AUTHOR=Whittall-Garcia Laura , Goliad Kirubel , Kim Michael , Bonilla Dennisse , Gladman Dafna , Urowitz Murray , Fortin Paul R. , Atenafu Eshetu G. , Touma Zahi , Wither Joan 

TITLE=Identification and Validation of a Urinary Biomarker Panel to Accurately Diagnose and Predict Response to Therapy in Lupus Nephritis

JOURNAL=Frontiers in Immunology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.889931

DOI=10.3389/fimmu.2022.889931

ISSN=1664-3224

ABSTRACT=Background. We have previously shown that 15 urine biomarkers (of 129 tested by Luminex), discriminate between active Lupus Nephritis (ALN) and non-LN patients. The aim of this study was to evaluate the ability of these 15 previously identified urinary biomarkers to predict treatment responses to conventional therapy, and for the most predictive of these biomarkers to validate their utility to identify ALN patients in an independent prospectively acquired lupus cohort.
Methods: Our study had a 2-stage approach. In stage 1, we used Luminex to examine whether our previously identified urinary biomarkers at the time of the renal flare (±3 months) or 12±3 months after treatment of biopsy proven ALN could predict treatment responses. In stage 2, a larger prospectively acquired cross-sectional cohort was used to further validate the utility of the most predictive urinary biomarkers (identified in stage 1) to detect ALN patients. In this 2nd stage, cut-offs with the best operating characteristics to detect ALN patients were produced for each biomarker and different combinations and/or numbers of elevated biomarkers needed to accurately identify ALN patients were analyzed. 
Results:  Twenty-one patients were included in the stage 1. Twelve (57.14%), 4 (19.06%), and 5 (23.8%) patients had a complete (CR), partial (PR) and no (NR) remission at 24+/-3 months, respectively. The percentage decrease following 12±3 months of treatment for Adiponectin, MCP-1, sVCAM-1, PF4, IL-15 and vWF was significantly higher in patients with CR in comparison to those with PR/NR.
In stage 2, a total of 247 SLE patients were included, of which 24 (9.72%) had ALN, 79 (31.98%) had LN in remission (RLN) and 144 (58.30%) were non-LN (NLN) patients. Based on the combinations of biomarkers with the best operating characteristics we propose “rule out” and “rule in” ALN criteria. 
Conclusions: Our results provide further evidence to support the role of Adiponectin, MCP-1, sVCAM-1 and PF4 in the detection of ALN cases.  We further show the clinical utility of measuring multiple rather than a single biomarker and we propose a novel “rule in” and “rule out” criteria for the detection of ALN with excellent operating characteristics.