Affiliation:
1. Department of Pathology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
2. Department of Clinical Immunology & Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
Abstract
Introduction: Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease with various clinical manifestations and approximately 50% of the SLE patients develop lupus nephritis (LN), which increases the risk of renal failure, cardiovascular diseases and overall survival. Objectives: Evaluation of neutrophil-derived parameters (Neut-X, Neut-Y and Neut-Z) as an inflammatory, disease activity marker and as a predictor of nephritis in SLE patients. Material and Methods: In this cross-sectional study, 3 ml K3EDTA blood was taken from 110 SLE patients presented in Department of Clinical Immunology to evaluate neutrophil-derived parameters in Sysmex XT2000i haematology analyser and their correlation with other inflammatory biomarkers like, erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) as well as SLE disease activity index-2000 (SLEDAI-2K). 24-hours urine protein levels were also estimated as a marker of renal involvement. Records of renal biopsy were available in 73 SLE patients, who belonged to different morphologic classification of LN. Results: After performing bivariate Spearman correlation analysis (SPSS software, version 26.0), Neut-X (measures cytoplasmic granularity by side scattering) and Neut-Z (vector sum of Neut-X and Neut-Y) showed a significant positive correlation ( r > 0.200, P < .05) with ESR, CRP and SLEDAI-2K while Neut-Y (measures nucleic acid content by sideward fluorescence) showed a significant negative correlation ( r > 0.200, P < .05) with ESR and CRP. Receiver-operating characteristic curve analysis was used to evaluate diagnostic value of 24-hour urine protein and predictive values of neutrophil-derived parameters for renal involvement in SLE patients. Among neutrophil-derived parameters, Neut-X was found to be the best predictor of renal dysfunction with highest AUC of 0.710 (95% CI: 0.604-0.816; cut-off: 1344.50; sensitivity: 84.7%; specificity: 50%) followed by Neut-Z with AUC of 0.707 (95% CI: 0.600-0.813; cut-off: 1403.67; sensitivity: 87.5%; specificity: 50%). Conclusion: Our study shows that neutrophil-derived parameters may be used as novel cost-effective, non-invasive biomarker of disease activity as well as for predicting renal involvement in SLE patients.