Genomic Changes in Pediatric Renal Transplant Patients Detected by aCGH

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Abstract

Introduction

Acute and chronic allograft rejection are major problems in kidney transplantation. Identifying differences among individuals at the genomic level might help us to understand the rationale of tissue and organ rejection. The aim of this study is to identify the copy losses and gains in the genomes of patients experienced rejection in acute and chronic terms.

Materials and Methods

This study was designed as a retrospective single center study. A total of 24 pediatric renal transplant patients (F/M:10/14) were enrolled in the study. Patients were divided into 3 groups which are 8 kidney transplantation patients without rejection, 8 patients with acute rejection and 8 patients with chronic rejection. Agilent SurePrint G3 Human CGH 60K arrays were used to identify genome wide copy number variations.

Results

Mean transplant age of the non-rejection group, acute rejection, and chronic rejections patients were 15.8±4.2, 13.2±2.7, 16.4±3.8 years respectively. Average rejection time for acute and chronic rejection patients was 16.9±9.7 and 26.4±6.7 months, respectively. Results of the aCGH analysis showed that copy number losses were detected on chromosomes 1q42.2-q42.3, 2q13, 4q31.1, 7q11.23, 11q13.2, 14q11.2, 20q13.32, and copy number gains were detected on chromosomes 1p36.13, 1p32.3, 2p24.1, 2p21, 3q23, 5p13.2, 11q13.2, 12q24.21, 13q12.12, 16p11.2, 18p11.31, 19q13.43, 20p13, 20q11.21, 21q22.12, 21q22.2. Copy number variations were detected in patients with acute and chronic kidney rejection group but not in the non-rejection group.

Discussion

The management of acute and chronic allograft transplantation rejection is one of the major concerns during the follow up of transplantation patients. Nevertheless standardized protocols and well tuned immunosuppressant therapies are used in transplant patients; interindividual differences can cause different responses to drugs. In this study, we identified several genomic loci that show differences in terms of copy number state among patient groups. 18p11.31 is one of the loci identified in this study. TGIF1 gene within this region was reported to be over-expressed previously in kidney transplantation patients who experienced chronic rejection, which supports our finding that overexpression could be due to gain detected.

Conclusion

In this study, we identified copy number differences among kidney transplantation patients which might be important for the short and long term graft survival. Each region and genes within these regions could be individual possible biomarker to predict graft health.

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