Introduction: Abdominal Aortic Aneurysm (AAA) is a life-threatening condition characterized by the dilation of the abdominal aortic lumen ≥ 50% of its original diameter, claiming approximately 14,000 lives annually. A key pathway leading to AAA involves phenotypic changes and loss of aortic smooth muscle cells (AoSMCs), which in turn triggers pro-inflammatory macrophage (M1-Macs) signaling, and promotes the disease. Low-density lipoprotein (LDL) has also been shown to increase in AAA patients, suggesting that increased LDL is another contributing factor. There are no preventive approaches for AAA, however understanding these intricate molecular mechanisms is paramount for developing preventative strategies. Proprotein convertase subtilisin kexin type 9 (PCSK9) typically originates in the liver and is known for its degrading function of LDL-receptors that causes high LDL levels in plasma and can lead to life-threatening cardiovascular events. Emerging evidence suggests that ectopic PCSK9 expression in the AoSMCs fosters pro-inflammatory pathways in the aorta through direct stimulation of inflammatory signaling and through increased levels of oxidized LDL that could exacerbate AAA development. Notably, inhibiting PCSK9 has already been effectively utilized to treat statin-resistant hypercholesterolemia. However, little is known in the literature whether such inhibition would effectively disrupt the positive feedback loop between the AoSMCs and the pro-inflammatory M1-Macs, both key players in AAA progression. Since PCSK9 has been shown to increase LDL levels, we hypothesize that its addition to hAoSMCs will cause a pro-inflammatory response through the buildup of lipids and a phenotypic switch from contractile to synthetic.
Materials and
Methods: To test this hypothesis, we quantified the difference in lipid content in AoSMCs with and without PCSK9 using holotomographic microscopy (HTM). HTM is a novel imaging technique which images the refractive index of cells and their subcellular organelles and components label-free with a resolution of 200 nm. This imaging technique allows for longterm cell imaging without the need for staining or fixing. hAoSMCs were imaged in 5 minute intervals over 12 hours and subsequently treated with one 2.5 µg/ml dose of PCSK9. The same cells were then imaged for another 12 hours to monitor any differences in cellular lipid content and morphological changes. Since HTM images are saved as a 3D stack, advanced image processing is required. Each image was converted into a max intensity projection image, brightened, and thresholded using ImageJ. An automated script was implemented to use the analyze particles plugin to obtain lipid counts at T=0, T=12 hours, and T=24 hours.
Results, Conclusions, and Discussions: In Figure 1A and Figure 1 B, respectively we report HTM images of untreated and treated hAoSMC images with clearly visible lipids. Lipid content in untreated hAoSMCs decreased from 296 droplets at T=0 to 279 at T=1 Hr, while it increased in treated hAoSMCs from 298 at T=0 to 307 at T=1 Hr as seen in Figure 2. The image processing yielded quantitative data suggesting that there was an increase in lipids after PCSK9 was added to the culture. However, the data has yet to be repeated, so we plan to perform replicates in order to test our hypothesis. Qualitatively speaking, cellular morphology also appeared different as the cells began to migrate more and appear to obtain a hill and valley growth consistent with the synthetic phenotype. The morphological changes of hAoSMCs requires further work to determine conclusive findings. Furthermore, the investigation of intercellular networking between hAoSMCs and M1-Macs via SMC-derived EVs will be performed. There is promising evidence that PCSK9 addition to hAoSMCs produces a pro-inflammatory response through an increase in lipid intake and phenotypic switch to a synthetic phenotype. Understanding this response and how it affects hAoSMC-M1-Mac signaling will bring us one step closer to determining the effectiveness of PCSK9-inhibitors as a treatment for AAA.
Acknowledgements (Optional): I would like to acknowledge Dr. Yae Hyun Rhee and Dr. Philip S. Tsao for their guidance and support on this project.
