Affiliation:
1. Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds
2. Leeds University Business School
3. NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust
Abstract
AbstractBiomarkers for the classification of rheumatoid arthritis (RA), and particularly of anti-citrullinated peptide antibody (ACPA) negative patients, remains an important hurdle for the early initiation of treatment despite the use of 2010 classification criteria. Taking advantage of DNA-methylation patterns specific to early RA, quantitative methylation-specific qPCR (qMSP) offers a robust technology for the development of biomarker. We developed assays and established their value as RA classification biomarkers.Methods: DNA-methylation data were screened to select candidate to design for qMSP assays. 8 assays were developed and tested on 2 early inflammatory arthritis cohorts. Logistic regression and bootstrapping were used to demonstrate added value.Result: Differentially methylated CpG data were screened for candidate-CpG meeting the qMSP assay requirements. The top CpG candidate was in theTNFgene, for which we successfully developed a qMSP-assay. Significant lower DNA-methylation levels were observed in RA (p < 4x10− 9), with high predictive value (OR < 0.54/AUC < 0.198) in 2 cohorts (n = 127/n = 157). Regression using both cohorts showed improved accuracy = 87.7% and AUC = 0.944 over the model using only clinical variables (accuracy = 85.2%, AUC = 0.917). Similar data were obtained in ACPA-negative patients (n = 167, accuracy = 82.6%, AUC = 0.930) compared to clinical variable model accuracy = 79.5%, AUC = 0.892. Bootstrapping using 2000 datasets confirmed that the AUCs for the clinical + TNF-qMSP model had significant added value in both analysis.Conclusion: The qMSP technology is robust and can successfully be developed with high specificity of the TNF qMSP-assay for RA in patients with early inflammatory arthritis. It should assist classification in ACPA-negative patients providing a means of reducing delay to diagnosis and treatment.
Publisher
Research Square Platform LLC