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Arthritis Research & Therapy
Published in: Arthritis Research & Therapy 1/2015

Open Access 01-12-2015 | Research article

PTGER4 gene variant rs76523431 is a candidate risk factor for radiological joint damage in rheumatoid arthritis patients: a genetic study of six cohorts

Authors: Luis Rodriguez-Rodriguez, Jose Ivorra-Cortes, F. David Carmona, Javier Martín, Alejandro Balsa, Hanna W. van Steenbergen, Annette H. M. van der Helm-van Mil, Isidoro González-Álvaro, Benjamín Fernandez-Gutiérrez

Published in: Arthritis Research & Therapy | Issue 1/2015

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Abstract

Introduction

Prostaglandin E receptor 4 (PTGER4) is implicated in immune regulation and bone metabolism. The aim of this study was to analyze its role in radiological joint damage in rheumatoid arthritis (RA).

Methods

Six independent cohorts of patients with RA of European or North American descent were included, comprising 1789 patients with 5083 sets of X-rays. The Hospital Clínico San Carlos Rheumatoid Arthritis, Princesa Early Arthritis Register Longitudinal study, and Hospital Universitario de La Paz early arthritis (Spain) cohorts were used as discovery cohorts, and the Leiden Early Arthritis Clinic (The Netherlands), Wichita (United States), and National Databank for Rheumatic Diseases (United States and Canada) cohorts as replication cohorts. First, the PTGER4 rs6896969 single-nucleotide polymorphism (SNP) was genotyped using TaqMan assays and available Illumina Immunochip data and studied in the discovery and replication cohorts. Second, the PTGER4 gene and adjacent regions were analyzed using Immunochip genotyping data in the discovery cohorts. On the basis of pooled p values, linkage disequilibrium structure of the region, and location in regions with transcriptional properties, SNPs were selected for replication. The results from discovery, replication, and overall cohorts were pooled using inverse-variance–weighted meta-analysis. Influence of the polymorphisms on the overall radiological damage (constant effect) and on damage progression over time (time-varying effect) was analyzed.

Results

The rs6896969 polymorphism showed a significant association with radiological damage in the constant effect pooled analysis of the discovery cohorts, although no significant association was observed in the replication cohorts or the overall pooled analysis. Regarding the analysis of the PTGER4 region, 976 variants were analyzed in the discovery cohorts. From the constant and time-varying effect analyses, 12 and 20 SNPs, respectively, were selected for replication. Only the rs76523431 variant showed a significant association with radiographic progression in the time-varying effect pooled analysis of the discovery, replication, and overall cohorts. The overall pooled effect size was 1.10 (95 % confidence interval 1.05–1.14, p = 2.10 × 10−5), meaning that radiographic yearly progression was 10 % greater for each copy of the minor allele.

Conclusions

The PTGER4 gene is a candidate risk factor for radiological progression in RA.
Appendix
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Literature
1.
Morel J, Combe B. How to predict prognosis in early rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2005;19:137–46.CrossRefPubMed
2.
Radner H, Smolen JS, Aletaha D. Comorbidity affects all domains of physical function and quality of life in patients with rheumatoid arthritis. Rheumatology (Oxford). 2011;50:381–8.CrossRef
3.
van Nies JAB, Krabben A, Schoones JW, Huizinga TWJ, Kloppenburg M, van der Helm-van Mil AHM. What is the evidence for the presence of a therapeutic window of opportunity in rheumatoid arthritis? A systematic literature review. Ann Rheum Dis. 2014;73:861–70.CrossRefPubMed
4.
Inoue H, Takamori M, Shimoyama Y, Ishibashi H, Yamamoto S, Koshihara Y. Regulation by PGE2 of the production of interleukin-6, macrophage colony stimulating factor, and vascular endothelial growth factor in human synovial fibroblasts. Br J Pharmacol. 2002;136:287–95.PubMedCentralCrossRefPubMed
5.
Honda T, Segi-Nishida E, Miyachi Y, Narumiya S. Prostacyclin-IP signaling and prostaglandin E2-EP2/EP4 signaling both mediate joint inflammation in mouse collagen-induced arthritis. J Exp Med. 2006;203:325–35.PubMedCentralCrossRefPubMed
6.
Sheibanie AF, Yen JH, Khayrullina T, Emig F, Zhang M, Tuma R, et al. The proinflammatory effect of prostaglandin E2 in experimental inflammatory bowel disease is mediated through the IL-23 → IL-17 axis. J Immunol. 2007;178:8138–47.CrossRefPubMed
7.
Yao C, Sakata D, Esaki Y, Li Y. Prostaglandin E2–EP4 signaling promotes immune inflammation through TH1 cell differentiation and TH17 cell expansion. Nat Med. 2009;15:633–40.CrossRefPubMed
8.
Chen Q, Muramoto K, Masaaki N, Ding Y, Yang H, Mackey M, et al. A novel antagonist of the prostaglandin E2 EP4 receptor inhibits Th1 differentiation and Th17 expansion and is orally active in arthritis models. Br J Pharmacol. 2010;160:292–310.PubMedCentralCrossRefPubMed
9.
Evans DM, Spencer CCA, Pointon JJ, Su Z, Harvey D, Kochan G, et al. Interaction between ERAP1 and HLA-B27 in ankylosing spondylitis implicates peptide handling in the mechanism for HLA-B27 in disease susceptibility. Nat Genet. 2011;43:761–7.PubMedCentralCrossRefPubMed
10.
11.
Yoshida K, Oida H, Kobayashi T, Maruyama T, Tanaka M, Katayama T, et al. Stimulation of bone formation and prevention of bone loss by prostaglandin E EP4 receptor activation. Proc Natl Acad Sci U S A. 2002;99:4580–5.PubMedCentralCrossRefPubMed
12.
Ono K, Akatsu T, Kugai N, Pilbeam CC, Raisz LG. The effect of deletion of cyclooxygenase-2, prostaglandin receptor EP2, or EP4 in bone marrow cells on osteoclasts induced by mouse mammary cancer cell lines. Bone. 2003;33:798–804.CrossRefPubMed
13.
Li X, Okada Y, Pilbeam CC, Lorenzo JA, Kennedy CR, Breyer RM, et al. Knockout of the murine prostaglandin EP2 receptor impairs osteoclastogenesis in vitro. Endocrinology. 2000;141:2054–61.PubMed
14.
Yoshida T, Horiuchi T, Sakamoto H, Inoue H, Takayanagi H, Nishikawa T, et al. Production of parathyroid hormone-related peptide by synovial fibroblasts in human osteoarthritis. FEBS Lett. 1998;433:331–4.CrossRefPubMed
15.
16.
De Jager PL, Jia X, Wang J, de Bakker PIW, Ottoboni L, Aggarwal NT, et al. Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci. Nat Genet. 2009;41:776–82.PubMedCentralCrossRefPubMed
17.
Arnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF, Cooper NS, et al. The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum. 1988;31:315–24.CrossRefPubMed
18.
Rodriguez-Rodriguez L, Jover-Jover JA, Fontsere O, Peña-Blanco RC, León L, Fernández-Gutierrez B, et al. Leflunomide discontinuation in rheumatoid arthritis and influence of associated disease-modifying anti-rheumatic drugs: a survival analysis. Scand J Rheumatol. 2013;42:433–6.CrossRefPubMed
19.
González-Álvaro I, Ortiz AM, Alvaro-Gracia JM, Castañeda S, Díaz-Sánchez B, Carvajal I, et al. Interleukin 15 levels in serum may predict a severe disease course in patients with early arthritis. PLoS One. 2011;6:e29492.PubMedCentralCrossRefPubMed
20.
Richi P, Balsa A, Muñoz-Fernández S, Villaverde V, Fernández-Prada M, Vicario JL, et al. Factors related to radiological damage in 61 Spaniards with early rheumatoid arthritis. Ann Rheum Dis. 2002;61:270–2.PubMedCentralCrossRefPubMed
21.
de Rooy DPC, van der Linden MPM, Knevel R, Huizinga TWJ, van der Helm-van Mil AHM. Predicting arthritis outcomes—what can be learned from the Leiden Early Arthritis Clinic? Rheumatology (Oxford). 2011;50:93–100.CrossRef
22.
Choi HK, Hernán MA, Seeger JD, Robins JM, Wolfe F. Methotrexate and mortality in patients with rheumatoid arthritis: a prospective study. Lancet. 2002;359:1173–7.CrossRefPubMed
23.
Wolfe F, Michaud K. The National Data Bank for rheumatic diseases: a multi-registry rheumatic disease data bank. Rheumatology (Oxford). 2011;50:16–24.CrossRef
24.
25.
de Rooy DPC, Zhernakova A, Tsonaka R, Willemze A, Kurreeman BAS, Trynka G, et al. A genetic variant in the region of MMP-9 is associated with serum levels and progression of joint damage in rheumatoid arthritis. Ann Rheum Dis. 2014;73:1163–9.CrossRefPubMed
26.
Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 2012;22:1790–7.PubMedCentralCrossRefPubMed
27.
Westra HJ, Peters MJ, Esko T, Yaghootkar H, Schurmann C, Kettunen J, et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat Genet. 2013;45:1238–43.PubMedCentralCrossRefPubMed
28.
van der Helm-van Mil AHM, Knevel R, van der Heijde D, Huizinga TWJ. How to avoid phenotypic misclassification in using joint destruction as an outcome measure for rheumatoid arthritis? Rheumatology (Oxford). 2010;49:1429–35.CrossRef
29.
Knevel R, Tsonaka R, le Cessie S, van der Linden MPM, Huizinga TWJ, van der Heijde DMFM, et al. Comparison of methodologies for analysing the progression of joint destruction in rheumatoid arthritis. Scand J Rheumatol. 2013;42:182–9.CrossRefPubMed
30.
Strand V, Landéwé R, van der Heijde D. Using estimated yearly progression rates to compare radiographic data across recent randomised controlled trials in rheumatoid arthritis. Ann Rheum Dis. 2002;61 Suppl 2:ii64–6.PubMedCentralCrossRefPubMed
31.
32.
Noack M, Miossec P. Th17 and regulatory T cell balance in autoimmune and inflammatory diseases. Autoimmun Rev. 2014;13:668–77.CrossRefPubMed
33.
Chai W, Lian Z, Chen C, Liu J, Shi LL, Wang Y. JARID1A, JMY, and PTGER4 polymorphisms are related to ankylosing spondylitis in Chinese Han patients: a case-control study. PLoS One. 2013;8:e74794.PubMedCentralCrossRefPubMed
34.
Jostins L, Ripke S, Weersma RK, Duerr RH, McGovern DP, Hui KY, et al. Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature. 2012;491:119–24.PubMedCentralCrossRefPubMed
35.
Julià A, Domènech E, Ricart E, Tortosa R, García-Sánchez V, Gisbert JP, et al. A genome-wide association study on a southern European population identifies a new Crohn’s disease susceptibility locus at RBX1-EP300. Gut. 2013;62:1440–5.CrossRefPubMed
36.
Franke A, McGovern DPB, Barrett JC, Wang K, Radford-Smith GL, Ahmad T, et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn’s disease susceptibility loci. Nat Genet. 2010;42:1118–25.PubMedCentralCrossRefPubMed
37.
Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447:661–78.CrossRef
38.
Perdigones N, Martín E, Robledo G, Lamas JR, Taxonera C, Díaz-Rubio M, et al. Study of chromosomal region 5p13.1 in Crohn’s disease, ulcerative colitis, and rheumatoid arthritis. Hum Immunol. 2010;71:826–8.CrossRefPubMed
39.
Weersma RK, Stokkers PCF, Cleynen I, Wolfkamp SCS, Henckaerts L, Schreiber S, et al. Confirmation of multiple Crohn’s disease susceptibility loci in a large Dutch-Belgian cohort. Am J Gastroenterol. 2009;104:630–8.CrossRefPubMed
40.
Glas J, Seiderer J, Czamara D, Pasciuto G, Diegelmann J, Wetzke M, et al. PTGER4 expression-modulating polymorphisms in the 5p13.1 region predispose to Crohn’s disease and affect NF-κB and XBP1 binding sites. PLoS One. 2012;7:e52873.PubMedCentralCrossRefPubMed
41.
Barrett JC, Hansoul S, Nicolae DL, Cho JH, Duerr RH, Rioux JD, et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn’s disease. Nat Genet. 2008;40:955–62.PubMedCentralCrossRefPubMed
42.
Kenny EE, Pe’er I, Karban A, Ozelius L, Mitchell AA, Ng SM, et al. A genome-wide scan of Ashkenazi Jewish Crohn’s disease suggests novel susceptibility loci. PLoS Genet. 2012;8:e1002559.PubMedCentralCrossRefPubMed
43.
Peter I, Mitchell AA, Ozelius L, Erazo M, Hu J, Doheny D, et al. Evaluation of 22 genetic variants with Crohn’s disease risk in the Ashkenazi Jewish population: a case-control study. BMC Med Genet. 2011;12:63.PubMedCentralCrossRefPubMed
44.
Libioulle C, Louis E, Hansoul S, Sandor C, Farnir F, Franchimont D, et al. Novel Crohn disease locus identified by genome-wide association maps to a gene desert on 5p13.1 and modulates expression of PTGER4. PLoS Genet. 2007;3:e58.PubMedCentralCrossRefPubMed
45.
Rioux JD, Xavier RJ, Taylor KD, Silverberg MS, Goyette P, Huett A, et al. Genome-wide association study identifies new susceptibility loci for Crohn disease and implicates autophagy in disease pathogenesis. Nat Genet. 2007;39:596–604.PubMedCentralCrossRefPubMed
46.
Latiano A, Palmieri O, Latiano T, Corritore G, Bossa F, Martino G, et al. Investigation of multiple susceptibility loci for inflammatory bowel disease in an Italian cohort of patients. PLoS One. 2011;6:e22688.PubMedCentralCrossRefPubMed
47.
McGovern DPB, Gardet A, Törkvist L, Goyette P, Essers J, Taylor KD, et al. Genome-wide association identifies multiple ulcerative colitis susceptibility loci. Nat Genet. 2010;42:332–7.PubMedCentralCrossRefPubMed
48.
Anderson CA, Boucher G, Lees CW, Franke A, D’Amato M, Taylor KD, et al. Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47. Nat Genet. 2011;43:246–52.PubMedCentralCrossRefPubMed
49.
Matesanz F, González-Pérez A, Lucas M, Sanna S, Gayán J, Urcelay E, et al. Genome-wide association study of multiple sclerosis confirms a novel locus at 5p13.1. PLoS One. 2012;7:e36140.PubMedCentralCrossRefPubMed
50.
Sawcer S, Hellenthal G, Pirinen M, Spencer CCA, Patsopoulos NA, Moutsianas L, et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature. 2011;476:214–9.PubMedCentralCrossRefPubMed
51.
52.
Metadata
Title
PTGER4 gene variant rs76523431 is a candidate risk factor for radiological joint damage in rheumatoid arthritis patients: a genetic study of six cohorts
Authors
Luis Rodriguez-Rodriguez
Jose Ivorra-Cortes
F. David Carmona
Javier Martín
Alejandro Balsa
Hanna W. van Steenbergen
Annette H. M. van der Helm-van Mil
Isidoro González-Álvaro
Benjamín Fernandez-Gutiérrez
Publication date
01-12-2015
Publisher
BioMed Central
Published in
Arthritis Research & Therapy / Issue 1/2015
Electronic ISSN: 1478-6362
DOI
https://doi.org/10.1186/s13075-015-0830-z

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