Inflammatory cytokines shape a changing DNA methylome in monocytes mirroring disease activity in rheumatoid arthritis

A comprehensive map of the aging blood methylome in humans

BACKGROUND

During aging, the human methylome undergoes both differential and variable shifts, accompanied by increased entropy. The distinction between variably methylated positions (VMPs) and differentially methylated positions (DMPs), their contribution to epigenetic age, and the role of cell type heterogeneity remain unclear.

RESULTS

We conduct a comprehensive analysis of > 32,000 human blood methylomes from 56 datasets (age range = 6-101 years). We find a significant proportion of the blood methylome that is differentially methylated with age (48% DMPs; FDR < 0.005) and variably methylated with age (37% VMPs; FDR < 0.005), with considerable overlap between the two groups (59% of DMPs are VMPs). Bivalent and Polycomb regions become increasingly methylated and divergent between individuals, while quiescent regions lose methylation more uniformly. Both chronological and biological clocks, but not pace-of-aging clocks, show a strong enrichment for CpGs undergoing both mean and variance changes during aging. The accumulation of DMPs shifting towards a methylation fraction of 50% drives the increase in entropy, smoothening the epigenetic landscape. However, approximately a quarter of DMPs exhibit anti-entropic effects, opposing this direction of change. While changes in cell type composition minimally affect DMPs, VMPs and entropy measurements are moderately sensitive to such alterations.

CONCLUSION

This study represents the largest investigation to date of genome-wide DNA methylation changes and aging in a single tissue, providing valuable insights into primary molecular changes relevant to chronological and biological aging.

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.

Role of IFN-α in Rheumatoid Arthritis

PURPOSE OF REVIEW

Type 1 interferons (IFN-I) are of increasing interest across a wide range of autoimmune rheumatic diseases. Historically, research into their role in rheumatoid arthritis (RA) has been relatively neglected, but recent work continues to highlight a potential contribution to RA pathophysiology.

RECENT FINDINGS

We emphasise the importance of disease stage when examining IFN-I in RA and provide an overview on how IFN-I may have a direct role on a variety of relevant cellular functions. We explore how clinical trajectory may be influenced by increased IFN-I signalling, and also, the limitations of scores composed of interferon response genes. Relevant environmental triggers and inheritable RA genetic risk relating to IFN-I signalling are explored with emphasis on intriguing data potentially linking IFN-I exposure, epigenetic changes, and disease relevant processes. Whilst these data cumulatively illustrate a likely role for IFN-I in RA, they also highlight the knowledge gaps, particularly in populations at risk for RA, and suggest directions for future research to both better understand IFN-I biology and inform targeted therapeutic strategies.

A novel approach toward optimal workflow selection for DNA methylation biomarker discovery

DNA methylation is a major epigenetic modification involved in many physiological processes. Normal methylation patterns are disrupted in many diseases and methylation-based biomarkers have shown promise in several contexts. Marker discovery typically involves the analysis of publicly available DNA methylation data from high-throughput assays. Numerous methods for identification of differentially methylated biomarkers have been developed, making the need for best practices guidelines and context-specific analyses workflows exceedingly high. To this end, here we propose TASA, a novel method for simulating methylation array data in various scenarios. We then comprehensively assess different data analysis workflows using real and simulated data and suggest optimal start-to-finish analysis workflows. Our study demonstrates that the choice of analysis pipeline for DNA methylation-based marker discovery is crucial and different across different contexts.

BERT-5mC: an interpretable model for predicting 5-methylcytosine sites of DNA based on BERT

DNA 5-methylcytosine (5mC) is widely present in multicellular eukaryotes, which plays important roles in various developmental and physiological processes and a wide range of human diseases. Thus, it is essential to accurately detect the 5mC sites. Although current sequencing technologies can map genome-wide 5mC sites, these experimental methods are both costly and time-consuming. To achieve a fast and accurate prediction of 5mC sites, we propose a new computational approach, BERT-5mC. First, we pre-trained a domain-specific BERT (bidirectional encoder representations from transformers) model by using human promoter sequences as language corpus. BERT is a deep two-way language representation model based on Transformer. Second, we fine-tuned the domain-specific BERT model based on the 5mC training dataset to build the model. The cross-validation results show that our model achieves an AUROC of 0.966 which is higher than other state-of-the-art methods such as iPromoter-5mC, 5mC_Pred, and BiLSTM-5mC. Furthermore, our model was evaluated on the independent test set, which shows that our model achieves an AUROC of 0.966 that is also higher than other state-of-the-art methods. Moreover, we analyzed the attention weights generated by BERT to identify a number of nucleotide distributions that are closely associated with 5mC modifications. To facilitate the use of our model, we built a webserver which can be freely accessed at: http://5mc-pred.zhulab.org.cn.

Innate immune memory in inflammatory arthritis

The concept of immunological memory was demonstrated in antiquity when protection against re-exposure to pathogens was observed during the plague of Athens. Immunological memory has been linked with the adaptive features of T and B cells; however, in the past decade, evidence has demonstrated that innate immune cells can exhibit memory, a phenomenon called 'innate immune memory' or 'trained immunity'. Innate immune memory is currently being defined and is transforming our understanding of chronic inflammation and autoimmunity. In this Review, we provide an up-to-date overview of the memory-like features of innate immune cells in inflammatory arthritis and the crosstalk between chronic inflammatory milieu and cell reprogramming. Aberrant pro-inflammatory signalling, including cytokines, regulates the metabolic and epigenetic reprogramming of haematopoietic progenitors, leading to exacerbated inflammatory responses and osteoclast differentiation, in turn leading to bone destruction. Moreover, imprinted memory on mature cells including terminally differentiated osteoclasts alters responsiveness to therapies and modifies disease outcomes, commonly manifested by persistent inflammatory flares and relapse following medication withdrawal.

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.

Meta-analysis and GRADE assessment of randomized controlled trials on the efficacy and safety of bimekizumab in psoriatic arthritis patients

OBJECTIVE

A persistent immune-mediated inflammatory disorder called psoriatic arthritis affects about 25% of persons with psoriasis. Bimekizumab, a humanized monoclonal IgG1 antibody, is a novel therapeutic approach that inhibits homodimers and heterodimers of IL-17A and IL-17F by binding to comparable locations in these molecules. Bimekizumab was the subject of a meta-analysis to assess its efficacy and safety in psoriatic arthritis patients.

METHODS

All randomized clinical trials were looked up on PubMed, Scopus, and Web of Science. The Systematic Review Accelerator tool was used to screen them, and RevMan was used to analyze them. The Mean Difference (MD) and 95% Confidence Interval (CI) were used to examine continuous data, whereas the Risk Ratio (RR) and 95% CI were used to evaluate dichotomous data.

RESULTS

A total of 1364 participants from 4 trials were included in this meta-analysis. The number of participants who met the American College of Rheumatology 50 threshold was significantly higher in the bimekizumab group compared to the placebo group [RR = 4.94, 95% CI (3.73, 6.55), p < .00001]. Psoriasis Area and Severity Index 100 was achieved by significantly more people in the bimekizumab group than in the placebo group [RR = 11.45, 95% CI (6.67, 19.67), p < .00001]. There was no significant difference between the bimekizumab group and the placebo group in terms of treatment-emergent adverse events [RR = 1.08, 95% CI (0.97, 1.21), p = .15].

CONCLUSION

In comparison to a placebo, bimekizumab treatment significantly improved joint and skin efficacy outcomes. Also, its safety results were acceptable.

Ocimum sanctum L water extract: In-situ green synthesis of zinc oxide nanoparticles for treatment of rheumatoid arthritis: Preclinical study

BACKGROUND AND OBJECTIVE

Rheumatoid arthritis is a chronic progressive autoimmune disorder, characterised by destruction of cartilage and under line bones. Though exact etiology of rheumatoid arthritis (RA) remains unknown. It is believed that alteration in control of cellular or molecular responses is involved in the chronic inflammation. Earlier in RA patients it was observed the circulating RA specific biomarkers and immunoglobulin deposits in the synovial joints. Zinc Oxide Nanoparticles (ZnO NPs) is used as an anti-inflammatory and anticancer agent, however there is nil/very less scientific data shows the anti-arthritic activity of green synthesis ZnO nanoparticles (Ocimum sanctum water extract in-situ synthesis of ZnO NPs having active compound Caffeic acid and Rosmerinic acid). Hence, the present activity was planned to assess the anti-arthritic activity of ZnO NPs in CIA rats.

METHODS

Arthritis in rats were induced by subcutaneous injection of collagen type II (CII) (200 µl) at the base of tail on day 0 followed by booster dose on day 14. ZnO NPs were given (2 mg/kg b.wt./day) orally for 20 days. At the end of the study serum, joint homogenate was used to assess the level of biomarkers (RF, a-CCP, a-CII and CRP) and inflammatory mediators. In addition, m-RNA expression of various genes such as Nuclear factor-kB (NF-kB), inflammatory mediators like tumour necrosis factor-α (TNF-α), cyclooxygenase-2 (COX-2) etc. were assayed in joint tissue. Finally all these biochemical and molecular results were confirmed by microscopic study of joint tissue.

RESULTS

ZnO NPs, treated rats showed decrease in inflammation and clinical severity. This was related with decrease in the level of biomarkers (like RF, a-CCP and CRP), inflammatory mediators (TNF-α, COX-2) and activity of transcription factor NF-kB. All these findings were positively correlated with microscopic analysis of joint tissue that showed reduced inflammation and bone erosion in treated group.

CONCLUSION

This study validates the anti-arthritic activity of ZnO NPs as it mitigates the arthritis related symptoms in CIA rats.

DGA-5mC: A 5-methylcytosine site prediction model based on an improved DenseNet and bidirectional GRU method

The 5-methylcytosine (5mC) in the promoter region plays a significant role in biological processes and diseases. A few high-throughput sequencing technologies and traditional machine learning algorithms are often used by researchers to detect 5mC modification sites. However, high-throughput identification is laborious, time-consuming and expensive; moreover, the machine learning algorithms are not so advanced. Therefore, there is an urgent need to develop a more efficient computational approach to replace those traditional methods. Since deep learning algorithms are more popular and have powerful computational advantages, we constructed a novel prediction model, called DGA-5mC, to identify 5mC modification sites in promoter regions by using a deep learning algorithm based on an improved densely connected convolutional network (DenseNet) and the bidirectional GRU approach. Furthermore, we added a self-attention module to evaluate the importance of various 5mC features. The deep learning-based DGA-5mC model algorithm automatically handles large proportions of unbalanced data for both positive and negative samples, highlighting the model's reliability and superiority. So far as the authors are aware, this is the first time that the combination of an improved DenseNet and bidirectional GRU methods has been used to predict the 5mC modification sites in promoter regions. It can be seen that the DGA-5mC model, after using a combination of one-hot coding, nucleotide chemical property coding and nucleotide density coding, performed well in terms of sensitivity, specificity, accuracy, the Matthews correlation coefficient (MCC), area under the curve and Gmean in the independent test dataset: 90.19%, 92.74%, 92.54%, 64.64%, 96.43% and 91.46%, respectively. In addition, all datasets and source codes for the DGA-5mC model are freely accessible at https://github.com/lulukoss/DGA-5mC.

Psoriatic Arthritis: Pathogenesis and Targeted Therapies

Psoriatic arthritis (PsA), a heterogeneous chronic inflammatory immune-mediated disease characterized by musculoskeletal inflammation (arthritis, enthesitis, spondylitis, and dactylitis), generally occurs in patients with psoriasis. PsA is also associated with uveitis and inflammatory bowel disease (Crohn's disease and ulcerative colitis). To capture these manifestations as well as the associated comorbidities, and to recognize their underlining common pathogenesis, the name of psoriatic disease was coined. The pathogenesis of PsA is complex and multifaceted, with an interplay of genetic predisposition, triggering environmental factors, and activation of the innate and adaptive immune system, although autoinflammation has also been implicated. Research has identified several immune-inflammatory pathways defined by cytokines (IL-23/IL-17, TNF), leading to the development of efficacious therapeutic targets. However, heterogeneous responses to these drugs occur in different patients and in the different tissues involved, resulting in a challenge to the global management of the disease. Therefore, more translational research is necessary in order to identify new targets and improve current disease outcomes. Hopefully, this may become a reality through the integration of different omics technologies that allow better understanding of the relevant cellular and molecular players of the different tissues and manifestations of the disease. In this narrative review, we aim to provide an updated overview of the pathophysiology, including the latest findings from multiomics studies, and to describe current targeted therapies.

Placental DNA methylation profile as predicting marker for autism spectrum disorder (ASD)

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that impairs normal brain development and socio-cognitive abilities. The pathogenesis of this condition points out the involvement of genetic and environmental factors during in-utero life. Placenta, as an interface tissue between mother and fetus, provides developing fetus requirements and exposes it to maternal environment as well. Therefore, the alteration of DNA methylation as epigenetic consequence of gene-environmental interaction in the placenta could shed light on ASD pathogenesis. In this study, we reviewed the current findings on placental methylation status and its association with ASD. Differentially methylated regions (DMRs) in ASD-developing placenta were found to be mainly enriched in ASD gene loci affecting synaptogenesis, microtubule dynamics, neurogenesis and neuritogenesis. In addition, non-genic DMRs in ASD-placenta proposes an alternative contributing mechanism for ASD development. Our study highlights the importance of placental DNA methylation signature as a biomarker for ASD prediction.

Mechanisms of DNA methylation and histone modifications

The field of genetics has expanded a lot in the past few decades due to the accessibility of human genome sequences, but still, the regulation of transcription cannot be explicated exclusively by the sequence of DNA of an individual. The coordination and crosstalk between chromatin factors which are conserved is indispensable for all living creatures. The regulation of gene expression has been dependent on the methylation of DNA, post-translational modifications of histones, effector proteins, chromatin remodeler enzymes that affect the chromatin structure and function, and other cellular activities such as DNA replication, DNA repair, proliferation and growth. The mutation and deletion of these factors can lead to human diseases. Various studies are being performed to identify and understand the gene regulatory mechanisms in the diseased state. The information from these high throughput screening studies is able to aid the treatment developments based on the epigenetics regulatory mechanisms. This book chapter will discourse on various modifications and their mechanisms that take place on histones and DNA that regulate the transcription of genes.

Epigenetic and transcriptomic reprogramming in monocytes of severe COVID-19 patients reflects alterations in myeloid differentiation and the influence of inflammatory cytokines

BACKGROUND

COVID-19 manifests with a wide spectrum of clinical phenotypes, ranging from asymptomatic and mild to severe and critical. Severe and critical COVID-19 patients are characterized by marked changes in the myeloid compartment, especially monocytes. However, little is known about the epigenetic alterations that occur in these cells during hyperinflammatory responses in severe COVID-19 patients.

METHODS

In this study, we obtained the DNA methylome and transcriptome of peripheral blood monocytes from severe COVID-19 patients. DNA samples extracted from CD14 + CD15- monocytes of 48 severe COVID-19 patients and 11 healthy controls were hybridized on MethylationEPIC BeadChip arrays. In parallel, single-cell transcriptomics of 10 severe COVID-19 patients were generated. CellPhoneDB was used to infer changes in the crosstalk between monocytes and other immune cell types.

RESULTS

We observed DNA methylation changes in CpG sites associated with interferon-related genes and genes associated with antigen presentation, concordant with gene expression changes. These changes significantly overlapped with those occurring in bacterial sepsis, although specific DNA methylation alterations in genes specific to viral infection were also identified. We also found these alterations to comprise some of the DNA methylation changes occurring during myeloid differentiation and under the influence of inflammatory cytokines. A progression of DNA methylation alterations in relation to the Sequential Organ Failure Assessment (SOFA) score was found to be related to interferon-related genes and T-helper 1 cell cytokine production. CellPhoneDB analysis of the single-cell transcriptomes of other immune cell types suggested the existence of altered crosstalk between monocytes and other cell types like NK cells and regulatory T cells.

CONCLUSION

Our findings show the occurrence of an epigenetic and transcriptional reprogramming of peripheral blood monocytes, which could be associated with the release of aberrant immature monocytes, increased systemic levels of pro-inflammatory cytokines, and changes in immune cell crosstalk in these patients.

Designing Studies for Epigenetic Biomarker Development in Autoimmune Rheumatic Diseases

In just a few years, the number of epigenetic studies in autoimmune rheumatic and inflammatory diseases has greatly increased. This is in part due to the need of identifying additional determinants to genetics to explain the pathogenesis and development of these disorders. In this regard, epigenetics provides potential mechanisms that determine gene function, are linked to environmental factors, and could explain a wide range of phenotypic variability among patients with these diseases. Despite the high interest and number of studies describing epigenetic alterations under these conditions and exploring their relationship to various clinical aspects, few of the proposed biomarkers have yet reached clinical practice. The potential of epigenetic markers is high, as these alterations link measurable features with a number of biological traits. In the present article, we present published studies in the field, discuss some frequent limitations in the existing research, and propose a number of considerations that should be taken into account by those starting new projects in the field, with an aim to generate biomarkers that could make it into the clinics.

Interferon-α-mediated therapeutic resistance in early rheumatoid arthritis implicates epigenetic reprogramming

OBJECTIVES

An interferon (IFN) gene signature (IGS) is present in approximately 50% of early, treatment naive rheumatoid arthritis (eRA) patients where it has been shown to negatively impact initial response to treatment. We wished to validate this effect and explore potential mechanisms of action.

METHODS

In a multicentre inception cohort of eRA patients (n=191), we examined the whole blood IGS (MxA, IFI44L, OAS1, IFI6, ISG15) with reference to circulating IFN proteins, clinical outcomes and epigenetic influences on circulating CD19+ B and CD4+ T lymphocytes.

RESULTS

We reproduced our previous findings demonstrating a raised baseline IGS. We additionally showed, for the first time, that the IGS in eRA reflects circulating IFN-α protein. Paired longitudinal analysis demonstrated a significant reduction between baseline and 6-month IGS and IFN-α levels (p<0.0001 for both). Despite this fall, a raised baseline IGS predicted worse 6-month clinical outcomes such as increased disease activity score (DAS-28, p=0.025) and lower likelihood of a good EULAR clinical response (p=0.034), which was independent of other conventional predictors of disease activity and clinical response. Molecular analysis of CD4+ T cells and CD19+ B cells demonstrated differentially methylated CPG sites and dysregulated expression of disease relevant genes, including PARP9, STAT1, and EPSTI1, associated with baseline IGS/IFNα levels. Differentially methylated CPG sites implicated altered transcription factor binding in B cells (GATA3, ETSI, NFATC2, EZH2) and T cells (p300, HIF1α).

CONCLUSIONS

Our data suggest that, in eRA, IFN-α can cause a sustained, epigenetically mediated, pathogenic increase in lymphocyte activation and proliferation, and that the IGS is, therefore, a robust prognostic biomarker. Its persistent harmful effects provide a rationale for the initial therapeutic targeting of IFN-α in selected patients with eRA.

The Role of M1/M2 Macrophage Polarization in Rheumatoid Arthritis Synovitis

Innate and adaptive immunity represent a harmonic counterbalanced system involved in the induction, progression, and possibly resolution of the inflammatory reaction that characterize autoimmune rheumatic diseases (ARDs), including rheumatoid arthritis (RA). Although the immunopathophysiological mechanisms of the ARDs are not fully clarified, they are often associated with an inappropriate macrophage/T-cell interaction, where classical (M1) or alternative (M2) macrophage activation may influence the occurrence of T-helper (Th)1 or Th2 responses. In RA patients, M1/Th1 activation occurs in an inflammatory environment dominated by Toll-like receptor (TLR) and interferon (IFN) signaling, and it promotes a massive production of pro-inflammatory cytokines [i.e., tumor necrosis factor-α (TNFα), interleukin (IL)-1, IL-12, IL-18, and IFNγ], chemotactic factors, and matrix metalloproteinases resulting in osteoclastogenesis, erosion, and progressive joint destruction. On the other hand, the activation of M2/Th2 response determines the release of growth factors and cytokines [i.e., IL-4, IL-10, IL-13, and transforming growth factor (TGF)-β] involved in the anti-inflammatory process leading to the clinical remission of RA. Several subtypes of macrophages have been described. Five polarization states from M1 to M2 have been confirmed in in vitro studies analyzing morphological characteristics, gene expression of phenotype markers (CD80, CD86, TLR2, TLR4, or CD206, CD204, CD163, MerTK), and functional aspect, including the production of reactive oxygen species (ROS). An M1 and M2 macrophage imbalance may induce pathological consequences and contribute to several diseases, such as asthma or osteoclastogenesis in RA patients. In addition, the macrophage dynamic polarization from M1 to M2 includes the presence of intermediate polarity stages distinguished by the expression of specific surface markers and the production/release of distinct molecules (i.e., nitric oxide, cytokines), which characterize their morphological and functional state. This suggests a “continuum” of macrophage activation states playing an important role during inflammation and its resolution. This review discusses the importance of the delicate M1/M2 imbalance in the different phases of the inflammatory process together with the identification of specific pathways, cytokines, and chemokines involved, and its clinical outcomes in RA. The analysis of these aspects could shed a light on the abnormal inflammatory activation, leading to novel therapeutical approaches which may contribute to restore the M1/M2 balance.

Longitudinal analysis of blood DNA methylation identifies mechanisms of response to tumor necrosis factor inhibitor therapy in rheumatoid arthritis

Background

Rheumatoid arthritis (RA) is a chronic, immune-mediated inflammatory disease of the joints that has been associated with variation in the peripheral blood methylome. In this study, we aim to identify epigenetic variation that is associated with the response to tumor necrosis factor inhibitor (TNFi) therapy.

Methods

Peripheral blood genome-wide DNA methylation profiles were analyzed in a discovery cohort of 62 RA patients at baseline and at week 12 of TNFi therapy. DNA methylation of individual CpG sites and enrichment of biological pathways were evaluated for their association with drug response. Using a novel cell deconvolution approach, altered DNA methylation associated with TNFi response was also tested in the six main immune cell types in blood. Validation of the results was performed in an independent longitudinal cohort of 60 RA patients.

Findings

Treatment with TNFi was associated with significant longitudinal peripheral blood methylation changes in biological pathways related to RA (FDR<0.05). 139 biological functions were modified by therapy, with methylation levels changing systematically towards a signature similar to that of healthy controls. Differences in the methylation profile of T cell activation and differentiation, GTPase-mediated signaling, and actin filament organization pathways were associated with the clinical response to therapy. Cell type deconvolution analysis identified CpG sites in CD4+T, NK, neutrophils and monocytes that were significantly associated with the response to TNFi.

Interpretation

Our results show that treatment with TNFi restores homeostatic blood methylation in RA. The clinical response to TNFi is associated to methylation variation in specific biological pathways, and it involves cells from both the innate and adaptive immune systems.

Funding

The Instituto de Salud Carlos III.

Characterization of chronic relapsing antibody mediated arthritis in mice with a mutation in Ncf1 causing reduced oxidative burst

Rheumatoid arthritis (RA) is a chronic autoimmune disorder affecting joints with a hallmark of autoantibody production. Mannan-enhanced collagen type II (COL2) antibody induced arthritis (mCAIA) in neutrophil cytosolic factor 1(Ncf1) mutation mouse is a chronic disease model imitating RA in mice. In this study, we characterize the chronic phase of mCAIA in Ncf1 mutated (BQ.Ncf1^m1j/m1j) mice. Arthritis was induced by an intravenous injection of anti-COL2 monoclonal antibodies on day 0 followed by intra-peritoneal injections of mannan (from Saccharomyces cerevisiae) on days 3 and 65 in BQ.Ncf1^m1j/m1j and BQ mice. Bone erosion was analysed by computed tomography (CT) and blood cell phenotypes by flow cytometry. Cytokines and anti-COL2 antibodies were analyzed with multiplex bead-based assays. The arthritis in the Ncf1^m1j/m1j mice developed with a chronic and relapsing disease course, which was followed for 200 days and bone erosions of articular joints were evaluated. An increased number of circulating CD11b⁺ Ly6G⁺ neutrophils were observed during the chronic phase, together with a higher level of G-CSF (granulocyte colony-stimulating factor) and TNF-α. In conclusion, the chronic relapsing arthritis of mCAIA in the Ncf1^m1j/m1j mice develop bone erosions associated with a sustained neutrophil type of inflammatory responses.

The synovial and blood monocyte DNA methylomes mirror prognosis, evolution and treatment in early arthritis

Identifying predictive biomarkers at early stages of inflammatory arthritis is crucial for starting appropriate therapies to avoid poor outcomes. Monocytes (MOs) and macrophages, largely associated with arthritis, are contributors and sensors of inflammation through epigenetic modifications. In this study, we investigated associations between clinical features and DNA methylation in blood and synovial fluid (SF) MOs in a prospective cohort of patients with early inflammatory arthritis. DNA methylation profiles of undifferentiated arthritis (UA) blood MOs exhibited marked alterations in comparison with those from healthy donors. We identified additional differences both in blood and SF MOs after comparing patients with UA grouped by their future outcomes, i.e., good versus poor. Patient profiles in subsequent visits revealed a reversion toward a healthy level in both groups, those requiring disease-modifying antirheumatic drugs and those who remitted spontaneously. Changes in disease activity between visits also affected DNA methylation, which was partially concomitant in the SF of UA and in blood MOs of patients with rheumatoid arthritis. Epigenetic similarities between arthritis types allow a common prediction of disease activity. Our results constitute a resource of DNA methylation–based biomarkers of poor prognosis, disease activity, and treatment efficacy for the personalized clinical management of early inflammatory arthritis.

Triiodothyronine (T3) Induces Limited Transcriptional and DNA Methylation Reprogramming in Human Monocytes

Thyroid hormones have immunomodulatory roles, but their effects on the transcriptome and epigenome of innate immune cell types remain unexplored. In this study, we investigate the effects of triiodothyronine (T3) on the transcriptome and methylome of human monocytes in vitro, both in resting and lipopolysaccharide (LPS)-stimulated conditions. In resting monocytes, 5 µM T3 affected the expression of a small number of monocyte-to-macrophage differentiation-associated genes, including TLR4 (p-value < 0.05, expression fold change >1.5). T3 attenuated a small proportion of monocyte-to-macrophage differentiation-associated DNA methylation changes, while specifically inducing DNA methylation changes at several hundred differentially methylated CpG probes (DMPs) (p-value < 0.05, Δβ > 0.05). In LPS-stimulated monocytes, the presence of T3 attenuated the effect of 27% of LPS-induced DMPs (p-value < 0.05, Δβ > 0.05). Interestingly, co-stimulation with T3 + LPS induced a unique DNA methylation signature that was not observed in the LPS-only or T3-only exposure groups. Our results suggest that T3 induces limited transcriptional and DNA methylation remodeling in genes enriched in metabolism and immune processes and alters the normal in vitro LPS response. The overlap between differentially expressed genes and genes associated with DMPs was minimal; thus, other epigenetic mechanisms may underpin the expression changes. This research provides insight into the complex interplay between thyroid hormones, epigenetic remodeling, and transcriptional dynamics in monocytes.

Genetics of rheumatoid arthritis

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease involving symmetric joints and is generally characterized by persistent pain, tenderness, and destruction of joints. The vast majority of RA patients produce autoantibodies, and immune cell involvement in disease development is well recognized, as is the contribution of other types of cells in synovial tissue, like fibroblasts. It is known that there are major genetic associations with the HLA locus, while multiple non-HLA genetic variants display relatively low risk of RA. Both HLA and non-HLA associations suggest that the profiles of genetic associations for autoantibody-positive vs. autoantibody-negative RA are different. Several alleles of HLA-DRB1 are associated with high risk for autoantibody-positive RA, with the strongest risk characterized by valine at position 11 of the protein sequence (HLA-DRB1*04 and *10 alleles). There is a strong protective effect for the risk of autoantibody-positive RA associated with HLA-DRB1*13 alleles. Although major genetic associations have been known for several years, understanding of the specific mechanisms in the development of increased risk of RA for these variations is work in progress. Current studies focus on the binding of immune receptors involved in recognition of putative peptides in activation of T cells, as well as investigation of cell signaling mechanisms. At least a part of RA risk could be explained by gene-gene and gene-environment interactions. There are currently more than 150 candidate loci with polymorphisms that associate with RA, mainly related to seropositive disease, and new discoveries are anticipated in the future from investigation of diverse human populations. This new research will help create a strong foundation for the continuing process of integrating genetic, epigenetic, transcriptomic, and proteomic data in studies of RA.

Integrative blood-derived epigenetic and transcriptomic analysis reveals the potential regulatory role of DNA methylation in ankylosing spondylitis

Background

The currently known risk loci could explain a small proportion of the heritability of ankylosing spondylitis (AS). Epigenetics might account for the missing heritability. We aimed to seek more novel AS-associated DNA methylation alterations and delineate the regulatory effect of DNA methylation and gene expression with integrated analysis of methylome and transcriptome.

Methods

Epigenome-wide DNA methylation and mRNA expression were profiled in peripheral blood mononuclear cells (PBMCs) from 45 individuals (AS: health controls (HCs) = 30:15) with high-throughput array. The methylome was validated in an independent cohort (AS: HCs = 12:12). Pearson correlation analysis and causal inference tests (CIT) were conducted to determine potentially causative regulatory effects of methylation on mRNA expression.

Results

A total of 4794 differentially methylated positions (DMPs) were identified associated with AS, 2526 DMPs of which were validated in an independent cohort. Both cohorts highlighted T cell receptor (TCR) signaling and Th17 differentiation pathways. Besides, AS patients manifested increased DNA methylation variability. The methylation levels of 158 DMPs were correlated with the mRNA expression levels of 112 genes, which formed interconnected network concentrated on Th17 cell differentiation and TCR signaling pathway (LCK, FYN, CD3G, TCF7, ZAP70, CXCL12, and PLCG1). We also identified several cis-acting DNA methylation and gene expression changes associated with AS risk, which might regulate the cellular mechanisms underlying AS.

Conclusions

Our studies outlined the landscapes of epi-signatures of AS and several methylation-gene expression-AS regulatory axis and highlighted the Th17 cell differentiation and TCR signaling pathway, which might provide innovative molecular targets for therapeutic interventions for AS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02697-3.

Vitamin D Metabolic Pathway Genes Polymorphisms and Their Methylation Levels in Association With Rheumatoid Arthritis

Abnormal vitamin D metabolism is involved in the pathogenesis of rheumatoid arthritis (RA). In this study, we evaluated the association of single nucleotide polymorphisms (SNPs) and methylation levels in vitamin D metabolic pathway genes with RA susceptibility. Ten SNPs in vitamin D metabolic pathway genes (CYP2R1, CYP24A1, VDR, CYP27B1) were genotyped in 477 RA patients and 496 controls by improved multiple ligase detection reaction (iMLDR). The methylation levels of the promoter regions of these genes were detected in 122 RA patients and 123 controls using Illumina Hiseq platform. We found that the CYP2R1 rs1993116 GA genotype, CYP27B1 rs4646536 GA genotype, rs4646536 A allele frequencies were significantly increased in RA patients when compared to controls. The decreased risk of rs1993116, rs4646536 was found under the dominant mode in RA patients. However, no significant association was found between CYP2R1 rs7936142, rs12794714, CYP24A1 rs2762934, rs6068816, rs2296239, rs2296241, VDR rs11574129, rs3847987 polymorphism, and RA susceptibility. The VDR, CYP27B1 methylation levels in RA patients were significantly lower than those in controls, while CYP2R1, CYP24A1 methylation levels were not associated with RA. There were no statistical associations between CYP2R1, CYP24A1, VDR, CYP27B1 methylation levels and their respective genotype in RA patients. In addition, plasma 25OHD level in RA patients was significantly lower than that in healthy controls. In summary, our results showed that CYP2R1, CYP27B1 genetic variations were associated with the genetic background of RA, while altered VDR, CYP27B1 methylation levels were related to the risk of RA.

Epigenome association study for DNA methylation biomarkers in buccal and monocyte cells for female rheumatoid arthritis

Genetics (i.e., mutations) has been assumed to be the major factor in rheumatoid arthritis (RA) etiology, but accounts for a minority of the variance in disease risk for RA. In contrast to genetics, the environment can have dramatic impacts on epigenetics that associate with disease etiology. The current study used buccal cells and purified blood monocytes from two different clinical cohorts involving Caucasian or African American female populations with or without arthritis. The differential DNA methylation regions (DMRs) between the control and RA populations were identified with an epigenome-wide association study. The DMRs (i.e., epimutations) identified in the buccal cells and monocytes were found to be distinct. The DMR associated genes were identified and many have previously been shown to be associated with arthritis. Observations demonstrate DNA methylation epimutation RA biomarkers are cell type specific and similar findings were observed with the two racial background populations. Rheumatoid arthritis susceptibility epigenetic diagnosis appears feasible and may improve the clinical management of RA and allowpreventative medicine considerations.

BiLSTM-5mC: A Bidirectional Long Short-Term Memory-Based Approach for Predicting 5-Methylcytosine Sites in Genome-Wide DNA Promoters

An important reason of cancer proliferation is the change in DNA methylation patterns, characterized by the localized hypermethylation of the promoters of tumor-suppressor genes together with an overall decrease in the level of 5-methylcytosine (5mC). Therefore, identifying the 5mC sites in the promoters is a critical step towards further understanding the diverse functions of DNA methylation in genetic diseases such as cancers and aging. However, most wet-lab experimental techniques are often time consuming and laborious for detecting 5mC sites. In this study, we proposed a deep learning-based approach, called BiLSTM-5mC, for accurately identifying 5mC sites in genome-wide DNA promoters. First, we randomly divided the negative samples into 11 subsets of equal size, one of which can form the balance subset by combining with the positive samples in the same amount. Then, two types of feature vectors encoded by the one-hot method, and the nucleotide property and frequency (NPF) methods were fed into a bidirectional long short-term memory (BiLSTM) network and a full connection layer to train the 22 submodels. Finally, the outputs of these models were integrated to predict 5mC sites by using the majority vote strategy. Our experimental results demonstrated that BiLSTM-5mC outperformed existing methods based on the same independent dataset.

Insights Into the Role of DNA Methylation in Immune Cell Development and Autoimmune Disease

To date, nearly 100 autoimmune diseases have been an area of focus, and these diseases bring health challenges to approximately 5% of the population worldwide. As a type of disease caused by tolerance breakdown, both environmental and genetic risk factors contribute to autoimmune disease development. However, in most cases, there are still gaps in our understanding of disease pathogenesis, diagnosis, and treatment. Therefore, more detailed knowledge of disease pathogenesis and potential therapies is indispensable. DNA methylation, which does not affect the DNA sequence, is one of the key epigenetic silencing mechanisms and has been indicated to play a key role in gene expression regulation and to participate in the development of certain autoimmune diseases. Potential epigenetic regulation via DNA methylation has garnered more attention as a disease biomarker in recent years. In this review, we clarify the basic function and distribution of DNA methylation, evaluate its effects on gene expression and discuss related key enzymes. In addition, we summarize recent aberrant DNA methylation modifications identified in the most important cell types related to several autoimmune diseases and then provide potential directions for better diagnosing and monitoring disease progression driven by epigenetic control, which may broaden our understanding and contribute to further epigenetic research in autoimmune diseases.

Splicing machinery is impaired in rheumatoid arthritis, associated with disease activity and modulated by anti-TNF therapy

OBJECTIVES

To characterise splicing machinery (SM) alterations in leucocytes of patients with rheumatoid arthritis (RA), and to assess its influence on their clinical profile and therapeutic response.

METHODS

Leucocyte subtypes from 129 patients with RA and 29 healthy donors (HD) were purified, and 45 selected SM elements (SME) were evaluated by quantitative PCR-array based on microfluidic technology (Fluidigm). Modulation by anti-tumour necrosis factor (TNF) therapy and underlying regulatory mechanisms were assessed.

RESULTS

An altered expression of several SME was found in RA leucocytes. Eight elements (SNRNP70, SNRNP200, U2AF2, RNU4ATAC, RBM3, RBM17, KHDRBS1 and SRSF10) were equally altered in all leucocytes subtypes. Logistic regressions revealed that this signature might: discriminate RA and HD, and anti-citrullinated protein antibodies (ACPAs) positivity; classify high-disease activity (disease activity score-28 (DAS28) >5.1); recognise radiological involvement; and identify patients showing atheroma plaques. Furthermore, this signature was altered in RA synovial fluid and ankle joints of K/BxN-arthritic mice. An available RNA-seq data set enabled to validate data and identified distinctive splicing events and splicing variants among patients with RA expressing high and low SME levels. 3 and 6 months anti-TNF therapy reversed their expression in parallel to the reduction of the inflammatory profile. In vitro, ACPAs modulated SME, at least partially, by Fc Receptor (FcR)-dependent mechanisms. Key inflammatory cytokines further altered SME. Lastly, induced SNRNP70-overexpression and KHDRBS1-overexpression reversed inflammation in lymphocytes, NETosis in neutrophils and adhesion in RA monocytes and influenced activity of RA synovial fibroblasts.

CONCLUSIONS

Overall, we have characterised for the first time a signature comprising eight dysregulated SME in RA leucocytes from both peripheral blood and synovial fluid, linked to disease pathophysiology, modulated by ACPAs and reversed by anti-TNF therapy.

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. The primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure-activity relationship to drug repositioning, protein misfolding to protein-protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

Tuning Monocytes and Macrophages for Personalized Therapy and Diagnostic Challenge in Rheumatoid Arthritis

Monocytes/macrophages play a central role in chronic inflammatory disorders, including rheumatoid arthritis (RA). Activation of these cells results in the production of various mediators responsible for inflammation and RA pathogenesis. On the other hand, the depletion of macrophages using specific antibodies or chemical agents can prevent their synovial tissue infiltration and subsequently attenuates inflammation. Their plasticity is a major feature that helps the switch from a pro-inflammatory phenotype (M1) to an anti-inflammatory state (M2). Therefore, understanding the precise strategy targeting pro-inflammatory monocytes/macrophages should be a powerful way of inhibiting chronic inflammation and bone erosion. In this review, we demonstrate potential consequences of different epigenetic regulations on inflammatory cytokines production by monocytes. In addition, we present unique profiles of monocytes/macrophages contributing to identification of new biomarkers of disease activity or predicting treatment response in RA. We also outline novel approaches of tuning monocytes/macrophages by biologic drugs, small molecules or by other therapeutic modalities to reduce arthritis. Finally, the importance of cellular heterogeneity of monocytes/macrophages is highlighted by single-cell technologies, which leads to the design of cell-specific therapeutic protocols for personalized medicine in RA in the future.

Properties and molecular mechanisms underlying geniposide-mediated therapeutic effects in chronic inflammatory diseases

ETHNOPHARMACOLOGICAL RELEVANCE

Geniposide (GE) is ubiquitous in nearly 40 species of plants, among which Gardenia jasminoides J. Ellis has the highest content, and has been used ethnopharmacologically to treat chronic inflammatory diseases. As a traditional Chinese medicine, Gardenia jasminoides J. Ellis has a long history of usage in detumescence and sedation, liver protection and cholestasis, hypotension and hemostasis. It is commonly used in the treatment of diabetes, hypertension, jaundice hepatitis, sprain and contusion. As a type of iridoid glycosides extracted from Gardenia jasminoides J. Ellis, GE has many pharmacological effects, such as anti-inflammatory, anti-angiogenesic, anti-oxidative, etc. AIM OF THE REVIEW: In this article, we reviewed the sources, traditional usage, pharmacokinetics, toxicity and therapeutic effect of GE on chronic inflammatory diseases, and discussed its potential regulatory mechanisms and clinical application.

RESULTS

GE is a common iridoid glycoside in medicinal plants, which has strong activity in the treatment of chronic inflammatory diseases. A large number of in vivo and in vitro experiments confirmed that GE has certain therapeutic value for a variety of chronic inflammation disease. Its mechanism of function is mainly based on its anti-inflammatory, anti-oxidant, neuroprotective properties, as well as regulation of apoptotsis. GE plays a role in the treatment of chronic inflammatory diseases by regulating cell proliferation and apoptosis, realizing the dynamic balance of pro/anti-inflammatory factors, improving the state of oxidative stress, and restoring abnormally expressed inflammation-related pathways.

CONCLUSION

According to its extensive pharmacological effects, GE is a promising drug for the treatment of chronic inflammatory diseases.

The DNA methylation Profile of Undifferentiated Arthritis Patients Anticipates their Subsequent Differentiation to Rheumatoid Arthritis

OBJECTIVE

Undifferentiated arthritis (UA) is the term used to cover all the cases of arthritis that do not fit a specific diagnosis. A significant percentage of UA patients progress to rheumatoid arthritis (RA), others to a different definite rheumatic disease, and the rest undergo spontaneous remission. Therapeutic intervention in patients with UA can delay or halt disease progression and its long-term consequences. It is therefore of inherent interest to identify those UA patients with a high probability of progressing to RA who would benefit from early appropriate therapy. We hypothesized that alterations in the DNA methylation profiles of immune cells may inform on the genetically- or environmentally-determined status of patients and potentially discriminate between disease subtypes.

METHODS

In this study, we performed DNA methylation profiling of a UA patient cohort, in which progression into RA occurs for a significant proportion of the patients.

RESULTS

We find differential DNA methylation in UA patients compared to healthy controls. Most importantly, our analysis identifies a DNA methylation signature characteristic of those UA cases that differentiate to RA. We demonstrate that the methylome of peripheral mononuclear cells can be used to anticipate the evolution of UA to RA, and that this methylome is associated with a number of inflammatory pathways and transcription factors. Finally, we design a machine-learning strategy for DNA methylation-based classification that predicts the differentiation of UA patients towards RA.

CONCLUSION

DNA methylation profiling provides a good predictor of UA-to-RA progression to anticipate targeted treatments and improve clinical management.

Chromatin accessibility landscapes of immune cells in rheumatoid arthritis nominate monocytes in disease pathogenesis

BACKGROUND

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease that involves a variety of cell types. However, how the epigenetic dysregulations of peripheral immune cells contribute to the pathogenesis of RA still remains largely unclear.

RESULTS

Here, we analysed the genome-wide active DNA regulatory elements of four major immune cells, namely monocytes, B cells, CD4⁺ T cells and CD8⁺ T cells, in peripheral blood of RA patients, osteoarthritis (OA) patients and healthy donors using Assay of Transposase Accessible Chromatin with sequencing (ATAC-seq). We found a strong RA-associated chromatin dysregulation signature in monocytes, but no other examined cell types. Moreover, we found that serum C-reactive protein (CRP) can induce the RA-associated chromatin dysregulation in monocytes via in vitro experiments. And the extent of this dysregulation was regulated through the transcription factor FRA2.

CONCLUSIONS

Together, our study revealed a CRP-induced pathogenic chromatin dysregulation signature in monocytes from RA patients and predicted the responsible signalling pathway as potential therapeutic targets for the disease.

Apremilast Inhibits Inflammatory Osteoclastogenesis

BACKGROUND

Psoriatic arthritis (PsA) is associated with bone erosion and inflammation-induced bone loss, which are mediated by osteoclasts and modulated by inflammatory cytokines. Apremilast (a selective phosphodiesterase 4 inhibitor) is efficacious in PsA and acts by inhibiting cytokine production. However, there are no direct data informing whether and how apremilast affects osteoclast formation in humans.

METHODS

Osteoclastogenic cytokine production by activated human peripheral blood mononuclear cells (PBMCs) was measured in the presence and absence of apremilast. Effects of apremilast on osteoclast differentiation were tested (i) in co-cultures of activated PBMCs and human CD14+ blood monocytes as well as (ii) in CD14+ blood monocytes stimulated with activated-PBMCs supernatant, TNF or IL-17A. Bone resorption was measured on OsteoAssay plates. Effects of apremilast on ex vivo osteoclast differentiation were compared in PsA, pre-PsA and psoriasis patients as well as in healthy controls.

RESULTS

Apremilast significantly impaired the expression of key osteoclastogenic cytokines in activated PBMCs. Furthermore, apremilast dose-dependently and significantly inhibited activated PBMC-driven osteoclast differentiation, and ex-vivo osteoclast differentiation of PBMCs derived from PsA and pre-PsA patients, but not from psoriasis patients or healthy controls. TNF and IL-17A-enhanced osteoclastogenesis and osteolytic activity of CD14+ blood monocytes from PsA patients was also significantly inhibited by apremilast. Finally, apremilast inhibited expression of the key osteoclast fusion protein DC-STAMP.

CONCLUSION

Phosphodiesterase-4 targeting by apremilast not only inhibits osteoclastogenic cytokine production, but also directly suppresses inflammation-driven osteoclastogenesis. These data provide initial evidence that apremilast has the potential to provide a direct bone protective effect in PsA.

Epigenomic and transcriptomic analysis of chronic inflammatory diseases

Chronic inflammatory diseases (CIDs) have complex pathologies that result from aberrant and persistent immune responses. However, the precise triggers and mechanisms remain elusive. An important aspect of CID research focuses on epigenetics modifications, which regulate gene expression and provide a dynamic transcriptional response to inflammation. In recent years, mounting evidence has demonstrated an association between epigenomic and transcriptomic dysregulation and the phenotypes of CIDs. In particular, epigenetic changes at cis-regulatory elements have provided new insights for immune cell-specific alterations that contribute to disease etiology. Furthermore, the advancements in single-cell genomics provide novel solutions to cell type heterogeneity, which has long posed challenges for CID diagnosis and treatment. In this review, we discuss the current state of epigenomics research of CID and the insights derived from single-cell transcriptomic and epigenomic studies.

Si Miao San Attenuates Inflammation and Oxidative Stress in Rats with CIA via the Modulation of the Nrf2/ARE/PTEN Pathway

Objective

Si Miao San (SMS) is a traditional Chinese formula used in China to treat rheumatic diseases. To date, its mechanism in rheumatoid arthritis (RA) treatment is uncertain. Our study aims to assess the antiarthritic effects of SMS in experimental arthritic rats.

Materials and Methods

SMS (8.63, 4.31, and 2.16 g/kg/day) was orally administered after the first immunization from day 14 to day 53. The effects of SMS on rats with collagen-induced arthritis (CIA) were evaluated by arthritis score and histological assessment. The levels of cytokines and anti-CII antibodies in rat serum were measured by ELISAs. The expression of oxidative stress parameters was detected by biochemical assay kits. The levels of Nrf2, HO-1, NQO1, and PTEN were determined by western blotting.

Results

Medium- and high-dose SMS treatment significantly decreased arthritis scores and alleviated ankle joint histopathology in the rats with CIA. It inhibited the production of IL-6, TNF-α, COX-2, and PGE2 in rat serum. SMS also suppressed the expression of anti-CII antibodies IgG1 and IgG2a. Moreover, SMS significantly suppressed the levels of MDA and MPO in the synovial tissues while increasing the levels of SOD and CAT in the rats with CIA. The levels of Nrf2, HO-1, NQO1, and PTEN were upregulated by SMS in rat synovial tissues.

Conclusions

This study demonstrated that SMS effectively alleviated the disease progression of CIA by decreasing the levels of proinflammatory cytokines and reducing oxidative stress damage, as indicated by IL-6, TNF-α, COX-2, and PGE2 levels; inhibiting the overproduction of MDA and MPO; and enhancing antioxidant enzymes by upregulating the Nrf2/ARE/PTEN signalling pathway.

Biologic Drugs for Rheumatoid Arthritis in the Context of Biosimilars, Genetics, Epigenetics and COVID-19 Treatment

Rheumatoid arthritis (RA) affects around 1.2% of the adult population. RA is one of the main reasons for work disability and premature retirement, thus substantially increasing social and economic burden. Biological disease-modifying antirheumatic drugs (bDMARDs) were shown to be an effective therapy especially in those rheumatoid arthritis (RA) patients, who did not adequately respond to conventional synthetic DMARD therapy. However, despite the proven efficacy, the high cost of the therapy resulted in limitation of the widespread use and unequal access to the care. The introduction of biosimilars, which are much cheaper relative to original drugs, may facilitate the achievement of the therapy by a much broader spectrum of patients. In this review we present the properties of original biologic agents based on cytokine-targeted (blockers of TNF, IL-6, IL-1, GM-CSF) and cell-targeted therapies (aimed to inhibit T cells and B cells properties) as well as biosimilars used in rheumatology. We also analyze the latest update of bDMARDs' possible influence on DNA methylation, miRNA expression and histone modification in RA patients, what might be the important factors toward precise and personalized RA treatment. In addition, during the COVID-19 outbreak, we discuss the usage of biologicals in context of effective and safe COVID-19 treatment. Therefore, early diagnosing along with therapeutic intervention based on personalized drugs targeting disease-specific genes is still needed to relieve symptoms and to improve the quality of life of RA patients.

shinyÉPICo: A graphical pipeline to analyze Illumina DNA methylation arrays

SUMMARY

Illumina DNA methylation bead arrays provide a cost-effective platform for the simultaneous analysis of a high number of human samples. However, the analysis can be time-demanding and requires some computational expertise. shinyÉPICo is an interactive, web-based, and graphical tool that allows the user to analyze Illumina DNA methylation arrays (450k and EPIC), from the user's own computer or from a server. The tool covers the entire analysis, from the raw data to the final list of differentially methylated positions and differentially methylated regions between sample groups. It allows the user to test several normalization methods, linear model parameters, including covariates, and differentially methylated CpGs filters, in a quick and easy manner, with interactive graphics helping to select the options in each step. shinyÉPICo represents a comprehensive tool for standardizing and accelerating DNA methylation analysis, as well as optimizing computational resources in laboratories studying DNA methylation.

AVAILABILITY AND IMPLEMENTATION

shinyÉPICo is freely available as an R package at the Bioconductor project (http://bioconductor.org/packages/shinyepico/) and GitHub (https://github.com/omorante/shinyepico) under an AGPL3 license.

Tolerogenic Dendritic Cells in Autoimmunity and Inflammatory Diseases

Dendritic cells (DCs), the most efficient antigen-presenting cells, are necessary for the effective activation of naïve T cells. DCs can also acquire tolerogenic functions in vivo and in vitro in response to various stimuli, including interleukin (IL)-10, transforming growth factor (TGF)-β, vitamin D3, corticosteroids, and rapamycin. In this review, we provide a wide perspective on the regulatory mechanisms, including crosstalk with other cell types, downstream signaling pathways, transcription factors, and epigenetics, underlying the acquisition of tolerogenesis by DCs, with a special focus on human studies. Finally, we present clinical assays targeting, or based on, tolerogenic DCs in inflammatory diseases. Our discussion provides a useful resource for better understanding the biology of tolerogenic DCs and their manipulation to improve the immunological fitness of patients with certain inflammatory conditions.

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.

Central Role for Adipocyte Na,K-ATPase Oxidant Amplification Loop in the Pathogenesis of Experimental Uremic Cardiomyopathy

BACKGROUND

Oxidative stress in adipocyte plays a central role in the pathogenesis of obesity as well as in the associated cardiovascular complications. The putative uremic toxin indoxyl sulfate induces oxidative stress and dramatically alters adipocyte phenotype in vitro. Mice that have undergone partial nephrectomy serve as an experimental model of uremic cardiomyopathy. This study examined the effects on adipocytes of administering a peptide that reduces oxidative stress to the mouse model.

METHODS

A lentivirus vector introduced the peptide NaKtide with an adiponectin promoter into the mouse model of experimental uremic cardiomyopathy, intraperitoneally. Then adipocyte-specific expression of the peptide was assessed for mice fed a standard diet compared with mice fed a western diet enriched in fat and fructose.

RESULTS

Partial nephrectomy induced cardiomyopathy and anemia in the mice, introducing oxidant stress and an altered molecular phenotype of adipocytes that increased production of systemic inflammatory cytokines instead of accumulating lipids, within 4 weeks. Consumption of a western diet significantly worsened the adipocyte oxidant stress, but expression of NaKtide in adipocytes completely prevented the worsening. The peptide-carrying lentivirus achieved comparable expression in skeletal muscle, but did not ameliorate the disease phenotype.

CONCLUSIONS

Adipocyte-specific expression of NaKtide, introduced with a lentiviral vector, significantly ameliorated adipocyte dysfunction and uremic cardiomyopathy in partially nephrectomized mice. These data suggest that the redox state of adipocytes controls the development of uremic cardiomyopathy in mice subjected to partial nephrectomy. If confirmed in humans, the oxidative state of adipocytes may be a therapeutic target in chronic renal failure.

Differential DNA Methylation of Networked Signaling, Transcriptional, Innate and Adaptive Immunity, and Osteoclastogenesis Genes and Pathways in Gout

OBJECTIVE

In gout, autoinflammatory responses to urate crystals promote acute arthritis flares, but the pathogeneses of tophi, chronic synovitis, and erosion are less well understood. Defining the pathways of epigenomic immunity training can reveal novel pathogenetic factors and biomarkers. The present study was undertaken to seminally probe differential DNA methylation patterns utilizing epigenome-wide analyses in patients with gout.

METHODS

Peripheral blood mononuclear cells (PBMCs) were obtained from a San Diego cohort of patients with gout (n = 16) and individually matched healthy controls (n = 14). PBMC methylome data were processed with ChAMP package in R. ENCODE data and Taiji data analysis software were used to analyze transcription factor (TF)-gene networks. As an independent validation cohort, whole blood DNA samples from New Zealand Māori subjects (n = 13 patients with gout, n = 16 control subjects without gout) were analyzed.

RESULTS

Differentially methylated loci clearly separated gout patients from controls, as determined by hierarchical clustering and principal components analyses. IL23R, which mediates granuloma formation and cell invasion, was identified as one of the multiple differentially methylated gout risk genes. Epigenome-wide analyses revealed differential methylome pathway enrichment for B and T cell receptor signaling, Th17 cell differentiation and interleukin-17 signaling, convergent longevity regulation, circadian entrainment, and AMP-activated protein kinase signaling, which are pathways that impact inflammation via insulin-like growth factor 1 receptor, phosphatidylinositol 3-kinase/Akt, NF-κB, mechanistic target of rapamycin signaling, and autophagy. The gout cohorts overlapped for 37 (52.9%) of the 70 TFs with hypomethylated sequence enrichment and for 30 (78.9%) of the 38 enriched KEGG pathways identified via TFs. Evidence of shared differentially methylated gout TF-gene networks, including the NF-κB activation-limiting TFs MEF2C and NFATC2, pointed to osteoclast differentiation as the most strongly weighted differentially methylated pathway that overlapped in both gout cohorts.

CONCLUSION

These findings of differential DNA methylation of networked signaling, transcriptional, innate and adaptive immunity, and osteoclastogenesis genes and pathways suggest that they could serve as novel therapeutic targets in the management of flares, tophi, chronic synovitis, and bone erosion in patients with gout.

Understanding the Relevance of DNA Methylation Changes in Immune Differentiation and Disease

Immune cells are one of the most complex and diverse systems in the human organism. Such diversity implies an intricate network of different cell types and interactions that are dependently interconnected. The processes by which different cell types differentiate from progenitors, mature, and finally exert their function requires an orchestrated succession of molecular processes that determine cell phenotype and function. The acquisition of these phenotypes is highly dependent on the establishment of unique epigenetic profiles that confer identity and function on the various types of effector cells. These epigenetic mechanisms integrate microenvironmental cues into the genome to establish specific transcriptional programs. Epigenetic modifications bridge environment and genome regulation and play a role in human diseases by their ability to modulate physiological programs through external stimuli. DNA methylation is one of the most ubiquitous, stable, and widely studied epigenetic modifications. Recent technological advances have facilitated the generation of a vast amount of genome-wide DNA methylation data, providing profound insights into the roles of DNA methylation in health and disease. This review considers the relevance of DNA methylation to immune system cellular development and function, as well as the participation of DNA methylation defects in immune-mediated pathologies, illustrated by selected paradigmatic diseases.