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Meta-analysis identifies loci affecting levels of the potential osteoarthritis biomarkers sCOMP and uCTX-II with genome wide significance
  1. Yolande F M Ramos1,2,
  2. Sarah Metrustry3,
  3. Nigel Arden4,5,
  4. Anne C Bay-Jensen6,
  5. Marian Beekman1,2,
  6. Anton J M de Craen7,2,
  7. L Adrienne Cupples8,9,
  8. Tõnu Esko10,11,12,
  9. Evangelos Evangelou13,3,
  10. David T Felson14,
  11. Deborah J Hart3,
  12. John P A Ioannidis13,15,16,17,
  13. Morten Karsdal6,
  14. Margreet Kloppenburg18,
  15. Floris Lafeber19,
  16. Andres Metspalu10,
  17. Kalliope Panoutsopoulou20,
  18. P Eline Slagboom1,2,
  19. Tim D Spector3,
  20. Erwin W E van Spil19,
  21. Andre G Uitterlinden2,21,
  22. Yanyan Zhu22,
  23. arcOGEN consortium,
  24. TreatOA collaborators,
  25. Ana M Valdes23,
  26. Joyce B J van Meurs2,21,
  27. Ingrid Meulenbelt1,2
  1. 1Department of Molecular Epidemiology, LUMC, Leiden, The Netherlands
  2. 2The Netherlands Genomics Initiative-Sponsored Netherlands Consortium for Healthy Aging, Leiden and Rotterdam, The Netherlands
  3. 3Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
  4. 4NIHR Musculoskeletal Biomedical Research Unit, University of Oxford, Oxford, UK
  5. 5Arthritis Research UK, Sport, Exercise and Osteoarthritis Centre of Excellence, London, UK
  6. 6Department of Rheumatology, Nordic Bioscience, Herlev, Denmark
  7. 7Department of Gerontology and Geriatrics, LUMC, Leiden, The Netherlands
  8. 8Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
  9. 9The Framingham Heart Study, Framingham, Massachusetts, USA
  10. 10Institute of Molecular and Cell Biology and Estonian Genome Center, University of Tartu, Tartu, Estonia
  11. 11Department of Endocrinology, Children's Hospital Boston, Boston, Massachusetts, USA
  12. 12Broad Institute, Cambridge, Massachusetts, USA
  13. 13Department of Hygiene & Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
  14. 14Clinical Epidemiology Unit, Boston University School of Medicine, Boston, Massachusetts, USA
  15. 15Department of Medicine, Stanford Prevention Research Center, Stanford, USA
  16. 16Department of Health Research and Policy, Stanford University School of Medicine, Stanford, USA
  17. 17Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, USA
  18. 18Department of Rheumatology & Clinical Epidemiology, LUMC, Leiden, The Netherlands
  19. 19Department of Rheumatology & Clinical Immunology, UMC Utrecht, Utrecht, The Netherlands
  20. 20Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
  21. 21Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
  22. 22Global Analytical Science, Takeda Pharmaceuticals International Co., Cambridge, Massachusetts, USA
  23. 23Academic Rheumatology, University of Nottingham, Nottingham, UK
  1. Correspondence to Dr Yolande F M Ramos, Department of Molecular Epidemiology, Leiden University Medical Center, LUMC Postzone S-05-P, P.O. Box 9600, Leiden 2300 RC, The Netherlands; y.f.m.ramos{at}


Background Research for the use of biomarkers in osteoarthritis (OA) is promising, however, adequate discrimination between patients and controls may be hampered due to innate differences. We set out to identify loci influencing levels of serum cartilage oligomeric protein (sCOMP) and urinary C-telopeptide of type II collagen (uCTX-II).

Methods Meta-analysis of genome-wide association studies was applied to standardised residuals of sCOMP (N=3316) and uCTX-II (N=4654) levels available in 6 and 7 studies, respectively, from TreatOA. Effects were estimated using a fixed-effects model. Six promising signals were followed up by de novo genotyping in the Cohort Hip and Cohort Knee study (N=964). Subsequently, their role in OA susceptibility was investigated in large-scale genome-wide association studies meta-analyses for OA. Differential expression of annotated genes was assessed in cartilage.

Results Genome-wide significant association with sCOMP levels was found for a SNP within MRC1 (rs691461, p=1.7×10−12) and a SNP within CSMD1 associated with variation in uCTX-II levels with borderline genome-wide significance (rs1983474, p=8.5×10−8). Indication for association with sCOMP levels was also found for a locus close to the COMP gene itself (rs10038, p=7.1×10−6). The latter SNP was subsequently found to be associated with hip OA whereas COMP expression appeared responsive to the OA pathophysiology in cartilage.

Conclusions We have identified genetic loci affecting either uCTX-II or sCOMP levels. The genome wide significant association of MRC1 with sCOMP levels was found likely to act independent of OA subtypes. Increased sensitivity of biomarkers with OA may be accomplished by taking genetic variation into account.

  • Genetic epidemiology
  • Genome-wide
  • Osteoarthritis

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