Effects and Mechanisms of Tea Regulating Blood Pressure: Evidences and Promises.
Daxiang LiRuru WangJinbao HuangQingshuang CaiChung S YangXiaochun WanZhong-Wen XiePublished in: Nutrients (2019)
Cardiovascular diseases have overtaken cancers as the number one cause of death. Hypertension is the most dangerous factor linked to deaths caused by cardiovascular diseases. Many researchers have reported that tea has anti-hypertensive effects in animals and humans. The aim of this review is to update the information on the anti-hypertensive effects of tea in human interventions and animal studies, and to summarize the underlying mechanisms, based on ex-vivo tissue and cell culture data. During recent years, an increasing number of human population studies have confirmed the beneficial effects of tea on hypertension. However, the optimal dose has not yet been established owing to differences in the extent of hypertension, and complicated social and genetic backgrounds of populations. Therefore, further large-scale investigations with longer terms of observation and tighter controls are needed to define optimal doses in subjects with varying degrees of hypertensive risk factors, and to determine differences in beneficial effects amongst diverse populations. Moreover, data from laboratory studies have shown that tea and its secondary metabolites have important roles in relaxing smooth muscle contraction, enhancing endothelial nitric oxide synthase activity, reducing vascular inflammation, inhibiting rennin activity, and anti-vascular oxidative stress. However, the exact molecular mechanisms of these activities remain to be elucidated.
Keyphrases
- blood pressure
- smooth muscle
- endothelial cells
- oxidative stress
- hypertensive patients
- cardiovascular disease
- nitric oxide synthase
- heart rate
- risk factors
- case control
- nitric oxide
- electronic health record
- healthcare
- induced pluripotent stem cells
- pluripotent stem cells
- blood glucose
- dna damage
- physical activity
- dna methylation
- type diabetes
- machine learning
- genome wide
- signaling pathway
- ischemia reperfusion injury
- gene expression
- big data
- coronary artery disease
- cardiovascular risk factors
- metabolic syndrome
- deep learning
- copy number
- skeletal muscle
- molecular dynamics
- heat shock