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Abstract: FR-PO872

Involvement of Genetic Variation and Related Gene Expression Changes on Acute Rejection in Renal Transplant Recipients

Session Information

Category: Transplantation

  • 1802 Transplantation: Clinical

Authors

  • Hwang, Hyeon Seok, Division of Nephrology, Department of Internal Medicine, College of Medicine, Kyung Hee University, Seoul, Korea (the Republic of)
  • Kim, Yang gyun, Division of Nephrology, Department of Internal Medicine, College of Medicine, Kyung Hee University, Seoul, Korea (the Republic of)
  • Moon, Ju young, Division of Nephrology, Department of Internal Medicine, College of Medicine, Kyung Hee University, Seoul, Korea (the Republic of)
  • Lee, Tae won, Division of Nephrology, Department of Internal Medicine, College of Medicine, Kyung Hee University, Seoul, Korea (the Republic of)
  • Kim, Chan-Duck, Kyungpook University Hospital, Daegu, Korea (the Republic of)
  • Chung, Byung ha, Seoul St. Mary's Hospital , Seoul, Korea (the Republic of)
  • Lee, Sangho, Division of Nephrology, Department of Internal Medicine, College of Medicine, Kyung Hee University, Seoul, Korea (the Republic of)
Background

Acute rejection (AR) is one of the major risk factors for renal allograft loss. The effect of genetic factors on the transplant outcomes has been clear. However, the correlation between genetic variation and acute rejection remains undetermined.

Methods

We collected blood samples from recipients with biopsy-proven AR (n = 81) and with stable graft function (n = 48). Gene expression data was pooled from RNA microarray and RNA sequencing. Integrative analysis combining genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) was used to identify single nucleotide polymorphisms (SNPs) for acute rejection.

Results

In eQTL analysis, we detected potential 35,465 SNPs, which correlated with RNA expression. We analyzed AR-related SNPs in GWAS with covariate adjustment, and detected 140 overlapped SNPs in integrative analyses of eQTL and GWAS. The corresponding genes of these SNPs were matched with genes whose expression level differs between patients with AR and stable graft, and three loci were finally mated. One locus encompasses PFDN6, which involves the activation and development of lymphocyte. Two other loci encompasses ZSCAN10 and HEBP2, which involves the DNA binding transcription factor activity and microtubule dynamics, respectively.

Conclusion

Our integrated analysis of GWAS and eQTL helps to find relevant genes, which had both biological and clinical significance, and identify three novel acute rejection susceptibility loci in renal transplant recipients.