TET2 and CSMD1 genes affect SBP response to hydrochlorothiazide in never-treated essential hypertensives

Genetic polymorphisms influencing antihypertensive drug responses

Hypertension is a major contributor to cardiovascular disease and its associated morbidity and mortality. The low efficacy observed with some anti-hypertensive therapies has been attributed partly to inter-individual genetic variability. This paper reviews the major findings regarding these genetic variabilities that modulate responses to anti-hypertensive therapies such as angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), diuretics, calcium channel blockers (CCBs) and β-adrenoceptor blockers. The importance of studying these genetic polymorphisms stems from the goal to optimise anti-hypertensive therapy for each individual patient, aiming for the highest efficacy and lowest risk of adverse effects. It is important to recognise that environmental and epigenetic factors can contribute to the observed variations in drug responses. Owing to the multigenic and multifactorial nature of drug responses, further research is crucial for translating these findings into clinical practice and the establishment of reliable recommendations.

Genome-Wide Approach of Gene-Nutrient Intake Interaction Study for Essential Hypertension in a Large Korean Cohort (KoGES)

Background/Objectives: There is limited evidence on gene-nutrient interaction associated with hypertension (HTN). We examined interactions between genotypes and various nutrients that influenced high blood pressure (BP). Methods: Data were obtained from a total of 50,808 participants from the Korean Genome and Epidemiology Study (KoGES). Dietary intake was assessed by a food frequency questionnaire, and dietary reference intakes (DRIs) were set. We performed genome-wide association analyses (GWAS) and subsequent interaction analyses with genome-wide significant SNPs to identify genomic loci that interact with specific nutrients associated with HTN. Results: We identified one locus near the CUB and Sushi Multiple Domains 1 (CSMD1) gene that showed interaction with dietary iron and vitamin B6 (Vit.B6) intake and significantly influenced HTN risk. Among the individuals consuming iron above DRI (9.5 mg/day for men, 9.25 mg/day for women), carriers of the rs13282715 minor allele (A) at 8p23.2 showed a lower risk of HTN than those who did not (odds ratio [OR] 0.723, 95% confidence interval [CI] (0.644-0.813), p-value 4.858 × 10-8; interaction p-value 1.336 × 10-3). Among the individuals consuming Vit.B6 above DRI (1.5 mg/day for men, 1.4 mg/day for women), carriers of the same variant rs13282715 minor allele (A) also showed a lower risk of HTN (OR 0.733, 95% CI 0.733 (0.656-0.819), p-value 4.121 × 10-8; interaction p-value 7.183 × 10-4). Conclusions: We identified a novel gene-nutrient interaction regarding dietary iron and Vit.B6 intake affecting the risk of HTN in Korean adults. This suggests individuals with the variant may benefit from lower HTN risk from dietary intervention of iron and Vit.B6 intake. Further studies with larger diverse populations are warranted to validate our findings.

Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test

Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.

Investigating the causal associations between five anthropometric indicators and nonalcoholic fatty liver disease: Mendelian randomization study

BACKGROUND

Although the etiology of nonalcoholic fatty liver disease (NAFLD) has not been thoroughly understood, the emerging roles of anthropometric indicators in assessing and predicting the risk of NAFLD have been highlighted by accumulating evidence.

AIM

To evaluate the causal relationships between five anthropometric indicators and NAFLD employing Mendelian randomization (MR) design.

METHODS

The Anthropometric Consortium provided genetic exposure data for five anthropometric indicators, including hip circumference (HC), waist circumference (WC), waist-to-hip ratio (WHR), body mass index (BMI), and body fat percentage (BF). Genetic outcome data for NAFLD were obtained from the United Kingdom Biobank and FinnGen Consortium. Genome-wide significant single nucleotide polymorphisms were chosen as instrumental variables. Univariable MR (UVMR) and multivariable MR (MVMR) designs with analytical approaches, including inverse variance weighted (IVW), MR-Egger, weighted median (WM), and weighted mode methods, were used to assess the causal relationships between anthropometric indicators and NAFLD.

RESULTS

Causal relationships were revealed by UVMR, indicating that a higher risk of NAFLD was associated with a per-unit increase in WC [IVW: odds ratio (OR) = 2.67, 95%CI: 1.42-5.02, P = 2.25 × 10-3], and BF was causally associated with an increased risk of NAFLD (WM: OR = 2.23, 95%CI: 1.07-4.66, P = 0.033). The presence of causal effects of WC on the decreased risk of NAFLD was supported by MVMR after adjusting for BMI and smoking. However, no causal association between BF and NAFLD was observed. In addition, other causal relationships of HC, WHR (BMI adjusted), and BMI with the risk of NAFLD were not retained after FDR correction.

CONCLUSION

This study establishes a causal relationship, indicating that an increase in WC is associated with a higher risk of NAFLD. This demonstrates that a suitable decrease in WC is advantageous for preventing NAFLD.

An individualized Bayesian method for estimating genomic variants of hypertension

BACKGROUND

Genomic variants of the disease are often discovered nowadays through population-based genome-wide association studies (GWAS). Identifying genomic variations potentially underlying a phenotype, such as hypertension, in an individual is important for designing personalized treatment; however, population-level models, such as GWAS, may not capture all the important, individualized factors well. In addition, GWAS typically requires a large sample size to detect the association of low-frequency genomic variants with sufficient power. Here, we report an individualized Bayesian inference (IBI) algorithm for estimating the genomic variants that influence complex traits, such as hypertension, at the level of an individual (e.g., a patient). By modeling at the level of the individual, IBI seeks to find genomic variants observed in the individual's genome that provide a strong explanation of the phenotype observed in this individual.

RESULTS

We applied the IBI algorithm to the data from the Framingham Heart Study to explore the genomic influences of hypertension. Among the top-ranking variants identified by IBI and GWAS, there is a significant number of shared variants (intersection); the unique variants identified only by IBI tend to have relatively lower minor allele frequency than those identified by GWAS. In addition, IBI discovered more individualized and diverse variants that explain hypertension patients better than GWAS. Furthermore, IBI found several well-known low-frequency variants as well as genes related to blood pressure that GWAS missed in the same cohort. Finally, IBI identified top-ranked variants that predicted hypertension better than GWAS, according to the area under the ROC curve.

CONCLUSIONS

The results support IBI as a promising approach for complementing GWAS, especially in detecting low-frequency genomic variants as well as learning personalized genomic variants of clinical traits and disease, such as the complex trait of hypertension, to help advance precision medicine.

Precision Medicine and the future of Cardiovascular Diseases: A Clinically Oriented Comprehensive Review

Cardiac diseases form the lion's share of the global disease burden, owing to the paradigm shift to non-infectious diseases from infectious ones. The prevalence of CVDs has nearly doubled, increasing from 271 million in 1990 to 523 million in 2019. Additionally, the global trend for the years lived with disability has doubled, increasing from 17.7 million to 34.4 million over the same period. The advent of precision medicine in cardiology has ignited new possibilities for individually personalized, integrative, and patient-centric approaches to disease prevention and treatment, incorporating the standard clinical data with advanced "omics". These data help with the phenotypically adjudicated individualization of treatment. The major objective of this review was to compile the evolving clinically relevant tools of precision medicine that can help with the evidence-based precise individualized management of cardiac diseases with the highest DALY. The field of cardiology is evolving to provide targeted therapy, which is crafted as per the "omics", involving genomics, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics, for deep phenotyping. Research for individualizing therapy in heart diseases with the highest DALY has helped identify novel genes, biomarkers, proteins, and technologies to aid early diagnosis and treatment. Precision medicine has helped in targeted management, allowing early diagnosis, timely precise intervention, and exposure to minimal side effects. Despite these great impacts, overcoming the barriers to implementing precision medicine requires addressing the economic, cultural, technical, and socio-political issues. Precision medicine is proposed to be the future of cardiovascular medicine and holds the potential for a more efficient and personalized approach to the management of cardiovascular diseases, contrary to the standardized blanket approach.

Genetic Contributors of Efficacy and Adverse Metabolic Effects of Chlorthalidone in African Americans from the Genetics of Hypertension Associated Treatments (GenHAT) Study

Hypertension is a leading risk factor for cardiovascular disease mortality. African Americans (AAs) have the highest prevalence of hypertension in the United States, and to alleviate the burden of hypertension in this population, better control of blood pressure (BP) is needed. Previous studies have shown considerable interpersonal differences in BP response to antihypertensive treatment, suggesting a genetic component. Utilizing data from 4297 AA participants randomized to chlorthalidone from the Genetics of Hypertension Associated Treatments (GenHAT) study, we aimed to identify variants associated with the efficacy of chlorthalidone. An additional aim was to find variants that contributed to changes in fasting glucose (FG) in these individuals. We performed genome-wide association analyses on the change of systolic and diastolic BP (SBP and DBP) over six months and FG levels over 24 months of treatment. We sought replication in the International Consortia of Pharmacogenomics Studies. We identified eight variants statistically associated with BP response and nine variants associated with FG response. One suggestive LINC02211-CDH9 intergenic variant was marginally replicated with the same direction of effect. Given the impact of hypertension in AAs, this study implies that understanding the genetic background for BP control and glucose changes during chlorthalidone treatment may help prevent adverse cardiovascular events in this population.

Pharmacoepigenetics of hypertension: genome-wide methylation analysis of responsiveness to four classes of antihypertensive drugs using a double-blind crossover study design

Essential hypertension remains the leading risk factor of global disease burden, but its treatment goals are often not met. We investigated whether DNA methylation is associated with antihypertensive responses to a diuretic, a beta-blocker, a calcium channel blocker or an angiotensin receptor antagonist. In addition, since we previously showed an SNP at the transcription start site (TSS) of the catecholamine biosynthesis-related ACY3 gene to associate with blood pressure (BP) response to beta-blockers, we specifically analysed the association of methylation sites close to the ACY3 TSS with BP responses to beta-blockers. We conducted an epigenome-wide association study between leukocyte DNA methylation and BP responses to antihypertensive monotherapies in two hypertensive Finnish cohorts: the GENRES (https://clinicaltrials.gov/ct2/show/NCT03276598; amlodipine 5 mg, bisoprolol 5 mg, hydrochlorothiazide 25 mg, or losartan 50 mg daily) and the LIFE-Fin studies (https://clinicaltrials.gov/ct2/show/NCT00338260; atenolol 50 mg or losartan 50 mg daily). The monotherapy groups consisted of approximately 200 individuals each. We identified 64 methylation sites to suggestively associate (P < 1E-5) with either systolic or diastolic BP responses to a particular study drug in GENRES. These associations did not replicate in LIFE-Fin . Three methylation sites close to the ACY3 TSS were associated with systolic BP responses to bisoprolol in GENRES but not genome-wide significantly (P < 0.05). No robust associations between DNA methylation and BP responses to four different antihypertensive drugs were identified. However, the findings on the methylation sites close to the ACY3 TSS may support the role of ACY3 genetic and epigenetic variation in BP response to bisoprolol.

Genomic Association of Single Nucleotide Polymorphisms with Blood Pressure Response to Hydrochlorothiazide among South African Adults with Hypertension

This study described single nucleotide polymorphisms (SNPs) in hydrochlorothiazide-associated genes and further assessed their correlation with blood pressure control among South African adults living with hypertension. A total of 291 participants belonging to the Nguni tribes of South Africa on treatment for hypertension were recruited. Nineteen SNPs in hydrochlorothiazide pharmacogenes were selected and genotyped using MassArray. Uncontrolled hypertension was defined as blood pressure ≥140/90 mmHg. The association between genotypes, alleles and blood pressure response to treatment was determined by conducting multivariate logistic regression model analysis. The majority of the study participants were female (73.19%), Xhosa (54.98%) and had blood pressure ≥140/90 mmHg (68.73%). Seventeen SNPs were observed among the Xhosa tribe, and two (rs2070744 and rs7297610) were detected among Swati and Zulu participants. Furthermore, alleles T of rs2107614 (AOR = 6.69; 95%CI 1.42–31.55; p = 0.016) and C of rs2776546 (AOR = 3.78; 95%CI 1.04–13.74; p = 0.043) were independently associated with uncontrolled hypertension, whilst rs2070744 TC (AOR = 38.76; 95%CI 5.54–270.76; p = 0.00023), CC (AOR = 10.44; 95%CI 2.16–50.29; p = 0.003) and allele T of rs7297610 (AOR = 1.86; 95%CI 1.09–3.14; p = 0.023) were significantly associated with uncontrolled hypertension among Zulu and Swati participants. We confirmed the presence of SNPs associated with hydrochlorothiazide, some of which were significantly associated with uncontrolled hypertension in the study sample. Findings open doors for further studies on personalized therapy for hypertension in the country.

Human essential hypertension: no significant association of polygenic risk scores with antihypertensive drug responses

Polygenic risk scores (PRSs) for essential hypertension, calculated from > 900 genomic loci, were recently found to explain a significant fraction of hypertension heritability and complications. To investigate whether variation of hypertension PRS also captures variation of antihypertensive drug responsiveness, we calculated two different PRSs for both systolic and diastolic blood pressure: one based on the top 793 independent hypertension-associated single nucleotide polymorphisms and another based on over 1 million genome-wide variants. Using our pharmacogenomic GENRES study comprising four different antihypertensive monotherapies (n ~ 200 for all drugs), we identified a weak, but (after Bonferroni correction) statistically nonsignificant association of higher genome-wide PRSs with weaker response to a diuretic. In addition, we noticed a correlation between high genome-wide PRS and electrocardiographic left ventricular hypertrophy. Finally, using data of the Finnish arm of the LIFE study (n = 346), we found that PRSs for systolic blood pressure were slightly higher in patients with drug-resistant hypertension than in those with drug-controlled hypertension (p = 0.03, not significant after Bonferroni correction). In conclusion, our results indicate that patients with elevated hypertension PRSs may be predisposed to difficult-to-control hypertension and complications thereof. No general association between a high PRS and less efficient drug responsiveness was noticed.

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.

Pharmacogenomics of amlodipine and hydrochlorothiazide therapy and the quest for improved control of hypertension: a mini review

Blood pressure (BP) is a complex trait that is regulated by multiple physiological pathways and include but is not limited to extracellular fluid volume homeostasis, cardiac contractility, and vascular tone through renal, neural, or endocrine systems. Uncontrolled hypertension (HTN) has been associated with an increased mortality risk. Therefore, understanding the genetics that underpins and influence BP regulation will have a major impact on public health. Moreover, uncontrolled HTN has been linked to inter-individual variation in the drugs’ response and this has been associated with an individual’s genetics architecture. However, the identification of candidate genes that underpin the genetic basis of HTN remains a major challenge. To date, few variants associated with inter-individual BP regulation have been identified and replicated. Research in this field has accelerated over the past 5 years as a direct result of on-going genome-wide association studies (GWAS) and the progress in the identification of rare gene variants and mutations, epigenetic markers, and the regulatory pathways involved in the pathophysiology of BP. In this review we describe and enhance our current understanding of how genetic variants account for the observed variability in BP response in patients on first-line antihypertensive drugs, amlodipine and hydrochlorothiazide.

Hypertensive APOL1 risk allele carriers demonstrate greater blood pressure reduction with angiotensin receptor blockade compared to low risk carriers

Background

Hypertension (HTN) disproportionately affects African Americans (AAs), who respond better to thiazide diuretics than other antihypertensives. Variants of the APOL1 gene found in AAs are associated with a higher rate of kidney disease and play a complex role in cardiovascular disease.

Methods

AA subjects from four HTN trials (n = 961) (GERA1, GERA2, PEAR1, and PEAR2) were evaluated for blood pressure (BP) response based on APOL1 genotype after 4–9 weeks of monotherapy with thiazides, beta blockers, or candesartan. APOL1 G1 and G2 variants were determined by direct sequencing or imputation.

Results

Baseline systolic BP (SBP) and diastolic BP (DBP) levels did not differ based on APOL1 genotype. Subjects with 1–2 APOL1 risk alleles had a greater SBP response to candesartan (-12.2 +/- 1.2 vs -7.5 +/- 1.8 mmHg, p = 0.03; GERA2), and a greater decline in albuminuria with candesartan (-8.3 +/- 3.1 vs +3.7 +/- 4.3 mg/day, p = 0.02). APOL1 genotype did not associate with BP response to thiazides or beta blockers. GWAS was performed to determine associations with BP response to candesartan depending on APOL1 genotype. While no SNPs reached genome wide significance, SNP rs10113352, intronic in CSMD1, predicted greater office SBP response to candesartan (p = 3.7 x 10⁻⁷) in those with 1–2 risk alleles, while SNP rs286856, intronic in DPP6, predicted greater office SBP response (p = 3.2 x 10⁻⁷) in those with 0 risk alleles.

Conclusions

Hypertensive AAs without overt kidney disease who carry 1 or more APOL1 risk variants have a greater BP and albuminuria reduction in response to candesartan therapy. BP response to thiazides or beta blockers did not differ by APOL1 genotype. Future studies confirming this initial finding in an independent cohort are required.

TET2: A Novel Epigenetic Regulator and Potential Intervention Target for Atherosclerosis

Atherosclerosis is the underlying cause of cardio-cerebrovascular disease. However, the mechanisms of atherosclerosis are still unclear. The modification of DNA methylation has an important role in atherosclerosis development. As a member of the Ten-eleven translocation (TET) family, TET methylcytosine dioxygenase 2 (TET2) can modify DNA methylation by catalyzing 5-methylcytosine to 5-hydroxymethylcytosine and mediate DNA demethylation. Recent findings suggest that TET2 is related to the phenotype transformation of vascular smooth muscle cells, endothelial dysfunction, and inflammation of macrophage, the key factors of atherosclerosis. Therefore, TET2 may be a potential target for atherosclerosis treatment. This review will elaborate the recent findings that suggest the role of TET2 in atherosclerosis.

Pharmacogenomic studies of hypertension: paving the way for personalized antihypertensive treatment

Introduction

Increasing clinical evidence supports the implementation of genotyping for anti-hypertensive drug dosing and selection. Despite robust evidence gleaned from clinical trials, the translation of genotype guided therapy into clinical practice faces significant challenges. Challenges to implementation include the small effect size of individual variants and the polygenetic nature of antihypertensive drug response, a lack of expert consensus on dosing guidelines even without genetic information, and proper definition of major antihypertensive drug toxicities. Balancing clinical benefit with cost, while overcoming these challenges, remains crucial.

Areas covered

This review presents the most impactful clinical trials and cohorts which continue to inform and guide future investigation. Variants were selected from among those identified in the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR), the Genetic Epidemiology of Responses to Antihypertensives study (GERA), the Genetics of Drug Responsiveness in Essential Hypertension (GENRES) study, the SOPHIA study, the Milan Hypertension Pharmacogenomics of hydro-chlorothiazide (MIHYPHCTZ), the Campania Salute Network, the International Verapamil SR Trandolapril Study (INVEST), the Nordic Diltiazem (NORDIL) Study, GenHAT, and others.

Expert Commentary

The polygenic nature of antihypertensive drug response is a major barrier to clinical implementation. Further studies examining clinical effectiveness are required to support broad-based implementation of genotype-based prescribing in medical practice.

Effects of four different antihypertensive drugs on plasma metabolomic profiles in patients with essential hypertension

Objective

In order to search for metabolic biomarkers of antihypertensive drug responsiveness, we measured >600 biochemicals in plasma samples of subjects participating in the GENRES Study. Hypertensive men received in a double-blind rotational fashion amlodipine, bisoprolol, hydrochlorothiazide and losartan, each as a monotherapy for one month, with intervening one-month placebo cycles.

Methods

Metabolomic analysis was carried out using ultra high performance liquid chromatography-tandem mass spectrometry. Full metabolomic signatures (the drug cycles and the mean of the 3 placebo cycles) became available in 38 to 42 patients for each drug. Blood pressure was monitored by 24-h recordings.

Results

Amlodipine (P values down to 0.002), bisoprolol (P values down to 2 x 10⁻⁵) and losartan (P values down to 2 x 10⁻⁴) consistently decreased the circulating levels of long-chain acylcarnitines. Bisoprolol tended to decrease (P values down to 0.002) the levels of several medium- and long-chain fatty acids. Hydrochlorothiazide administration was associated with an increase of plasma uric acid level (P = 5 x 10^-4) and urea cycle metabolites. Decreases of both systolic (P = 0.06) and diastolic (P = 0.04) blood pressure after amlodipine administration tended to associate with a decrease of plasma hexadecanedioate, a dicarboxylic fatty acid recently linked to blood pressure regulation.

Conclusions

Although this systematic metabolomics study failed to identify circulating metabolites convincingly predicting favorable antihypertensive response to four different drug classes, it provided accumulating evidence linking fatty acid metabolism to human hypertension.

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.

Is There a Role for Genomics in the Management of Hypertension?

Hypertension (HTN) affects about 1 billion people worldwide and the lack of a single identifiable cause complicates its treatment. Blood pressure (BP) levels are influenced by environmental factors, but there is a strong genetic component. Linkage analysis has identified several genes involved in Mendelian forms of HTN and the associated pathophysiological mechanisms have been unravelled, leading to targeted therapies. The majority of these syndromes are due to gain-of-function or loss-of-functions mutations, resulting in an alteration of mineralocorticoid, glucocorticoid, or sympathetic pathways. The diagnosis of monogenic forms of HTN has limited practical implications on the population and a systematic genetic screening is not justifiable. Genome-wide linkage and association studies (GWAS) have identified single nucleotide polymorphisms (SNPs), which influence BP. Forty-three variants have been described with each SNP affecting systolic and diastolic BP by 1.0 and 0.5 mmHg, respectively. Taken together Mendelian inheritance and all GWAS-identified HTN-associated variants explain 2–3% of BP variance. Epigenetic modifications, such as DNA methylation, histone modification and non-coding RNAs, have become increasingly recognized as important players in BP regulation and may justify a further part of missing heritability. In this review, we will discuss how genetics and genomics may assist clinicians in managing patients with HTN.

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.

New Developments in the Genetics of Hypertension: What Should Clinicians Know?

It has long been known that genetic factors play a major role in determining an individual's propensity to hypertension. In recent years, there has been major progress towards realizing the goal of identifying the specific genetic factors that lead to alterations in blood pressure. Of particular note, new genes regulating renal sodium handling and aldosterone regulation have been discovered via the study of rare Mendelian disorders. Similarly, a number of large genome-wide association studies have been completed, which have added to our understanding as well. Here, recent progress in the genetics of hypertension will be reviewed, with an emphasis towards highlighting specific areas where clinical practice has already or will soon be affected.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI’s Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

The widely used statistical methods test interaction for single phenotype. However, we often observe pleotropic genetic interaction effects. The simultaneous gene-gene (GxG) interaction analysis of multiple complementary traits will increase statistical power to detect GxG interactions. Although GxG interactions play an important role in uncovering the genetic structure of complex traits, the statistical methods for detecting GxG interactions in multiple phenotypes remains less developed owing to its potential complexity. Therefore, we extend functional regression model from single variate to multivariate for simultaneous GxG interaction analysis of multiple correlated phenotypes. Large-scale simulations are conducted to evaluate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare power with traditional multivariate pair-wise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for interaction analysis is applied to five phenotypes of exome sequence data from the NHLBI’s Exome Sequencing Project (ESP) to detect pleiotropic GxG interactions. 267 pairs of genes that formed a genetic interaction network showed significant evidence of interactions influencing five traits.

Hypertension pharmacogenomics: in search of personalized treatment approaches

Cardiovascular and renal diseases are associated with many risk factors, of which hypertension is one of the most prevalent. Worldwide, blood pressure control is only achieved in ∼50% of those treated for hypertension, despite the availability of a considerable number of antihypertensive drugs from different pharmacological classes. Although many reasons exist for poor blood pressure control, a likely contributor is the inability to predict to which antihypertensive drug an individual is most likely to respond. Hypertension pharmacogenomics and other 'omics' technologies have the potential to identify genetic signals that are predictive of response or adverse outcome to particular drugs, and guide selection of hypertension treatment for a given individual. Continued research in this field will enhance our understanding of how to maximally deploy the various antihypertensive drug classes to optimize blood pressure response at the individual level. This Review summarizes the available literature on the most convincing genetic signals associated with antihypertensive drug responses and adverse cardiovascular outcomes. Future research in this area will be facilitated by enhancing collaboration between research groups through consortia such as the International Consortium for Antihypertensives Pharmacogenomics Studies, with the goal of translating replicated findings into clinical implementation.

Pharmacogenomics of hypertension and heart disease

Heart disease is a leading cause of death in the United States, and hypertension is a predominant risk factor. Thus, effective blood pressure control is important to prevent adverse sequelae of hypertension, including heart failure, coronary artery disease, atrial fibrillation, and ischemic stroke. Over half of Americans have uncontrolled blood pressure, which may in part be explained by interpatient variability in drug response secondary to genetic polymorphism. As such, pharmacogenetic testing may be a supplementary tool to guide treatment. This review highlights the pharmacogenetics of antihypertensive response and response to drugs that treat adverse hypertension-related sequelae, particularly coronary artery disease and atrial fibrillation. While pharmacogenetic evidence may be more robust for the latter with respect to clinical implementation, there is increasing evidence of genetic variants that may help predict antihypertensive response. However, additional research and validation are needed before clinical implementation guidelines for antihypertensive therapy can become a reality.

Pharmacogenomics considerations in the control of hypertension

The response to antihypertensive therapy is very heterogeneous and the need by the physicians to account for it has driven much interest in pharmacogenomics of antihypertensive drugs. The Human Genome Project and the initiatives in genomics that followed, generated a huge number of genetic data that furnished the tools to explore the genotype-phenotype association in candidate genes and at genome-wide level. In spite of the efforts and the great number of publications, pharmacogenomics of antihypertensive drugs is far from being used in clinical practice. In this review, we analyze the main findings available in PubMed from 2010 to 2015, in relation to the major classes of antihypertensive drugs. We also describe a new Phase II drug that targets two specific hypertension predisposing mechanisms.