Chromatin profiling of cortical neurons identifies individual epigenetic signatures in schizophrenia

Cell-type-specific effects of age and sex on human cortical neurons

Altered transcriptional and epigenetic regulation of brain cell types may contribute to cognitive changes with advanced age. Using single-nucleus multi-omic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex from young adult and aged donors, we found widespread age- and sex-related variation in specific neuron types. The proportion of inhibitory SST- and VIP-expressing neurons was reduced in aged donors. Excitatory neurons had more profound age-related changes in their gene expression and DNA methylation than inhibitory cells. Hundreds of genes involved in synaptic activity, including EGR1, were less expressed in aged adults. Genes located in subtelomeric regions increased their expression with age and correlated with reduced telomere length. We further mapped cell-type-specific sex differences in gene expression and X-inactivation escape genes. Multi-omic single-nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.

Antipsychotic-induced epigenomic reorganization in frontal cortex of individuals with schizophrenia

Genome-wide association studies have revealed >270 loci associated with schizophrenia risk, yet these genetic factors do not seem to be sufficient to fully explain the molecular determinants behind this psychiatric condition. Epigenetic marks such as post-translational histone modifications remain largely plastic during development and adulthood, allowing a dynamic impact of environmental factors, including antipsychotic medications, on access to genes and regulatory elements. However, few studies so far have profiled cell-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects, or the effect of antipsychotic treatment on such epigenetic marks. Here, we conducted ChIP-seq analyses focusing on histone marks indicative of active enhancers (H3K27ac) and active promoters (H3K4me3), alongside RNA-seq, using frontal cortex samples from antipsychotic-free (AF) and antipsychotic-treated (AT) individuals with schizophrenia, as well as individually matched controls (n=58). Schizophrenia subjects exhibited thousands of neuronal and non-neuronal epigenetic differences at regions that included several susceptibility genetic loci, such as NRG1, DISC1, and DRD3. By analyzing the AF and AT cohorts separately, we identified schizophrenia-associated alterations in specific transcription factors, their regulatees, and epigenomic and transcriptomic features that were reversed by antipsychotic treatment; as well as those that represented a consequence of antipsychotic medication rather than a hallmark of schizophrenia in postmortem human brain samples. Notably, we also found that the effect of age on epigenomic landscapes was more pronounced in frontal cortex of AT-schizophrenics, as compared to AF-schizophrenics and controls. Together, these data provide important evidence of epigenetic alterations in the frontal cortex of individuals with schizophrenia, and remark for the first time on the impact of age and antipsychotic treatment on chromatin organization.

The 3-hit animal models of schizophrenia: Improving strategy to decipher and treat the disease?

Schizophrenia is a complex disease related to combination and interactions between genetic and environmental factors, with an epigenetic influence. After the development of the first mono-factorial animal models of schizophrenia (1-hit), that reproduced patterns of either positive, negative and/or cognitive symptoms, more complex models combining two factors (2-hit) have been developed to better fit with the multifactorial etiology of the disease. In the two past decades, a new way to design animal models of schizophrenia have emerged by adding a third hit (3-hit). This review aims to discuss the relevance of the risk factors chosen for the tuning of the 3-hit animal models, as well as the validities measurements and their contribution to schizophrenia understanding. We intended to establish a comprehensive overview to help in the choice of factors for the design of multiple-hit animal models of schizophrenia.

Permissive epigenetic regulatory mechanisms at the histone level are enhanced in postmortem dorsolateral prefrontal cortex of individuals with schizophrenia

BACKGROUND

Susceptibility to schizophrenia is determined by interactions between genes and environment, possibly via epigenetic mechanisms. Schizophrenia has been associated with a restrictive epigenome, and histone deacetylase (HDAC) inhibitors have been postulated as coadjuvant agents to potentiate the efficacy of current antipsychotic drugs. We aimed to evaluate global histone posttranslational modifications (HPTMs) and HDAC expression and activity in the dorsolateral prefrontal cortex (DLPFC) of individuals with schizophrenia.

METHODS

We used postmortem DLPFC samples of individuals with schizophrenia and controls matched for sex, age, and postmortem interval. Schizophrenia samples were classified into antipsychotic-treated or antipsychotic-free subgroups according to blood toxicology. Expression of HPTMs and HDAC was quantified by Western blot. HDAC activity was measured with a fluorometric assay.

RESULTS

H3K9ac, H3K27ac, and H3K4me3 were globally enhanced in the DLPFC of individuals with schizophrenia (+24%-42%, p < 0.05). HDAC activity (-17%, p < 0.01) and HDAC4 protein expression (-20%, p < 0.05) were downregulated in individuals with schizophrenia. Analyses of antipsychotic-free and antipsychotic-treated subgroups revealed enhanced H3K4me3 and H3K27ac (+24%-49%, p < 0.05) and reduced HDAC activity in the antipsychotic-treated, but not in the antipsychotic-free subgroup.

LIMITATIONS

Special care was taken to control the effect of confounding factors: age, sex, postmortem interval, and storage time. However, replication studies in bigger cohorts might strengthen the association between permissive HPTMs and schizophrenia.

CONCLUSION

We found global HPTM alterations consistent with an aberrantly permissive epigenome in schizophrenia. Further studies to elucidate the significance of enhanced permissive HPTMs in schizophrenia and its association with the mechanism of action of antipsychotic drugs are encouraged.

Epigenetic Alterations of Brain Non-Neuronal Cells in Major Mental Diseases

The tissue-specific expression and epigenetic dysregulation of many genes in cells derived from the postmortem brains of patients have been reported to provide a fundamental biological framework for major mental diseases such as autism, schizophrenia, bipolar disorder, and major depression. However, until recently, the impact of non-neuronal brain cells, which arises due to cell-type-specific alterations, has not been adequately scrutinized; this is because of the absence of techniques that directly evaluate their functionality. With the emergence of single-cell technologies, such as RNA sequencing (RNA-seq) and other novel techniques, various studies have now started to uncover the cell-type-specific expression and DNA methylation regulation of many genes (e.g., TREM2, MECP2, SLC1A2, TGFB2, NTRK2, S100B, KCNJ10, and HMGB1, and several complement genes such as C1q, C3, C3R, and C4) in the non-neuronal brain cells involved in the pathogenesis of mental diseases. Additionally, several lines of experimental evidence indicate that inflammation and inflammation-induced oxidative stress, as well as many insidious/latent infectious elements including the gut microbiome, alter the expression status and the epigenetic landscapes of brain non-neuronal cells. Here, we present supporting evidence highlighting the importance of the contribution of the brain's non-neuronal cells (in particular, microglia and different types of astrocytes) in the pathogenesis of mental diseases. Furthermore, we also address the potential impacts of the gut microbiome in the dysfunction of enteric and brain glia, as well as astrocytes, which, in turn, may affect neuronal functions in mental disorders. Finally, we present evidence that supports that microbiota transplantations from the affected individuals or mice provoke the corresponding disease-like behavior in the recipient mice, while specific bacterial species may have beneficial effects.

Co-Expression Network Analysis Identifies Molecular Determinants of Loneliness Associated with Neuropsychiatric and Neurodegenerative Diseases

Loneliness and social isolation are detrimental to mental health and may lead to cognitive impairment and neurodegeneration. Although several molecular signatures of loneliness have been identified, the molecular mechanisms by which loneliness impacts the brain remain elusive. Here, we performed a bioinformatics approach to untangle the molecular underpinnings associated with loneliness. Co-expression network analysis identified molecular 'switches' responsible for dramatic transcriptional changes in the nucleus accumbens of individuals with known loneliness. Loneliness-related switch genes were enriched in cell cycle, cancer, TGF-β, FOXO, and PI3K-AKT signaling pathways. Analysis stratified by sex identified switch genes in males with chronic loneliness. Male-specific switch genes were enriched in infection, innate immunity, and cancer-related pathways. Correlation analysis revealed that loneliness-related switch genes significantly overlapped with 82% and 68% of human studies on Alzheimer's (AD) and Parkinson's diseases (PD), respectively, in gene expression databases. Loneliness-related switch genes, BCAM, NECTIN2, NPAS3, RBM38, PELI1, DPP10, and ASGR2, have been identified as genetic risk factors for AD. Likewise, switch genes HLA-DRB5, ALDOA, and GPNMB are known genetic loci in PD. Similarly, loneliness-related switch genes overlapped in 70% and 64% of human studies on major depressive disorder and schizophrenia, respectively. Nine switch genes, HLA-DRB5, ARHGAP15, COL4A1, RBM38, DMD, LGALS3BP, WSCD2, CYTH4, and CNTRL, overlapped with known genetic variants in depression. Seven switch genes, NPAS3, ARHGAP15, LGALS3BP, DPP10, SMYD3, CPXCR1, and HLA-DRB5 were associated with known risk factors for schizophrenia. Collectively, we identified molecular determinants of loneliness and dysregulated pathways in the brain of non-demented adults. The association of switch genes with known risk factors for neuropsychiatric and neurodegenerative diseases provides a molecular explanation for the observed prevalence of these diseases among lonely individuals.

Gene Expression and Epigenetic Regulation in the Prefrontal Cortex of Schizophrenia

Schizophrenia pathogenesis remains challenging to define; however, there is strong evidence that the interaction of genetic and environmental factors causes the disorder. This paper focuses on transcriptional abnormalities in the prefrontal cortex (PFC), a key anatomical structure that determines functional outcomes in schizophrenia. This review summarises genetic and epigenetic data from human studies to understand the etiological and clinical heterogeneity of schizophrenia. Gene expression studies using microarray and sequencing technologies reported the aberrant transcription of numerous genes in the PFC in patients with schizophrenia. Altered gene expression in schizophrenia is related to several biological pathways and networks (synaptic function, neurotransmission, signalling, myelination, immune/inflammatory mechanisms, energy production and response to oxidative stress). Studies investigating mechanisms driving these transcriptional abnormalities focused on alternations in transcription factors, gene promoter elements, DNA methylation, posttranslational histone modifications or posttranscriptional regulation of gene expression mediated by non-coding RNAs.

Whole exome sequencing in dense families suggests genetic pleiotropy amongst Mendelian and complex neuropsychiatric syndromes

Whole Exome Sequencing (WES) studies provide important insights into the genetic architecture of serious mental illness (SMI). Genes that are central to the shared biology of SMIs may be identified by WES in families with multiple affected individuals with diverse SMI (F-SMI). We performed WES in 220 individuals from 75 F-SMI families and 60 unrelated controls. Within pedigree prioritization employed criteria of rarity, functional consequence, and sharing by ≥ 3 affected members. Across the sample, gene and gene-set-wide case-control association analysis was performed with Sequence Kernel Association Test (SKAT). In 14/16 families with ≥ 3 sequenced affected individuals, we identified a total of 78 rare predicted deleterious variants in 78 unique genes shared by ≥ 3 members with SMI. Twenty (25%) genes were implicated in monogenic CNS syndromes in OMIM (OMIM-CNS), a fraction that is a significant overrepresentation (Fisher's Exact test OR = 2.47, p = 0.001). In gene-set SKAT, statistically significant association was noted for OMIM-CNS gene-set (SKAT-p = 0.005) but not the synaptic gene-set (SKAT-p = 0.17). In this WES study in F-SMI, we identify private, rare, protein altering variants in genes previously implicated in Mendelian neuropsychiatric syndromes; suggesting pleiotropic influences in neurodevelopment between complex and Mendelian syndromes.

Differential brain ADRA2A and ADRA2C gene expression and epigenetic regulation in schizophrenia. Effect of antipsychotic drug treatment

Postsynaptic α_2A-adrenoceptor density is enhanced in the dorsolateral prefrontal cortex (DLPFC) of antipsychotic-treated schizophrenia subjects. This alteration might be due to transcriptional activation, and could be regulated by epigenetic mechanisms such as histone posttranslational modifications (PTMs). The aim of this study was to evaluate ADRA2A and ADRA2C gene expression (codifying for α₂-adrenoceptor subtypes), and permissive and repressive histone PTMs at gene promoter regions in the DLPFC of subjects with schizophrenia and matched controls (n = 24 pairs). We studied the effect of antipsychotic (AP) treatment in AP-free (n = 12) and AP-treated (n = 12) subgroups of schizophrenia subjects and in rats acutely and chronically treated with typical and atypical antipsychotics. ADRA2A mRNA expression was selectively upregulated in AP-treated schizophrenia subjects (+93%) whereas ADRA2C mRNA expression was upregulated in all schizophrenia subjects (+53%) regardless of antipsychotic treatment. Acute and chronic clozapine treatment in rats did not alter brain cortex Adra2a mRNA expression but increased Adra2c mRNA expression. Both ADRA2A and ADRA2C promoter regions showed epigenetic modification by histone methylation and acetylation in human DLPFC. The upregulation of ADRA2A expression in AP-treated schizophrenia subjects might be related to observed bivalent chromatin at ADRA2A promoter region in schizophrenia (depicted by increased permissive H3K4me3 and repressive H3K27me3) and could be triggered by the enhanced H4K16ac at ADRA2A promoter. In conclusion, epigenetic predisposition differentially modulated ADRA2A and ADRA2C mRNA expression in DLPFC of schizophrenia subjects.

The Molecular Biology of Susceptibility to Post-Traumatic Stress Disorder: Highlights of Epigenetics and Epigenomics

Exposure to trauma is one of the most important and prevalent risk factors for mental and physical ill-health. Excessive or prolonged stress exposure increases the risk of a wide variety of mental and physical symptoms. However, people differ strikingly in their susceptibility to develop signs and symptoms of mental illness after traumatic stress. Post-traumatic stress disorder (PTSD) is a debilitating disorder affecting approximately 8% of the world’s population during their lifetime, and typically develops after exposure to a traumatic event. Despite that exposure to potentially traumatizing events occurs in a large proportion of the general population, about 80–90% of trauma-exposed individuals do not develop PTSD, suggesting an inter-individual difference in vulnerability to PTSD. While the biological mechanisms underlying this differential susceptibility are unknown, epigenetic changes have been proposed to underlie the relationship between exposure to traumatic stress and the susceptibility to develop PTSD. Epigenetic mechanisms refer to environmentally sensitive modifications to DNA and RNA molecules that regulate gene transcription without altering the genetic sequence itself. In this review, we provide an overview of various molecular biological, biochemical and physiological alterations in PTSD, focusing on changes at the genomic and epigenomic level. Finally, we will discuss how current knowledge may aid us in early detection and improved management of PTSD patients.

Frequent lineage-specific substitution rate changes support an episodic model for protein evolution

Since the inception of the molecular clock model for sequence evolution, the investigation of protein divergence has revolved around the question of a more or less constant change of amino acid sequences, with specific overall rates for each family. Although anomalies in clock-like divergence are well known, the assumption of a constant decay rate for a given protein family is usually taken as the null model for protein evolution. However, systematic tests of this null model at a genome-wide scale have lagged behind, despite the databases’ enormous growth. We focus here on divergence rate comparisons between very closely related lineages since this allows clear orthology assignments by synteny and reliable alignments, which are crucial for determining substitution rate changes. We generated a high-confidence dataset of syntenic orthologs from four ape species, including humans. We find that despite the appearance of an overall clock-like substitution pattern, several hundred protein families show lineage-specific acceleration and deceleration in divergence rates, or combinations of both in different lineages. Hence, our analysis uncovers a rather dynamic history of substitution rate changes, even between these closely related lineages, implying that one should expect that a large fraction of proteins will have had a history of episodic rate changes in deeper phylogenies. Furthermore, each of the lineages has a separate set of particularly fast diverging proteins. The genes with the highest percentage of branch-specific substitutions are ADCYAP1 in the human lineage (9.7%), CALU in chimpanzees (7.1%), SLC39A14 in the internal branch leading to humans and chimpanzees (4.1%), RNF128 in gorillas (9%), and S100Z in gibbons (15.2%). The mutational pattern in ADCYAP1 suggests a biased mutation process, possibly through asymmetric gene conversion effects. We conclude that a null model of constant change can be problematic for predicting the evolutionary trajectories of individual proteins.

Loop Interrupted: Dysfunctional Chromatin Relations in Neurological Diseases

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

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

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

Decreased DNA methylation at promoters and gene-specific neuronal hypermethylation in the prefrontal cortex of patients with bipolar disorder

Bipolar disorder (BD) is a severe mental disorder characterized by repeated mood swings. Although genetic factors are collectively associated with the etiology of BD, the underlying molecular mechanisms, particularly how environmental factors affect the brain, remain largely unknown. We performed promoter-wide DNA methylation analysis of neuronal and nonneuronal nuclei in the prefrontal cortex of patients with BD (N = 34) and controls (N = 35). We found decreased DNA methylation at promoters in both cell types in the BD patients. Gene Ontology (GO) analysis of differentially methylated region (DMR)-associated genes revealed enrichment of molecular motor-related genes in neurons, chemokines in both cell types, and ion channel- and transporter-related genes in nonneurons. Detailed GO analysis further revealed that growth cone- and dendrite-related genes, including NTRK2 and GRIN1, were hypermethylated in neurons of BD patients. To assess the effect of medication, neuroblastoma cells were cultured under therapeutic concentrations of three mood stabilizers. We observed that up to 37.9% of DMRs detected in BD overlapped with mood stabilizer-induced DMRs. Interestingly, mood stabilizer-induced DMRs showed the opposite direction of changes in DMRs, suggesting the therapeutic effects of mood stabilizers. Among the DMRs, 12 overlapped with loci identified in a genome-wide association study (GWAS) of BD. We also found significant enrichment of neuronal DMRs in the loci reported in another GWAS of BD. Finally, we performed qPCR of DNA methylation-related genes and found that DNMT3B was overexpressed in BD. The cell-type-specific DMRs identified in this study will be useful for understanding the pathophysiology of BD.

A novel CERNNE approach for predicting Parkinson's Disease-associated genes and brain regions based on multimodal imaging genetics data

The detection and pathogenic factors analysis of Parkinson's disease (PD) has a practical significance for its diagnosis and treatment. However, the traditional research paradigms are commonly based on single neural imaging data, which is easy to ignore the complementarity between multimodal imaging genetics data. The existing researches also pay little attention to the comprehensive framework of patient detection and pathogenic factors analysis for PD. Based on functional magnetic resonance imaging (fMRI) data and single nucleotide polymorphism (SNP) data, a novel brain disease multimodal data analysis model is proposed in this paper. Firstly, according to the complementarity between the two types of data, the classical correlation analysis method is used to construct the fusion feature of subjects. Secondly, based on the artificial neural network, the fusion feature analysis tool named clustering evolutionary random neural network ensemble (CERNNE) is designed. This method integrates multiple neural networks constructed randomly, and uses clustering evolution strategy to optimize the ensemble learner by adaptive selective integration, selecting the discriminative features for PD analysis and ensuring the generalization performance of the ensemble model. By combining with data fusion scheme, the CERNNE is applied to forming a multi-task analysis framework, recognizing PD patients and predicting PD-associated brain regions and genes. In the multimodal data experiment, the proposed framework shows better classification performance and pathogenic factors predicting ability, which provides a new perspective for the diagnosis of PD.