Child Kidney Dis.  2021 Dec;25(2):92-111. 10.3339/jkspn.2021.25.2.92.

Biomarkers Predicting Treatment-Response in Nephrotic Syndrome of Children: A Systematic Review

• Lee JM
• Ahn YH
• Lim SH
• Kang HG

• KMID: 2524511
• DOI: http://doi.org/10.3339/jkspn.2021.25.2.92

Abstract

Purpose
Nephrotic syndrome (NS) is the most common form of glomerulopathy in children. Most pediatric patients respond to glucocorticosteroid treatment (steroid-sensitive NS, SSNS), while approximately 10–15% will remain unresponsive or later become steroid-resistant. There has been a long-standing effort to find biomarkers that may predict steroid responsiveness.
Methods
We systematically reviewed current studies which investigated clinically relevant biomarkers for predicting steroid responsiveness in pediatric NS. We performed a PubMed and EMBASE search to identify eligible articles. We collected data on urinary markers, blood/serum markers (including cellular phenotypes and mRNA expression), genotypes and HLA allele frequency.
Results
A total of 659 articles were identified following electronic and manual searches. After reviewing the titles, abstracts, and full texts, 72 eligible articles were finally included. Vitamin D-binding protein (VDBP) seemed to be significantly elevated in SRNS than in SSNS, in both serum and urine specimen, although further validation is required.
Conclusions
The present paper narratively illustrates current understandings of potential biomarkers that may help predict steroid responsiveness. Further investigation and collaboration involving a larger number of patients are necessary.

Keyword

Nephrotic syndrome; Steroid resistant; Biomarker; Treatment; Pediatric

Figure

• 

  Fig. 1. Flow chart of literature search. NS, nephrotic syndrome; SSNS, steroid sensitive NS; SRNS, steroid resistant nephrotic syndrome.

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  Fig. 2. Prediction of SRNS using immunoglobulin.

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  Fig. 3. Prediction of SRNS using suPAR.

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  Fig. 4. Distribution of ACE polymorphism and the risk of SRNS.

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  Fig. 5. Distribution of MDR1 polymorphism and the risk of SRNS.

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  Fig. 6. Distribution of MIF and CYP3A5 polymorphism and the risk of SRNS.

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  Fig. 7. Distribution of TNFα and IL-6 polymorphism and the risk of SRNS.

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  Fig. 8. Distribution of podocin polymorphism and the risk of SRNS.

Reference

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