Gene-Expression Profiles and Age of Donor Kidney Biopsies Obtained Before Transplantation Distinguish Medium Term Graft Function

Stanford University, Palo Alto, California, United States
Transplantation (Impact Factor: 3.83). 04/2007; 83(8):1048-54. DOI: 10.1097/
Source: PubMed


Donor factors such as age profoundly influence long-term graft function after cadaveric renal transplantation, but the molecular signature of these aspects in the allograft remains unknown.
We analyzed the genome-wide gene expression signature of donor kidney biopsies of different ages obtained before transplantation. Subsequent analysis compared expression profiles from allografts with excellent function versus impaired function at 1 yr after engraftment. Differential expression profiles were analyzed on the level of molecular function and biologic role, as well as by analysis of co-regulation through transcription factors, regulatory networks, and protein-protein interaction data utilizing extended bioinformatics.
The 15 subjects with excellent transplant function defined as calculated GFR>or=45 mL/min/1.73 m2 at 1 yr exhibited a distinctly different gene expression profile than the matched 16 subjects with impaired function defined as calculated GFR<45 mL/min/1.73 m2. Donor kidneys from recipients with impaired allograft function showed activation of genes mainly belonging to the functional classes of immunity, signal transduction, and oxidative stress response. Two-thirds of these genes exhibited at least one protein interacting partner, suggesting choreographed intracellular events differentiating the two recipient groups. However, donor age may have confounded some of the associations found between gene profiles and graft function.
In summary, a distinctive gene expression profile in the donor kidney at transplantation together with donor age predicts medium term allograft function in recipients of cadaveric allografts.

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    • "Kainz et al. conducted a genome-wide analysis of donor organs before transplantation and at 1 year post-transplant dividing the groups based on good or poor graft function [28]. They identified 52 genes that were differentially expressed between the two groups [28]. The genes that were upregulated in subjects with poor graft function were related to immune system/complement pathway, signal transduction, and oxidative stress [28]. "
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    ABSTRACT: The diagnosis of rejection in kidney transplant patients is based on histologic classification of a graft biopsy. The current "gold standard" is the Banff 97 criteria; however, there are several limitations in classifying rejection based on biopsy samples. First, a biopsy involves an invasive procedure. Second, there is significant variance among blinded pathologists in the interpretation of a biopsy. And third, there is also variance between the histology and the molecular profiles of a biopsy. To increase the positive predictive value of classifiers of rejection, a Banff committee is developing criteria that integrate histologic and molecular data into a unified classifier that could diagnose and prognose rejection. To develop the most appropriate molecular criteria, there have been studies by multiple groups applying omics technologies in attempts to identify biomarkers of rejection. In this review, we discuss studies using genome-wide data sets of the transcriptome and proteome to investigate acute rejection, chronic allograft dysfunction, and tolerance. We also discuss studies which focus on genetic biomarkers in urine and peripheral blood, which will provide clinicians with minimally invasive methods for monitoring transplant patients. We also discuss emerging technologies, including whole-exome sequencing and RNA-Seq and new bioinformatic and systems biology approaches, which should increase the ability to develop both biomarkers and mechanistic understanding of the rejection process.
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