Single-nucleotide polymorphisms in P450 oxidoreductase and peroxisome proliferator-activated receptor-α are associated with the development of new-onset diabetes after transplantation in kidney transplant recipients treated with tacrolimus

Abstract

New-onset diabetes after transplantation (NODAT) is an important complication after kidney transplantation. The etiology of the malady is multifactorial and includes both environmental and genetic factors. NODAT is a polygenic disease and many single-nucleotide polymorphisms could constitute potential risk factors. Peroxisome proliferator-activated receptor α (PPARα) and P450 oxidoreductase (POR) play a central role in the control of energy metabolism in humans. Some recent data highlighted a possible functional impact of two single-nucleotide polymorphisms in PPARα (rs4253728 G>A and rs4823613 A>G) and one coding variant in POR (rs1057868; POR*28; A503V) on the activity of their respective encoded proteins. In the present study, we assessed the association between these variants and the risk of developing NODAT after kidney transplantation. Development of NODAT was investigated in 101 renal transplant recipients receiving tacrolimus-based immunosuppressive therapy. Patients were genotyped for PPARα and POR. The incidence of NODAT was compared between different genotypes. Kaplan-Meier and Cox's proportional-hazard analysis were used to evaluate the association of NODAT with potential risk factors. Potential nongenetic risk factors were also considered. The PPARα rs4253728A>G and POR*28 variant alleles were both independently associated with an increased risk for NODAT with respective odds ratios of 8.6 [95% confidence interval (CI)=1.4-54.2; P=0.02] and 8.1 (95% CI=1.1-58.3; P=0.04). Other risk predictors included sex and body weight. This candidate-gene study shows that polymorphisms in PPARα and POR might predispose patients being treated with tacrolimus to the development of NODAT after kidney transplantation. Patient management after organ transplantation might benefit from genotype data.