Background: Renal involvement is common in systemic lupus erythematosus (SLE) and can lead to chronic kidney disease (CKD). Diagnosis of lupus nephritis (LN) is dependent on renal biopsy. Due to its invasiveness, repeat renal biopsy for monitoring disease activity is not recommended, thus creating a need for noninvasive and accurate biomarkers. Monocyte chemoattractant protein-1 (MCP-1) and tumour necrosis factor-like weak inducer of apoptosis (TWEAK) have been implicated in the pathogenesis of LN and are thus potential biomarkers for disease activity monitoring. Methods: In this study urinary MCP-1 (uMCP-1) and TWEAK (uTWEAK), together with standard markers of disease activity, were analysed in a cohort of 50 biopsy-proven LN patients at baseline, after sixmonths of induction therapy, and at one-year. Results: Throughout the study there was correlation between uMCP-1 and uTWEAK (r=0.52, p< 0.001). Both biomarkers also correlated with standard of care tests and clinical scores. The median [interquartile range] of uMCP-1 and uTWEAK were significantly increased in the active group when compared to the quiescent group (1440 [683–2729] vs 256 [175–477] pg/mL, p< 0.0001, and 209 [117–312] vs 74 [11– 173] pg/mL, p=0.0008, respectively). After completion of induction therapy in the active group, there was no significant difference in biomarker results between the groups. The sensitivity and specificity for indicating disease activity was 95% and 73% for uMCP-1 (area under curve [AUC]=0.875), and 60% and 90% for uTWEAK (AUC=0.783), respectively. Conclusion: uMCP-1 and uTWEAK reflect LN disease activity, and correlate with standard of care biomarkers in a South African cohort. Further studies are needed to assess additional clinical benefit.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/33899 |
Date | 15 September 2021 |
Creators | Rusch, Jody Alan |
Contributors | Okpechi, Ikechi Gareth, Omar, Fierdoz |
Publisher | Faculty of Health Sciences, Division of Chemical Pathology |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Master Thesis, Masters, MMed |
Format | application/pdf |
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