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Hypertension pharmacogenomics: in search of personalized treatment approaches.

ABSTRACT: 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.

SUBMITTER: Cooper-DeHoff RM

PROVIDER: S-EPMC4778736 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Hypertension pharmacogenomics: in search of personalized treatment approaches.

Cooper-DeHoff Rhonda M RM Johnson Julie A JA

Nature reviews. Nephrology 20151123 2

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 li ...[more]

PMID: 26592190

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Project description:Background The implementation of genotyping for anti-hypertensive drugs in clinical practice remains a challenge. We conducted this study to analyze the distribution of polymorphisms of antihypertensive drug-related genes in Changsha County in China and compare the clinical effectiveness of genotype-guided and clinical experience-guided antihypertensive therapy in hypertensive individuals. Methods A total of 9,933 essential hypertensive participants from Changsha County were consecutively enrolled in our study, and 7 genetic polymorphic loci (CYP2D6*10, ADRB1, CYP2C9*3, AGTR1, ACE, CYP3A5*3 and NPPA) were detected by a polymerase chain reaction (PCR)-fluorescence probe. From an available sample of 660 hypertensive participants, 495 cases were randomly identified by genotype-guided therapy and 165 cases by clinical experience-guided therapy. We performed 24-hour ambulatory blood pressure (BP) monitoring on each of these cases, pre- and post-intervention. Results In the enrolled 9,933 cases, the mutation frequencies of CYP2C9*3, ADRB1(1165G>C), AGTR1(1166A>C), CYP2D6*10, ACE(I/D), CYP3A5*3 and NPPA(2238T>C) were 4.41%, 74.60%, 5.55%, 57.08%, 30.94%, 69.03% and 1.19%, respectively. In both genotype-guided and clinical experience-guided groups, the comparisons of intra-group pre-and post-treatments showed significant decreases in diastolic blood pressure (DBP) (P<0.01) and significant increases in the control rate of BP (47.1% vs. 38.6% and 37.5% vs. 33.9%, P<0.05) in response to adjusted antihypertensive agents. Correspondingly, the extent of the reduction of systolic blood pressure (SBP; 3.52±11.72 vs. 0.92±9.14 mmHg), the extent of the increase in the rate of BP control (8.5% vs. 3.6%) and the percentage rate of decrease of grades 2 and 3 hypertensive individuals were more significant in the genotype-guided group than that in the clinical experience-guided group (P<0.01). Conclusions While prescribing anti-hypertensive drugs, appropriate dosage and type adjustments should be made according to the gene mutation frequency and individual circumstances. Pharmacogenomics-guided personalized treatment of hypertensive patients is likely to be a more effective strategy, especially in those with significantly elevated SBP.

Project description:Personalized medicine (personalized psychiatry in a specific setting) is a new model towards individualized care, in which knowledge from genomics and other omic pillars (microbiome, epigenomes, proteome, and metabolome) will be combined with clinical data to guide efforts to new drug development and targeted prescription of the existing treatment options. In this review, we summarize pharmacogenomic studies in mood disorders that may lay the foundation towards personalized psychiatry. In addition, we have discussed the possible strategies to integrate data from omic pillars as a future path to personalized psychiatry. So far, the progress of uncovering single nucleotide polymorphisms (SNPs) underpinning treatment efficacy in mood disorders (e.g., SNPs associated with selective serotonin re-uptake inhibitors or lithium treatment response in patients with bipolar disorder and major depressive disorder) are encouraging, but not adequate. Genetic studies have pointed to a number of SNPs located at candidate genes that possibly influence response to; (a) antidepressants COMT, HTR2A, HTR1A, CNR1, SLC6A4, NPY, MAOA, IL1B, GRIK4, BDNF, GNB3, FKBP5, CYP2D6, CYP2C19, and ABCB1 and (b) mood stabilizers (lithium) 5-HTT, TPH, DRD1, FYN, INPP1, CREB1, BDNF, GSK3β, ARNTL, TIM, DPB, NR3C1, BCR, XBP1, and CACNG2. We suggest three alternative and complementary strategies to implement knowledge gained from pharmacogenomic studies. The first strategy can be to implement diagnostic, therapeutic, or prognostic genetic testing based on candidate genes or gene products. The second alternative is an integrative analysis (systems genomics approach) to combine omics data obtained from the different pillars of omics investigation, including genomics, epigenomes, proteomics, metabolomics and microbiomes. The main goal of system genomics is an identification and understanding of biological pathways, networks, and modules underlying drug-response. The third strategy aims to the development of multivariable diagnostic or prognostic algorithms (tools) combining individual's genomic information (polygenic score) with other predictors (e.g., omics pillars, neuroimaging, and clinical characteristics) to finally predict therapeutic outcomes. An integration of molecular science with that of traditional clinical practice is the way forward to drug discoveries and novel therapeutic approaches and to characterize psychiatric disorders leading to a better predictive, preventive, and personalized medicine (PPPM) in psychiatry. With future advances in the omics technology and methodological developments for data integration, the goal of PPPM in psychiatry is promising.

Dataset Information

Hypertension pharmacogenomics: in search of personalized treatment approaches.

Publications

Hypertension pharmacogenomics: in search of personalized treatment approaches.

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