AN OBSERVATIONAL STUDY OF C/D RATIO TO PREDICT CYP3A5 GENOTYPE POLYMORPHISM AND TACROLIMUS METABOLISM IN INDIAN RENAL TRANSPLANT PATIENTS
Introduction:
Regimen containing Tacrolimus showed a superior allograft function and better prevention of acute rejection in renal transplant patients. Unfortunately, Tacrolimus has a narrow therapeutic window. Therefore, it is of high clinical impact to identify factors which can identify who is endangered to develop CNI toxicity. The most relevant are genes encoding the CYP3A5 leading to significant differences in Tacrolimus pharmacodynamics.(1)However, genetic profiling of patients is not available in many transplant centres. Therefore, factors which can predict patients’ risk of developing tacrolimus side effects would be of high interest to transplant physicians. We hypothesize that the Tacrolimus metabolism rate expressed as the blood concentration normalized by the dose(C/D ratio) can be a simple predictor.
Methods:
We analyzed data from 56 western Indian patients who underwent renal transplant from November 2022 to May 2023. Immunosuppressive regimen consisted of Tacrolimus, mycophenolate mofetil and prednisolone. An induction therapy with ATG or Basiliximab was given as per institute protocol. Tacrolimus was started at a dose of 0.1 mg/kg bid with a target trough level of 7–12 ng/mL during the first month, 6–10 ng/mL from month 2 to 3 and 3–8 ng/mL for the following time. Recipient and donor data were collected at the time of kidney transplant. To keep the approach simple, patients were divided into three C/D groups: slow(C/D ratio >1.55), intermediate(C/D ratio 1.05-1.55) and fast(C/D ratio <1.05) metabolizers.(2) Renal function was analyzed at 1,3,7,14,30 and 90 days after kidney transplant in 56 patients with an immunosuppressive regimen including tacrolimus, mycophenolate mofetil and prednisolone.
Results:
In our study population mean age of kidney transplant recipient was 39.2 years, whereas mean age of donor was 49.9 years. Majority of recipient were male patients around 47(83.9%), whereas majority of donor were female around 36(64.3%). Out of total recipients, fast metabolizers were only 1(1.8%), whereas slow and intermediate metabolizers were 39(70%) and 15(27.3%) respectively. We analysed CYP3A5 genetic polymorphism of our patients and correlated it with metabolizer groups. Out of 39 slow metabolizers 27 were homozygous (CYP3A5 3*3),15 of intermediate 9 were heterozygous (CYP3A5 3*1) and only 1 was fast metabolizer was wild type of genotype (CYP3A5 1*1). Hence the correlation between CYP polymorphism and C/D ratio was statistically significant with P value of 0.013. Patients with slow metabolizes have high tacrolimus level hence chances of CNI toxicity were likely to be more, whereas fast metabolizers have low tacrolimus level and chances of allograft rejections were likely to be more common with this group. This observation emphasizes the importance of identification of patient’s metabolizer type in renal transplant patients.
Conclusions:
We conclude that in order to achieve long term survival of allograft it is important to minimize risk factors affecting graft survival. One of the major factor is a tailored immunosuppressive regimen. In our experience calculating a simple C/D ratio would be a simple and cost effective surrogate marker of CYP3A5 genotype polymorphism in renal transplant patients. If C/D ratio can fulfil these criteria and needs, it can be evaluated in further studies.
REFERENCES
(1) Thölking G., Fortmann C., Koch R., Gerth H. U., Pabst D., Pavenstädt H., et al. (2014). The tacrolimus metabolism rate influences renal function after kidney transplantation. PloS One 9(10), e111128.
(2)Thölking G., Schmidt C., Koch R., Schuette-Nuetgen K., Pabst D., Wolters H., et al. (2016). Influence of tacrolimus metabolism rate on BKV infection after kidney transplantation. Sci. Rep. 6, 32273. 10.1038/srep32273
I have no potential conflict of interest to disclose.
I did not use generative AI and AI-assisted technologies in the writing process.