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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

E. Crespo, A. Vidal-Alabró, T. Jouve, P. Fontova, M. Stein, S. Mocka, M. Meneghini, A. Sefrin, P. Hruba, M. Gomà, A. Torija, L. Donadeu, A. Favà, JM. Cruzado, E. Melilli, F. Moreso, O. Viklicky, F. Bemelman, P. Reinke, J. Grinyó, N. Lloberas, O. Bestard

. 2022 ; 13 (-) : 869554. [pub] 20220627

Language English Country Switzerland

Document type Journal Article

Persistent link   https://www.medvik.cz/link/bmc22025399

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.

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$a 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.
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