Personalized medicine in rheumatic diseases: how close are we to being able to use genetic biomarkers to predict response to TNF inhibitors?

Introduction: A genetic biomarker to select which drug will work best for which patients with rheumatic diseases is a goal of pharmacogenetic precision medicine approaches and one that patients and the public support. However, studies to date have yielded inconsistent findings with no robustly replicated or clinically useful genetic biomarkers emerging. Areas covered: Using studies investigating biomarkers to predict response to tumor necrosis factor inhibitor therapies in rheumatoid arthritis as an exemplar, we consider factors that reduce the power to detect such predictive biomarkers, including non-adherence, immunogenicity, the use of clinical outcome measures comprising composite scores and sample size. We argue that the biologic therapies were developed to target joint inflammation and so the outcome measure should be closer to the biology and, ideally, should be a biological measure. Given that heritability studies have shown a substantial genetic contribution, there is merit in designing studies to optimize the chance of identifying robust genetic markers and that includes testing drug levels for adherence. Expert opinion: Ultimately, we think that genetics will be used as part of an algorithm to assess likely response to individual drugs but that other factors will also be important including clinical and environmental factors.