions and in CpG differentially methylated regions. Many variably methylated regions are unique to a specific brain region, with only 202 common across all brain regions, as well as lung and thyroid. Variably methylated regions identified in the amygdala, anterior cingulate cortex, and hippocampus are enriched for heritability of schizophrenia.

CONCLUSIONS

These data suggest that epigenetic variation in these particular human brain regions could be associated with the risk for this neuropsychiatric disorder.

Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex. We identified extensive layer-enriched expression signatures and refined associations to previous laminar markers. We overlaid our laminar expression signatures on large-scale single nucleus RNA-sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions in which morphological architecture is not as well defined as cortical laminae. Last, we created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research ( http://research.libd.org/spatialLIBD ).

Massively Parallel Reporter Assays: Defining Functional Psychiatric Genetic Variants Across Biological Contexts

Neuropsychiatric phenotypes have long been known to be influenced by heritable risk factors, directly confirmed by the past decade of genetic studies that have revealed specific genetic variants enriched in disease cohorts. However, the initial hope that a small set of genes would be responsible for a given disorder proved false. The more complex reality is that a given disorder may be influenced by myriad small-effect noncoding variants and/or by rare but severe coding variants, many de novo. Noncoding genomic sequences-for which molecular functions cannot usually be inferred-harbor a large portion of these variants, creating a substantial barrier to understanding higher-order molecular and biological systems of disease. Fortunately, novel genetic technologies-scalable oligonucleotide synthesis, RNA sequencing, and CRISPR (clustered regularly interspaced short palindromic repeats)-have opened novel avenues to experimentally identify biologically significant variants en masse. Massively parallel reporter assays (MPRAs) are an especially versatile technique resulting from such innovations. MPRAs are powerful molecular genetics tools that can be used to screen thousands of untranscribed or untranslated sequences and their variants for functional effects in a single experiment. This approach, though underutilized in psychiatric genetics, has several useful features for the field. We review methods for assaying putatively functional genetic variants and regions, emphasizing MPRAs and the opportunities they hold for dissection of psychiatric polygenicity. We discuss literature applying functional assays in neurogenetics, highlighting strengths, caveats, and design considerations-especially regarding disease-relevant variables (cell type, neurodevelopment, and sex), and we ultimately propose applications of MPRA to both computational and experimental neurogenetics of polygenic disease risk.

Transcriptomic Insight Into the Polygenic Mechanisms Underlying Psychiatric Disorders

Over the past decade, large-scale genetic studies have successfully identified hundreds of genetic variants robustly associated with risk for psychiatric disorders. However, mechanistic insight and clinical translation continue to lag the pace of risk variant identification, hindered by the sheer number of targets and their predominant noncoding localization, as well as pervasive pleiotropy and incomplete penetrance. Successful next steps require identification of "causal" genetic variants and their proximal biological consequences; placing variants within biologically defined functional contexts, reflecting specific molecular pathways, cell types, circuits, and developmental windows; and characterizing the downstream, convergent neurobiological impact of polygenicity within an individual. Here, we discuss opportunities and challenges of high-throughput transcriptomic profiling in the human brain, and how transcriptomic approaches can help pinpoint mechanisms underlying genetic risk for psychiatric disorders at a scale necessary to tackle daunting levels of polygenicity. These include transcriptome-wide association studies for risk gene prioritization through integration of genome-wide association studies with expression quantitative trait loci. We outline transcriptomic results that inform our understanding of the brain-level molecular pathology of psychiatric disorders, including autism spectrum disorder, bipolar disorder, major depressive disorder, and schizophrenia. Finally, we discuss systems-level approaches for integration of distinct genetic, genomic, and phenotypic levels, including combining spatially resolved gene expression and human neuroimaging maps. Results highlight the importance of understanding gene expression (dys)regulation across human brain development as a major contributor to psychiatric disease pathogenesis, from common variants acting as expression quantitative trait loci to rare variants enriched for gene expression regulatory pathways.

Cortical cellular diversity and development in schizophrenia

While a definitive understanding of schizophrenia etiology is far from current reality, an increasing body of evidence implicates perturbations in early development that alter the trajectory of brain maturation in this disorder, leading to abnormal function in early childhood and adulthood. This atypical development likely arises from an interaction of many brain cell types that follow distinct developmental paths. Because both cellular identity and development are governed by the transcriptome and epigenome, two levels of gene regulation that have the potential to reflect both genetic and environmental influences, mapping "omic" changes over development in diverse cells is a fruitful avenue for schizophrenia research. In this review, we provide a survey of human brain cellular composition and development, levels of genomic regulation that determine cellular identity and developmental trajectories, and what is known about how genomic regulation is dysregulated in specific cell types in schizophrenia. We also outline technical challenges and solutions to conducting cell type-specific functional genomic studies in human postmortem brain.