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.
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.
The highest heritability estimates were found for ΔSJC (h(2)gbayz=0.76 and h(2)gGCTA=0.87) and ΔTJC (h(2)gbayz=0.62 and h(2)gGCTA=0.82); lower heritability was found for ΔDAS28 (h(2)gbayz=0.59 and h(2)gGCTA=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.
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.