Sargent, Thomas James ORCID: https://orcid.org/0000-0002-4114-4540 (2023) TNF gene promoter DNA methylation level in early rheumatoid arthritis. MSc by research thesis, University of Leeds.
Abstract
Background: To improve disease outcomes, Rheumatoid Arthritis (RA) should be treated early as possible. The role of biomarkers is essential to facilitate diagnosis and early access to treatment. Epigenetic modification is an important mechanism that could act as a biomarker in early RA. The value of differential methylation of the TNF gene was explored as a biomarker using the quantitative methylation specific qPCR (qMSP).
Hypothesis: There will be significant difference in the percentage of DNA methylation of the TNF gene in patients with RA.
Objective: To measure percentage DNA methylation of the TNF gene from PBMC samples of patients with early drug naïve inflammatory arthritis using a qMSP assay to measure difference in TNF gene methylation between RA and non-RA in patient from an early inflammatory arthritic clinic and see whether it can be utilised as a biomarker to predict the diagnosis of RA.
Methods: A qMSP assay was developed to measure DNA methylation from blood samples. PBMC samples from the IACON and RADAR cohorts (n=312). Logistic regression was used to establish the added value of the assay compared to clinical data only.
Results: Percentage DNA-methylation of the TNF gene was significantly lower in RA (median 3.13) compared with other forms of inflammatory arthritis (median 6.61), with a p-value 4.1x10-9 by MWU, distinguishing early RA from other forms of inflammatory arthritis. Using Forward logistic regression, the qMSP assay performed well, with an OR of 1.840 (95%CI: 1.567-2.162, p<0.0001) and an AUROC of 0.826 (0.771-0.881) for predicting RA. The reference model predicted 87.8% of cases with an AUC=0.950 (P=≤0.0001). Adding the TNF DNA methylation levels increased the prediction accuracy by +1.7% (89.4%) accuracy and an AUC=0.967 (P=≤0.0001).
Conclusion: The outcome is the characterisation of a novel biomarker of early RA which could be utilised to improve the management of RA.
Metadata
Supervisors: | Ponchel, Frederique and Mankia, Kulveer |
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Awarding institution: | University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) |
Depositing User: | Mr Thomas James Sargent |
Date Deposited: | 16 Nov 2023 16:03 |
Last Modified: | 06 Dec 2023 16:29 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:33808 |
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