Abstract
Rheumatoid arthritis (RA) and osteoarthritis (OA) are common, but pathophysiologically distinct disorders that disproportionately affect postmenopausal women. Conventional biomarkers remain limited, particularly in seronegative RA and early OA. This study evaluated a multidimensional biomarker panel covering inflammatory, oxidative, hormonal, and extracellular matrix (ECM) markers to define disease-related patterns and discriminatory potential. A cross-sectional case-control study was conducted on 90 postmenopausal women classified into RA, OA, and healthy control groups (n=30 each). Serum C-reactive protein (CRP), anti-cyclic citrullinated peptide (anti-CCP), interleukin-33 (IL-33), interleukin-36 (IL-36), estradiol (E2), matrix metalloproteinase-13 (MMP-13), and aggrecan were measured by ELISA. Oxidative stress was assessed using malondialdehyde (MDA) and oxidative stress index (OSI). RA activity was quantified using DAS28-CRP. Statistical analyses included ANOVA, Spearman correlation, separate age- and BMI-adjusted binary logistic regression models for each biomarker, and ROC analysis with stratified bootstrap internal validation (2000 resamples). Compared with OA and controls, RA showed higher CRP, anti-CCP, IL-33, IL-36, MDA, OSI, MMP-13 and aggrecan levels and lower E2. OA showed moderate changes in IL-33, IL-36, oxidative indices, and ECM turnover, consistent with a low-grade inflammatory phenotype. In RA, DAS28-CRP correlated positively with IL-33, IL-36, OSI, MMP-13, and aggrecan, and negatively with E2. Several biomarkers showed age- and BMI-adjusted associations with disease status. ROC analysis provided clear within-cohort discriminatory estimates. Multidimensional biomarker profiling identified distinct but overlapping pathogenic patterns across RA, OA, and controls in postmenopausal women. However, these exploratory estimates require external confirmation in larger independent cohorts before clinical use.