Prediction of the progression of undifferentiated arthritis to rheumatoid arthritis using DNA methylation profiling

Objective The term "undifferentiated arthritis (UA)" is used to refer to all 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. This study was undertaken to investigate whether alterations in the DNA methylation profiles of immune cells may provide information on the genetically or environmentally determined status of patients and potentially discriminate between disease subtypes. Methods We performed DNA methylation profiling of a UA patient cohort, in which progression to RA occurred for a significant proportion of the patients. Results We found differential DNA methylation in UA patients compared to healthy controls. Most importantly, our analysis identified a DNA methylation signature characteristic of those UA cases that differentiated to RA. We demonstrated 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 designed a machine learning strategy for DNA methylation-based classification that predicts the differentiation of UA toward RA. Conclusion Our findings indicate that DNA methylation profiling provides a good predictor of UA-to-RA progression to anticipate targeted treatments and improve clinical management.Pathophysiology and treatment of rheumatic disease

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

Identifying predictive biomarkers at early stages of early inflammatory arthritis is crucial for starting appropriate therapies to avoid poor outcomes. Monocytes 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) monocytes in a prospective cohort of early inflammatory arthritis patients. Undifferentiated arthritis (UA) blood monocyte DNA methylation profiles exhibited significant alterations in comparison with those from healthy donors. We identified additional differences both in blood and SF monocytes after comparing UA patients grouped by their future outcomes, good versus poor. Patient profiles in subsequent visits revealed a reversion towards a healthy level in both groups, those requiring disease-modifying antirheumatic drugs (DMARDs) and those that remitted spontaneously. Changes in disease activity between visits also impacted DNA methylation, partially concomitant in the SF of UA and in blood monocytes of rheumatoid arthritis patients. 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 in early untreated UA patients for the personalized clinical management of early inflammatory arthritis patients

Single-cell Atlas of common variable immunodeficiency shows germinal center-associated epigenetic dysregulation in B-cell responses

Common variable immunodeficiency (CVID), the most prevalent symptomatic primary immunodeficiency, displays impaired terminal B-cell differentiation and defective antibody responses. Incomplete genetic penetrance and ample phenotypic expressivity in CVID suggest the participation of additional pathogenic mechanisms. Monozygotic (MZ) twins discordant for CVID are uniquely valuable for studying the contribution of epigenetics to the disease. Here, we generate a single-cell epigenomics and transcriptomics census of naïve-to-memory B cell differentiation in a CVID-discordant MZ twin pair. Our analysis identifies DNA methylation, chromatin accessibility and transcriptional defects in memory B-cells mirroring defective cell-cell communication upon activation. These findings are validated in a cohort of CVID patients and healthy donors. Our findings provide a comprehensive multi-omics map of alterations in naïve-to-memory B-cell transition in CVID and indicate links between the epigenome and immune cell cross-talk. Our resource, publicly available at the Human Cell Atlas, gives insight into future diagnosis and treatments of CVID patients

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

Objective The term "undifferentiated arthritis (UA)" is used to refer to all 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. This study was undertaken to investigate whether alterations in the DNA methylation profiles of immune cells may provide information on the genetically or environmentally determined status of patients and potentially discriminate between disease subtypes. Methods We performed DNA methylation profiling of a UA patient cohort, in which progression to RA occurred for a significant proportion of the patients. Results We found differential DNA methylation in UA patients compared to healthy controls. Most importantly, our analysis identified a DNA methylation signature characteristic of those UA cases that differentiated to RA. We demonstrated 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 designed a machine learning strategy for DNA methylation-based classification that predicts the differentiation of UA toward RA. Conclusion Our findings indicate that DNA methylation profiling provides a good predictor of UA-to-RA progression to anticipate targeted treatments and improve clinical management.Pathophysiology and treatment of rheumatic disease

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

Objective: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease that mainly targets joints. Monocytes and macrophages are critical in RA pathogenesis and contribute to inflammatory lesions. These extremely plastic cells respond to extracellular signals which cause epigenomic changes that define their pathogenic phenotype. Here, we interrogated how DNA methylation alterations in RA monocytes are determined by extracellular signals. Methods: High-throughput DNA methylation analyses of patients with RA and controls and in vitro cytokine stimulation were used to investigate the underlying mechanisms behind DNA methylation alterations in RA as well as their relationship with clinical parameters, including RA disease activity. Results: The DNA methylomes of peripheral blood monocytes displayed significant changes and increased variability in patients with RA with respect to healthy controls. Changes in the monocyte methylome correlate with DAS28, in which high-activity patients are divergent from healthy controls in contrast to remission patients whose methylome is virtually identical to healthy controls. Indeed, the notion of a changing monocyte methylome is supported after comparing the profiles of same individuals at different stages of activity. We show how these changes are mediated by an increase in disease activity-associated cytokines, such as tumour necrosis factor alpha and interferons, as they recapitulate the DNA methylation changes observed in patients in vitro. Conclusion: We demonstrate a direct link between RA disease activity and the monocyte methylome through the action of inflammation-associated cytokines. Finally, we have obtained a DNA methylation-based mathematical formula that predicts inflammation-mediated disease activity for RA and other chronic immune-mediated inflammatory diseases.We thank CERCA Programme/Generalitat de Catalunya for institutional support. EB was funded by the Spanish Ministry of Economy and Competitiveness (MINECO; grant numbers SAF2014-55942-R and SAF2017-88086-R). JDC was funded by FIS grant (PI17/00993) from Institute of Health Carlos III (ISCIII). JDC, JM and EB are supported by RETICS network grant from ISCIII (RIER, RD16/0012/0013), FEDER 'Una manera de hacer Europa

Single-cell Atlas of common variable immunodeficiency shows germinal center-associated epigenetic dysregulation in B-cell responses.

Funder: Wellcome TrustCommon variable immunodeficiency (CVID), the most prevalent symptomatic primary immunodeficiency, displays impaired terminal B-cell differentiation and defective antibody responses. Incomplete genetic penetrance and ample phenotypic expressivity in CVID suggest the participation of additional pathogenic mechanisms. Monozygotic (MZ) twins discordant for CVID are uniquely valuable for studying the contribution of epigenetics to the disease. Here, we generate a single-cell epigenomics and transcriptomics census of naïve-to-memory B cell differentiation in a CVID-discordant MZ twin pair. Our analysis identifies DNA methylation, chromatin accessibility and transcriptional defects in memory B-cells mirroring defective cell-cell communication upon activation. These findings are validated in a cohort of CVID patients and healthy donors. Our findings provide a comprehensive multi-omics map of alterations in naïve-to-memory B-cell transition in CVID and indicate links between the epigenome and immune cell cross-talk. Our resource, publicly available at the Human Cell Atlas, gives insight into future diagnosis and treatments of CVID patients