Serum levels of free light chains and syndecan-1 in patients with rheumatoid arthritis and systemic lupus erythematosus

Abstract

Objectives: Systemic autoimmune rheumatic diseases (SARDs) are characterized by chronic inflammation. Reliable biomarkers are crucial for diagnosis, monitoring disease progression and therapeutic responses. This study explores serum syndecan-1 (SDC-1) as a biomarker for these conditions and its relationship with free light chain (FLC) levels.

Methods: A retrospective analysis was performed on sera from 60 patients with rheumatoid arthritis (RA) and from 60 with systemic lupus erythematosus (SLE), alongside 50 healthy donors (HD). Κ- and λ- FLCs were determined by turbidimetric assay, while SDC-1 levels were determined by ELISA. Kruskal-Wallis test, Wilcoxon Mann-Whitney U test, multivariable linear regression and Spearman's correlation were employed to compare biomarker levels across groups and to explore correlations.

Results: SDC-1, κ-FLC and λ-FLC were significantly increased in RA and SLE patients compared with HD (P < 0.001), while no significant differences in the κ/λ ratio were observed among the groups (P = 0.4). A significant difference in subject age was also identified. However, multivariate regression analysis indicated that RA and SLE are significantly associated with the levels of these markers, with minimal confounding by age. A significant correlation was observed separately in all groups between the FLC markers. Conversely, no correlation was detected between SDC-1 and FLCs, nor between these markers and age or disease activity indices.

Conclusion: Elevated serum levels of FLCs and SDC-1 in RA and SLE patients compared with HD underscore their potential as biomarkers for SARDs. The findings also suggest sustained plasma cell activation, supporting the multifaceted role of SDC-1 in the pathogenesis of SARDs.

Keywords: FLC; RA; SARD; SDC-1; SLE; autoimmunity; biomarkers.

Figure 1.

Structure and shedding mechanism of syndecan-1. Syndecan-1 is composed of three main domains: the extracellular domain (ectodomain), which consists of a core protein interaction domain and heparan sulphate chains that interact with growth factors and fibronectin; a single transmembrane domain that drives syndecan dimer formation; and the highly conserved cytoplasmic domain, composed of three sub-domains that allow interaction with intracellular proteins. The shedding process involves the proteolytic cleavage of the syndecan-1 ectodomain near the plasma membrane by enzymes such as metalloproteinases (MMPs). Heparan sulphate (HS) chains can be further cleaved by heparanase. Soluble syndecan-1 is in dynamic interplay with the extracellular matrix (ECM), cytokines, chemokines, several receptors and various growth factors, acting as co-receptors and mediating numerous signalling pathways

Figure 2.

Visual representation of clinical and laboratory data for SLE and RA patients. (A) prevalence of musculoskeletal issues; (B) distribution of SLEDAI-2K disease activity scores; (C) counts of patients with positive extractable nuclear antigens (ENAs), highlighting Anti-SS-B/La antibodies; (D) breakdown of ANA titres; (E–F) levels of complement proteins C3 and C4; and (G) anti-dsDNA levels indicating autoimmune activity; (H) distribution of Sharp/van der Heijde (SvdH) scores depicting varying degrees of joint damage; (I) patterns of initial articular involvement; and (J) prevalence of rheumatoid factor (RF)

Figure 3.

Box plot analysis illustrating levels of syndecan-1 and free light chains. SDC-1 (A), k-FLC (B), λ-FLC (C) and their ratio (D). Post-hoc analysis, using a Bonferroni-corrected Wilcoxon Mann–Whitney U test, highlights significant differences between the pathological groups and healthy controls, while no significant differences are observed between RA and SLE patients. Significance levels are indicated by asterisks: *P < 0.05, **P < 0.01, ***P < 0.001 and ****P < 0.0001

Figure 4.

Correlational analysis. Correlations among demographic parameters (age), serum levels of syndecan-1, free light chains (κ, λ and their ratio) and disease activity indexes, when available. Correlations are evaluated using the Spearman correlation coefficient and are arranged in correlation matrices. (A) Correlational data for SLE patients; (B) syndecan-1 levels in SLE patients with active disease (SLEDAI-2K >6) vs inactive disease (SLEDAI-2K ≤6); in C and D we report correlational data for RA patients and healthy donors, respectively. A colour code is used for the correlation matrices: strong positive correlations are represented in dark blue, and strong negative correlations are indicated in dark red. Significant correlations are marked with an asterisk (*), with significance set at P < 0.05