The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients

Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies

Background

In addition to HLA genetic incompatibility, non-HLA difference between donor and recipients of transplantation leading to allograft rejection are now becoming evident. We aimed to create a unique genome-wide platform to facilitate genomic research studies in transplant-related studies. We designed a genome-wide genotyping tool based on the most recent human genomic reference datasets, and included customization for known and potentially relevant metabolic and pharmacological loci relevant to transplantation.

Methods

We describe here the design and implementation of a customized genome-wide genotyping array, the ‘TxArray’, comprising approximately 782,000 markers with tailored content for deeper capture of variants across HLA, KIR, pharmacogenomic, and metabolic loci important in transplantation. To test concordance and genotyping quality, we genotyped 85 HapMap samples on the array, including eight trios.

Results

We show low Mendelian error rates and high concordance rates for HapMap samples (average parent-parent-child heritability of 0.997, and concordance of 0.996). We performed genotype imputation across autosomal regions, masking directly genotyped SNPs to assess imputation accuracy and report an accuracy of >0.962 for directly genotyped SNPs. We demonstrate much higher capture of the natural killer cell immunoglobulin-like receptor (KIR) region versus comparable platforms. Overall, we show that the genotyping quality and coverage of the TxArray is very high when compared to reference samples and to other genome-wide genotyping platforms.

Conclusions

We have designed a comprehensive genome-wide genotyping tool which enables accurate association testing and imputation of ungenotyped SNPs, facilitating powerful and cost-effective large-scale genotyping of transplant-related studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0211-x) contains supplementary material, which is available to authorized users.

Role of pharmacogenomics in dialysis and transplantation

PURPOSE OF REVIEW

Pharmacogenomics is the study of differences in drug response on the basis of individual genetic background. With rapidly advancing genomic technologies and decreased costs of genotyping, the field of pharmacogenomics continues to develop. Application to patients with kidney disease provides growing opportunities for improving drug therapy.

RECENT FINDINGS

Pharmacogenomics studies are lacking in patients with chronic kidney disease and dialysis, but are abundant in the kidney transplant field. A potentially clinically actionable genetic variant exists in the CYP3A5 gene, with the initial tacrolimus dose selection being optimized based on CYP3A5 genotype. Although many pharmacogenomics studies have focused on transplant immunosuppression pharmacokinetics, an expanding literature on pharmacodynamic outcomes, such as calcineurin inhibitor toxicity and new onset diabetes, is providing new information on patients at risk.

SUMMARY

Appropriately powered pharmacogenomics studies with well-defined phenotypes are needed to validate existing studies and unearth new findings in patients with kidney disease, especially the chronic kidney disease and dialysis population.

Clinical and Genetic Factors Associated with Cutaneous Squamous Cell Carcinoma in Kidney and Heart Transplant Recipients

BACKGROUND

Cutaneous squamous cell carcinoma (cSCC) occurs with higher frequency and recurrence rates, increased morbidity and mortality, and more aggressive metastasis in kidney and heart transplant recipients compared to the general population but all transplant recipients do not develop cSCC. In addition, the phenotypic expression of cSCC among transplant recipients can vary between mild disease to extensive recurrent metastatic disease. These clinically observed differences in occurrence and severity of cSCC among transplant recipients suggest the possibility that an underlying genetic component might modify risk.

METHODS

We identified 88 white post-transplant cSCC cases (71 kidney and 17 heart) and 300 white post-transplant controls (265 kidney and 35 heart) using a DNA biobank linked with de-identified electronic medical records. Logistic regression was used to determine adjusted odds ratios (OR) for clinical characteristics and single nucleotide polymorphisms (SNP) associated with cSCC in both a candidate SNP and genome wide analysis.

RESULTS

Age (OR 1.08 [1.05-1.11], p<0.001) and azathioprine exposure (OR 8.64 [3.92-19.03], p<0.001) were significantly associated while gender, smoking tobacco use, dialysis duration and immunosuppression duration were not. Ten candidate SNPs previously associated with non-melanoma skin cancer in the general population were significantly associated with cSCC in transplant recipients. Genome wide association analysis implicated SNPs in genes previously associated with malignancy, CSMD1 (OR 3.14 [1.90-5.20]) and CACNA1D (OR 2.67 [1.73-4.10]).

CONCLUSIONS

This study shows an association of increasing age and azathioprine exposure with cSCC and confirms a genetic contribution for cSCC development in kidney and heart transplant recipients.

Extracting research-quality phenotypes from electronic health records to support precision medicine

The convergence of two rapidly developing technologies - high-throughput genotyping and electronic health records (EHRs) - gives scientists an unprecedented opportunity to utilize routine healthcare data to accelerate genomic discovery. Institutions and healthcare systems have been building EHR-linked DNA biobanks to enable such a vision. However, the precise extraction of detailed disease and drug-response phenotype information hidden in EHRs is not an easy task. EHR-based studies have successfully replicated known associations, made new discoveries for diseases and drug response traits, rapidly contributed cases and controls to large meta-analyses, and demonstrated the potential of EHRs for broad-based phenome-wide association studies. In this review, we summarize the advantages and challenges of repurposing EHR data for genetic research. We also highlight recent notable studies and novel approaches to provide an overview of advanced EHR-based phenotyping.

CYP3A5 and CYP3A4, but not ABCB1 polymorphisms affect tacrolimus dose-adjusted trough concentrations in kidney transplant recipients

BACKGROUND

Tacrolimus (TAC), acting as a calcineurin inhibitor, is an immunosuppressant widely used after kidney transplantation. TAC requires blood concentration monitoring due to large interindividual variability in its pharmacokinetics and a narrow therapeutic index. Since genetic factors are considered responsible for a part of the observed pharmacokinetic variability, hereby SNPs within the CYP3A4, CYP3A5 and ABCB1 genes in kidney transplant patients of Polish Caucasian origin were investigated.

PATIENTS & METHODS

A total of 241 patients treated with TAC through the first year after kidney transplantation were genotyped for the presence of common SNPs: rs776746:A>G (CYP3A5*3), rs35599367:C>T (CYP3A4*22), rs2740574:A>G (CYP3A4*1B) and rs1045642:C>T (ABCB1 3435C>T) using TaqMan(®) assays.

RESULTS

CYP3A5 expressers received significantly higher weight-adjusted TAC doses, and were characterized by markedly lower C0 and dose adjusted C0 values in the course of treatment. CYP3A4*1B was significantly associated with TAC pharmacokinetics in univariate analysis. Impact of the CYP3A4*22 allele was significant only at particular time points, that is, 3 months after transplantation, with marginal significance 6 months after transplantation. The ABCB1 genotype did not influence TAC pharmacokinetics. Multivariate analysis of all the studied loci demonstrated that only the CYP3A5*1 (starting from month 1) and CYP3A4*22 alleles (at 3 and 6 months) were independent predictors of TAC dose-adjusted C0.

CONCLUSION

Our results confirm the impact of the CYP3A4*22 allele on TAC pharmacokinetics, as a second significant genetic factor (in addition to the CYP3A5*1 allele) influencing TAC dose-adjusted blood concentrations in kidney transplant recipients.

The Making of a CYP3A Biomarker Panel for Guiding Drug Therapy

CYP3A ranks among the most abundant cytochrome P450 enzymes in the liver, playing a dominant role in metabolic elimination of clinically used drugs. A main member in CYP3A family, CYP3A4 expression and activity vary considerably among individuals, attributable to genetic and non-genetic factors, affecting drug dosage and efficacy. However, the extent of genetic influence has remained unclear. This review assesses current knowledge on the genetic factors influencing CYP3A4 activity. Coding region CYP3A4 polymorphisms are rare and account for only a small portion of inter-person variability in CYP3A metabolism. Except for the promoter allele CYP3A4*1B with ambiguous effect on expression, common CYP3A4 regulatory polymorphisms were thought to be lacking. Recent studies have identified a relatively common regulatory polymorphism, designated CYP3A4*22 with robust effects on hepatic CYP3A4 expression. Combining CYP3A4*22 with CYP3A5 alleles *1, *3 and *7 has promise as a biomarker predicting overall CYP3A activity. Also contributing to variable expression, the role of polymorphisms in transcription factors and microRNAs is discussed.

Clinical implementation of pharmacogenetics in kidney transplantation: calcineurin inhibitors in the starting blocks

Pharmacogenetics has generated many expectations for its potential to individualize therapy proactively and improve medical care. However, despite the huge amount of reported genetic associations with either pharmacokinetics or pharmacodynamics of drugs, the translation into patient care is still slow. In fact, strong evidence for a substantial clinical benefit of pharmacogenetic testing is still limited, with a few exceptions. In kidney transplantation, established pharmacogenetic discoveries are being investigated for application in the clinic to improve efficacy and to limit toxicity associated with the use of immunosuppressive drugs, especially the frequently used calcineurin inhibitors (CNIs) tacrolimus and ciclosporin. The purpose of the present review is to picture the current status of CNI pharmacogenetics and to discuss the most promising leads that have been followed so far.

Pharmacogenetics and immunosuppressive drugs in solid organ transplantation

The transplantation literature includes numerous papers that report associations between polymorphisms in genes encoding metabolizing enzymes and drug transporters, and pharmacokinetic data on immunosuppressive drugs. Most of these studies are retrospective in design, and although a substantial number report significant associations, pharmacogenetic tests are hardly used in clinical practice. One of the reasons for this poor implementation is the current lack of evidence of improved clinical outcome with pharmacogenetic testing. Furthermore, with efficient therapeutic drug monitoring it is possible to rapidly correct for the effect of genotypic deviations on pharmacokinetics, thereby decreasing the utility of genotype-based dosing. The future of pharmacogenetics will be in treatment models in which patient characteristics are combined with data on polymorphisms in multiple genes. These models should focus on pharmacodynamic parameters, variations in the expression of drug transporter proteins, and predictors of toxicity. Such models will provide more information than the relatively small candidate gene studies performed so far. For implementation of these models into clinical practice, linkage of genotype data to medication prescription systems within electronic health records will be crucial.

Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems

We describe here the design and initial implementation of the eMERGE-PGx project. eMERGE-PGx, a partnership of the eMERGE and PGRN consortia, has three objectives : 1) Deploy PGRNseq, a next-generation sequencing platform assessing sequence variation in 84 proposed pharmacogenes, in nearly 9,000 patients likely to be prescribed drugs of interest in a 1–3 year timeframe across several clinical sites; 2) Integrate well-established clinically-validated pharmacogenetic genotypes into the electronic health record with associated clinical decision support and assess process and clinical outcomes of implementation; and 3) Develop a repository of pharmacogenetic variants of unknown significance linked to a repository of EHR-based clinical phenotype data for ongoing pharmacogenomics discovery. We describe site-specific project implementation and anticipated products, including genetic variant and phenotype data repositories, novel variant association studies, clinical decision support modules, clinical and process outcomes, approaches to manage incidental findings, and patient and clinician education methods.

Extracting and standardizing medication information in clinical text - the MedEx-UIMA system

Extraction of medication information embedded in clinical text is important for research using electronic health records (EHRs). However, most of current medication information extraction systems identify drug and signature entities without mapping them to standard representation. In this study, we introduced the open source Java implementation of MedEx, an existing high-performance medication information extraction system, based on the Unstructured Information Management Architecture (UIMA) framework. In addition, we developed new encoding modules in the MedEx-UIMA system, which mapped an extracted drug name/dose/form to both generalized and specific RxNorm concepts and translated drug frequency information to ISO standard. We processed 826 documents by both systems and verified that MedEx-UIMA and MedEx (the Python version) performed similarly by comparing both results. Using two manually annotated test sets that contained 300 drug entries from medication list and 300 drug entries from narrative reports, the MedEx-UIMA system achieved F-measures of 98.5% and 97.5% respectively for encoding drug names to corresponding RxNorm generic drug ingredients, and F-measures of 85.4% and 88.1% respectively for mapping drug names/dose/form to the most specific RxNorm concepts. It also achieved an F-measure of 90.4% for normalizing frequency information to ISO standard. The open source MedEx-UIMA system is freely available online at http://code.google.com/p/medex-uima/.

Transplantation genetics: current status and prospects

Over the last decade, advances in genetic technologies have accelerated our understanding of the genetic diversity across individuals and populations. Case-control and population-based studies have led to several thousand genetic associations across a range of phenotypes and traits being unveiled. Despite widespread and successful use of organ transplantation as a curative therapy for organ failure, genetic research has yet to make a major impact on transplantation practice aside from HLA matching. New studies indicate that non-HLA loci, termed minor histocompatibility antigens (mHAs), may play an important role in graft rejection. With several million common and rare polymorphisms observed between any two unrelated individuals, a number of these polymorphisms represent mHAs, and may underpin transplantation rejection. Genetic variation is also recognized as contributing to clinical outcomes including response to immunosuppressants, introducing the possibility of genotype-guided prescribing in the very near future. This review summarizes existing knowledge of the impact of genetics on transplantation outcomes and therapeutic responses, and highlights the translational potential that new genomic knowledge may bring to this field.

Assessment of a pharmacogenomic marker panel in a polypharmacy population identified from electronic medical records

BACKGROUND

The ADME Core Panel assays 184 variants across 34 pharmacogenes, many of which are difficult to accurately genotype with standard multiplexing methods.

METHODS

We genotyped 326 frequently medicated individuals of European descent in Vanderbilt's biorepository linked to de-identified electronic medical records, BioVU, on the ADME Core Panel to assess quality and performance of the assay. We compared quality control metrics and determined the extent of direct and indirect marker overlap between the ADME Core Panel and the Illumina Omni1-Quad.

RESULTS

We found the quality of the ADME Core Panel data to be high, with exceptions in select copy number variants and markers in certain genes (notably CYP2D6). Most of the common variants on the ADME panel are genotyped by the Omni1, but absent rare variants and copy number variants could not be accurately tagged by single markers.

CONCLUSION

Our frequently medicated study population did not convincingly differ in allele frequency from reference populations, suggesting that heterogeneous clinical samples (with respect to medications) have similar allele frequency distributions in pharmacogenetics genes compared with reference populations.

Secondary use of clinical data: the Vanderbilt approach

The last decade has seen an exponential growth in the quantity of clinical data collected nationwide, triggering an increase in opportunities to reuse the data for biomedical research. The Vanderbilt research data warehouse framework consists of identified and de-identified clinical data repositories, fee-for-service custom services, and tools built atop the data layer to assist researchers across the enterprise. Providing resources dedicated to research initiatives benefits not only the research community, but also clinicians, patients and institutional leadership. This work provides a summary of our approach in the secondary use of clinical data for research domain, including a description of key components and a list of lessons learned, designed to assist others assembling similar services and infrastructure.

Pharmacogenetics in solid organ transplantation: genes involved in mechanism of action and pharmacokinetics of immunosuppressive drugs

Allogenic solid organ transplantation has become the routine procedure in patients with end stage organ disease. Although the transplanted organ compensates deficient body functions, its allogenic nature requires institution of immune tolerance, nowadays provided by immunosuppressive drug administration. Both the safety and efficacy of immunosuppressive treatment depend on many factors, and maintaining levels of immunosuppressants within therapeutic range is the essential target for success in graft function preservation. It is obvious that drug and metabolite concentrations depend on efficiency of individual patient metabolism. Recently, many studies were undertaken to investigate the relationship between genetic factors, drug pharmacokinetics and therapy outcome, and interindividual variability apparently can be explained, at least in part, by genetically determined polymorphisms of xenobiotic-metabolizing enzymes, transport proteins and also in some cases, drug targets. This review presents the recent state of knowledge in the field of pharmacogenetics related to solid organ transplantation.

Utilization of an EMR-biorepository to identify the genetic predictors of calcineurin-inhibitor toxicity in heart transplant recipients

Calcineurin-inhibitors CI are immunosuppressive agents prescribed to patients after solid organ transplant to prevent rejection. Although these drugs have been transformative for allograft survival, long-term use is complicated by side effects including nephrotoxicity. Given the narrow therapeutic index of CI, therapeutic drug monitoring is used to prevent acute rejection from underdosing and acute toxicity from overdosing, but drug monitoring does not alleviate long-term side effects. Patients on calcineurin-inhibitors for long periods almost universally experience declines in renal function, and a subpopulation of transplant recipients ultimately develop chronic kidney disease that may progress to end stage renal disease attributable to calcineurin inhibitor toxicity (CNIT). Pharmacogenomics has the potential to identify patients who are at high risk for developing advanced chronic kidney disease caused by CNIT and providing them with existing alternate immunosuppressive therapy. In this study we utilized BioVU, Vanderbilt University Medical Center's DNA biorepository linked to de-identified electronic medical records to identify a cohort of 115 heart transplant recipients prescribed calcineurin-inhibitors to identify genetic risk factors for CNIT We identified 37 cases of nephrotoxicity in our cohort, defining nephrotoxicity as a monthly median estimated glomerular filtration rate (eGFR)<30 mL/min/1.73 m2 at least six months post-transplant for at least three consecutive months. All heart transplant patients were genotyped on the Illumina ADME Core Panel, a pharmacogenomic genotyping platform that assays 184 variants across 34 genes. In Cox regression analysis adjusting for age at transplant, pre-transplant chronic kidney disease, pre-transplant diabetes, and the three most significant principal components (PCAs), we did not identify any markers that met our multiple-testing threshold. As a secondary analysis we also modeled post-transplant eGFR directly with linear mixed models adjusted for age at transplant, cyclosporine use, median BMI, and the three most significant principal components. While no SNPs met our threshold for significance, a SNP previously identified in genetic studies of the dosing of tacrolimus CYP34A rs776746, replicated in an adjusted analysis at an uncorrected p-value of 0.02 (coeff(S.E.)=14.60(6.41)). While larger independent studies will be required to further validate this finding, this study underscores the EMRs usefulness as a resource for longitudinal pharmacogenetic study designs.

Discordant associations between SLCO1B1 521T→C and plasma levels of ritonavir-boosted protease inhibitors in AIDS clinical trials group study A5146

OBJECTIVE

Among HIV-positive patients prescribed ritonavir-boosted lopinavir, SLCO1B1 521T→C (rs4149056) is associated with increased plasma lopinavir exposure. Protease inhibitors (PIs) are also substrates for cytochrome P450 (CYP) 3A and ABCB1, which are induced by NR1I2. We characterized relationships between ABCB1, CYP3A4, CYP3A5, NR1I2, and SLCO1B1 polymorphisms and trough PI concentrations among AIDS Clinical Trials Group study A5146 participants.

METHODS

At study entry, subjects with virologic failure on PI-containing regimens initiated new ritonavir-boosted PI regimens. We studied associations between week 2 PI plasma trough concentrations and 143 polymorphisms in these genes, including 4 targeted polymorphisms.

RESULTS

Among 275 subjects with both drug concentrations and genetic data, allelic frequencies of SLCO1B1 521T→C were 15%, 1%, and 8% in whites, blacks, and Hispanics, respectively. Further analyses were limited to 268 white, black, or Hispanic subjects who initiated ritonavir-boosted lopinavir (n = 98), fosamprenavir (n = 69), or saquinavir (n = 99). Of targeted polymorphisms, SLCO1B1 521T→C tended to be associated with higher lopinavir concentrations, with a 1.38-fold increase in the mean per C allele (95% confidence interval, 0.97-1.96; n = 98; P = 0.07). With fosamprenavir, SLCO1B1 521T→C was associated with lower amprenavir concentrations, with a 35% decrease in the mean per C allele (geometric mean ratio 0.65; 95% confidence interval, 0.44-0.94; n = 69; adjusted P = 0.02). There was no significant association with saquinavir concentrations, and none of the remaining 139 exploratory polymorphisms were statistically significant after correcting for multiple comparisons.

CONCLUSIONS

With ritonavir-boosted PIs, a SLCO1B1 polymorphism that predicts higher lopinavir trough concentrations seems to predict lower amprenavir trough concentrations. The mechanism underlying this discordant association is uncertain.

A published pharmacogenetic algorithm was poorly predictive of tacrolimus clearance in an independent cohort of renal transplant recipients

AIMS

An algorithm based on the CYP3A5 genotype to predict tacrolimus clearance to inform the optimal initial dose was derived using data from the DeKAF study (Passey et al. Br J Clin Pharmacol 2011; 72: 948-57) but was not tested in an independent cohort of patients. Our aim was to test whether the DeKAF dosing algorithm could predict estimated tacrolimus clearance in renal transplant recipients at our centre.

METHODS

Predicted tacrolimus clearance based on the DeKAF algorithm was compared with dose-normalized trough whole-blood concentrations (estimated clearance) on day 7 after transplantation in a single-centre cohort of 255 renal transplant recipients.

RESULTS

There was a weak correlation (r = 0.431) between clearance based on dose-normalized trough whole-blood concentrations and DeKAF algorithm-predicted clearance. The means of the tacrolimus clearance predicted by the DeKAF algorithm and the estimated tacrolimus clearance based on the dose-normalized trough blood concentrations were plotted against the differences in the clearance as a Bland-Altman plot. Logarithmic transformation was performed owing to the increased difference in tacrolimus clearance as the mean clearance increased. There was a highly significant systematic error (P < 0.0005) characterized by a sloped regression line [gradient, 0.88 (95% confidence interval, 0.75-1.01)] on the Bland-Altman plot.

CONCLUSIONS

The DeKAF algorithm was unable to predict the estimated tacrolimus clearance accurately based on real tacrolimus doses and blood concentrations in our cohort of patients. Other genes are known to influence the clearance of tacrolimus, and a polygenic algorithm may be more predictive than those based on a single genotype.

Novel single nucleotide polymorphisms in interleukin 6 affect tacrolimus metabolism in liver transplant patients

BACKGROUND

Tacrolimus is the first-line immunosuppressant after organ transplantation. It is mainly metabolized by cytochrome P450, family 3, subfamily A (CYP3A) enzymes, but there are large individual differences in metabolism. Interleukin 6 (IL6) has been shown to cause a pan-suppression of mRNA levels of ten major CYP enzymes in human hepatocyte cultures. IL6 has been shown to provide hepatoprotection in various models of liver injury. Rs1800796 is a locus in the IL6 gene promoter region which regulates cytokine production. We speculated that IL6 rs1800796 polymorphisms may lead to individual differences in tacrolimus metabolism by affecting CYP3A enzymes levels and liver function after liver transplantation.

METHODOLOGY/PRINCIPAL FINDINGS

Ninety-six liver transplant patients receiving tacrolimus were enrolled in the study. Two single nucleotide polymorphisms (SNP), CYP3A5 rs776746 and IL6 rs1800796, were genotyped in both donors and recipients. The effects of SNPs on tacrolimus concentration/dose (C/D ratio) at four weeks after transplantation were studied, as well as the effects of donor IL6 rs1800796 polymorphisms on liver function. Both donor and recipient CYP3A5 rs776746 allele A showed association with lower C/D ratios, while donor IL6 rs1800796 allele G showed an association with higher C/D ratios. Donor CYP3A5 rs776746 allele A, IL6 rs1800796 allele C, and recipient CYP3A5 rs776746 allele A were associated with fast tacrolimus metabolism. With increasing numbers of these alleles, patients were found to have increasingly lower tacrolimus C/D ratios at time points after transplantation. Donor IL6 rs1800796 allele G carriers showed an association with higher glutamic-pyruvic transaminase (GPT) levels.

CONCLUSIONS

Combined analysis of donor CYP3A5 rs776746, IL6 rs1800796, and recipient CYP3A5 rs776746 polymorphisms may distinguish tacrolimus metabolism better than CYP3A5 rs776746 alone. IL6 may lead to individual differences in tacrolimus metabolism mainly by affecting liver function.

From gut to kidney: transporting and metabolizing calcineurin-inhibitors in solid organ transplantation

Since their introduction circa 35 years ago, calcineurin-inhibitors (CNI) have become the cornerstone of immunosuppressive therapy in solid organ transplantation. However, CNI's possess a narrow therapeutic index with potential severe consequences of drug under- or overexposure. This demands a meticulous policy of Therapeutic Drug Monitoring (TDM) to optimize outcome. In clinical practice optimal dosing is difficult to achieve due to important inter- and intraindividual variation in CNI pharmacokinetics. A complex and often interdependent set of factors appears relevant in determining drug exposure. These include recipient characteristics such as age, race, body composition, organ function, and food intake, but also graft-related characteristics such as: size, donor-age, and time after transplantation can be important. Fundamental (in vitro) and clinical studies have pointed out the intrinsic relation between the aforementioned variables and the functional capacity of enzymes and transporters involved in CNI metabolism, primarily located in intestine, liver and kidney. Commonly occurring polymorphisms in genes responsible for CNI metabolism (CYP3A4, CYP3A5, CYP3A7, PXR, POR, ABCB1 (P-gp) and possibly UGT) are able to explain an important part of interindividual variability. In particular, a highly prevalent SNP in CYP3A5 has proven to be an important determinant of CNI dose requirements and drug-dose-interactions. In addition, a discrepancy in genotype between graft and receptor has to be taken into account. Furthermore, common phenomena in solid organ transplantation such as inflammation, ischemia- reperfusion injury, graft function, co-medication, altered food intake and intestinal motility can have a differential effect on the expression enzymes and transporters involved in CNI metabolism. Notwithstanding the built-up knowledge, predicting individual CNI pharmacokinetics and dose requirements on the basis of current clinical and experimental data remains a challenge.

Biobanking: The Melding of Research with Clinical Care

The number of biobanks around the world has increased dramatically, owing in part, to the need for researchers to have access to large numbers of samples for genomic research. Policies for enrolling participants, returning research results and obtaining samples and data can have a far reaching impact on the type of research that can be performed with each biobank. Research using biobank samples includes studies of the impact of environmental and other risk exposures on health, understanding genetic risks for common disease, identification of biomarkers in disease progression and prognosis, and implementation of personalized medicine projects. This research has been instrumental in the progress of genetic and genomic research and translational medicine. This article will highlight some of the controversies and recent research associated with biobanking over the past year.

Cytochrome P450 enzymes in drug metabolism: regulation of gene expression, enzyme activities, and impact of genetic variation

Cytochromes P450 (CYP) are a major source of variability in drug pharmacokinetics and response. Of 57 putatively functional human CYPs only about a dozen enzymes, belonging to the CYP1, 2, and 3 families, are responsible for the biotransformation of most foreign substances including 70-80% of all drugs in clinical use. The highest expressed forms in liver are CYPs 3A4, 2C9, 2C8, 2E1, and 1A2, while 2A6, 2D6, 2B6, 2C19 and 3A5 are less abundant and CYPs 2J2, 1A1, and 1B1 are mainly expressed extrahepatically. Expression of each CYP is influenced by a unique combination of mechanisms and factors including genetic polymorphisms, induction by xenobiotics, regulation by cytokines, hormones and during disease states, as well as sex, age, and others. Multiallelic genetic polymorphisms, which strongly depend on ethnicity, play a major role for the function of CYPs 2D6, 2C19, 2C9, 2B6, 3A5 and 2A6, and lead to distinct pharmacogenetic phenotypes termed as poor, intermediate, extensive, and ultrarapid metabolizers. For these CYPs, the evidence for clinical significance regarding adverse drug reactions (ADRs), drug efficacy and dose requirement is rapidly growing. Polymorphisms in CYPs 1A1, 1A2, 2C8, 2E1, 2J2, and 3A4 are generally less predictive, but new data on CYP3A4 show that predictive variants exist and that additional variants in regulatory genes or in NADPH:cytochrome P450 oxidoreductase (POR) can have an influence. Here we review the recent progress on drug metabolism activity profiles, interindividual variability and regulation of expression, and the functional and clinical impact of genetic variation in drug metabolizing P450s.

The success of pharmacogenomics in moving genetic association studies from bench to bedside: study design and implementation of precision medicine in the post-GWAS era

Pharmacogenomics is emerging as a popular type of study for human genetics in recent years. This is primarily due to the many success stories and high potential for translation to clinical practice. In this review, the strengths and limitations of pharmacogenomics are discussed as well as the primary epidemiologic, clinical trial, and in vitro study designs implemented. A brief discussion of molecular and analytic approaches will be reviewed. Finally, several examples of bench-to-bedside clinical implementations of pharmacogenetic traits will be described. Pharmacogenomics continues to grow in popularity because of the important genetic associations identified that drive the possibility of precision medicine.

Identification of factors affecting tacrolimus level and 5-year clinical outcome in kidney transplant patients

The purpose of this study was to identify and characterize the association of various clinical variables and CYP3A5 genotypes with the pharmacokinetics of tacrolimus and outcome over 1-5 years in kidney transplantation patients in Korea. A total of 129 recipients (aged 18-65 years) administered tacrolimus were genotyped for CYP3A5 (6986A>G in intron 3; rs776746). Clinical covariates and trough levels, doses and dose-adjusted trough levels of tacrolimus, as well as complications during the 1-5 years after transplantation, were analysed. A linear mixed model was used to investigate potential factors affecting the trough levels, doses and dose-adjusted levels of tacrolimus. We identified factors affecting chronic allograft nephropathy (CAN) and tacrolimus-related complications. After adjusting for sex, body-weight and doses of corticosteroids and mycophenolate mofetil, we noted that CYP3A5 genotypes had the most profound effect on the dose and dose-adjusted trough levels of tacrolimus 1-5 years after transplantation (p < 0.001). Trough levels of tacrolimus were associated with post-transplantation hyperlipidaemia (p < 0.05), and estimated glomerular filtration rate was associated with CAN (p < 0.05). Therefore, the CYP3A5 genotype is a variable marker for tacrolimus dose requirement, and the trough level of tacrolimus should be controlled to minimize post-transplant hyperlipidaemia to achieve optimum outcome.