Simvastatin intolerance genetic determinants: some features in ethnic Uzbek patients with coronary artery disease

Pharmacogenomics-based systematic review of coronary artery disease based on personalized medicine procedure

Background

Coronary artery disease (CAD) is the most common reason for mortality and disability-adjusted life years (DALYs) lost globally. This study aimed to suggest a new gene list for the treatment of CAD by a systematic review of bioinformatics analyses of pharmacogenomics impacts of potential genes and variants.

Methods

PubMed search was filtered by the title including Coronary Artery Disease during 2020-2023. To find the genes with pharmacogenetic impact on the CAD, additional filtrations were considered according to the variant annotations. Protein-Protein Interactions (PPIs), Gene-miRNA Interactions (GMIs), Protein-Drug Interactions (PDIs), and variant annotation assessments (VAAs) performed by STRING-MODEL (ver. 12), Cytoscape (ver. 3.10), miRTargetLink.2., NetworkAnalyst (ver 0.3.0), and PharmGKB.

Results

Results revealed 5618 publications, 1290 papers were qualified, and finally, 650 papers were included. 4608 protein-coding genes were extracted, among them, 1432 unique genes were distinguished and 530 evidence-based repeated genes remained. 71 genes showed a pharmacogenetics-related variant annotation in at least (entirely 6331 annotations). Variant annotation assessment (VAA) showed 532 potential variants for the final report, and finally, the concluding PGs list represented 175 variants. Based on the function and MAF, 57 nonsynonymous variants of 29 Pharmacogenomics-related genes were associated with CAD.

Conclusion

Conclusively, evaluating circulating miR33a in individuals' plasma with CAD, and genotyping of rs2230806, rs2230808, rs2487032, rs12003906, rs2472507, rs2515629, and rs4149297 (ABCA1 variants) lead to precisely prescribing of well-known drugs. Also, the findings of this review can be used in both whole-genome sequencing (WGS) and whole-exome sequencing (WES) analysis in the prognosis and diagnosis of CAD.

Impacts of ABCG2 loss of function variant (p. Gln141Lys, c.421 C > A, rs2231142) on lipid levels and statin efficiency: a systematic review and meta-analysis

BACKGROUND

The latest evidence indicates that ATP-binding cassette superfamily G member 2 (ABCG2) is critical in regulating lipid metabolism and mediating statin or cholesterol efflux. This study investigates whether the function variant loss within ABCG2 (rs2231142) impacts lipid levels and statin efficiency.

METHODS

PubMed, Cochrane Library, Central, CINAHL, and ClinicalTrials.gov were searched until November 18, 2023.

RESULTS

Fifteen studies (34,150 individuals) were included in the analysis. The A allele [Glu141Lys amino acid substitution was formed by a transversion from cytosine (C) to adenine (A)] of rs2231142 was linked to lower levels of high-density lipoprotein cholesterol (HDL-C), and higher levels of low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC). In addition, the A allele of rs2231142 substantially increased the lipid-lowering efficiency of rosuvastatin in Asian individuals with dyslipidemia. Subgroup analysis indicated that the impacts of rs2231142 on lipid levels and statin response were primarily in Asian individuals.

CONCLUSIONS

The ABCG2 rs2231142 loss of function variant significantly impacts lipid levels and statin efficiency. Preventive use of rosuvastatin may prevent the onset of coronary artery disease (CAD) in Asian individuals with dyslipidemia.

Pharmacogenomics of lipid-lowering agents: the impact on efficacy and safety

Hyperlipidemia is a significant risk factor for cardiovascular disease morbidity and mortality. The lipid-lowering drugs are considered the cornerstone of primary and secondary prevention of atherosclerotic cardiovascular disease. Unfortunately, the lack of efficacy and associated adverse effects, ranging from mild-to-moderate to potentially life-threatening, lead to therapy discontinuation. Numerous reports support the role of gene polymorphisms in drugs' pharmacokinetic parameters and their associated adverse reactions. Therefore, this study aims to understand the pharmacogenomics of lipid-lowering drugs and the impact of genetic variants of key genes on the drugs' efficacy and toxicity. Indeed, genetically guided lipid-lowering therapy enhances overall safety, improves drug adherence and achieves long-term therapy.

Admixture Has Shaped Romani Genetic Diversity in Clinically Relevant Variants

Genetic patterns of inter-population variation are a result of different demographic and adaptive histories, which gradually shape the frequency distribution of the variants. However, the study of clinically relevant mutations has a Eurocentric bias. The Romani, the largest transnational minority ethnic group in Europe, originated in South Asia and received extensive gene flow from West Eurasia. Most medical genetic studies have only explored founder mutations related to Mendelian disorders in this population. Here we analyze exome sequences and genome-wide array data of 89 healthy Spanish Roma individuals to study complex traits and disease. We apply a different framework and focus on variants with both increased and decreased allele frequencies, taking into account their local ancestry. We report several OMIM traits enriched for genes with deleterious variants showing increased frequencies in Roma or in non-Roma (e.g., obesity is enriched in Roma, with an associated variant linked to South Asian ancestry; while non-insulin dependent diabetes is enriched in non-Roma Europeans). In addition, previously reported pathogenic variants also show differences among populations, where some variants segregating at low frequency in non-Roma are virtually absent in the Roma. Lastly, we describe frequency changes in drug-response variation, where many of the variants increased in Roma are clinically associated with metabolic and cardiovascular-related drugs. These results suggest that clinically relevant variation in Roma cannot only be characterized in terms of founder mutations. Instead, we observe frequency differences compared to non-Roma: some variants are absent, while other have drifted to higher frequencies. As a result of the admixture events, these clinically damaging variants can be traced back to both European and South Asian-related ancestries. This can be attributed to a different prevalence of some genetic disorders or to the fact that genetic susceptibility variants are mostly studied in populations of European descent, and can differ in individuals with different ancestries.

Robust Performance of Potentially Functional SNPs in Machine Learning Models for the Prediction of Atorvastatin-Induced Myalgia

Statins can cause muscle symptoms resulting in poor adherence to therapy and increased cardiovascular risk. We hypothesize that combinations of potentially functional SNPs (pfSNPs), rather than individual SNPs, better predict myalgia in patients on atorvastatin. This study assesses the value of potentially functional single nucleotide polymorphisms (pfSNPs) and employs six machine learning algorithms to identify the combination of SNPs that best predict myalgia.

Methods: Whole genome sequencing of 183 Chinese, Malay and Indian patients from Singapore was conducted to identify genetic variants associated with atorvastatin induced myalgia. To adjust for confounding factors, demographic and clinical characteristics were also examined for their association with myalgia. The top factor, sex, was then used as a covariate in the whole genome association analyses. Variants that were highly associated with myalgia from this and previous studies were extracted, assessed for potential functionality (pfSNPs) and incorporated into six machine learning models. Predictive performance of a combination of different models and inputs were compared using the average cross validation area under ROC curve (AUC). The minimum combination of SNPs to achieve maximum sensitivity and specificity as determined by AUC, that predict atorvastatin-induced myalgia in most, if not all the six machine learning models was determined.

Results: Through whole genome association analyses using sex as a covariate, a larger proportion of pfSNPs compared to non-pf SNPs were found to be highly associated with myalgia. Although none of the individual SNPs achieved genome wide significance in univariate analyses, machine learning models identified a combination of 15 SNPs that predict myalgia with good predictive performance (AUC >0.9). SNPs within genes identified in this study significantly outperformed SNPs within genes previously reported to be associated with myalgia. pfSNPs were found to be more robust in predicting myalgia, outperforming non-pf SNPs in the majority of machine learning models tested.

Conclusion: Combinations of pfSNPs that were consistently identified by different machine learning models to have high predictive performance have good potential to be clinically useful for predicting atorvastatin-induced myalgia once validated against an independent cohort of patients.

Personalized rosuvastatin therapy in problem patients with partial statin intolerance

Introduction

The aim was to study the pharmacogenetic determinants of switching simvastatin-intolerant ethnic Uzbek patients with coronary artery disease (CAD) to rosuvastatin treatment.

Material and methods

The study included 50 patients with CAD, who demonstrated statin-induced adverse liver symptoms, accompanied by an elevation in transaminase level (3-fold or more in 37 cases) or statin-induced adverse muscle symptoms, accompanied by elevations in serum (CK > 3 times above the upper limit of normal (ULN)) in simvastatin treatment with a dose of 10-20 mg/day. The control group consisted of 50 patients without side effects. Patients were genotyped for polymorphisms in the genes coding for the cytochrome P450 (CYP) metabolic enzymes CYP3A5(6986A>G), CYP2C9(430C>T), CYP2C9(1075A>C), and hepatic influx and efflux transporters SLCO1B1(521T>C) and BCRP(ABCG2, 421C>A) by means of the PCR-RFLP method.

Results

When the 50 patients of the case group were switched to the starting rosuvastatin dose of 5 mg, intolerance symptoms were not observed in 29 (58%) versus 21 with adverse symptoms. In this case-control study, the groups differed significantly only in the prevalence of the *3/*3 genotype CYP3A5 (OR = 5.25; 95% CI: 1.6-17.8; p = 0.014).

Conclusions

In a considerable proportion of ethnic Uzbek patients with CAD and simvastatin intolerance symptoms, serious side effects when switching to a starting dose of rosuvastatin were not observed, and it should be noted that in most cases (72.4%) this phenomenon was observed among the carriers of *3/*3 genotype of the CYP3A5 (6986A> G) gene.