Human pigmentation characteristics play an important role in the effects of sun exposure, skin cancer induction and disease outcomes. Several of the genes most important for this diversity are involved in the regulation and distribution of melanin pigmentation or enzymes involved in melanogenesis itself within the melanocyte cell present in the skin, hair and eyes. The single nucleotide polymorphisms and extended haplotypes within or surrounding these genes have been identified as risk factors for skin cancer, in particular, melanoma. These same polymorphisms have been under selective pressure leading towards lighter pigmentation in Europeans in the last 5,000-20,000 years that have driven the increase in frequency in modern populations. Although pigmentation is a polygenic trait, due to interactive and quantitative gene effects, strong phenotypic associations are readily apparent for these major genes. However, predictive value and utility are increased when considering gene polymorphism interactions. In melanoma, an increased penetrance is found in cases when pigmentation gene risk alleles such as MC1R variants are coincident with mutation of higher-risk melanoma genes including CDKN2A, CDK4 and MITF E318K, demonstrating an interface between the pathways for pigmentation, naevogenesis and melanoma. The clinical phenotypes associated with germline changes in pigmentation and naevogenic genes must be understood by clinicians, and will be of increasing relevance to dermatologists, as genomics is incorporated into the delivery of personalised medicine.
Summary We have compared the melanogenic activities of cultured melanocytes carrying two common TYR alleles as homozygous 192S-402R wildtype, heterozygous and homozygous variant. This includes assays of TYR protein, DOPAoxidase activity, glycosylation and temperature sensitivity of protein and DOPAoxidase levels. Homozygous wildtype strains on average had higher levels of TYR protein and enzyme activity than other genotypes. Homozygous 402Q/Q melanocytes produced significantly less TYR protein, displayed altered trafficking and glycosylation, with reduced DOPAoxidase. However, near wildtype TYR activity levels could be recovered at lower growth temperature. In a sample population from Southeast Queensland these two polymorphisms were present on four TYR haplotypes, designated as WT 192S-402R, 192Y-402R, 192S-402Q with a double variant 192Y-402Q of low frequency at 1.9%. Based on cell culture findings and haplotype associations, we have used an additive model to assess the penetrance of the ten possible TYR genotypes derived from the combination of these haplotypes.
Prednisolone and prednisone are integral components of induction and maintenance immunosuppressive regimens in solid organ transplantation. The pharmacokinetics of these agents are extremely complex. Prednisolone is the active drug moiety while prednisone is both a pro-drug and inactive metabolite of prednisolone. Within the dosage range used in transplantation, prednisolone and prednisone exhibit concentration-dependent non-linear pharmacokinetics when parameters are measured with reference to total drug concentration. Dose dependency disappears when free (unbound) prednisolone is measured. Altered organ function, changing biochemistry and use of a number of concomitant medicines in transplantation appear to lead to pharmacokinetic differences in transplant recipients compared with other patient groups. Greater than threefold variability in dose-adjusted exposure to total prednisolone in transplant recipients is evident. Time post-transplant, hepatic and renal dysfunction, patient age, sex, bodyweight, serum albumin concentration, concomitant medication exposure, various disease states and genetic polymorphisms in metabolic enzymes and drug transporters have sometimes been associated with prednisolone pharmacokinetic variability. The clinical impact of corticosteroid therapy on the disposition of ciclosporin, tacrolimus and sirolimus and the impact of different immunosuppressant therapy combinations on prednisolone exposure needs to be further elucidated. Patient response patterns to prednisolone are consistent with delayed and indirect mechanisms of corticosteroid action involving modification of nuclear transcription and protein synthesis. Many adverse effects have been linked with prednisolone and prednisone therapy, but not all of these have been investigated thoroughly in transplant populations. Dyslipidaemia, growth restriction, diabetogenesis, hypertension and cataracts are well studied toxicities. Evidence is less clear for prednisolone-induced osteonecrosis, obesity and hypertriglyceridaemia. There have been some reports of a relationship between prednisolone pharmacokinetics and incidence of acute rejection, Cushing's syndrome and adverse cardiovascular and metabolic events. Dosing of prednisolone and prednisone in transplantation is typically empirical and varies significantly across transplant centres. Currently, authoritative guidelines are conflicting in their opinions regarding corticosteroid avoidance and early discontinuation in adult kidney transplantation. Overall, data suggest the promise of corticosteroid-free immunosuppression in paediatric patients. Further investigation of the pharmacokinetics and pharmacodynamics of prednisolone and prednisone in transplant recipients based on new chromatography assay techniques and free drug measurement, population pharmacokinetic/pharmacodynamic modelling approaches, genetic testing and larger studies in patients on modern day immunosuppressant protocols may lead to better individualization of corticosteroid therapy in the future.
Mycophenolic acid (MPA) is a cornerstone immunosuppressant therapy in solid organ transplantation. MPA is metabolized by uridine diphosphate glucuronosyltransferase to inactive 7-O-MPA-glucuronide (MPAG). At least three minor metabolites are also formed, including a pharmacologically active acyl-glucuronide. MPA and MPAG are subject to enterohepatic recirculation. Biliary excretion of MPA/MPAG involves several transporters, including organic anion transporting polypeptides and multidrug resistant protein-2 (MRP-2). MPA metabolites are also excreted via the kidney, at least in part by MRP-2. MPA exerts its immunosuppressive effect through the inhibition of inosine-5-monophosphate dehydrogenase. Several SNPs have been identified in the genes encoding for uridine diphosphate glucuronosyltransferase, organic anion transporting polypeptides, MRP-2 and inosine-5-monophosphate dehydrogenase. This article provides an extensive overview of the known effects of these SNPs on the pharmacokinetics and pharmacodynamics of MPA.
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• Tacrolimus pre-dose (C0) concentrations are currently used to guide tacrolimus dosing. • However, conflicting data exist regarding the relationship of C0 with tacrolimus area under the concentration-time curve from 0 to 12 h post-dose (AUC0-12) and clinical outcomes.• Previous literature suggests that limited sampling methods, such as multiple linear regression-derived limited sampling strategies or maximum a posteriori (MAP) Bayesian analyses, may provide more reliable estimations of tacrolimus exposure. WHAT THIS STUDY ADDS• For the first time, the predictive performances of all published limited sampling methods for tacrolimus are compared in an independent cohort of adult kidney transplant recipients.• Limited sampling methods better predict tacrolimus exposure compared with measurement of C0. • However, the predictive power of the methods is highly variable, highlighting the importance of validating any method prior to applying it to an alternative population. AIMSTo examine the predictive performance of limited sampling methods for estimation of tacrolimus exposure in adult kidney transplant recipients. METHODSTwenty full tacrolimus area under the concentration-time curve from 0 to 12 h post-dose (AUC0-12) profiles (AUCf ) were collected from 20 subjects. Predicted tacrolimus AUC0-12 (AUCp) was calculated using the following: (i) 42 multiple regression-derived limited sampling strategies (LSSs); (ii) five population pharmacokinetic (PK) models in the Bayesian forecasting program TCIWorks; and (iii) a Web-based consultancy service. Correlations (r 2 ) between C0 and AUCf and between AUCp and AUCf were examined. Median percentage prediction error (MPPE) and median absolute percentage prediction error (MAPE) were calculated. RESULTSCorrelation between C0 and AUCf was 0.53. Using the 42 LSS equations, correlation between AUCp and AUCf ranged from 0.54 to 0.99. The MPPE and MAPE were <15% for 29 of 42 equations (62%), including five of eight equations based on sampling taken Յ2 h post-dose. Using the PK models in TCIWorks, AUCp derived from only C0 values showed poor correlation with AUCf (r 2 = 0.27-0.54) and unacceptable imprecision (MAPE 17.5-31.6%). In most cases, correlation, bias and imprecision estimates progressively improved with inclusion of a greater number of concentration time points. When concentration measurements at 0, 1, 2 and 4 h post-dose were applied, correlation between AUCp and AUCf ranged from 0.75 to 0.93, and MPPE and MAPE were <15% for all models examined. Using the Web-based consultancy service, correlation between AUCp and AUCf was 0.74, and MPPE and MAPE were 6.6 and 9.6%, respectively. CONCLUSIONSLimited sampling methods better predict tacrolimus exposure compared with C0 measurement. Several LSSs based on sampling taken 2 h or less post-dose predicted exposure with acceptable bias and imprecision. Generally, Bayesian forecasting methods required inclusion of a concentration measurement from >2 h post-dose to adequately predict exposure.
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