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. 2010 Nov;20(11):665-76.
doi: 10.1097/FPC.0b013e32833f2cd0.

Generation of novel pharmacogenomic candidates in response to methotrexate in juvenile idiopathic arthritis: correlation between gene expression and genotype

Halima Moncrieffe  1 , Anne Hinks, Simona Ursu, Laura Kassoumeri, Angela Etheridge, Mike Hubank, Paul Martin, Tracey Weiler, David N Glass, Susan D Thompson, Wendy Thomson, Lucy R Wedderburn
Affiliations

Generation of novel pharmacogenomic candidates in response to methotrexate in juvenile idiopathic arthritis: correlation between gene expression and genotype

Halima Moncrieffe et al. Pharmacogenet Genomics. 2010 Nov.

Abstract

Objectives: Little is known about the mechanisms of efficacy of methotrexate (MTX) in childhood arthritis, or genetic influences upon response to MTX. The aims of this study were to use gene expression profiling to identify novel pathways/genes altered by MTX and then investigate these genes for genotype associations with response to MTX treatment.

Methods: Gene expression profiling before and after MTX treatment was performed on 11 children with juvenile idiopathic arthritis (JIA) treated with MTX, in whom response at 6 months of treatment was defined. Genes showing the most differential gene expression after the treatment were selected for single nucleotide polymorphism (SNP) genotyping. Genotype frequencies were compared between nonresponders and responders (ACR-Ped70). An independent cohort was available for validation.

Results: Gene expression profiling before and after MTX treatment revealed 1222 differentially expressed probes sets (fold change >1.7, P<0.05) and 1065 when restricted to full responder cases only. Six highly differentially expressed genes were analyzed for genetic association in response to MTX. Three SNPs in the SLC16A7 gene showed significant association with MTX response. One SNP showed validated association in an independent cohort.

Conclusion: This study is the first, to our knowledge, to evaluate gene expression profiles in children with JIA before and after MTX, and to analyze genetic variation in differentially expressed genes. We have identified a gene, which may contribute to genetic variability in MTX response in JIA, and established as proof of principle that genes that are differentially expressed at mRNA level after drug administration may also be good candidates for genetic analysis.

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Conflict of interest statement

Conflicts of Interest: NONE

Figures

Figure 1
Figure 1. Gene expression changes in JIA patients with ‘best response’ after MTX, each compared to before starting MTX
Heat map contains probe sets (n=87) that are 1.7-fold differentially expressed at a significance of p < 0.05 by the Student's t-test with Welch's correction and after Benjamini-Hochberg correction. Each row represents a probeset and each column represents a patient, either before or after MTX as shown. The normalized expression level for each probe set is indicated by colour with red and blue reflecting higher or lower expression levels as shown.
Figure 2
Figure 2. mRNA expression by QPCR of the 6 genes selected for genotyping in ‘best’ responder JIA patients, comparing before and after MTX treatment
Bars show mean expression levels relative to beta2 microglobulin (B2M) gene expression, pre- (white bars) and post- (black bars) MTX; error bars indicate 1 standard error of the mean. Significant differences (p < 0.05) between pre- and post- MTX are indicated by *.
Figure 3
Figure 3. Linkage disequilibrium plot for SNPs across the SLC16A7 gene using Haploview version 4.1, showing LD block around the associated SNPs
Significant SNPs highlighted in black boxes. Pairwise LD calculated using D', with the coloured squares showing the strength of LD, with red denoting high LD, blue moderate LD and white low LD. The numbers in the block denotes LD calculated using r2.
Figure 4
Figure 4. Meta-analysis of rs3763980 in UK CHARMS dataset and US dataset
Forest plot displaying odds ratios (OR) and 95% confidence intervals for each of the two studies (US, UK) and the weighting for each study according to sample size. The combined OR (1.89) from the two studies is displayed as a diamond with the peaks denoting the upper and lower limits of the confidence intervals (1.26 – 2.85). The combined p-value for association of the A allele with non-responder status was 0.002. The Breslow-Day test was performed to test for heterogeneity between the two studies, and showed no evidence of heterogeneity (p=0.87).
Figure 5
Figure 5. SLC16A7 gene expression by genotype of rs3763980
Gene expression levels in B cells from 195 healthy individuals was plotted by genotype at the rs3763980 SNP in the SLC16A7 gene. Data obtained from reference 46. The box and whisker plot shows the correlation of genotype at rs3763980 with normalized log2 quantitative gene expression of SLC16A7.
See this image and copyright information in PMC

References

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