Background Lupus nephritis (LN) is a serious manifestation of Juvenile-onset Systemic Lupus Erythematosus (JSLE), affecting up to 80% of patients . Conventional markers of JSLE disease activity fail to adequately predict impending LN flares. Renal histology is the gold standard for diagnosing and predicting renal prognosis in LN, and is rarely repeated for monitoring purposes due to its invasive nature. Single novel urine biomarkers are good at predicting and detecting LN flares , but to date, no individual urine biomarkers have achieved an “excellent” predictive value (area under the curve (AUC) >0.9).
Objectives To assess if combining novel and traditional biomarkers can result in an excellent biomarker panel for identifying active LN.
Methods Participants of the UK JSLE cohort study were aged less than 16 years at the time of diagnosis. Disease activity data was collected using the paediatric British Isles Lupus Assessment Group (pBILAG2004) score. Patients were cross-sectionally categorised as active LN (pBILAG2004 renal domain score A or B plus previous histological confirmation of LN), in-active LN (pBILAG2004 renal domain score D or E) or healthy controls (HC's). Novel urinary biomarkers; vascular cell adhesion molecule-1 (VCAM-1), monocyte chemoattractant protein 1 (MCP-1), lipocalin like prostaglandin D synthase (LPGDS), transferrin, ceruloplasmin and alpha-1-acid glycoprotein (AGP) were quantified by enzyme-linked immunosorbent assays. Neutrophil gelatinase associated lipocalin (NGAL) was measured using the Abbot Architect assay. Binary logistic regression modeling and receiver-operating curve (ROC curve) analysis assessed combinations of novel and traditional biomarkers. The study had full ethical approval in place.
Results 61 JSLE patients and 19 HC's were recruited. 15 (25%) JSLE patients had active LN and 46 (75%) had in-active LN. Urinary AGP, ceruloplasmin, VCAM-1, MCP-1, LPGDS and transferrin levels were significantly increased in active LN (all p≤0.01). Urinary NGAL levels did not differ between patient groups (p=0.245). AGP was the best single biomarker differentiating active and inactive LN (good AUC 0.890, p≤0.001). Combining novel biomarkers improved the identification of active LN (optimal combination; AGP, ceruloplasmin, LPGDS, transferrin, excellent AUC 0.923, p<0.001). Additional improvement was seen with the addition of dsDNA to this combination (excellent AUC 0.933, p≤0.001).
Conclusions A combination of novel urinary and traditional biomarkers produces an excellent “biomarker panel” for active LN identification on a cross sectional basis. It is anticipated that biomarker led monitoring will improve long-term renal outcomes in JSLE patients in the future.
Watson L, Leone V, Pilkington C, et al. Disease activity, severity, and damage in the UK Juvenile-Onset Systemic Lupus Erythematosus Cohort. Arth Rheum 2012;64(7):2356-65.
Watson L, Tullus K, Pilkington C, et al. Urine biomarkers for monitoring juvenile lupus nephritis: a prospective longitudinal study. Ped Nephrol 2013;29(3):397-405.
Disclosure of Interest None declared