A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance

Abstract

Background and aims: The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping. In this study, we aimed to develop an easy, clinically implementable functional gene risk score (GRS) of common variants in SLCO1B1 to identify patients at risk of statin intolerance.

Methods and results: A GRS was developed from four common variants in SLCO1B1. In statin users from Tayside, Scotland, UK, those with a high-risk GRS had increased odds across three phenotypes of statin intolerance [general statin intolerance (GSI): ORGSI 2.42; 95% confidence interval (CI): 1.29-4.31, P = 0.003; statin-related myopathy: ORSRM 2.51; 95% CI: 1.28-4.53, P = 0.004; statin-related suspected rhabdomyolysis: ORSRSR 2.85; 95% CI: 1.03-6.65, P = 0.02]. In contrast, using the Val174Ala genotype alone or the recommended OATP1B1 functional phenotypes produced weaker and less reliable results. A meta-analysis with results from adjudicated cases of statin-induced myopathy in the PREDICTION-ADR Consortium confirmed these findings (ORVal174Ala 1.99; 95% CI: 1.01-3.95, P = 0.048; ORGRS 1.76; 95% CI: 1.16-2.69, P = 0.008). For those requiring high-dose statin therapy, the high-risk GRS was more consistently associated with the time to onset of statin intolerance amongst the three phenotypes compared with Val174Ala (GSI: HRVal174Ala 2.49; 95% CI: 1.09-5.68, P = 0.03; HRGRS 2.44; 95% CI: 1.46-4.08, P < 0.001). Finally, sequence kernel association testing confirmed that rare variants in SLCO1B1 are associated with the risk of intolerance (P = 0.02).

Conclusion: We provide evidence that a GRS based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance.

Keywords: SLCO1B1; Adverse drug reactions; Musculoskeletal symptoms; Pharmacogenomics; Precision medicine; Statins.

Graphical Abstract

Schematic representation of the definition of cases and controls, common SLCO1B1 variants included in the gene risk score (GRS), and findings from the study. The GRS, based on four common SLCO1B1 variants, is more reliable than Val174Ala alone in estimating the risk and predicting early onset statin intolerance.

Figure 1

Models adjusted for age, sex, previous cardiovascular events, interacting medications, statin type, and statin dose. GSI, general statin intolerance; CI, confidence interval; SRM, statin-related myopathy; SRSR, statin-related suspected rhabdomyolysis.

Figure 2

Forest plot showing combined results from a fixed-effects meta-analysis of the association between SLCO1B1 GRS and Val174Ala to statin intolerance in Tayside Bioresources and PREDICTION-ADR Consortium. GRS, gene risk score.

Figure 3

Unadjusted Kaplan–Meier curves and risk tables for cumulative incidence of (a) general statin intolerance, (b) statin-related myopathy, and (c) statin-related suspected rhabdomyolysis in individuals on an equivalent simvastatin dose ≥40 mg, according to the gene risk score (GRS) (blue: high-risk GRS; grey: low-risk GRS). Using likelihood ratio tests, the fit of the genetic models (either Val174Ala or SLCO1B1 GRS) was compared with the clinical model, showing that the addition of the SLCO1B1 GRS, and not Val174Ala, resulted in a statistically significant improvement (Table 3).