Pharmacogenomics And Hypertension: Current Insights

Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications

Electronic health records (EHRs) coupled with large-scale biobanks offer great promises to unravel the genetic underpinnings of treatment efficacy. However, medication-induced biomarker trajectories stemming from such records remain poorly studied. Here, we extract clinical and medication prescription data from EHRs and conduct GWAS and rare variant burden tests in the UK Biobank (discovery) and the All of Us program (replication) on ten cardiometabolic drug response outcomes including lipid response to statins, HbA1c response to metformin and blood pressure response to antihypertensives (N = 740-26,669). Our findings at genome-wide significance level recover previously reported pharmacogenetic signals and also include novel associations for lipid response to statins (N = 26,669) near LDLR and ZNF800. Importantly, these associations are treatment-specific and not associated with biomarker progression in medication-naive individuals. Furthermore, we demonstrate that individuals with higher genetically determined low-density and total cholesterol baseline levels experience increased absolute, albeit lower relative biomarker reduction following statin treatment. In summary, we systematically investigated the common and rare pharmacogenetic contribution to cardiometabolic drug response phenotypes in over 50,000 UK Biobank and All of Us participants with EHR and identified clinically relevant genetic predictors for improved personalized treatment strategies.

Single nucleotide polymorphism (SNP) rs4291 of the angiotensin-converting enzyme (ACE) gene is associated with the response to losartan treatment in hypertensive patients

Arterial hypertension is characterized by systolic pressure ≥ 140 mmHg and/or diastolic pressure ≥ 90 mmHg and its treatment consists of the use of antihypertensive drugs, as losartan and hydrochlorothiazide. Blood pressure is regulated by angiotensin-converting enzyme (ACE) and polymorphisms in the ACE gene are associated to a greater predisposition to hypertension and response to treatment. The aim of this study was to evaluate the association of genetic polymorphisms of ACE rs4363, rs4291 and rs4335 and the response to antihypertensive drugs in hypertensive patients from Ouro Preto/MG, Brazil. A case-control study was carried out with 87 hypertensive patients being treated with losartan and 75 with hydrochlorothiazide, who answered a questionnaire and had blood samples collected. Biochemical analyzes were performed on serum using UV/Vis spectrophotometry and identification of ACE variants rs4363, rs4291 and rs4335 was performed by real-time PCR using the TaqMan® system. Univariate logistic regression test was performed to compare categorical data in STATA 13.0 software. The results showed that there was an influence of ACE polymorphisms on the response to losartan, demonstrating that AT or TT genotypes of rs4291 were more frequent in the group of controlled AH (54.9%), indicating that these individuals are 2.8 times more likely to of being controlled AH (95% CI 1.12-6.80, p. =0.026) compared to those with AA genotype. In contrast, no influence of ACE polymorphisms on the response to hydrochlorothiazide was observed. In conclusion, the presence of the T allele of the rs4291 variant was associated to controled blood pressure when losartan was used as an antihypertensive agent. These results show the importance of pharmacogenetic studies to detect genetic characteristics, enabling therapeutic individuality and reducing costs for the healthcare system.

Maternally Inherited Essential Hypertension May Be Associated with the Mutations in Mitochondrial tRNAGlu Gene

Background

Mitochondrial DNA (mtDNA) mutations are associated with essential hypertension (EH), but the molecular mechanism remains largely unknown.

Objective

The aim of this study is to explore the association between mtDNA mutations and EH.

Methods

Two maternally inherited families with EH are underwent clinical, genetic and biochemical assessments. mtDNA mutations are screened by PCR-Sanger sequencing and phylogenetic, and bioinformatics analyses are performed to evaluate the pathogenicity of mtDNA mutations. We also generate cytoplasmic hybrid (cybrid) cell lines to analysis mitochondrial functions.

Results

Matrilineal relatives exhibit variable degree of clinical phenotypes. Molecular analysis reveals the presence of m.A14693G and m.A14696G mutations in two pedigrees. Notably, the m.A14693G mutation occurs at position 54 in the TψC loop of tRNAGlu, a position which is critical for post-transcriptionally modification of tRNAGlu. While the m.A14696G mutation creates a novel base-pairing (51C-64G). Bioinformatic analysis shows that these mutations alter tRNAGlu secondary structure. Additionally, patients with tRNAGlu mutations exhibit markedly decreased in mtDNA copy number, mitochondrial membrane potential (MMP) and ATP, whereas the levels of reactive oxygen species (ROS) increase significantly.

Conclusion

The m.A14696G and m.A14693G mutations lead to failure in tRNAGlu metabolism and cause mitochondrial dysfunction that is responsible for EH.

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.

Physiologically based pharmacokinetic (PBPK) modeling to predict the pharmacokinetics of irbesartan in different CYP2C9 genotypes

Irbesartan, a potent and selective angiotensin II type-1 (AT1) receptor blocker (ARB), is one of the representative medications for the treatment of hypertension. Cytochrome P450 (CYP) 2C9 is primarily involved in the oxidation of irbesartan. CYP2C9 is highly polymorphic, and genetic polymorphism of this enzyme is the leading cause of significant alterations in the pharmacokinetics of irbesartan. This study aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of irbesartan in different CYP2C9 genotypes. The irbesartan PBPK model was established using the PK-Sim® software. Our previously reported pharmacogenomic data for irbesartan was leveraged in the development of the PBPK model and collected clinical pharmacokinetic data for irbesartan was used for the validation of the model. Physicochemical and ADME properties of irbesartan were obtained from previously reported data, predicted by the modeling software, or optimized to fit the observed plasma concentration-time profiles. Model evaluation was performed by comparing the predicted plasma concentration-time profiles and pharmacokinetic parameters to the observed results. Predicted plasma concentration-time profiles were visually similar to observed profiles. Predicted AUCinf in CYP2C9*1/*3 and CYP2C9*1/*13 genotypes were increased by 1.54- and 1.62-fold compared to CYP2C9*1/*1 genotype, respectively. All fold error values for AUC and Cmax in non-genotyped and CYP2C9 genotyped models were within the two-fold error criterion. We properly established the PBPK model of irbesartan in different CYP2C9 genotypes. It can be used to predict the pharmacokinetics of irbesartan for personalized pharmacotherapy in individuals of various races, ages, and CYP2C9 genotypes.

Antihypertensives associated adverse events: a review of mechanisms and pharmacogenomic biomarkers available evidence in multi-ethnic populations

Hypertension remains a significant health burden worldwide, re-emphasizing the outstanding need for more effective and safer antihypertensive therapeutic approaches. Genetic variation contributes significantly to interindividual variability in treatment response and adverse events, suggesting pharmacogenomics as a major approach to optimize such therapy. This review examines the molecular mechanisms underlying antihypertensives-associated adverse events and surveys existing research on pharmacogenomic biomarkers associated with these events. The current literature revealed limited conclusive evidence supporting the use of genetic variants as reliable indicators of antihypertensive adverse events. However, several noteworthy associations have emerged, such as 1) the role of ACE variants in increasing the risk of multiple adverse events, 2) the bradykinin pathway's involvement in cough induced by ACE inhibitors, and 3) the impact of CYP2D6 variants on metoprolol-induced bradycardia. Nonetheless, challenges persist in identifying biomarkers for adverse events across different antihypertensive classes, sometimes due to the rarity of certain events, such as ACE inhibitors-induced angioedema. We also highlight the main limitations of previous studies that warrant attention, including using a targeted gene approach with a limited number of tested variants, small sample sizes, and design issues such as overlooking doses or the time between starting treatment and the onset of adverse events. Addressing these challenges requires collaborative efforts and the integration of technological advancements, such as next-generation sequencing, which can significantly enhance research outcomes and provide the needed evidence. Furthermore, the potential combination of genomic biomarker identification and machine learning is a promising approach for tailoring antihypertensive therapy to individual patients, thereby mitigating the risk of developing adverse events. In conclusion, a deeper understanding of the mechanisms and the pharmacogenomics of adverse events in antihypertensive therapy will likely pave the way for more personalized treatment strategies to improve patient outcomes.

Pharmacogenomics of Hypertension in Africa: Paving the Way for a Pharmacogenetic-Based Approach for the Treatment of Hypertension in Africans

In Africa, the burden of hypertension has been rising at an alarming rate for the last two decades and is a major cause for cardiovascular disease (CVD) mortality and morbidity. Hypertension is characterised by elevated blood pressure (BP) ≥ 140/90 mmHg. Current hypertension guidelines recommend the use of antihypertensives belonging to the following classes: calcium channel blockers (CCB), angiotensin converting inhibitors (ACEI), angiotensin receptor blockers (ARB), diuretics, β-blockers, and mineralocorticoid receptor antagonists (MRAs), to manage hypertension. Still, a considerable number of hypertensives in Africa have their BP uncontrolled due to poor drug response and remain at the risk of CVD events. Genetic factors are a major contributing factor, accounting for 20% to 80% of individual variability in therapy and poor response. Poor response to antihypertensive drug therapy is characterised by elevated BPs and occurrence of adverse drug reactions (ADRs). As a result, there have been numerous studies which have examined the role of genetic variation and its influence on antihypertensive drug response. These studies are predominantly carried out in non-African populations, including Europeans and Asians, with few or no Africans participating. It is important to note that the greatest genetic diversity is observed in African populations as well as the highest prevalence of hypertension. As a result, this warrants a need to focus on how genetic variation affects response to therapeutic interventions used to manage hypertension in African populations. In this paper, we discuss the implications of genetic diversity in CYP11B2, GRK4, NEDD4L, NPPA, SCNN1B, UMOD, CYP411, WNK, CYP3A4/5, ACE, ADBR1/2, GNB3, NOS3, B2, BEST3, SLC25A31, LRRC15 genes, and chromosome 12q loci on hypertension susceptibility and response to antihypertensive therapy. We show that African populations are poorly explored genetically, and for the few characterised genes, they exhibit qualitative and quantitative differences in the profile of pharmacogene variants when compared to other ethnic groups. We conclude by proposing prioritization of pharmacogenetics research in Africa and possible adoption of pharmacogenetic-guided therapies for hypertension in African patients. Finally, we outline the implications, challenges, and opportunities these studies present for populations of non-European descent.

PSnpBind-ML: predicting the effect of binding site mutations on protein-ligand binding affinity

Protein mutations, especially those which occur in the binding site, play an important role in inter-individual drug response and may alter binding affinity and thus impact the drug's efficacy and side effects. Unfortunately, large-scale experimental screening of ligand-binding against protein variants is still time-consuming and expensive. Alternatively, in silico approaches can play a role in guiding those experiments. Methods ranging from computationally cheaper machine learning (ML) to the more expensive molecular dynamics have been applied to accurately predict the mutation effects. However, these effects have been mostly studied on limited and small datasets, while ideally a large dataset of binding affinity changes due to binding site mutations is needed. In this work, we used the PSnpBind database with six hundred thousand docking experiments to train a machine learning model predicting protein-ligand binding affinity for both wild-type proteins and their variants with a single-point mutation in the binding site. A numerical representation of the protein, binding site, mutation, and ligand information was encoded using 256 features, half of them were manually selected based on domain knowledge. A machine learning approach composed of two regression models is proposed, the first predicting wild-type protein-ligand binding affinity while the second predicting the mutated protein-ligand binding affinity. The best performing models reported an RMSE value within 0.5 [Formula: see text] 0.6 kcal/mol^-1 on an independent test set with an R² value of 0.87 [Formula: see text] 0.90. We report an improvement in the prediction performance compared to several reported models developed for protein-ligand binding affinity prediction. The obtained models can be used as a complementary method in early-stage drug discovery. They can be applied to rapidly obtain a better overview of the ligand binding affinity changes across protein variants carried by people in the population and narrow down the search space where more time-demanding methods can be used to identify potential leads that achieve a better affinity for all protein variants.

Tackling Atherosclerosis via Selected Nutrition

The development and pathogenesis of atherosclerosis are significantly influenced by lifestyle, particularly nutrition. The modern level of science and technology development promote personalized nutrition as an efficient preventive measure against atherosclerosis. In this survey, the factors were revealed that contribute to the formation of an individual approach to nutrition: genetic characteristics, the state of the microbiota of the gastrointestinal tract (GIT) and environmental factors (diets, bioactive components, cardioprotectors, etc.). In the course of the work, it was found that in order to analyze the predisposition to atherosclerosis associated with nutrition, genetic features affecting the metabolism of nutrients are significant. The genetic features include the presence of single nucleotide polymorphisms (SNP) of genes and epigenetic factors. The influence of telomere length on the pathogenesis of atherosclerosis and circadian rhythms was also considered. Relatively new is the study of the relationship between chrono-nutrition and the development of metabolic diseases. That is, to obtain the relationship between nutrition and atherosclerosis, a large number of genetic markers should be considered. In this relation, the question arises: “How many genetic features need to be analyzed in order to form a personalized diet for the consumer?” Basically, companies engaged in nutrigenetic research and choosing a diet for the prevention of a number of metabolic diseases use SNP analysis of genes that accounts for lipid metabolism, vitamins, the body’s antioxidant defense system, taste characteristics, etc. There is no set number of genetic markers. The main diets effective against the development of atherosclerosis were considered, and the most popular were the ketogenic, Mediterranean, and DASH-diets. The advantage of these diets is the content of foods with a low amount of carbohydrates, a high amount of vegetables, fruits and berries, as well as foods rich in antioxidants. However, due to the restrictions associated with climatic, geographical, material features, these diets are not available for a number of consumers. The way out is the use of functional products, dietary supplements. In this approach, the promising biologically active substances (BAS) that exhibit anti-atherosclerotic potential are: baicalin, resveratrol, curcumin, quercetin and other plant metabolites. Among the substances, those of animal origin are popular: squalene, coenzyme Q10, omega-3. For the prevention of atherosclerosis through personalized nutrition, it is necessary to analyze the genetic characteristics (SNP) associated with the metabolism of nutrients, to assess the state of the microbiota of the GIT. Based on the data obtained and food preferences, as well as the individual capabilities of the consumer, the optimal diet can be selected. It is topical to exclude nutrients of which their excess consumption stimulates the occurrence and pathogenesis of atherosclerosis and to enrich the diet with functional foods (FF), BAS containing the necessary anti-atherosclerotic, and stimulating microbiota of the GIT nutrients. Personalized nutrition is a topical preventive measure and there are a number of problems hindering the active use of this approach among consumers. The key factors include weak evidence of the influence of a number of genetic features, the high cost of the approach, and difficulties in the interpretation of the results. Eliminating these deficiencies will contribute to the maintenance of a healthy state of the population through nutrition.

Dissecting the Polygenic Basis of Primary Hypertension: Identification of Key Pathway-Specific Components

Introduction and Objectives

Genome-wide association studies have identified a high number of genetic loci associated with hypertension suggesting the presence of an underlying polygenic architecture. In this study, we aimed to dissect the polygenic component of primary hypertension searching also for pathway-specific components.

Methods

The polygenic risk score (PRS) models, based on the UK biobank genetic signals for hypertension status, were obtained on a target Italian case/control cohort including 561 cases and 731 hyper-normal controls from HYPERGENES, and were then applied to an independent validation cohort composed by multi-countries European-based samples including 1,284 cases and 960 hyper-normal controls.

Results

The resulting genome-wide PRS was capable of stratifying the individuals for hypertension risk by comparing between individuals in the last PRS decile and the median decile: we observed an odds ratio (OR) of 3.62, CI = [2.01, 6.32] (P = 9.01E-07) and 3.22, 95% CI = [2.06, 5.10] (P = 6.47E-08) in the target and validation cohorts, respectively. The relatively high case/control ORs across PRS quantiles corroborates the presence of strong polygenic components which could be driven by an enrichment of risk alleles within the cases but also by potential enrichment of protective alleles in the old normotensive controls. Moreover, novel pathway-specific PRS revealed an enrichment of the polygenic signal attributable to specific biological pathways. Among those the most significantly associated with hypertension status was the calcium signaling pathway together with other mainly related such as the phosphatidylinositol/inositol phosphate pathways.

Conclusions

The development of pathway-specific PRS could prioritize biological mechanisms, according to their contribution to the genetic susceptibility, whose regulations might be a potential pharmacological preventive target.

Warfarin Pharmacogenomics for Precision Medicine in Real-Life Clinical Practice in Southern Africa: Harnessing 73 Variants in 29 Pharmacogenes

Pharmacogenomics is universally relevant for worldwide modern therapeutics and yet needs further development in resource-limited countries. While there is an abundance of genetic association studies in controlled medical settings, there is a paucity of studies with a naturalistic design in real-life clinical practice in patients with comorbidities and under multiple drug treatment regimens. African patients are often burdened with communicable and noncommunicable comorbidities, yet the application of pharmacogenomics in African clinical settings remains limited. Using warfarin as a model, this study aims at minimizing gaps in precision/personalized medicine research in African clinical practice. We present, therefore, pharmacogenomic profiles of a cohort of 503 black Africans (n = 252) and Mixed Ancestry (n = 251) patients from Southern Africa, on warfarin and co-prescribed drugs in a naturalized noncontrolled environment. Seventy-three (n = 73) single nucleotide polymorphisms (SNPs) in 29 pharmacogenes were characterized using a combination of allelic discrimination, Sanger sequencing, restriction fragment length polymorphism, and Sequenom Mass Array. The common comorbidities were hypertension (43-46%), heart failure (39-45%), diabetes mellitus (18%), arrhythmia (25%), and HIV infection (15%). Accordingly, the most common co-prescribed drugs were antihypertensives, antiarrhythmic drugs, antidiabetics, and antiretroviral therapy. We observed marked variation in major pharmacogenes both at interethnic levels and within African subpopulations. The Mixed Ancestry group presented a profile of genetic variants reflecting their European, Asian, and African admixture. Precision medicine requires that African populations begin to capture their own pharmacogenetic SNPs as they cannot always infer with absolute certainty from Asian and European populations. In the current historical moment of the COVID-19 pandemic, we also underscore that the spectrum of drugs interacting with warfarin will likely increase, given the systemic and cardiovascular effects of COVID-19, and the anticipated influx of COVID-19 medicines in the near future. This observational clinical pharmacogenomics study of warfarin, together with past precision medicine research, collectively, lends strong support for incorporation of pharmacogenetic profiling in clinical settings in African patients for effective and safe administration of therapeutics.

Pharmacogenomics Informs Cardiovascular Pharmacotherapy

Precision medicine exemplifies the emergence of personalized treatment options which may benefit specific patient populations based upon their genetic makeup. Application of pharmacogenomics requires an understanding of how genetic variations impact pharmacokinetic and pharmacodynamic properties. This particular approach in pharmacotherapy is helpful because it can assist in and improve clinical decisions. Application of pharmacogenomics to cardiovascular pharmacotherapy provides for the ability of the medical provider to gain critical knowledge on a patient's response to various treatment options and risk of side effects.

Cross-sectional study of the association of 5 single nucleotide polymorphisms with enalapril treatment response among South African adults with hypertension

This study investigates the association of 5 single nucleotide polymorphisms (SNPs) in selected genes (ABO, VEGFA, BDKRB2, NOS3, and ADRB2) with blood pressure (BP) response to enalapril. The study further assessed genetic interactions that exist within these genes and their implications in enalapril treatment response among South African adults with hypertension.A total of 284 participants belonging to the Nguni tribe of South Africa on continuous treatment for hypertension were recruited. Five SNPs in enalapril pharmacogenes were selected and genotyped using MassArray. Uncontrolled hypertension was defined as BP ≥140/90 mm Hg. The association between genotypes, alleles, and BP response to treatment was determined by fitting multivariate logistic regression model analysis, and genetic interactions between SNPs were assessed by multifactor dimensionality reduction.Majority of the study participants were female (75.00%), Xhosa (78.87%), and had uncontrolled hypertension (69.37%). All 5 SNPs were exclusively detected among Swati and Zulu participants. In the multivariate (adjusted) logistic model analysis, ADRB2 rs1042714 GC (adjusted odds ratio [AOR] = 2.31; 95% confidence interval [CI] 1.02-5.23; P = .044) and BDKRB2 rs1799722 CT (AOR = 2.74; 95% CI 1.19-6.28; P = .017) were independently associated with controlled hypertension in response to enalapril. While the C allele of VEGFA rs699947 (AOR = 0.37; 95% CI 0.15-0.94; P = .037) was significantly associated with uncontrolled hypertension. A significant interaction between rs699947, rs495828, and rs2070744 (cross-validation consistency = 10/10; P = .0005) in response to enalapril was observed.We confirmed the association of rs1042714 (ADRB2) and rs1799722 (BDKRB2) with controlled hypertension and established an interaction between rs699947 (VEGFA), rs495828 (ABO), and rs2070744 (NOS3) with BP response to enalapril. Our findings have provided substantial evidence for the use of SNPs as predictors for enalapril response among South Africans adults with hypertension.

A multicenter case-control study of the effect of e-nos VNTR polymorphism on upper gastrointestinal hemorrhage in NSAID users

Bleeding in non-steroidal anti-inflammatory drug (NSAID) users limited their prescription. This first multicenter full case–control study (325 cases and 744 controls), explored the association of e-NOS intron 4 variable number tandem repeat (VNTR) polymorphism with upper gastrointestinal hemorrhage (UGIH) in NSAID exposed and unexposed populations and assessed any interaction between this polymorphism and NSAIDs. NSAID users carrying e-NOS intron 4 wild type genotype or VNTR polymorphism have higher odds of UGIH than those unexposed to NSAIDs [Odds Ratio (OR): 6.62 (95% Confidence Interval (CI): 4.24, 10.36) and OR: 5.41 (95% CI 2.62, 11.51), respectively], with no effect modification from VNTR polymorphism-NSAIDs interaction [Relative Excess Risk due to Interaction (RERI): −1.35 (95% CI −5.73, 3.03); Synergism Index (S): 0.77 (95% CI 0.31, 1.94)]. Similar findings were obtained for aspirin exposure. Non-aspirin NSAID users who carry e-NOS intron 4 VNTR polymorphism have lower odds of UGIH [OR: 4.02 (95% CI 1.85, 8.75) than those users with wild type genotype [OR: 6.52 (95% CI 4.09, 10.38)]; though the interaction estimates are not statistically significant [RERI: −2.68 (95% CI −6.67, 1.31); S: 0.53 (95% CI 0.18, 1.55)]. This exploratory study suggests that the odds of UGIH in NSAID or aspirin users does not modify according to patient´s e-NOS intron 4 genotype.

Influence of CYP2D6 and CYP3A5 Polymorphisms on the Pharmacokinetics and Pharmacodynamics of Bisoprolol in Hypertensive Chinese Patients

Purpose: This study was performed to investigate the effects of common polymorphisms in CYP2D6 and CYP3A5 on the plasma concentrations and antihypertensive effects of bisoprolol in hypertensive Chinese patients. Methods: One hundred patients with essential hypertension were treated with open-label bisoprolol 2.5 mg daily for 6 weeks. Clinic blood pressure (BP) and ambulatory BP (ABP) were measured after the placebo run-in and after 6 weeks treatment. Peak plasma concentrations of bisoprolol were measured at 3 h after the first dose and 3 h after the dose after 6 weeks treatment. Trough levels were measured before the dose after 6 weeks treatment. Bisoprolol plasma concentrations were measured with a validated liquid chromatography tandem mass spectrometry method. Six common polymorphisms in CYP2D6 and the CYP3A5 ^* 3 polymorphism were genotyped by TaqMan® assay. Results: After 6 weeks of treatment, clinic BP and heart rate were significantly reduced by 14.3 ± 10.9/8.4 ± 6.2 mmHg (P < 0.01) and 6.3 ± 7.6 BPM (P < 0.01), respectively. Similar reductions were seen in ABP values. Bisoprolol plasma concentration at 3 h after the first dose and 3 h post-dose after 6 weeks of treatment were significantly associated with baseline body weight (P < 0.001) but there was no significant effect of the CYP2D6 and CYP3A5 polymorphisms on these or the trough plasma concentrations. There was no significant association of the CYP2D6 and CYP3A5 polymorphisms or plasma bisoprolol concentrations with the clinic BP or ABP responses to bisoprolol. Conclusion: Bisoprolol 2.5 mg daily effectively reduced BP and HR. The common polymorphisms in CYP2D6 that were examined and the CYP3A5 ^* 3 polymorphism appear to have no benefit in predicting the hemodynamic response to bisoprolol in these patients.

Hypertension in African Populations: Review and Computational Insights

Hypertension (HTN) is a persistent public health problem affecting approximately 1.3 billion individuals globally. Treatment-resistant hypertension (TRH) is defined as high blood pressure (BP) in a hypertensive patient that remains above goal despite use of ≥3 antihypertensive agents of different classes including a diuretic. Despite a plethora of treatment options available, only 31.0% of individuals have their HTN controlled. Interindividual genetic variability to drug response might explain this disappointing outcome because of genetic polymorphisms. Additionally, the poor knowledge of pathophysiological mechanisms underlying hypertensive disease and the long-term interaction of antihypertensive drugs with blood pressure control mechanisms further aggravates the problem. Furthermore, in Africa, there is a paucity of pharmacogenomic data on the treatment of resistant hypertension. Therefore, identification of genetic signals having the potential to predict the response of a drug for a given individual in an African population has been the subject of intensive investigation. In this review, we aim to systematically extract and discuss African evidence on the genetic variation, and pharmacogenomics towards the treatment of HTN. Furthermore, in silico methods are utilized to elucidate biological processes that will aid in identifying novel drug targets for the treatment of resistant hypertension in an African population. To provide an expanded view of genetic variants associated with the development of HTN, this study was performed using publicly available databases such as PubMed, Scopus, Web of Science, African Journal Online, PharmGKB searching for relevant papers between 1984 and 2020. A total of 2784 articles were reviewed, and only 42 studies were included following the inclusion criteria. Twenty studies reported associations with HTN and genes such as AGT (rs699), ACE (rs1799752), NOS3 (rs1799983), MTHFR (rs1801133), AGTR1 (rs5186), while twenty-two studies did not show any association within the African population. Thereafter, an in silico predictive approach was utilized to identify several genes including CLCNKB, CYPB11B2, SH2B2, STK9, and TBX5 which may act as potential drug targets because they are involved in pathways known to influence blood pressure. Next, co-expressed genes were identified as they are controlled by the same transcriptional regulatory program and may potentially be more effective as multiple drug targets in the treatment regimens for HTN. Genes belonging to the co-expressed gene cluster, ACE, AGT, AGTR1, AGTR2, and NOS3 as well as CSK and ADRG1 showed enrichment of G-protein-coupled receptor activity, the classical targets of drug discovery, which mediate cellular signaling processes. The latter is of importance, as the targeting of co-regulatory gene clusters will allow for the development of more effective HTN drug targets that could decrease the prevalence of both controlled and TRH.

Genetic polymorphism of the prostasin gene in hypertensive pregnant Pakistani females

Objective

The study was performed to investigate the association of hypertension in pregnancy with prostasin gene polymorphism in Pakistani females.

Methods

This case-control study was performed at University of Karachi, Pakistan from April 2018 to May 2019. A total of 160 females, including 90 hypertensives and 70 healthy pregnant females, were recruited by purposive sampling after obtaining informed written consent. Genotyping was performed by polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP).

Results

The frequencies of the TC and CC genotypes were higher in hypertensive pregnant females compared to healthy controls. A significant difference was evident for CC (P=0.012) genotype; however, no significant difference was observed for TC (P=0.49) and TT genotypes (P=0.06) between control and hypertensive groups. The adjusted odds ratio for CC genotype was 6.2 (P=0.025) and 1.48 (P=0.44) for TC genotype compared to the TT genotype. There was a significantly higher prevalence of the C allele of the prostasin gene at rs12597511 in the hypertensive group, suggesting that this allele is a risk factor for hypertension and cardiovascular diseases.

Conclusion

C allele at rs12597511 of prostasin gene demonstrate as a risk factor for having hypertension in pregnancy.

The Two Faces of ACE2: The Role of ACE2 Receptor and Its Polymorphisms in Hypertension and COVID-19

The mechanism for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection requires the binding of the virus to the angiotensin-converting enzyme 2 (ACE2) receptor, well-known for its role in counteracting ACE. ACE2 is involved in modulating blood pressure and establishing blood pressure homeostasis. Recently, a critical debatable question has arisen whether using antihypertensive medications will have a favorable impact on people infected with SARS-CoV-2 or a deleterious one, mainly because angiotensin-converting enzyme inhibitor (ACEI) and angiotensin-receptor blocker (ARB) therapy can modulate the expression of ACE2 protein. The concern is that the use of ACEIs and ARBs will increase the expression of ACE2 and increase patient susceptibility to viral host cell entry and propagation. On the other hand, several genetic association studies have examined the relationship between ACE2 genetic variants and the risk of developing hypertension in different ethnic populations. In this review, we discuss the ongoing arguments in the literature about ACE2's role in mortality rate among coronavirus disease 2019 (COVID-19) patients comorbid with hypertension and critically evaluate the current debate about the usage or discontinuation of ACEI/ARB antihypertensive drugs. Moreover, we explore the two opposing roles that ACE2 genetic variants might be playing in COVID-19 by reducing ACE2 receptor effectiveness and mitigating SARS-CoV-2 infectivity.

Genetic Hypothesis and Pharmacogenetics Side of Renin-Angiotensin-System in COVID-19

The importance of host genetics and demography in coronavirus disease 2019 (COVID-19) is a crucial aspect of infection, prognosis and associated case fatality rate. Individual genetic landscapes can contribute to understand Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) burden and can give information on how to fight virus spreading and the associated severe acute respiratory distress syndrome (ARDS). The spread and pathogenicity of the virus have become pandemic on specific geographic areas and ethnicities. Interestingly, SARS-CoV-2 firstly emerged in East Asia and next in Europe, where it has caused higher morbidity and mortality. This is a peculiar feature of SARS-CoV-2, different from past global viral infections (i.e., SARS-1 or MERS); it shares with the previous pandemics strong age- and sex-dependent gaps in the disease outcome. The observation that the severest COVID-19 patients are more likely to have a history of hypertension, diabetes and/or cardiovascular disease and receive Renin-Angiotensin-System (RAS) inhibitor treatment raised the hypothesis that RAS-unbalancing may have a crucial role. Accordingly, we recently published a genetic hypothesis on the role of RAS-pathway genes (ACE1, rs4646994, rs1799752, rs4340, rs13447447; and ACE2, rs2285666, rs1978124, rs714205) and ABO-locus (rs495828, rs8176746) in COVID-19 prognosis, suspecting inherited genetic predispositions to be predictive of COVID-19 severity. In addition, recently, Genome-Wide Association Studies (GWAS) found COVID-19-association signals at locus 3p21.31 (rs11385942) comprising the solute carrier SLC6A20 (Na+ and Cl- coupled transporter family) and at locus 9q34.2 (rs657152) coincident with ABO-blood group (rs8176747, rs41302905, rs8176719), and interestingly, both loci are associated to RAS-pathway. Finally, ACE1 and ACE2 haplotypes seem to provide plausible explanations for why SARS-CoV-2 have affected more heavily some ethnic groups, namely people with European ancestry, than Asians.

Pharmacogenomics of Hypertension Treatment

Hypertension is one of the strongest modifiable cardiovascular risk factors, affecting an increasing number of people worldwide. Apart from poor medication adherence, the low efficacy of some therapies could also be related to inter-individual genetic variability. Genetic studies of families revealed that heritability accounts for 30% to 50% of inter-individual variation in blood pressure (BP). Genetic factors not only affect blood pressure (BP) elevation but also contribute to inter-individual variability in response to antihypertensive treatment. This article reviews the recent pharmacogenomics literature concerning the key classes of antihypertensive drugs currently in use (i.e., diuretics, β-blockers, ACE inhibitors, ARB, and CCB). Due to the numerous studies on this topic and the sometimes-contradictory results within them, the presented data are limited to several selected SNPs that alter drug response. Genetic polymorphisms can influence drug responses through genes engaged in the pathogenesis of hypertension that are able to modify the effects of drugs, modifications in drug–gene mechanistic interactions, polymorphisms within drug-metabolizing enzymes, genes related to drug transporters, and genes participating in complex cascades and metabolic reactions. The results of numerous studies confirm that genotype-based antihypertension therapies are the most effective and may help to avoid the occurrence of major adverse events, as well as decrease the costs of treatment. However, the genetic heritability of drug response phenotypes seems to remain hidden in multigenic and multifactorial complex traits. Therefore, further studies are required to analyze all associations and formulate final genome-based treatment recommendations.