Impact of Pharmacogenetic Determinants of Tacrolimus and Mycophenolate on Adverse Events in Renal Transplant Patients.

BACKGROUND: Graft acceptance against immunity is one of the major challenges in solid organ transplant. Immunosuppressive medications have effectively improved the post-transplantation outcome however, it has its own limitations. Genetic polymorphisms in drug-metabolizing enzymes have been identified as the potential targets in developing a pharmacogenetic strategy, to individualize drug dose and also in preventing the adverse events. OBJECTIVE: The rationale of the study was to explore polymorphisms in tacrolimus and mycophenolate metabolic pathways that influence the adverse clinical outcomes in renal transplant recipients. METHODS: A total of 255 renal transplant recipients were analyzed for the pharmacogenetic determinants of tacrolimus (CYP3A5*3 ABCB1 1236 T>C ABCB1 2677 G>A/T ABCB1 3435 T>C) and mycophenolate (UGT1A8*3 UGT1A9 IMPDH I IMPDH II c.787C>T ABCC2 -24 C>T and c.3972C>T) using Sanger sequencing. RESULTS: Acute rejection (AR) was observed in 5.88% of the transplant recipients whereas acute tubular necrosis (ATNs) was observed in 7.45% of the patients within early stage of the maintenance phase. Infections such as urinary tract infection (UTI) and cytomegalovirus (CMV) infection were observed in 11.37% and 12.16% of the patients. The AUC of mycophenolate was significantly higher in patients with increased risk for infections. ABCC2 -24 C>T c.3972C>T polymorphisms and ABCB1 3435 C-allele were associated with reduced risk for infections. ABCC2 rs3740066 was associated with 2.06-fold all-cause mortality risk. CYP3A5 AG- and UGT1A9-440 CC-genotypes showed increased risk and ABCC 3972C>T CC-genotype showed protection against adverse events. CONCLUSION: Genetic variants in tacrolimus and mycophenolate metabolic pathways were found to influence the morbidity and mortality in renal transplant recipients.

Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation.

The objective of the current study was to explore the role of ABCB1 and CYP3A5 genetic polymorphisms in predicting the bioavailability of tacrolimus and the risk for post-transplant diabetes. Artificial neural network (ANN) and logistic regression (LR) models were used to predict the bioavailability of tacrolimus and risk for post-transplant diabetes, respectively. The five-fold cross-validation of ANN model showed good correlation with the experimental data of bioavailability (r2 = 0.93-0.96). Younger age, male gender, optimal body mass index were shown to exhibit lower bioavailability of tacrolimus. ABCB1 1236 C>T and 2677G>T/A showed inverse association while CYP3A5*3 showed a positive association with the bioavailability of tacrolimus. Gender bias was observed in the association with ABCB1 3435 C>T polymorphism. CYP3A5*3 was shown to interact synergistically in increasing the bioavailability in combination with ABCB1 1236 TT or 2677GG genotypes. LR model showed an independent association of ABCB1 2677 G>T/A with post transplant diabetes (OR: 4.83, 95% CI: 1.22-19.03). Multifactor dimensionality reduction analysis (MDR) revealed that synergistic interactions between CYP3A5*3 and ABCB1 2677 G>T/A as the determinants of risk for post-transplant diabetes. To conclude, the ANN and MDR models explore both individual and synergistic effects of variables in modulating the bioavailability of tacrolimus and risk for post-transplant diabetes.

Association of CTLA4 exon-1 polymorphism with the tumor necrosis factor-α in the risk of systemic lupus erythematosus among South Indians.

Cytotoxic T lymphocyte associated-antigen (CTLA4) is a potential negative regulatory molecule of T-cells and associated with several autoimmune diseases. Several reports from different ethnic groups showed that the polymorphisms of the CTLA4 gene have been associated with autoimmune diseases including SLE. Therefore, we aimed to investigate the +49 A/G polymorphism in South Indian SLE patients and its association with disease aetiology and serological markers. A total of 534 samples were genotyped for the +49 A/G polymorphism in exon 1 of the CTLA-4 gene through PCR-RFLP method. We found significant association of genotype and allele frequencies with +49 A/G polymorphism in SLE patients. The frequency of the +49 A/G polymorphism rs231775 'GG' genotype was significantly higher in patients with SLE (12.32%) than those in healthy control subjects (4.6%) (OR: 1.797; 95% CI 1.264-2.554; p=0.001). The frequency of mutant allele 'G' also found to be significantly higher in cases (36.01%) than controls (24.92%) (OR: 1.695, 95% CI: 1.298-2.214, p<0.001). We observed significant increase in serum TNF-α, interferon-α, IL-10 and IL-12 in SLE cases compared to controls. We also found a significant association of serum TNF-α, interferon-α, IL-10 and IL-12 with SLE phenotypes. In addition there was a significant increase in serum TNF-α level in "GG" genotype SLE subjects suggesting that it might play a major role in the advancement of SLE disease.