Literature DB >> 17971501

Interference of globin genes with biomarker discovery for allograft rejection in peripheral blood samples.

Li Li1, Lihua Ying, Maarten Naesens, Wenzhong Xiao, Tara Sigdel, Sue Hsieh, Jon Martin, Rong Chen, Kang Liu, Michael Mindrinos, Ron Davis, Minnie Sarwal.   

Abstract

Microarray technology is a powerful tool in the discovery of new biomarkers for disease. After solid organ transplantation, where the detection of rejection is usually made on invasive biopsies, it could be hypothesized that noninvasive transcriptional profiling of peripheral blood will reveal rejection-specific expression patterns from circulating immune cells. However, in kidney transplant rejection, the analysis of gene expression data in whole blood has proven difficult for detecting significant genes specific for acute graft rejection. Previous studies have demonstrated that the abundance of globin genes in whole blood may mask the underlying biological differences between whole blood samples. In the present study, we compared the gene expression profiles of peripheral blood of nine stable renal allograft recipients with seven matched patients having an ongoing acute renal transplant rejection, using four different protocols of preparation, amplification, and synthesis of cRNA or cDNA and hybridization on the Affymetrix platform. We demonstrated that the globin reduction method is not sufficient to unmask clinically relevant rejection-specific transcriptome profiles in whole blood. Applying an additional mathematical depletion of the globin genes improves the efficacy of globin reduction but cannot remove the confounding influence of globin gene hybridization. Sampling of peripheral blood leukocytes alone, without the confounding influence of globin mRNA, provides sensitive and specific peripheral signatures for graft rejection, with many of these signals overlapping with rejection-driven tissue (kidney)-specific signatures from matched biopsies. Similar applications may exist for array-based biomarker discovery for other diseases associated with changes in leukocyte trafficking, activation, or function.

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Year:  2007        PMID: 17971501     DOI: 10.1152/physiolgenomics.00216.2007

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


  23 in total

Review 1.  Molecular diagnostics in transplantation.

Authors:  Maarten Naesens; Minnie M Sarwal
Journal:  Nat Rev Nephrol       Date:  2010-08-24       Impact factor: 28.314

Review 2.  Recent advances in biomarker discovery in solid organ transplant by proteomics.

Authors:  Tara K Sigdel; Minnie M Sarwal
Journal:  Expert Rev Proteomics       Date:  2011-12       Impact factor: 3.940

Review 3.  A genomic approach to human autoimmune diseases.

Authors:  Virginia Pascual; Damien Chaussabel; Jacques Banchereau
Journal:  Annu Rev Immunol       Date:  2010       Impact factor: 28.527

4.  Deciphering normal blood gene expression variation--The NOWAC postgenome study.

Authors:  Vanessa Dumeaux; Karina S Olsen; Gregory Nuel; Ruth H Paulssen; Anne-Lise Børresen-Dale; Eiliv Lund
Journal:  PLoS Genet       Date:  2010-03-12       Impact factor: 5.917

5.  cDNA targets improve whole blood gene expression profiling and enhance detection of pharmocodynamic biomarkers: a quantitative platform analysis.

Authors:  Mark L Parrish; Chris Wright; Yarek Rivers; David Argilla; Heather Collins; Brendan Leeson; Andrey Loboda; Michael Nebozhyn; Matthew J Marton; Serguei Lejnine
Journal:  J Transl Med       Date:  2010-09-25       Impact factor: 5.531

Review 6.  Noninvasive diagnosis of acute rejection of renal allografts.

Authors:  Choli Hartono; Thangamani Muthukumar; Manikkam Suthanthiran
Journal:  Curr Opin Organ Transplant       Date:  2010-02       Impact factor: 2.640

Review 7.  The proteogenomic path towards biomarker discovery.

Authors:  Tara K Sigdel; Minnie M Sarwal
Journal:  Pediatr Transplant       Date:  2008-08-22

8.  A peripheral blood diagnostic test for acute rejection in renal transplantation.

Authors:  L Li; P Khatri; T K Sigdel; T Tran; L Ying; M J Vitalone; A Chen; S Hsieh; H Dai; M Zhang; M Naesens; V Zarkhin; P Sansanwal; R Chen; M Mindrinos; W Xiao; M Benfield; R B Ettenger; V Dharnidharka; R Mathias; A Portale; R McDonald; W Harmon; D Kershaw; V M Vehaskari; E Kamil; H J Baluarte; B Warady; R Davis; A J Butte; O Salvatierra; M M Sarwal
Journal:  Am J Transplant       Date:  2012-10       Impact factor: 8.086

Review 9.  Deconvoluting the 'omics' for organ transplantation.

Authors:  Minnie M Sarwal
Journal:  Curr Opin Organ Transplant       Date:  2009-10       Impact factor: 2.640

Review 10.  In praise of arrays.

Authors:  Lihua Ying; Minnie Sarwal
Journal:  Pediatr Nephrol       Date:  2008-06-21       Impact factor: 3.714

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