Abstract
BackgroundAn individual patient’s response to a particular drug is influenced by multiple factors, which may include genetic predisposition. Pharmacogenetic studies attempt to discover and estimate the contributions of genetic variants to the variability in response to a drug treatment. The task of identifying the genetic contribution is often complicated by response phenotypes that are based on imprecise or subjective clinical observations. Because the success of a pharmacogenetic study depends on the analysis of a heritable phenotype, it is important to identify phenotypes with a significant heritable component to ensure reliable and reproducible results in subsequent genetic association studies.MethodsWe retrospectively analyzed data collected from 436 rheumatoid arthritis patients treated with golimumab during the phase III GO-FURTHER study. We investigated the reliability of several potential response outcomes after golimumab treatment. Using whole-genome sequencing of the clinical trial cohort, we estimated the heritability of each potential outcome measure. We further performed a longitudinal analysis of the clinical data to estimate variability of outcome measures over time and the degree to which each response metric could be confounded by placebo response.ResultsWe determined that the high degree of within-patient variation over time makes a single follow-up visit insufficient to assess an individual patient’s response to golimumab treatment. We found that different potential response outcomes had varying degrees of heritability and that averaging across multiple follow-up visits yielded higher heritability estimates than single follow-up estimates. Importantly, we found that the change in swollen and tender joint counts were the most heritable outcome metrics we tested; however, we showed that they are also more likely to be confounded by a placebo response than objective phenotypes like the change in C-reactive protein levels.ConclusionsOur rigorous approach to finding robust and heritable response phenotypes could be beneficial to all pharmacogenetic studies and may lead to more reliable and reproducible results.Trial RegistrationClinicaltrials.gov NCT00973479. Registered 4 September 2009.
Highlights
An individual patient’s response to a particular drug is influenced by multiple factors, which may include genetic predisposition
When we regressed the change in disease state against the baseline disease state, a common covariate included in genetic association studies, we found that the residuals of the C-reactive protein (CRP), Swollen joint count (SJC), and Tender joint count (TJC) metrics violated the assumption of normality
We found similar distributions of within-patient error across the population, regardless of which outcome metric was used (i.e., Disease Activity Score (DAS), logarithmic scale for CRP (lCRP), Square root of SJC (rSJC), or Square root of TJC (rTJC); Fig. 2a)
Summary
An individual patient’s response to a particular drug is influenced by multiple factors, which may include genetic predisposition. Pharmacogenetic studies attempt to discover and estimate the contributions of genetic variants to the variability in response to a drug treatment. The task of identifying the genetic contribution is often complicated by response phenotypes that are based on imprecise or subjective clinical observations. Close to 100 loci from non-HLA genes have been shown to contribute to disease susceptibility [4]. Because the genetic variants cumulatively explain only about 18% of Standish et al Arthritis Research & Therapy (2017) 19:90 disease variance, a large environmental influence has yet to be clearly defined [5]
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