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Estimation of heritability of different outcomes for genetic studies of TNFi response in patients with rheumatoid arthritis
  1. Maša Umićević Mirkov1,
  2. Luc Janss2,
  3. Sita H Vermeulen1,3,
  4. Mart A F J van de Laar4,
  5. Piet L C M van Riel3,
  6. Henk-Jan Guchelaar5,
  7. Han G Brunner1,
  8. Cornelis A Albers1,
  9. Marieke J H Coenen1
  1. 1Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
  2. 2Faculty of Science and Technology, Department of Molecular Biology and Genetics, University of Aarhus, Tjele, Denmark
  3. 3Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
  4. 4Department of Rheumatology, University Twente&Medisch Spectrum Twente, Enschede, The Netherlands
  5. 5Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands
  1. Correspondence to Dr Marieke Coenen, Department of Human Genetics (855), Radboud Institute for Health Sciences, Radboud university medical center, PO Box 9101, Nijmegen 6500 HB, The Netherlands; Marieke.Coenen{at}radboudumc.nl

Abstract

Objectives Pharmacogenetic studies of tumour necrosis factor inhibitors (TNFi) response in patients with rheumatoid arthritis (RA) have largely relied on the changes in complex disease scores, such as disease activity score 28 (DAS28), as a measure of treatment response. It is expected that genetic architecture of such complex score is heterogeneous and not very suitable for pharmacogenetic studies. We aimed to select the most optimal phenotype for TNFi response using heritability estimates.

Methods Using two linear mixed-modelling approaches (Bayz and GCTA), we estimated heritability, together with genomic and environmental correlations for the TNFi drug-response phenotype ΔDAS28 and its separate components: Δ swollen joint count (SJC), Δ tender joint count (TJC), Δ erythrocyte sedimentation rate (ESR) and Δ visual-analogue scale of general health (VAS-GH). For this, we used genome-wide single nucleotide polymorphism (SNP) data from 878 TNFi-treated Dutch patients with RA. Furthermore, a multivariate genome-wide association study (GWAS) approach was implemented, analysing separate DAS28 components simultaneously.

Results The highest heritability estimates were found for ΔSJC (Graphic=0.76 and Graphic=0.87) and ΔTJC (Graphic=0.62 and Graphic=0.82); lower heritability was found for ΔDAS28 (Graphic=0.59 and Graphic=0.71) while estimates for ΔESR and ΔVASGH were near or equal to zero. The highest genomic correlations were observed for ΔSJC and ΔTJC (0.49), and the highest environmental correlation was seen between ΔTJC and ΔVASGH (0.62). The multivariate GWAS did not generate excess of low p values as compared with a univariate analysis of ΔDAS28.

Conclusions Our results indicate that multiple SNPs together explain a substantial portion of the variation in change in joint counts in TNFi-treated patients with RA. In conclusion, of the outcomes studied, the joint counts are most suitable for TNFi pharmacogenetics in RA.

  • Anti-TNF
  • Pharmacogenetics
  • Rheumatoid Arthritis
  • Gene Polymorphism
  • DAS28

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