Hypomethylation of FAM63B in bipolar disorder patients

Exosomal circFAM63Bsuppresses bone regeneration of postmenopausal osteoporosis via regulating miR-578/HMGA2 axis

Postmenopausal osteoporosis (PMOP) affects hundreds of millions of elderly women worldwide. The imbalance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption is the key factor in the progression of PMOP. Recently, exosomal circular RNAs have been considered as critical regulators in physiological and pathological progress. However, their roles in PMOP still require further exploration. Herein, we identified that the expression of exosomal circFAM63B significantly increased in PMOP patients and is closely related to bone density. We further demonstrated that circFAM63B inhibits osteogenic differentiation of bone marrow stromal cells and bone formation in ovariectomy mice by using a combination of in vitro and in vivo experiment strategies. Mechanistically, circFAM63B promotes HMGA2 expression by inhibiting miR-578, thereby suppressing bone repair. Our study proved that exosomal circFAM63B suppresses the bone regeneration of PMOP by regulating the miR-578/HMGA2 axis, which may provide new insights into the pathogenesis and development of PMOP. Knocking down exosomal circFAM63B could be regarded as a new strategy for the treatment of PMOP.

Building Minimized Epigenetic Clock by iPlex MassARRAY Platform

Epigenetic clocks are valuable tools for estimating both chronological and biological age by assessing DNA methylation levels at specific CpG dinucleotides. While conventional epigenetic clocks rely on genome-wide methylation data, targeted approaches offer a more efficient alternative. In this study, we explored the feasibility of constructing a minimized epigenetic clock utilizing data acquired through the iPlex MassARRAY technology. The study enrolled a cohort of relatively healthy individuals, and their methylation levels of eight specific CpG dinucleotides in genes SLC12A5, LDB2, FIGN, ACSS3, FHL2, and EPHX3 were evaluated using the iPlex MassARRAY system and the Illumina EPIC array. The methylation level of five studied CpG sites demonstrated significant correlations with chronological age and an acceptable convergence of data obtained by the iPlex MassARRAY and Illumina EPIC array. At the same time, the methylation level of three CpG sites showed a weak relationship with age and exhibited a low concordance between the data obtained from the two technologies. The construction of the epigenetic clock involved the utilization of different machine-learning models, including linear models, deep neural networks (DNN), and gradient-boosted decision trees (GBDT). The results obtained from these models were compared with each other and with the outcomes generated by other well-established epigenetic clocks. In our study, the TabNet architecture (deep tabular data learning architecture) exhibited the best performance (best MAE = 5.99). Although our minimized epigenetic clock yielded slightly higher age prediction errors compared to other epigenetic clocks, it still represents a viable alternative to the genome-wide epigenotyping array.

Are the epigenetic changes predictive of therapeutic efficacy for psychiatric disorders? A translational approach towards novel drug targets

The etiopathogenesis of mental disorders is not fully understood and accumulating evidence support that clinical symptomatology cannot be assigned to a single gene mutation, but it involves several genetic factors. More specifically, a tight association between genes and environmental risk factors, which could be mediated by epigenetic mechanisms, may play a role in the development of mental disorders. Several data suggest that epigenetic modifications such as DNA methylation, post-translational histone modification and interference of microRNA (miRNA) or long non-coding RNA (lncRNA) may modify the severity of the disease and the outcome of the therapy. Indeed, the study of these mechanisms may help to identify patients particularly vulnerable to mental disorders and may have potential utility as biomarkers to facilitate diagnosis and treatment of psychiatric disorders. This article summarizes the most relevant preclinical and human data showing how epigenetic modifications can be central to the therapeutic efficacy of antidepressant and/or antipsychotic agents, as possible predictor of drugs response.

Epigenetic signatures relating to disease-associated genotypic burden in familial risk of bipolar disorder

Environmental factors contribute to risk of bipolar disorder (BD), but how environmental factors impact the development of psychopathology within the context of elevated genetic risk is unknown. We herein sought to identify epigenetic signatures operating in the context of polygenic risk for BD in young people at high familial risk (HR) of BD. Peripheral blood-derived DNA was assayed using Illumina PsychArray, and Methylation-450K or -EPIC BeadChips. Polygenic risk scores (PRS) were calculated using summary statistics from recent genome-wide association studies for BD, major depressive disorder (MDD) and cross-disorder (meta-analysis of eight psychiatric disorders). Unrelated HR participants of European ancestry (n = 103) were stratified based on their BD-PRS score within the HR-population distribution, and the top two quintiles (High-BD-PRS; n = 41) compared against the bottom two quintiles (Low-BD-PRS; n = 41). The High-BD-PRS stratum also had higher mean cross-disorder-PRS and MDD-PRS (ANCOVA p = 0.035 and p = 0.024, respectively). We evaluated DNA methylation differences between High-BD-PRS and Low-BD-PRS strata using linear models. One differentially methylated probe (DMP) (cg00933603; p = 3.54 × 10^-7) in VARS2, a mitochondrial aminoacyl-tRNA synthetase, remained significantly hypomethylated after multiple-testing correction. Overall, BD-PRS appeared to broadly impact epigenetic processes, with 1,183 genes mapped to nominal DMPs (p < 0.05); these displayed convergence with genes previously associated with BD, schizophrenia, chronotype, and risk taking. We tested poly-methylomic epigenetic profiles derived from nominal DMPs in two independent samples (n = 54 and n = 82, respectively), and conducted an exploratory evaluation of the effects of family environment, indexing cohesion and flexibility. This study highlights an important interplay between heritable risk and epigenetic factors, which warrant further exploration.

Identification of Endocannabinoid Predictors of Treatment Outcomes in Major Depressive Disorder: A Secondary Analysis of the First Canadian Biomarker Integration Network in Depression (CAN-BIND 1) Study

INTRODUCTION

An increasing number of studies are examining the link between the endocannabinoidome and major depressive disorder (MDD). We conducted an exploratory analysis of this system to identify potential markers of treatment outcomes.

METHODS

The dataset of the Canadian Biomarker Integration Network in Depression-1 study, consisting of 180 patients with MDD treated for eight weeks with escitalopram followed by eight weeks with escitalopram alone or augmented with aripiprazole was analyzed. Association between response Montgomery-Asberg Depression Rating Scale (MADRS; score reduction≥50%) or remission (MADRS score≤10) at weeks 8 and 16 and single nucleotide polymorphisms (SNPs), methylation, and mRNA levels of 33 endocannabinoid markers were examined. A standard genome-wide association studies protocol was used for identifying SNPs, and logistic regression was used to assess methylation and mRNA levels.

RESULTS

Lower methylation of CpG islands of the diacylglycerol lipase alpha gene (DAGLA) was associated with non-remission at week 16 (DAGLA; OR=0.337, p<0.003, q=0.050). Methylation of DAGLA was correlated with improvement in Clinical Global Impression (p=0.026), Quick Inventory of Depressive Symptomatology (p=0.010), and Snaith-Hamilton Pleasure scales (p=0.028). We did not find any association between SNPs or mRNA levels and treatment outcomes.

DISCUSSION

Methylation of DAGLA is a promising candidate as a marker of treatment outcomes for MDD and needs to be explored further.

Epigenetic Basis of Psychiatric Disorders: A Narrative Review

BACKGROUND

Psychiatric disorders are complex, multifactorial illnesses with a demonstrated biological component in their etiopathogenesis. Epigenetic modifications, through the modulation of DNA methylation, histone modifications and RNA interference, tune tissue-specific gene expression patterns and play a relevant role in the etiology of psychiatric illnesses.

OBJECTIVE

This review aims to discuss the epigenetic mechanisms involved in psychiatric disorders, their modulation by environmental factors and their interactions with genetic variants, in order to provide a comprehensive picture of their mutual crosstalk.

METHODS

In accordance with the PRISMA guidelines, systematic searches of Medline, EMBASE, PsycINFO, Web of Science, Scopus, and the Cochrane Library were conducted.

RESULTS

Exposure to environmental factors, such as poor socio-economic status, obstetric complications, migration, and early life stressors, may lead to stable changes in gene expression and neural circuit function, playing a role in the risk of psychiatric diseases. The most replicated genes involved by studies using different techniques are discussed. Increasing evidence indicates that these sustained abnormalities are maintained by epigenetic modifications in specific brain regions and they interact with genetic variants in determining the risk of psychiatric disorders.

CONCLUSION

An increasing amount of evidence suggests that epigenetics plays a pivotal role in the etiopathogenesis of psychiatric disorders. New therapeutic approaches may work by reversing detrimental epigenetic changes that occurred during the lifespan.

MiR-574-5P, miR-1827, and miR-4429 as Potential Biomarkers for Schizophrenia

Schizophrenia is a severe chronic debilitating disorder with millions of affected individuals. Diagnosis is based on clinical presentations, which are made when the progressive disease has appeared. Early diagnosis may help improve the clinical outcomes and response to treatments. Lack of a reliable molecular diagnostic invokes the identification of novel biomarkers. To elucidate the molecular basis of the disease, in this study we used two mRNA expression arrays, including GSE93987 and GSE38485, and one miRNA array, GSE54914, and meta-analysis was conducted for evaluation of mRNA expression arrays via metaDE package. Using WGCNA package, we performed network analysis for both mRNA expression arrays separately. Then, we constructed protein-protein interaction network for significant modules. Limma package was employed to analyze the miRNA array for identification of dysregulated miRNAs (DEMs). Using genes of significant modules and DEMs, a mRNA-miRNA network was constructed and hub genes and miRNAs were identified. To confirm the dysregulated genes, expression values were evaluated through available datasets including GSE62333, GSE93987, and GSE38485. The ability of the detected hub miRNAs to discriminate schizophrenia from healthy controls was evaluated by assessing the receiver-operating curve. Finally, the expression levels of genes and miRNAs were evaluated in 40 schizophrenia patients compared with healthy controls via Real-Time PCR. The results confirmed dysregulation of hsa-miR-574-5P, hsa-miR-1827, hsa-miR-4429, CREBRF, ARPP19, TGFBR2, and YWHAZ in blood samples of schizophrenia patients. In conclusion, three miRNAs including hsa-miR-574-5P, hsa-miR-1827, and hsa-miR-4429 are suggested as potential biomarkers for diagnosis of schizophrenia.

Epigenomic Dysregulation in Schizophrenia: In Search of Disease Etiology and Biomarkers

Schizophrenia is a severe psychiatric disorder with a complex array of signs and symptoms that causes very significant disability in young people. While schizophrenia has a strong genetic component, with heritability around 80%, there is also a very significant range of environmental exposures and stressors that have been implicated in disease development and neuropathology, such as maternal immune infection, obstetric complications, childhood trauma and cannabis exposure. It is postulated that epigenetic factors, as well as regulatory non-coding RNAs, mediate the effects of these environmental stressors. In this review, we explore the most well-known epigenetic marks, including DNA methylation and histone modification, along with emerging RNA mediators of epigenomic state, including miRNAs and lncRNAs, and discuss their collective potential for involvement in the pathophysiology of schizophrenia implicated through the postmortem analysis of brain tissue. Given that peripheral tissues, such as blood, saliva, and olfactory epithelium have the same genetic composition and are exposed to many of the same environmental exposures, we also examine some studies supporting the application of peripheral tissues for epigenomic biomarker discovery in schizophrenia. Finally, we provide some perspective on how these biomarkers may be utilized to capture a signature of past events that informs future treatment.

Screening for autoantibody targets in post-vaccination narcolepsy using proteome arrays

Narcolepsy type 1 (NT1) is a chronic sleep disorder caused by a specific loss of hypocretin-producing neurons. The incidence of NT1 increased in Sweden, Finland and Norway following Pandemrix®-vaccination, initiated to prevent the 2009 influenza pandemic. The pathogenesis of NT1 is poorly understood, and causal links to vaccination are yet to be clarified. The strong association with Human leukocyte antigen (HLA) DQB1*06:02 suggests an autoimmune pathogenesis, but proposed autoantigens remain controversial. We used a two-step approach to identify autoantigens in patients that acquired NT1 after Pandemrix®-vaccination. Using arrays of more than 9000 full-length human proteins, we screened the sera of 10 patients and 24 healthy subjects for autoantibodies. Identified candidate antigens were expressed in vitro to enable validation studies with radiobinding assays (RBA). The validation cohort included NT1 patients (n = 39), their first-degree relatives (FDR) (n = 66), population controls (n = 188), and disease controls representing multiple sclerosis (n = 100) and FDR to type 1 diabetes patients (n = 41). Reactivity towards previously suggested NT1 autoantigen candidates including Tribbles homolog 2, Prostaglandin D2 receptor, Hypocretin receptor 2 and α-MSH/proopiomelanocortin was not replicated in the protein array screen. By comparing case to control signals, three novel candidate autoantigens were identified in the protein array screen; LOC401464, PARP3 and FAM63B. However, the RBA did not confirm elevated reactivity towards either of these proteins. In summary, three putative autoantigens in NT1 were identified by protein array screening. Autoantibodies against these candidates could not be verified with independent methods. Further studies are warranted to identify hypothetical autoantigens related to the pathogenesis of Pandemrix®-induced NT1.

Theiler's Virus-Mediated Immunopathology in the CNS and Heart: Roles of Organ-Specific Cytokine and Lymphatic Responses

Theiler's murine encephalomyelitis virus (TMEV) induces different diseases in the central nervous system (CNS) and heart, depending on the mouse strains and time course, with cytokines playing key roles for viral clearance and immune-mediated pathology (immunopathology). In SJL/J mice, TMEV infection causes chronic TMEV-induced demyelinating disease (TMEV-IDD) in the spinal cord about 1 month post-inoculation (p.i.). Unlike other immunopathology models, both pro- and anti-inflammatory cytokines can play dual roles in TMEV-IDD. Pro-inflammatory cytokines play beneficial roles in viral clearance while they are also detrimental in immune-mediated demyelination. Anti-inflammatory cytokines suppress not only protective anti-viral immune responses but also detrimental autoreactive immune responses. Conversely, in C3H mice, TMEV infection induces a non-CNS disease, myocarditis, with three distinctive phases: phase I, viral pathology with interferon and chemokine responses; phase II, immunopathology mediated by acquired immune responses; and phase III, cardiac fibrosis. Although the exact mechanism(s) by which a single virus, TMEV, induces these different diseases in different organs is unclear, our bioinformatics approaches, especially principal component analysis (PCA) of transcriptome data, allow us to identify the key factors contributing to organ-specific immunopathology. The PCA demonstrated that in vitro infection of a cardiomyocyte cell line reproduced the transcriptome profile of phase I in TMEV-induced myocarditis; distinct interferon/chemokine-related responses were induced in vitro in TMEV-infected cardiomyocytes, but not in infected neuronal cells. In addition, the PCA of the in vivo CNS transcriptome data showed that decreased lymphatic marker expressions were weakly associated with inflammation in TMEV infection. Here, dysfunction of lymphatic vessels is shown to potentially contribute to immunopathology by delaying the clearance of cytokines and immune cells from the inflammatory site, although this can also confine the virus at these sites, preventing virus spread via lymphatic vessels. On the other hand, in the heart, dysfunction of lymphatics was associated with reduced lymphatic muscle contractility provoked by pro-inflammatory cytokines. Therefore, TMEV infection may induce different patterns of cytokine expressions as well as lymphatic vessel dysfunction by rather different mechanisms between the CNS and heart, which might explain observed patterns of organ-specific immunopathology.

DNA Methylation as a Biomarker of Treatment Response Variability in Serious Mental Illnesses: A Systematic Review Focused on Bipolar Disorder, Schizophrenia, and Major Depressive Disorder

So far, genetic studies of treatment response in schizophrenia, bipolar disorder, and major depression have returned results with limited clinical utility. A gene × environment interplay has been proposed as a factor influencing not only pathophysiology but also the treatment response. Therefore, epigenetics has emerged as a major field of research to study the treatment of these three disorders. Among the epigenetic marks that can modify gene expression, DNA methylation is the best studied. We performed a systematic search (PubMed) following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA guidelines for preclinical and clinical studies focused on genome-wide and gene-specific DNA methylation in the context of schizophrenia, bipolar disorders, and major depressive disorder. Out of the 112 studies initially identified, we selected 31 studies among them, with an emphasis on responses to the gold standard treatments in each disorder. Modulations of DNA methylation levels at specific CpG sites have been documented for all classes of treatments (antipsychotics, mood stabilizers, and antidepressants). The heterogeneity of the models and methodologies used complicate the interpretation of results. Although few studies in each disorder have assessed the potential of DNA methylation as biomarkers of treatment response, data support this hypothesis for antipsychotics, mood stabilizers and antidepressants.

DNA Methylation and Psychiatric Disorders

DNA methylation has been an important area of research in the study of molecular mechanism to psychiatric disorders. Recent evidence has suggested that abnormalities in global methylation, methylation of genes, and pathways could play a role in the etiology of many forms of mental illness. In this article, we review the mechanisms of DNA methylation, including the genetic and environmental factors affecting methylation changes. We report and discuss major findings regarding DNA methylation in psychiatric patients, both within the context of global methylation studies and gene-specific methylation studies. Finally, we discuss issues surrounding data quality improvement, the limitations of current methylation analysis methods, and the possibility of using DNA methylation-based treatment for psychiatric disorders in the future.

DNA methylation analyses of the candidate genes identified by a methylome-wide association study revealed common epigenetic alterations in schizophrenia and bipolar disorder

AIM

Schizophrenia (SZ) and bipolar disorder (BD) have been known to share genetic and environmental risk factors, and complex gene-environmental interactions may contribute to their pathophysiology. In contrast to high genetic overlap between SZ and BD, as revealed by genome-wide association studies, the extent of epigenetic overlap remains largely unknown. In the present study, we explored whether SZ and BD share epigenetic risk factors in the same manner as they share genetic components.

METHODS

We performed DNA methylation analyses of the CpG sites in the top five candidate regions (FAM63B, ARHGAP26, CTAGE11P, TBC1D22A, and intergenic region [IR] on chromosome 16) reported in a previous methylome-wide association study (MWAS) of SZ, using whole blood samples from subjects with BD and controls.

RESULTS

Among the five candidate regions, the CpG sites in FAM63B and IR on chromosome 16 were significantly hypomethylated in the samples from subjects with BD as well as those from subjects with SZ. On the other hand, the CpG sites in TBC1D22A were hypermethylated in the samples from subjects with BD, in contrast to hypomethylation in the samples from subjects with SZ.

CONCLUSION

Hypomethylation of FAM63B and IR on chromosome 16 could be common epigenetic risk factors for SZ and BD. Further comprehensive epigenetic studies for BD, such as MWAS, will uncover the extent of similarity and uniqueness of epigenetic alterations.

Neurocognitive function in clinically stable individuals with long-term bipolar I disorder: Comparisons with schizophrenia patients and controls

This study compared the levels of the five domains of neurocognitive function-executive function, attention, memory, verbal comprehension, and perceptual organization-among clinically stable individuals with long-term bipolar I disorder, individuals with long-term schizophrenia, and a group of controls. We recruited a total of 93 clinically stable individuals with bipolar I disorder, 94 individuals with schizophrenia, and 106 controls in this study. Their neurocognitive function was measured using a series of neurocognitive function tests: the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III), Line Cancellation Test, Visual Form Discrimination, Controlled Oral Word Association Test, Wisconsin Card Sorting Test, Continuous Performance Task, and Wechsler Memory Scale-Third Edition. Neurocognitive function was compared among the three groups through a multivariate analysis of variance. The results indicated that when the effect of age was controlled, clinically stable individuals with bipolar I disorder and those with schizophrenia demonstrated poor neurocognitive function on all tests except for the WAIS-III Similarity and Information and the Line Cancellation Test. The individuals with bipolar I disorder had similar levels of neurocognitive function compared with the schizophrenia group, but higher levels of neurocognitive function on the WAIS-III Comprehension, Controlled Oral Word Association Test, and Wechsler Memory Scale-Third Edition Auditory Immediate and Delayed Index and Visual Immediate and Delayed Index. The conclusions of this study suggest that compared with controls, individuals with long-term bipolar I disorder and those with long-term schizophrenia have poorer neurocognitive function, even when clinically stable. Individuals with long-term bipolar I disorder and those with long-term schizophrenia have similar levels of deficits in several domains of neurocognitive function.

Epigenetic profiling of human brain differential DNA methylation networks in schizophrenia

Background

Epigenetics of schizophrenia provides important information on how the environmental factors affect the genetic architecture of the disease. DNA methylation plays a pivotal role in etiology for schizophrenia. Previous studies have focused mostly on the discovery of schizophrenia-associated SNPs or genetic variants. As postmortem brain samples became available, more and more recent studies surveyed transcriptomics of the diseases. In this study, we constructed protein-protein interaction (PPI) network using the disease associated SNP (or genetic variants), differentially expressed disease genes and differentially methylated disease genes (or promoters). By combining the different datasets and topological analyses of the PPI network, we established a more comprehensive understanding of the development and genetics of this devastating mental illness.

Results

We analyzed the previously published DNA methylation profiles of prefrontal cortex from 335 healthy controls and 191 schizophrenic patients. These datasets revealed 2014 CpGs identified as GWAS risk loci with the differential methylation profile in schizophrenia, and 1689 schizophrenic differential methylated genes (SDMGs) identified with predominant hypomethylation. These SDMGs, combined with the PPIs of these genes, were constructed into the schizophrenic differential methylation network (SDMN). On the SDMN, there are 10 hypermethylated SDMGs, including GNA13, CAPNS1, GABPB2, GIT2, LEFTY1, NDUFA10, MIOS, MPHOSPH6, PRDM14 and RFWD2. The hypermethylation to differential expression network (HyDEN) were constructed to determine how the hypermethylated promoters regulate gene expression. The enrichment analyses of biochemical pathways in HyDEN, including TNF alpha, PDGFR-beta signaling, TGF beta Receptor, VEGFR1 and VEGFR2 signaling, regulation of telomerase, hepatocyte growth factor receptor signaling, ErbB1 downstream signaling and mTOR signaling pathway, suggested that the malfunctioning of these pathways contribute to the symptoms of schizophrenia.

Conclusions

The epigenetic profiles of DNA differential methylation from schizophrenic brain samples were investigated to understand the regulatory roles of SDMGs. The SDMGs interplays with SCZCGs in a coordinated fashion in the disease mechanism of schizophrenia. The protein complexes and pathways involved in SDMN may be responsible for the etiology and potential treatment targets. The SDMG promoters are predominantly hypomethylated. Increasing methylation on these promoters is proposed as a novel therapeutic approach for schizophrenia.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-016-0229-y) contains supplementary material, which is available to authorized users.

The role of DNA methylation in the pathophysiology and treatment of bipolar disorder

Bipolar disorder (BD) is a multifactorial illness thought to result from an interaction between genetic susceptibility and environmental stimuli. Epigenetic mechanisms, including DNA methylation, can modulate gene expression in response to the environment, and therefore might account for part of the heritability reported for BD. This paper aims to review evidence of the potential role of DNA methylation in the pathophysiology and treatment of BD. In summary, several studies suggest that alterations in DNA methylation may play an important role in the dysregulation of gene expression in BD, and some actually suggest their potential use as biomarkers to improve diagnosis, prognosis, and assessment of response to treatment. This is also supported by reports of alterations in the levels of DNA methyltransferases in patients and in the mechanism of action of classical mood stabilizers. In this sense, targeting specific alterations in DNA methylation represents exciting new treatment possibilities for BD, and the 'plastic' characteristic of DNA methylation accounts for a promising possibility of restoring environment-induced modifications in patients.