Circulating Biomarkers for the Prediction of Abdominal Aortic Aneurysm Growth

Background: Abdominal aortic aneurysm represents a distinct group of vascular lesions, in terms of surveillance and treatment. Screening and follow-up of patients via duplex ultrasound has been well established and proposed by current guidelines. However, serum circulating biomarkers could earn a position in individualized patient surveillance, especially in cases of aggressive AAA growth rates. A systematic review was conducted to assess the correlation of AAA expansion rates with serum circulating biomarkers. Methods: A data search of English medical literature was conducted, using PubMed, EMBASE, and CENTRAL, until 7 March 2021, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement (PRISMA) guidelines. Studies reporting on humans, on abdominal aortic aneurysm growth rates and on serum circulating biomarkers were included. No statistical analysis was conducted. Results: A total of 25 studies with 4753 patients were included. Studies were divided in two broad categories: Those reporting on clinically applicable (8 studies) and those reporting on experimental (17 studies) biomarkers. Twenty-three out of 25 studies used duplex ultrasound (DUS) for following patients. Amongst clinically applicable biomarkers, D-dimers, LDL-C, HDL-C, TC, ApoB, and HbA1c were found to bear the most significant association with AAA growth rates. In terms of the experimental biomarkers, PIIINP, osteopontin, tPA, osteopontin, haptoglobin polymorphisms, insulin-like growth factor I, thioredoxin, neutrophil extracellular traps (NETs), and genetic factors, as polymorphisms and microRNAs were positively correlated with increased AAA expansion rates. Conclusion: In the presence of future robust data, specific serum biomarkers could potentially form the basis of an individualized surveillance strategy of patients presenting with increased AAA growth rates.


Introduction
Despite abdominal aortic aneurysm (AAA) being an asymptomatic entity, rupture complicates this silent pathology with a high mortality risk. Aneurysm identification on incidental imaging or screening programs at an early stage and small diameter allows for a close surveillance and repair [1]. However, not all aneurysms expand with the same rate and are not associated with the same risk of rupture, while diameter cannot always predict the physical evolution of an AAA [2][3][4]. A plethora of studies using imaging modalities and AAA anatomical characteristics tended to define models that could describe the expansion model of small or larger AAAs [5][6][7][8]. From ultrasonography to modern mathematical flow models, different methods have been used to identify these markers that could eliminate this group of patients needing closer re-evaluation and earlier management [9].
As different anatomical characteristics recorded on imaging modalities have been associated with aneurysm expansion, an analogous interest exists regarding the application of biomarkers that could identify AAA growth [10,11]. However, important discrepancies exist among the available studies [11]. A large spectrum of biomarkers is recorded in the current literature, from the commonly applied clinical circulating biomarkers to more specific sophisticated genetic models that could be used to evaluate AAA expansion rate [12]. The need to predict aneurysm evolution and if possible, to hamper sac expansion, is of high interest, as this approach would permit a closer surveillance screening and a more individualized therapeutic approach.
Along this line, a systematic review was conducted to present the existing evidence of different circulating biomarkers that may have a potential role on AAA growth prediction.

Eligible Studies
The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed [13]. Studies of English medical literature, reporting data on the evaluation of biomarkers (see Section 2.5), regarding their potential role on the identification of AAA growth (see Section 2.5) on humans, were considered eligible. Studies referring to data based on animal studies, any other aortic pathology besides AAA, and non-plasma circulating biomarkers (unavailable by venipuncture) were excluded. Scientific council approval in terms of ethical considerations was not required due to the nature of the study. Data extraction and methodological assessment was carried out by two independent investigators (P.N., K.D.). Any discrepancy was resolved after consultation by a senior investigator (G.K.). Consequently, a full-text review of the eligible studies was conducted, respecting the eligibility and exclusion criteria ( Figure 1).

Search Strategy
A data search of English medical literature was conducted, the endpoint being 7 March 2021. The established medical databases PubMed, EMBASE, and CENTRAL were searched under the patient/population, intervention, comparison and outcomes (PICO) model, in order to determine the clinical questions and select the appropriate articles (Supplementary Table S1) [14]. The following search terms including Expanded Medical Subject Headings (MeSH) were used in various combinations: Abdominal aortic aneurysm, growth, biomarker. Primary selection was constructed on titles and abstracts, while a secondary investigation was executed based on full texts.

Data Extraction
A standard Microsoft Excel extraction file was developed. Extracted data included general data such as article author, year of publication, study period, journal of publication, and type of study. In addition, clinical data extracted from text or tables included the number of patients included, cohort characteristics, biomarker in evaluation, method of biomarker assessment, growth rate definition in each study, type of imaging used, correlation of biomarker to AAA growth, and statistical significance.

Quality Assessment
Quality assessment for individual studies and risk of bias evaluation was addressed using the ROBINS-I tool [15] for observational, non-randomized studies and the RoB-II tool [16] for randomized, controlled studies. Observational studies were judged as bearing a "Low", "Moderate", "Serious", or "Critical" risk of bias, based on 7 domains, while RCTs were evaluated bearing a "Low", "Some concerns", or a "High" risk of bias, based on 5 domains (Supplementary Table S2). Risk of bias evaluation was carried out by two independent investigators (P.N., K.D.). In cases of disagreement, a third author was advised (G.K.).

Search Strategy
A data search of English medical literature was conducted, the endpoint being 7 March 2021. The established medical databases PubMed, EMBASE, and CENTRAL were searched under the patient/population, intervention, comparison and outcomes (PICO) model, in order to determine the clinical questions and select the appropriate articles (Supplementary Table S1) [14]. The following search terms including Expanded Medical Subject Headings (MeSH) were used in various combinations: Abdominal aortic aneurysm, growth, biomarker. Primary selection was constructed on titles and abstracts, while a secondary investigation was executed based on full texts.

Data Extraction
A standard Microsoft Excel extraction file was developed. Extracted data included general data such as article author, year of publication, study period, journal of publication, and type of study. In addition, clinical data extracted from text or tables included the number of patients included, cohort characteristics, biomarker in evaluation, method of biomarker assessment, growth rate definition in each study, type of imaging used, correlation of biomarker to AAA growth, and statistical significance.

Definitions
A biomarker was considered a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention, as defined by the biomarkers.

Definitions Working Group
AAA growth was considered as the difference among two measurements of the maximal anteroposterior diameter of a diagnosed abdominal aortic aneurysm, based on measurements achieved either by ultrasonography (US), computed tomography (CT) or magnetic resonance imaging (MRI), between two set timepoints, at least 12 months apart or more. AAA growth was measured as mm/year [17].

Statistical Analysis
Only descriptive data were presented, because this systematic review did not aim to compare the efficacy of biomarkers on AAA growth.

Results
Twenty-five studies with 4753 patients were included in this systematic review. To facilitate data presentation, the studies were divided into two groups. The first group included studies assessing clinically applicable biomarkers and the second group included studies recording data on experimental biomarkers not used in the daily clinical practice.
Eight studies presenting data on clinical biomarkers were included; one randomized control trial [18], 3 prospective [19][20][21], and 4 retrospective [22][23][24][25] observational studies, published between 2008 and 2018 ( Table 1). All analyses assessed patients that underwent screening controls or were hospital referrals and presented an AAA of more than 30 mm of diameter (range 30-50 mm). Considering experimental circulating biomarkers, 17 articles were included, all presenting results from prospective [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41] observational studies, except one retrospective [42] analysis (Table 2). In total, 3152 patients with AAA of more than 30 mm were included (range 30-49 mm).   Among studies presenting clinical biomarkers, the most commonly applied one was Ddimers which was assessed in three studies [20,21,25]. D-dimers' role as an indicator of the process of thrombosis and thrombolysis and their known association with other cardiovascular entities has been assessed to further identify their potential impact on AAA evolution. The lipidemic biomarkers (total cholesterol [18], apolipoprotein-B [18], low density lipids (LDL) [18] and high-density lipids (HDL) [22]) and C-reactive protein (CRP) [19] have been used due to their proven role on the process of atherothrombosis and their relationship to a higher-risk of cardiovascular events. In one study, the role of HbA1 c was addressed due to the already known negative association between diabetes and AAA pathogenesis [24]. All the markers assessed in the studies, as well as the potential underlying etiopathologic relationship between them and AAA evolution is presented in Table 3. In the experimental group, a variety of biomarkers was applied to identify prediction models in AAA evolution (Table 4). Nine out of them participate in the inflammation cascade while 3 are associated with the physiological coagulation mechanisms and 2 on the degenerative procedures of the tissues. Neutrophil gelatinase-associated lipocalin was studied as an indicator of the inflammatory degenerative process of aneurysm formation [34,42] and evolution while the potential role of insulin-like growth factor I (IGF-I) and II was analyzed under the spectrum of the negative association between diabetes and AAA [33]. The etiopathological association of all experimental markers and AAA growth is also presented in Table 4.
For the evaluation of aneurysm growth, duplex ultrasonography (DUS) was used in the vast majority of the studies (23 out of 25 studies) [18][19][20][21][22][23][24][25][26][27][28][30][31][32][33][34][35][36][37][38][39][40]42]. Aneurysm growth definition varied among studies. The change in the antero-posterior diameter of the aneurysm sac during the whole observation period divided by the aforementioned time interval (diameter at the latest evaluation-diameter at the initial evaluation/time interval in years) was used in 15 studies to identify the annual growth rate of the aneurysm. All approaches used to evaluate AAA growth rate are presented in Tables 3 and 4.     intra-and interobserver variability ranging at 0.13 and 0.27 mm, respectively CTA D-dimers were positively associated in 3 studies with aneurysm growth with an associated statistical significance. In accordance, the lipidemic markers played a predictive role in AAA expansion; total cholesterol and apolipoprotein-B had a positive relation while HDL presented a negative association; higher HDL levels were associated with lower AAA growth. The negative association of diabetes and AAA pathogenesis was detected by the negative correlation between HbA1 and expansion rate. The association between clinical biomarkers and AAA growth is presented in Table 5. Among the experimental biomarkers, amino-terminal propeptide of type III procollagen (PIIINP) [26], tissue-type plasminogen activator (tPA) [27,29,40], osteopontin [34], haptoglobin polymorphism [30], IGF I and II [33], thioredoxin (TRX) [31], neutrophil extracellular traps (NETs) [41], and genetic factors, as polymorphisms [35] and micro RNAs [36] were positively associated with aneurysm expansion. Two studies reported no association between NGAL and AAA growth [34,42]. All data regarding the experimental markers are available in Table 6. Table 5. The association between clinical biomarkers and AAA growth. Notes: AAA: Abdominal aortic aneurysm.

Author Association of Biomarker to Growth Significance Additional Information
Deeg et al. [18] Without  Table 6. The association between experimental biomarkers and AAA growth.

Author Association of Biomarker to Growth Significance Additional Information
Satta et al. [26] Acceleration of AAA growth increased s-PIIINP correlation in the course of AAA disease (from 0.22-0.55) p = 0.002 (p = 0.01 during the first year) The correlation between thrombus changes and s-PIIINP tend to be lower than between diameter and s-PIIINP, except in the first year (p = 0.02 at the end of follow-up) Lindholt et al. [27] Positive correlation between annual expansion rate and tPA, IgA ± CP, and S-cotinine r = 0.37-p = 0.002, r = 0.29-p = 0.006 and r = 0.24-p = 0.038, respectively In multiple linear regression analyses adjusting for S-Cotinine, the correlation between tPA and expansion rate remained significantly correlated Colledge et al. [28] Serum OPN correlated with aortic diameter change p < 0.001 Adjustment for other known risk factors for aortic expansion, serum OPN predicted AAA growth (p < 0.001) Flondell-Site et al. [29] No significant correlations between levels of MMP-2 or -9, TIMP-1, serpine-1, tPa-serpine-1, or the APC-PCI complex and yearly AAA growth, TIMP-1 levels independent predictors of fatal AAA rupture

Discussion
AAA represent a category of vascular lesions with high morbidity and mortality, especially in the case of aneurysm rupture. Current guidelines suggest elective repair based mainly on aneurysmal diameter and/or other characteristics of the AAA [8,43]. Proposed screening strategies vastly stand on imaging techniques, including mainly DUS, adhering to the phenomenon of increased rupture risk in patients of specific demographic attributes and AAA diameter [44]. Studies have shown that patients with particular aneurysmal attributes would be acceptable surgical candidates, especially for endovascular interventions, even if AAA diameter has not achieved the diameter's threshold [45,46]. While AAA growth is observed through typical, time-set imaging follow-up, stratification of high-risk patients with expeditious AAA growth, through serum biomarkers, could be a valid approach for individualized imaging surveillance. These patients could benefit from a rather targeted surveillance approach as well as an early endovascular or open surgical repair.
The pathogenesis of AAAs advocates for an extensive list of serum circulating or histologically detected biomarker candidates. Each category bears an important role in the different phases of the natural history of AAA [47][48][49]. Biomarkers detected through histological evaluation of an AAA open surgical repair specimen do not conform with the concept of preoperative surveillance and disease progression and therefore cannot be used in clinical practice. However, serum circulating biomarkers appertaining to recognized pathophysiologic processes of AAA pathogenesis, including thrombosis, inflammation, extracellular matrix (ECM) degradation, lipid metabolism, as well as genetic predisposition, could potentially form the basis of a stratification screening or surveillance strategy for patients in need of more frequent follow-up.
As proposed by many studies, certain mediators or by-products of thrombosis and lipid metabolism have been linked to AAA growth. These biomarkers can be easily and cost-effectively implemented in everyday clinical practice [18][19][20]22,25]. D-dimers, a known fibrin degradation by-product, has been shown to be associated with AAA expansion, as higher levels have been correlated with increased growth rate. Correlation of other thrombosis-related biomarkers, including PAP complex [21,50], homocysteine [51], and TAT [25], has also been reported. Higher levels of HDL-C, a biomarker related to lipid metabolism, have been correlated with decreased AAA growth rates in a screening population [22]. Furthermore, increased levels of total cholesterol and apolipoprotein B, both markers easily quantified and major constituents of lipid metabolism, have been associated with increased growth rates of AAA [18]. On the other hand, given the potentially protective nature of diabetes mellitus in AAA, glycated hemoglobin (HbA1c) has been studied as a possible biomarker of inverse association with AAA expansion [52][53][54][55]. A lower growth rate was observed in patients with higher HbA1c levels; 1.8 mm/year decrease of rate in HbA1c 44-77 compared to 28-39 mmol/mol [24]. The recognized correlations of the abovementioned biomarkers, in addition to their cost-effectiveness and their wide-spread use in everyday clinical practice, renders them attractive candidates for future studies aiming to provide robust data on their relation to AAA expansion rates.
Concurrently, a plethora of less utilized biomarkers correlating to various stages of AAA progression have been studied, posturing as alluring secondary candidates. Firstly, extracellular matrix components and degradation enzymes have been associated with AAA growth rate. The well-defined role of elastin, biglycan, and type III collagen in the structural integrity of the aortic wall provided the basis for studies reporting data on the by-products of these proteins associated with AAA progress and increased sac expansion [18,26,29,56,57]. Inadvertently, extracellular matrix proteinases (MMP-2, MMP-9 [58], cathepsins B, D, L, and S [59]) responsible for ECM cleavage, and proteinases inhibitors (a1-antithrypsin [19], cystatin-B [37], cystatin-C [60]) play a significant role in the aortic wall remodeling occurring in AAA pathogenesis with several studies revealing either positive or inverse correlations with AAA growth rates. An abundance of modulators and mediators expressing the inflammatory and oxidative processes have also been studied with conflicting outcomes [31,32,38,61,62]. Synchronously, studies on promising novel biomarkers requiring genome sequencing analysis have been conducted, with propitious results. Specifically, genomic DNA analysis of genetic polymorphisms showed increased risk of aggressive-growth over slow-growth AAA [36,41,[63][64][65]. Current data on these aforementioned biomarkers are promising, despite the fact that firm conclusions cannot be provided. Interestingly, calprotectin, a protein commonly associated with inflammatory cells (neutrophil granulocytes, monocytes, macrophages), has been related to AAA pathogenesis. These results provide further solid ground for future trials, aiming to assess the relation between the antimicrobial protein and AAA growth rate [66,67]. As the knowledge on AAA pathogenesis increases, novel studies may offer validated markers that could be used for the detection of this high-risk group of patients while pharmaceutical factors may provide a conservative management on AAA presence and expansion.

Limitations
The strength of the current review is limited by a series of factors. Firstly, the retrospective nature of the included studies confines its ability to reach pertinent results. Secondly, vast incoherencies among studies in terms of the types of biomarker assessed, studied population and cohorts, lack of control groups, follow-up intervals, and standardized methodological evaluations (imaging techniques, biomarkers quantification methods) impede the production of robust results, as well as the ability of quantitative analysis of the said results. Finally, most studies were judged as having "Moderate" risk of bias, mainly due to selection bias and inadequate confounder control.

Conclusions
Blood circulating biomarkers may offer a valid approach in the future for the detection of AAA expansion. The current literature provides a plethora of data with conflicting results and firm conclusions cannot be provided. In the presence of future robust data, specific serum biomarkers could potentially form the basis of an individualized surveillance strategy of patients presenting with increased AAA growth rates.

Conflicts of Interest:
The authors declare no conflict of interest.