Dataset Information

Differential DNA methylation correlates with response to methotrexate in rheumatoid arthritis.

ABSTRACT: OBJECTIVES:Identifying blood-based biomarkers that predict treatment response in RA is a clinical priority. We investigated differential DNA methylation as a candidate biomarker of response for the first-line drug used in RA, MTX. METHODS:DNA methylation was measured in DNA samples from individuals recruited to the Rheumatoid Arthritis Medication Study. Differentially methylated positions were compared between whole blood samples collected at baseline and at 4 weeks from patients who, by 6 months, had a good (n = 34) or poor response (n = 34) to MTX using linear modelling, adjusting for gender, age, cell composition, baseline 28-joint disease activity score (DAS28) and smoking status. Analyses also compared methylation with changes in DAS28 and changes in swollen joint count and tender joint count, and changes in CRP over the initial 6 months after MTX commencement. Differentially methylated positions showing significant differences with any response parameter were tested using pyrosequencing in an independent group of 100 patients from the Rheumatoid Arthritis Medication Study. RESULTS:In the discovery group, two CpG sites showed methylation changes at 4 weeks associated with clinical EULAR response by 6 months. Significant changes in methylation for three differentially methylated positions associated with change in tender joint counts, three with change in swollen joint count and a further four with change in CRP. Of the 12 CpGs, four showed replicated association in an independent dataset of samples from the Rheumatoid Arthritis Medication Study. CONCLUSION:These data represent an advance on current practice by contributing to a personalized medicine strategy allowing an escalation or change in therapy as early as 4 weeks.

SUBMITTER: Nair N

PROVIDER: S-EPMC7244777 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Differential DNA methylation correlates with response to methotrexate in rheumatoid arthritis.

Nair Nisha N Plant Darren D Verstappen Suzanne M SM Isaacs John D JD Morgan Ann W AW Hyrich Kimme L KL Barton Anne A Wilson Anthony G AG

Rheumatology (Oxford, England) 20200601 6

<h4>Objectives</h4>Identifying blood-based biomarkers that predict treatment response in RA is a clinical priority. We investigated differential DNA methylation as a candidate biomarker of response for the first-line drug used in RA, MTX.<h4>Methods</h4>DNA methylation was measured in DNA samples from individuals recruited to the Rheumatoid Arthritis Medication Study. Differentially methylated positions were compared between whole blood samples collected at baseline and at 4 weeks from patients ...[more]

PMID: 31598719

Similar Datasets

Project description:ObjectiveWe 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.MethodsPatients 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.ResultsWe 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.ConclusionWe 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.

Project description:BackgroundMethotrexate (MTX) is the first line treatment for rheumatoid arthritis (RA), but failure of satisfying treatment response occurs in a significant proportion of patients. Here we present a longitudinal multi-omics study aimed at detecting molecular and cellular processes in peripheral blood associated with a successful methotrexate treatment of rheumatoid arthritis.MethodsEighty newly diagnosed patients with RA underwent clinical assessment and donated blood before initiation of MTX, and 3 months into treatment. Flow cytometry was used to describe cell types and presence of activation markers in peripheral blood, the expression of 51 proteins was measured in serum or plasma, and RNA sequencing was performed in peripheral blood mononuclear cells (PBMC). Response to treatment after 3 months was determined using the EULAR response criteria. We assessed the changes in biological phenotypes during treatment, and whether these changes differed between responders and non-responders with regression analysis. By using measurements from baseline, we also tried to find biomarkers of future MTX response or, alternatively, to predict MTX response.ResultsAmong the MTX responders, (Good or Moderate according to EULAR treatment response classification, n = 60, 75%), we observed changes in 29 partly overlapping cell types proportions, levels of 13 proteins and expression of 38 genes during treatment. These changes were in most cases suppressions that were stronger among responders compared to non-responders. Within responders to treatment, we observed a suppression of FOXP3 gene expression, reduction of immunoglobulin gene expression and suppression of genes involved in cell proliferation. The proportion of many HLA-DR expressing T-cell populations were suppressed in all patients irrespective of clinical response, and the proportion of many IL21R+ T-cells were reduced exclusively in non-responders. Using only the baseline measurements we could not detect any biomarkers or prediction models that could predict response to MTX.ConclusionWe conclude that a deep molecular and cellular phenotyping of peripheral blood cells in RA patients treated with methotrexate can reveal previously not recognized differences between responders and non-responders during 3 months of treatment with MTX. This may contribute to the understanding of MTX mode of action and explain non-responsiveness to MTX therapy.

Project description:ObjectivesTo assess the differences in circulating DNA methylation levels of CXCR5 between rheumatoid arthritis (RA) and osteoarthritis (OA) and healthy controls (HC), and the correlation of methylation changes with clinical characteristics of RA patients.MethodsPeripheral blood samples were collected from 239 RA patients, 30 patients with OA, and 29 HC. Target region methylation sequencing to the promoter region of CXCR5 was achieved using MethylTarget. The methylation level of cg04537602 and methylation haplotype were compared among the three groups, and the correlation between methylation levels and clinical characteristics of RA patients was performed by Spearman's rank correlation analysis.ResultsThe methylation level of cg04537602 was significantly higher in the peripheral blood of RA patients compared with OA patients (p = 1.3 × 10-3 ) and in the HC group (p = 5.5 × 10- 4 ). The sensitivity was enhanced when CXCR5 methylation level combined with rheumatoid factor and anti-cyclic citrullinated peptide with area under curve (AUC) of 0.982 (95% confidence interval 0.970-0.995). The methylation level of cg04537602 in RA was positively correlated with C-reactive protein (CRP) (r = .16, p = .01), and in RA patients aged 60 years and above, cg04537602 methylation levels were positively correlated with CRP (r = .31, p = 4.7 × 10- 4 ), tender joint count (r = .21, p = .02), visual analog scales score (r = .21, p = .02), Disease Activity Score in 28 joints (DAS28) using the CRP level DAS28-CRP (r = .27, p = 2.1 × 10- 3 ), and DAS28-ESR (r = .22, p = .01). We also observed significant differences of DNA methylation haplotypes in RA patients compared with OA patients and HC, which was consistent with single-loci-based CpG methylation measurement.ConclusionThe methylation level of CXCR5 was significantly higher in RA patients than in OA and HC, and correlated with the level of inflammation in RA patients, our study establishes a link between CXCR5 DNA methylation and clinical features that may help in the diagnosis and disease management of RA patients.

Project description:Biologic drug therapies represent a huge advance in the treatment of rheumatoid arthritis (RA). However, very good disease control is achieved in only 30% of patients, making identification of biomarkers of response a research priority. We undertook this study to test our hypothesis that differential DNA methylation patterns may provide biomarkers predictive of response to tumor necrosis factor inhibitor (TNFi) therapy in patients with RA.An epigenome-wide association study was performed on pretreatment whole blood DNA from patients with RA. Patients who displayed good response (n?=?36) or no response (n?=?36) to etanercept therapy at 3 months were selected. Differentially methylated positions were identified using linear regression. Variance of methylation at differentially methylated positions was assessed for correlation with cis-acting single-nucleotide polymorphisms (SNPs). A replication experiment for prioritized SNPs was performed in an independent cohort of 1,204 RA patients.Five positions that were differentially methylated between responder groups were identified, with a false discovery rate of <5%. The top 2 differentially methylated positions mapped to exon 7 of the LRPAP1 gene on chromosome 4 (cg04857395, P?=?1.39 × 10(-8) and cg26401028, P?=?1.69 × 10(-8) ). The A allele of the SNP rs3468 was correlated with higher levels of methylation for both of the top 2 differentially methylated positions (P?=?2.63 × 10(-7) and P?=?1.05 × 10(-6) , respectively). Furthermore, the A allele of rs3468 was correlated with European League Against Rheumatism nonresponse in the discovery cohort (P?=?0.03; n?=?56) and in the independent replication cohort (P?=?0.003; n?=?1,204).We identify DNA methylation as a potential biomarker of response to TNFi therapy, and we report the association between response and the LRPAP1 gene, which encodes a chaperone of low-density lipoprotein receptor-related protein 1. Additional replication experiments in independent sample collections are now needed.

Project description:Methotrexate (MTX) is the standard first-line therapy in rheumatoid arthritis (RA) with variable clinical efficacy that is difficult to predict. The glycosylation status of immunoglobulin G (IgG) is altered in RA and influenced by MTX treatment. We aimed to further investigate if IgG glycosylation in untreated early RA can predict therapeutic response to MTX.We used a shotgun proteomic approach to screen for the Fc glycopeptides in the serum of 12 control subjects and 59 untreated patients with early RA prior to and following MTX initiation. MTX treatment response was defined according to the European League Against Rheumatism at a median of 14 weeks (range 13-15) after treatment initiation. Seropositive patients were defined as those testing positive for anticitrullinated protein antibodies and/or rheumatoid factor at baseline (n = 44). Data analysis was performed using uni- and multivariate statistics.We could confirm a low abundance of galactosylated glycans in untreated patients with early RA compared with control subjects that was partially restored by MTX treatment. This was more evident among future nonresponders than among responders to MTX treatment. Results were further validated and confirmed by multivariate statistical analysis of the baseline Fc glycan, proteomic, and clinical data. We found that the ratio between the main agalactosylated (FA2) and main mono- and di-galactosylated Fc glycans (FA2G1 and FA2G2) of IgG1 ranked as the most prominent factor distinguishing responders from nonresponders. A low baseline ratio of FA2/[FA2G1 + FA2G2]-IgG1 was associated with nonresponse (OR 5.3 [1.6-17.0]) and was able to discriminate future nonresponders from responders to MTX therapy with a sensitivity of 70% (95% CI 46-88%) and a specificity of 69% (95% CI 52-83%). For seropositive patients (n = 44), this trend was improved with a sensitivity of 73% (95% CI 45-92%) for nonresponse and a specificity of 79% (95% CI 60-92%).We show that the FA2/[FA2G1 + FA2G2] of IgG1 is a biomarker candidate that is significantly associated with nonresponding patients and has potential value for prediction of MTX clinical response.

Project description:BackgroundThe genetic risk associated with rheumatoid arthritis (RA) includes genes regulating DNA methylation, one of the hallmarks of epigenetic re-programing, as well as many T-cell genes, with a strong MHC association, pointing to immunogenetic mechanisms as disease triggers leading to chronicity. The aim of our study was to explore DNA methylation in early, drug-naïve RA patients, towards a better understanding of early events in pathogenesis.ResultMonocytes, naïve and memory CD4+ T-cells were sorted from 6 healthy controls and 10 RA patients. DNA methylation was assessed using a genome-wide Illumina 450K CpG promoter array. Differential methylation was confirmed using bisulfite sequencing for a specific gene promoter, ELISA for several cytokines and flow cytometry for cell surface markers. Differentially methylated (DM) CpGs were observed in 1047 genes in naïve CD4+ T-cells, 913 in memory cells and was minimal in monocytes with only 177 genes. Naive CD4+ T-cells were further investigated as presenting differential methylation in the promoter of > 500 genes associated with several disease-relevant pathways, including many cytokines and their receptors. We confirmed hypomethylation of a region of the TNF-alpha gene in early RA and differential expression of 3 cytokines (IL21, IL34 and RANKL). Using a bioinformatics package (DMRcate) and an in-house analysis based on differences in β values, we established lists of DM genes between health and RA. Publicly available gene expression data were interrogated to confirm differential expression of over 70 DM genes. The lists of DM genes were further investigated based on a functional relationship database analysis, which pointed to an IL6/JAK1/STAT3 node, related to TNF-signalling and engagement in Th17 cell differentiation amongst many pathways. Five DM genes for cell surface markers (CD4, IL6R, IL2RA/CD25, CD62L, CXCR4) were investigated towards identifying subpopulations of CD4+ T-cells undergoing these modifications and pointed to a subset of naïve T-cells, with high levels of CD4, IL2R, and CXCR4, but reduction and loss of IL6R and CD62L, respectively.ConclusionOur data provided novel conceptual advances in the understanding of early RA pathogenesis, with implications for early treatment and prevention.

Dataset Information

Differential DNA methylation correlates with response to methotrexate in rheumatoid arthritis.

Publications

Differential DNA methylation correlates with response to methotrexate in rheumatoid arthritis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets