Urinary biomarkers of chronic allograft nephropathy

Proteomics Clin Appl. 2015 Jun;9(5-6):574-85. doi: 10.1002/prca.201400200.

Abstract

Purpose: Chronic allograft nephropathy (CAN) is widely accepted as the leading cause of renal allograft loss after the first year post transplantation. This study aimed to identify urinary biomarkers that could predict CAN in transplant patients.

Experimental design: The study included 34 renal transplant patients with histologically proven CAN and 36 renal transplant patients with normal renal function. OrbiTrap MS was utilized to analysis a urinary fraction in order to identify other members of a previously identified biomarker tree . This novel biomarker pattern offers the potential to distinguish between transplant recipients with CAN and those with normal renal function.

Results: The primary node of the biomarker pattern was reconfirmed as β2 microglobulin. Three other members of this biomarker pattern were identified: neutrophil gelatinase-associated lipocalin, clusterin, and kidney injury biomarker 1. Significantly higher urinary concentrations of these proteins were found in patients with CAN compared to those with normal kidney function.

Conclusions and clinical relevance: While further validation in a larger more-diverse patient population is required to determine if this biomarker pattern provides a potential means of diagnosing CAN by noninvasive methods in a clinical setting, this study clearly demonstrates the biomarkers' ability to stratify patients based on transplant function.

Keywords: Biomarkers; Chronic allograft nephropathy; Clusterin; NGAL; Renal transplantation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Allografts
  • Amino Acid Sequence
  • Biomarkers / urine
  • Delayed Graft Function
  • Graft Rejection / urine*
  • Humans
  • Kidney Diseases / urine*
  • Kidney Transplantation
  • Molecular Sequence Data
  • Peptide Fragments / chemistry
  • Peptide Fragments / urine*
  • Proteinuria / urine*

Substances

  • Biomarkers
  • Peptide Fragments