Targeting Biomechanical Signaling in AAA

Ralph H Johnson Va Medical Center, Charleston SC

Investigators

Abstract

Abdominal aortic aneurysms (AAA) afflict ~8% of Americans and ruptured AAA carries >80% mortality. Screening programs have increased identification of small AAA, but there is no directed medical therapy to inhibit growth and rupture rates have not decreased. The technologic advances in endovascular AAA repair have been vast while our ability to correlate pathology to clinical care has lagged. There is a clear need for a platform to incorporate patient-specific mechanobiologic stressors to complement aortic diameter measurements and inform treatment decisions. Inhibition of two mechanical signaling molecules, the AngiotensinII-type 1 receptor (AT1R) and the serum and glucocorticoid inducible kinase-1 (SGK-1), has been explored in pre-clinical experimentation and hold promise for clinical application. In mice treated with the AT1R blocker Losartan or SGK-1 inhibitor EMD638683, AAA growth was abrogated and only ~25% aortic dilation was observed, suggesting that there was a non-mechanical contribution to this early matrix remodeling. Additionally, since both inhibitors led to the same degree of aortic remodeling, it has raised the question of whether AT1R and SGK-1 operate interdependent mechanical signaling cascades. Interest in SGK-1 as a druggable target in small AAA was amplified when it was discovered that upregulated SGK-1 activity promoted VSMC pro-inflammatory cytokine synthesis, while SGK-1 inhibition restored VSMC contractile function as quantified by ultrasound-derived pulse propagation velocity (PPV). Therefore, SGK-1 is a prime candidate to transduce aortic mechanical strain to promote VSMC synthetic activity in AAA growth. We propose that VSMC synthetic phenotypes evolve during AAA growth based on mechanical activation of SGK-1 and that the plasma levels of well-documented AAA biomarkers represent an opportunity to define these transitions. Specific biomarkers assessed in this project incorporate inflammatory cytokines (Interleukin-6, IL-6), protease systems (Matrix metalloproteinse-9, MMP-9; CathepsinS, CtsS; CystatinC, CysC), markers of calcification (Osteoprotegerin, OPG), and fibrillar matrix peptides (TenascinC, TNC). Integrating these pathologic matrix markers (PMMs) with ultrasound-derived mechanical aortic strain and immunohistochemical analysis may enable prediction of aortic wall instability. We hypothesize that increased aortic stiffness can mechanically activate SGK-1 to alter VSMC synthetic activity to promote PMM production, aortic matrilysis, and AAA growth. In Aim 1, stimulation with axial tension will confirm upregulated SGK-1 activity in murine abdominal aortic rings. Dependence of PMM expression on SGK-1 activity will be explored by blocking with EMD638683 versus Losartan. Data will be computationally integrated to explore additional pathways engaged in tension-induced VSMC synthetic activity. In Aim 2, mice will undergo AAA induction with peri- adventitial application of CaCl2. Ultrasound-derived aortic strain parameters include quantification of global radial strain, distensibility, and pulse propagation velocity. Assessment of aortic strain parameters, plasma PMMs, and SGK-1 activity will occur at days 0, 7, 21, and 42. Integrity of matrix components as well as the quantification and localization of inflammatory infiltrate and VSMC phenotypes will be completed utilizing the Hyperion Imaging Mass Cytometry. To demonstrate the integral role of SGK-1 in PMM production, aortic wall inflammation, and VSMC synthetic phenotype, a subset of animals will have EMD638683 versus Losartan therapy initiated at day 21. Computational modeling will integrate aortic strain parameters, PMMs, and SGK-1 activity to define synergistic relationships that can be further interrogated. In Aim 3, patients with normal aorta versus small AAA will have plasma PMMs and ultrasound-derived aortic strain collected annually over 3 years. Computational assessment of this data will further support the concept that these easily accessible biomechanical indicators can be utilized to predict aortic growth. Integrating mechanical stressors with PMMs may enhance the analysis of aortic wall pathobiology during growth of small AAA to expedite identification of druggable targets and the characteristics of patients who would benefit from that therapy.