Crosstalk of Diabetic Conditions with Static Versus Dynamic Flow Environment-Impact on Aortic Valve Remodeling.
Jessica I SeligJoana BoulgaropoulosNaima NiazyD Margriet OuwensKarlheinz PreußPatrick HornRalf WestenfeldArtur LichtenbergPayam AkhyariMareike BarthPublished in: International journal of molecular sciences (2021)
Type 2 diabetes mellitus (T2D) is one of the prominent risk factors for the development and progression of calcific aortic valve disease. Nevertheless, little is known about molecular mechanisms of how T2D affects aortic valve (AV) remodeling. In this study, the influence of hyperinsulinemia and hyperglycemia on degenerative processes in valvular tissue is analyzed in intact AV exposed to an either static or dynamic 3D environment, respectively. The complex native dynamic environment of AV is simulated using a software-governed bioreactor system with controlled pulsatile flow. Dynamic cultivation resulted in significantly stronger fibrosis in AV tissue compared to static cultivation, while hyperinsulinemia and hyperglycemia had no impact on fibrosis. The expression of key differentiation markers and proteoglycans were altered by diabetic conditions in an environment-dependent manner. Furthermore, hyperinsulinemia and hyperglycemia affect insulin-signaling pathways. Western blot analysis showed increased phosphorylation level of protein kinase B (AKT) after acute insulin stimulation, which was lost in AV under hyperinsulinemia, indicating acquired insulin resistance of the AV tissue in response to elevated insulin levels. These data underline a complex interplay of diabetic conditions on one hand and biomechanical 3D environment on the other hand that possesses an impact on AV tissue remodeling.
Keyphrases
- aortic valve
- type diabetes
- transcatheter aortic valve replacement
- transcatheter aortic valve implantation
- aortic valve replacement
- aortic stenosis
- glycemic control
- insulin resistance
- signaling pathway
- protein kinase
- metabolic syndrome
- south africa
- cell proliferation
- heart failure
- coronary artery disease
- electronic health record
- oxidative stress
- atrial fibrillation
- cardiovascular disease
- epithelial mesenchymal transition
- long non coding rna
- machine learning
- data analysis
- binding protein
- induced apoptosis
- polycystic ovary syndrome