Tacrolimus, an approved first-line calcineurin inhibitor, is widely prescribed in organ transplantation to prevent allograft rejection. Its narrow therapeutic index requires precise management to achieve optimal dosing and to minimize adverse drug events (ADEs) while ensuring its therapeutic efficacy. Among several factors, genetic differences contribute significantly to the inter-individual and inter-ethnic variability in pharmacokinetics (PK) of tacrolimus in kidney transplant recipients. As a result, investigating the role of genetic variation in Greek transplant recipients becomes crucial to optimizing therapeutic strategies and enhancing the efficacy of immunosuppressive treatment.

Genetic variants which are known to influence the activity of enzymes or drug-transporters critical to tacrolimus pharmacokinetics, may significantly affect the required kidney post-transplant tacrolimus daily dose.

To assess the correlation of ABCB1 genetic variants (rs1128503, rs2229109) and CYP3A4 (rs2242480, rs4986910) with tacrolimus dose-adjusted trough concentration (C0/D), in Greek kidney transplant recipients.

Ninety-four unrelated Greek kidney transplant recipients were included in this study from the Department of Nephrology and Kidney Transplantation of the University General Hospital of Patras. Patients' dose-adjusted trough levels were measured at five distinct time points after transplantation and analyzed in relation to the possible influence of CYP3A4 and correlated with the abovementioned ABCB1 genetic variants using standard genotyping analysis and Sanger sequencing.

The genetic variants rs1128503, rs2229109, rs2242480, rs4986910 did not show any significant association with the daily dosing requirements of tacrolimus for at least 1 year, in Greek patients who have undergone kidney transplant.

It remains uncertain whether these genetic variants influence the assessment of the appropriate tacrolimus dosing 1 year after transplantation in Greek kidney transplant recipients.

Clinical observations have revealed that patients undergoing organ transplantation administered tacrolimus often experience abnormal lipid metabolism with serious consequences. Thus, the intricate interplay between tacrolimus and lipid metabolism must be addressed to develop targeted therapeutic interventions. Our ongoing research aims to develop precision medicine approaches that not only alleviate the immediate repercussions for organ transplant patients but also enhance their long-term outcomes. To this end, we investigated the potential genes associated with tacrolimus metabolism in familial combined hyperlipidemia (FCHL) to identify relevant biomarkers of FCHL, develop predictive diagnostic models for hyperlipidemia, and reveal potential therapeutic targets for FCHL.

Dataset GSE1010 containing information on patients diagnosed with FCHL was obtained from the Gene Expression Omnibus (GEO), and an ensemble of tacrolimus-related genes (TRGs) was retrieved from the GeneCards, STITCH, and Molecular Signatures Database databases. A thorough weighted gene co-expression network analysis was conducted, including a differential expression analysis of the GSE1010 and TRG datasets, to identify intricate patterns of gene co-expression and provide insights on the underlying molecular dynamics within the datasets. Key genes were screened, diagnostic models were constructed, and all genes associated with logFC values were assessed using gene set variation and enrichment analyses. Upregulated genes were identified by a positive logFC (>0) and P < 0.05, while downregulated genes were characterized by a negative logFC (<0) and P < 0.05. These criteria facilitated a more nuanced categorization of gene expression changes within the analyzed datasets. Given tacrolimus's immunosuppressive impact, the gene expression matrix data obtained from dataset GSE1010 was submitted to CIBERSORT to assess immune cell infiltration outcomes. Finally, we examined the regulatory network of screened key genes that interact with RNA-binding proteins, potential drugs, small-molecule compounds, and transcription factors.

We screened 14 statistically significant key genes, built a reliable risk model, and grouped the dataset into categories at high and low risk for hyperlipidemia development. FCHL was linked to memory B and immature B immune cells. The gene set variation analysis revealed two pathways associated with cholesterol homeostasis and the complement system that were closely associated with the potential functions of FCHL and tacrolimus-related differentially expressed genes.

Our research offers a better understanding of FCHL and the TRGs involved in lipid metabolism. Additionally, it provides research directions for identifying potential targets for clinical therapies.

One of the most critical goals in healthcare is safe and effective drug therapy, which is directly related to an individual's response to treatment. Precision medicine can improve drug safety in many scenarios, including polypharmacy, and it requires the development of new genetic characterization methods. In this report, we use real-time PCR, microarray techniques, and mass spectrometry (MALDI-TOF), which allows us to compare them and identify the potential benefits of technological improvements, leading to better quality medical care. These comparative studies, as part of our pharmacogenetic Five-Step Precision Medicine (5SPM) approach, reveal the superiority of mass spectrometry over the other methods analyzed and highlight the importance of updating the laboratory's pharmacogenetic methodology to identify new variants with clinical impact.

Background/Objectives: Plasma levels of 4β-hydroxycholesterol (4β-OHC), a CYP3A-specific metabolite of cholesterol, are elevated after administration of CYP3A inducers like rifampicin and carbamazepine. To simulate such plasma 4β-OHC increase, we developed a physiologically based pharmacokinetic (PBPK) model of cholesterol and 4β-OHC in the Simcyp PBPK Simulator (Version 23, Certara UK Ltd.) using a middle-out approach. Methods: Relevant physicochemical properties and metabolic pathway data for CYP3A and CYP27A1 was incorporated in the model. Results: The PBPK model recovered the observed baseline plasma 4β-OHC levels in Caucasian, Japanese, and Korean populations. The model also captured the higher baseline 4β-OHC levels in females compared to males, indicative of sex-specific differences in CYP3A abundance. More importantly, the model recapitulated the increased 4β-OHC plasma levels after multiple-dose rifampicin treatment in six independent studies, indicative of hepatic CYP3A induction. The verified model also captured the altered 4β-OHC levels in CYP3A4/5 polymorphic populations and with other CYP3A inducers. The model is limited by scant data on relative contributions of CYP3A and CYP27A1 pathways and does not account for regulatory mechanisms that control plasma cholesterol and 4β-OHC levels. Conclusion: This study provides a quantitative fit-for-purpose and framed-for-future modelling framework for an endogenous biomarker to evaluate the DDI risk with hepatic CYP3A induction.

African American (AA) kidney transplant recipients (KTRs) have poor outcomes, which may in-part be due to tacrolimus (TAC) sub-optimal immunosuppression. We previously determined the common genetic regulators of TAC pharmacokinetics in AAs which were CYP3A5 *3, *6, and *7. To identify low-frequency variants that impact TAC pharmacokinetics, we used extreme phenotype sampling and compared individuals with extreme high (n = 58) and low (n = 60) TAC troughs (N = 515 AA KTRs). Targeted next generation sequencing was conducted in these two groups. Median TAC troughs in the high group were 7.7 ng/ml compared with 6.3 ng/ml in the low group, despite lower daily doses of 5 versus 12 mg, respectively. Of 34,542 identified variants across 99 genes, 1406 variants were suggestively associated with TAC troughs in univariate models (p-value < 0.05), however none were significant after multiple testing correction. We suggest future studies investigate additional sources of TAC pharmacokinetic variability such as drug-drug-gene interactions and pharmacomicrobiome.

Calcineurin inhibitors (CNIs) are the mainstay of immunosuppression in kidney transplantation. Interpatient variability in the disposition of calcineurin inhibitors is a well-researched phenomenon and has a well-established genetic contribution. There is great diversity in the makeup of African genomes, but very little is known about the pharmacogenetics of CNIs and transplant outcomes. This review focuses on genetic variants of calcineurin inhibitors' metabolizing enzymes (CYP3A4, CYP3A5), related molecules (POR, PPARA) and membrane transporters involved in the metabolism of calcineurin inhibitors. Given the genetic diversity across the African continent, it is imperative to generate pharmacogenetic data, especially in the era of personalized medicine and emphasizes the need for studies specific to African populations. The study of allelic variants in populations where they have greater frequencies will help answer questions regarding their impact. We aim to fill the knowledge gaps by reviewing existing research and highlighting areas where African research can contribute.

Tacrolimus metabolism is heavily influenced by the CYP3A5 genotype, which varies widely among African Americans (AA). We aimed to assess the performance of a published genotype-informed tacrolimus dosing model in an independent set of adult AA kidney transplant (KTx) recipients. CYP3A5 genotypes were obtained for all AA KTx recipients (n = 232) from 2010 to 2019 who met inclusion criteria at a single transplant center in Philadelphia, Pennsylvania, USA. Medical record data were used to calculate predicted tacrolimus clearance using the published AA KTx dosing equation and two modified iterations. Observed and model-predicted trough levels were compared at 3 days, 3 months, and 6 months post-transplant. The mean prediction error at day 3 post-transplant was 3.05 ng/mL, indicating that the model tended to overpredict the tacrolimus trough. This bias improved over time to 1.36 and 0.78 ng/mL at 3 and 6 months post-transplant, respectively. Mean absolute prediction error-a marker of model precision-improved with time to 2.33 ng/mL at 6 months. Limiting genotype data in the model decreased bias and improved precision. The bias and precision of the published model improved over time and were comparable to studies in previous cohorts. The overprediction observed by the published model may represent overfitting to the initial cohort, possibly limiting generalizability.

The effect of drug-drug interaction (DDI) between tacrolimus and voriconazole on the pharmacokinetics of tacrolimus in different CYP3A5 genotypes has not been reported in previous studies.

The objective of this study was to investigate whether CYP3A5 genotype could influence tacrolimus-voriconazole DDI in Chinese kidney transplant patients.

All kidney transplant patients were divided into combination and non-combination groups based on whether tacrolimus was combined with or without voriconazole. Each group was subdivided into CYP3A5 expresser (CYP3A5*1/*1 or CYP3A5*1/*3) and CYP3A5 nonexpresser (CYP3A5*3/*3). A retrospective analysis compared tacrolimus dose (D)-corrected trough concentrations (C0) (C0/D) between combination and non-combination groups, respectively. Tacrolimus C0/D was also compared between CYP3A5 expresser and nonexpresser in both groups.

The C0/D values of tacrolimus were significantly different between CYP3A5 expresser and nonexpresser in combination group (378.20 [219.38, 633.48] ng/mL/[mg/kg/d] vs 720.00 [595.35, 1681.50] ng/mL/[mg/kg/d], P = 0.0010). Either in CYP3A5 expresser or nonexpresser, we found a statistically significant difference in tacrolimus C0/D between combination and non-combination group (P < 0.0001). The increase in CYP3A5 nonexpresser was 1.38 times higher than that in CYP3A5 expresser (320.93% vs 232.19%).

The median C0/D values were 90.38% higher in kidney transplant recipients with CYP3A5*3/*3 genotype than in those with CYP3A5*1/*1 or CYP3A5*1/*3 genotype when treated with both tacrolimus and voriconazole. A CYP3A5 genotype-dependent DDI was found between tacrolimus and voriconazole. Therefore, personalized therapy accounting for CYP3A5 genotype detection and therapeutic drug monitoring is necessary for kidney transplant patients when treating with tacrolimus and voriconazole.

The objective of this study was to estimate the cost-effectiveness of CYP3A5 genotype-guided tacrolimus dosing in kidney, liver, heart, and lung transplant recipients relative to standard of care (SOC) tacrolimus dosing, from a US healthcare payer perspective. We developed decision-tree models to compare economic and clinical outcomes between CYP3A5 genotype-guided and SOC tacrolimus therapy in the first six months post-transplant. We derived inputs for CYP3A5 phenotype frequencies and physician use of genotype test results to inform clinical care from literature; tacrolimus exposure [high vs low tacrolimus time in therapeutic range using the Rosendaal algorithm (TAC TTR-Rosendaal)] and outcomes (incidences of acute tacrolimus nephrotoxicity, acute cellular rejection, and death) from real-world data; and costs from the Medicare Fee Schedule and literature. We calculated cost per avoided event and performed sensitivity analyses to evaluate the robustness of the results to changes in inputs. Incremental costs per avoided event for CYP3A5 genotype-guided vs SOC tacrolimus dosing were $176,667 for kidney recipients, $364,000 for liver recipients, $12,982 for heart recipients, and $93,333 for lung recipients. The likelihood of CYP3A5 genotype-guided tacrolimus dosing leading to cost-savings was 19.8% in kidney, 32.3% in liver, 51.8% in heart, and 54.1% in lung transplant recipients. Physician use of genotype results to guide clinical care and the proportion of patients with a high TAC TTR-Rosendaal were key parameters driving the cost-effectiveness of CYP3A5 genotype-guided tacrolimus therapy. Relative to SOC, CYP3A5 genotype-guided tacrolimus dosing resulted in a slightly greater benefit at a higher cost. Further economic evaluations examining intermediary outcomes (e.g., dose modifications) are needed, particularly in populations with higher frequencies of CYP3A5 expressers.

The effect of drug-drug interaction between tacrolimus and caspofungin on the pharmacokinetics of tacrolimus in different CYP3A5 genotypes has not been reported in previous studies.

To investigate the effect of caspofungin on the blood concentration and dose of tacrolimus under different CYP3A5 genotypes.

We conducted a retrospective cohort study in The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital from January 2015 to December 2022. All kidney transplant patients were divided into the combination or non-combination group based on whether tacrolimus was combined with caspofungin or not. Patients were subdivided into CYP3A5 expressers (CYP3A5*1/*1 or CYP3A5*1/*3) and CYP3A5 non-expressers (CYP3A5*3/*3).

Data from the combination and the non-combination groups were matched with propensity scores to reduce confounding by SPSS 22.0. A total of 200 kidney transplant patients receiving tacrolimus combined with caspofungin or not were enrolled in this study. Statistical analysis was conducted on the dose-corrected trough concentrations (C0/D) and dose requirements (D) of tacrolimus using independent sample two-sided t-test and nonparametric tests to investigate the impact on patients with different.

In this study, the C0/D values of tacrolimus were not significantly different between the combination and non-combination groups (p = 0.054). For CYP3A5 expressers, there was no significant difference in tacrolimus C0/D or D values between the combination and non-combination groups (p = 0.359; p = 0.851). In CYP3A5 nonexpressers, the C0/D values of tacrolimus were significantly lower in the combination than in the non-combination groups (p = 0.039), and the required daily dose of tacrolimus was increased by 11.11% in the combination group.

Co-administration of caspofungin reduced tacrolimus blood levels and elevated the required daily dose of tacrolimus. In CYP3A5 non-expressers, co-administration of caspofungin had a significant effect on tacrolimus C0/D values. An approximate 10% increase in the weight-adjusted daily dose of tacrolimus in CYP3A5 non-expressers is recommended to ensure the safety of tacrolimus administration.

African American (AA) kidney transplant recipients (KTRs) have poor outcomes, which may in-part be due to tacrolimus (TAC) sub-optimal immunosuppression. We previously determined the common genetic regulators of TAC pharmacokinetics in AAs which were CYP3A5 *3, *6, and *7. To identify low-frequency variants that impact TAC pharmacokinetics, we used extreme phenotype sampling and compared individuals with extreme high (n=58) and low (n=60) TAC troughs (N=515 AA KTRs). Targeted next generation sequencing was conducted in these two groups. Median TAC troughs in the high group were 7.7 ng/ml compared with 6.3 ng/ml in the low group, despite lower daily doses of 5 versus 12mg, respectively. Of 34,542 identified variants across 99 genes, 1,406 variants were suggestively associated with TAC troughs in univariate models (p-value <0.05), however none were significant after multiple testing correction. We suggest future studies investigate additional sources of TAC pharmacokinetic variability such as drug-drug-gene interactions and pharmacomicrobiome.

The strategy of the concentration-dose (C/D) approach and the different profiles of tacrolimus (Tac) according to the cytochrome P450 polymorphisms (CYPs) focus on the metabolism of Tac and are proposed as tools for the follow-up of transplant patients. The objective of this study is to analyse both strategies to confirm whether the stratification of patients according to the pharmacokinetic behaviour of C/D corresponds to the classification according to their CYP3A4/5 cluster metabolizer profile.

425 kidney transplant patients who received Tac as immunosuppressive treatment have been included. The concentration/dose ratio (C/D) was used to divide patients in terciles and classify them according to their Tac metabolism rate (fast, intermediate, and slow). Based on CYP3A4 and A5 polymorphisms, patients were classified into 3 metabolizer groups: fast (CYP3A5*1 carriers and CYP34A*1/*1), intermediate (CYP3A5*3/3 and CYP3A4*1/*1) and slow (CYP3A5*3/*3 and CYP3A4*22 carriers).

When comparing patients included in each metabolizer group according to C/D ratio, 47% (65/139) of the fast metabolizers, 85% (125/146) of the intermediate and only 12% (17/140) of the slow also fitted in the homonym genotype group. Statistically lower Tac concentrations were observed in the fast metabolizers group and higher Tac concentrations in the slow metabolizers when compared with the intermediate group both in C/D ratio and polymorphisms criteria. High metabolizers required approximately 60% more Tac doses than intermediates throughout follow-up, while poor metabolizers required approximately 20% fewer doses than intermediates. Fast metabolizers classified by both criteria presented a higher percentage of times with sub-therapeutic blood Tac concentration values.

Determination of the metabolizer phenotype according to CYP polymorphisms or the C/D ratio allows patients to be distinguished according to their exposure to Tac. Probably the combination of both classification criteria would be a good tool for managing Tac dosage for transplant patients.

Tacrolimus (TAC) is the mainstay of immunosuppressive regimen for kidney transplantations. Its clinical use is complex due to high inter-individual variations which can be partially attributed to genetic variations at the metabolizing enzymes CYP3A4 and CYP3A5. Two single nucleotide polymorphisms (SNPs), CYP3A4*22 and CYP3A5*3, have been reported as important causes of differences in pharmacokinetics that can affect efficacy and/or toxicity of TAC.

Investigating the effect of CYP3A4*22 and CYP3A5*3 SNPs individually and in combination on the TAC concentration in Egyptian renal recipients.

Overall, 72 Egyptian kidney transplant recipients were genotyped for CYP3A4*22 G>A and CYP3A5*3 T>C. According to the functional defect associated with CYP3A variants, patients were clustered into: poor (PM) and non-poor metabolizers (Non-PM). The impact on dose adjusted through TAC concentrations (C0) and daily doses at different time points after transplantation was evaluated.

Cyp3A4*1/*22 and PM groups require significantly lower dose of TAC (mg/kg) at different time points with significantly higher concentration/dose (C0/D) ratio at day 10 in comparison to Cyp3A4*1/*1 and Non-PM groups respectively. However, CyP3A5*3 heterozygous individuals did not show any significant difference in comparison to CyP3A5*1/*3 individuals. By comparing between PM and Non-PM, the PM group had a significantly lower rate of recipients not reaching target C0 at day 14.

This is the first study on Egyptian population to investigate the impact of CYP3A4*22 and CYP3A5*3 SNPs individually and in combination on the TAC concentration. This study and future multicenter studies can contribute to the individualization of TAC dosing in Egyptian patients.

The calcineurin inhibitor (CNI) Tacrolimus (Tac) is the most prescribed immunosuppressant drug after solid organ transplantation. After renal transplantation (RTx) approximately 95% of recipients are discharged with a Tac-based immunosuppressive regime. Despite the high immunosuppressive efficacy, its adverse effects, narrow therapeutic window and high intra- and interpatient variability (IPV) in pharmacokinetics require therapeutic drug monitoring (TDM), which makes treatment with Tac a major challenge for physicians. The C/D ratio (full blood trough level normalized by daily dose) is able to classify patients receiving Tac into two major metabolism groups, which were significantly associated with the clinical outcomes of patients after renal or liver transplantation. Therefore, the C/D ratio is a simple but effective tool to identify patients at risk of an unfavorable outcome. This review highlights the challenges of Tac-based immunosuppressive therapy faced by transplant physicians in their daily routine, the underlying causes and pharmacokinetics (including genetics, interactions, and differences between available Tac formulations), and the latest data on potential solutions to optimize treatment of high-risk patients.

Kidney transplant recipients carrying the CYP3A5*1 allele have lower tacrolimus troughs, and higher dose requirements compared to those with the CYP3A5*3/*3 genotype. However, data on the effect of CYP3A5 alleles on post-transplant tacrolimus management are lacking. The effect of CYP3A5 metabolism phenotypes on the number of tacrolimus dose adjustments and troughs in the first 6 months post-transplant was evaluated in 78 recipients (64% Caucasians). Time to first therapeutic concentration, percentage of time in therapeutic range (TTR), and estimated glomerular filtration rate (eGFR) were also evaluated. Fifty-five kidney transplant recipients were CYP3A5 poor metabolizers (PM), 17 were intermediate metabolizers (IM), and 6 were extensive metabolizers (EM). Compared to PMs, EMs/IMs had significantly more dose adjustments (6.1 vs. 8.1, p = .015). Overall, 33.82% of trough measurements resulted in a dose change. There was no difference in the number of tacrolimus trough measurements between PMs and EM/IMs. The total daily tacrolimus dose requirements were higher in EMs and IMs compared to PMs (<.001). TTR was ∼50% in the PMs and EMs/IMs groups. CYP3A5 EM/IM metabolizers have more tacrolimus dose changes and higher dose requirements which increases clinical management complexity. Larger studies are needed to assess the cost and benefits of including genotyping data to improve clinical management.

Hepatic drug metabolizing enzymes (DMEs), whose activity may be affected by liver diseases, are major determinants of drug pharmacokinetics. Hepatitis C liver samples in different functional states, i.e., the Child-Pugh class A (n = 30), B (n = 21) and C (n = 7) were analyzed for protein abundances (LC-MS/MS) and mRNA levels (qRT-PCR) of 9 CYPs and 4 UGTs enzymes. The protein levels of CYP1A1, CYP2B6, CYP2C8, CYP2C9, and CYP2D6 were not affected by the disease. In the Child-Pugh class A livers, a significant up-regulation of UGT1A1 (to 163% of the controls) was observed. The Child-Pugh class B was associated with down-regulation of the protein abundance of CYP2C19 (to 38% of the controls), CYP2E1 (to 54%), CYP3A4 (to 33%), UGT1A3 (to 69%), and UGT2B7 (to 56%). In the Child-Pugh class C livers, CYP1A2 was found to be reduced (to 52%). A significant trend in down-regulation of the protein abundance was documented for CYP1A2, CYP2C9, CYP3A4, CYP2E1, UGT2B7, and UGT2B15. The results of the study demonstrate that DMEs protein abundances in the liver are affected by hepatitis C virus infection and depend on the severity of the disease.

The initial dose of tacrolimus after liver transplantation (LT) is critical for rapidly achieving the steady state of the drug concentration, minimizing the potential adverse reactions and warranting long-term patient prognosis. We aimed to develop and validate a genotype-guided model for determining personalized initial dose of tacrolimus.

By combining pharmacokinetic modeling, pharmacogenomic analysis and multiple statistical methods, we developed a genotype-guided model to predict individualized tacrolimus initial dose after LT in the discovery (n = 150) and validation cohorts (n = 97) respectively. This model was further validated in a prospective, randomized and single-blind clinical trial from August, 2021 to February, 2022 (n = 40, ChiCTR2100050288).

Our model included donor's and recipient's genotypes, recipient's weight and total bilirubin, which achieved an area under the curve of receiver operating characteristic curve (AUC of ROC) of 0.88 and 0.79 in the discovery and validation cohorts, respectively. We found that patients who were given tacrolimus within the recommended concentration range (RCR) (4-10 ng/mL), the new-onset metabolic syndromes are lower, especially for new-onset diabetes (p = 0.043). In the clinical trial, compared to those in experience-based (EB) group, patients in the model-based (MB) group were more likely to achieving the RCR (75% vs 40%, p = 0.025) with a more variable individualized dose (0.023-0.096 mg/kg/day vs 0.045-0.057 mg/kg/day). Moreover, significantly fewer medication adjustments were required for the MB group than the EB group (2.75 ± 2.01 vs 6.05 ± 3.35, p = 0.001).

Our genotype-based model significantly improved the initial dosing accuracy of tacrolimus and reduced the number of medication adjustments, which are critical for improving the prognosis of LT patients.

National Natural Science Foundation of China, Shanghai three-year action plan, National Science and Technology Major Project of China.

The Sensitization in Transplantation: Assessment of Risk workgroup is a collaborative effort of the American Society of Transplantation and the American Society of Histocompatibility and Immunogenetics that aims at providing recommendations for clinical testing, highlights gaps in current knowledge, and proposes areas for further research to enhance histocompatibility testing in support of solid organ transplantation. This report provides updates on topics discussed by the previous Sensitization in Transplantation: Assessment of Risk working groups and introduces 2 areas of exploration: non-human leukocyte antigen antibodies and utilization of human leukocyte antigen antibody testing measurement to evaluate the efficacy of antibody-removal therapies.

Tacrolimus is an immunosuppressant with a narrow therapeutic window. Tacrolimus exposure increased significantly during voriconazole co-therapy. The magnitude of this interaction is highly variable, but it is hard to predict quantitatively. We conducted a study on 91 kidney transplantation recipients with voriconazole co-therapy. Furthermore, 1701 tacrolimus concentration data were collected. Standard concentration adjusted by tacrolimus daily dose (C/D) and weight-adjusted standard concentration (CDW) increased to 6 times higher during voriconazole co-therapy. C/D and CDW increased with voriconazole concentration. Patients with the genotype of CYP3A5 *3/*3 and CYP2C19 *2/*2 or *2/*3 were more variable at the same voriconazole concentration level. The final prediction model could explain 54.27% of the variation in C/D and 51.11% of the variation in CDW. In conclusion, voriconazole was the main factor causing C/D and CDW variation, and the effect intensity should be quantitative by its concentration. Kidney transplant recipients with CYP3A5 genotype of *3/*3 and CYP2C19 genotype of *2/*2 and *2/*3 should be given more attention during voriconazole co-therapy. The prediction model established in this study may help to reduce the occurrence of rejection.

Aim: To investigate the influence of CYP3A5 and IL-10 polymorphisms on tarcolimus metabolism and renal function for renal transplantation recipients at a stable period. Methods: CYP3A5 and IL-10 polymorphisms, together with other clinical factors, were collected for 149 renal transplantation patients at postoperative stable period. Statistics analysis was performed to explore key factors affecting tarcolimus metabolism. Results: CYP3A5 6986A >G and IL-10 -819C >T significantly impacted tacrolimus metabolism (p < 0.001). CYP3A5 6986A >G G allele and IL-10 -819C >T T allele were associated with poorer tacrolimus metabolic capability. Patients with various tacrolimus metabolism rates presented little difference in renal functions at stable period. Conclusion: Genotyping of CYP3A5 and IL-10 might benefit the precision dosage of tacrolimus for renal transplantation recipients.

Tacrolimus (TAC) is an immunosuppressant widely used in kidney transplantation. TAC displays considerable interindividual variability in pharmacokinetics (PKs). Genetic and clinical factors play important roles in TAC PKs. We enrolled a total of 251 Chinese renal transplant recipients and conducted a genomewide association study (GWAS), linkage disequilibrium (LD), and one-way analysis of variance (ANOVA) to find genetic variants affecting log-transformed TAC trough blood concentration/dose ratio (log[C0 /D]). In addition, we performed dual luciferase reporter gene assays and multivariate regression models to evaluate the effect of the genetic variants. The GWAS results showed that all 23 genomewide significant single-nucleotide polymorphisms (p < 5 × 10-8 ) were located on chromosome 7, including CYP3A5*3. LD, conditional association analysis, and one-way ANOVA showed that rs75125371 T > C independently influenced TAC log(C0 /D). Dual luciferase reporter gene assays indicated that rs75125371 minor allele (C) was significantly associated with increased normalized luciferase activity than the major allele (T) in the Huh7 cells (p = 1.2 × 10-5 ) and HepaRG cells (p = 0.0097). A model inclusive of age, sex, hematocrit, CYP3A5*3, and rs75125371 explained 37.34% variance in TAC C0 . These results suggest that rs75125371 T > C is a functional and population-specific variant affecting TAC C0 in Chinese renal transplant recipients.

This study aims to investigate the frequencies and association of CYP3A5 polymorphism with tacrolimus concentration among renal transplant recipients in Vietnam.

Sixty-eight kidney transplant recipients were included in this study from the department of nephrology and dialysis, Military Hospital 103. Blood samples were collected for monitoring of tacrolimus levels and determination of CYP3A5 genetic polymorphism.

A total of 68 patients studied. The CYP3A5*3*3, CYP3A5*1*3, and CYP3A5*1*1 genotypes were detected in 48 (70.6%), 16 (23.5%), and 4 (5.9%), respectively. Tacrolimus concentrations were much lower in CYP3A5 expressors than in CYP3A5 nonexpressors on the first day, month 1, 3, 6, and 12 (5.98 ± 1.05 vs 6.57 ± 1.03, P = .03; 5.79 ± 1.13 vs 6.82 ± 1.05, P < .001; 4.76 ± 1.48 vs 6.73 ± 1.09, P < .001; 4.29 ± 1.64 vs 6.46 ± 1.23, P < .001; 4.20 ± 1.36 vs 6.04 ± 1.26, P < .001), respectively. Notably, the concentration/dose ratio in the CYP3A5 expressors was lower than in CYP3A5 nonexpressors at time points of follow up (P < .001). However, there were no significant differences in the age, sex, HLA mismatch, type of donors, acute rejection, and creatinine levels at time points between group of CYP3A5 expressors and those of CYP3A5 nonexpressors.

In conclusion, this research indicated the significant association of CYP3A5 genetic polymorphism with daily dose and tacrolimus concentrations in renal transplant recipients. This study provided a closer step to individualize the dose of tacrolimus in renal transplant patients in Vietnam.

The influence of pharmacogenetics in tacrolimus pharmacokinetics and pharmacodynamics needs further investigation, considering its potential in assisting clinicians to predict the optimal starting dosage and the need for a personalized adjustment of the dose, as well as to identify patients at a high risk of rejection, drug-related adverse effects, or poor outcomes. In the past decade, new pharmacokinetic strategies have been developed to improve personalized tacrolimus treatment. Several studies have shown that patients with tacrolimus doses C0/D < 1 ng/mL/mg may demonstrate a greater incidence of drug-related adverse events and infections. In addition, C0 tacrolimus intrapatient variability (IPV) has been identified as a potential biomarker to predict poor outcomes related to drug over- and under-exposure. With regard to tacrolimus pharmacodynamics, inconsistent genotype-phenotype relationships have been identified. The aim of this review is to provide a concise summary of currently available data regarding the influence of pharmacogenetics on the clinical outcome of patients with high intrapatient variability and/or a fast metabolizer phenotype. Moreover, the role of membrane transporters in the interindividual variability of responses to tacrolimus is critically discussed from a transporter scientist’s perspective. Indeed, the relationship between transporter polymorphisms and intracellular tacrolimus concentrations will help to elucidate the interplay between the biological mechanisms underlying genetic variations impacting drug concentrations and clinical effects.

Various factors, including genetic polymorphisms, drug-drug interactions, and patient characteristics influence the blood concentrations of tacrolimus in renal transplant patients. In the present study, we established a population pharmacokinetic model to explore the effect of combined use of Wuzhi capsules/echinocandins and the patients' biochemical parameters such as hematocrit on blood concentrations and target doses of tacrolimus in renal transplant patients with different CYP3A5 genotypes. The aim of the study was to propose an individualized tacrolimus administration regimen for early renal transplant recipients.In this retrospective cohort study, we included 240 renal transplant recipients within 21 days of surgery (174 males and 66 females, mean age 39.4 years), who received tacrolimus alone (n = 54), in combination with Wuzhi capsules (99) or caspofungin (57) or micafungin (30). We collected demographic characteristics, clinical indicators, CYP3A5 genotypes, and 1950 steady-state trough concentrations of tacrolimus and included them in population pharmacokinetic model. An additional 110 renal transplant recipients and 625 steady-state trough concentrations of tacrolimus were included for external validation of the model. The population pharmacokinetic model was established and Monte Carlo was used to simulate probabilities for achieving the target concentration for individual tacrolimus administration.A two-compartment model of first-order absorption and elimination was developed to describe the population pharmacokinetics of tacrolimus. CYP3A5 genotypes and co-administration of Wuzhi capsules, as well as time after renal transplantation and hematocrit, were important factors affecting the clearance of tacrolimus. We found no obvious change in trend in the scatter plot of tacrolimus clearance rate vs. hematocrit. The Monte Carlo simulation indicated the following recommended doses of tacrolimus alone: 0.14 mg·kg^-1·d^-1 for genotype CYP3A5*1*1, 0.12 mg·kg^-1·d^-1 for CYP3A5*1*3, and 0.10 mg·kg^-1·d^-1 for CYP3A5*3*3. For patients receiving the combination with Wuzhi capsules, the recommended doses of tacrolimus were 0.10 mg·kg^-1·d^-1 for CYP3A5*1*1, 0.08 mg·kg^-1·d^-1 for CYP3A5*1*3, and 0.06 mg·kg^-1·d^-1 for CYP3A5*3*3 genotypes. Caspofungin or micafungin had no effect on the clearance of tacrolimus in renal transplant recipients.The population pharmacokinetics of tacrolimus in renal transplant patients was evaluated and the individual administration regimen of tacrolimus was simulated. For early kidney transplant recipients receiving tacrolimus treatment, not only body weight, but also CYP3A5 genotypes and drugs used in combination should be considered when determining the target dose of tacrolimus.

The purpose of this study was to investigate the effect of CYP3A7, CYP3A4, and CYP3A5 genetic polymorphisms in liver transplant recipients and donors on tacrolimus concentrations in the early stages after liver transplantation.

One hundred and thirty-eight liver transplant recipients and matched donors were genotyped for CYP3A7 (rs10211 and rs2257401), CYP3A4 (rs4646437 and rs2242480), and CYP3A5*3 (rs776746) polymorphisms. The relationships between dose-adjusted trough concentrations (C₀/D) of tacrolimus and corresponding genotypes were investigated.

Recipient CYP3A polymorphisms were associated with tacrolimus concentrations. The CYP3A7 rs10211 AA carriers (186.2 vs 90.5, p < 0.001), CYP3A4 rs4646437 CC carriers (184.0 vs 88.8, p < 0.001), CYP3A4*1G rs2242480 CC carriers (189.8 vs 99.7, p < 0.001), and CYP3A5*3 rs776746 GG carriers (197.3 vs 86.0, p < 0.001) had an almost twofold increase in the tacrolimus C₀/D compared to that of the non-carriers. We further investigated the effect of the combination of recipient (intestinal) and donor (hepatic) genotypes on tacrolimus concentrations. Regardless of the genotype of the matched donor, CYP3A7 rs10211, CYP3A4*1G (rs2242480), and CYP3A5*3 (rs776746) polymorphisms of recipients could affect tacrolimus concentrations. For the CYP3A4 rs4646437 polymorphisms, when the donor carried CYP3A4 rs4646437 CC, the recipient CYP3A4 rs4646437 polymorphism was associated with the C₀/D of tacrolimus, and when the donor carried CYP3A4 rs4646437 CT/TT genotype, the recipient CYP3A4 rs4646437 polymorphism also affected on tacrolimus C₀/D, although the effect was not significant.

The large inter-individual variation in tacrolimus concentrations in the early stages after liver transplantation is influenced by genetic polymorphisms of CYP3A7, CYP3A4, and CYP3A5. Recipient (intestinal) CYP3A7, CYP3A4, and CYP3A5 polymorphisms seem to contribute more to such variation than donors. Therefore, the detection of CYP3A polymorphisms in recipients could help to predict the tacrolimus starting dose in the early stages after liver transplantation.

Inter-ethnic variability in pharmacokinetics (PK) has been attributed to several factors ranging from genetic to environmental. It is not clear how current teaching in higher education (HE) reflects what published literature suggests on this subject. This study aims to gain insights into current knowledge about inter-ethnic differences in PK based on reports from published literature and current teaching practices in HE. A systematic literature search was conducted on PubMed and Scopus to identify suitable literature to be reviewed. Insights into inter-ethnic differences in PK teaching among educators in HE and industry were determined using a questionnaire. Thirty-one percent of the studies reviewed reported inter-ethnic differences in PK, of these, 37% of authors suggested genetic polymorphism as possible explanation for the inter-ethnic differences observed. Other factors authors proposed included diet and weight differences between ethnicities. Most respondents (80%) who taught inter-ethnic difference in PK attributed inter-ethnic differences to genetic polymorphism. While genetic polymorphism is one source of variability in PK, the teaching of genetic polymorphism is better associated with interindividual variabilities rather than inter-ethnic differences in PK as there are no genes with PK implications specific to any one ethnic group. Nongenetic factors such as diet, weight, and environmental factors, should be highlighted as potential sources of interindividual variation in the PK of drugs.

Genetic variation in the CYP3A4 and CYP3A5 (CYP3A4/5) genes, which encode the key enzymes in tacrolimus metabolism, is associated with tacrolimus clearance and dose requirements. Tacrolimus has a narrow therapeutic index with high intra- and intersubject variability, in part because of genetic variation. High tacrolimus clearance and low trough concentration are associated with a greater risk for rejection, whereas high troughs are associated with calcineurin-induced toxicity. The objective of this study was to develop a model of tacrolimus clearance with a dosing equation accounting for genotypes and clinical factors in adult kidney transplant recipients of European ancestry that could preemptively guide dosing. Recipients receiving immediate-release tacrolimus for maintenance immunosuppression from 2 multicenter studies were included. Participants in the GEN03 study were used for tacrolimus model development (n = 608 recipients) and was validated by prediction performance in the DeKAF Genomics study (n = 1361 recipients). Nonlinear mixed-effects modeling was used to develop the apparent oral tacrolimus clearance (CL/F) model. CYP3A4/5 genotypes and clinical covariates were tested for their influence on CL/F. The predictive performance of the model was determined by assessing the bias (median prediction error [ME] and median percentage error [MPE]) and the precision (root median squared error [RMSE]) of the model. CYP3A5*3, CYP3A4*22, corticosteroids, calcium channel blocker and antiviral drug use, age, and diabetes significantly contributed to the interindividual variability of oral tacrolimus apparent clearance. The bias (ME, MPE) and precision (RMSE) of the final model was good, 0.49 ng/mL, 6.5%, and 3.09 ng/mL, respectively. Prospective testing of this equation is warranted.

Several healthcare organizations across Minnesota have developed formal pharmacogenomic (PGx) clinical programs to increase drug safety and effectiveness. Healthcare professional and student education is strong and there are multiple opportunities in the state for learners to gain workforce skills and develop advanced competency in PGx. Implementation planning is occurring at several organizations and others have incorporated structured utilization of PGx into routine workflows. Laboratory-based and translational PGx research in Minnesota has driven important discoveries in several therapeutic areas. This article reviews the state of PGx activities in Minnesota including educational programs, research, national consortia involvement, technology, clinical implementation and utilization and reimbursement, and outlines the challenges and opportunities in equitable implementation of these advances.

The strong inter-individual pharmacokinetic variability and the narrow therapeutic window of tacrolimus (TAC) have hampered the clinical application. Gene polymorphisms play an important role in TAC pharmacokinetics. Here, we investigate the influence of genotypes of IL-10, CYP3A5, CYP2C8, and ABCB1 on dose-adjusted trough blood concentrations (the C₀/D ratio) of TAC to reveal unclear genetic factors that may affect TAC dose requirements for renal transplant recipients.

Genetic polymorphisms of IL-10, CYP3A5, CYP2C8, and ABCB1 in 188 renal transplant recipients were determined using Kompetitive Allele Specific PCR (KASP). Statistical analysis was applied to examine the effect of genetic variation on the TAC C₀/D at 5, 10, 15, and 30 days after transplantation.

Recipients carrying the IL-10 -819C > T TT genotype showed a significantly higher TAC C₀/D than those with the TC/CC genotype (p < 0.05). Additionally, the TAC C₀/D values of recipients with the capacity for low IL-10 activity (-819 TT) engrafted with CYP3A5 non-expressers were higher compared to the intermediate/high activity of IL-10 -819C > T TC or CC carrying CYP3A5 expressers, and the difference was statistically significant at different time points (p < 0.05).

Genetic polymorphisms of IL-10 -819C > T and CYP3A5 6986A > G influence the TAC C₀/D, which may contribute to variation in TAC dose requirements during the early post-transplantation period. Detecting IL-10 -819C > T and CYP3A5 6986A > G polymorphisms may allow determination of individualized tacrolimus dosage regimens for renal transplant recipients during the early post-transplantation period.

The aim of this study was to identify novel genetic variants affecting tacrolimus trough blood concentrations. We analyzed the association between 58 single nucleotide polymorphisms (SNPs) across the CYP3A gene cluster and the log-transformed tacrolimus concentration/dose ratio (log (C₀/D)) in 819 renal transplant recipients (Discovery cohort). Multivariate linear regression was used to test for associations between tacrolimus log (C₀/D) and clinical factors. Luciferase reporter gene assays were used to evaluate the functions of select SNPs. Associations of putative functional SNPs with log (C₀/D) were further tested in 631 renal transplant recipients (Replication cohort). Nine SNPs were significantly associated with tacrolimus log (C₀/D) after adjustment for CYP3A5*3 and clinical factors. Dual luciferase reporter assays indicated that the rs4646450 G allele and rs3823812 T allele were significantly associated with increased normalized luciferase activity ratios (p < 0.01). Moreover, CYP3A7*2 was associated with higher TAC log(C₀/D) in the group of CYP3A5 expressers. Age, serum creatinine and hematocrit were significantly associated with tacrolimus log (C₀/D). CYP3A7*2, rs4646450, and rs3823812 are proposed as functional SNPs affecting tacrolimus trough blood concentrations in Chinese renal transplant recipients. Clinical factors also significantly affect tacrolimus metabolism.

Clinical outcomes after organ transplantation have greatly improved in the past 2 decades with the discovery and development of immunosuppressive drugs such as calcineurin inhibitors, antiproliferative agents, and mammalian target of rapamycin inhibitors. However, individualized dosage regimens have not yet been fully established for these drugs except for therapeutic drug monitoring-based dosage modification because of extensive interindividual variations in immunosuppressive drug pharmacokinetics. The variations in immunosuppressive drug pharmacokinetics are attributed to interindividual variations in the functional activity of cytochrome P450 enzymes, UDP-glucuronosyltransferases, and ATP-binding cassette subfamily B member 1 (known as P-glycoprotein or multidrug resistance 1) in the liver and small intestine. Some genetic variations have been found to be involved to at least some degree in pharmacokinetic variations in post-transplant immunosuppressive therapy. It is well known that the frequencies and effect size of minor alleles vary greatly between different races. Thus, ethnic considerations might provide useful information for optimizing individualized immunosuppressive therapy after organ transplantation. Here, we review ethnic factors affecting the pharmacokinetics of immunosuppressive drugs requiring therapeutic drug monitoring, including tacrolimus, cyclosporine, mycophenolate mofetil, sirolimus, and everolimus.

BACKGROUND The pharmacokinetics and metabolism of tacrolimus, an immunosuppressant commonly used to prevent transplant rejection, can differ in specific subpopulations. This analysis examined treatment outcomes and safety of immediate-release tacrolimus (IR-Tac) and LCP-tacrolimus (LCPT) in stable Hispanic kidney transplant recipients. MATERIAL AND METHODS This was a post hoc analysis of clinical trial data from Hispanic adult stable kidney transplant recipients randomized to remain on IR-Tac or convert from IR-Tac to a reduced dose of LCPT (NCT00817206). Composite treatment failure was evaluated at 12 months. Estimated glomerular filtration rate and tacrolimus trough concentrations were evaluated over 12 months. RESULTS Fifty-five stable (LCPT n=26, IR-Tac n=29) kidney transplant recipients who self-identified as Hispanic or Latino were included in this analysis. Composite treatment failure occurred in 1 patient (4%) who converted to LCPT and 1 (3%) who remained on IR-Tac. The estimated glomerular filtration rate was stable over time and similar in the 2 treatment groups (P=0.08). Tacrolimus trough levels for both groups were similar over time in the 2 treatment groups (P=0.98). Treatment-emergent adverse events were similar in patients who converted to LCPT and in those who remained on IR-Tac. CONCLUSIONS Efficacy and safety were similar in Hispanic kidney transplant recipients who converted from IR-Tac to LCPT and in those remaining on IR-Tac.

Meltdose tacrolimus (Envarsus) is marketed as a formulation with a more consistent exposure. Due to the narrow therapeutic window, therapeutic drug monitoring is essential to maintain adequate exposure. The primary objective of this study was to develop a population pharmacokinetic (PK) model of Envarsus among liver transplant patients and select a limited sampling strategy (LSS) for AUC estimation. The secondary objective was to investigate potential covariates including CYP3A/IL genotype suitable for initial dose optimization when converting to Envarsus.

Adult liver transplant patients were converted from prolonged release tacrolimus (Advagraf) to Envarsus and blood samples were obtained using whole blood and dried blood spot sampling. Subsequently the population PK parameters were estimated using nonlinear-mixed effect modelling. Demographic factors, and recipient and donor CYP3A4, CYP3A5, IL-6, -10 and -18 genotype were tested as potential covariates to explain interindividual variability.

Fifty-five patients were included. A 2-compartment model with delayed absorption was the most suitable to describe population PK parameters. The population PK parameters were as follows: clearance, 3.27 L/h; intercompartmental clearance, 9.6 L/h; volume of distribution of compartments 1 and 2, 95 and 500 L, respectively. No covariates were found to significantly decrease interindividual variability. The best 3-point LSS was t = 0,4,8 with a median bias of 1.8% (-12.5-12.5).

The LSS can be used to adequately predict the AUC. No clinically relevant covariates known to influence the PK of Envarsus, including CYP3A status, were identified and therefore do not seem useful for initial dose optimization.