(A-20) Systems Analysis of Beta-Blocker Activation of Cardiomyocyte Proliferation

Introduction::

Heart disease continues to be the leading cause of death in the United States. An underlying complication when treating diseases such as a Myocardial Infarction (MI) is the lack of regenerating cardiomyocytes (CMs). Renewal of CMs approaches a standstill shortly after birth. Regeneration of functional CMs requires proliferation from myocardium as opposed to endogenous progenitor cells. The beta-adrenergic receptor activates cAMP, PKA, etc. and results in an increase of heart rate and blood pressure. There exist multiple forms of beta-receptors, but beta-1-adrenergic predominates in CMs. Beta-blockers are the standard of care therapeutic prescribed following MI. Partial agonism/antagonism and selectivity of the types of beta-adrenergic receptors characterize the classes of beta-blockers. While beta-blockers increase CM mitosis and cytokinesis (Sakabe et al. 2022), the drug-specific processes that drive this proliferative effect remain unclear. The goal of this project is to discover the Network mechanisms that drive cardiomyocyte proliferation in response to beta blockers.

Materials and Methods::

A model was compiled that combined the previous Proliferation (Harris et al. 2022) and Beta-1-Adrenergic (Kraeutler et al. 2022) network models. The original Proliferation model produces the dynamic activity of its outputs: Mitosis, Cytokinesis, DNA Replication, Polyploid, and Binucleation. Both models made use of Netflux, a program that utilizes logic-based differential equations. A sensitivity analysis measured the system reactivity towards the knockdown of each node. Subsequent simulations measured the steady-state activity of each species when B1AR was completely inhibited. Cytoscape was utilized to assemble the system and visualize the network. The CyAnimator tool on Cytoscape demonstrated the dynamics of nodal activity over each time point.  Overlapping nodes were calibrated to approximately reproduce the activity and dynamics of the original model outputs. The model simulated inhibition/antagonism by manually knocking-out of the B1AR node. The change and fold-change of the activity of each node between the control and B1AR-inhibition context were found. The change of each node was visualized in Cytoscape. Model validation was accomplished by comparing models to experimental findings. PH3-positive cell proportion served as a representation of the activity of mitosis and number of cells expressing Aurora Kinase B (AURKB) in the midbody served as a predictor for cytokinesis activity.

Results, Conclusions, and Discussions::

The new combination model included connections that had overlapping nodes such as PKA, G-protein beta-gamma subunit, and Ras. The simulation predicts both an increase in cytokinesis and mitosis upon B1AR inhibition. Assuming metoprolol as solely an inactivator of B1AR, both the proportion of PH3-positive cells and number of cells expressing AURKB increase when metoprolol is applied. The model also predicted that the inhibition of the G-protein alpha subunit (Gsa) resulted in an increase in the activities of both mitosis and cytokinesis and a reduction in the activity of cyclic AMP (cAMP). Consistent with model predictions, the experimental knockout of Gsa, the gene that encodes for the G-protein alpha subunit, caused both an increase in the percent of cells expressing PH3+ and AURKB and a decrease in relative cAMP expression when the metoprolol is applied. The model also simulated the effects of a YAP co-knock out, resulting in an increased mitotic activity when YAP expressed normally and no beta-blocker proliferative effects when YAP was inhibited. The experiment resulted in negligible metoprolol effects when YAP is knocked out, and a significant increase in PH3+ expression with metoprolol when YAP is left unchanged, consistent with model simulations. This result demonstrates the central role that the YAP-Hippo pathway is in the efficacy of beta-blockers. Overall, we were able to predict 80% of the output activity with the combined Beta-Adrenergic-Proliferation Model. Implementing further with different types of beta-blockers, such as propranolol and carvedilol, will allow for a greater understanding of the mechanisms by which these drugs differ, which has immense biological and clinical value. In the future, exploration of additional pathways, such as a possible connection to the protein RhoA, is necessary to optimize the proportion of correct predictions. In-vitro and in-vivo experiments for the effects other types of beta-blockers have on proliferation will certainly also need to be performed in the future. This work enhances our current understanding of beta-blocker mechanisms.

Acknowledgements (Optional): : Funding source: NSF Award #1950374

References (Optional): : Masahide Sakabe, Michael Thompson, Nong Chen, Mark Verba, Aishlin Hassan, Richard Lu, Mei Xin (2022) Inhibition of β1-AR/Gαs signaling promotes cardiomyocyte proliferation in juvenile mice through activation of RhoA-YAP axis eLife 11:e74576
https://doi.org/10.7554/eLife.74576