Evaluation of Oxidative Stress and Inflammatory biomarkers in Iraqi Patients with Rheumatoid Arthritis Oxidative & Inflammatory Markers in RA

Abstract

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease in which oxidative stress and inflammation are closely linked, yet integrated evaluation of these processes in Iraqi patients remains limited. This cross-sectional case-control study included 80 adults in Baghdad, Iraq: 40 patients fulfilling the 2010 ACR/EULAR classification criteria and 40 age- and sex-matched healthy controls. Serum malondialdehyde (MDA), glutathione (GSH), total antioxidant capacity (TAC), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), tumour necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6) were measured. Between-group differences were evaluated with independent-samples t-tests, with Mann–Whitney U sensitivity analyses for selected markers, and pooled Pearson correlations were assessed using a Bonferroni-adjusted significance threshold. All seven biomarkers differed significantly between groups (all p < 0.001): MDA, TNF-α, IL-6, CRP, and ESR were higher in RA, whereas GSH and TAC were lower. Standardized mean differences were very large (Cohen’s d = 2.96–4.26). Pooled correlations showed positive associations among oxidative and inflammatory markers and inverse associations with antioxidant markers, although these coefficients may partly reflect the strong separation between cases and controls. Exploratory rank-based study-group discrimination was also high, but the healthy-control case-control design and extreme biomarker separation limit interpretation as clinical diagnostic accuracy. A parsimonious two-predictor model containing MDA and TNF-α showed strong in-sample association with case status but was not treated as a validated prediction model. These findings support concurrent redox and inflammatory abnormalities in Iraqi RA patients. Larger studies with clinical comparator groups, participant-level validation, and longitudinal follow-up are required before diagnostic or monitoring applications can be inferred.