No association between CYP3A4*22 and statin effectiveness in reducing the risk for myocardial infarction

When the same treatment has different response: The role of pharmacogenomics in statin therapy

Statins, also known as HMG-CoA reductase inhibitors, are one of the most potently prescribed and thoroughly researched medications, predominantly utilized for managing cardiovascular diseases by modulating serum cholesterol levels. Despite the well-documented efficacy of statins in reducing overall mortality via attenuating the risk of cardiovascular diseases, notable interindividual variability in therapeutic responses persists as such variability could compromise the lipid-lowering efficacy of the drug, potentially increasing susceptibility to adverse effects or attenuating therapeutic outcomes.This phenomenon has catalysed a growing interest in the scientific community to explore common genetic polymorphisms within genes that encode for pivotal enzymes within the pharmacokinetic pathways of statins. In our review, we focus to provide insight into potentially clinically relevant polymorphisms associated with statins' pharmacokinetic participants and assess their consequent implications on modulating the therapeutic outcomes of statins among distinct genetic carrier.

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.

Pharmacogenetics of statins treatment: Efficacy and safety

WHAT IS KNOWN AND OBJECTIVE

Statins are widely used worldwide in the prevention and treatment of coronary atherosclerotic heart disease and ischaemic stroke. However, in clinical application, statins have shown great individual differences in terms of the efficacy and safety, some of which are related to genetic factors. The purpose of this article was to summarize the recent advances about the correlation between gene polymorphisms and the efficacy/safety of statins.

METHODS

We searched the databases including PharmGKB and PubMed (published before June 2019) using the keywords such as 'statin', 'gene polymorphism' and 'SNP' and obtained more than 100 articles. In this review, we described the clinical studies of genetic variants associated with both the efficacy and adverse reactions of statins. We also clarified the importance of taking pharmacogenetic variation into account to improve the clinical application of statins.

RESULTS AND DISCUSSION

The available data were collected and analysed to present the polymorphisms of candidate genes encoding the most promising proteins including SLCO1B1 (encoding uptake transporters); ABCB1, ABCC2, ABCG2 (encoding effluent transporter); APOE, APOA5 (encoding apolipoprotein); genes encoding cytochrome P450 enzyme system; KIF6, HMGCR, LDLR, LPA, PCSK9, COQ2, CETP, etc These genes were proved to be related to the pharmacodynamics and pharmacokinetics of statins, thus affecting the efficacy and safety.

WHAT IS NEW AND CONCLUSION

In this paper, the correlation between gene polymorphisms and the efficacy/safety of statins was summarized. The authors reached a consensus that the variants of the genes encoding uptake and effluent transporters have the most effect on the efficacy/safety of statins. It pointed out that it is desirable to do genetic testing of these transporter genes to reduce the incidence of myopathy or to achieve better outcomes before patients use statins, especially in the regions with high frequency of risk allele.

Genetic polymorphisms of cytochrome P450 enzymes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 in the Croatian population

BACKGROUND

Data on the frequency of pharmacogenetic polymorphisms in the Croatian population are limited. We determined and analyzed frequencies for the most important CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 genetic variants in the Croatian population.

METHODS

2637 subjects were included. Genotyping was performed by real-time polymerase chain reaction (PCR) using TaqMan® DME or TaqMan® SNP Genotyping Assays, and by PCR, and PCR-RFLP analysis.

RESULTS

For CYP2C9, allele frequencies of *2 and *3 variant were 14.5% and 7.6%, respectively. Among them, 3.98% of subjects were predicted to be poor metabolizers. For CYP2C19, the most frequent variant alleles were *2 (14.8%), and *17 (23.7%), while 2.4% of subjects were predicted to be poor metabolizers, and 5.39% were homozygous carriers of *17 predicted to be ultrarapid metabolizers (UM). For CYP2D6, the frequencies of tested variant alleles were *3 (2.2%), *4 (17.4%), *5 (1%), *6 (1.1%), and *41 (10.8%). Out of these, 5.59% were predicted to be poor metabolizers, 3.19% were classified as UM while 1.0% were carriers of variant alleles duplications (undefined phenotype). For CYP3A4 allele frequencies of *1B and *22 variants were 1.4% and 2.7%, respectively. Allele frequency of CYP3A5*3 was 95.5%. Analyzing CYP3A cluster according to the combination of CYP3A4*22 and CYP3A5*3 revealed 5.34% of subjects to be poor metabolizers, while 8.66% were classified as extensive metabolizers.

CONCLUSIONS

The frequency of the CYP allelic variants, genotypes, and predicted phenotypes in the Croatian population is in accordance with the other European populations, between the values of published data for Middle European and Mediterranean populations.

Pharmacogenetic Foundations of Therapeutic Efficacy and Adverse Events of Statins

Background: In the era of precision medicine, more attention is paid to the search for predictive markers of treatment efficacy and tolerability. Statins are one of the classes of drugs that could benefit from this approach because of their wide use and their incidence of adverse events. Methods: Literature from PubMed databases and bibliography from retrieved publications have been analyzed according to terms such as statins, pharmacogenetics, epigenetics, toxicity and drug–drug interaction, among others. The search was performed until 1 October 2016 for articles published in English language. Results: Several technical and methodological approaches have been adopted, including candidate gene and next generation sequencing (NGS) analyses, the latter being more robust and reliable. Among genes identified as possible predictive factors associated with statins toxicity, cytochrome P450 isoforms, transmembrane transporters and mitochondrial enzymes are the best characterized. Finally, the solute carrier organic anion transporter family member 1B1 (SLCO1B1) transporter seems to be the best target for future studies. Moreover, drug–drug interactions need to be considered for the best approach to personalized treatment. Conclusions: Pharmacogenetics of statins includes several possible genes and their polymorphisms, but muscular toxicities seem better related to SLCO1B1 variant alleles. Their analysis in the general population of patients taking statins could improve treatment adherence and efficacy; however, the cost–efficacy ratio should be carefully evaluated.

Statin intolerance: diagnosis and remedies

Despite the efficacy of statins in reducing cardiovascular events in both primary and secondary prevention, the adherence to statin therapy is not optimal, mainly due to the occurrence of muscular adverse effects. Several risk factors may concur to the development of statin-induced myotoxicity, including patient-related factors (age, sex, and race), statin properties (dose, lipophilicity, and type of metabolism), and the concomitant administration of other drugs. Thus, the management of patients intolerant to statins, particularly those at high or very high cardiovascular risk, involves alternative therapies, including the switch to another statin or the use of intermittent dosage statin regimens, as well as nonstatin lipid lowering drugs (ezetimibe and fibrates) or new hypolipidemic drugs such as PCSK9 monoclonal antibodies, the antisense oligonucleotide against the coding region of human apolipoprotein B mRNA (mipomersen), and microsomal triglyceride transfer protein inhibitor lomitapide. Ongoing clinical trials will reveal whether the lipid-lowering effects of alternative therapies to statins can also translate into a cardiovascular benefit.

Seventeen years of statin pharmacogenetics: a systematic review

AIM

We evaluated the evidence of pharmacogenetic associations with statins in a systematic review.

METHODS

Two separate outcomes were considered of interest: modification of low-density lipoprotein cholesterol (LDL-C) response and modification of risk for cardiovascular events.

RESULTS

In candidate gene studies, 141 loci were claimed to be associated with LDL-C response. Only 5% of these associations were positively replicated. In addition, six genome-wide association studies of LDL-C response identified common SNPs in APOE, LPA, SLCO1B1, SORT1 and ABCG2 at genome-wide significance. None of the investigated SNPs consistently affected the risk reduction for cardiovascular events.

CONCLUSION

Only five genetic loci were consistently associated with LDL-C response. However, as effect sizes are modest, there is no evidence for the value of genetic testing in clinical practice.

The Rotterdam Study: 2016 objectives and design update

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in over 1200 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy ). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.

ABCG2 gene polymorphisms as risk factors for atorvastatin adverse reactions: a case-control study

AIM

To explore the association between dose-related adverse drug reactions (ADRs) of atorvastatin and polymorphisms of ABCG2, taking into account the influence of CYP3A4 and SLCO1B1 genes.

MATERIALS & METHODS

Sixty patients who experienced atorvastatin dose-related ADRs and 90 matched patients without ADRs were enrolled in the study. Genotyping for ABCG2 421C > A, CYP3A4*22, SLCO1B1 388A > G, SLCO1B1 521T > C variants was performed by real-time PCR.

RESULTS

Patients with ABCG2 421CA or AA genotypes had 2.9 times greater odds of developing atorvastatin dose-dependent ADRs (OR: 2.91; 95% CI: 1.22-6.95; p = 0.016) than those with ABCG2 421CC genotype. After adjustments for clinical and genetic risk factors, ABCG2 remained a statistically significant predictor of adverse drug reactions (OR: 2.75; 95% CI: 1.1-6.87; p = 0.03;). Also, carriers of SLCO1B1 521 TC or CC genotypes had 2.3 greater odds (OR: 1.03-4.98; 95% CI: 1.03-4.98; p = 0.043) of experiencing ADRs caused by atorvastatin in comparison with carriers of SLCO1B1 521 TT genotype.

CONCLUSION

Our study demonstrated an association between atorvastatin-induced ADRs and genetic variants in the ABCG2 gene.