A recent study identified unique peripheral biomarker signatures that could enhance the detection of rheumatoid arthritis–associated interstitial lung disease beyond traditional clinical risk factors.
In the study, published in Arthritis & Rheumatology, investigators analyzed data from 2,001 participants in the Veterans Affairs (VA) Rheumatoid Arthritis registry, 6.4% (n = 121) of whom had rheumatoid arthritis–associated interstitial lung disease (RA-ILD). Participants with RA-ILD were older (mean age = 67.4 vs 63.5 years, P < .001) and predominantly male (94.2% vs 88.3%, P = .05) compared with those without ILD.
The investigators used principal component analysis (PCA) to categorize biomarkers into distinct profiles, identifying 15 principal components, with eight significantly associated with RA-ILD after adjusting for age, sex, race, and smoking history. These included pro-inflammatory cytokines, autoantibodies (anti-CCP, RF, and anti-MAA adducts), adipokines, alarmins, and markers of neutrophil chemotaxis.
Integrating these biomarker signatures with the MUC5B rs35705950 promoter variant significantly improved RA-ILD risk stratification, yielding an area under the curve (AUC) of 0.75 compared with 0.63 for clinical risk factors alone (P < .001). Notably, the biomarker signature model also outperformed models combining clinical factors with MUC5B alone (AUC = 0.75 vs 0.68).
Specific biomarker profiles strongly linked to RA-ILD included PC3 (innate immune cytokines: interleukin [IL]-3, IL-5, IL-15, and interferon alpha–2a) and PC8 (adipokines and cytokines: Fms-like tyrosine kinase 3 ligand, leptin, fractalkine, and fibroblast growth factor-21). Autoantibody-associated PCs (PC4, PC6, and PC7) were also elevated in RA-ILD cases, underscoring their role in disease pathogenesis.
Subgroup analysis revealed that the usual interstitial pneumonia pattern had stronger associations with specific biomarkers, particularly IL-17e/IL-25 and thymic stromal lymphopoietin, suggesting potential differences in RA-ILD pathophysiology.
"Peripheral biomarker signatures are associated with RA-ILD and improve RA-ILD identification beyond clinical risk factors," said lead study author Austin M. Wheeler, MD, of the VA Nebraska–Western Iowa Health Care System and the University of Nebraska Medical Center, and colleagues.
Despite its cross-sectional design and predominantly male cohort, internal validation confirmed the robustness of the biomarker-based predictive model. The findings suggested diverse pathways in RA-ILD pathogenesis and highlighted the need for further research into biomarker-driven risk stratification, disease monitoring, and treatment response assessment in patients with RA.
Full disclosures are available in the study.
