Gene expression profiling in abdominal aortic aneurysms after finite element rupture risk assessment

• Verfasst von: Erhart, Philipp [VerfasserIn]
• Verfasst von: Schiele, Sandra [VerfasserIn]
• Verfasst von: Grond-Ginsbach, Caspar [VerfasserIn]
• Verfasst von: Hakimi, Maani [VerfasserIn]
• Verfasst von: Böckler, Dittmar [VerfasserIn]
• Verfasst von: Lorenzo Bermejo, Justo [VerfasserIn]
• Verfasst von: Dihlmann, Susanne [VerfasserIn]
• Titel: Gene expression profiling in abdominal aortic aneurysms after finite element rupture risk assessment
• Verf.angabe: Philipp Erhart, Sandra Schiele, Philip Ginsbach, Caspar Grond-Ginsbach, Maani Hakimi, Dittmar Böckler, Justo Lorenzo-Bermejo, and Susanne Dihlmann
• E-Jahr: 2017
• Jahr: December 1, 2017
• Umfang: 9 S.
• Fussnoten: Gesehen am 21.11.2018
• Titel Quelle: Enthalten in: Journal of endovascular therapy
• Ort Quelle: Thousand Oaks, Calif. : Sage, 2000
• Jahr Quelle: 2017
• Band/Heft Quelle: 24(2017), 6, Seite 861-869
• ISSN Quelle: 1545-1550
• DOI: doi:10.1177/1526602817729165
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1583935169

Abstract

Purpose: To investigate the association between local biomechanical rupture risk calculations from finite element analysis (FEA) and whole-genome profiling of the abdominal aortic aneurysm (AAA) wall to determine if AAA wall regions with highest and lowest estimated rupture risk show different gene expression patterns. Methods: Six patients (mean age 74 years; all men) scheduled for open surgery to treat asymptomatic AAAs (mean diameter 55.2±3.5 mm) were recruited for the study. Rupture risk profiles were estimated by FEA from preoperative computed tomography angiography data. During surgery, AAA wall samples of ~10 mm2 were extracted from the lowest and highest rupture risk locations identified by the FEA. Twelve samples were processed for RNA extraction and subsequent whole genome expression profiling. Expression of single genes and of predefined gene groups were compared between vessel wall areas with highest and lowest predicted rupture risk. Results: Normalized datasets comprised 15,079 gene transcripts with expression above background. In biopsies with high rupture risk, upregulation of 18 and downregulation of 18 genes was detected when compared to the low-risk counterpart. Global analysis of predefined gene groups revealed expression differences in genes associated with extracellular matrix (ECM) degradation (p<0.001), matrix metalloproteinase activity (p<0.001), and chemokine signaling (p<0.001). Conclusion: Increased expression of genes involved in degrading ECM components was present in AAA wall regions with highest biomechanical stress, supporting the thesis of mechanotransduction. More experimental studies with cooperation of multicenter vascular biobanks are necessary to understand AAA etiologies and identify further parameters of FEA model complementation.