Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • News & Views
  • Published:

RHEUMATOID ARTHRITIS

Unravelling the pharmacogenomics of TNF inhibition

Despite the previous identification of genes involved in the treatment response to TNF inhibition in rheumatoid arthritis, no genetic biomarkers are currently used in clinical decision-making. Might the heterogeneous nature of the disease activity score, which is often used as the outcome measure in genetic studies, partly explain this gap?

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

References

  1. Massey, J. et al. Genome-wide association study of response to tumour necrosis factor inhibitor therapy in rheumatoid arthritis. Pharmacogenomics J. 18, 657–664 (2018).

    Article  CAS  Google Scholar 

  2. Umicevic Mirkov, M. et al. Estimation of heritability of different outcomes for genetic studies of TNFi response in patients with rheumatoid arthritis. Ann. Rheum. Dis. 74, 2183–2187 (2015).

    Article  Google Scholar 

  3. Loos, R. J. & Yeo, G. S. The bigger picture of FTO: the first GWAS-identified obesity gene. Nat. Rev. Endocrinol. 10, 51–61 (2014).

    Article  CAS  Google Scholar 

  4. Singh, S. et al. Obesity and response to anti-tumor necrosis factor-alpha agents in patients with select immune-mediated inflammatory diseases: a systematic review and meta-analysis. PLOS ONE 13, e0195123 (2018).

    Article  Google Scholar 

  5. Iles, M. M. et al. A variant in FTO shows association with melanoma risk not due to BMI. Nat. Genet. 45, 428–432 (2013).

    Article  CAS  Google Scholar 

  6. MacGregor, A. J. et al. Characterizing the quantitative genetic contribution to rheumatoid arthritis using data from twins. Arthritis Rheum. 43, 30–37 (2000).

    Article  CAS  Google Scholar 

  7. Nielsen, C. S. et al. Individual differences in pain sensitivity: genetic and environmental contributions. Pain 136, 21–29 (2008).

    Article  Google Scholar 

  8. Wen, H. et al. Comparison of expectations of physicians and patients with rheumatoid arthritis for rheumatology clinic visits: a pilot, multicenter, international study. Int. J. Rheum. Dis. 15, 380–389 (2012).

    Article  Google Scholar 

  9. Canhao, H. et al. TRAF1/C5 but not PTPRC variants are potential predictors of rheumatoid arthritis response to anti-tumor necrosis factor therapy. Biomed. Res. Int. 2015, 490295 (2015).

    Article  Google Scholar 

  10. Khera, A. V. et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat. Genet. 50, 1219–1224 (2018).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marieke J. H. Coenen.

Ethics declarations

Competing interests

The author declares no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Coenen, M.J.H. Unravelling the pharmacogenomics of TNF inhibition. Nat Rev Rheumatol 14, 689–690 (2018). https://doi.org/10.1038/s41584-018-0114-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41584-018-0114-5

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing