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Tacrolimus CYP3A Single-Nucleotide Polymorphisms and Preformed T- and B-Cell Alloimmune Memory Improve Current Pretransplant Rejection-Risk Stratification in Kidney Transplantation

ABSTRACT: Achieving fast immunosuppression blood exposure after kidney transplantation is key to abrogating both preformed and de novo anti-donor humoral and cellular alloresponses. However, while tacrolimus (TAC) is the cornerstone immunosuppressant inhibiting adaptive alloimmunity, its blood exposure is directly impacted by different single-nucleotide polymorphisms (SNPs) in CYP3A TAC-metabolizing enzymes. Here, we investigated how functional TAC-CYP3A genetic variants (CYP3A4*22/CYP3A5*3) influence the main baseline clinical and immunological risk factors of biopsy-proven acute rejection (BPAR) by means of preformed donor-specific antibodies (DSAs) and donor-specific alloreactive T cells (DSTs) in a large European cohort of 447 kidney transplants receiving TAC-based immunosuppression. A total of 70 (15.7%) patients developed BPAR. Preformed DSAs and DSTs were observed in 12 (2.7%) and 227 (50.8%) patients, respectively. According to the different CYP3A4*22 and CYP3A5*3 functional allele variants, we found 4 differential new clusters impacting fasting TAC exposure after transplantation; 7 (1.6%) were classified as high metabolizers 1 (HM1), 71 (15.9%) as HM2, 324 (72.5%) as intermediate (IM), and 45 (10.1%) as poor metabolizers (PM1). HM1/2 showed significantly lower TAC trough levels and higher dose requirements than IM and PM (p < 0.001) and more frequently showed TAC underexposure (<5 ng/ml). Multivariate Cox regression analyses revealed that CYP3A HM1 and IM pharmacogenetic phenotypes (hazard ratio (HR) 12.566, 95% CI 1.99–79.36, p = 0.007, and HR 4.532, 95% CI 1.10–18.60, p = 0.036, respectively), preformed DSTs (HR 3.482, 95% CI 1.99–6.08, p < 0.001), DSAs (HR 4.421, 95% CI 1.63–11.98, p = 0.003), and delayed graft function (DGF) (HR 2.023, 95% CI 1.22–3.36, p = 0.006) independently predicted BPAR. Notably, a significant interaction between T-cell depletion and TAC underexposure was observed, showing a reduction of the BPAR risk (HR 0.264, 95% CI 0.08–0.92, p = 0.037). Such variables except for DSAs displayed a higher predictive risk for the development of T cell-mediated rejection (TCMR). Refinement of pretransplant monitoring by incorporating TAC CYP3A SNPs with preformed DSAs as well as DSTs may improve current rejection-risk stratification and help induction treatment decision-making.

SUBMITTER: Crespo E

PROVIDER: S-EPMC9272702 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background and objectivesDefinition of individual risk profile is the first step to implement strategies to keep the delicate balance between under- and overimmunosuppression after kidney transplantation.Design, setting, participants, & measurementsWe used data from the Efficacy Limiting Toxicity Elimination Symphony Study (1190 patients between 2002 and 2004) to model risk of rejection and infection in the first year after kidney transplantation. External validation was performed in a study population from the Fixed-Dose Concentration-Controlled Trial (630 patients between 2003 and 2006).ResultsDespite different temporal dynamics, rejections and severe infections had similar overall incidences in the first year after transplantation (23.4% and 25.5%, respectively), and infections were the principal cause of death (43.2% of all deaths). Recipient older age, deceased donor, higher number of HLA mismatches, and high risk for cytomegalovirus disease were associated with infection; deceased donor, higher number of HLA mismatches, and immunosuppressive therapy including cyclosporin A (compared with tacrolimus), with rejection. These factors were integrated into a two-dimensional risk stratification model, which defined four risk groups: low risk for infection and rejection (30.8%), isolated risk for rejection (36.1%), isolated risk for infection (7.0%), and high risk for infection and rejection (26.1%). In internal validation, this model significantly discriminated the subgroups in terms of composite end point (low risk for infection/rejection, 24.4%; isolated risk for rejection and isolated risk for infection, 31.3%; high risk for infection/rejection, 54.4%; P<0.001), rejection episodes (isolated risk for infection and low risk for infection/rejection, 13.0%; isolated risk for rejection and high risk for infection/rejection, 24.2%; P=0.001), and infection episodes (low risk for infection/rejection and isolated risk for rejection, 12.0%; isolated risk for infection and high risk for infection/rejection, 37.6%; P<0.001). External validation confirmed the applicability of the model to an independent cohort.ConclusionsWe propose a two-dimensional risk stratification model able to disentangle the individual risk for rejection and infection in the first year after kidney transplantation. This concept can be applied to implement a personalized immunosuppressive and antimicrobial treatment approach.

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Tacrolimus CYP3A Single-Nucleotide Polymorphisms and Preformed T- and B-Cell Alloimmune Memory Improve Current Pretransplant Rejection-Risk Stratification in Kidney Transplantation

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