Pharmacogenomics And Hypertension: Current Insights.
Gustavo H Oliveira-PaulaSherliane Carla PereiraJose E Tanus-SantosRiccardo LacchiniPublished in: Pharmacogenomics and personalized medicine (2019)
Hypertension is a multifactorial disease that affects approximately one billion subjects worldwide and is a major risk factor associated with cardiovascular events, including coronary heart disease and cerebrovascular accidents. Therefore, adequate blood pressure control is important to prevent these events, reducing premature mortality and disability. However, only one third of patients have the effective control of blood pressure, despite several classes of antihypertensive drugs available. These disappointing outcomes may be at least in part explained by interpatient variability in drug response due to genetic polymorphisms. To address the effects of genetic polymorphisms on blood pressure responses to the antihypertensive drug classes, studies have applied candidate genes and genome wide approaches. More recently, a third approach that considers gene-gene interactions has also been applied in hypertension pharmacogenomics. In this article, we carried out a comprehensive review of recent findings on the pharmacogenomics of antihypertensive drugs, including diuretics, β-blockers, angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, and calcium channel blockers. We also discuss the limitations and inconsistences that have been found in hypertension pharmacogenomics and the challenges to implement this valuable approach in clinical practice.
Keyphrases
- blood pressure
- angiotensin converting enzyme
- angiotensin ii
- cardiovascular events
- hypertensive patients
- genome wide
- adverse drug
- heart rate
- vascular smooth muscle cells
- clinical practice
- risk factors
- copy number
- clinical decision support
- dna methylation
- coronary artery disease
- cardiovascular disease
- end stage renal disease
- newly diagnosed
- blood glucose
- multiple sclerosis
- ejection fraction
- prognostic factors
- chronic kidney disease
- gene expression
- adipose tissue
- type diabetes
- transcription factor
- patient reported outcomes
- patient reported