Patient‐specific genetic factors predict treatment failure in sofosbuvir‐treated patients with chronic hepatitis C. (21st February 2022) - Loucks, Catrina M.; Lin, Jennifer J.; Trueman, Jessica N.; Drögemöller, Britt I.; Wright, Galen E. B.; Chang, Wan‐Chun; Li, Kathy H.; Yoshida, Eric M.; Ford, Jo‐Ann; Lee, Samuel S.; Crotty, Pam; Kim, Richard B.; et al.
Abstract: Background & Aims: According to pivotal clinical trials, cure rates for sofosbuvir‐based antiviral therapy exceed 96%. Treatment failure is usually assumed to be because of virological resistance‐associated substitutions or clinical risk factors, yet the role of patient‐specific genetic factors has not been well explored. We determined if patient‐specific genetic factors help predict patients likely to fail sofosbuvir treatment in real‐world treatment situations. Methods: We recruited sofosbuvir‐treated patients with chronic hepatitis C from five Canadian treatment sites, and performed a case‐control pharmacogenomics study assessing both previously published and novel genetic polymorphisms. Specifically studied were variants predicted to impair CES1‐dependent production of sofosbuvir's active metabolite, interferon‐λ signalling variants expected to impact a patient's immune response to the virus and an HLA variant associated with increased spontaneous and treatment‐induced viral clearance. Results: Three hundred and fifty‐nine sofosbuvir‐treated patients were available for analyses after exclusions, with 34 (9.5%) failing treatment. We identified CES1 variants as novel predictors for treatment failure in European patients (rs115629050 or rs4513095; odds ratio (OR): 5.43; 95% confidence interval (CI): 1.64‐18.01; P  = .0057), replicated associations with IFNL4 variants predicted to increase interferon‐λ signalling (eg rs12979860; OR: 2.25; 95% CI: 1.25‐4.06; P  = .0071) and discovered a novel association with a coding variant predicted to enhance the activity of IFNL4's receptor (rs2834167 in IL10RB ; OR: 1.81; 95% CI: 1.01‐3.24; P  = .047). Conclusions: Ultimately, this work demonstrates that patient‐specific genetic factors could be used as a tool to identify patients at higher risk of treatment failure and allow for these patients to receive effective therapy sooner.