Genetic Factors for the Severity of ACPA-negative Rheumatoid Arthritis in 2 Cohorts of Early Disease: A Genome-wide Study

Objective. Rheumatoid arthritis (RA) that is negative for anticitrullinated protein antibodies (ACPA) is a subentity of RA, characterized by less severe disease. At the individual level, however, considerable differences in the severity of joint destruction occur. We performed a study on genetic factors underlying the differences in joint destruction in ACPA-negative patients. Methods. A genome-wide association study was done with 262 ACPA-negative patients with early RA included in the Leiden Early Arthritis Clinic and related to radiographic joint destruction over 7 years. Significant single-nucleotide polymorphisms (SNP) were evaluated for association with progression of radiographic joint destruction in 253 ACPA-negative patients with early RA included in the Better Anti-Rheumatic Farmaco Therapy (BARFOT) study. According to the Bonferroni correction of the number of tested SNP, the threshold for significance was p < 2 × 10−7 in phase 1 and 0.0045 in phase 2. In both cohorts, joint destruction was measured by Sharp/van der Heijde method with good reproducibility. Results. Thirty-three SNP associated with severity of joint destruction (p < 2 × 10−7) in phase 1. In phase 2, rs2833522 (p = 0.0049) showed borderline significance. A combined analysis of both the Leiden and BARFOT datasets of rs2833522 confirmed this association with joint destruction (p = 3.57 × 10−9); the minor allele (A) associated with more severe damage (for instance, after 7 yrs followup, patients carrying AA had 1.22 times more joint damage compared to patients carrying AG and 1.50 times more joint damage than patients carrying GG). In silico analysis using the ENCODE and Ensembl databases showed presence of H3K4me3 histone mark, transcription factors, and long noncoding RNA in the region of rs2833522, an intergenic SNP located between HUNK and SCAF4. Conclusion. Rs2833522 might be associated with the severity of joint destruction in ACPA-negative RA.

[1]  Alejandro Balsa,et al.  A genome-wide association study of rheumatoid arthritis without antibodies against citrullinated peptides , 2014, Annals of the rheumatic diseases.

[2]  D. M. van der Heijde,et al.  Smoking as a risk factor for the radiological severity of rheumatoid arthritis: a study on six cohorts , 2014, Annals of the rheumatic diseases.

[3]  Jun S. Liu,et al.  Genetics of rheumatoid arthritis contributes to biology and drug discovery , 2013 .

[4]  P. Gregersen,et al.  Identification of BACH2 and RAD51B as rheumatoid arthritis susceptibility loci in a meta-analysis of genome-wide data. , 2013, Arthritis & Rheumatism.

[5]  R. Tsonaka,et al.  Comparison of methodologies for analysing the progression of joint destruction in rheumatoid arthritis , 2013, Scandinavian journal of rheumatology.

[6]  Buhm Han,et al.  Chromatin marks identify critical cell types for fine mapping complex trait variants , 2012 .

[7]  Eli Stahl,et al.  High density genetic mapping identifies new susceptibility loci for rheumatoid arthritis , 2012, Nature Genetics.

[8]  Data production leads,et al.  An integrated encyclopedia of DNA elements in the human genome , 2012 .

[9]  Raymond K. Auerbach,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[10]  ENCODEConsortium,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[11]  A. Barton,et al.  Genetic markers of rheumatoid arthritis susceptibility in anti-citrullinated peptide antibody negative patients , 2012, Annals of the rheumatic diseases.

[12]  J. Lausen,et al.  Tal1 regulates osteoclast differentiation through suppression of the master regulator of cell fusion DC‐STAMP , 2012, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[13]  T. Huizinga,et al.  Genetic predisposition of the severity of joint destruction in rheumatoid arthritis: a population-based study , 2012, Annals of the rheumatic diseases.

[14]  B. Mertens,et al.  Can anti-cyclic citrullinated peptide antibody-negative RA be subdivided into clinical subphenotypes? , 2011, Arthritis research & therapy.

[15]  Thomas W. Yang,et al.  Hunk is required for HER2/neu-induced mammary tumorigenesis. , 2011, The Journal of clinical investigation.

[16]  Rachel Knevel,et al.  Predicting arthritis outcomes--what can be learned from the Leiden Early Arthritis Clinic? , 2011, Rheumatology.

[17]  Geert Molenberghs,et al.  Random Effects Models for Longitudinal Data , 2010 .

[18]  Jing Cui,et al.  Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci , 2010, Nature Genetics.

[19]  Katsuhiko Murakami,et al.  H-InvDB in 2009: extended database and data mining resources for human genes and transcripts , 2009, Nucleic Acids Res..

[20]  M. Daly,et al.  Genetic variants at CD28, PRDM1, and CD2/CD58 are associated with rheumatoid arthritis risk , 2009, Nature Genetics.

[21]  T. Huizinga,et al.  Advances in the genetics of rheumatoid arthritis point to subclassification into distinct disease subsets , 2008, Arthritis research & therapy.

[22]  C. Pipper,et al.  [''R"--project for statistical computing]. , 2008, Ugeskrift for laeger.

[23]  M. van Oosterhout,et al.  Differences in synovial tissue infiltrates between anti-cyclic citrullinated peptide-positive rheumatoid arthritis and anti-cyclic citrullinated peptide-negative rheumatoid arthritis. , 2008, Arthritis and rheumatism.

[24]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[25]  D. Clayton,et al.  An R Package for Analysis of Whole-Genome Association Studies , 2007, Human Heredity.

[26]  M. Brent,et al.  Iterative gene prediction and pseudogene removal improves genome annotation. , 2006, Genome research.

[27]  Michael R. Brent,et al.  Using Multiple Alignments to Improve Gene Prediction , 2005, RECOMB.

[28]  Wei Chen,et al.  Refining the complex rheumatoid arthritis phenotype based on specificity of the HLA-DRB1 shared epitope for antibodies to citrullinated proteins. , 2005, Arthritis and rheumatism.

[29]  A. Boonen,et al.  Low-dose prednisolone in addition to the initial disease-modifying antirheumatic drug in patients with early active rheumatoid arthritis reduces joint destruction and increases the remission rate: a two-year randomized trial. , 2005, Arthritis and rheumatism.

[30]  F. Breedveld,et al.  Antibodies to citrullinated proteins and differences in clinical progression of rheumatoid arthritis , 2005, Arthritis research & therapy.

[31]  Kanako O. Koyanagi,et al.  Integrative Annotation of 21,037 Human Genes Validated by Full-Length cDNA Clones , 2004, PLoS Biology.

[32]  Stephen M. Mount,et al.  Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. , 2003, Nucleic acids research.

[33]  Philip Lijnzaad,et al.  The Ensembl genome database project , 2002, Nucleic Acids Res..

[34]  Ian Korf,et al.  Integrating genomic homology into gene structure prediction , 2001, ISMB.

[35]  D. M. van der Heijde,et al.  Methodological issues in radiographic scoring methods in rheumatoid arthritis. , 1999, The Journal of rheumatology.

[36]  Douglas M. Bates,et al.  LINEAR AND NONLINEAR MIXED-EFFECTS MODELS , 1998 .

[37]  S. Karlin,et al.  Prediction of complete gene structures in human genomic DNA. , 1997, Journal of molecular biology.

[38]  C. Werning.  [Rheumatoid arthritis]. , 1983, Medizinische Monatsschrift fur Pharmazeuten.

[39]  J. Ware,et al.  Random-effects models for longitudinal data. , 1982, Biometrics.

[40]  J. Gower.  Some distance properties of latent root and vector methods used in multivariate analysis , 1966 .