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- DOI: 10.1136/annrheumdis-2012-202405
- PMID: 23233654
- UKPMCID: 23233654
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Genome-wide association analysis of anti-TNF drug response in patients with rheumatoid arthritis.
Umicevic Mirkov, Masa; Cui, Jing; Vermeulen, Sita H; Stahl, Eli A; Toonen, Erik J M; Makkinje, Remco R; Lee, Annette T; Huizinga, Tom W J; Allaart, Renee; Barton, Anne; Mariette, Xavier; Miceli, Corinne Richard; Criswell, Lindsey A; Tak, Paul P; de Vries, Niek; Saevarsdottir, Saedis; Padyukov, Leonid; Bridges, S Louis; van Schaardenburg, Dirk-Jan; Jansen, Tim L; Dutmer, Ellen A J; van de Laar, Mart A F J; Barrera, Pilar; Radstake, Timothy R D J; van Riel, Piet L C M; Scheffer, Hans; Franke, Barbara; Brunner, Han G; Plenge, Robert M; Gregersen, Peter K; Guchelaar, Henk-Jan; Coenen, Marieke J H
Annals of the rheumatic diseases. 2013;72(8):1375-1381.
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Full-text held externally
- DOI: 10.1136/annrheumdis-2012-202405
- PMID: 23233654
- UKPMCID: 23233654
Abstract
BACKGROUND: Treatment strategies blocking tumour necrosis factor (anti-TNF) have proven very successful in patients with rheumatoid arthritis (RA). However, a significant subset of patients does not respond for unknown reasons. Currently, there are no means of identifying these patients before treatment. This study was aimed at identifying genetic factors predicting anti-TNF treatment outcome in patients with RA using a genome-wide association approach. METHODS: We conducted a multistage, genome-wide association study with a primary analysis of 2 557 253 single-nucleotide polymorphisms (SNPs) in 882 patients with RA receiving anti-TNF therapy included through the Dutch Rheumatoid Arthritis Monitoring (DREAM) registry and the database of Apotheekzorg. Linear regression analysis of changes in the Disease Activity Score in 28 joints after 14 weeks of treatment was performed using an additive model. Markers with p<10(-3) were selected for replication in 1821 patients from three independent cohorts. Pathway analysis including all SNPs with p<10(-3) was performed using Ingenuity. RESULTS: 772 markers showed evidence of association with treatment outcome in the initial stage. Eight genetic loci showed improved p value in the overall meta-analysis compared with the first stage, three of which (rs1568885, rs1813443 and rs4411591) showed directional consistency over all four cohorts studied. We were unable to replicate markers previously reported to be associated with anti-TNF outcome. Network analysis indicated strong involvement of biological processes underlying inflammatory response and cell morphology. CONCLUSIONS: Using a multistage strategy, we have identified eight genetic loci associated with response to anti-TNF treatment. Further studies are required to validate these findings in additional patient collections.
Bibliographic metadata
- Umicevic Mirkov, Masa
- Cui, Jing
- Vermeulen, Sita H
- Stahl, Eli A
- Toonen, Erik J M
- Makkinje, Remco R
- Lee, Annette T
- Huizinga, Tom W J
- Allaart, Renee
- Barton, Anne
- Mariette, Xavier
- Miceli, Corinne Richard
- Criswell, Lindsey A
- Tak, Paul P
- de Vries, Niek
- Saevarsdottir, Saedis
- Padyukov, Leonid
- Bridges, S Louis
- van Schaardenburg, Dirk-Jan
- Jansen, Tim L
- Dutmer, Ellen A J
- van de Laar, Mart A F J
- Barrera, Pilar
- Radstake, Timothy R D J
- van Riel, Piet L C M
- Scheffer, Hans
- Franke, Barbara
- Brunner, Han G
- Plenge, Robert M
- Gregersen, Peter K
- Guchelaar, Henk-Jan
- Coenen, Marieke J H