P03 Novel Urine Biomarkers For Monitoring Disease Activity in Juvenile Lupus Nephritis: A Prospective Longitudinal Validation Study

Abstract

Introduction: Systemic Lupus Erythematosus (SLE) is a severe autoimmune condition with lupus nephritis (LN) seen more frequently in juvenile disease (JSLE) where up to 80% have renal involvement [1]. The renal biopsy is crucial for diagnosis and classification but has a limited role in monitoring. Current methods of monitoring renal disease activity over time rely on a variety of standard laboratory markers and the use of disease activity tools such as the British Isles Lupus Assessment Group index score (BILAG). Improving methods of monitoring and predicting disease activity changes may allow earlier intervention and improve the long-term renal outcome. Patients & Methods: This prospective longitudinal study aimed to identify whether standard and/or novel biomarkers are useful for monitoring and predicting LN disease activity. Using patients recruited to the UK JSLE study, urine and blood samples were collected during routine clinical reviews. The study had full ethical approval. Results: The JSLE cohort (n=64), seen at 3 (interquartile range IQR: 2- 5) clinical reviews over 364 (182-532) days were aged 14.1 (11.8-15.8) years and 80% female. Active renal episodes (23% total; renal BILAG A/B) had significantly increased concentration of; monocyte chemoattractant protein 1 (MCP1), neutrophil gelatinase associated lipocalin (NGAL), erythrocyte sedimentation rate, anti-double stranded DNA, urine albumin:creatinine ratio (UACR), creatinine, and reduced complement 3 (C3), C4 and lymphocytes. Multivariate analysis demonstrated MCP1 and C3 as independent variables (p<0.001) for active renal disease. MCP1 was an excellent predictor of improved renal disease (area under the curve AUC: 0.81; p=0.013; concentration 343pg/ml, specificity 71%, sensitivity 70%); NGAL was a good predictor of worsened renal disease activity (AUC 0.76; p=0.04; concentration 30ng/ml, specificity 60%, sensitivity 61%). Urine MCP1 and uNGAL changed as subsequent renal disease changed (MCP1 p=0.015; NGAL p=0.038). Standard markers could not predict disease activity changes. Conclusions: We have demonstrated that biomarkers (MCP1 C3) perform well for monitoring renal disease in JSLE, and novel biomarkers (MCP1 NGAL) out perform standard markers for predicting change. Biomarker-led monitoring may facilitate the titration of medication and allow earlier diagnosis and intervention opportunities. Collaboration with industry to develop point of care urine biomarker testing is now in progress.