Literature DB >> 21136927

Identification of Apolipoprotein AI as a serum biomarker of chronic kidney disease in liver transplant recipients, using proteomic techniques.

Aisling O'Riordan1, Olwyn Johnston, Tara McMorrow, Kieran Wynne, Patricia Maguire, John E Hegarty, Aidan McCormick, Alan J Watson, Gerard Cagney, William M Gallagher, Michael P Ryan.   

Abstract

Chronic kidney disease (CKD) is a common complication post-orthotopic liver transplantation (OLT). Development of CKD is detected by monitoring serum urea and creatinine, however disease can occasionally be at an advanced stage before they become abnormal. Therefore, more accurate parameters are required. In order to identify novel biomarkers of CKD, serum was obtained from 47 OLT recipients with CKD (glomerular filtration rate <60 mL/min) and 23 with normal renal function (glomerular filtration rate >90 mL/min). Using the proteomic technique SELDI-TOF-MS, three protein biomarkers (55.6 kDa, 9.5 kDa and 11.4 kDa) were identified that, together, could stratify patients into cases or controls with a sensitivity and specificity of 93.6 and 91.3%, respectively. The area under the curve was 0.94. The primary splitter of the groups at 55.6 kDa was an alternative version of a molecule at 27.8 kDa, which was subsequently identified by 1-D SDS-PAGE and LC-ESI-MS/MS to be Apolipoprotein AI. Protein expression was shown to be reduced in CKD, by both ELISA (p = 0.057) and Western blot analysis (p = 0.003). Apolipoprotein AI is a novel, accurate marker of CKD post-OLT. It does require further validation in a large, more diverse patient population but could potentially improve detection of CKD.
Copyright © 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Year:  2008        PMID: 21136927     DOI: 10.1002/prca.200780167

Source DB:  PubMed          Journal:  Proteomics Clin Appl        ISSN: 1862-8346            Impact factor:   3.494


  2 in total

1.  Clinical and plasma proteomic markers correlating with chronic kidney disease after liver transplantation.

Authors:  J Levitsky; D R Salomon; M Abecassis; P Langfelder; S Horvath; J Friedewald; E Wang; S M Kurian; T Mondala; S Gil; R McDade; K Ballard; L Gallon
Journal:  Am J Transplant       Date:  2011-07-27       Impact factor: 8.086

2.  Discovery and Validation of a Biomarker Model (PRESERVE) Predictive of Renal Outcomes After Liver Transplantation.

Authors:  Josh Levitsky; Sumeet K Asrani; Goran Klintmalm; Thomas Schiano; Adyr Moss; Kenneth Chavin; Charles Miller; Kexin Guo; Lihui Zhao; Linda W Jennings; Merideth Brown; Brian Armstrong; Michael Abecassis
Journal:  Hepatology       Date:  2020-01-28       Impact factor: 17.425

  2 in total

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