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Urinary Neutrophil Gelatinase Associated Lipocalin: A Novel Biomarker Determining Steroid Responsiveness in Nephrotic Syndrome

Background: Urinary Neutrophil Gelatinase Associated Lipocalin (uNGAL) has been demonstrated to be a powerful marker of progression in chronic kidney disease. The present study was done to find out the ability of uNGAL as a biomarker to differentiate steroid-sensitive nephrotic syndrome (SSNS), ster...

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Detalles Bibliográficos
Autores principales: Kumar, Rakesh, Shekhar, Ravi, Gupta, Anand K, Kumar, Amit, Prasad, Nidhi, Kumar, Santosh, Sinha, Seema R, Prakash, Jayant
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9983706/
https://www.ncbi.nlm.nih.gov/pubmed/36874337
http://dx.doi.org/10.7759/cureus.34503
Descripción
Sumario:Background: Urinary Neutrophil Gelatinase Associated Lipocalin (uNGAL) has been demonstrated to be a powerful marker of progression in chronic kidney disease. The present study was done to find out the ability of uNGAL as a biomarker to differentiate steroid-sensitive nephrotic syndrome (SSNS), steroid-dependent nephrotic syndrome (SDNS), and steroid-resistant nephrotic syndrome (SRNS) from each other. Method: The cross-sectional study included 45 patients with Idiopathic Nephrotic Syndrome (INS) (15 each of SSNS, SDNS, and SRNS). uNGAL was measured by ELISA. Demographic profile of patients with INS, lab parameters including Serum albumin, cholesterol, urinary albumin, creatinine, etc., were estimated using standard laboratory methods. Various statistical methods were used to assay the usefulness of NGAL as a diagnostic marker. Results: Among the three groups, the median value of uNGAL was 8.68 ng/ml in SSNS, higher in SDNS (32.8 ng/ml), and highest in the SRNS group (50 ng/ml). The receiver operating curve (ROC) was generated for uNGAL to differentiate between SDNS and SSNS. Cut-off 13.26 ng/ml had a sensitivity of 86.7% and specificity of 97.4%, PPV 92.9%, and NPV 87.5 % with an area under the curve (AUC) of 0.958. Another ROC was generated for uNGAL to differentiate between SRNS and SDNS, and cut-off 40.02 ng/ml had a sensitivity of 80% and specificity of 86.7% with an AUC of 0.907. A similar result was observed when ROC was generated to differentiate SRNS from SSNS and SDNS combined. Conclusion: uNGAL can distinguish between SSNS, SDNS, and SRNS.