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. 2019 Sep;26(3):148-155.
doi: 10.1080/13506129.2019.1625323. Epub 2019 Jun 18.

Idiopathic degenerative thoracic aneurysms are associated with increased aortic medial amyloid

Hannah A Davies  1 , Eva Caamaño-Gutiérrez  2 , Ya Hua Chim  3 , Mark Field  4 , Omar Nawaytou  4 , Lorenzo Ressel  5 , Riaz Akhtar  3 , Jillian Madine  1
Affiliations

Idiopathic degenerative thoracic aneurysms are associated with increased aortic medial amyloid

Hannah A Davies et al. Amyloid. 2019 Sep.

Abstract

Objective: To explore the relationship of aortic medial amyloid with biochemical and micromechanical properties of the aortic wall in aneurysm patients. Methods: Human aortic tissues removed during aneurysm surgery from tricuspid (idiopathic degenerative aneurysm, DA) and bicuspid valve (BAV) patients were subjected to oscillatory nanoindentation experiments to determine localised mechanical properties of the tissue (shear storage modulus, G´ and shear loss modulus, G˝). Collagen, elastin, matrix metalloproteinase 2 and glycosaminoglycans concentrations were determined, along with relative levels of aortic medial amyloid-related factors (medin, milk fat globule-EGF factor 8, oligomers and fibrils). Measurements were combined with clinical data and statistical analyses performed. Results: The DA cohort can be divided based on their phenotype. One group shared similar characteristics with BAV patients, termed bicuspid like phenotype-tricuspid valve. The second group had high amyloid oligomer species present with a significantly lower G´ (p = .01), indicative of reduced elastic response of the tissue, termed amyloid-rich. Conclusions: We identified a group of DA patients with high amyloid oligomers and altered micromechanical and structural properties of the vessel wall. We propose these findings as a cause for aneurysm formation in these patients. Amyloid is not found in BAV patients, suggesting at least two distinct mechanisms for pathogenesis.

Keywords: Aortic medial amyloid; bicuspid valve syndrome; biomechanics; medin; oligomer; thoracic aortic aneurysm.

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Figures

Figure 1.
Figure 1.
Workflow for the study. Aortic tissue was obtained during aortic replacement surgery from 26 aneurysm patients. Tissue was subjected to biomechanical testing and subsequently digested (using papain or oxalic acid) or homogenised as shown for each biochemical measurement. Biomechanical and biochemical data were combined with patient data to perform statistical analyses which resulted in disease re-classification of the degenerative aneurysm patients into two distinct groups.
Figure 2.
Figure 2.
Ward hierarchical clustering of degenerative aneurysm patients. Ward hierarchical clustering for degenerative aneurysm patients (n = 13) using Euclidean distance of all the quantitative variables. Boxes represent clusters with an unbiased p values over 0.90 indicating that these clusters are robust, thus identifying two groups of patients.
Figure 3.
Figure 3.
PCA plot with three classification groups. (A) PCA score plot of all quantitative variables for all patients. Each dot represents a patient, which are coloured by their grouping; bicuspid valve (BAV, open squares, n = 13), bicuspid like phenotype-tricuspid valve (BP-TV, black triangles, n = 4) and amyloid-rich (black circles, n = 9). Ellipses represent 75% of the region around the mean of the points of each group. (B) Biplot of the PCA shown in (A) that superposes the scores with the loadings showing that the variables that contribute the most in the separation between the amyloid-rich group and both BAV and BP-TV are oligomers, medin, MFGE8 and fibril levels as well as age, G´ and G˝.
Figure 4.
Figure 4.
Heatmap of all patients. In rows are shown the patients grouped by their identity as shown. It is noticeable that bicuspid like phenotype-tricuspid valve (BP-TV) share more similarities with bicuspid valve (BAV) patients that amyloid-rich particularly in amyloid characteristics (bottom right corner); medin, MFGE8, oligomer, fibril levels and age. Data was mean centred and scaled. Colours represent lower abundance than the mean (blue), close to the mean (white) and higher abundance than the mean (red). Variables are ordered based on complete-linkage clustering for easy visualisation.
Figure 5.
Figure 5.
Boxplots of variables between the three groups. (A) Variables that show significant differences between the three groups as shown in Table 1 (bicuspid valve n = 13, bicuspid like phenotype-tricuspid valve n = 4, amyloid-rich n = 9). (B) Additional variables showing increased levels in the amyloid-rich group compared to the other two groups. Variable distribution is shown as boxes containing the interquartile ratio (first and third quantiles) with the median shown (bold line), whiskers represent the 5–95% range, respectively. Each point within the plot represents a patient sample for the variable specified.
Figure 6.
Figure 6.
Histological appearance of aortic wall in samples from bicuspid valve (A) and amyloid-rich (B) groups. Appearance of aorta exhibiting a structure within normal limits and correct orientation of elastic fibres (inset) (A). Loss of structure, and de-arrangement of smooth muscle and elastic fibres (inset) (B). Haematoxylin Eosin, original magnification ×100; Inset: Verhoeff-van Gieson (EVG), original magnification ×400.
Figure 7.
Figure 7.
Summary schematic showing hypothesised involvement of amyloid formation in thoracic aortic aneurysm. Data presented here suggests amyloid aggregation (increased oligomers and fibrils) affect the normal mechanical response of the aorta through altered microstructure (decreased G´ ) within the aorta wall, in turn leasing to aneurysm formation (grey boxes). It has been shown previously that medin and other amyloid proteins cause enhanced inflammatory and oxidative stress conditions that may provide the link between aggregation and altered aortic wall integrity.
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