1750: Urinary Proteomic Signature Identifies Rheumatoid Arthritis Patients at Risk for Interstitial Lung Disease

Background/Purpose: Interstitial lung disease (ILD) is a serious pulmonary complication of rheumatoid arthritis (RA), contributing significantly to morbidity and mortality. Non-invasive tools for identifying ILD risk in RA patients remain limited. As a stable and accessible biofluid, urine represents a promising source of biomarkers. We aimed to identify ILD-associated urinary proteomic signatures and evaluate their potential utility for risk stratification and clinical assessment.

Methods: We analyzed the urine proteome of 78 RA patients (14 with ILD and 64 without ILD) using data-independent acquisition (DIA) liquid chromatography-tandem mass spectrometry (LC-MS). ILD-associated proteins were identified through differential expression analysis and LASSO regression, supported by 1000 bootstrap iterations. Candidate markers were evaluated using logistic regression, ROC analysis, and correlation with pulmonary function.

Results: A total of 2,482 urinary proteins were quantified. Differential expression analysis, LASSO regression, and 1,000 bootstrap iterations (Figure 1) jointly identified two robust ILD-associated proteins: SPOCK1 and PGRMC1, both significantly upregulated in RA-ILD patients (p < 0.001). A composite Urine_ILD_Score was constructed based on their expression levels. The score was significantly elevated in ILD patients (p < 0.001; Figure 2A) and associated with pulmonary impairment. In ROC analysis, the score demonstrated high discriminatory ability (AUC = 0.904, p < 0.0001), outperforming either protein alone (SPOCK1: AUC = 0.812; PGRMC1: AUC = 0.786; Figure 2D). In multivariable logistic regression adjusting for age and sex, the Urine_ILD_Score remained independently associated with ILD (OR = 6.19, 95% CI [2.34–24.64], p = 0.002; Figure 2C). A combined multivariable model incorporating clinical covariates further improved classification performance (AUC = 0.950; Figure 2D). Importantly, PGRMC1 levels correlated positively with KL-6 (r = 0.79, p = 0.028) and negatively with total lung capacity (TLC%) (r = –0.79, p = 0.048), suggesting potential relevance to ILD pathogenesis and severity.

Conclusion: Urinary proteomic profiling can identify RA patients at increased risk for ILD. A composite score based on SPOCK1 and PGRMC1 provides a promising, non-invasive biomarker for ILD risk stratification in RA and may support clinical decision-making and patient monitoring.