Meta-analysis of gene expression profiles to predict response to biologic agents in rheumatoid arthritis
- Authors
- Lee, Young Ho; Bae, Sang-Cheol; Song, Gwan Gyu
- Issue Date
- 6월-2014
- Publisher
- SPRINGER LONDON LTD
- Keywords
- Biologic agent; Gene expression; Meta-analysis; Response; Rheumatoid arthritis
- Citation
- CLINICAL RHEUMATOLOGY, v.33, no.6, pp.775 - 782
- Indexed
- SCIE
SCOPUS
- Journal Title
- CLINICAL RHEUMATOLOGY
- Volume
- 33
- Number
- 6
- Start Page
- 775
- End Page
- 782
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/98407
- DOI
- 10.1007/s10067-014-2547-9
- ISSN
- 0770-3198
- Abstract
- Our aim was to identify differentially expressed (DE) genes and biological processes that may help predict patient response to biologic agents for rheumatoid arthritis (RA). Using the INMEX (integrative meta-analysis of expression data) software tool, we performed a meta-analysis of publicly available microarray Gene Expression Omnibus (GEO) datasets that examined patient response to biologic therapy for RA. Three GEO datasets, containing 79 responders and 34 non-responders, were included in the metaanalysis. We identified 1,374 genes that were consistently differentially expressed in responders vs. non-responders (651 up-regulated and 723 down-regulated). The upregulated gene with the smallest p value (p=0.000192) was ASCC2 (Activating Signal Cointegrator 1 Complex Subunit 2), and the up-regulated gene with the largest fold change (average log fold change=-0.75869, p=0.000206) was KLRC3 (Killer Cell Lectin-Like Receptor Subfamily C, Member 3). The down-regulated gene with the smallest p value (p=0.000195) was MPL (Myeloproliferative Leukemia Virus Oncogene). Among the 236 GO terms associated with the set of DE genes, the most significantly enriched was "CTP biosynthetic process" (GO:0006241; p=0.000454). Our meta-analysis identified genes that were consistently DE in responders vs. non-responders, as well as biological pathways associated with this set of genes. These results provide insight into the molecular mechanisms underlying responsiveness to biologic therapy for RA.
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Collections - College of Medicine > Department of Medical Science > 1. Journal Articles
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