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Systematic approach demonstrates enrichment of multiple interactions between non-HLA risk variants and HLA-DRB1 risk alleles in rheumatoid arthritis
  1. Lina-Marcela Diaz-Gallo1,
  2. Daniel Ramsköld1,
  3. Klementy Shchetynsky1,
  4. Lasse Folkersen2,
  5. Karine Chemin1,
  6. Boel Brynedal3,
  7. Steffen Uebe4,
  8. Yukinori Okada5,6,
  9. Lars Alfredsson3,
  10. Lars Klareskog1,
  11. Leonid Padyukov1
  1. 1 Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
  2. 2 Sankt Hans Hospital, Capital Region Hospitals, Roskilde, Denmark
  3. 3 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
  4. 4 Human Genetics Institute, Universitätsklinikum Erlangen, Erlangen, Germany
  5. 5 Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
  6. 6 Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Osaka, Japan
  1. Correspondence to Dr Lina-Marcela Diaz-Gallo, Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm 17176, Sweden; lina.diaz{at}ki.se

Abstract

Objective In anti-citrullinated protein antibody positive rheumatoid arthritis (ACPA-positive RA), a particular subset of HLA-DRB1 alleles, called shared epitope (SE) alleles, is a highly influential genetic risk factor. Here, we investigated whether non-HLA single nucleotide polymorphisms (SNP), conferring low disease risk on their own, interact with SE alleles more frequently than expected by chance and if such genetic interactions influence the HLA-DRB1 SE effect concerning risk to ACPA-positive RA.

Methods We computed the attributable proportion (AP) due to additive interaction at genome-wide level for two independent ACPA-positive RA cohorts: the Swedish epidemiological investigation of rheumatoid arthritis (EIRA) and the North American rheumatoid arthritis consortium (NARAC). Then, we tested for differences in the AP p value distributions observed for two groups of SNPs, non-associated and associated with disease. We also evaluated whether the SNPs in interaction with HLA-DRB1 were cis-eQTLs in the SE alleles context in peripheral blood mononuclear cells from patients with ACPA-positive RA (SE-eQTLs).

Results We found a strong enrichment of significant interactions (AP p<0.05) between the HLA-DRB1 SE alleles and the group of SNPs associated with ACPA-positive RA in both cohorts (Kolmogorov-Smirnov test D=0.35 for EIRA and D=0.25 for NARAC, p<2.2e-16 for both). Interestingly, 564 out of 1492 SNPs in consistent interaction for both cohorts were significant SE-eQTLs. Finally, we observed that the effect size of HLA-DRB1 SE alleles for disease decreases from 5.2 to 2.5 after removal of the risk alleles of the two top interacting SNPs (rs2476601 and rs10739581).

Conclusion Our data demonstrate that there are massive genetic interactions between the HLA-DRB1 SE alleles and non-HLA genetic variants in ACPA-positive RA.

  • rheumatoid arthritis
  • ANT-CCP
  • gene polymorphism

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Footnotes

  • Handling editor Josef S Smolen

  • Twitter @LinMarDiaz

  • Contributors LMDG: conceptualisation, data curation, formal analysis, investigation, methodology, software, project administration, validation, visualisation, writing—original draft preparation and review and editing. DR: conceptualisation, formal analysis, methodology, resources, writing—review and editing. KS: conceptualisation, investigation, methodology, software, writing—review and editing. LF: conceptualisation, formal analysis, writing—review and editing. KC: conceptualisation, validation, writing—review and editing. BB: conceptualisation, writing—review and editing. SU: data curation. YO: data curation, resources, writing—review and editing. LA: conceptualisation, investigation, resources, software, writing—review and editing. LK: conceptualisation, funding acquisition, resources, writing—review and editing. LP: conceptualisation, funding acquisition, investigation, methodology, project administration, resources, supervision, validation, writing—original draft preparation and review and editing.

  • Funding This study was supported by the Swedish Council of Science (Vetenskapsrådet, https://www.vr.se/) (grant number 2015-03006); COMBINE project (Vinnova, https://www.vinnova.se/); BeTheCure EU IMI programme (http://cordis.europa.eu/project/rcn/203688_en.html); and Stiftelsen Konung Gustaf V:s 80-årsfond (KGV) Foundation (grant numbers FAI2014-0093, FAI2015-0207, FAI2016-0287, SGI2014-0022).

  • Competing interests None declared.

  • Patient consent Not required.

  • Ethics approval Karolinska Institutet Ethics Committee and the Regional Stockholm Ethics Committee.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement The full output of the interaction analysis is available upon request. It is not included in the manuscript due to the size of the files.

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