Pharmacogenomics in acute coronary syndrome

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.

β1-adrenergic receptor polymorphisms: a possible genetic predictor of bisoprolol response in acute coronary syndrome

Aim

To investigate the association between beta1-adrenergic receptor (ADRB1) polymorphisms and response to bisoprolol treatment in beta-blocker naive patients with acute coronary syndrome (ACS).

Patients & methods

Seventy-seven patients received bisoprolol for four weeks. Blood pressure and heart rate were measured at baseline and during treatment. TaqMan allelic discrimination method was utilized for ADRB1 Ser49Gly and Arg389Gly genotyping.

Results

Arg389Arg carriers showed greater reductions in systolic and diastolic blood pressure (-8.5% ± 7.8% vs -0.76% ± 8.7%, p = 0.000218), and (-9.5% ± 9.7% vs -0.80% ± 11.5%, p = 0.000149), respectively, compared with Gly389 carriers. No statistical difference was found for study's outcomes based on codon 49.

Conclusion

Arg389Gly polymorphism is a promising bisoprolol response predictor in ACS patients.

Meta-analysis of the association between Apolipoprotein E polymorphism and risks of myocardial infarction

BACKGROUND

Myocardial infarction (MI) remains the leading cause of death and disability among cardiovascular diseases worldwide. Studies show that elevated low-density lipid protein cholesterol (LDL-C) levels confer the highest absolute risk of MI, and Apolipoprotein E (ApoE) is implicated in regulating levels of triglycerides (TGs), cholesterol, and LDL-C. Our study aimed to evaluate the association between APOE polymorphism and MI, and to provide evidence for the etiology of MI.

METHODS

Case-control studies on the association between APOE polymorphisms and the risk of myocardial infarction were included by searching PubMed, Web of Science, and CNKI, and this meta-analysis was written in accordance with PRISMA guideline statement. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using either random-effects or fixed-effects models by R software.

RESULTS

A total of 33 eligible articles involving 13,706 cases and 14,817 controls were finally selected. The pooled analysis based on the total eligible articles showed that the risk of MI was associated with ApoE epsilon 2 and epsilon 4 alleles. The results showed that patients with MI had a low frequency of the ε2 allele (OR 0.74, 95% CI 0.64-0.86) and a high frequency of the ε4 allele (OR 1.24, 95% CI 1.09-1.42).

CONCLUSIONS

APOE ε2-involved genotypes may be protective factors for MI; in contrast, ε4-involved genotypes (ε4/ε3 vs. ε3/ε3, and ε4/ε4 vs. ε3/ε3) may be risk factors for MI.