Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex

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

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

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.

Genetic and Epigenetic Analysis Revealing Variants in the NCAM1-TTC12-ANKK1-DRD2 Cluster Associated Significantly With Nicotine Dependence in Chinese Han Smokers

BACKGROUNDS

Although studies have demonstrated that the NCAM1-TTC12-ANKK1-DRD2 gene cluster plays essential roles in addictions in subjects of European and African origin, study of Chinese Han subjects is limited. Further, the underlying biological mechanisms of detected associations are largely unknown.

METHODS

Sixty-four single-nucleotide polymorphisms (SNPs) in this cluster were analyzed for association with Fagerstrőm Test for Nicotine Dependence score (FTND) and cigarettes per day (CPD) in male Chinese Han smokers (N = 2616). Next-generation bisulfite sequencing was used to discover smoking-associated differentially methylated regions (DMRs). Both cis-eQTL and cis-mQTL analyses were applied to assess the cis-regulatory effects of these risk SNPs.

RESULTS

Association analysis revealed that rs4648317 was significantly associated with FTND and CPD (p = .00018; p = .00072). Moreover, 14 additional SNPs were marginally significantly associated with FTND or CPD (p = .05-.01). Haplotype-based association analysis showed that one haplotype in DRD2, C-T-A-G, formed by rs4245148, rs4581480, rs4648317, and rs11214613, was significantly associated with CPD (p = .0005) and marginally associated with FTND (p = .003). Further, we identified four significant smoking-associated DMRs, three of which are located in the DRD2/ANKK1 region (p = .0012-.00005). Finally, we found five significant CpG-SNP pairs (p = 7.9 × 10-9-6.6 × 10-6) formed by risk SNPs rs4648317, rs11604671, and rs2734849 and three methylation loci.

CONCLUSIONS

We found two missense variants (rs11604671; rs2734849) and an intronic variant (rs4648317) with significant effects on ND and further explored their mechanisms of action through expression and methylation analysis. We found the majority of smoking-related DMRs are located in the ANKK1/DRD2 region, indicating a likely causative relation between non-synonymous SNPs and DMRs.

IMPLICATIONS

This study shows that there exist significant association of variants and haplotypes in ANKK1/DRD2 region with ND in Chinese male smokers. Further, this study also shows that DNA methylation plays an important role in mediating such associations.

Cellular correlates of cortical thinning throughout the lifespan

Cortical thinning occurs throughout the entire life and extends to late-life neurodegeneration, yet the neurobiological substrates are poorly understood. Here, we used a virtual-histology technique and gene expression data from the Allen Human Brain Atlas to compare the regional profiles of longitudinal cortical thinning through life (4004 magnetic resonance images [MRIs]) with those of gene expression for several neuronal and non-neuronal cell types. The results were replicated in three independent datasets. We found that inter-regional profiles of cortical thinning related to expression profiles for marker genes of CA1 pyramidal cells, astrocytes and, microglia during development and in aging. During the two stages of life, the relationships went in opposite directions: greater gene expression related to less thinning in development and vice versa in aging. The association between cortical thinning and cell-specific gene expression was also present in mild cognitive impairment and Alzheimer's Disease. These findings suggest a role of astrocytes and microglia in promoting and supporting neuronal growth and dendritic structures through life that affects cortical thickness during development, aging, and neurodegeneration. Overall, the findings contribute to our understanding of the neurobiology underlying variations in MRI-derived estimates of cortical thinning through life and late-life disease.

Peroxisome proliferator-activated receptor α as a novel therapeutic target for schizophrenia

BACKGROUND

The pathophysiology of schizophrenia, a major psychiatric disorder, remains elusive. In this study, the role of peroxisome proliferator-activated receptor (PPAR)/retinoid X receptor (RXR) families, belonging to the ligand-activated nuclear receptor superfamily, in schizophrenia, was analyzed.

METHODS

The PPAR/RXR family genes were screened by exploiting molecular inversion probe (MIP)-based targeted next-generation sequencing (NGS) using the samples of 1,200 Japanese patients with schizophrenia. The results were compared with the whole-genome sequencing databases of the Japanese cohort (ToMMo) and the gnomAD. To reveal the relationship between PPAR/RXR dysfunction and schizophrenia, Ppara KO mice and fenofibrate (a clinically used PPARα agonist)-administered mice were assessed by performing behavioral, histological, and RNA-seq analyses.

FINDINGS

Our findings indicate that c.209-2delA, His117Gln, Arg141Cys, and Arg226Trp of the PPARA gene are risk variants for schizophrenia. The c.209-2delA variant generated a premature termination codon. The three missense variants significantly decreased the activity of PPARα as a transcription factor in vitro. The Ppara KO mice exhibited schizophrenia-relevant phenotypes, including behavioral deficits and impaired synaptogenesis in the cerebral cortex. Oral administration of fenofibrate alleviated spine pathology induced by phencyclidine, an N-methyl-d-aspartate (NMDA) receptor antagonist. Furthermore, pre-treatment with fenofibrate suppressed the sensitivity of mice to another NMDA receptor antagonist, MK-801. RNA-seq analysis revealed that PPARα regulates the expression of synaptogenesis signaling pathway-related genes.

INTERPRETATION

The findings of this study indicate that the mechanisms underlying schizophrenia pathogenesis involve PPARα-regulated transcriptional machinery and modulation of synapse physiology. Hence, PPARα can serve as a novel therapeutic target for schizophrenia.

Developmental effects of maternal smoking during pregnancy on the human frontal cortex transcriptome

Cigarette smoking during pregnancy is a major public health concern. While there are well-described consequences in early child development, there is very little known about the effects of maternal smoking on human cortical biology during prenatal life. We therefore performed a genome-wide differential gene expression analysis using RNA sequencing (RNA-seq) on prenatal (N = 33; 16 smoking-exposed) as well as adult (N = 207; 57 active smokers) human postmortem prefrontal cortices. Smoking exposure during the prenatal period was directly associated with differential expression of 14 genes; in contrast, during adulthood, despite a much larger sample size, only two genes showed significant differential expression (FDR < 10%). Moreover, 1,315 genes showed significantly different exposure effects between maternal smoking during pregnancy and direct exposure in adulthood (FDR < 10%)-these differences were largely driven by prenatal differences that were enriched for pathways previously implicated in addiction and synaptic function. Furthermore, prenatal and age-dependent differentially expressed genes were enriched for genes implicated in non-syndromic autism spectrum disorder (ASD) and were differentially expressed as a set between patients with ASD and controls in postmortem cortical regions. These results underscore the enhanced sensitivity to the biological effect of smoking exposure in the developing brain and offer insight into how maternal smoking during pregnancy affects gene expression in the prenatal human cortex. They also begin to address the relationship between in utero exposure to smoking and the heightened risks for the subsequent development of neuropsychiatric disorders.

Subacute cannabidiol alters genome-wide DNA methylation in adult mouse hippocampus

Use of cannabidiol (CBD), the most abundant non-psychoactive compound found in cannabis (Cannabis sativa), has recently increased as a result of widespread availability of CBD-containing products. CBD is FDA-approved for the treatment of epilepsy and exhibits anxiolytic, antipsychotic, prosocial, and other behavioral effects in animal studies and clinical trials, however, the underlying mechanisms governing these phenotypes are still being elucidated. The epigenome, particularly DNA methylation, is responsive to environmental input and can govern persistent patterns of gene regulation affecting phenotype across the life course. In order to understand the epigenomic activity of cannabidiol exposure in the adult brain, 12-week-old male wild-type a/a Agouti viable yellow (A^vy ) mice were exposed to either 20 mg/kg CBD or vehicle daily by oral administration for 14 days. Hippocampal tissue was collected and reduced-representation bisulfite sequencing (RRBS) was performed. Analyses revealed 3,323 differentially methylated loci (DMLs) in CBD-exposed animals with a small skew toward global hypomethylation. Genes for cell adhesion and migration, dendritic spine development, and excitatory postsynaptic potential were found to be enriched in a gene ontology term analysis of DML-containing genes, and disease ontology enrichment revealed an overrepresentation of DMLs in gene sets associated with autism spectrum disorder, schizophrenia, and other phenotypes. These results suggest that the epigenome may be a key substrate for CBD's behavioral effects and provides a wealth of gene regulatory information for further study.

Deciphering cell-type specific signal transduction in the brain: Challenges and promises

Signal transduction designates the set of molecular events that take place within a cell upon extracellular stimulation to mediate a functional outcome. Decades after the discovery that dopamine triggers opposing signaling pathways in D1- and D2-expressing medium spiny neurons, it is now clear that there are as many different flavors of signaling pathways in the brain as there are neuron types. One of the biggest challenges in molecular neuroscience is to elucidate cell-type specific signaling, in order to understand neurological diseases with regional vulnerability, but also to identify targets for precision drugs devoid of off-target effects. Here, we make a case for the importance of the study of neuron-type specific molecular characteristics. We then review the technologies that exist to study neurons in their full diversity and highlight their disease-relevant idiosyncrasies.

Molecular mechanisms of psychiatric diseases

For most psychiatric diseases, pathogenetic concepts as well as paradigms underlying neuropsychopharmacologic approaches currently revolve around neurotransmitters such as dopamine, serotonin, and norepinephrine. However, despite the fact that several generations of neurotransmitter-based psychotropics including atypical antipsychotics, selective serotonin reuptake inhibitors, and serotonin-norepinephrine reuptake inhibitors are available, the effectiveness of these medications is limited, and relapse rates in psychiatric diseases are relatively high, indicating potential involvement of other pathogenetic pathways. Indeed, recent high-throughput studies in genetics and molecular biology have shown that pathogenesis of major psychiatric illnesses involves hundreds of genes and numerous pathways via such fundamental processes as DNA methylation, transcription, and splicing. Current review summarizes these and other molecular mechanisms of such psychiatric illnesses as schizophrenia, major depressive disorder, and alcohol use disorder and suggests a conceptual framework for future studies.

The Developmental Chronnecto-Genomics (Dev-CoG) study: A multimodal study on the developing brain

Brain development has largely been studied through unimodal analysis of neuroimaging data, providing independent results for structural and functional data. However, structure clearly impacts function and vice versa, pointing to the need for performing multimodal data collection and analysis to improve our understanding of brain development, and to further inform models of typical and atypical brain development across the lifespan. Ultimately, such models should also incorporate genetic and epigenetic mechanisms underlying brain structure and function, although currently this area is poorly specified. To this end, we are reporting here a multi-site, multi-modal dataset that captures cognitive function, brain structure and function, and genetic and epigenetic measures to better quantify the factors that influence brain development in children originally aged 9-14 years. Data collection for the Developmental Chronnecto-Genomics (Dev-CoG) study (http://devcog.mrn.org/) includes cognitive, emotional, and social performance scales, structural and functional MRI, diffusion MRI, magnetoencephalography (MEG), and saliva collection for DNA analysis of single nucleotide polymorphisms (SNPs) and DNA methylation patterns. Across two sites (The Mind Research Network and the University of Nebraska Medical Center), data from over 200 participants were collected and these children were re-tested annually for at least 3 years. The data collection protocol, sample demographics, and data quality measures for the dataset are presented here. The sample will be made freely available through the collaborative informatics and neuroimaging suite (COINS) database at the conclusion of the study.

Obsessive-compulsive disorder and attention-deficit/hyperactivity disorder: distinct associations with DNA methylation and genetic variation

BACKGROUND

A growing body of research has demonstrated associations between specific neurodevelopmental disorders and variation in DNA methylation (DNAm), implicating this molecular mark as a possible contributor to the molecular etiology of these disorders and/or as a novel disease biomarker. Furthermore, genetic risk variants of neurodevelopmental disorders have been found to be enriched at loci associated with DNAm patterns, referred to as methylation quantitative trait loci (mQTLs).

METHODS

We conducted two epigenome-wide association studies in individuals with attention-deficit/hyperactivity disorder (ADHD) or obsessive-compulsive disorder (OCD) (aged 4-18 years) using DNA extracted from saliva. DNAm data generated on the Illumina Human Methylation 450 K array were used to examine the interaction between genetic variation and DNAm patterns associated with these disorders.

RESULTS

Using linear regression followed by principal component analysis, individuals with the most endorsed symptoms of ADHD or OCD were found to have significantly more distinct DNAm patterns from controls, as compared to all cases. This suggested that the phenotypic heterogeneity of these disorders is reflected in altered DNAm at specific sites. Further investigations of the DNAm sites associated with each disorder revealed that despite little overlap of these DNAm sites across the two disorders, both disorders were significantly enriched for mQTLs within our sample.

CONCLUSIONS

Our DNAm data provide insights into the regulatory changes associated with genetic variation, highlighting their potential utility both in directing GWAS and in elucidating the pathophysiology of neurodevelopmental disorders.

Abnormal Contingent Negative Variation Drifts During Facial Expression Judgment in Schizophrenia Patients

Schizophrenia patients often show impaired facial expression recognition, which leads to difficulties in adaptation to daily life. However, it remains unclear whether the deficit is at the perceptual or higher cognitive level of facial emotion processing. Recent studies have shown that earlier face-evoked event-related potential (ERP) components such as N170 and P100 can effectively distinguish schizophrenia patients from healthy controls; however, findings for later waveforms are ambiguous. To clarify this point, in this study we compared electroencephalographic signals in schizophrenia patients and control subjects during a facial expression judgment task. We found that group effects of the occipital N170 and frontal lobe contingent negative variation (CNV) were both significant. The effect sizes (ESs) of N170 and CNV amplitudes were generally medium or small, whereas that of CNV slope for an upright face was large (>0.8). Moreover, N170 amplitude and CNV slope but not CNV amplitude was correlated with Personal and Social Performance (PSP) Scale score. These results suggest that the slope of CNV drift during facial expression processing has a potential clinical value for schizophrenia.

Epigenetic mechanisms in schizophrenia and other psychotic disorders: a systematic review of empirical human findings

Schizophrenia and other psychotic disorders are highly debilitating psychiatric conditions that lack a clear etiology and exhibit polygenic inheritance underlain by pleiotropic genes. The prevailing explanation points to the interplay between predisposing genes and environmental exposure. Accumulated evidence suggests that epigenetic regulation of the genome may mediate dynamic gene-environment interactions at the molecular level by modulating the expression of psychiatric phenotypes through transcription factors. This systematic review summarizes the current knowledge linking schizophrenia and other psychotic disorders to epigenetics, based on PubMed and Web of Science database searches conducted according to the PRISMA guidelines. Three groups of mechanisms in case-control studies  of human tissue (i.e., postmortem brain and bio-fluids) were considered: DNA methylation, histone modifications, and non-coding miRNAs. From the initial pool of 3,204 records, 152 studies met our inclusion criteria (11,815/11,528, 233/219, and 2,091/1,827 cases/controls for each group, respectively). Many of the findings revealed associations with epigenetic modulations of genes regulating neurotransmission, neurodevelopment, and immune function, as well as differential miRNA expression (e.g., upregulated miR-34a, miR-7, and miR-181b). Overall, actual evidence moderately supports an association between epigenetics and schizophrenia and other psychotic disorders. However, heterogeneous results and cross-tissue extrapolations call for future work. Integrating epigenetics into systems biology may critically enhance research on psychosis and thus our understanding of the disorder. This may have implications for psychiatry in risk stratification, early recognition, diagnostics, precision medicine, and other interventional approaches targeting epigenetic fingerprints.

DNA methylation in Schwann cells and in oligodendrocytes

DNA methylation is one of many epigenetic marks, which directly modifies base residues, usually cytosines, in a multiple-step cycle. It has been linked to the regulation of gene expression and alternative splicing in several cell types, including during cell lineage specification and differentiation processes. DNA methylation changes have also been observed during aging, and aberrant methylation patterns have been reported in several neurological diseases. We here review the role of DNA methylation in Schwann cells and oligodendrocytes, the myelin-forming glia of the peripheral and central nervous systems, respectively. We first address how methylation and demethylation are regulating myelinating cells' differentiation during development and repair. We then mention how DNA methylation dysregulation in diseases and cancers could explain their pathogenesis by directly influencing myelinating cells' proliferation and differentiation capacities.

Genetic origins of suicidality? A synopsis of genes in suicidal behaviours, with regard to evidence diversity, disorder specificity and neurodevelopmental brain transcriptomics

With regard to suicidal behavior (SB) genetics, many novel genes have been implicated over the years, in particular by a variety of hypothesis-free genomic methods (e.g. GWAS and exome sequencing). In addition, many novel SB gene findings appear enigmatic in their biological relevance and have weak statistical support, e.g. lack direct replications. Adding to this is the comorbidity between psychiatric disorders and SB. Here we provide a synopsis of SB genes, by prioritization of 106 (out of ~2500) genes based on their highest level of evidence diversity across mainly five genetic evidence types (candidate/GWAS SNP, CNV, linkage and whole exome sequencing), supplemented by three functional categories. This is a representative set of both old and new SB gene candidates, implicated by all kinds of evidence. Furthermore, we define a subset of 40 SB "specific" genes, which are not found among ~3900 genes implicated in other neuropsychiatric disorders, e.g. Autism spectrum disorders (ASD) or Schizophrenia. Biological research of suicidality contains a major developmental focus, e.g. with regard to the gene-environment interactions and epigenetic effects during childhood. Less is known about early (fetal) development and SB genes. Inspired by huge efforts to understand the role early (fetal) neurodevelopment in e.g. ASD by using brain transcriptomic data, we here also characterize the 106 SB genes. We find interesting spatiotemporal expression differences and similarities between SB specific and non-specific genes during brain neurodevelopment. These aspects are of interest to investigate further, to better understand and counteract the genetic origins suicidality.

Leveraging epigenetics to examine differences in developmental trajectories of social attention: A proof-of-principle study of DNA methylation in infants with older siblings with autism

Preliminary evidence suggests that changes in DNA methylation, a widely studied epigenetic mechanism, contribute to the etiology of Autism Spectrum Disorder (ASD). However, data is primarily derived from post-mortem brain samples or peripheral tissue from adults. Deep-phenotyped longitudinal infant cohorts are essential to understand how epigenetic modifications relate to early developmental trajectories and emergence of ASD symptoms. We present a proof-of-principle study designed to evaluate the potential of prospective epigenetic studies of infant siblings of children with ASD. Illumina genome-wide 450 K DNA methylation data from buccal swabs was generated for 63 male infants at multiple time-points from 8 months to 2 years of age (total N = 107 samples). 11 of those infants received a diagnosis of ASD at 3 years. We conducted a series of analyses to characterize DNA methylation signatures associated with categorical outcome and neurocognitive measures from parent-report questionnaire, eye-tracking and electro-encephalography. Effects observed across the entire genome (epigenome-wide association analyses) suggest that collecting DNA methylation samples within infant-sibling designs allows for the detection of meaningful signals with smaller sample sizes than previously estimated. Mapping networks of co-methylated probes associated with neural correlates of social attention implicated enrichment of pathways involved in brain development. Longitudinal modelling found covariation between phenotypic traits and DNA methylation levels in the proximity of genes previously associated with cognitive development, although larger samples and more complete datasets are needed to obtain generalizable results. In conclusion, assessment of DNA methylation profiles at multiple time-points in infant-sibling designs is a promising avenue to comprehend developmental origins and mechanisms of ASD.

Characterizing the dynamic and functional DNA methylation landscape in the developing human cortex

DNA methylation (DNAm) is a key epigenetic regulator of gene expression across development. The developing prenatal brain is a highly dynamic tissue, but our understanding of key drivers of epigenetic variability across development is limited. We, therefore, assessed genomic methylation at over 39 million sites in the prenatal cortex using whole-genome bisulfite sequencing and found loci and regions in which methylation levels are dynamic across development. We saw that DNAm at these loci was associated with nearby gene expression and enriched for enhancer chromatin states in prenatal brain tissue. Additionally, these loci were enriched for genes associated with neuropsychiatric disorders and genes involved with neurogenesis. We also found autosomal differences in DNAm between the sexes during prenatal development, though these have less clear functional consequences. We lastly confirmed that the dynamic methylation at this critical period is specifically CpG methylation, with generally low levels of CpH methylation. Our findings provide detailed insight into prenatal brain development as well as clues to the pathogenesis of psychiatric traits seen later in life.

Investigation of Schizophrenia with Human Induced Pluripotent Stem Cells

Schizophrenia is a chronic and severe neuropsychiatric condition manifested by cognitive, emotional, affective, perceptual, and behavioral abnormalities. Despite decades of research, the biological substrates driving the signs and symptoms of the disorder remain elusive, thus hampering progress in the development of treatments aimed at disease etiologies. The recent emergence of human induced pluripotent stem cell (hiPSC)-based models has provided the field with a highly innovative approach to generate, study, and manipulate living neural tissue derived from patients, making possible the exploration of fundamental roles of genes and early-life stressors in disease-relevant cell types. Here, we begin with a brief overview of the clinical, epidemiological, and genetic aspects of the condition, with a focus on schizophrenia as a neurodevelopmental disorder. We then highlight relevant technical advancements in hiPSC models and assess novel findings attained using hiPSC-based approaches and their implications for disease biology and treatment innovation. We close with a critical appraisal of the developments necessary for both further expanding knowledge of schizophrenia and the translation of new insights into therapeutic innovations.

Integration analysis of methylation quantitative trait loci and GWAS identify three schizophrenia risk variants

Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with schizophrenia (SCZ). However, prioritizing risk variants and regulatory elements for follow-up functional studies remains a major challenge. Therefore, we performed an integrated analysis to identify variants who affect methylation levels of nearby genes and contribute to the risk of SCZ, and to explore the potential role of these variants in SCZ pathogenesis. First, we used the Summary data-based Mendelian Randomization (SMR) method to integrate GWAS and methylation quantitative trait loci data. Then, the SNP-methylation combinations as associated with SCZ were replicated across multiple samples. Totally, we identified and replicated 14 and one SNP-methylation combinations in blood and brain tissues, respectively, that significantly associated with SCZ. Furthermore, our expression quantitative trait loci analysis, differential methylation analysis, neuroimaging genetics, and cognitive genetics analysis consistently supported the potential roles of these 15 SNPs in the pathogenesis of SCZ. Finally, using the convergent functional genomics method, we prioritized three risk SNPs, including rs3765971 (RERE, P_SMR = 3.87 × 10^-8), rs55742290 (ARL6IP4, P_SMR = 1.50 × 10^-7), and rs7293091 (CENPM, P_SMR = 5.09 × 10^-7), may represent promising risk variants in SCZ. These convergent lines of evidence suggest that three risk variants may be involved in the pathogenesis of SCZ. Further investigation of the roles of these variants in the pathogenesis of SCZ is warranted.

Association of a Reproducible Epigenetic Risk Profile for Schizophrenia With Brain Methylation and Function

IMPORTANCE

Schizophrenia is a severe mental disorder in which epigenetic mechanisms may contribute to illness risk. Epigenetic profiles can be derived from blood cells, but to our knowledge, it is unknown whether these predict established brain alterations associated with schizophrenia.

OBJECTIVE

To identify an epigenetic signature (quantified as polymethylation score [PMS]) of schizophrenia using machine learning applied to genome-wide blood DNA-methylation data; evaluate whether differences in blood-derived PMS are mirrored in data from postmortem brain samples; test whether the PMS is associated with alterations of dorsolateral prefrontal cortex hippocampal (DLPFC-HC) connectivity during working memory in healthy controls (HC); explore the association between interactions between polygenic and epigenetic risk with DLPFC-HC connectivity; and test the specificity of the signature compared with other serious psychiatric disorders.

DESIGN, SETTING, AND PARTICIPANTS

In this case-control study conducted from 2008 to 2018 in sites in Germany, the United Kingdom, the United States, and Australia, blood DNA-methylation data from 2230 whole-blood samples from 6 independent cohorts comprising HC (1238 [55.5%]) and participants with schizophrenia (803 [36.0%]), bipolar disorder (39 [1.7%]), major depressive disorder 35 [1.6%]), and autism (27 [1.2%]), and first-degree relatives of all patient groups (88 [3.9%]) were analyzed. DNA-methylation data were further explored from 244 postmortem DLPFC samples from 136 HC and 108 patients with schizophrenia. Neuroimaging and genome-wide association data were available for 393 HC. The latter data was used to calculate a polygenic risk score (PRS) for schizophrenia. The data were analyzed in 2019.

MAIN OUTCOMES AND MEASURES

The accuracy of schizophrenia control classification based on machine learning using epigenetic data; association of schizophrenia PMS scores with DLPFC-HC connectivity; and association of the interaction between PRS and PMS with DLPFC-HC connectivity.

RESULTS

This study included 7488 participants (4395 men [58.7%]), of whom 3158 (2230 men [70.6%]) received a diagnosis of schizophrenia. The PMS signature was associated with schizophrenia across 3 independent data sets (area under the curve [AUC] from 0.69 to 0.78; P value from 0.049 to 1.24 × 10-7) and data from postmortem DLPFC samples (AUC = 0.63; P = 1.42 × 10-4), but not with major depressive disorder (AUC = 0.51; P = .16), autism (AUC = 0.53; P = .66), or bipolar disorder (AUC = 0.58; P = .21). Pathways contributing most to the classification included synaptic processes. Healthy controls with schizophrenia-like PMS showed significantly altered DLPFC-HC connectivity (validation methylation/magnetic resonance imaging, t < -3.81; P for familywise error, <.04; validation magnetic resonance imaging, t < -3.54; P for familywise error, <.02), mirroring the lack of functional decoupling in schizophrenia. There was no significant association of the interaction between PMS and PRS with DLPFC-HC connectivity (P > .19).

CONCLUSIONS AND RELEVANCE

We identified a reproducible blood DNA-methylation signature specific for schizophrenia that was correlated with altered functional DLPFC-HC coupling during working memory and mapped to methylation differences found in DLPFC postmortem samples. This indicates a possible epigenetic contribution to a schizophrenia intermediate phenotype and suggests that PMS could be of interest to be studied in the context of multimodal biomarkers for disease stratification and treatment personalization.

Cannabinoid receptor CNR1 expression and DNA methylation in human prefrontal cortex, hippocampus and caudate in brain development and schizophrenia

Beyond being one the most widely used psychoactive drugs in the world, cannabis has been identified as an environmental risk factor for psychosis. Though the relationship between cannabis use and psychiatric disorders remains controversial, consistent association between early adolescent cannabis use and the subsequent risk of psychosis suggested adolescence may be a particularly vulnerable period. Previous findings on gene by environment interactions indicated that cannabis use may only increase the risk for psychosis in the subjects who have a specific genetic vulnerability. The type 1 cannabinoid receptor (CB1), encoded by the CNR1 gene, is a key component of the endocannabinoid system. As the primary endocannabinoid receptor in the brain, CB1 is the main molecular target of the endocannabinoid ligand, as well as tetrahydrocannabinol (THC), the principal psychoactive ingredient of cannabis. In this study, we have examined mRNA expression and DNA methylation of CNR1 in human prefrontal cortex (PFC), hippocampus, and caudate samples. The expression of CNR1 is higher in fetal PFC and hippocampus, then drops down dramatically after birth. The lifespan trajectory of CNR1 expression in the DLPFC differentially correlated with age by allelic variation at rs4680, a functional polymorphism in the COMT gene. Compared with COMT methionine¹⁵⁸ carriers, Caucasian carriers of the COMT valine¹⁵⁸ allele have a stronger negative correlation between the expression of CNR1 in DLPFC and age. In contrast, the methylation level of cg02498983, which is negatively correlated with the expression of CNR1 in PFC, showed the strongest positive correlation with age in PFC of Caucasian carriers of COMT valine¹⁵⁸. Additionally, we have observed decreased mRNA expression of CNR1 in the DLPFC of patients with schizophrenia. Further analysis revealed a positive eQTL SNP, rs806368, which predicted the expression of a novel transcript of CNR1 in human DLPFC, hippocampus and caudate. This SNP has been associated with addiction and other psychiatric disorders. THC or ethanol are each significantly associated with dysregulated expression of CNR1 in the PFC of patients with affective disorder, and the expression of CNR1 is significantly upregulated in the PFC of schizophrenia patients who completed suicide. Our results support previous studies that have implicated the endocannabinoid system in the pathology of schizophrenia and provided additional insight into the mechanism of increasing risk for schizophrenia in the adolescent cannabis users.

Pancan-meQTL: a database to systematically evaluate the effects of genetic variants on methylation in human cancer

DNA methylation is an important epigenetic mechanism for regulating gene expression. Aberrant DNA methylation has been observed in various human diseases, including cancer. Single-nucleotide polymorphisms can contribute to tumor initiation, progression and prognosis by influencing DNA methylation, and DNA methylation quantitative trait loci (meQTL) have been identified in physiological and pathological contexts. However, no database has been developed to systematically analyze meQTLs across multiple cancer types. Here, we present Pancan-meQTL, a database to comprehensively provide meQTLs across 23 cancer types from The Cancer Genome Atlas by integrating genome-wide genotype and DNA methylation data. In total, we identified 8 028 964 cis-meQTLs and 965 050 trans-meQTLs. Among these, 23 432 meQTLs are associated with patient overall survival times. Furthermore, we identified 2 214 458 meQTLs that overlap with known loci identified through genome-wide association studies. Pancan-meQTL provides a user-friendly web interface (http://bioinfo.life.hust.edu.cn/Pancan-meQTL/) that is convenient for browsing, searching and downloading data of interest. This database is a valuable resource for investigating the roles of genetics and epigenetics in cancer.

Biochemical characteristics of the chondrocyte-enriched SNORC protein and its transcriptional regulation by SOX9

Snorc (Small NOvel Rich in Cartilage) has been identified as a chondrocyte-specific gene in the mouse. Yet little is known about the SNORC protein biochemical properties, and mechanistically how the gene is regulated transcriptionally in a tissue-specific manner. The goals of the present study were to shed light on those important aspects. The chondrocyte nature of Snorc expression was confirmed in mouse and rat tissues, in differentiated (day 7) ATDC5, and in RCS cells where it was constitutive. Topological mapping and biochemical analysis brought experimental evidences that SNORC is a type I protein carrying a chondroitin sulfate (CS) attached to serine 44. The anomalous migration of SNORC on SDS-PAGE was due to its primary polypeptide features, suggesting no additional post-translational modifications apart from the CS glycosaminoglycan. A highly conserved SOX9-binding enhancer located in intron 1 was necessary to drive transcription of Snorc in the mouse, rat, and human. The enhancer was active independently of orientation and whether located in a heterologous promoter or intron. Crispr-mediated inactivation of the enhancer in RCS cells caused reduction of Snorc. Transgenic mice carrying the intronic multimerized enhancer drove high expression of a βGeo reporter in chondrocytes, but not in the hypertrophic zone. Altogether these data confirmed the chondrocyte-specific nature of Snorc and revealed dependency on the intronic enhancer binding of SOX9 for transcription.

decorate: differential epigenetic correlation test

MOTIVATION

Identifying correlated epigenetic features and finding differences in correlation between individuals with disease compared to controls can give novel insight into disease biology. This framework has been successful in analysis of gene expression data, but application to epigenetic data has been limited by the computational cost, lack of scalable software and lack of robust statistical tests.

RESULTS

Decorate, differential epigenetic correlation test, identifies correlated epigenetic features and finds clusters of features that are differentially correlated between two or more subsets of the data. The software scales to genome-wide datasets of epigenetic assays on hundreds of individuals. We apply decorate to four large-scale datasets of DNA methylation, ATAC-seq and histone modification ChIP-seq.

AVAILABILITY AND IMPLEMENTATION

decorate R package is available from https://github.com/GabrielHoffman/decorate.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Epigenetic pacemaker: closed form algebraic solutions

Background

DNA methylation is widely used as a biomarker in crucial medical applications as well as for human age prediction of very high accuracy. This biomarker is based on the methylation status of several hundred CpG sites. In a recent line of publications we have adapted a versatile concept from evolutionary biology - the Universal Pacemaker (UPM) - to the setting of epigenetic aging and denoted it the Epigenetic PaceMaker (EPM). The EPM, as opposed to other epigenetic clocks, is not confined to specific pattern of aging, and the epigenetic age of the individual is inferred independently of other individuals. This allows an explicit modeling of aging trends, in particular non linear relationship between chronological and epigenetic age. In one of these recent works, we have presented an algorithmic improvement based on a two-step conditional expectation maximization (CEM) algorithm to arrive at a critical point on the likelihood surface. The algorithm alternates between a time step and a site step while advancing on the likelihood surface.

Results

Here we introduce non trivial improvements to these steps that are essential for analyzing data sets of realistic magnitude in a manageable time and space. These structural improvements are based on insights from linear algebra and symbolic algebra tools, providing us greater understanding of the degeneracy of the complex problem space. This understanding in turn, leads to the complete elimination of the bottleneck of cumbersome matrix multiplication and inversion, yielding a fast closed form solution in both steps of the CEM.In the experimental results part, we compare the CEM algorithm over several data sets and demonstrate the speedup obtained by the closed form solutions. Our results support the theoretical analysis of this improvement.

Conclusions

These improvements enable us to increase substantially the scale of inputs analyzed by the method, allowing us to apply the new approach to data sets that could not be analyzed before.

High polygenic burden is associated with blood DNA methylation changes in individuals with suicidal behavior

Suicidal behavior is result of the interaction of several contributors, including genetic and environmental factors. The integration of approaches considering the polygenic component of suicidal behavior, such as polygenic risk scores (PRS) and DNA methylation is promising for improving our understanding of the complex interplay between genetic and environmental factors in this behavior. The aim of this study was the evaluation of DNA methylation differences between individuals with high and low genetic burden for suicidality. The present study was divided into two phases. In the first phase, genotyping with the Psycharray chip was performed in a discovery sample of 568 Mexican individuals, of which 149 had suicidal behavior (64 individuals with suicidal ideation, 50 with suicide attempt and 35 with completed suicide). Then, a PRS analysis based on summary statistics from the Psychiatric Genomic Consortium was performed in the discovery sample. In a second phase, we evaluated DNA methylation differences between individuals with high and low genetic burden for suicidality in a sub-sample of the discovery sample (target sample) of 94 subjects. We identified 153 differentially methylated sites between individuals with low and high-PRS. Among genes mapped to differentially methylated sites, we found genes involved in neurodevelopment (CHD7, RFX4, KCNA1, PLCB1, PITX1, NUMBL) and ATP binding (KIF7, NUBP2, KIF6, ATP8B1, ATP11A, CLCN7, MYLK, MAP2K5). Our results suggest that genetic variants might increase the predisposition to epigenetic variations in genes involved in neurodevelopment. This study highlights the possible implication of polygenic burden in the alteration of epigenetic changes in suicidal behavior.

Schizophrenia risk variants influence multiple classes of transcripts of sorting nexin 19 (SNX19)

Genome-wide association studies (GWAS) have identified many genomic loci associated with risk for schizophrenia, but unambiguous identification of the relationship between disease-associated variants and specific genes, and in particular their effect on risk conferring transcripts, has proven difficult. To better understand the specific molecular mechanism(s) at the schizophrenia locus in 11q25, we undertook cis expression quantitative trait loci (cis-eQTL) mapping for this 2 megabase genomic region using postmortem human brain samples. To comprehensively assess the effects of genetic risk upon local expression, we evaluated multiple transcript features: genes, exons, and exon-exon junctions in multiple brain regions-dorsolateral prefrontal cortex (DLPFC), hippocampus, and caudate. Genetic risk variants strongly associated with expression of SNX19 transcript features that tag multiple rare classes of SNX19 transcripts, whereas they only weakly affected expression of an exon-exon junction that tags the majority of abundant transcripts. The most prominent class of SNX19 risk-associated transcripts is predicted to be overexpressed, defined by an exon-exon splice junction between exons 8 and 10 (junc8.10) and that is predicted to encode proteins that lack the characteristic nexin C terminal domain. Risk alleles were also associated with either increased or decreased expression of multiple additional classes of transcripts. With RACE, molecular cloning, and long read sequencing, we found a number of novel SNX19 transcripts that further define the set of potential etiological transcripts. We explored epigenetic regulation of SNX19 expression and found that DNA methylation at CpG sites near the primary transcription start site and within exon 2 partially mediate the effects of risk variants on risk-associated expression. ATAC sequencing revealed that some of the most strongly risk-associated SNPs are located within a region of open chromatin, suggesting a nearby regulatory element is involved. These findings indicate a potentially complex molecular etiology, in which risk alleles for schizophrenia generate epigenetic alterations and dysregulation of multiple classes of SNX19 transcripts.

Integrating genome-wide association study and expression quantitative trait loci data identifies NEGR1 as a causal risk gene of major depression disorder

BACKGROUND

Genome-wide association studies (GWAS) have identified several genetic variants associated with major depression disorder (MDD). However, pinpointing the causal variants which are responsible for the association signal at a risk locus remains a major challenge.

METHODS

We used Summary data-based Mendelian Randomization (SMR) with Psychiatric Genomics Consortium (PGC) GWAS summary and brain expression quantitative trait loci (eQTL) data to identify genes whose expression levels are causally associated with MDD. Then we performed differential expression analysis, methylation quantitative trait loci analysis, and cognitive genetics analysis to investigate the potential roles of risk genes in the pathogenesis of MDD.

RESULTS

Through SMR integrative analysis, we identified the SNP rs10789336 located in Neuronal growth regulator 1 (NEGR1) gene significantly affected the expression level of RPL31P12 in brain tissues and contributed to the risk of MDD (P = 1.96 × 10^-6). Consistently, the SNP rs10789336 was associated with the methylation levels of three nearby DNA methylation sites, including cg09256413 (NEGR1, P=1.72 × 10^-10), cg11418303 (prostaglandin E receptor 3 [PTGER3], P = 4.78 × 10^-6), and cg23032215 (ZRANB2 antisense RNA 2 [ZRANB2-AS2], P = 1.23 × 10^-4). Differential expression analysis suggested that the NEGR1 gene was upregulated in prefrontal cortex (P = 5.14 × 10^-3). Cognitive genetics analysis showed that the SNP rs10789336 was associated with cognitive performance (P = 2.41 × 10^-16), educational attainment (P = 1.75 × 10^-14), general cognitive function (P = 2.65 × 10^-12), and verbal numerical reasoning (P = 1.36 × 10^-12).

CONCLUSION

Collectively, our results revealed that the SNP rs10789336 in NEGR1 might confer risk to MDD. Further investigation of the roles of NEGR1 in the pathogenesis of MDD is warranted.

Profiling haplotype specific CpG and CpH methylation within a schizophrenia GWAS locus on chromosome 14 in schizophrenia and healthy subjects

Interrogating DNA methylation within schizophrenia risk loci holds promise to identify mechanisms by which genes influence the disease. Based on the hypothesis that allele specific methylation (ASM) of a single CpG, or perhaps CpH, might mediate or mark the effects of genetic variants on disease risk and phenotypes, we explored haplotype specific methylation levels of individual cytosines within a genomic region harbouring the BAG5, APOPT1 and KLC1 genes in peripheral blood of schizophrenia patients and healthy controls. Three DNA fragments located in promoter, intronic and intergenic areas were studied by single-molecule real-time bisulfite sequencing enabling the analysis of long reads of DNA with base-pair resolution and the determination of haplotypes directly from sequencing data. Among 1,012 cytosines studied, we did not find any site where methylation correlated with the disease or cognitive deficits after correction for multiple testing. At the same time, we determined the methylation profile associated with the schizophrenia risk haplotype within the KLC1 fourth intron and confirmed ASM for cytosines located in the vicinity of rs67899457. These genetically associated DNA methylation variations may be related to the pathophysiological mechanism differentiating the risk and non-risk haplotypes and merit further investigation.

Analysis of DNA methylation associates the cystine-glutamate antiporter SLC7A11 with risk of Parkinson's disease

An improved understanding of etiological mechanisms in Parkinson's disease (PD) is urgently needed because the number of affected individuals is projected to increase rapidly as populations age. We present results from a blood-based methylome-wide association study of PD involving meta-analysis of 229 K CpG probes in 1,132 cases and 999 controls from two independent cohorts. We identify two previously unreported epigenome-wide significant associations with PD, including cg06690548 on chromosome 4. We demonstrate that cg06690548 hypermethylation in PD is associated with down-regulation of the SLC7A11 gene and show this is consistent with an environmental exposure, as opposed to medications or genetic factors with effects on DNA methylation or gene expression. These findings are notable because SLC7A11 codes for a cysteine-glutamate anti-porter regulating levels of the antioxidant glutathione, and it is a known target of the environmental neurotoxin β-methylamino-L-alanine (BMAA). Our study identifies the SLC7A11 gene as a plausible biological target in PD.

The proteome and its dynamics: A missing piece for integrative multi-omics in schizophrenia

The complex and heterogeneous pathophysiology of schizophrenia can be deconstructed by integration of large-scale datasets encompassing genes through behavioral phenotypes. Genome-wide datasets are now available for genetic, epigenetic and transcriptomic variations in schizophrenia, which are then analyzed by newly devised systems biology algorithms. A missing piece, however, is the inclusion of information on the proteome and its dynamics in schizophrenia. Proteomics has lagged behind omics of the genome, transcriptome and epigenome since analytic platforms were relatively less robust for proteins. There has been remarkable progress, however, in the instrumentation of liquid chromatography (LC) and mass spectrometry (MS) (LCMS), experimental paradigms and bioinformatics of the proteome. Here, we present a summary of methodological innovations of recent years in MS based proteomics and the power of new generation proteomics, review proteomics studies that have been conducted in schizophrenia to date, and propose how such data can be analyzed and integrated with other omics results. The function of a protein is determined by multiple molecular properties, i.e., subcellular localization, posttranslational modification (PTMs) and protein-protein interactions (PPIs). Incorporation of these properties poses additional challenges in proteomics and their integration with other omics; yet is a critical next step to close the loop of multi-omics integration. In sum, the recent advent of high-throughput proteome characterization technologies and novel mathematical approaches enable us to incorporate functional properties of the proteome to offer a comprehensive multi-omics based understanding of schizophrenia pathophysiology.

The association between schizophrenia and the immune system: Review of the evidence from unbiased 'omic-studies'

A role for immune processes in the pathogenesis of schizophrenia has been suggested by genetic and epidemiological studies, as well as cross-sectional studies on blood and brain samples. However, results are heterogeneous, which is likely caused by low samples sizes, insufficient control of confounders that influence immune processes, and potentially publication bias. Large hypothesis-free 'omic' studies partially circumvent these problems and could provide further evidence for a role of immune pathways in schizophrenia. In this review we assessed whether the largest genome, transcriptome and methylome studies in schizophrenia to date support a link with the immune system. We constructed an overview of the schizophrenia-associated genes and transcripts that were identified in these large 'omic' studies. We then performed a hypothesis-driven analysis to examine the association and enrichment of immune system-related genes and transcripts in these datasets. Additionally, we reviewed secondary analyses that were previously performed on these 'omic' studies. Except for the link between complement factor 4 (C4), we found limited evidence for a role of microglia and immune processes among genetic risk variants. Transcriptome and methylome studies point towards alterations in immune system related genes, pathways and cells. This includes changes in microglia, as well as complement, nuclear factor-κB, toll-like receptor and interferon signaling pathways. Many of these associated immune-related genes and pathways have been shown to be involved in neurodevelopment and neuronal functioning. Additional replication of these findings is needed, but once further conformation is provided, these findings could be a potentially interesting target for future therapies.

Brain-derived neurotrophic factor and schizophrenia

The brain-derived neurotrophic factor (BDNF) is a secretory growth factor that promotes neuronal proliferation and survival, synaptic plasticity and long-term potentiation in the central nervous system. Brain-derived neurotrophic factor biosynthesis and secretion are chrono-topically regulated processes at the cellular level, accounting for specific localizations and functions. Given its role in regulating brain development and activity, BDNF represents a potentially relevant gene for schizophrenia, and indeed BDNF and its non-synonymous functional variant, rs6265 (C → T, Val → Met) have been widely studied in psychiatric genetics. Human and animal studies have indicated that brain-derived neurotrophic factor is relevant for schizophrenia-related phenotypes, and that: (1) fine-tuned regulation of brain-derived neurotrophic factor secretion and activity is necessary to guarantee brain optimal development and functioning; (2) the Val → Met substitution is associated with impaired activity-dependent secretion of brain-derived neurotrophic factor; (3) disruption of brain-derived neurotrophic factor signaling is associated with altered synaptic plasticity and neurodevelopment. However, genome-wide association studies failed to associate the BDNF locus with schizophrenia, even though a sub-threshold association exists. Here, we will review studies focused on the relationship between the genetic variation of BDNF and schizophrenia, trying to fill the gap between genetic risk per se and insights from molecular biology. A deeper understanding of brain-derived neurotrophic factor biology and of the epigenetic regulation of brain-derived neurotrophic factor and its interactome during development may help clarifying the potential role of this gene in schizophrenia, thus informing development of brain-derived neurotrophic factor-based strategies of prevention and treatment of this disorder.

Identification of 34 genes conferring genetic and pharmacological risk for the comorbidity of schizophrenia and smoking behaviors

The prevalence of smoking is significantly higher in persons with schizophrenia (SCZ) than in the general population. However, the biological mechanisms of the comorbidity of smoking and SCZ are largely unknown. This study aimed to reveal shared biological pathways for the two diseases by analyzing data from two genome-wide association studies with a total sample size of 153,898. With pathway-based analysis, we first discovered 18 significantly enriched pathways shared by SCZ and smoking, which were classified into five groups: postsynaptic density, cadherin binding, dendritic spine, long-term depression, and axon guidance. Then, by using an integrative analysis of genetic, epigenetic, and expression data, we found not only 34 critical genes (e.g., PRKCZ, ARHGEF3, and CDKN1A) but also various risk-associated SNPs in these genes, which convey susceptibility to the comorbidity of the two disorders. Finally, using both in vivo and in vitro data, we demonstrated that the expression profiles of the 34 genes were significantly altered by multiple psychotropic drugs. Together, this multi-omics study not only reveals target genes for new drugs to treat SCZ but also reveals new insights into the shared genetic vulnerabilities of SCZ and smoking behaviors.

Integrating Multi-Omics Data to Identify Novel Disease Genes and Single-Neucleotide Polymorphisms

Stroke ranks the second leading cause of death among people over the age of 60 in the world. Stroke is widely regarded as a complex disease that is affected by genetic and environmental factors. Evidence from twin and family studies suggests that genetic factors may play an important role in its pathogenesis. Therefore, research on the genetic association of susceptibility genes can help understand the mechanism of stroke. Genome-wide association study (GWAS) has found a large number of stroke-related loci, but their mechanism is unknown. In order to explore the function of single-nucleotide polymorphisms (SNPs) at the molecular level, in this paper, we integrated 8 GWAS datasets with brain expression quantitative trait loci (eQTL) dataset to identify SNPs and genes which are related to four types of stroke (ischemic stroke, large artery stroke, cardioembolic stroke, small vessel stroke). Thirty-eight SNPs which can affect 14 genes expression are found to be associated with stroke. Among these 14 genes, 10 genes expression are associated with ischemic stroke, one gene for large artery stroke, six genes for cardioembolic stroke and eight genes for small vessel stroke. To explore the effects of environmental factors on stroke, we identified methylation susceptibility loci associated with stroke using methylation quantitative trait loci (MQTL). Thirty-one of these 38 SNPs are at greater risk of methylation and can significantly change gene expression level. Overall, the genetic pathogenesis of stroke is explored from locus to gene, gene to gene expression and gene expression to phenotype.

Chromatin accessibility dynamics in a model of human forebrain development

Forebrain development is characterized by highly synchronized cellular processes, which, if perturbed, can cause disease. To chart the regulatory activity underlying these events, we generated a map of accessible chromatin in human three-dimensional forebrain organoids. To capture corticogenesis, we sampled glial and neuronal lineages from dorsal or ventral forebrain organoids over 20 months in vitro. Active chromatin regions identified in human primary brain tissue were observed in organoids at different developmental stages. We used this resource to map genetic risk for disease and to explore evolutionary conservation. Moreover, we integrated chromatin accessibility with transcriptomics to identify putative enhancer-gene linkages and transcription factors that regulate human corticogenesis. Overall, this platform brings insights into gene-regulatory dynamics at previously inaccessible stages of human forebrain development, including signatures of neuropsychiatric disorders.

Dissecting transcriptomic signatures of neuronal differentiation and maturation using iPSCs

Human induced pluripotent stem cells (hiPSCs) are a powerful model of neural differentiation and maturation. We present a hiPSC transcriptomics resource on corticogenesis from 5 iPSC donor and 13 subclonal lines across 9 time points over 5 broad conditions: self-renewal, early neuronal differentiation, neural precursor cells (NPCs), assembled rosettes, and differentiated neuronal cells. We identify widespread changes in the expression of both individual features and global patterns of transcription. We next demonstrate that co-culturing human NPCs with rodent astrocytes results in mutually synergistic maturation, and that cell type-specific expression data can be extracted using only sequencing read alignments without cell sorting. We lastly adapt a previously generated RNA deconvolution approach to single-cell expression data to estimate the relative neuronal maturity of iPSC-derived neuronal cultures and human brain tissue. Using many public datasets, we demonstrate neuronal cultures are maturationally heterogeneous but contain subsets of neurons more mature than previously observed.

Psychosis-associated DNA methylomic variation in Alzheimer's disease cortex

Psychotic symptoms are a common and debilitating feature of Alzheimer's disease (AD) and are associated with a more rapid course of decline. Current evidence from postmortem and neuroimaging studies implicates frontal, temporal, and parietal lobes, with reported disruptions in monoaminergic pathways. However, the molecular mechanisms underlying this remain unclear. In the present study, we investigated methylomic variation associated with AD psychosis in 3 key brain regions implicated in the etiology of psychosis (prefrontal cortex, entorhinal cortex, and superior temporal gyrus) in postmortem brain samples from 29 AD donors with psychosis and 18 matched AD donors without psychosis. We identified psychosis-associated methylomic changes in a number of loci, with these genes being enriched in known schizophrenia-associated genetic and epigenetic variants. One of these known loci resided in the AS3MT gene-previously implicated in schizophrenia in a large GWAS meta-analysis. We used bisulfite-pyrosequencing to confirm hypomethylation across 4 neighboring CpG sites in the ASM3T gene. Finally, our regional analysis nominated multiple CpG sites in TBX15 and WT1, which are genes that have been previously implicated in AD. Thus one potential implication from our study is whether psychosis-associated variation drives reported associations in AD case-control studies.

Characterizing the nuclear and cytoplasmic transcriptomes in developing and mature human cortex uncovers new insight into psychiatric disease gene regulation

Transcriptome compartmentalization by the nuclear membrane provides both stochastic and functional buffering of transcript activity in the cytoplasm, and has recently been implicated in neurodegenerative disease processes. Although many mechanisms regulating transcript compartmentalization are also prevalent in brain development, the extent to which subcellular localization differs as the brain matures has yet to be addressed. To characterize the nuclear and cytoplasmic transcriptomes during brain development, we sequenced both RNA fractions from homogenate prenatal and adult human postmortem cortex using poly(A)+ and Ribo-Zero library preparation methods. We find that while many genes are differentially expressed by fraction and developmental expression changes are similarly detectable in nuclear and cytoplasmic RNA, the compartmented transcriptomes become more distinct as the brain matures, perhaps reflecting increased utilization of nuclear retention as a regulatory strategy in adult brain. We examined potential mechanisms of this developmental divergence including alternative splicing, RNA editing, nuclear pore composition, RNA-binding protein motif enrichment, and RNA secondary structure. Intron retention is associated with greater nuclear abundance in a subset of transcripts, as is enrichment for several splicing factor binding motifs. Finally, we examined disease association with fraction-regulated gene sets and found nuclear-enriched genes were also preferentially enriched in gene sets associated with neurodevelopmental psychiatric disorders. These results suggest that although gene-level expression is globally comparable between fractions, nuclear retention of transcripts may play an underappreciated role in developmental regulation of gene expression in brain, particularly in genes whose dysregulation is related to neuropsychiatric disorders.

Cell and tissue type independent age-associated DNA methylation changes are not rare but common

Age-associated DNA methylation changes have been widely reported across many different tissue and cell types. Epigenetic ‘clocks’ that can predict chronological age with a surprisingly high degree of accuracy appear to do so independently of tissue and cell-type, suggesting that a component of epigenetic drift is cell-type independent. However, the relative amount of age-associated DNAm changes that are specific to a cell or tissue type versus the amount that occurs independently of cell or tissue type is unclear and a matter of debate, with a recent study concluding that most epigenetic drift is tissue-specific. Here, we perform a novel comprehensive statistical analysis, including matched multi cell-type and multi-tissue DNA methylation profiles from the same individuals and adjusting for cell-type heterogeneity, demonstrating that a substantial amount of epigenetic drift, possibly over 70%, is shared between significant numbers of different tissue/cell types. We further show that ELOVL2 is not unique and that many other CpG sites, some mapping to genes in the Wnt and glutamate receptor signaling pathways, are altered with age across at least 10 different cell/tissue types. We propose that while most age-associated DNAm changes are shared between cell-types that the putative functional effect is likely to be tissue-specific.

coMethDMR: accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies with continuous phenotypes

Recent technology has made it possible to measure DNA methylation profiles in a cost-effective and comprehensive genome-wide manner using array-based technology for epigenome-wide association studies. However, identifying differentially methylated regions (DMRs) remains a challenging task because of the complexities in DNA methylation data. Supervised methods typically focus on the regions that contain consecutive highly significantly differentially methylated CpGs in the genome, but may lack power for detecting small but consistent changes when few CpGs pass stringent significance threshold after multiple comparison. Unsupervised methods group CpGs based on genomic annotations first and then test them against phenotype, but may lack specificity because the regional boundaries of methylation are often not well defined. We present coMethDMR, a flexible, powerful, and accurate tool for identifying DMRs. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-methylated sub-regions first. Next, coMethDMR tests association between methylation levels within the sub-region and phenotype via a random coefficient mixed effects model that models both variations between CpG sites within the region and differential methylation simultaneously. coMethDMR offers well-controlled Type I error rate, improved specificity, focused testing of targeted genomic regions, and is available as an open-source R package.

The fetal origins of mental illness

The impact of infections and inflammation during pregnancy on the developing fetal brain remains incompletely defined, with important clinical and research gaps. Although the classic infectious TORCH pathogens (ie, Toxoplasma gondii, rubella virus, cytomegalovirus [CMV], herpes simplex virus) are known to be directly teratogenic, emerging evidence suggests that these infections represent the most extreme end of a much larger spectrum of injury. We present the accumulating evidence that prenatal exposure to a wide variety of viral and bacterial infections-or simply inflammation-may subtly alter fetal brain development, leading to neuropsychiatric consequences for the child later in life. The link between influenza infections in pregnant women and an increased risk for development of schizophrenia in their children was first described more than 30 years ago. Since then, evidence suggests that a range of infections during pregnancy may also increase risk for autism spectrum disorder and depression in the child. Subsequent studies in animal models demonstrated that both pregnancy infections and inflammation can result in direct injury to neurons and neural progenitor cells or indirect injury through activation of microglia and astrocytes, which can trigger cytokine production and oxidative stress. Infectious exposures can also alter placental serotonin production, which can perturb neurotransmitter signaling in the developing brain. Clinically, detection of these subtle injuries to the fetal brain is difficult. As the neuropsychiatric impact of perinatal infections or inflammation may not be known for decades after birth, our construct for defining teratogenic infections in pregnancy (eg, TORCH) based on congenital anomalies is insufficient to capture the full adverse impact on the child. We discuss the clinical implications of this body of evidence and how we might place greater emphasis on prevention of prenatal infections. For example, increasing uptake of the seasonal influenza vaccine is a key strategy to reduce perinatal infections and the risk for fetal brain injury. An important research gap exists in understanding how antibiotic therapy during pregnancy affects the fetal inflammatory load and how to avoid inflammation-mediated injury to the fetal brain. In summary, we discuss the current evidence and mechanisms linking infections and inflammation with the increased lifelong risk of neuropsychiatric disorders in the child, and how we might improve prenatal care to protect the fetal brain.

Differential activity of transcribed enhancers in the prefrontal cortex of 537 cases with schizophrenia and controls

Transcription at enhancers is a widespread phenomenon which produces so-called enhancer RNA (eRNA) and occurs in an activity-dependent manner. However, the role of eRNA and its utility in exploring disease-associated changes in enhancer function, and the downstream coding transcripts that they regulate, is not well established. We used transcriptomic and epigenomic data to interrogate the relationship of eRNA transcription to disease status and how genetic variants alter enhancer transcriptional activity in the human brain. We combined RNA-seq data from 537 postmortem brain samples from the CommonMind Consortium with cap analysis of gene expression and enhancer identification, using the assay for transposase-accessible chromatin followed by sequencing (ATACseq). We find 118 differentially transcribed eRNAs in schizophrenia and identify schizophrenia-associated gene/eRNA co-expression modules. Perturbations of a key module are associated with the polygenic risk scores. Furthermore, we identify genetic variants affecting expression of 927 enhancers, which we refer to as enhancer expression quantitative loci or eeQTLs. Enhancer expression patterns are consistent across studies, including differentially expressed eRNAs and eeQTLs. Combining eeQTLs with a genome-wide association study of schizophrenia identifies a genetic variant that alters enhancer function and expression of its target gene, GOLPH3L. Our novel approach to analyzing enhancer transcription is adaptable to other large-scale, non-poly-A depleted, RNA-seq studies.

Integrate GWAS, eQTL, and mQTL Data to Identify Alzheimer's Disease-Related Genes

It is estimated that the impact of related genes on the risk of Alzheimer's disease (AD) is nearly 70%. Identifying candidate causal genes can help treatment and diagnosis. The maturity of sequencing technology and the reduction of cost make genome-wide association study (GWAS) become an important means to find disease-related mutation sites. Because of linkage disequilibrium (LD), neither the gene regulated by SNP nor the specific SNP can be determined. Because GWAS is affected by sample size and interaction, we introduced empirical Bayes (EB) to make a meta-analysis of GWAS to greatly eliminate the bias caused by sample and the interaction of SNP. In addition, most SNPs are in the noncoding region, so it is not clear how they relate to phenotype. In this paper, expression quantitative trait locus (eQTL) studies and methylation quantitative trait locus (mQTL) studies are combined with GWAS to find the genes associated with Alzheimer disease in expression levels by pleiotropy. Summary data-based Mendelian randomization (SMR) is introduced to integrate GWAS and eQTL/mQTL data. Finally, we prioritized 274 significant SNPs, which belong to 20 genes by eQTL analysis and 379 significant SNPs, which belong to seven known genes by mQTL. Among them, 93 SNPs and 2 genes are overlapped. Finally, we did 10 case studies to prove the effectiveness of our method.

African-American and Caucasian participation in postmortem human brain donation for neuropsychiatric research

Increased African-American research participation is critical to the applicability and generalizability of biomedical research, as population diversity continues to increase both domestically and abroad. Yet numerous studies document historical origins of mistrust, as well as other barriers that may contribute to resistance in the African-American community towards participation in biomedical research. However, a growing body of more recent scientific evidence suggests that African-Americans value research and are willing to participate when asked. In the present study, we set out to determine factors associated with research participation of African-American families in postmortem human brain tissue donation for neuropsychiatric disorders as compared with Caucasian families, from same-day medical examiner autopsy referrals. We retrospectively reviewed brain donation rates, as well as demographic and clinical factors associated with donation in 1,421 consecutive referrals to three medical examiner’s offices from 2010–2015. Overall, 69.7% of all next-of-kin contacted agreed to brain donation. While Caucasian families consented to donate brain tissue at a significantly higher rate (74.1%) than African-American families (57.0%) (p<0.001), African-American brain donation rates were as high as 60.5% in referrals from Maryland. Neither African-American nor Caucasian donors differed significantly from non-donors on any demographic or clinical factors ascertained, including age, sex, diagnosis of the donor, or in the relationship of the next-of-kin being contacted (p>0.05). However, Caucasian donors were significantly older, had more years of education, were more likely to be referred for study due to a psychiatric diagnosis, more likely to have comorbid substance abuse, and more likely to have died via suicide, as compared with African-American donors (p<0.05). When African-American participants are identified and approached, African-American families as well as Caucasian families are indeed willing to donate brain tissue on the spot for neuropsychiatric research, which supports the belief that African-American attitudes towards biomedical research may be more favorable than previously thought.

Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms

Tissue-specific regulatory regions harbor substantial genetic risk for disease. Because brain development is a critical epoch for neuropsychiatric disease susceptibility, we characterized the genetic control of the transcriptome in 201 mid-gestational human brains, identifying 7,962 expression quantitative trait loci (eQTL) and 4,635 spliceQTL (sQTL), including several thousand prenatal-specific regulatory regions. We show that significant genetic liability for neuropsychiatric disease lies within prenatal eQTL and sQTL. Integration of eQTL and sQTL with genome-wide association studies (GWAS) via transcriptome-wide association identified dozens of novel candidate risk genes, highlighting shared and stage-specific mechanisms in schizophrenia (SCZ). Gene network analysis revealed that SCZ and autism spectrum disorder (ASD) affect distinct developmental gene co-expression modules. Yet, in each disorder, common and rare genetic variation converges within modules, which in ASD implicates superficial cortical neurons. More broadly, these data, available as a web browser and our analyses, demonstrate the genetic mechanisms by which developmental events have a widespread influence on adult anatomical and behavioral phenotypes.

Chromatin profiling of cortical neurons identifies individual epigenetic signatures in schizophrenia

Both heritability and environment contribute to risk for schizophrenia. However, the molecular mechanisms of interactions between genetic and non-genetic factors remain unclear. Epigenetic regulation of neuronal genome may be a presumable mechanism in pathogenesis of schizophrenia. Here, we performed analysis of open chromatin landscape of gene promoters in prefrontal cortical (PFC) neurons from schizophrenic patients. We cataloged cell-type-based epigenetic signals of transcriptional start sites (TSS) marked by histone H3-K4 trimethylation (H3K4me3) across the genome in PFC from multiple schizophrenia subjects and age-matched control individuals. One of the top-ranked chromatin alterations was found in the major histocompatibility (MHC) locus on chromosome 6 highlighting the overlap between genetic and epigenetic risk factors in schizophrenia. The chromosome conformation capture (3C) analysis in human brain cells revealed the architecture of multipoint chromatin interactions between the schizophrenia-associated genetic and epigenetic polymorphic sites and distantly located HLA-DRB5 and BTNL2 genes. In addition, schizophrenia-specific chromatin modifications in neurons were particularly prominent for non-coding RNA genes, including an uncharacterized LINC01115 gene and recently identified BNRNA_052780. Notably, protein-coding genes with altered epigenetic state in schizophrenia are enriched for oxidative stress and cell motility pathways. Our results imply the rare individual epigenetic alterations in brain neurons are involved in the pathogenesis of schizophrenia.

Epigenome-wide association study of narcolepsy-affected lateral hypothalamic brains, and overlapping DNA methylation profiles between narcolepsy and multiple sclerosis

Narcolepsy with cataplexy is a sleep disorder caused by a deficiency in hypocretin neurons in the lateral hypothalamus (LH). Here we performed an epigenome-wide association study (EWAS) of DNA methylation for narcolepsy and replication analyses using DNA samples extracted from two brain regions: LH (Cases: N = 4; Controls: N = 4) and temporal cortex (Cases: N = 7; Controls: N = 7). Seventy-seven differentially methylated regions (DMRs) were identified in the LH analysis, with the top association of a DMR in the myelin basic protein (MBP) region. Only five DMRs were detected in the temporal cortex analysis. Genes annotated to LH DMRs were significantly associated with pathways related to fatty acid response or metabolism. Two additional analyses applying the EWAS data were performed: (1) investigation of methylation profiles shared between narcolepsy and other disorders and (2) an integrative analysis of DNA methylation data and a genome-wide association study for narcolepsy. The results of the two approaches, which included significant overlap of methylated positions associated with narcolepsy and multiple sclerosis, indicated that the two diseases may partly share their pathogenesis. In conclusion, DNA methylation in LH where loss of orexin-producing neurons occurs may play a role in the pathophysiology of the disease.