A Genetic Response Score for Hydrochlorothiazide Use: Insights From Genomics and Metabolomics Integration

Intestinal serotonergic vagal signaling as a mediator of microbiota-induced hypertension

Hypertension is a pervasive global health challenge, impacting over a billion individuals worldwide. Despite strides in therapeutic strategies, a significant proportion of patients remain resistant to the currently available therapies. While conventional treatments predominantly focus on cardiac, renal, and cerebral targets, emerging research underscores the pivotal role of the gut and its microbiota. Yet, the precise mechanisms governing interactions between the gut microbiota and the host blood pressure remain unclear. Here we describe a neural host-microbiota interaction that is mediated by the intestinal serotonin (5-HT) signaling via vagal 5HT3a receptors and which is crucial for maintenance of blood pressure homeostasis. Notably, a marked decrease in both intestinal 5-HT and vagal 5HT3aR signaling is observed in hypertensive rats, and in rats subjected to fecal microbiota transplantation from hypertensive rats. Leveraging an intersectional genetic strategy in a Cre rat line, we demonstrate that intestinal 5HT3aR vagal signaling is a crucial link between the gut microbiota and blood pressure homeostasis and that recovery of 5-HT signaling in colon innervating vagal neurons can alleviate hypertension. This paradigm-shifting finding enhances our comprehension of hypertensive pathophysiology and unveils a promising new therapeutic target for combating resistant hypertension associated with gut dysbiosis.

A hypothesis-driven study to comprehensively investigate the association between genetic polymorphisms in EPHX2 gene and cardiovascular diseases: Findings from the UK Biobank

BACKGROUND

Epoxyeicosatrienoic acids (EETs) are protective factors against cardiovascular diseases (CVDs) because of their vasodilatory, cholesterol-lowering, and anti-inflammatory effects. Soluble epoxide hydrolase (sEH), encoded by the EPHX2 gene, degrades EETs into less biologically active metabolites. EPHX2 is highly polymorphic, and genetic polymorphisms in EPHX2 have been linked to various types of CVDs, such as coronary heart disease, essential hypertension, and atrial fibrillation recurrence.

METHODS

Based on a priori hypothesis that EPHX2 genetic polymorphisms play an important role in the pathogenesis of CVDs, we comprehensively investigated the associations between 210 genetic polymorphisms in the EPHX2 gene and an array of 118 diseases in the circulatory system using a large sample from the UK Biobank (N = 307,516). The diseases in electronic health records were mapped to the phecode system, which was more representative of independent phenotypes. Survival analyses were employed to examine the effects of EPHX2 variants on CVD incidence, and a phenome-wide association study was conducted to study the impact of EPHX2 polymorphisms on 62 traits, including blood pressure, blood lipid levels, and inflammatory indicators.

RESULTS

A novel association between the intronic variant rs116932590 and the phenotype "aneurysm and dissection of heart" was identified. In addition, the rs149467044 and rs200286838 variants showed nominal evidence of association with arterial aneurysm and cerebrovascular disease, respectively. Furthermore, the variant rs751141, which was linked with a lower hydrolase activity of sEH, was significantly associated with metabolic traits, including blood levels of triglycerides, creatinine, and urate.

CONCLUSIONS

Multiple novel associations observed in the present study highlight the important role of EPHX2 genetic variation in the pathogenesis of CVDs.

Application of omics in hypertension and resistant hypertension

Hypertension is a major modifiable risk factor that affects the global health burden. Despite the availability of multiple antihypertensive drugs, blood pressure is often not optimally controlled. The prevalence of true resistant hypertension in treated hypertensive patients is ~2-20%, and these patients are at higher risk for adverse events and poor clinical outcomes. Therefore, an in-depth dissection of the pathophysiological mechanisms of hypertension and resistant hypertension is needed to identify more effective targets for regulating blood pressure. Omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and microbiomics, can accurately present the characteristics of organisms at varying molecular levels. Integrative omics can further reveal the network of interactions between molecular levels and provide a complete dynamic view of the organism. In this review, we describe the applications, progress, and challenges of omics technologies in hypertension. Specifically, we discuss the application of omics in resistant hypertension. We believe that omics approaches will produce a better understanding of the pathogenesis of hypertension and resistant hypertension and improve diagnostic and therapeutic strategies, thus increasing rates of blood pressure control and reducing the public health burden of hypertension.

Plasma metabolomic profiles associated with hypertension and blood pressure in response to thiazide diuretics

This study aimed to identify the metabolomic alterations associated with hypertension (HTN) and the response of blood pressure (BP) to thiazide diuretics. A total of 50 participants previously untreated for HTN were prospectively recruited. After a 2-week lifestyle adjustment, 30 participants with systolic BP ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg were classified into the HTN group and prescribed hydrochlorothiazide (HCTZ) at 50 mg per day for 2 weeks. The remaining 20 participants, who had relatively normal BP, were assigned to the normotension group. Metabolomic profiles related to the response of BP to thiazide diuretics were analyzed. A total of 73 differential metabolites were found to be associated with HTN, and 27 metabolites were significantly changed upon HCTZ treatment (HCTZ-sensitive metabolites). Among the identified metabolites, 7 (aspartate, histidine, C5-DC, C5-M-DC, C14:1, phosphatidylcholine ae C34:1, and phosphatidylcholine ae C34:3) were positively associated with HTN and decreased in abundance upon HCTZ treatment (HCTZ-reduced/HTN-associated metabolites). Moreover, multivariate analysis of 20 metabolites whose baseline levels were associated with the response of BP revealed that aspartate, glutamate, lysophosphatidylcholine C16:0, lysophosphatidylcholine C20:3, and sphingomyelin C24:1 were independently related to systolic BP reduction, and lysophosphatidylcholine C20:3 was independently associated with diastolic BP reduction. In conclusion, we identified 5 metabolites independently related to BP changes with HCTZ treatment. An advanced biomarker profile of thiazide-induced metabolomic changes may provide a clue with which to further explore the complex and mixed effects of thiazide treatment in a clinical setting.

Metabolomics Signature of Plasma Renin Activity and Linkage with Blood Pressure Response to Beta Blockers and Thiazide Diuretics in Hypertensive European American Patients

Plasma renin activity (PRA) is a predictive biomarker of blood pressure (BP) response to antihypertensives in European–American hypertensive patients. We aimed to identify the metabolic signatures of baseline PRA and the linkages with BP response to β-blockers and thiazides. Using data from the Pharmacogenomic Evaluation of Antihypertensive Responses-2 (PEAR-2) trial, multivariable linear regression adjusting for age, sex and baseline systolic-BP (SBP) was performed on European–American individuals treated with metoprolol (n = 198) and chlorthalidone (n = 181), to test associations between 856 metabolites and baseline PRA. Metabolites with a false discovery rate (FDR) < 0.05 or p < 0.01 were tested for replication in 463 European–American individuals treated with atenolol or hydrochlorothiazide. Replicated metabolites were then tested for validation based on the directionality of association with BP response. Sixty-three metabolites were associated with baseline PRA, of which nine, including six lipids, were replicated. Of those replicated, two metabolites associated with higher baseline PRA were validated: caprate was associated with greater metoprolol SBP response (β = −1.7 ± 0.6, p = 0.006) and sphingosine-1-phosphate was associated with reduced hydrochlorothiazide SBP response (β = 7.6 ± 2.8, p = 0.007). These metabolites are clustered with metabolites involved in sphingolipid, phospholipid, and purine metabolic pathways. The identified metabolic signatures provide insights into the mechanisms underlying BP response.

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.

Polygenic Score for β-Blocker Survival Benefit in European Ancestry Patients With Reduced Ejection Fraction Heart Failure

BACKGROUND

β-Blockers (BBs) are mainstay therapy for heart failure with reduced ejection fraction. However, individual patient responses to BB vary, which may be partially due to genetic variation. The goal of this study was to derive and validate the first polygenic response predictor (PRP) for BB survival benefit in heart failure with reduced ejection fraction patients.

METHODS

Derivation and validation analyses were performed in n=1436 total HF patients of European descent and with ejection fraction <50%. The PRP was derived in a random subset of the Henry Ford Heart Failure Pharmacogenomic Registry (n=248) and then validated in a meta-analysis of the remaining patients from Henry Ford Heart Failure Pharmacogenomic Registry (n=247), the TIME-CHF (Trial of Intensified Versus Standard Medical Therapy in Elderly Patients With Congestive Heart Failure; n=431), and HF-ACTION trial (Heart Failure: a Controlled Trial Investigating Outcomes of Exercise Training; n=510). The PRP was constructed from a genome-wide analysis of BB×genotype interaction predicting time to all-cause mortality, adjusted for Meta-Analysis Global Group in Chronic Heart Failure score, genotype, level of BB exposure, and BB propensity score.

RESULTS

Five-fold cross-validation summaries out to 1000 single-nucleotide polymorphisms identified optimal prediction with a 44 single-nucleotide polymorphism score and cutoff at the 30th percentile. In validation testing (n=1188), greater BB exposure was associated with reduced all-cause mortality in patients with low PRP score (n=251; hazard ratio, 0.19 [95% CI, 0.04-0.51]; P=0.0075) but not high PRP score (n=937; hazard ratio, 0.84 [95% CI, 0.53-1.3]; P=0.448)-a difference that was statistically significant (P interaction, 0.0235). Results were consistent regardless of atrial fibrillation, ejection fraction (≤40% versus 41%-50%), or when examining cardiovascular death.

CONCLUSIONS

Among patients of European ancestry with heart failure with reduced ejection fraction, a PRP distinguished patients who derived substantial survival benefit from BB exposure from a larger group that did not. Additional work is needed to prospectively test clinical utility and to develop PRPs for other population groups and other medications.

Genomic Determinants of Hypertension With a Focus on Metabolomics and the Gut Microbiome

Epidemiologic and genomic studies have progressively improved our understanding of the causation of hypertension and the complex relationship with diet and environment. The majority of Mendelian forms of syndromic hypotension and hypertension (HTN) have all been linked to mutations in genes whose encoded proteins regulate salt-water balance in the kidney, supporting the primacy of the kidneys in blood pressure regulation. There are more than 1,477 single nucleotide polymorphisms associated with blood pressure and hypertension and the challenge is establishing a causal role for these variants. Hypertension is a complex multifactorial phenotype and it is likely to be influenced by multiple factors including interactions between diet and lifestyle factors, microbiome, and epigenetics. Given the finite genetic variability that is possible in humans, it is likely that incremental gains from single marker analyses have now plateaued and a greater leap in our understanding of the genetic basis of disease will come from integration of other omics and the interacting environmental factors. In this review, we focus on emerging results from the microbiome and metabolomics and discuss how leveraging these findings may facilitate a deeper understanding of the interrelationships between genomics, diet, and microbial ecology in humans in the causation of essential hypertension.

The Effect of Genetically Guided Mathematical Prediction and the Blood Pressure Response to Pharmacotherapy in Hypertension Patients

Purpose:

The purpose of this study was to determine the effectiveness of a simple algorithm to mathematically predict a patients’ response to blood pressure (BP) therapy using functional genes in the 3 major organ systems involved in hypertension.

Methods:

Eighty-six patients with controlled hypertension completed 1 study visit consisting of a buccal swab collection, measurement of office BP, and a medical chart review for BP history. Genes in the analysis included 14 functional alleles in 11 genes. These genotypes were mathematically summed per organ system to determine whether a patient would likely respond to target therapy.

Results:

Patients recommended to and taking a diuretic had significantly higher rates of control (<120/<80) than patients recommended but not taking this drug class (0.2 ± 0.1 and 0.03 ± 0.03, respectively). Furthermore, there was a difference between patients genetically recommended and taking an angiotensin receptor blocker (ARB) vs patients recommended but not taking an ARB for the lowest diastolic blood pressure (DBP) and mean arterial pressure (MAP) recorded in the past 2 years (DBP = 66.2 ± 2.9 and 75.3 ± 1.7, MAP = 82.3 ± 2.8 and 89.3 ± 1.5, respectively). In addition, there was a nonsignificant trend for greater reductions in ΔSBP, ΔDBP, and ΔMAP in patients on recommended drug class for beta-blockers, diuretics, and angiotensin II receptor blockers vs patients not on these classes.

Conclusion:

The present study suggests that simple mathematical weighting of functional genotypes known to control BP may be ineffective in predicting control. This study demonstrates the need for a more complex, weighted, multigene algorithm to more accurately predict BP therapy response.

Economic evaluation of a pharmacogenomic multi-gene panel test to optimize anti-hypertension therapy: simulation study

AIMS

Hypertension is the strongest modifiable risk factor for cardiovascular disease, affecting 80 million individuals in the US and responsible for ∼360,000 deaths, at total annual costs of $93.5 billion. Antihypertension therapies guided by single genotypes are clinically more effective and may avert more adverse events than the standard of care of layering anti-hypertensive drug therapies, thus potentially decreasing costs. This study aimed to determine the economic benefits of the implementation of multi-gene panel guided therapies for hypertension from the payer perspective within a 3-year time horizon.

MATERIALS AND METHODS

A simulation analysis was conducted for a panel of 10 million insured patients categorized clinically as untreated, treated but uncontrolled, and treated and controlled over a 3-year treatment period. Inputs included research data; empirical data from a 11-gene panel with known functional, heart, blood vessel, and kidney genotypes; and therapy efficacy and safety estimates from literature. Cost estimates were categorized as related to genetic testing, evaluation and management, medication, or adverse events.

RESULTS

Multi-gene panel guided therapy yielding savings of $6,256,607,500 for evaluation and management, $908,160,000 for medications, and $37,467,508,716 for adverse events, after accounting for incremental genetic testing costs of $2,355,540,000. This represents total 3-year savings of $42,276,736,216, or a 47% reduction, and 3-year savings of $4,228 and annual savings of $1,409 per covered patient.

CONCLUSIONS

A precision medicine approach to genetically guided therapy for hypertension patients using a multi-gene panel reduced total 3-year costs by 47%, yielding savings exceeding $42.3 billion in an insured panel of 10 million patients. Importantly, 89% of these savings are generated by averting specific adverse events and, thus, optimizing choice of therapy in function of both safety and efficacy.

An Overview of Metabolic Phenotyping in Blood Pressure Research

PURPOSE OF THE REVIEW

This review presents the analytical techniques, processing and analytical steps used in metabolomics phenotyping studies, as well as the main results from epidemiological studies on the associations between metabolites and high blood pressure.

RECENT FINDINGS

A variety of metabolomic approaches have been applied to a range of epidemiological studies to uncover the pathophysiology of high blood pressure. Several pathways have been suggested in relation to blood pressure including the possible role of the gut microflora, inflammatory, oxidative stress, and lipid pathways. Metabolic changes have also been identified associated with blood pressure lowering effects of diets high in fruits and vegetables and low in meat intake. However, the current body of literature on metabolic profiling and blood pressure is still in its infancy, not fully consistent and requires careful interpretation. Metabolic phenotyping is a promising approach to uncover metabolic pathways associated with high blood pressure and throw light into the complex pathophysiology of hypertension.

Does Obstructive Sleep Apnea Influence Blood Pressure and Arterial Stiffness in Response to Antihypertensive Treatment?

Untreated obstructive sleep apnea (OSA) is common in patients with hypertension and may impair blood pressure (BP) and target-organ damage responses to antihypertensive therapy. In this study, we recruited hypertensive patients who underwent treatment with a 30-day regimen of hydrochlorothiazide 25 mg plus enalapril (20 mg BID) or losartan (50 mg BID) and were assessed with a baseline clinical evaluation, polysomnography, 24-hour ambulatory BP monitoring, and carotid-femoral pulse wave velocity. All the examinations except for polysomnography were repeated at 6 and 18 months of follow-up. We studied 94 hypertensive patients (mean age, 55±9 years). The frequency of OSA was 55%. Compared with baseline, we did not observe significant differences between groups in 24-hour BP, daytime systolic and diastolic BPs, or night-time systolic BP at 6 and 18 months. The BP control rate at 24 hours (<130/80 mm Hg) was similar between the groups (baseline, 42.3% versus 45.2%; 6 months, 46.9% versus 57.5%; 18 months, 66.7% versus 61.5%). However, patients with OSA had higher night-time diastolic BP decrease than did the non-OSA group (6 months, -4.9±11.8 versus -0.3±10.3 mm Hg; 18 months, -6.7±11.1 versus -1.2±10.6 mm Hg; P=0.027). There were no differences in the number and class of antihypertensive medications prescribed during follow-up. In terms of arterial stiffness, patients with OSA had higher pulse wave velocity than did patients without OSA at baseline (10.3±1.9 versus 9.2±1.7 m/s; P=0.024), but both groups had similar decreases in pulse wave velocity during follow-up. In conclusion, with combined antihypertensive treatment aimed at controlling BP, hypertensive patients with OSA had similar 24-hour BP and arterial stiffness to those without OSA.

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.

Sphingolipid Metabolic Pathway Impacts Thiazide Diuretics Blood Pressure Response: Insights From Genomics, Metabolomics, and Lipidomics

BACKGROUND

Although hydrochlorothiazide (HCTZ) is a well-established first-line antihypertensive in the United States, <50% of HCTZ treated patients achieve blood pressure (BP) control. Thus, identifying biomarkers that could predict the BP response to HCTZ is critically important. In this study, we utilized metabolomics, genomics, and lipidomics to identify novel pathways and biomarkers associated with HCTZ BP response.

METHODS AND RESULTS

First, we conducted a pathway analysis for 13 metabolites we recently identified to be significantly associated with HCTZ BP response. From this analysis, we found the sphingolipid metabolic pathway as the most significant pathway (P=5.8E-05). Testing 78 variants, within 14 genes involved in the sphingolipid metabolic canonical pathway, with the BP response to HCTZ identified variant rs6078905, within the SPTLC3 gene, as a novel biomarker significantly associated with the BP response to HCTZ in whites (n=228). We found that rs6078905 C-allele carriers had a better BP response to HCTZ versus noncarriers (∆SBP/∆DBP: -11.4/-6.9 versus -6.8/-3.5 mm Hg; ∆SBP P=6.7E-04; ∆DBP P=4.8E-04). Additionally, in blacks (n=148), we found genetic signals in the SPTLC3 genomic region significantly associated with the BP response to HCTZ (P<0.05). Last, we observed that rs6078905 significantly affects the baseline level of 4 sphingomyelins (N24:2, N24:3, N16:1, and N22:1; false discovery rate <0.05), from which N24:2 sphingomyelin has a significant correlation with both HCTZ DBP-response (r=-0.42; P=7E-03) and SBP-response (r=-0.36; P=2E-02).

CONCLUSIONS

This study provides insight into potential pharmacometabolomic and genetic mechanisms underlying HCTZ BP response and suggests that SPTLC3 is a potential determinant of the BP response to HCTZ.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT00246519.

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.

The Future of "Omics" in Hypertension

Despite decades of research and clinical practice, the pathogenesis of hypertension remains incompletely understood, and blood pressure is often suboptimally controlled. “Omics” technologies allow the description of a large number of molecular features and have the potential to identify new factors that contribute to blood pressure regulation and how they interact. In this review, we focus on the potential of genomics, transcriptomics, proteomics, and metabolomics and explore their roles in unraveling the pathophysiology and diagnosis of hypertension, the prediction of organ damage and treatment response, and monitoring treatment effect. Substantial progress has been made in the area of genomics, in which genome-wide association studies have identified > 50 blood pressure–related, single-nucleotide polymorphisms, and sequencing studies (especially in secondary forms of hypertension) have discovered novel regulatory pathways. In contrast, other omics technologies, despite their ability to provide detailed insights into the physiological state of an organism, have only more recently demonstrated their impact on hypertension research and clinical practice. The majority of current proteomic studies focus on organ damage resulting from hypertension and may have the potential to help us understand the link between blood pressure and organ failure but also serve as biomarkers for early detection of cerebrovascular or coronary disease. Examples include signatures for early detection of left ventricular dysfunction or albuminuria. Metabolomic studies have the potential to integrate environmental and intrinsic factors and are particularly suited to monitor the response to treatment. We discuss examples of omics studies in hypertension and explore the challenges related to these novel technologies.

Metabolomics enables precision medicine: "A White Paper, Community Perspective"

INTRODUCTION BACKGROUND TO METABOLOMICS

Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or "-omics" level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person's metabolic state provides a close representation of that individual's overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates.

OBJECTIVES OF WHITE PAPER—EXPECTED TREATMENT OUTCOMES AND METABOLOMICS ENABLING TOOL FOR PRECISION MEDICINE

We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject's response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient's metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine.

CONCLUSIONS KEY SCIENTIFIC CONCEPTS AND RECOMMENDATIONS FOR PRECISION MEDICINE

Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our Metabolomics Society, through its "Precision Medicine and Pharmacometabolomics Task Group", with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.