Author(s): Huang MH, Poh KK, Tan HC, Welt FG, Lui CY
Abstract Share this page
Abstract The β1-blocker when administered before reperfusion activates myocyte prosurvival signaling via β2-adrenergic receptor (β2-AR) and protein kinase A (PKA)-dependent mechanism during ischemia/reperfusion (I/R). The heart is endowed with powerful self-protective ability executed by endogenous β2-adrenopeptide receptor activation. I/R triggers cardiac epinephrine and neuropeptide calcitonin gene-related peptide (CGRP) release. Cardiac β1- and β2-AR stimulation mediates pro- and anti-apoptotic cell signaling, respectively. Removal of myocardial β1-AR-derived proapoptotic force with β1-AR blockade unmasks the dominance of β2-AR mediated prosurvival cell signaling through the well-defined PKA-Akt dependent mechanism. This review focuses on recent clinical and experimental findings including intrinsic cardiac β2-adrenopeptide neuroparacrine signaling mechanisms involved in I/R injury protection. While β2-adrenopeptide-mediated cardioprotection is important, age-related β2-adrenopeptide receptor decoupling can result in their ineffectiveness in response to the receptor-specific therapies. Accordingly, direct activation of receptor-coupled upstream PKA-dependent signaling may serve as a therapeutic alternative to achieve cardioprotection bypassing adrenopeptidergic receptor decoupling accompanied with aging. Phosphodiesterase-3 (PDE3) inhibitor reduces infarct-size via cAMP-dependent PKA signaling. Non-β1-AR-mediated PKA activation activates multiple prosurvival signaling pathways eventually leading to Akt activation. Combination therapy with β1-blocker esmolol and PDE3 inhibitor milrinone additively reduced infarct-size in preclinical studies. Concurrent β1-AR blockade and PDE3 inhibition provides complementary synergy with promising therapeutic potential in patients with acute myocardial infarction and beyond. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
This article was published in Int J Cardiol
and referenced in Journal of Data Mining in Genomics & Proteomics