2010 - TTS International Congress


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Genomics and Biomarkers

86.9 - Discerning gene expression profiles involved in loss of graft function with IF/TA: utility in diagnosis and disease progression.

Presenter: Mariano, Scian, ,
Authors: Scian M., Maluf D., Archer K., Whitehill B., Suh L., King A., Gehr T., Sharma A., Kapoor S., Cotterell A., Massey D., Posner M., Mas V.

DISCERNING GENE EXPRESSION PROFILES INVOLVED IN LOSS OF GRAFT FUNCTION WITH IF/TA: UTILITY IN DIAGNOSIS AND DISEASE PROGRESSION.

GENOMICS AND BIOMARKERS

M.J. Scian1, D. Maluf2, K.J. Archer3, B.C. Whitehill1, L.J. Suh4, A. King5, T.W. Gehr5, A. Sharma6, S. Kapoor1, A. Cotterell2, D.H. Massey7, M.P. Posner2, V. Mas8
1Surgery, VCUHS, Richmond/UNITED STATES OF AMERICA, 2Transplantation Surgery, Virginia Commonwealth University, Richmond/UNITED STATES OF AMERICA, 3Biostatistics, VCU, Richmond/VA/UNITED STATES OF AMERICA, 4Surgery, VCUHS, Richmond/VA/UNITED STATES OF AMERICA, 5Nephrology, VCUHS, Richmond/UNITED STATES OF AMERICA, 6Transplantation Surgery, Virginia Commonwealth University, Richmond/VA/UNITED STATES OF AMERICA, 7Pathology, VCUHS, Richmond/VA/UNITED STATES OF AMERICA, 8Surgery And Pathology, VCUHS, Richmond/VA/UNITED STATES OF AMERICA

Body: Background: Loss of kidney graft function due to interstitial fibrosis (IF) and tubular atrophy (TA) is the most common cause of kidney allograft loss. IF/TA-related loss of graft function remains the main clinical challenge for long-term graft survival rate. A major challenge in the future of kidney transplantation is to identify the distinct etiological aspects of this condition and to develop methods for early identification and treatment. The aim of this research was to identify gene expression changes occurring in histologically defined IF/TA allografts that could be used as early detection / diagnostic biomarkers of IF/TA. Methods: Gene expression microarray data was analyzed using a two sample t-test followed by Bonferroni correction in order to identify differentially expressed genes between IF/TA (n = 22) and normal allograft (NA) (n = 18) biopsies. An independent set of sample biopsies was also collected. Samples from this set were collected at pre-implantation (n = 58), 3-months post-transplantation (n = 38), or 9 -months post-transplantation (n =15). Ingenuity pathway and the DAVID annotation tool were used to identify biological processes and pathways represented by the differentially expressed genes. The least absolute shrinkage and selection operator (LASSO) model was fit where the dependent variable predicted was IF/TA vs. NA. To obtain an unbiased estimate of classification error, N-fold cross-validation was used. Results: Gene expression analysis of the NA and IF/TA biopsies identified a total of 763 (404 up-regulated and 359 down-regulated) differentially expressed probe sets between the two groups. Gene ontology analyses revealed that biological processes and pathways over-represented by up-regulated genes are primarily associated with programmed cell death, natural killer cell mediated cytotoxicity, T-cell activation and differentiation, and TNFR2 signaling whereas pathways and biological processes identified from down-regulated genes included various general metabolic processes (q-value < 0.05). A least absolute shrinkage and selection operator (LASSO) model was then derived from the differentially expressed probe sets, resulting in a final model of 9 probe sets with high discriminatory capacity (100% accuracy on the training set). Using N-fold cross-validation, the cross-validated error was 5% with 2 of the 22 IF/TA cases and 0 of the 18 NA cases misclassified (sensitivity 90.9%, specificity 100%). When the model was applied to gene expression data from an independent set of sample biopsies collected at pre-implantation, 3-months post-transplantation, or 9 -months post-transplantation, all but one of the samples (a 3-month biopsy) were classified as normal allografts. Interestingly, 63% of these samples were histologically classified as having mild IF and 41% as having mild TA, with a total of 38% of the samples having both mild IF and TA. Conclusions: A characteristic gene expression signature was observed in samples with IF/TA. Gene expression profiling was able to distinguish IF/TA vs. NA. However, this type of modeling was not useful for predicting subsequent or future development of IF/TA in newly transplanted kidneys.

Disclosure: All authors have declared no conflicts of interest.


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