Biomarker panels may be superior over single molecules in prediction of renal flares in systemic lupus erythematosus: an exploratory study. (24th March 2020)

• Record Type: Journal Article
• Authors: Fasano, Serena; Pierro, Luciana; Borgia, Alessia; Coscia, Melania Alessia; Formica, Ranieri; Bucci, Laura; Riccardi, Antonella; Ciccia, Francesco
• Is Part Of: Rheumatology. Volume 59:Number 11(2020)
• Page Start: 3193
• Page End: 3200
• Publication Date: 2020-03-24
• Subjects: systemic lupus erythematosus -- lupus nephritis -- biomarkers; Rheumatism -- Periodicals; Rheumatology -- Periodicals; 616.723005
• DOI: 10.1093/rheumatology/keaa074
• Languages: English
• ISSNs: 1462-0324

Abstract

Abstract: Objective: Recent evidence suggests that some urinary biomarkers, namely Vascular Cell Adhesion Molecule-1 (VCAM-1), Intercellular Adhesion Molecule-1 (ICAM-1), Monocyte Chemoattractant Protein 1 (MCP-1), Neutrophil Gelatinase Associated Lipocalcin and Lipocalin-type Prostaglandin D-Synthetase (L-PGDS), might discriminate SLE patients with ongoing renal activity from those with stable disease. The objective of this study was to assess the role of these markers in predicting renal flares in comparison with conventional biomarkers and to derive a biomarker panel which may improve diagnostic accuracy. Methods: Eligible participants were SLE patients prospectively followed at our clinic. Urinary biomarker levels were measured in urinary sample by ELISA assay and were compared by the unpaired Student's t test or the Mann–Whitney U test as appropriate. Receiver operating characteristic analysis was used to calculate the area under the curve. Cox regression was used to identify independent factors associated with disease flares. Results: Urine was collected from 61 patients. During 8 months' follow-up, eight patients experienced a renal flare. Urinary L-PGDS, ICAM-1 and VCAM-1 levels were significantly increased in the patients who subsequently experienced a renal flare with respect to the remaining 53. At Cox regression analysis, L-PGDS, ICAM-1, VCAM-1, hypocomplementemia and anti-dsDNA antibodies were factors associated with renal flares. Based on receiver operating characteristic analysis, a combination of novel and conventional biomarkers demonstrated an excellent ability for accurately identifying a flare. Conclusion: This study might suggest the usefulness of a novel biomarker panel in predicting a renal flare in SLE.