Influence of Donor and Recipient CYP3A4, CYP3A5, and ABCB1 Genotypes on Clinical Outcomes and Nephrotoxicity in Liver Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: This study investigated the influence of the CYP3A4*22, CYP3A5*3, and ABCB1 exons 12, 21, and 26 polymorphisms in donors and recipients on clinical outcomes and renal function in 170 liver transplant patients on cyclosporin A (CsA) or tacrolimus (Tac). METHODS: Allelic discrimination assays were used for genotyping. Multivariate time-dependent Cox proportional hazard models, multiple linear regression using the generalized estimating equation and linear mixed-effect models were used for statistical analysis. RESULTS: Expression of CYP3A5 by either or both the donor and the recipient was significantly associated with lower Tac, but not CsA, dose-normalized trough levels. In the whole population, graft loss was only significantly associated with longer exposure to high calcineurin inhibitor (CNI) concentrations (hazard ratio, 6.93; 95% confidence interval, 2.13-22.55), P = 0.00129), whereas in the Tac subgroup, the risk of graft loss was significantly higher in recipient CYP3A5*1 expressers (hazard ratio, 3.39; 95% confidence interval, 1.52-7.58; P = 0.0028). Renal function was significantly associated with: (1) baseline modification of diet in renal disease (β = 0.51 ± 0.05; P < 0.0001); (2) duration of patient follow-up (per visit, β = -0.98 ± 0.22; P < 0.0001); and (3) CNI exposure (per quantile increase, β = -2.42 ± 0.59; P < 0.0001). No genetic factor was associated with patient survival, acute rejection, liver function test results, recurrence of viral or other initial liver disease, or renal function. CONCLUSIONS: This study confirms the effect of CYP3A5*3 on tacrolimus dose requirement in liver transplantation and shows unexpected associations between the type of, and exposure to, CNI and either chronic rejection or graft loss. None of the genetic polymorphisms studied had a noticeable impact on renal function degradation at 10 years.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".