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.
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.
Authors: Thomas A Griffin; Michael G Barnes; Norman T Ilowite; Judyann C Olson; David D Sherry; Beth S Gottlieb; Bruce J Aronow; Paul Pavlidis; Claas H Hinze; Sherry Thornton; Susan D Thompson; Alexei A Grom; Robert A Colbert; David N Glass Journal: Arthritis Rheum Date: 2009-07
Authors: T M Williams; D Moolten; J Burlein; J Romano; R Bhaerman; A Godillot; M Mellon; F J Rauscher; J A Kant Journal: Science Date: 1991-12-20 Impact factor: 47.728
Authors: Nicolino Ruperto; Kevin J Murray; Valeria Gerloni; Nico Wulffraat; Sheila Knupp Feitosa de Oliveira; Fernanda Falcini; Pavla Dolezalova; Maria Alessio; Ruben Burgos-Vargas; Fabrizia Corona; Richard Vesely; Helen Foster; Joyce Davidson; Francesco Zulian; Line Asplin; Eileen Baildam; Julia Garcia Consuegra; Huri Ozdogan; Rotraud Saurenmann; Rik Joos; Angela Pistorio; Pat Woo; Alberto Martini Journal: Arthritis Rheum Date: 2004-07
Authors: Stephan Sauer; Ludovica Bruno; Arnulf Hertweck; David Finlay; Marion Leleu; Mikhail Spivakov; Zachary A Knight; Bradley S Cobb; Doreen Cantrell; Eric O'Connor; Kevan M Shokat; Amanda G Fisher; Matthias Merkenschlager Journal: Proc Natl Acad Sci U S A Date: 2008-05-28 Impact factor: 11.205
Authors: Ivan P Gorlov; Gary E Gallick; Olga Y Gorlova; Christopher Amos; Christopher J Logothetis Journal: PLoS One Date: 2009-08-04 Impact factor: 3.240
Authors: Anne Hinks; Joanna Cobb; Miranda C Marion; Sampath Prahalad; Marc Sudman; John Bowes; Paul Martin; Mary E Comeau; Satria Sajuthi; Robert Andrews; Milton Brown; Wei-Min Chen; Patrick Concannon; Panos Deloukas; Sarah Edkins; Stephen Eyre; Patrick M Gaffney; Stephen L Guthery; Joel M Guthridge; Sarah E Hunt; Judith A James; Mehdi Keddache; Kathy L Moser; Peter A Nigrovic; Suna Onengut-Gumuscu; Mitchell L Onslow; Carlos D Rosé; Stephen S Rich; Kathryn J A Steel; Edward K Wakeland; Carol A Wallace; Lucy R Wedderburn; Patricia Woo; John F Bohnsack; Johannes Peter Haas; David N Glass; Carl D Langefeld; Wendy Thomson; Susan D Thompson Journal: Nat Genet Date: 2013-04-21 Impact factor: 38.330
Authors: J Cobb; E Cule; H Moncrieffe; A Hinks; S Ursu; F Patrick; L Kassoumeri; E Flynn; M Bulatović; N Wulffraat; B van Zelst; R de Jonge; M Bohm; P Dolezalova; S Hirani; S Newman; P Whitworth; T R Southwood; M De Iorio; L R Wedderburn; W Thomson Journal: Pharmacogenomics J Date: 2014-04-08 Impact factor: 3.550