Kinin B1 Receptor Mediates Bidirectional Interaction between Neuroinflammation and Oxidative Stress.
Drew TheobaldSrinivas SriramulaPublished in: Antioxidants (Basel, Switzerland) (2023)
Hypertension is associated with increased expression of kinin B1 receptors (B1R) and increased levels of pro-inflammatory cytokines within the neurons. We previously reported that angiotensin II (Ang II) upregulates B1R expression and can induce neuroinflammation and oxidative stress in primary hypothalamic neurons. However, the order in which B1R activation, neuroinflammation, and oxidative stress occur has not yet been studied. Using primary hypothalamic neurons from neonatal mice, we show that tumor necrosis factor (TNF), lipopolysaccharides (LPS), and hydrogen peroxide (H 2 O 2 ) can upregulate B1R expression and increase oxidative stress. Furthermore, our study shows that B1R blockade with R715, a specific B1R antagonist, can attenuate these effects. To further confirm our findings, we used a deoxycorticosterone acetate (DOCA)-salt model of hypertension to show that oxidative stress is upregulated in the hypothalamic paraventricular nucleus (PVN) of the brain. Together, these data provide novel evidence that relationship between oxidative stress, neuroinflammation, and B1R upregulation in the brain is bidirectional, and that B1R antagonism may have beneficial effects on neuroinflammation and oxidative stress in various disease pathologies.
Keyphrases
- oxidative stress
- angiotensin ii
- dna damage
- poor prognosis
- diabetic rats
- hydrogen peroxide
- ischemia reperfusion injury
- traumatic brain injury
- lipopolysaccharide induced
- cerebral ischemia
- lps induced
- blood pressure
- cognitive impairment
- spinal cord
- inflammatory response
- rheumatoid arthritis
- nitric oxide
- cell proliferation
- white matter
- resting state
- type diabetes
- binding protein
- long non coding rna
- heat shock
- vascular smooth muscle cells
- functional connectivity
- artificial intelligence
- multiple sclerosis
- skeletal muscle
- endoplasmic reticulum stress
- deep learning