Dataset Information

SLCO1B1 Variants and Methotrexate Clearance

ABSTRACT:

Methotrexate plasma concentration is related to its clinical effects. To identify the genetic basis of interindividual variability in methotrexate pharmacokinetics in children with newly diagnosed acute lymphoblastic leukemia (ALL), we performed a genome-wide analysis (GWAS) of 500,568 germline single-nucleotide polymorphisms (SNPs) in 434 children with ALL who received 3,014 courses of methotrexate at 2 to 5 g/m2. SNPs were validated in an independent cohort of 206 patients. Adjusting for age, race, sex, and methotrexate regimen, the most significant associations were with SNPs in the organic anion transporter polypeptide, SLCO1B1 (rs11045879 (P = 1.7 x 10^-10) and rs4149081 (P = 1.7 x 10^-9) (Trevino et al, PMID: 19901119). To test whether rare variants in SLCO1B1 could alter its function, we genotyped SLCO1B1 exons in a slightly larger group of 699 children with ALL who received methotrexate and identified 93 single nucleotide polymorphisms (SNPs). We found several common and rare non-synonymous (NS) SNPs associated with methotrexate clearance.

NS SNPs predicted to be functionally damaging (common or rare) were more likely to be found among patients with the lowest adjusted methotrexate clearance (lowest 10%) than patients with high clearance (highest 10%). Four SLCO1B1 haplotypes were associated with reduced methotrexate clearance and we verified that these haplotypes have lower function with in vitro transport assays. We were able to quantitatively account for a third of the population variability in clearance of methotrexate with clinical and genetic covariates. This data set includes the dependent variable of methotrexate clearance and all of the SNP data available from arrays, sequencing, and genotyping.

PROVIDER: phs000426.v1.p1 | EGA |

REPOSITORIES: EGA

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Publications

Polymorphisms of the SLCO1B1 gene predict methotrexate-related toxicity in childhood acute lymphoblastic leukemia.

Lopez-Lopez Elixabet E Martin-Guerrero Idoia I Ballesteros Javier J Piñan M Angeles MA Garcia-Miguel Purificacion P Navajas Aurora A Garcia-Orad Africa A

Pediatric blood & cancer 20110308 4

<h4>Background</h4>Methotrexate (MTX) is an important component of the therapy for childhood acute lymphoblastic leukemia. Treatment with high-dose MTX often causes toxicity, recommending a dose reduction and/or cessation of treatment. Polymorphisms in genes involved in the MTX metabolism have been associated with toxicity with controversial results. The discrepancies could be due to differences in treatment protocols among studies, small, or non-homogeneous populations or the use of different t ...[more]

PMID: 21387541

Publication: 1/4

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Project description:This a model from the article: Population-based analysis of methadone distribution and metabolism using an age-dependent physiologically based pharmacokinetic model. Yang F, Tong X, McCarver DG, Hines RN, Beard DA. J Pharmacokinet Pharmacodyn 2006 Aug;33(4):485-518 16758333 , Abstract: Limited pharmacokinetic (PK) and pharmacodynamic (PD) data are available to use in methadone dosing recommendations in pediatric patients for either opioid abstinence or analgesia. Considering the extreme inter-individual variability of absorption and metabolism of methadone, population-based PK would be useful to provide insight into the relationship between dose, blood concentrations, and clinical effects of methadone. To address this need, an age-dependent physiologically based pharmacokinetic (PBPK) model has been constructed to systematically study methadone metabolism and PK. The model will facilitate the design of cost-effective studies that will evaluate methadone PK and PD relationships, and may be useful to guide methadone dosing in children. The PBPK model, which includes whole-body multi-organ distribution, plasma protein binding, metabolism, and clearance, is parameterized based on a database of pediatric PK parameters and data collected from clinical experiments. The model is further tailored and verified based on PK data from individual adults, then scaled appropriately to apply to children aged 0-24 months. Based on measured variability in CYP3A enzyme expression levels and plasma orosomucoid (ORM2) concentrations, a Monte-Carlo-based simulation of methadone kinetics in a pediatric population was performed. The simulation predicts extreme variability in plasma concentrations and clearance kinetics for methadone in the pediatric population, based on standard dosing protocols. In addition, it is shown that when doses are designed for individuals based on prior protein expression information, inter-individual variability in methadone kinetics may be greatly reduced. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Yang F, Tong X, McCarver DG, Hines RN, Beard DA. (2006) - version=1.0 The original CellML model was created by: Catherine Lloyd c.lloyd@auckland.ac.nz The University of Auckland This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Project description:Introduction: Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism. Methods: We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in-silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analysed in-vitro and in-vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2754 carriers. Results: We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterised three cis-regulatory SNPs located at the promoter and two intronic regulatory elements, which affect the binding of the transcription factors C/EBPα, HMGA1, DBP and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele HR=0.85, 95%CI=0.72-1.00, P-trend=0.048). Conclusion: Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2, which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele. Total gene expression of normal breast sample from healthy controls. This submission represents transcriptome component of study.

Project description:Introduction: Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism. Methods: We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in-silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analysed in-vitro and in-vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2754 carriers. Results: We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterised three cis-regulatory SNPs located at the promoter and two intronic regulatory elements, which affect the binding of the transcription factors C/EBPα, HMGA1, DBP and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele HR=0.85, 95%CI=0.72-1.00, P-trend=0.048). Conclusion: Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2, which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele. Genotype of normal breast sample from healthy controls.

Dataset Information

SLCO1B1 Variants and Methotrexate Clearance

Publications

Polymorphisms of the SLCO1B1 gene predict methotrexate-related toxicity in childhood acute lymphoblastic leukemia.

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