Pharmacogenomics considerations in the control of hypertension

PTPRD gene variant rs10739150: A potential game-changer in hypertension diagnosis

BACKGROUND

High blood pressure, also known as hypertension (HTN), is a complicated disorder that is controlled by a complex network of physiological processes. Untreated hypertension is associated with increased death incidence, rise the need for understanding the genetic basis affecting hypertension susceptibility and development. The current study sought to identify the genetic association between twelve single nucleotide polymorphisms (SNPs) within seven candidate genes (NOS3, NOS1AP, REN, PLA2G4A, TCF7L, ADRB1, and PTPRD).

METHODS

The current study included 200 Jordanian individuals diagnosed with hypertension, compared to 224 healthy controls. Whole blood samples were drawn from each individual for DNA isolation and genotyping. The SNPStats tool was used to assess haplotype, genotype, and allele frequencies by the mean of chi-square (χ2).

RESULTS

Except for rs10739150 of PTPRD (P = 0.0003), the genotypic and allelic distribution of the SNP was identical between patients and controls. The prevalence of the G/G genotype in healthy controls (45.5%) was lower than in hypertension patients (64.3%), suggesting that it might be a risk factor for the disease. PTPRD TTC genetic haplotypes were strongly linked with hypertension (P = 0.003, OR = 4.03).

CONCLUSION

This study provides a comprehensive understanding of the involvement of rs10739150 within the PTPRD gene in hypertension. This new knowledge could potentially transform the way we approach hypertension diagnosis, providing an accurate diagnostic tool for classifying individuals who are at a higher risk of developing this condition.

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.

Computational and Pharmacogenomic Insights on Hypertension Treatment: Rational Drug Design and Optimization Strategies

Background::

Hypertension is a prevalent cardiovascular complication caused by genetic and nongenetic factors. Blood pressure (BP) management is difficult because most patients become resistant to monotherapy soon after treatment initiation. Although many antihypertensive drugs are available, some patients do not respond to multiple drugs. Identification of personalized antihypertensive treatments is a key for better BP management.

Objective::

This review aimed to elucidate aspects of rational drug design and other methods to develop better hypertension management.

Results::

Among hypertension-related signaling mechanisms, the renin-angiotensin-aldosterone system is the leading genetic target for hypertension treatment. Identifying a single drug that acts on multiple targets is an emerging strategy for hypertension treatment, and could be achieved by discovering new drug targets with less mutated and highly conserved regions. Extending pharmacogenomics research to include patients with hypertension receiving multiple antihypertensive drugs could help identify the genetic markers of hypertension. However, available evidence on the role of pharmacogenomics in hypertension is limited and primarily focused on candidate genes. Studies on hypertension pharmacogenomics aim to identify the genetic causes of response variations to antihypertensive drugs. Genetic association studies have identified single nucleotide polymorphisms affecting drug responses. To understand how genetic traits alter drug responses, computational screening of mutagenesis can be utilized to observe drug response variations at the protein level, which can help identify new inhibitors and drug targets to manage hypertension.

Conclusions::

Rational drug design facilitates the discovery and design of potent inhibitors. However, further research and clinical validation are required before novel inhibitors can be clinically used as antihypertensive therapies.

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.

Ion Channels in Drug Discovery and Safety Pharmacology

Ion channels are membrane proteins involved in almost all physiological processes, including neurotransmission, muscle contraction, pace-making activity, secretion, electrolyte and water balance, immune response, and cell proliferation. Due to their broad distribution in human body and physiological roles, ion channels are attractive targets for drug discovery and safety pharmacology. Over the years ion channels have been associated to many genetic diseases ("channelopathies"). For most of these diseases the therapy is mainly empirical and symptomatic, often limited by lack of efficacy and tolerability for a number of patients. The search for the development of new and more specific therapeutic approaches is therefore strongly pursued. At the same time acquired channelopathies or dangerous side effects (such as proarrhythmic risk) can develop as a consequence of drugs unexpectedly targeting ion channels. Several noncardiovascular drugs are known to block cardiac ion channels, leading to potentially fatal delayed ventricular repolarization. Thus, the search of reliable preclinical cardiac safety testing in early stage of drug discovery is mandatory. To fulfill these needs, both ion channels drug discovery and toxicology strategies are evolving toward comprehensive research approaches integrating ad hoc designed in silico predictions and experimental studies for a more reliable and quick translation of results to the clinic side.Here we discuss two examples of how the combination of in silico methods and patch clamp experiments can help addressing drug discovery and safety issues regarding ion channels.

Personalized medicine: Genetic risk prediction of drug response

Pharmacogenomics (PGx), a substantial component of "personalized medicine", seeks to understand each individual's genetic composition to optimize drug therapy -- maximizing beneficial drug response, while minimizing adverse drug reactions (ADRs). Drug responses are highly variable because innumerable factors contribute to ultimate phenotypic outcomes. Recent genome-wide PGx studies have provided some insight into genetic basis of variability in drug response. These can be grouped into three categories. [a] Monogenic (Mendelian) traits include early examples mostly of inherited disorders, and some severe (idiosyncratic) ADRs typically influenced by single rare coding variants. [b] Predominantly oligogenic traits represent variation largely influenced by a small number of major pharmacokinetic or pharmacodynamic genes. [c] Complex PGx traits resemble most multifactorial quantitative traits -- influenced by numerous small-effect variants, together with epigenetic effects and environmental factors. Prediction of monogenic drug responses is relatively simple, involving detection of underlying mutations; due to rarity of these events and incomplete penetrance, however, prospective tests based on genotype will have high false-positive rates, plus pharmacoeconomics will require justification. Prediction of predominantly oligogenic traits is slowly improving. Although a substantial fraction of variation can be explained by limited numbers of large-effect genetic variants, uncertainty in successful predictions and overall cost-benefit ratios will make such tests elusive for everyday clinical use. Prediction of complex PGx traits is almost impossible in the foreseeable future. Genome-wide association studies of large cohorts will continue to discover relevant genetic variants; however, these small-effect variants, combined, explain only a small fraction of phenotypic variance -- thus having limited predictive power and clinical utility.

Pharmacovigilance database search discloses ClC-K channels as a novel target of the AT1 receptor blockers valsartan and olmesartan

BACKGROUND AND PURPOSE

Human ClC-K chloride channels are highly attractive targets for drug discovery as they have a variety of important physiological functions and are associated with genetic disorders. These channels are crucial in the kidney as they control chloride reabsorption and water diuresis. In addition, loss-of-function mutations of CLCNKB and BSND genes cause Bartter's syndrome (BS), whereas CLCNKA and CLCNKB gain-of-function polymorphisms predispose to a rare form of salt sensitive hypertension. Both disorders lack a personalized therapy that is in most cases only symptomatic. The aim of this study was to identify novel ClC-K ligands from drugs already on the market, by exploiting the pharmacological side activity of drug molecules available from the FDA Adverse Effects Reporting System database.

EXPERIMENTAL APPROACH

We searched for drugs having a Bartter-like syndrome as a reported side effect, with the assumption that BS could be causatively related to the block of ClC-K channels. The ability of the selected BS-causing drugs to bind and block ClC-K channels was then validated through an integrated experimental and computational approach based on patch clamp electrophysiology in HEK293 cells and molecular docking simulations.

KEY RESULTS

Valsartan and olmesartan were able to block ClC-Ka channels and the molecular requirements for effective inhibition of these channels have been identified.

CONCLUSION AND IMPLICATIONS

These results suggest additional mechanisms of action for these sartans further to their primary AT₁ receptor antagonism and propose these compounds as leads for designing new potent ClC-K ligands.

Genome-Wide and Gene-Based Meta-Analyses Identify Novel Loci Influencing Blood Pressure Response to Hydrochlorothiazide

This study aimed to identify novel loci influencing the antihypertensive response to hydrochlorothiazide monotherapy. A genome-wide meta-analysis of blood pressure (BP) response to hydrochlorothiazide was performed in 1739 white hypertensives from 6 clinical trials within the International Consortium for Antihypertensive Pharmacogenomics Studies, making it the largest study to date of its kind. No signals reached genome-wide significance (P<5×10-8), and the suggestive regions (P<10-5) were cross-validated in 2 black cohorts treated with hydrochlorothiazide. In addition, a gene-based analysis was performed on candidate genes with previous evidence of involvement in diuretic response, in BP regulation, or in hypertension susceptibility. Using the genome-wide meta-analysis approach, with validation in blacks, we identified 2 suggestive regulatory regions linked to gap junction protein α1 gene (GJA1) and forkhead box A1 gene (FOXA1), relevant for cardiovascular and kidney function. With the gene-based approach, we identified hydroxy-delta-5-steroid dehydrogenase, 3 β- and steroid δ-isomerase 1 gene (HSD3B1) as significantly associated with BP response (P<2.28×10-4 ). HSD3B1 encodes the 3β-hydroxysteroid dehydrogenase enzyme and plays a crucial role in the biosynthesis of aldosterone and endogenous ouabain. By amassing all of the available pharmacogenomic studies of BP response to hydrochlorothiazide, and using 2 different analytic approaches, we identified 3 novel loci influencing BP response to hydrochlorothiazide. The gene-based analysis, never before applied to pharmacogenomics of antihypertensive drugs to our knowledge, provided a powerful strategy to identify a locus of interest, which was not identified in the genome-wide meta-analysis because of high allelic heterogeneity. These data pave the way for future investigations on new pathways and drug targets to enhance the current understanding of personalized antihypertensive treatment.