Pharmacogenomic approaches to study the effects of antihypertensive drugs

Screening and validation of double allele-specific binding F-primers for the measurement of antihypertensive pharmacogenomics

Objective

Previous studies have proposed that genetic polymorphisms of CYP2D6*10, ADRB1, NPPA, CYP3A5*3, ACE, CYP2C9*3, and AGTR1 are involved in antihypertensive pharmacogenomics. The purpose of this study is to develop an amplification analysis using double allele-specific (AS) binding primers for accurate measurement of antihypertensive pharmacogenomics.

Methods

To establish a quadruplex quantitative PCR (qPCR) analysis for genotyping of CYP2D6*10, ADRB1 (1165 G>C), NPPA (2238 T>C) and CYP3A5*3, and a triplex qPCR analysis for genotyping of ACE (I/D), CYP2C9*3 and AGTR1 (1166 A>C), mismatch AS F-primers were screened by detection of plasmid/gDNA, and were validated by agreement analysis/reproducibility evaluation, in which the ΔCq (differences in threshold cycles between the wild-type F-primer-based amplification assay and the mutant-type F-primer-based amplification assay) was employed to determine genotypes.

Results

Seven pairs of primers were successfully selected through three rounds of F-primers screening. Except for ADRB1, the robustness assessment showed the amplification efficiency ranging from 0.9 to 1.1. In agreement analysis, two specimens in the training set (n = 203) were defined by the triplex analysis rather than NGS as heterozygotes for ACE, which was evidenced by gel electrophoresis. Reproducibility evaluation demonstrated that the coefficient of variation (CV) was <5%.

Conclusion

Multiplex amplification analysis using screened AS binding primers is a simple, reliable, and accurate tool to guide drug delivery in antihypertensive personalized treatment.

Enzymatic activity on valsartan of 38 CYP2C9 variants from the Chinese population

BACKGROUND AND OBJECTIVE

Valsartan is widely used for the treatment of moderate hypertension. However, previous studies have found that efficacy of the valsartan depends on the dose and intake. Cytochrome P450 (CYP) 2C9 metabolizes ∼15% of the clinical drugs. Genetic polymorphisms of CYP2C9 markedly affect the safety and effectiveness of many drugs, which might lead to adverse reactions and therapeutic failure. Twenty-four novel CYP2C9 variants (*36-*60) had been previously discovered via gene sequencing in the Han population. Our study aims to evaluate the impact of 38 CYP2C9 variants from the Chinese population on valsartan metabolism compared with CYP2C9*1 in vitro.

METHODS

Wild-type CYP2C9*1 and other CYP2C9 variants were expressed in Spodoptera frugiperda 21 insect cells. Incubations were performed at 37 °C with 20-2000 μM substrate for 30 min. The metabolite 4-OH valsartan was determined via UPLC-MS/MS.

RESULTS

Among the 38 CYP2C9 variants, the enzymatic activities of most variants were significantly altered compared with the wild-type. Three variants (CYP2C9*27, *40 and *49) exhibited increased intrinsic clearance values (134-153% relative clearance). However, 12 variants (CYP *8, *13, *16, *19, *33, *36, *42, *43, *45, *52, *54, *58) caused >90% decreases in the relative clearance of valsartan compared to CYP2C9*1.

CONCLUSIONS

Our research provides systematic data for evaluating the effects of CYP2C9 variants on valsartan metabolism in the Chinese population. These results will expand our understanding of the impact of CYP2C9 genetic polymorphisms on valsartan metabolism and will contribute to precision medicine.

Pharmacogenomics And Hypertension: Current Insights

Hypertension is a multifactorial disease that affects approximately one billion subjects worldwide and is a major risk factor associated with cardiovascular events, including coronary heart disease and cerebrovascular accidents. Therefore, adequate blood pressure control is important to prevent these events, reducing premature mortality and disability. However, only one third of patients have the effective control of blood pressure, despite several classes of antihypertensive drugs available. These disappointing outcomes may be at least in part explained by interpatient variability in drug response due to genetic polymorphisms. To address the effects of genetic polymorphisms on blood pressure responses to the antihypertensive drug classes, studies have applied candidate genes and genome wide approaches. More recently, a third approach that considers gene-gene interactions has also been applied in hypertension pharmacogenomics. In this article, we carried out a comprehensive review of recent findings on the pharmacogenomics of antihypertensive drugs, including diuretics, β-blockers, angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, and calcium channel blockers. We also discuss the limitations and inconsistences that have been found in hypertension pharmacogenomics and the challenges to implement this valuable approach in clinical practice.

Genome-wide response to antihypertensive medication using home blood pressure measurements: a pilot study nested within the HOMED-BP study

BACKGROUND

Patients with mild-to-moderate essential hypertension in the HOMED-BP trial were randomly allocated to first-line treatment with a calcium channel blocker (CCB), angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II receptor blocker (ARB).

METHODS

We recruited 265 (93 for CCB, 71 for ACEI and 101 for ARB) patients who completed the genomic study. Home blood pressure was measured for 5 days off-treatment before randomization and for 5 days after 2-4 weeks of randomized drug treatment. Genotyping was performed by 500K DNA microarray chips. The blood pressure responses to the three drugs were analyzed separately as a quantitative trait. For replication of SNPs with p < 10(-4), we used the multicenter GEANE study, in which patients were randomized to valsartan or amlodipine.

RESULTS

SNPs in PICALM, TANC2, NUMA1 and APCDD1 were found to be associated with CCB responses and those in ABCC9 and YIPF1 were found to be associated with ARB response with replication.

CONCLUSION

Our approach, the first based on high-fidelity phenotyping by home blood pressure measurement, might be a step in moving towards the personalized treatment of hypertension.

[Cardiovascular pharmacogenomics]

Cardiovascular disease remains a major cause of morbidity and mortality worldwide. Current medical practice takes into account information based on population studies and benefits observed in large populations or cohorts. However, individual patients present great differences in both toxicity and clinical efficacy that can be explained by variations in adherence, unknown drug to drug interactions and genetic variability. The latter seems to explain from 20% up to 95% of patient to patient variability. Treating patients with cardiovascular disorders faces the clinician with the challenge to include genomic analysis into daily practice. There are several examples within cardiovascular disease of treatments that can vary in toxicity or clinical usefulness based on genetic changes. One of the main factors affecting the efficacy of Clopidogrel is the phenotype associated with polymorphisms in the gene CYP 2C9. Furthermore, regarding oral anticoagulants, changes in CYP2C9 and VKORC1 play an important role in changing the clinical response to anticoagulation. When analyzing statin treatment, one of their main toxicities (myopathy) can be predicted by the SLCO1B1 polymorphism. The potential for prediction of toxicity and clinical efficacy from the use of genetic analysis warrants further studies aiming towards its inclusion in daily clinical practice.

Human pharmacogenomic variation of antihypertensive drugs: from population genetics to personalized medicine

Aim: To investigate the human pharmacogenetic variation related to antihypertensive drugs, providing a survey of functional interpopulation differences in hypertension pharmacogenes. Materials & methods: The study was divided into two stages. In the first stage, we analyzed 1249 variants located in 57 hypertension pharmacogenes. This first-stage analysis confirmed that geographic origin strongly affects hypertension pharmacogenomic variation and that 31 pharmacogenes are geographically differentiated. In the second stage, we focused our attention on the ethnic-differentiated pharmacogenes, investigating 55,521 genetic variants. In silico analyses were performed to predict the effect of genetic variation. Results: Our analyses indicated functional interpopulation differences, suggesting insight into the mechanisms of antihypertensive drug response. Moreover, our data suggested that rare variants mainly determine the functionality of genes related to antihypertensive drugs. Conclusion: Our study provided important knowledge about the genetics of the antihypertensive drug response, suggesting that next-generation sequencing technologies may develop reliable pharmacogenetic tests for antihypertensive drugs.

Original submitted 19 September 2013; Revision submitted 14 November 2013