Urinary peptide patterns in native kidneys and kidney allografts

Yan Zhang, William S. Oetting, Stephen B. Harvey, Matthew D. Stone, Teresa Monkkonen, Arthur J. Matas, Fernando G. Cosio, Gary L. Nelsestuen

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

BACKGROUND.: The use of biopsies to determine kidney health after kidney transplantation is an invasive procedure with some risk to the patient. Consequently, a noninvasive test for transplanted kidney health would provide a significant advantage over current clinical practice. METHODS.: Urines from kidney donors before nephrectomy, pretransplant patients with native kidney disease, and posttransplant kidney recipients were examined for protein biomarkers to diagnose or prognose kidney disease. Proteins were extracted by C4 reverse phase affinity and analyzed by matrix assisted laser desorption/ionization time-of-flight mass spectrometry. RESULTS.: Urine from individuals with healthy kidneys showed few components other than two ubiquitous saposin B glycoisoforms. Patients with kidney disease lacked saposin B and showed new components in two patterns: the most common contained β-2 microglobulin (B2M, m/z=11,732) plus one or more peaks at m/z=10,350, 9480, 4337, and 4180. Pattern 2 lacked β-2 microglobulin but contained several degradation products of ±-1 antitrypsin. Other pathologic components included urinary protein 1 (m/z=15,835), transthyretin (m/z=13,880), and a component at m/z=13,350. CONCLUSIONS.: Patients with acute rejection showed profiles that ranged from those of kidney donors to those of advanced kidney disease. The range of patterns may be useful for analysis of transplant patients without complications and persons with developing kidney disease before or after transplant.

Original languageEnglish (US)
Pages (from-to)1807-1813
Number of pages7
JournalTransplantation
Volume87
Issue number12
DOIs
StatePublished - Jun 27 2009

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Keywords

  • Acute rejection
  • Biomarkers
  • Kidney allografts
  • Protein profiles
  • Proteomics

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