The Pharmacogenetics of Statin Therapy on Clinical Events: No Evidence that Genetic Variation Affects Statin Response on Myocardial Infarction

Background: The pharmacogenetic effect on cardiovascular disease reduction in response to statin treatment has only been assessed in small studies. In a pharmacogenetic genome wide association study (GWAS) analysis within the Genomic Investigation of Statin Therapy (GIST) consortium, we investigated whether genetic variation was associated with the response of statins on cardiovascular disease risk reduction.Methods: The investigated endpoint was incident myocardial infarction (MI) defined as coronary heart disease death and definite and suspect non-fatal MI. For imputed single nucleotide polymorphisms (SNPs), regression analysis was performed on expected allelic dosage and meta-analysed with a fixed-effects model, inverse variance weighted meta-analysis. All SNPs with p-values <5.0 × 10−4 in stage 1 GWAS meta-analysis were selected for further investigation in stage-2. As a secondary analysis, we extracted SNPs from the Stage-1 GWAS meta-analysis results based on predefined hypotheses to possibly modifying the effect of statin therapy on MI.Results: In stage-1 meta-analysis (eight studies, n = 10,769, 4,212 cases), we observed no genome-wide significant results (p < 5.0 × 10−8). A total of 144 genetic variants were followed-up in the second stage (three studies, n = 1,525, 180 cases). In the combined meta-analysis, no genome-wide significant hits were identified. Moreover, none of the look-ups of SNPs known to be associated with either CHD or with statin response to cholesterol levels reached Bonferroni level of significance within our stage-1 meta-analysis.Conclusion: This GWAS analysis did not provide evidence that genetic variation affects statin response on cardiovascular risk reduction. It does not appear likely that genetic testing for predicting effects of statins on clinical events will become a useful tool in clinical practice.

Determining propensity for sub-optimal low-density lipoprotein cholesterol response to statins and future risk of cardiovascular disease

Background Variability in low-density lipoprotein cholesterol (LDL-C) response to statins is underappreciated. We characterised patients by their statin response (SR), baseline risk of cardiovascular disease (CVD) and 10-year CVD outcomes. Methods and results A multivariable model was developed using 183,213 United Kingdom (UK) patients without CVD to predict probability of sub-optimal SR, defined by guidelines as <40% reduction in LDL-C. We externally validated the model in a Hong Kong (HK) cohort (n = 170,904). Patients were stratified into four groups by predicted SR and 10-year CVD risk score: [SR1] optimal SR & low risk; [SR2] sub-optimal SR & low risk; [SR3] optimal SR & high risk; [SR4] sub-optimal SR & high risk; and 10-year hazard ratios (HR) determined for first major adverse cardiovascular event (MACE). Our SR model included 12 characteristics, with an area under the curve of 0.70 (95% confidence interval [CI] 0.70–0.71; UK) and 0.68 (95% CI 0.67–0.68; HK). HRs for MACE in predicted sub-optimal SR with low CVD risk groups (SR2 to SR1) were 1.39 (95% CI 1.35–1.43, p<0.001; UK) and 1.14 (95% CI 1.11–1.17, p<0.001; HK). In both cohorts, patients with predicted sub-optimal SR with high CVD risk (SR4 to SR3) had elevated risk of MACE (UK HR 1.36, 95% CI 1.32–1.40, p<0.001: HK HR 1.25, 95% CI 1.21–1.28, p<0.001). Conclusions Patients with sub-optimal response to statins experienced significantly more MACE, regardless of baseline CVD risk. To enhance cholesterol management for primary prevention, statin response should be considered alongside risk assessment.

Vesicular trafficking is a key determinant of the statin response in acute myeloid leukemia

Cholesterol homeostasis has been proposed as one mechanism contributing to chemoresistance in AML and hence, inclusion of statins in therapeutic regimens as part of clinical trials in AML has shown encouraging results. Chemical screening of primary human AML specimens by our group led to the identification of lipophilic statins as potent inhibitors of AMLs from a wide range of cytogenetic groups. Genetic screening to identify modulators of the statin response uncovered the role of protein geranylgeranylation and of RAB proteins, coordinating various aspect of vesicular trafficking, in mediating the effects of statins on AML cell viability. We further show that statins can inhibit vesicle-mediated transport in primary human specimens, and that statins sensitive samples show expression signatures reminiscent of enhanced vesicular trafficking. Overall, this study sheds light into the mechanism of action of statins in AML and identifies a novel vulnerability for cytogenetically diverse AML.

Common Statin Intolerance Variants in ABCB1 and LILRB5 Show Synergistic Effects on Statin Response: An Observational Study Using Electronic Health Records

Background: Statin intolerance impacts approximately 10% of statin users, with side effects ranging from mild myalgia to extreme intolerance resulting in myopathy and rhabdomyolysis. Statin intolerance results in poor adherence to therapy and can impact statin efficacy. Many genetic variants are associated with statin intolerance. The effect of these variants on statin efficacy has not been systematically explored.Methods: Using longitudinal electronic health records and genetic biobank data from Tayside, Scotland, we examined the effect of seven genetic variants with previously reported associations with simvastatin or atorvastatin intolerance on the outcome of statin response. Statin response was measured by the reduction achieved when comparing pre- and post-statin non-high-density lipoprotein-cholesterol (non-HDL-C). Post-treatment statin response was limited to non-HDL-C measured within 6months of therapy initiation. Univariate and multivariable linear regression models were used to assess the main and adjusted effect of the variants on statin efficacy.Results: Around 9,401 statin users met study inclusion criteria, of whom 8,843 were first prescribed simvastatin or atorvastatin. The average difference in post-treatment compared to pre-treatment non-HDL-cholesterol was 1.45 (±1.04) mmol/L. In adjusted analyses, only two variants, one in the gene ATP-binding cassette transporter B1 (ABCB1; rs1045642), and one in leukocyte immunoglobulin like receptor B5 (LILRB5; rs12975366), were associated with statin efficacy. In ABCB1, homozygous carriers of the C allele at rs1045642 had 0.06mmol/L better absolute reduction in non-HDL-cholesterol than carriers of the T allele (95% CI: 0.01, 0.1). In LILRB5 (rs12975366), carriers of the C allele had 0.04mmol/L better absolute reduction compared to those homozygous for the T allele (95% CI: 0.004, 0.08). When combined into a two-variant risk score, individuals with both the rs1045642-CC genotype and the rs12975366-TC or CC genotype had a 0.11mmol/L greater absolute reduction in non-HDL-cholesterol compared to those with rs1045642-TC or TT genotype and the rs12975366-TT genotype (95% CI: 0.05, 0.16; p&lt;0.001).Conclusion: We report two genetic variants for statin adverse drug reactions (ADRs) that are associated with statin efficacy. While the ABCB1 variant has been shown to have an association with statin pharmacokinetics, no similar evidence for LILRB5 has been reported. These findings highlight the value of genetic testing to deliver precision therapeutics to statin users.

Identifying genetic modulators of statin response using subject-derived lymphoblastoid cell lines

Although statins (3-hydroxy-3-methylglutaryl-CoA reductase inhibitors) have proven effective in reducing plasma low-density lipoprotein levels and risk of cardiovascular disease, their lipid lowering efficacy is highly variable among individuals. Furthermore, statin treatment carries a small but significant risk of adverse effects, most notably myopathy and new onset diabetes. Hence, identification of biomarkers for predicting patients who would most likely benefit from statin treatment without incurring increased risk of adverse effects can have a significant public health impact. In this review, we discuss the rationale for the use of subject-derived lymphoblastoid cell lines in studies of statin pharmacogenomics and describe a variety of approaches we have employed to identify novel genetic markers associated with interindividual variation in statin response.

Abstract 16278: Discordant Lipid Phenotype and Other Determinants of Statin Response in the Pravastatin Inflammation/crp Evaluation (PRINCE) Trial

Introduction: Wide variability in LDL-C change is observed with statins, yet determinants of statin response are uncertain. Methods: Participants were selected from the primary prevention cohort of the Pravastatin Inflammation/CRP Evaluation double-blind trial that randomized participants to pravastatin 40 mg/d or placebo over 24 weeks. Baseline and 24-week levels of LDL-C and 15 other biomarkers were measured in 495 participants. We defined optimal statin response as >=30% LDL-C reduction and suboptimal response as <30% reduction. Sub-optimal hs-CRP response was defined as >=median (14%) decline in hs-CRP from baseline to 24 weeks and non-response as no decrease or an increase in hs-CRP. χ 2 , t-tests and ANOVA were used to compare variables across optimal statin response (N=166) and suboptimal response (N=287). Multivariable logistic regression models evaluated associations of determinants of statin response. Forward selection identified variables that associated with response. Xgboost was used to train and validate the models using 2/3 and 1/3 of the data respectively. Results: Significant determinants of optimal statin response included older age, and higher baseline levels of LDL-C and triglyceride-rich lipoproteins. By contrast, female sex, alcohol intake >=1 drink/day, diabetes, higher baseline levels of apo B and lipoprotein(a) were associated with decreased response, as was hs-CRP non-response (Table). Race, baseline hs-CRP and sub-optimal hs-CRP response, smoking, HDL-C and BMI had no significant effect on statin LDL-C response. Training and validation of models predicted suboptimal LDL-C response with an AUC of 0.71. Similarly, training and validation of models using Xgboost yielded an AUC of 0.85. Conclusion: This study identified discordant lipid phenotype and other determinants of moderate-intensity statin response and suggests other pathways of CVD risk beyond those addressed by statin treatment that require further investigation.

Atorvastatin Increases the Expression of Long Non-Coding RNAs ARSR and CHROME in Hypercholesterolemic Patients: A Pilot Study

Atorvastatin is extensively used to treat hypercholesterolemia. However, the wide interindividual variability observed in response to this drug still needs further elucidation. Nowadays, the biology of long non-coding RNAs (lncRNAs) is better understood, and some of these molecules have been related to cholesterol metabolism. Therefore, they could provide additional information on variability in response to statins. The objective of this research was to evaluate the effect of atorvastatin on three lncRNAs (lncRNA ARSR: Activated in renal cell carcinoma (RCC) with sunitinib resistance, ENST00000424980; lncRNA LASER: lipid associated single nucleotide polymorphism locus, ENSG00000237937; and lncRNA CHROME: cholesterol homeostasis regulator of miRNA expression, ENSG00000223960) associated with genes involved in cholesterol metabolism as predictors of lipid-lowering therapy performance. Twenty hypercholesterolemic patients were treated for four weeks with atorvastatin (20 mg/day). The lipid profile was determined before and after drug administration using conventional assays. The expression of lncRNAs was assessed in peripheral blood samples by RT-qPCR. As expected, atorvastatin improved the lipid profile, decreasing total cholesterol, LDL-C, and the TC/HDL-C ratio (p < 0.0001) while increasing the expression of lncRNAs ARSR and CHROME (p < 0.0001) upon completion of treatment. LASER did not show significant differences among the groups (p = 0.50). Our results indicate that atorvastatin modulates the expression of cholesterol-related lncRNAs differentially, suggesting that these molecules play a role in the variability of response to this drug; however, additional studies are needed to disclose the implication of this differential regulation on statin response.