Epigenome-wide association study of rheumatoid arthritis identifies differentially methylated loci in B cells

Epigenetic signature of very low birth weight in young adult life

BACKGROUND

Globally, one in ten babies is born preterm (<37 weeks), and 1-2% preterm at very low birth weight (VLBW, <1500 g). As adults, they are at increased risk for a plethora of health conditions, e.g., cardiometabolic disease, which may partly be mediated by epigenetic regulation. We compared blood DNA methylation between young adults born at VLBW and controls.

METHODS

157 subjects born at VLBW and 161 controls born at term, from the Helsinki Study of Very Low Birth Weight Adults, were assessed for peripheral venous blood DNA methylation levels at mean age of 22 years. Significant CpG-sites (5'-C-phosphate-G-3') were meta-analyzed against continuous birth weight in four independent cohorts (pooled n = 2235) with cohort mean ages varying from 0 to 31 years.

RESULTS

In the discovery cohort, 66 CpG-sites were differentially methylated between VLBW adults and controls. Top hits were located in HIF3A, EBF4, and an intergenic region nearest to GLI2 (distance 57,533 bp). Five CpG-sites, all in proximity to GLI2, were hypermethylated in VLBW and associated with lower birth weight in the meta-analysis.

CONCLUSION

We identified differentially methylated CpG-sites suggesting an epigenetic signature of preterm birth at VLBW present in adult life.

IMPACT

Being born preterm at very low birth weight has major implications for later health and chronic disease risk factors. The mechanism linking preterm birth to later outcomes remains unknown. Our cohort study of 157 very low birth weight adults and 161 controls found 66 differentially methylated sites at mean age of 22 years. Our findings suggest an epigenetic mark of preterm birth present in adulthood, which opens up opportunities for mechanistic studies.

Functional significance of DNA methylation: epigenetic insights into Sjögren's syndrome

Sjögren's syndrome (SjS) is a systemic, highly diverse, and chronic autoimmune disease with a significant global prevalence. It is a complex condition that requires careful management and monitoring. Recent research indicates that epigenetic mechanisms contribute to the pathophysiology of SjS by modulating gene expression and genome stability. DNA methylation, a form of epigenetic modification, is the fundamental mechanism that modifies the expression of various genes by modifying the transcriptional availability of regulatory regions within the genome. In general, adding a methyl group to DNA is linked with the inhibition of genes because it changes the chromatin structure. DNA methylation changes the fate of multiple immune cells, such as it leads to the transition of naïve lymphocytes to effector lymphocytes. A lack of central epigenetic enzymes frequently results in abnormal immune activation. Alterations in epigenetic modifications within immune cells or salivary gland epithelial cells are frequently detected during the pathogenesis of SjS, representing a robust association with autoimmune responses. The analysis of genome methylation is a beneficial tool for establishing connections between epigenetic changes within different cell types and their association with SjS. In various studies related to SjS, most differentially methylated regions are in the human leukocyte antigen (HLA) locus. Notably, the demethylation of various sites in the genome is often observed in SjS patients. The most strongly linked differentially methylated regions in SjS patients are found within genes regulated by type I interferon. This demethylation process is partly related to B-cell infiltration and disease progression. In addition, DNA demethylation of the runt-related transcription factor (RUNX1) gene, lymphotoxin-α (LTA), and myxovirus resistance protein A (MxA) is associated with SjS. It may assist the early diagnosis of SjS by serving as a potential biomarker. Therefore, this review offers a detailed insight into the function of DNA methylation in SjS and helps researchers to identify potential biomarkers in diagnosis, prognosis, and therapeutic targets.

Identification of genetic variants associated with anterior cruciate ligament rupture and AKC standard coat color in the Labrador Retriever

Canine anterior cruciate ligament (ACL) rupture is a common complex disease. Prevalence of ACL rupture is breed dependent. In an epidemiological study, yellow coat color was associated with increased risk of ACL rupture in the Labrador Retriever. ACL rupture risk variants may be linked to coat color through genetic selection or through linkage with coat color genes. To investigate these associations, Labrador Retrievers were phenotyped as ACL rupture case or controls and for coat color and were single nucleotide polymorphism (SNP) genotyped. After filtering, ~ 697 K SNPs were analyzed using GEMMA and mvBIMBAM for multivariate association. Functional annotation clustering analysis with DAVID was performed on candidate genes. A large 8 Mb region on chromosome 5 that included ACSF3, as well as 32 additional SNPs, met genome-wide significance at P < 6.07E-7 or Log10(BF) = 3.0 for GEMMA and mvBIMBAM, respectively. On chromosome 23, SNPs were located within or near PCCB and MSL2. On chromosome 30, a SNP was located within IGDCC3. SNPs associated with coat color were also located within ADAM9, FAM109B, SULT1C4, RTDR1, BCR, and RGS7. DZIP1L was associated with ACL rupture. Several significant SNPs on chromosomes 2, 3, 7, 24, and 26 were located within uncharacterized regions or long non-coding RNA sequences. This study validates associations with the previous ACL rupture candidate genes ACSF3 and DZIP1L and identifies novel candidate genes. These variants could act as targets for treatment or as factors in disease prediction modeling. The study highlighted the importance of regulatory SNPs in the disease, as several significant SNPs were located within non-coding regions.

Genetic architecture of asthma in African American patients

BACKGROUND

Asthma is a chronic inflammatory disorder with a strong genetic inheritance. Although more than 100 loci were reported through the genome-wide association study of European populations, the genetic underpinning of asthma in African American individuals remains largely elusive.

OBJECTIVE

We aimed to identify genetic loci associated with asthma in African American individuals.

METHODS

Three cohorts were genotyped at the Children's Hospital of Philadelphia by using the Illumina single-nucleotide polymorphism array platform. Genotype imputation was performed by using the Trans-Omics for Precision Medicine (TOPMed) reference panel, which includes whole genome sequencing data from more than 100,000 individuals. A meta-analysis of 3 Children's Hospital of Philadelphia cohorts and 10 Consortium on Asthma among African Ancestry Populations in the Americas cohorts, totaling 19,628 subjects, was conducted to identify genetic loci associated with asthma in African American individuals.

RESULTS

Our study identified 12 loci surpassing the classical genome-wide significance threshold (5 × 10-8). Of those loci, 8 reached the stricter significance threshold (3 × 10-8). The 9p24.1 locus (rs10975467 [P = 1.63 × 10-8]) has previously been associated with asthma in European individuals. Six loci are associated with enhancer activities, 2 loci are in DNase I-hypersensitive regions, and all of them are associated with regulatory motifs. Moreover, the locus 11q13.4 (rs7480008) is an expression quantitative trait locus of XRRA1 in lung (P = 9.4 × 10-10), and the locus 13q14.3 (rs1543525) is a splicing quantitative trait locus of DHRS12 in lung (P = 1.1 × 10-13).

CONCLUSIONS

Our findings provide candidate genetic loci for therapeutic target identification and prioritization for African populations.

CeDAR: incorporating cell type hierarchy improves cell type-specific differential analyses in bulk omics data

Bulk high-throughput omics data contain signals from a mixture of cell types. Recent developments of deconvolution methods facilitate cell type-specific inferences from bulk data. Our real data exploration suggests that differential expression or methylation status is often correlated among cell types. Based on this observation, we develop a novel statistical method named CeDAR to incorporate the cell type hierarchy in cell type-specific differential analyses of bulk data. Extensive simulation and real data analyses demonstrate that this approach significantly improves the accuracy and power in detecting cell type-specific differential signals compared with existing methods, especially in low-abundance cell types.

E3-ubiquitin ligases and recent progress in osteoimmunology

Ubiquitin-mediated proteasomal degradation is a post-transcriptional protein modification that is comprised of various components including the 76-amino acid protein ubiquitin (Ub), Ub-activating enzyme (E1), Ub-conjugating enzyme (E2), ubiquitin ligase (E3), deubiquitinating enzyme (DUB) and proteasome. We and others have recently provided genetic evidence showing that E3-ubiquitin ligases are associated with bone metabolism, the immune system and inflammation through ubiquitylation and subsequent degradation of their substrates. Dysregulation of the E3-ubiquitin ligase RNF146-mediated degradation of the adaptor protein 3BP2 (SH3 domain-binding protein 2) causes cherubism, an autosomal dominant disorder associated with severe inflammatory craniofacial dysmorphia syndrome in children. In this review, on the basis of our discoveries in cherubism, we summarize new insights into the roles of E3-ubiquitin ligases in the development of human disorders caused by an abnormal osteoimmune system by highlighting recent genetic evidence obtained in both human and animal model studies.

Circulating methylation level of HTR2A is associated with inflammation and disease activity in rheumatoid arthritis

Objectives

HTR2A is previously identified as a susceptibility gene for rheumatoid arthritis (RA). In this study, we performed the association analysis between DNA methylation of HTR2A with RA within peripheral blood samples.

Methods

We enrolled peripheral blood samples from 235 patients with RA, 30 osteoarthritis (OA) patients, and 30 healthy controls. The DNA methylation levels of about 218 bp from chr13: 46898190 to chr13: 46897973 (GRCh38/hg38) around HTR2A cg15692052 from patients were analyzed by targeted methylation sequencing.

Results

We measured methylation status for 7 CpGs in the promoter region of HTR2A and obseved overall methylation status are signficantly increased in RA compared with normal inviduals (FDR= 9.05 x 10^-5). The average cg15692052 methylation levels (methylation score) showed a positive correlation with CRP (r=0.15, P=0.023). Compared with the OA group or HC group, the proportion of haplotypes CCCCCCC (FDR=0.02 and 2.81 x 10^-6) is signficantly increased while TTTTTCC (FDR =0.01) and TTTTTTT(FDR =6.92 x 10^-3) are significantly decreased in RA. We find methylation haplotypes combining with RF and CCP could signficantly enhance the performance of the diagnosing RA and its comorbidities (hypertension, interstitial lung disease, and osteoporosis), especially in interstitial lung disease.

Conclusions

In our study, we found signficant hypermethylation of promoter region of HTR2A which indicates the potential clinical diagnostic role in rheumatoid arthritis.

Epigenetic regulation of B cells and its role in autoimmune pathogenesis

B cells play a pivotal role in the pathogenesis of autoimmune diseases. Although previous studies have shown many genetic polymorphisms associated with B-cell activation in patients with various autoimmune disorders, progress in epigenetic research has revealed new mechanisms leading to B-cell hyperactivation. Epigenetic mechanisms, including those involving histone modifications, DNA methylation, and noncoding RNAs, regulate B-cell responses, and their dysregulation can contribute to the pathogenesis of autoimmune diseases. Patients with autoimmune diseases show epigenetic alterations that lead to the initiation and perpetuation of autoimmune inflammation. Moreover, many clinical and animal model studies have shown the promising potential of epigenetic therapies for patients. In this review, we present an up-to-date overview of epigenetic mechanisms with a focus on their roles in regulating functional B-cell subsets. Furthermore, we discuss epigenetic dysregulation in B cells and highlight its contribution to the development of autoimmune diseases. Based on clinical and preclinical evidence, we discuss novel epigenetic biomarkers and therapies for patients with autoimmune disorders.

The Role of Oxidative Stress in Epigenetic Changes Underlying Autoimmunity

Significance: Epigenetic dysregulation plays an important role in the pathogenesis and development of autoimmune diseases. Oxidative stress is associated with autoimmunity and is also known to alter epigenetic mechanisms. Understanding the interplay between oxidative stress and epigenetics will provide insights into the role of environmental triggers in the development of autoimmunity in genetically susceptible individuals. Recent Advances: Abnormal DNA and histone methylation patterns in genes and pathways involved in interferon and tumor necrosis factor signaling, cellular survival, proliferation, metabolism, organ development, and autoantibody production have been described in autoimmunity. Inhibitors of DNA and histone methyltransferases showed potential therapeutic effects in animal models of autoimmune diseases. Oxidative stress can regulate epigenetic mechanisms via effects on DNA damage repair mechanisms, cellular metabolism and the local redox environment, and redox-sensitive transcription factors and pathways. Critical Issues: Studies looking into oxidative stress and epigenetics in autoimmunity are relatively limited. The number of available longitudinal studies to explore the role of DNA methylation in the development of autoimmune diseases is small. Future Directions: Exploring the relationship between oxidative stress and epigenetics in autoimmunity will provide clues for potential preventative measures and treatment strategies. Inception cohorts with longitudinal follow-up would help to evaluate epigenetic marks as potential biomarkers for disease development, progression, and treatment response in autoimmunity. Antioxid. Redox Signal. 36, 423-440.

Analysis of Epigenetic Changes in Vitamin D Pathway Genes in Rheumatoid Arthritis Patients

Background: Rheumatoid arthritis (RA) is an autoimmune inflammatory disease with complex etiopathogenesis launched by multiple risk factors, including epigenetic alterations. RA is possibly linked to vitamin D that is epigenetically active and may alter DNA methylation of certain genes. Therefore, the study aimed to evaluate the relationship between DNA methylation status of vitamin D signaling pathway genes (VDR, CYP24A1, CYP2R1), vitamin D level and associations with RA.Materials and Methods: Totally 76 participants (35 RA patients and 41 healthy controls) were enrolled from a case-control vitamin D and VDR gene polymorphisms study regarding age and vitamin D concentration. CpG islands in promoter regions of the VDR, CYP24A1, CYP2R1 genes were chosen for DNA methylation analysis by means of pyrosequencing. Chemiluminescent microplate immunoassay was used to assess 25(OH)D serum levels. RA clinical data, i.e. the disease activity score C-reactive protein 28 (DAS28 – CRP) as well as patient-reported outcome questionnaires were recorded.Results: The study showed similar methylation pattern in the promoter regions of vitamin D pathway genes in RA and control group with p>0.05 (VDR gene 2.39% vs. 2.48%, CYP24A1 gene 16.02% vs. 15.17% and CYP2R1 2.53% vs. 2.41%). CYP24A1 methylation intensity was significantly higher in compare to methylation intensity of VDR and CYP2R1 genes in both groups (p<0.0001). A tendency of higher vitamin D concentration in cases having methylated VDR (57.57±28.93 vs. 47.40±29.88 nmol/l), CYP24A1 (53.23±26.22 vs. 48.23±34.41 nmol/l) and CYP2R1 (60.41±30.73 vs. 44.54±27.63 nmol/l) genes and a positive correlation between VDR, CYP2R1 methylation intensity and vitamin D level in RA affected participants was revealed (p>0.05). A significantly higher CYP24A1 methylation intensity (p=0.0104) was detected in blood cells of vitamin D deficient (<50 nmol/l) RA patients vs. vitamin D deficient controls.Conclusions: Our data suggests some indirect associations between DNA methylation status of vitamin D pathway genes and vitamin D level in RA.

SETD2-mediated epigenetic regulation of noncanonical Wnt5A during osteoclastogenesis

To define the role of SETD2 in the WNT5a signaling in the context of osteoclastogenesis, we exploited two different models: in vitro osteoclast differentiation, and K/BxN serum-induced arthritis model. We found that SETD2 and WNT5a were upregulated during osteoclast differentiation and after induction of arthritis. Using gain- and loss-of-function approaches in the myeloid cell, we confirmed that SETD2 regulated the osteoclast markers, and WNT5a via modulating active histone marks by enriching H3K36me3, and by reducing repressive H3K27me3 mark. Additionally, during osteoclastic differentiation, the transcription of Wnt5a was also associated with the active histone H3K9 and H4K8 acetylations. Mechanistically, SETD2 directed induction of NF-κβ expression facilitated the recruitment of H3K9Ac and H4K8Ac around the TSS region of the Wnt5a gene, thereby, assisting osteoclast differentiation. Together these findings for the first time revealed that SETD2 mediated epigenetic regulation of Wnt5a plays a critical role in osteoclastogenesis and induced arthritis. Model for the Role of SETD2 dependent regulation of osteoclastic differentiation. A In monocyte cells SETD2-dependent H3K36 trimethylation help to create open chromatin region along with active enhancer mark, H3K27Ac. This chromatin state facilitated the loss of a suppressive H3K27me3 mark. B Additionally, SETD2 mediated induction of NF-κβ expression leads to the recruitment of histone acetyl transferases, P300/PCAF, to the Wnt5a gene and establish H3K9Ac and H4K8Ac marks. Along with other activation marks, these acetylation marks help in Wnt5a transcription which leads to osteoclastogenesis.

Ten Years of EWAS

Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

Dysregulated translational factors and epigenetic regulations orchestrate in B cells contributing to autoimmune diseases

B cells play a crucial role in antigen presentation, antibody production and pro-/anti-inflammatory cytokine secretion in adaptive immunity. Several translational factors including transcription factors and cytokines participate in the regulation of B cell development, with the cooperation of epigenetic regulations. Autoimmune diseases are generally characterized with autoreactive B cells and high-level pathogenic autoantibodies. The success of B cell depletion therapy in mouse model and clinical trials has proven the role of B cells in pathogenesis of autoimmune diseases. The failure of B cell tolerance in immune checkpoints results in accumulated autoreactive naïve B (B_N) cells with aberrant B cell receptor signaling and dysregulated B cell response, contributing to self-antibody-mediated autoimmune reaction. Dysregulation of translational factors and epigenetic alterations in B cells has been demonstrated to correlate with aberrant B cell compartment in autoimmune diseases, such as systemic lupus erythematosus, rheumatoid arthritis, primary Sjögren's syndrome, multiple sclerosis, diabetes mellitus and pemphigus. This review is intended to summarize the interaction of translational factors and epigenetic regulations that are involved with development and differentiation of B cells, and the mechanism of dysregulation in the pathogenesis of autoimmune diseases.

Peripheral blood mononuclear cells are hypomethylated in active rheumatoid arthritis and methylation correlates with disease activity

OBJECTIVE

Epigenetic modifications are dynamic and influence cellular disease activity. The aim of this study was to investigate global DNA methylation in peripheral blood mononuclear cells (PBMCs) of RA patients to clarify whether global DNA methylation pattern testing might be useful in monitoring disease activity as well as the response to therapeutics.

METHODS

Flow cytometric measurement of 5-methyl-cytosine (5'-mC) was established using the cell line U937. In the subsequent prospective study, 62 blood samples were investigated, including 17 healthy donors and 45 RA patients at baseline and after 3 months of treatment with methotrexate, the IL-6 receptor inhibitor sarilumab, and Janus kinase inhibitors. Methylation status was assessed with an anti-5'-mC antibody and analysed in PBMCs and CD4+, CD8+, CD14+ and CD19+ subsets. Signal intensities of 5'-mC were correlated with 28-joint DASs with ESR and CRP (DAS28-ESR and DAS28-CRP).

RESULTS

Compared with healthy individuals, PBMCs of RA patients showed a significant global DNA hypomethylation. Signal intensities of 5'-mC correlated with transcription levels of DNMT1, DNMT3B and MTR genes involved in methylation processes. Using flow cytometry, significant good correlations and linear regression values were achieved in RA patients between global methylation levels and DAS28-ESR values for PBMCs (r = -0.55, P = 0.002), lymphocytes (r = -0.57, P = 0.001), CD4+ (r = -0.57, P = 0.001), CD8+ (r = -0.54, P = 0.001), CD14+ (r = -0.49, P = 0.008) and CD19+ (r = -0.52, P = 0.004) cells.

CONCLUSIONS

The degree of global DNA methylation was found to be associated with disease activity. Based on this novel approach, the degree of global methylation is a promising biomarker for therapy monitoring and the prediction of therapy outcome in inflammatory diseases.

Comparative Analysis on Abnormal Methylome of Differentially Expressed Genes and Disease Pathways in the Immune Cells of RA and SLE

We identified abnormally methylated, differentially expressed genes (DEGs) and pathogenic mechanisms in different immune cells of RA and SLE by comprehensive bioinformatics analysis. Six microarray data sets of each immune cell (CD19⁺ B cells, CD4⁺ T cells and CD14⁺ monocytes) were integrated to screen DEGs and differentially methylated genes by using R package “limma.” Gene ontology annotations and KEGG analysis of aberrant methylome of DEGs were done using DAVID online database. Protein-protein interaction (PPI) network was generated to detect the hub genes and their methylation levels were compared using DiseaseMeth 2.0 database. Aberrantly methylated DEGs in CD19⁺ B cells (173 and 180), CD4⁺ T cells (184 and 417) and CD14⁺ monocytes (193 and 392) of RA and SLE patients were identified. We detected 30 hub genes in different immune cells of RA and SLE and confirmed their expression using FACS sorted immune cells by qPCR. Among them, 12 genes (BPTF, PHC2, JUN, KRAS, PTEN, FGFR2, ALB, SERB-1, SKP2, TUBA1A, IMP3, and SMAD4) of RA and 12 genes (OAS1, RSAD2, OASL, IFIT3, OAS2, IFIH1, CENPE, TOP2A, PBK, KIF11, IFIT1, and ISG15) of SLE are proposed as potential biomarker genes based on receiver operating curve analysis. Our study suggests that MAPK signaling pathway could potentially differentiate the mechanisms affecting T- and B- cells in RA, whereas PI3K pathway may be used for exploring common disease pathways between RA and SLE. Compared to individual data analyses, more dependable and precise filtering of results can be achieved by integrating several relevant data sets.

Nonlinear ridge regression improves cell-type-specific differential expression analysis

BACKGROUND

Epigenome-wide association studies (EWAS) and differential gene expression analyses are generally performed on tissue samples, which consist of multiple cell types. Cell-type-specific effects of a trait, such as disease, on the omics expression are of interest but difficult or costly to measure experimentally. By measuring omics data for the bulk tissue, cell type composition of a sample can be inferred statistically. Subsequently, cell-type-specific effects are estimated by linear regression that includes terms representing the interaction between the cell type proportions and the trait. This approach involves two issues, scaling and multicollinearity.

RESULTS

First, although cell composition is analyzed in linear scale, differential methylation/expression is analyzed suitably in the logit/log scale. To simultaneously analyze two scales, we applied nonlinear regression. Second, we show that the interaction terms are highly collinear, which is obstructive to ordinary regression. To cope with the multicollinearity, we applied ridge regularization. In simulated data, nonlinear ridge regression attained well-balanced sensitivity, specificity and precision. Marginal model attained the lowest precision and highest sensitivity and was the only algorithm to detect weak signal in real data.

CONCLUSION

Nonlinear ridge regression performed cell-type-specific association test on bulk omics data with well-balanced performance. The omicwas package for R implements nonlinear ridge regression for cell-type-specific EWAS, differential gene expression and QTL analyses. The software is freely available from https://github.com/fumi-github/omicwas.

Epigenome wide association study of response to methotrexate in early rheumatoid arthritis patients

Aim

To identify differentially methylated positions (DMPs) and regions (DMRs) that predict response to Methotrexate (MTX) in early rheumatoid arthritis (RA) patients.

Materials and methods

DNA from baseline peripheral blood mononuclear cells was extracted from 72 RA patients. DNA methylation, quantified using the Infinium MethylationEPIC, was assessed in relation to response to MTX (combination) therapy over the first 3 months.

Results

Baseline DMPs associated with response were identified; including hits previously described in RA. Additionally, 1309 DMR regions were observed. However, none of these findings were genome-wide significant. Likewise, no specific pathways were related to response, nor could we replicate associations with previously identified DMPs.

Conclusion

No baseline genome-wide significant differences were identified as biomarker for MTX (combination) therapy response; hence meta-analyses are required.

Biologically Enhanced Genome-Wide Association Study Provides Further Evidence for Candidate Loci and Discovers Novel Loci That Influence Risk of Anterior Cruciate Ligament Rupture in a Dog Model

Anterior cruciate ligament (ACL) rupture is a common condition that disproportionately affects young people, 50% of whom will develop knee osteoarthritis (OA) within 10 years of rupture. ACL rupture exhibits both hereditary and environmental risk factors, but the genetic basis of the disease remains unexplained. Spontaneous ACL rupture in the dog has a similar disease presentation and progression, making it a valuable genomic model for ACL rupture. We leveraged the dog model with Bayesian mixture model (BMM) analysis (BayesRC) to identify novel and relevant genetic variants associated with ACL rupture. We performed RNA sequencing of ACL and synovial tissue and assigned single nucleotide polymorphisms (SNPs) within differentially expressed genes to biological prior classes. SNPs with the largest effects were on chromosomes 3, 5, 7, 9, and 24. Selection signature analysis identified several regions under selection in ACL rupture cases compared to controls. These selection signatures overlapped with genome-wide associations with ACL rupture as well as morphological traits. Notable findings include differentially expressed ACSF3 with MC1R (coat color) and an association on chromosome 7 that overlaps the boundaries of SMAD2 (weight and body size). Smaller effect associations were within or near genes associated with regulation of the actin cytoskeleton and the extracellular matrix, including several collagen genes. The results of the current analysis are consistent with previous work published by our laboratory and others, and also highlight new genes in biological pathways that have not previously been associated with ACL rupture. The genetic associations identified in this study mirror those found in human beings, which lays the groundwork for development of disease-modifying therapies for both species.

Deconvolution of cellular subsets in human tissue based on targeted DNA methylation analysis at individual CpG sites

Background

The complex composition of different cell types within a tissue can be estimated by deconvolution of bulk gene expression profiles or with various single-cell sequencing approaches. Alternatively, DNA methylation (DNAm) profiles have been used to establish an atlas for multiple human tissues and cell types. DNAm is particularly suitable for deconvolution of cell types because each CG dinucleotide (CpG site) has only two states per DNA strand—methylated or non-methylated—and these epigenetic modifications are very consistent during cellular differentiation. So far, deconvolution of DNAm profiles implies complex signatures of many CpGs that are often measured by genome-wide analysis with Illumina BeadChip microarrays. In this study, we investigated if the characterization of cell types in tissue is also feasible with individual cell type-specific CpG sites, which can be addressed by targeted analysis, such as pyrosequencing.

Results

We compiled and curated 579 Illumina 450k BeadChip DNAm profiles of 14 different non-malignant human cell types. A training and validation strategy was applied to identify and test for cell type-specific CpGs. We initially focused on estimating the relative amount of fibroblasts using two CpGs that were either hypermethylated or hypomethylated in fibroblasts. The combination of these two DNAm levels into a “FibroScore” correlated with the state of fibrosis and was associated with overall survival in various types of cancer. Furthermore, we identified hypomethylated CpGs for leukocytes, endothelial cells, epithelial cells, hepatocytes, glia, neurons, fibroblasts, and induced pluripotent stem cells. The accuracy of this eight CpG signature was tested in additional BeadChip datasets of defined cell mixtures and the results were comparable to previously published signatures based on several thousand CpGs. Finally, we established and validated pyrosequencing assays for the relevant CpGs that can be utilized for classification and deconvolution of cell types.

Conclusion

This proof of concept study demonstrates that DNAm analysis at individual CpGs reflects the cellular composition of cellular mixtures and different tissues. Targeted analysis of these genomic regions facilitates robust methods for application in basic research and clinical settings.

DNA methylation signatures of autoimmune diseases in human B lymphocytes

B lymphocytes play key roles in adaptive and innate immunity. In autoimmune diseases, their participation in disease instigation and/or progression has been demonstrated in both experimental models and clinical trials. Recent epigenetic investigations of human B lymphocyte subsets revealed the importance of DNA methylation in exquisitely regulating the cellular activation and differentiation programs. This review discusses recent advances on the potential of DNA methylation to shape events that impart generation of plasma cells and memory B cells, providing novel insight into homeostatic regulation of the immune system. In parallel, epigenetic profiling of B cells from patients with systemic or organo-specific autoimmune diseases disclosed distinctive differential methylation regions that, in some cases, could stratify patients from controls. Development of tools for editing DNA methylation in the mammalian genome could be useful for future functional studies of epigenetic regulation by offering the possibility to edit locus-specific methylation, with potential translational applications.

Latin American Genes: The Great Forgotten in Rheumatoid Arthritis

The successful implementation of personalized medicine will rely on the integration of information obtained at the level of populations with the specific biological, genetic, and clinical characteristics of an individual. However, because genome-wide association studies tend to focus on populations of European descent, there is a wide gap to bridge between Caucasian and non-Caucasian populations before personalized medicine can be fully implemented, and rheumatoid arthritis (RA) is not an exception. In this review, we discuss advances in our understanding of genetic determinants of RA risk among global populations, with a focus on the Latin American population. Geographically restricted genetic diversity may have important implications for health and disease that will remain unknown until genetic association studies have been extended to include Latin American and other currently under-represented ancestries. The next few years will witness many breakthroughs in personalized medicine, including applications for common diseases and risk stratification instruments for targeted prevention/intervention strategies. Not all of these applications may be extrapolated from the Caucasian experience to Latin American or other under-represented populations.

A comprehensive comparison of residue-level methylation levels with the regression-based gene-level methylation estimations by ReGear

MOTIVATION

DNA methylation is a biological process impacting the gene functions without changing the underlying DNA sequence. The DNA methylation machinery usually attaches methyl groups to some specific cytosine residues, which modify the chromatin architectures. Such modifications in the promoter regions will inactivate some tumor-suppressor genes. DNA methylation within the coding region may significantly reduce the transcription elongation efficiency. The gene function may be tuned through some cytosines are methylated.

METHODS

This study hypothesizes that the overall methylation level across a gene may have a better association with the sample labels like diseases than the methylations of individual cytosines. The gene methylation level is formulated as a regression model using the methylation levels of all the cytosines within this gene. A comprehensive evaluation of various feature selection algorithms and classification algorithms is carried out between the gene-level and residue-level methylation levels.

RESULTS

A comprehensive evaluation was conducted to compare the gene and cytosine methylation levels for their associations with the sample labels and classification performances. The unsupervised clustering was also improved using the gene methylation levels. Some genes demonstrated statistically significant associations with the class label, even when no residue-level methylation features have statistically significant associations with the class label. So in summary, the trained gene methylation levels improved various methylome-based machine learning models. Both methodology development of regression algorithms and experimental validation of the gene-level methylation biomarkers are worth of further investigations in the future studies. The source code, example data files and manual are available at http://www.healthinformaticslab.org/supp/.

Clinical value of DNA methylation markers in autoimmune rheumatic diseases

Methylation of cytosine residues in DNA, the best studied epigenetic modification, is associated with gene transcription and nuclear organization, and ultimately the function of a cell. DNA methylation can be influenced by various factors, including changes in neighbouring genomic sites such as those induced by transcription factor binding. The DNA methylation profiles in relevant cell types are altered in most human diseases compared with the healthy state. Given the physical stability of DNA and methylated DNA compared with other epigenetic modifications, DNA methylation is an ideal marker for clinical purposes. However, few DNA methylation-based markers have made it into clinical practice, with the notable exception of some markers used in the field of oncology. Autoimmune rheumatic diseases are genetically complex entities that can vary widely in terms of prognosis, subtypes, progression and treatment responses. Increasing reports showing strong links between DNA methylation profiles and different clinical outcomes and other clinical aspects in autoimmune rheumatic diseases reinforce the usefulness of DNA methylation profiles as novel clinical markers. In this Review, we provide an updated discussion on DNA methylation alterations in autoimmune rheumatic diseases and the advantages and disadvantages of using these markers in clinical practice.

Epigenetic Regulation Mediated by Methylation in the Pathogenesis and Precision Medicine of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a complex disease triggered by the interaction between genetics and the environment, especially through the shared epitope (SE) and cell surface calreticulin (CSC) theory. However, the available evidence shows that genetic diversity and environmental exposure cannot explain all the clinical characteristics and heterogeneity of RA. In contrast, recent studies demonstrate that epigenetics play important roles in the pathogenesis of RA, especially DNA methylation and histone modification. DNA methylation and histone methylation are involved in innate and adaptive immune cell differentiation and migration, proliferation, apoptosis, and mesenchymal characteristics of fibroblast-like synoviocytes (FLS). Epigenetic-mediated regulation of immune-related genes and inflammation pathways explains the dynamic expression network of RA. In this review, we summarize the comprehensive evidence to show that methylation of DNA and histones is significantly involved in the pathogenesis of RA and could be applied as a promising biomarker in the disease progression and drug-response prediction. We also explain the advantages and challenges of the current epigenetics research in RA. In summary, epigenetic modules provide a possible interface through which genetic and environmental risk factors connect to contribute to the susceptibility and pathogenesis of RA. Additionally, epigenetic regulators provide promising drug targets to develop novel therapeutic drugs for RA. Finally, DNA methylation and histone modifications could be important features for providing a better RA subtype identification to accelerate personalized treatment and precision medicine.

Systemic Investigation of Promoter-wide Methylome and Genome Variations in Gout

Current knowledge of gout centers on hyperuricemia. Relatively little is known regarding the pathogenesis of gouty inflammation. To investigate the epigenetic background of gouty inflammation independent of hyperuricemia and its relationship to genetics, 69 gout patients and 1455 non-gout controls were included. Promoter-wide methylation was profiled with EPIC array. Whole-genome sequencing data were included for genetic and methylation quantitative trait loci (meQTL) analyses and causal inference tests. Identified loci were subjected to co-methylation analysis and functional localization with DNase hypersensitivity and histone marks analysis. An expression database was queried to clarify biologic functions of identified loci. A transcription factor dataset was integrated to identify transcription factors coordinating respective expression. In total, seven CpG loci involved in interleukin-1β production survived genetic/meQTL analyses, or causal inference tests. None had a significant relationship with various metabolic traits. Additional analysis suggested gouty inflammation, instead of hyperuricemia, provides the link between these CpG sites and gout. Six (PGGT1B, INSIG1, ANGPTL2, JNK1, UBAP1, and RAPTOR) were novel genes in the field of gout. One (CNTN5) was previously associated with gouty inflammation. Transcription factor mapping identified several potential transcription factors implicated in the link between differential methylation, interleukin-1β production, and gouty inflammation. In conclusion, this study revealed several novel genes specific to gouty inflammation and provided enhanced insight into the biological basis of gouty inflammation.

Detection and Comparative Analysis of Methylomic Biomarkers of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a common autoimmune disorder influenced by both genetic and environmental factors. To investigate possible contributions of DNA methylation to the etiology of RA with minimum confounding genetic heterogeneity, we investigated genome-wide DNA methylation in disease-discordant monozygotic twin pairs. This study hypothesized that methylomic biomarkers might facilitate accurate RA detection. A comprehensive series of biomarker detection algorithms were utilized to find the best methylomic biomarkers for detecting RA patients using the methylomic data of the peripheral blood samples. The best model achieved 100.00% in accuracy (Acc) with 81 methylomic biomarkers and a 10-fold cross-validation (10FCV) strategy. Some of the methylomic biomarkers were experimentally confirmed to be associated with the onset or development of RA. It is also interesting to observe that many of the detected biomarkers were from chromosome Y, supporting the knowledge that RA has a significant gender discrepancy.

Integration of single nucleotide variants and whole-genome DNA methylation profiles for classification of rheumatoid arthritis cases from controls

This study evaluated the use of multiomics data for classification accuracy of rheumatoid arthritis (RA). Three approaches were used and compared in terms of prediction accuracy: (1) whole-genome prediction (WGP) using SNP marker information only, (2) whole-methylome prediction (WMP) using methylation profiles only, and (3) whole-genome/methylome prediction (WGMP) with combining both omics layers. The number of SNP and of methylation sites varied in each scenario, with either 1, 10, or 50% of these preselected based on four approaches: randomly, evenly spaced, lowest p value (genome-wide association or epigenome-wide association study), and estimated effect size using a Bayesian ridge regression (BRR) model. To remove effects of high levels of pairwise linkage disequilibrium (LD), SNPs were also preselected with an LD-pruning method. Five Bayesian regression models were studied for classification, including BRR, Bayes-A, Bayes-B, Bayes-C, and the Bayesian LASSO. Adjusting methylation profiles for cellular heterogeneity within whole blood samples had a detrimental effect on the classification ability of the models. Overall, WGMP using Bayes-B model has the best performance. In particular, selecting SNPs based on LD-pruning with 1% of the methylation sites selected based on BRR included in the model, and fitting the most significant SNP as a fixed effect was the best method for predicting disease risk with a classification accuracy of 0.975. Our results showed that multiomics data can be used to effectively predict the risk of RA and identify cases in early stages to prevent or alter disease progression via appropriate interventions.

Single-cell technologies - studying rheumatic diseases one cell at a time

Cells, the basic units of life, have striking differences at transcriptomic, proteomic and epigenomic levels across tissues, organs, organ systems and organisms. The coordination of individual immune cells is essential for the generation of effective immune responses to pathogens while immune tolerance is maintained to protect the host. In rheumatic diseases, when immune responses are dysregulated, pathologically important cells might represent only a small fraction of the immune system. Interrogation of the contributions of individual immune cells to pathogenesis and disease progression should therefore reveal important insights into the complicated aetiology of rheumatic diseases. Technological advances are enabling the high-dimensional dissection of single cells at multiple omics levels, which could facilitate the identification of dysregulated molecular mechanisms in patients with rheumatic diseases and the discovery of new therapeutic targets and biomarkers. The single-cell technologies that have been developed over the past decade and the experimental platforms that enable multi-omics integrative analyses have already made inroads into immunology-related fields of study and have potential for use in rheumatology. Layers of omics data derived from single cells are likely to fundamentally change our understanding of the molecular pathways that underpin the pathogenesis of rheumatic diseases.

Lymphocyte DNA methylation mediates genetic risk at shared immune-mediated disease loci

Background

Defining regulatory mechanisms through which noncoding risk variants influence the cell-mediated pathogenesis of immune-mediated disease (IMD) has emerged as a priority in the post–genome-wide association study era.

Objectives

With a focus on rheumatoid arthritis, we sought new insight into genetic mechanisms of adaptive immune dysregulation to help prioritize molecular pathways for targeting in this and related immune pathologies.

Methods

Whole-genome methylation and transcriptional data from isolated CD4⁺ T cells and B cells of more than 100 genotyped and phenotyped patients with inflammatory arthritis, all of whom were naive to immunomodulatory treatments, were obtained. Analysis integrated these comprehensive data with genome-wide association study findings across IMDs and other publicly available resources.

Results

We provide strong evidence that disease-associated DNA variants regulate cis-CpG methylation in CD4⁺ T and/or B cells at 37% RA loci. Using paired, cell-specific transcriptomic data and causal inference testing, we identify examples where site-specific DNA methylation in turn mediates gene expression, including FCRL3 in both cell types and ORMDL3/GSDMB, IL6ST/ANKRD55, and JAZF1 in CD4⁺ T cells. A number of genes regulated in this way highlight mechanisms common to RA and other IMDs including multiple sclerosis and asthma, in turn distinguishing them from osteoarthritis, a primarily degenerative disease. Finally, we corroborate the observed effects experimentally.

Conclusions

Our observations highlight important mechanisms of genetic risk in RA and the wider context of immune dysregulation. They confirm the utility of DNA methylation profiling as a tool for causal gene prioritization and, potentially, therapeutic targeting in complex IMD.

The B side of rheumatoid arthritis pathogenesis

In the last years, a dramatic amount of research has been performedincreasing the knowledge about the biological mechanism underpinning Rheumatoid Arthritis (RA) inflammation, putting B lymphocytes in the center of RA pathogenesis. Nowadays, B cell phenotypes and autoantibodies positivity arose as important biomarkers in early and long-standing disease. Moreover, comparative analysis of peripheral blood and synovial tissue compartments enables the identification of novel physiopathological mechanisms promoting inflammation. In this narrative review we will discuss the biological relevance of B cell derived autoimmunity and in RA course, from disease onset to remission achievement.

Identification and Characterization of Post-activated B Cells in Systemic Autoimmune Diseases

Autoimmune diseases (AID) such as systemic lupus erythematosus (SLE), primary Sjögren's syndrome (pSS), and rheumatoid arthritis (RA) are chronic inflammatory diseases in which abnormalities of B cell function play a central role. Although it is widely accepted that autoimmune B cells are hyperactive in vivo, a full understanding of their functional status in AID has not been delineated. Here, we present a detailed analysis of the functional capabilities of AID B cells and dissect the mechanisms underlying altered B cell function. Upon BCR activation, decreased spleen tyrosine kinase (Syk) and Bruton's tyrosine kinase (Btk) phosphorylation was noted in AID memory B cells combined with constitutive co-localization of CD22 and protein tyrosine phosphatase (PTP) non-receptor type 6 (SHP-1) along with hyporesponsiveness to TLR9 signaling, a Syk-dependent response. Similar BCR hyporesponsiveness was also noted specifically in SLE CD27⁻ B cells together with increased PTP activities and increased transcripts for PTPN2, PTPN11, PTPN22, PTPRC, and PTPRO in SLE B cells. Additional studies revealed that repetitive BCR stimulation of normal B cells can induce BCR hyporesponsiveness and that tissue-resident memory B cells from AID patients also exhibited decreased responsiveness immediately ex vivo, suggesting that the hyporesponsive status can be acquired by repeated exposure to autoantigen(s) in vivo. Functional studies to overcome B cell hyporesponsiveness revealed that CD40 co-stimulation increased BCR signaling, induced proliferation, and downregulated PTP expression (PTPN2, PTPN22, and receptor-type PTPs). The data support the conclusion that hyporesponsiveness of AID and especially SLE B cells results from chronic in vivo stimulation through the BCR without T cell help mediated by CD40–CD154 interaction and is manifested by decreased phosphorylation of BCR-related proximal signaling molecules and increased PTPs. The hyporesponsiveness of AID B cells is similar to a form of functional anergy.

Epigenetic Changes in the Pathogenesis of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease that affects about 1% of the world’s population. The etiology of RA remains unknown. It is considered to occur in the presence of genetic and environmental factors. An increasing body of evidence pinpoints that epigenetic modifications play an important role in the regulation of RA pathogenesis. Epigenetics causes heritable phenotype changes that are not determined by changes in the DNA sequence. The major epigenetic mechanisms include DNA methylation, histone proteins modifications and changes in gene expression caused by microRNAs and other non-coding RNAs. These modifications are reversible and could be modulated by diet, drugs, and other environmental factors. Specific changes in DNA methylation, histone modifications and abnormal expression of non-coding RNAs associated with RA have already been identified. This review focuses on the role of these multiple epigenetic factors in the pathogenesis and progression of the disease, not only in synovial fibroblasts, immune cells, but also in the peripheral blood of patients with RA, which clearly shows their high diagnostic potential and promising targets for therapy in the future.

Integrative analysis of DNA methylation in discordant twins unveils distinct architectures of systemic sclerosis subsets

Background

Systemic sclerosis (SSc) is a rare autoimmune fibrosing disease with an incompletely understood genetic and non-genetic etiology. Defining its etiology is important to allow the development of effective predictive, preventative, and therapeutic strategies. We conducted this epigenomic study to investigate the contributions of DNA methylation to the etiology of SSc while minimizing confounding due to genetic heterogeneity.

Methods

Genomic methylation in whole blood from 27 twin pairs discordant for SSc was assayed over 450 K CpG sites. In silico integration with reported differentially methylated cytosines, differentially expressed genes, and regulatory annotation was conducted to validate and interpret the results.

Results

A total of 153 unique cytosines in limited cutaneous SSc (lcSSc) and 266 distinct sites in diffuse cutaneous SSc (dcSSc) showed suggestive differential methylation levels in affected twins. Integration with available data revealed 76 CpGs that were also differentially methylated in blood cells from lupus patients, suggesting their role as potential epigenetic blood biomarkers of autoimmunity. It also revealed 27 genes with concomitant differential expression in blood from SSc patients, including IFI44L and RSAD2. Regulatory annotation revealed that dcSSc-associated CpGs (but not lcSSc) are enriched at Encyclopedia of DNA Elements-, Roadmap-, and BLUEPRINT-derived regulatory regions, supporting their potential role in disease presentation. Notably, the predominant enrichment of regulatory regions in monocytes and macrophages is consistent with the role of these cells in fibrosis, suggesting that the observed cellular dysregulation might be, at least partly, due to altered epigenetic mechanisms of these cells in dcSSc.

Conclusions

These data implicate epigenetic changes in the pathogenesis of SSc and suggest functional mechanisms in SSc etiology.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0652-y) contains supplementary material, which is available to authorized users.

Identification of differentially methylated cell types in epigenome-wide association studies

An outstanding challenge of epigenome-wide association studies (EWASs) performed in complex tissues is the identification of the specific cell type(s) responsible for the observed differential DNA methylation. Here we present a statistical algorithm called CellDMC ( https://github.com/sjczheng/EpiDISH ), which can identify differentially methylated positions and the specific cell type(s) driving the differential methylation. We validated CellDMC on in silico mixtures of DNA methylation data generated with different technologies, as well as on real mixtures from epigenome-wide association and cancer epigenome studies. CellDMC achieved over 90% sensitivity and specificity in scenarios where current state-of-the-art methods did not identify differential methylation. By applying CellDMC to an EWAS performed in buccal swabs, we identified smoking-associated differentially methylated positions occurring in the epithelial compartment, which we validated in smoking-related lung cancer. CellDMC may be useful in the identification of causal DNA-methylation alterations in disease.

Genome-wide DNA methylation changes in CD19+ B cells from relapsing-remitting multiple sclerosis patients

Multiple Sclerosis (MS) is an inflammatory and neurodegenerative disease of the central nervous system. The inflammatory process in MS is driven by both T and B cells and current therapies are targeted to each of these cell types. Epigenetic mechanisms may provide a valuable link between genes and environment. DNA methylation is the best studied epigenetic mechanism and is recognized as a potential contributor to MS risk. The objective of this study was to identify DNA methylation changes associated with MS in CD19+ B-cells. We performed an epigenome-wide association analysis of DNA methylation in the CD19+ B-cells from 24 patients with relapsing-remitting MS on various treatments and 24 healthy controls using Illumina 450 K arrays. A large differentially methylated region (DMR) was observed at the lymphotoxin alpha (LTA) locus. This region was hypermethylated and contains 19 differentially methylated positions (DMPs) spanning 860 bp, all of which are located within the transcriptional start site. We also observed smaller DMRs at 4 MS-associated genes: SLC44A2, LTBR, CARD11 and CXCR5. These preliminary findings suggest that B-cell specific DNA-methylation may be associated with MS risk or response to therapy, specifically at the LTA locus. Development of B-cell specific epigenetic therapies is an attractive new avenue of research in MS treatment. Further studies are now required to validate these findings and understand their functional significance.

Increased DNA methylation variability in rheumatoid arthritis-discordant monozygotic twins

BACKGROUND

Rheumatoid arthritis is a common autoimmune disorder influenced by both genetic and environmental factors. Epigenome-wide association studies can identify environmentally mediated epigenetic changes such as altered DNA methylation, which may also be influenced by genetic factors. To investigate possible contributions of DNA methylation to the aetiology of rheumatoid arthritis with minimum confounding genetic heterogeneity, we investigated genome-wide DNA methylation in disease-discordant monozygotic twin pairs.

METHODS

Genome-wide DNA methylation was assessed in 79 monozygotic twin pairs discordant for rheumatoid arthritis using the HumanMethylation450 BeadChip array (Illumina). Discordant twins were tested for both differential DNA methylation and methylation variability between rheumatoid arthritis and healthy twins. The methylation variability signature was then compared with methylation variants from studies of other autoimmune diseases and with an independent healthy population.

RESULTS

We have identified a differentially variable DNA methylation signature that suggests multiple stress response pathways may be involved in the aetiology of the disease. This methylation variability signature also highlighted potential epigenetic disruption of multiple RUNX3 transcription factor binding sites as being associated with disease development. Comparison with previously performed epigenome-wide association studies of rheumatoid arthritis and type 1 diabetes identified shared pathways for autoimmune disorders, suggesting that epigenetics plays a role in autoimmunity and offering the possibility of identifying new targets for intervention.

CONCLUSIONS

Through genome-wide analysis of DNA methylation in disease-discordant monozygotic twins, we have identified a differentially variable DNA methylation signature, in the absence of differential methylation in rheumatoid arthritis. This finding supports the importance of epigenetic variability as an emerging component in autoimmune disorders.

An integrated -omics analysis of the epigenetic landscape of gene expression in human blood cells

Background

Gene expression can be influenced by DNA methylation 1) distally, at regulatory elements such as enhancers, as well as 2) proximally, at promoters. Our current understanding of the influence of distal DNA methylation changes on gene expression patterns is incomplete. Here, we characterize genome-wide methylation and expression patterns for ~ 13 k genes to explore how DNA methylation interacts with gene expression, throughout the genome.

Results

We used a linear mixed model framework to assess the correlation of DNA methylation at ~ 400 k CpGs with gene expression changes at ~ 13 k transcripts in two independent datasets from human blood cells. Among CpGs at which methylation significantly associates with transcription (eCpGs), > 50% are distal (> 50 kb) or trans (different chromosome) to the correlated gene. Many eCpG-transcript pairs are consistent between studies and ~ 90% of neighboring eCpGs associate with the same gene, within studies. We find that enhancers (P < 5e-18) and microRNA genes (P = 9e-3) are overrepresented among trans eCpGs, and insulators and long intergenic non-coding RNAs are enriched among cis and distal eCpGs. Intragenic-eCpG-transcript correlations are negative in 60–70% of occurrences and are enriched for annotated gene promoters and enhancers (P < 0.002), highlighting the importance of intragenic regulation. Gene Ontology analysis indicates that trans eCpGs are enriched for transcription factor genes and chromatin modifiers, suggesting that some trans eCpGs represent the influence of gene networks and higher-order transcriptional control.

Conclusions

This work sheds new light on the interplay between epigenetic changes and gene expression, and provides useful data for mining biologically-relevant results from epigenome-wide association studies.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4842-3) contains supplementary material, which is available to authorized users.

Epigenome-wide association studies for systemic autoimmune diseases: The road behind and the road ahead

Epigenetics is known to be an important mechanism in the pathogenesis of autoimmune diseases. Epigenetic variations can act as integrators of environmental and genetic exposures and propagate activated states in immune cells. Studying epigenetic alterations by means of genome-wide approaches promises to unravel novel molecular mechanisms related to disease etiology, disease progression, clinical manifestations and treatment responses. This paper reviews what we have learned in the last five years from epigenome-wide studies for three systemic autoimmune diseases, namely systemic lupus erythematosus, primary Sjögren's syndrome, and rheumatoid arthritis. We examine the degree of epigenetic sharing between different diseases and the possible mediating role of epigenetic associations in genetic and environmental risks. Finally, we also shed light into the use of epigenetic markers towards a better precision medicine regarding disease prediction, prevention and personalized treatment in systemic autoimmunity.

The Role of Epigenetics in Type 1 Diabetes

PURPOSE OF REVIEW

Epigenetics is defined as mitotically heritable changes in gene expression that do not directly alter the DNA sequence. By implication, such epigenetic changes are non-genetically determined, although they can be affected by inherited genetic variation. Extensive evidence indicates that autoimmune diseases including type 1 diabetes are determined by the interaction of genetic and non-genetic factors. Much is known of the genetic causes of these diseases, but the non-genetic effects are less clear-cut. Further, it remains unclear how they interact to cause the destructive autoimmune process. This review identifies the key issues in the genetic/non-genetic interaction, examining the most recent evidence of the role of non-genetic effects in the disease process, including the impact of epigenetic effects on key pathways.

RECENT FINDINGS

Recent research indicates that these pathways likely involve immune effector cells both of the innate and adaptive immune response. Specifically, there is evidence of cell type-specific enrichment in altered DNA methylation, changes which were temporally stable and enriched at gene regulatory elements. Epigenomics remains in its infancy, and we anticipate further studies will define how the interaction of genetic and non-genetic effects induces tissue-specific destruction and enhances our ability to predict, and possibly even modify that process.