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Review
. 2010 Apr;10(3):269-84.
doi: 10.1586/erm.10.6.

Molecular pathways involved in loss of graft function in kidney transplant recipients

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Review

Molecular pathways involved in loss of graft function in kidney transplant recipients

Valeria R Mas et al. Expert Rev Mol Diagn. 2010 Apr.

Abstract

Interstitial fibrosis (IF) and tubular atrophy (TA) are integral parts of chronic allograft dysfunction and represent in the new classification a separate entity with or without the identification of a specific etiology. Loss of kidney graft function with IF/TA is one of the causes of most kidney allograft losses. Despite progress in immunosuppression, chronic allograft dysfunction remains the main clinical challenge for improving long-term graft survival. The sustained damage to the allograft does not represent a single entity but the summated effects of tissue injury from several pathogenic insults, as well as the kidney's healing response, modified by alloimmunity and immunosuppression. A major challenge in the future of kidney transplantation includes the study of chronic allograft dysfunction pathogenesis to identify early markers of disease progression, as well as potential therapeutics pathways.

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Figures

Figure 1:
Figure 1:
The cellular and molecular mechanisms underlying these histopathological hallmarks remain obscure. Immunological and non-immunological factors have been associated with the progression to chronic allograft dysfunction. Many cell-cell, cell-matrix, and intracellular pathways have been implicated in the complex pathogenesis of CAN. CAN is characterized by slowly progressive graft dysfunction ultimately leading to chronic renal failure.
Figure 2:
Figure 2:
Negative trend in gene expression for genes involved in angiogenesis in kidney allograft samples with IF/TA.
Figure 3:
Figure 3:
Top canonical pathways identified for the analysis of IF/TA samples. Over expressed genes: red boxes, under expressed genes: green boxes. The numbers over the boxes indicated the number of genes that are part of the specific pathway identified as differentially expressed in the dataset (www.ingenuity.com) [200].
Figure 4:
Figure 4:
Two Affymetrix microarrays (HGU133Av2) were run for two samples (peripheral blood and kidney biopsy) from the same patient (ID 107). Samples were collected at the biopsy time and the biopsy showed IF/TA. In comparing gene expression of the kidney sample to the blood sample, 902 probe sets were found to be over expressed, 136 probe sets were under expressed (False Discovery Rate (FDR) <5%). The scatter plot of the intensities for these probe sets is shown in which green points represent over expressed probe sets and red points represent under expressed probe sets in the kidney sample.

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