DNA methylation as a marker of response in rheumatoid arthritis

Exploring the Mechanism of Topical Application of Clematis Florida in the Treatment of Rheumatoid Arthritis through Network Pharmacology and Experimental Validation

Clematis Florida (CF) is a folk medicinal herb in the southeast of China, which is traditionally used for treating osteoarticular diseases. However, the mechanism of its action remains unclear. The present study used network pharmacology and experimental validation to explore the mechanism of CF in the treatment of rheumatoid arthritis (RA). Liquid chromatography-mass spectrometry (LC-MS/MS) identified 50 main compounds of CF; then, their targets were obtained from TCMSP, ETCM, ITCM, and SwissTargetPrediction databases. RA disease-related targets were obtained from DisGeNET, OMIM, and GeneCards databases, and 99 overlapped targets were obtained using a Venn diagram. The protein-protein interaction network (PPI), the compound-target network (CT), and the compound-potential target genes-signaling pathways network (CPS) were constructed and analyzed. The results showed that the core compounds were screened as oleanolic acid, oleic acid, ferulic acid, caffeic acid, and syringic acid. The core therapeutic targets were predicted via network pharmacology analysis as PTGS2 (COX-2), MAPK1, NF-κB1, TNF, and RELA, which belong to the MAPK signaling pathway and NF-κB signaling pathway. The animal experiments indicated that topical application of CF showed significant anti-inflammatory activity in a mouse model of xylene-induced ear edema and had strong analgesic effect on acetic acid-induced writhing. Furthermore, in the rat model of adjuvant arthritis (AA), topical administration of CF was able to alleviate toe swelling and ameliorate joint damage. The elevated serum content levels of IL-6, COX-2, TNF-α, IL-1β, and RF caused by adjuvant arthritis were reduced by CF treatment. Western blotting tests showed that CF may regulate the ERK and NF-κB pathway. The results provide a new perspective for the topical application of CF for treatment of RA.

Identification of cell-specific epigenetic patterns associated with chondroitin sulfate treatment response in an endemic arthritis, Kashin-Beck disease

Aims

To assess the alterations in cell-specific DNA methylation associated with chondroitin sulphate response using peripheral blood collected from Kashin-Beck disease (KBD) patients before initiation of chondroitin sulphate treatment.

Methods

Peripheral blood samples were collected from KBD patients at baseline of chondroitin sulphate treatment. Methylation profiles were generated using reduced representation bisulphite sequencing (RRBS) from peripheral blood. Differentially methylated regions (DMRs) were identified using MethylKit, while DMR-related genes were defined as those annotated to the gene body or 2.2-kilobase upstream regions of DMRs. Selected DMR-related genes were further validated by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) to assess expression levels. Tensor composition analysis was performed to identify cell-specific differential DNA methylation from bulk tissue.

Results

This study revealed 21,060 hypermethylated and 44,472 hypomethylated DMRs, and 13,194 hypermethylated and 22,448 hypomethylated CpG islands for differential global methylation for chondroitin sulphate treatment response. A total of 12,666 DMR-related genes containing DMRs were identified in their promoter regions, such as CHL1 (false discovery rate (FDR) = 2.11 × 10-11), RIC8A (FDR = 7.05 × 10-4), and SOX12 (FDR = 1.43 × 10-3). Additionally, RIC8A and CHL1 were hypermethylated in responders, while SOX12 was hypomethylated in responders, all showing decreased gene expression. The patterns of cell-specific differential global methylation associated with chondroitin sulphate response were observed. Specifically, we found that DMRs located in TESPA1 and ATP11A exhibited differential DNA methylation between responders and non-responders in granulocytes, monocytes, and B cells.

Conclusion

Our study identified cell-specific changes in DNA methylation associated with chondroitin sulphate response in KBD patients.

DNA Methylation Signatures of Response to Conventional Synthetic and Biologic Disease-Modifying Antirheumatic Drugs (DMARDs) in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a complex condition that displays heterogeneity in disease severity and response to standard treatments between patients. Failure rates for conventional, target synthetic, and biologic disease-modifying rheumatic drugs (DMARDs) are significant. Although there are models for predicting patient response, they have limited accuracy, require replication/validation, or for samples to be obtained through a synovial biopsy. Thus, currently, there are no prediction methods approved for routine clinical use. Previous research has shown that genetics and environmental factors alone cannot explain the differences in response between patients. Recent studies have demonstrated that deoxyribonucleic acid (DNA) methylation plays an important role in the pathogenesis and disease progression of RA. Importantly, specific DNA methylation profiles associated with response to conventional, target synthetic, and biologic DMARDs have been found in the blood of RA patients and could potentially function as predictive biomarkers. This review will summarize and evaluate the evidence for DNA methylation signatures in treatment response mainly in blood but also learn from the progress made in the diseased tissue in cancer in comparison to RA and autoimmune diseases. We will discuss the benefits and challenges of using DNA methylation signatures as predictive markers and the potential for future progress in this area.

Identification of Cell-Specific Differential DNA Methylation Associated With Methotrexate Treatment Response in Rheumatoid Arthritis

OBJECTIVE

We undertook this study to estimate changes in cell-specific DNA methylation (DNAm) associated with methotrexate (MTX) response using whole blood samples collected from rheumatoid arthritis (RA) patients before and after initiation of MTX treatment.

METHODS

Patients included in this study were from the Rheumatoid Arthritis Medication Study (n = 66) and the University of California San Francisco Rheumatoid Arthritis study (n = 11). All patients met the American College of Rheumatology RA classification criteria. Blood samples were collected at baseline and following treatment. Disease Activity Scores in 28 joints using the C-reactive protein level were collected at baseline and after 3-6 months of treatment with MTX. Methylation profiles were generated using the Illumina Infinium HumanMethylation450 and MethylationEPIC v1.0 BeadChip arrays using DNA from whole blood. MTX response was defined using the EULAR response criteria (responders showed good/moderate response; nonresponders showed no response). Differentially methylated positions were identified using the Limma software package and Tensor Composition Analysis, which is a method for identifying cell-specific differential DNAm at the CpG level from tissue-level ("bulk") data. Differentially methylated regions were identified using Comb-p software.

RESULTS

We found evidence of differential global methylation between treatment response groups. Further, we found patterns of cell-specific differential global methylation associated with MTX response. After correction for multiple testing, 1 differentially methylated position was associated with differential DNAm between responders and nonresponders at baseline in CD4+ T cells, CD8+ T cells, and natural killer cells. Thirty-nine cell-specific differentially methylated regions associated with MTX treatment response were identified. There were no significant findings in analyses of whole blood samples.

CONCLUSION

We identified cell-specific changes in DNAm that were associated with MTX treatment response in RA patients. Future studies of DNAm and MTX treatment response should include measurements of DNAm from sorted cells.

Differential expression and correlation of immunoregulation related piRNA in rheumatoid arthritis

Background

Although PIWI-interacting RNAs (piRNAs) have recently been associated with germline development and many human diseases, their expression pattern and relationship in autoimmune diseases remain indistinct. This study aimed to investigate the presence and correlation of piRNAs in rheumatoid arthritis (RA).

Methods

We first analyzed the expression profile of piRNAs using small RNA sequencing in peripheral leukocytes of three new-onset untreated RA patients and three healthy controls (HCs). We then selected piRNAs related to immunoregulation by bioinformatics analysis and verified them in 42 new-onset RA patients and 81 HCs by RT-qPCR. Furthermore, a receiver operating characteristic curve was generated to quantify the diagnostic performance of these piRNAs. A correlation analysis was conducted to observe the link between piRNA expression and RA clinical characteristics.

Results

A total of 15 upregulated and 9 downregulated piRNAs among 1,565 known piRNAs were identified in peripheral leukocytes of RA patients. Dysregulated piRNAs were enriched in numerous pathways related to immunity. After selection and validation, two immunoregulation piRNAs (piR-hsa-27620 and piR-hsa-27124) were significantly elevated in RA patients and have good abilities to distinguish patients from controls, which have the potential to serve as biomarkers. PIWI and other proteins implicated in the piRNA pathway were also associated with RA.

Targeting epigenetic regulators for inflammation: Mechanisms and intervention therapy

Emerging evidence indicates that resolution of inflammation is a critical and dynamic endogenous process for host tissues defending against external invasive pathogens or internal tissue injury. It has long been known that autoimmune diseases and chronic inflammatory disorders are characterized by dysregulated immune responses, leading to excessive and uncontrol tissue inflammation. The dysregulation of epigenetic alterations including DNA methylation, posttranslational modifications to histone proteins, and noncoding RNA expression has been implicated in a host of inflammatory disorders and the immune system. The inflammatory response is considered as a critical trigger of epigenetic alterations that in turn intercede inflammatory actions. Thus, understanding the molecular mechanism that dictates the outcome of targeting epigenetic regulators for inflammatory disease is required for inflammation resolution. In this article, we elucidate the critical role of the nuclear factor‐κB signaling pathway, JAK/STAT signaling pathway, and the NLRP3 inflammasome in chronic inflammatory diseases. And we formulate the relationship between inflammation, coronavirus disease 2019, and human cancers. Additionally, we review the mechanism of epigenetic modifications involved in inflammation and innate immune cells. All that matters is that we propose and discuss the rejuvenation potential of interventions that target epigenetic regulators and regulatory mechanisms for chronic inflammation‐associated diseases to improve therapeutic outcomes.

Biomarkers to Predict DMARDs Efficacy and Adverse Effect in Rheumatoid Arthritis

Rheumatoid arthritis (RA), one of the most common immune system diseases, mainly affects middle-aged and elderly individuals and has a serious impact on the quality of life of patients. Pain and disability caused by RA are significant symptoms negatively affecting patients, and they are especially seen when inappropriate treatment is administered. Effective therapeutic strategies have evolved over the past few decades, with many new disease-modifying antirheumatic drugs (DMARDs) being used in the clinic. Owing to the breakthrough in the treatment of RA, the symptoms of patients who could not be treated effectively in the past few years have been relieved. However, some patients complain about symptoms that have not been reported, implying that there are still some limitations in the RA treatment and evaluation system. In recent years, biomarkers, an effective means of diagnosing and evaluating the condition of patients with RA, have gradually been used in clinical practice to evaluate the therapeutic effect of RA, which is constantly being improved for accurate application of treatment in patients with RA. In this article, we summarize a series of biomarkers that may be helpful in evaluating the therapeutic effect and improving the efficiency of clinical treatment for RA. These efforts may also encourage researchers to devote more time and resources to the study and application of biomarkers, resulting in a new evaluation system that will reduce the inappropriate use of DMARDs, as well as patients’ physical pain and financial burden.

A review of liquid biopsy as a tool to assess epigenetic, cfDNA and miRNA variability as methotrexate response predictors in patients with rheumatoid arthritis

Rheumatoid arthritis (RA) is a common autoimmune inflammatory disease affecting 0.5-1% of adults worldwide. Achieving long term remission or low disease activity is possible through early diagnosis, rapid initiation of disease modifying anti-rheumatic drugs (DMARDs) and implementation of a treat to target approach. Initial DMARD therapy usually involves methotrexate (MTX), either alone or in combination with other agents, however 40% of RA patients do not respond adequately, putting them at risk of disease progression and unnecessary exposure to MTX related adverse effects. Early predictors of MTX response would therefore enable a more personalized treatment strategy, ensuring timely access to MTX for those likely to respond and importantly, early initiation of alternative treatment for those in which MTX is unlikely to be efficacious. Predicting response to treatment will most likely require consideration of the clinical characteristics of the patient and interrogation of a number of factors including genetic, epigenetic, cell free DNA (cfDNA) and microRNA (miRNA), all of which can be investigated through blood derived liquid biopsies. This review will summarize the existing literature examining the use of epigenetic factors, cfDNA and miRNA as response predictors among RA patients treated with MTX.

Disruptive Selection of Human Immunostimulatory and Immunosuppressive Genes Both Provokes and Prevents Rheumatoid Arthritis, Respectively, as a Self-Domestication Syndrome

Using our previously published Web service SNP_TATA_Comparator, we conducted a genome-wide study of single-nucleotide polymorphisms (SNPs) within core promoters of 68 human rheumatoid arthritis (RA)-related genes. Using 603 SNPs within 25 genes clinically associated with RA-comorbid disorders, we predicted 84 and 70 candidate SNP markers for overexpression and underexpression of these genes, respectively, among which 58 and 96 candidate SNP markers, respectively, can relieve and worsen RA as if there is a neutral drift toward susceptibility to RA. Similarly, we predicted natural selection toward susceptibility to RA for 8 immunostimulatory genes (e.g., IL9R) and 10 genes most often associated with RA (e.g., NPY). On the contrary, using 25 immunosuppressive genes, we predicted 70 and 109 candidate SNP markers aggravating and relieving RA, respectively (e.g., IL1R2 and TGFB2), suggesting that natural selection can simultaneously additionally yield resistance to RA. We concluded that disruptive natural selection of human immunostimulatory and immunosuppressive genes is concurrently elevating and reducing the risk of RA, respectively. So, we hypothesize that RA in human could be a self-domestication syndrome referring to evolution patterns in domestic animals. We tested this hypothesis by means of public RNA-Seq data on 1740 differentially expressed genes (DEGs) of pets vs. wild animals (e.g., dogs vs. wolves). The number of DEGs in the domestic animals corresponding to worsened RA condition in humans was significantly larger than that in the related wild animals (10 vs. 3). Moreover, much less DEGs in the domestic animals were accordant to relieved RA condition in humans than those in the wild animals (1 vs. 8 genes). This indicates that the anthropogenic environment, in contrast to a natural one, affects gene expression across the whole genome (e.g., immunostimulatory and immunosuppressive genes) in a manner that likely contributes to RA. The difference in gene numbers is statistically significant as confirmed by binomial distribution (p < 0.01), Pearson's χ² (p < 0.01), and Fisher's exact test (p < 0.05). This allows us to propose RA as a candidate symptom within a self-domestication syndrome. Such syndrome might be considered as a human's payment with health for the benefits received during evolution.

Treatment expectations as a possible prognostic factor for DMARD response in rheumatoid arthritis: a prospective cohort study

Background:

The prediction of the individual’s response to disease modifying antirheumatic drugs (DMARDs) in rheumatoid arthritis (RA) is challenging and often limited. Here we evaluated the influence of patients’ expectations towards a change in treatment with DMARD on clinical outcome in RA.

Methods:

One hundred patients (74 female) with RA (2010 ACR/EULAR classification criteria) and an upcoming change in DMARD treatment due to non-response or adverse effects were included. Patients’ treatment beliefs, health-related quality of life and treatment expectations were measured using the Beliefs about Medicines Questionnaire (BMQ), the Short Form 36, and self-designed questions about expectations before treatment initiation (T0), and DAS28-CRP was calculated at T0 and after 4 months (T4). Associations between patients’ beliefs and expectations and changes in DAS28-CRP (T0 to T4, ΔDAS28-CRP) were explored by regression analyses after multiple imputation.

Results:

A total of 99 patients were included, of whom 84 completed all questionnaires. Thirty-six percent of all variability in treatment response (ΔDAS28-CRP) was explained by expectations assessed with the questionnaires and the C-reactive protein (CRP)-value at T0. Among these, the expected improvement rate, with 10.5%, as well as the CRP-value at T0, with 10.6%, had the greatest positive effect whereas the fear of adverse effects, with 11.4%, and the BMQ.concern scale, with 9.0%, had the greatest negative impact on ΔDAS28.

Conclusion:

Patients’ expectations towards newly induced DMARD therapies influence clinical response and may serve as possible explanatory factors for treatment response affecting subjective and objective outcome parameters.

Clinical trial registration number:

DRKS00017005

Novel Insights Into Rheumatoid Arthritis Through Characterization of Concordant Changes in DNA Methylation and Gene Expression in Synovial Biopsies of Patients With Differing Numbers of Swollen Joints

In this study, we sought to characterize synovial tissue obtained from individuals with arthralgia and disease-specific auto-antibodies and patients with established rheumatoid arthritis (RA), by applying an integrative multi-omics approach where we investigated differences at the level of DNA methylation and gene expression in relation to disease pathogenesis. We performed concurrent whole-genome bisulphite sequencing and RNA-Sequencing on synovial tissue obtained from the knee and ankle from 4 auto-antibody positive arthralgia patients and thirteen RA patients. Through multi-omics factor analysis we observed that the latent factor explaining the variance in gene expression and DNA methylation was associated with Swollen Joint Count 66 (SJC66), with patients with SJC66 of 9 or more displaying separation from the rest. Interrogating these observed differences revealed activation of the immune response as well as dysregulation of cell adhesion pathways at the level of both DNA methylation and gene expression. We observed differences for 59 genes in particular at the level of both transcript expression and DNA methylation. Our results highlight the utility of genome-wide multi-omics profiling of synovial samples for improved understanding of changes associated with disease spread in arthralgia and RA patients, and point to novel candidate targets for the treatment of the disease.

Cell-specific epigenetic drivers of pathogenesis in rheumatoid arthritis

Rheumatoid arthritis is a complex, inflammatory autoimmune disease, which is characterized by pain, swelling and joint damage driven by the altered behavior of a number of different cell types such as synovial fibroblasts macrophages and lymphocytes. The mechanism underlying pathogenesis is unclear but increasing evidence points to altered epigenetic regulation within these cell types which promotes the activated destructive behavior that underlies disease pathogenesis. This review summarizes the key epigenetic modifications in the most important cells types in rheumatoid arthritis, which are associated with disease activity. We also discuss emerging avenues of research focusing on readers of epigenetic markers which may serve to be potential therapeutic targets.

Multiomics and Machine Learning Accurately Predict Clinical Response to Adalimumab and Etanercept Therapy in Patients With Rheumatoid Arthritis

OBJECTIVE

To predict response to anti-tumor necrosis factor (anti-TNF) prior to treatment in patients with rheumatoid arthritis (RA), and to comprehensively understand the mechanism of how different RA patients respond differently to anti-TNF treatment.

METHODS

Gene expression and/or DNA methylation profiling on peripheral blood mononuclear cells (PBMCs), monocytes, and CD4+ T cells obtained from 80 RA patients before they began either adalimumab (ADA) or etanercept (ETN) therapy was studied. After 6 months, treatment response was evaluated according to the European League Against Rheumatism criteria for disease response. Differential expression and methylation analyses were performed to identify the response-associated transcription and epigenetic signatures. Using these signatures, machine learning models were built by random forest algorithm to predict response prior to anti-TNF treatment, and were further validated by a follow-up study.

RESULTS

Transcription signatures in ADA and ETN responders were divergent in PBMCs, and this phenomenon was reproduced in monocytes and CD4+ T cells. The genes up-regulated in CD4+ T cells from ADA responders were enriched in the TNF signaling pathway, while very few pathways were differential in monocytes. Differentially methylated positions (DMPs) were strongly hypermethylated in responders to ETN but not to ADA. The machine learning models for the prediction of response to ADA and ETN using differential genes reached an overall accuracy of 85.9% and 79%, respectively. The models using DMPs reached an overall accuracy of 84.7% and 88% for ADA and ETN, respectively. A follow-up study validated the high performance of these models.

CONCLUSION

Our findings indicate that machine learning models based on molecular signatures accurately predict response before ADA and ETN treatment, paving the path toward personalized anti-TNF treatment.

Сandidate SNP-markers of rheumatoid arthritis that can significantly alter the affinity of the TATA-binding protein for human gene promoters

Rheumatoid polyarthritis (RA) is an autoimmune disease with autoantibodies, including antibodies to citrullant antigens and proinflammatory cytokines, such as TNF-α and IL-6, which are involved in the induction of chronic synovitis, bone erosion, followed by deformity. Immunopathogenesis is based on the mechanisms of the breakdown of immune tolerance to its own antigens, which is characterized by an increase in the activity of T-effector cells, causing RA symptomatology. At the same time, against the background of such increased activity of effector lymphocytes, a decrease in the activity of a number of regulatory cells, including regulatory T-cells (Treg) and myeloid suppressor cells, is recorded. There is reason to say that it is the change in the activity of suppressor cells that is the leading element in RA pathogenesis. That is why only periods of weakening (remission) of RA are spoken of. According to the more powerful female immune system compared to the male one, the risk of developing RA in women is thrice as high, this risk decreases during breastfeeding and grows during pregnancy as well as after menopause in proportion to the level of sex hormones. It is believed that 50 % of the risk of developing RA depends on the conditions and lifestyle, while the remaining 50 % is dependent on genetic predisposition. That is why, RA fits the main idea of postgenomic predictive-preventive personalized medicine that is to give a chance to those who would like to reduce his/her risk of diseases by bringing his/her conditions and lifestyle in line with the data on his/her genome sequenced. This is very important, since doctors consider RA as one of the most frequent causes of disability. Using the Web service SNP_TATA_Z-tester (http://beehive.bionet.nsc.ru/cgi-bin/mgs/tatascan_fox/start.pl), 227 variants of single nucleotide polymorphism (SNP) of the human gene promoters were studied. As a result, 43 candidate SNP markers for RA that can alter the affinity of the TATA-binding protein (TBP) for the promoters of these genes were predicted.

The Pathogenic Role of Dysregulated Epigenetic Modifications in Autoimmune Diseases

Autoimmune diseases can be chronic with relapse of inflammatory symptoms, but it can be also acute and life-threatening if immune cells destroy life-supporting organs, such as lupus nephritis. The etiopathogenesis of autoimmune diseases has been revealed as that genetics and environmental factors-mediated dysregulated immune responses contribute to the initiation and development of autoimmune disorders. However, the current understanding of pathogenesis is limited and the underlying mechanism has not been well defined, which lows the development of novel biomarkers and new therapeutic strategies for autoimmune diseases. To improve this, broadening and deepening our understanding of pathogenesis is an unmet need. As genetic susceptibility cannot explain the low accordance rate of incidence in homozygous twins, epigenetic regulations might be an additional explanation. Therefore, this review will summarize current progress of studies on epigenetic dysregulations contributing to autoimmune diseases, including SLE, rheumatoid arthritis (RA), psoriasis, type 1 diabetes (T1D), and systemic sclerosis (SSc), hopefully providing opinions on orientation of future research, as well as discussing the clinical utilization of potential biomarkers and therapeutic strategies for these diseases.

DNA hypermethylation in disease: mechanisms and clinical relevance

Increasing numbers of studies implicate abnormal DNA methylation in cancer and many non-malignant diseases. This is consistent with numerous findings about differentiation-associated changes in DNA methylation at promoters, enhancers, gene bodies, and sites that control higher-order chromatin structure. Abnormal increases or decreases in DNA methylation contribute to or are markers for cancer formation and tumour progression. Aberrant DNA methylation is also associated with neurological diseases, immunological diseases, atherosclerosis, and osteoporosis. In this review, I discuss DNA hypermethylation in disease and its interrelationships with normal development as well as proposed mechanisms for the origin of and pathogenic consequences of disease-associated hypermethylation. Disease-linked DNA hypermethylation can help drive oncogenesis partly by its effects on cancer stem cells and by the CpG island methylator phenotype (CIMP); atherosclerosis by disease-related cell transdifferentiation; autoimmune and neurological diseases through abnormal perturbations of cell memory; and diverse age-associated diseases by age-related accumulation of epigenetic alterations.

A Comparison of Co-methylation Relationships Between Rheumatoid Arthritis and Parkinson's Disease

Rheumatoid arthritis (RA) is a complex autoimmune disease. Recent studies have identified the DNA methylation loci associated with RA and found that DNA methylation was a potential mediator of genetic risk. Parkinson's disease (PD) is a common neurodegenerative disease. Several studies have indicated that DNA methylation levels are linked to PD, and genes related to the immune system are significantly enriched in PD-related methylation modules. Although recent studies have provided profound insights into the DNA methylation of both RA and PD, no shared co-methylation relationships have been identified to date. Therefore, we sought to identify shared co-methylation relationships linked to RA and PD. Here, we calculated the Pearson's correlation coefficient (PCC) of 225,239,700 gene pairs and determined the differences and similarities between the two diseases. The global co-methylation change between in PD cases and controls was larger than that between RA cases and controls. We found 337 gene pairs with large changes that were shared between RA and PD. This co-methylation relationship study represents a new area of study for both RA and PD and provides new ideas for further study of the shared biological mechanisms of RA and PD.

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.