Biochemical Monitoring of Aortic Aneurysm Disease: History
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Aortic aneurysm (AA) disease is intractable. There are many different subtypes which may or may not include a genetic component. The pathology is different based on aneurysm location. Environmental factors, co-morbidities, and sex all differentially affect aneurysm formation and progression. Despite advancements in our understanding of the complex pathobiology of AAs, no efficient method for monitoring exists, and it is becoming clear that no single diagnostic approach will begin to address the many disparate pathological consequences.

  • aortic aneurysm
  • proteomic analysis
  • protein
  • quantification
  • microRNA
  • extracellular vesicles (EVs)
  • concentration

1. Background

Numerous studies have explored viable alternatives to imaging for detecting aneurysm disease. Several methods have included analyzing various “pathology” indicators such as circulating immune cells [33,34], markers of inflammation [35,36,37], hemostasis [38], acute-phase proteins [39,40], and plasma homocysteine levels [41,42,43]. Unfortunately, the presence of these analytes in the bloodstream can also result from recent surgery and other disease processes, problematizing diagnostic predictions.
Investigations have largely focused on the discovery of biomarkers for abdominal AAs. An outstanding review recently published in the Journal of Clinical Medicine provides an excellent summary of 25 studies that have identified specific “clinically applicable” and “experimental” biomarkers for AAs [44]. However, conclusions drawn from this retrospective analysis were somewhat anticipated: “The current literature provides a plethora of data with conflicting results and firm conclusions cannot be provided”. Given the existing hurdles in using biomarkers to predict aneurysm expansion in clinical settings—such as their lack of disease specificity and inability to cover all types of AA—an integrated prognostic model that combines select circulating markers will offer enhanced clinical utility [45]. Nevertheless, results consistently demonstrate that circulating biomarkers can be used to identify aneurysms and form the basis of an individualized surveillance strategy to discern risk. Although it is evident that these biomarkers signal the progression of pathology, creating a clinical assay based on them has proven to be challenging.

2. Genomic/Proteomic Analysis

In 2007, Wang et al. proposed a 41-panel gene signature array to identify the presence of TAAs [46]. This study successfully demonstrated that gene expression patterns in circulating leukocytes could predict the status and subtype of TAAs. More recently, Marshall et al. found elevated levels of fibrillin fragments in aneurysm patients, with concentrations varying in different anatomical locations of aneurysm (thoracic vs. abdominal) [47]. Despite the strengths of these studies, the authors were unable to definitively establish their uses as monitoring or diagnostic techniques for AAs.
In a separate investigation, proteomic analysis identified several markers for thoracic aortic aneurysms [48]. Among these, the four and a half LIM domain protein 1 (FHL1) emerged as the most useful in predicting TAA. FHL-1 was combined with Collagens I, III, V, and XI in a five-panel marker test, where upregulation of any three by over 50% successfully identified the presence of TAAs. Although these studies have made significant contributions, a successful method for biochemically monitoring aortic aneurysm disease remains obscure. Furthermore, the methodologies used in these past investigations may be too complex to expand effectively. Implementing quantitative and scalable approaches is essential for their practicality in a clinical setting.

3. Circulating Protein Quantification

Phase I results from the National Registry of Genetically Triggered Thoracic Aortic Aneurysms and Cardiovascular Conditions (GenTAC) trial revealed that circulating levels of transforming growth factor beta (TGF-β) are increased in Marfan (MFS) patients with thoracic AAs [49]. Specifically, the authors demonstrated that circulating TGF-β1 concentrations are elevated in MFS and decrease after the administration of losartan, beta-blocker therapy, or both, and therefore might serve as a prognostic and therapeutic marker in MFS patients with TAA. Given its pivotal role in vascular pathology and the maintenance of the extracellular matrix, there is considerable interest in investigating the impact of TGF-β1 on vascular remodeling. Its immense promise as a biological indicator for tracking pathology progression further accentuates this interest.
Both intracellular and extracellular mechanisms function to balance matrix deposition and degradation to maintain structural integrity of the aortic wall. In AAs, this balance becomes disrupted in favor of enhanced proteolysis, resulting in pathological remodeling, and leading to progressive dilation. Vascular remodeling is an important process in which a critical family of proteolytic enzymes, the matrix metalloproteinases (MMPs), actively participate through degradation of the vessel wall and the subsequent release of sequestered growth factors and cytokines, such as TGF-β [50,51]. This breakdown of normally long-lasting matrix molecules, such as elastin and collagen, has placed a great deal of emphasis on the importance of research focusing on the involvement of MMPs in AA. Multiple studies have demonstrated differential expression profiles of MMPs and their endogenous inhibitors, the tissue inhibitors of MMPs (TIMPs) in clinical AA specimens and animal models.
It has been shown that AAs can be identified in plasma by profiling the MMP/TIMP ratio as it provides a unique metric of aortic wall remodeling [50,51]. These proteolytic enzymes degrade all components of the vessel wall and are attributed to the development and progression of AA [52,53]. Alterations in the MMP/TIMP ratio may also be indicative of AA presence, location, and severity.
The extracellular MMP inducer (EMMPRIN), also called CD147, is a cell surface transmembrane glycoprotein that, mainly through interacting with cyclophilin A, is involved in several cellular processes including the induction of MMPs and the migration, inflammation, and transport of nutrients [54]. MMPs are known to facilitate pathological remodeling and EMMPRIN is directly involved in MMP production; thus, it is likely that EMMPRIN plays an important role in pathology. EMMPRIN is secreted from vascular smooth muscle cells in AA [55] and its expression is induced by angiotensin II and TGF-β administration in vitro [55,56].
A study of MFS patients with aortic ectasia found that EMMPRIN levels were markedly reduced; when compared with healthy controls, this proved predictive of ectasia [57]. This study attested that monitoring circulating EMMPRIN, in combination with current diagnostic tools, can effectively track aortic diameters. Importantly, circulating levels of the aforementioned proteins (MMPs, TIMPs, EMMPRIN, and TGF-βs) are all quantifiable using the high-throughput, immune-based, multiplexed screening platform: Multiplex Suspension Array [58].

4. Circulating microRNA Quantification

MicroRNAs, a class of small, non-coding RNA, function to regulate translation by interaction with the 3′-untranslated region (UTR) of targeted mRNAs [59]. Increasing evidence supports a direct role for altered microRNA abundance in pathological cardiovascular remodeling and disease progression. Alterations in microRNA abundance are emerging as a clear mechanism mediating changes in matrix remodeling pathways associated with AA. However, measuring microRNAs in blood poses challenges, primarily due to the absence of consistent, widely accepted protocols. However, by instituting standardized procedures and robust quality control measures, researchers and clinicians can heighten the dependability and precision in measuring circulating microRNAs [60]. This endeavor will bolster swift progress in molecular diagnostics and personalized medicine fields.
Multiple microRNAs are endogenous upstream regulators of many key proteins involved in aneurysm progression, and have been demonstrated to directly regulate cellular phenotype and extracellular matrix remodeling [61,62,63]. In combination with MMP and TIMP concentrations, microRNA levels, when united with multivariable stepwise regression, have shown significant promise in the algorithmic detection of thoracic AAs: these can identify and distinguish between etiological subtypes of TAA with an accuracy exceeding 95% [58]. Moreover, a linear correlation exists between circulating levels of several of these microRNAs and aortic diameters, suggesting that quantification may be used as a predictor of risk [58,61].

5. Circulating Extracellular Vesicle Concentration, Size Distribution, and Cargo Analysis

More circulating targets for AA diagnosis and monitoring are emerging. Wang and colleagues demonstrated the involvement of extracellular vesicles (EVs) derived from macrophages in the pathogenesis of abdominal aortic aneurysms [64]. EVs play a crucial role in cell-to-cell communication, comprising exosomes (sized between 30 and 100 nm) and microvesicles (ranging from 100 to 300 nm), originating from various cell types. Studies highlight that circulating EVs harbor MMPs, TIMPs, and microRNAs. Furthermore, vascular cells release multiple microRNAs in EVs due to disease progression [65]. This results in altered circulating microRNA profiles, reflecting the origin and location of an aneurysm, thereby establishing distinct EV contents specific to different types of aortic aneurysms. In addition to alterations in cargo, EV concentrations and size distributions are altered in MFS patients with TAA, suggesting that profiling them will establish their clinical utility as a novel diagnostic [66].
These findings illustrate EVs’ diagnostic potential, but EVs are technically difficult to examine and analyze; therefore, isolation protocols must be optimized and standardized to ensure consistent quantification and the accuracy of size-based categorization. Similarly to assessments of earlier protein and nucleic acid targets, quantifying EVs requires implementing standardized procedures and robust quality control measures [66]. This approach aims to enhance the reliability and precision of measurements and subsequent downstream analyses for researchers and clinicians.

This entry is adapted from the peer-reviewed paper 10.3390/jcm13030818

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