The effect of ABCB1 C3435T polymorphism on pharmacokinetics of tacrolimus in liver transplantation: A meta-analysis

Objectives

The effect of ABCB1 C3435T SNP on the pharmacokinetics of immunosuppressive drug tacrolimus in different studies was conflicting. So a meta-analysis was employed to study the correlation of ABCB1 C3435T SNP and the pharmacokinetics of tacrolimus at different post-transplantation times.

Method

Several studies about ABCB1 C3435T polymorphism and the pharmacokinetics of tacrolimus were collected through the search on PubMed and the Cochrane Library. After the extraction of pharmacokinetic parameters from these studies, a meta-analysis was performed on the software STATA version11.0.

Results

A total of 9 studies were adopted including 558 liver transplant recipients. For the dose of tacrolimus, the subjects with wild-type CC had a significantly higher tacrolimus dose than homozygous mutated genotype TT within 1 week (WMD = 0.01 (0.00, 0.02), P = 0.014) and the similar result in recipients with heterozygous CT compared with TT after transplantation for 1 month (WMD = 0.01 (0.00, 0.02), P = 0.002). For the tacrolimus concentration/dose ratio, subjects with CT had higher C/D ratio than those with CC and TT at different post-transplantation times. A subgroup analysis based on different ethnic populations was also carried out. Donors' genotypes were also considered in this meta-analysis.

Conclusion

Through this meta-analysis for the including studies about the pharmacokinetics of tacrolimus and ABCB1 C3435T SNP, several significant associations were obtained. Particularly, the Caucasians showed more significant associations between the C/D ratio and ABCB1 C3435T polymorphism; however, the correlations were not steady at different post-transplantation times.     

Protective effect of the KIR2DS1 gene in atopic dermatitis

Atopic dermatitis (AD) is a common skin disease of complex etiology including affected humoral and cellular immune responses. The role of NK cells in development of this disease has been recently postulated, but is still poorly documented. The current study was undertaken to determine the impact of genes for the most polymorphic NK cell receptors, known as killer cell immunoglobulin-like receptors (KIRs), on the development of AD.     

Genetic polymorphisms of CYP2E1 and DNA repair genes HOGG1 and XRCC1: Association with hepatitis B related advanced liver disease and cancer

A population based case–control study was designed to explore the genetic risk factors for hepatitis B virus (HBV) related liver disease susceptibility. A total of 424 subjects comprising 210 controls, 50 acute HBV (AVH), 84 chronic HBV (CHBV), 25 HBV related cirrhosis and 55 HBV related hepatocellular carcinoma (HCC) cases were included in the study. PCR-RFLP was used for the genotyping of Cyp2E1*5B, hOGG1 codon 326 and XRCC1 codon 399. Compared to controls, Cyp2E1 rsaI variant c2 genotype increased the risk of HBV related liver disease severity by 2.68 fold, the highest for HCC cases (3.981 folds, p = 0.106); and was associated with higher histology activity index (HAI) (p < 0.001) in CHBV patients. Cyp2E1 and hOGG1 variants were independently associated with a significantly higher fibrosis score in CHBV group. Analysis of gene–gene interaction studies showed an increased risk of HCC, cirrhosis and CHBV in a Cyp2E1 variant + XRCC1 variant combination (p < 0.001); and hOGG1 variants + XRCC1 variants. A mutually independent heterozygous hOGG1 and XRCC1 combination resulted in a decreased risk of HBV related liver disease. On the other hand, a wild-type hOGG1 and XRCC1 combination was associated with a significantly higher risk of AVH (p = 0.010) but a lower risk of CHBV (p = 0.032) and HCC (p = 0.006). The gene–gene interactions were also associated with a significant increase in HAI and fibrosis score in CHBV patients. Cyp2E1, hOGG1 and XRCC1 genotypes significantly alter the risk of HBV related liver disease susceptibility and severity, independently or through gene–gene interaction.     

Computation of Time-Specified Tolerance Intervals for Hybrid Time Series with Nonequidistant Sampling,Illustrated for Plasma Growth Hormone

The ideal reference interval for a variable of clinical interest would be specific for all deterministic factors affecting that variable, including the time of sampling in relation to biological rhythms. In particular, growth hormone is characterized in children by circadian and ultradian variability, with high peaks of secretion occurring mainly during sleep. For clinical applications, the use of tolerance intervals has been recommended, and they should substitute, whenever possible, for prediction limits. In the case of hybrid data (time series of data collected from a group of subjects), such a tolerance interval could be very difficult to determine following a parametric approach similar to the procedure used for the computation of prediction intervals, especially when consideration of both within-subjects and among-subjects variances is wanted. Accordingly, we have developed a nonparametric method for the computation of such tolerance intervals. Because the method is based on bootstrap techniques, it does not require the assumption of normality or symmetry in the data and is also more appropriate when dealing with small samples. The method was used to establish time-qualified reference limits for a series of growth hormone sampled around the clock in groups of prepubertal children differentiated according to stature. The use of these tolerance intervals may eliminate many false-positive and false-negative diagnoses that might be obtained when relying on time-unspecified single samples. The provision of such tolerance limits introduces time-specification and time-structure evaluation into prevention, diagnosis, and treatment of growth disorders. (Chronobiology International, 14(4), 409–425, 1997)     

Analysis of normal levels of free glycosaminoglycans in urine and plasma in adults

Plasma and urine glycosaminoglycans (GAGs) are long, linear sulfated polysaccharides that have been proposed as potential noninvasive biomarkers for several diseases. However, owing to the analytical complexity associated with the measurement of GAG concentration and disaccharide composition (the so-called GAGome), a reference study of the normal healthy GAGome is currently missing. Here, we prospectively enrolled 308 healthy adults and analyzed their free GAGomes in urine and plasma using a standardized ultra-high-performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry method together with comprehensive demographic and blood chemistry biomarker data. Of 25 blood chemistry biomarkers, we mainly observed weak correlations between the free GAGome and creatinine in urine and hemoglobin or erythrocyte counts in plasma. We found a higher free GAGome concentration – but not a more diverse composition - in males. Partitioned by gender, we also established reference intervals for all detectable free GAGome features in urine and plasma. Finally, we carried out a transference analysis in healthy individuals from two distinct geographical sites, including data from the Lifelines Cohort Study, which validated the reference intervals in urine. Our study is the first large-scale determination of normal free GAGomes reference intervals in plasma and urine and represents a critical resource for future physiology and biomarker research.     

Dynamics of EEG potentials at the beginning of a series of EEG-feedback sessions

We studied changes in the amplitudes of event-related EEG potentials (ERPs) and power spectra of background EEG in the course of a series of EEG-feedback sessions directed toward an increase in the ratio of powers of the α vs θ rhythms. The examined group included 70 volunteers divided into an experimental group (n = 37) and a control group (n = 33). The intensity of acoustic white noise overlapping the musical background served as a feedback signal; it became lower with increase in the above ratio, while in the control group it remained constant. The EEG potentials were recorded from C3 and C4 leads. The ERPs were recorded within a paradigm of measuring time intervals. Within a series of EEG-feedback sessions, the α/θ ratio decreased somewhat both in the control and experimental groups, but in subjects of the latter group this decrease was less significant, and the mean intragroup index became significantly greater than the respective value in the control group after the end of the third session. The EEG-feedback sessions also resulted in significant increases in the amplitudes of early components of the readiness potential in both hemispheres and in the amplitude of the contingent negative variation in the right hemisphere. We conclude that, in most healthy subjects, at least three sessions of α/θ training are necessary to form an effective series providing considerable changes in the pattern of EEG potentials. Neirofiziologiya/Neurophysiology, Vol. 39, No. 1, pp. 88–98, January–February, 2007.     

A class of latent Markov models for capture-recapture data allowing for time, heterogeneity, and behavior effects

We propose an extension of the latent class model for the analysis of capture-recapture data which allows us to take into account the effect of a capture on the behavior of a subject with respect to future captures. The approach is based on the assumption that the variable indexing the latent class of a subject follows a Markov chain with transition probabilities depending on the previous capture history. Several constraints are allowed on these transition probabilities and on the parameters of the conditional distribution of the capture configuration given the latent process. We also allow for the presence of discrete explanatory variables, which may affect the parameters of the latent process. To estimate the resulting models, we rely on the conditional maximum likelihood approach and for this aim we outline an EM algorithm. We also give some simple rules for point and interval estimation of the population size. The approach is illustrated by applying it to two data sets concerning small mammal populations.     

Rice reproductive development stage thermal time and calendar day intervals for six US rice cultivars in the Grand Prairie,Arkansas, over 4 years

The rice crop's reproductive developmental timing in days and thermal time is needed for effective modelling, research interpretation and management of the crop. To obtain these data, a field study was conducted at Stuttgart, Arkansas, USA in 2007, 2008, 2009 and 2010. The study utilised data collected from randomised complete block design field experiments with three replications and six rice lines in each of the years. Averaged across years and cultivars, the degree‐day‐10 (DD10) intervals (thermal time units with a base temperature of 10°C) for Reproductive Stages R3, R4, R5, R6, R7 and R8 were 21, 30, 19, 48, 70 and 189°C‐day, respectively. The average intervals in calendar days for R3, R4, R5, R6, R7 and R8 were 2.3, 3.3, 2.3, 6.0, 4.5 and 26.7 days, respectively. For R4 and R5, cultivar rankings differed over the 4 years with cultivar differences being mostly small, non‐significant or inconsistent. For R6, the cultivar Cypress had either the longest or among the longest intervals. For R7, the medium grains had the longest or among the longest intervals. For R3 and R8, cultivar differences were significant with no significant year by cultivar interactions. For the R3 intervals, the primary difference was between Bengal and the five other lines. For R8, the intervals in both days and DD10 were least for Cypress, followed by Wells, followed by LaGrue and XL723 followed by the medium grains Bengal and Jupiter which had the longest intervals for R8. Consequently, the R3 interval could be generalised to five of the six lines in the study while R4, R5, R6 and R7 intervals could be generally applied with some caution. The R8 intervals were different among lines and grain types. These differences should not be ignored. The extremely short R8 interval for Cypress is likely associated with its high head rice yields across a range of environments compared to other long‐grain rice cultivars and hybrids in the USA The utilisation of the rice reproductive growth stage intervals can potentially improve analysis and interpretation of field plot research, model predictions and management of the rice crop.     

Assessment of clinical outcomes in breast cancer patients treated with taxanes: multi-analytical approach

Polymorphisms in genes encoding CYPs (Phase I) and ABCB1 (Phase III) enzymes may attribute to variability of efficacy of taxanes. The present study aims to find the influence of CYP and ABCB1 gene polymorphisms on taxanes based clinical outcomes. 132 breast cancer patients treated with taxanes based chemotherapy were genotyped for CYP3A4*1B, CYP3A5*3, CYP1B1*3, CYP2C8*3, ABCB1 1236C>T, 2677G>T/A and 3435C>T polymorphisms using PCR-RFLP. Associations of genetic variants with clinical outcomes in terms of response in 58 patients receiving neo-adjuvant chemotherapy (NACT), and chemo-toxicity in 132 patients were studied. Multifactor dimensionality reduction (MDR) analysis was performed to evaluate higher order gene–gene interactions with clinical outcomes. Pathological response to taxane based NACT was associated with GA genotype as well as A allele of CYP3A5*3 polymorphism (P_corr = 0.0465, P_corr = 0.0465). Similarly, association was found in dominant model of CYP3A5*3 polymorphism with responders (P_corr = 0.0465). Haplotype analysis further revealed A_CYP3A4–A_CYP3A5 haplotype to be significantly associated with responders (P_corr = 0.048). In assessing toxicity, significant association of variant (TT) genotype and T allele of ABCB1 2677G>T/A polymorphism, was found with ‘grade 1 or no leucopenia’ (P_corr = 0.0465, P_corr = 0.048). On evaluating higher order gene–gene interaction models by MDR analysis, CYP3A5*3; ABCB11236C>T and ABCB1 2677G>T/A; ABCB1 3435C>T and CYP1B1*3 showed significant association with treatment response, grade 2–4 anemia and dose delay/reduction due to neutropenia (P = 0.024, P = 0.004, P = 0.026), respectively. Multi-analytical approaches may provide a better assessment of pharmacogenetic based treatment outcomes in breast cancer patients treated with taxanes.