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Pathophysiology, Classication andPrinciples ofManagement ofAcute Aortic…
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59. Nicolae V, Elkahlout A, Serban R.Uncomplicated acute Stanford B aortic dissection treated by
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63. Sailer AM, van Kuijk SM, Nelemans PJ, Chin AS, Kino A, Huininga M, et al. Computed
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of contrast-enhanced echocardiography on the diagnostic algorithm of acute aortic dissection.
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86. Nienaber CA, Kische S, Rousseau H, Eggebrecht H, Rehders TC, Kundt G, etal. Endovascular
repair of type B aortic dissection: long-term results of the randomized investigation of stent
grafts in aortic dissection trial. Circ Cardiovasc Interv. 2013;6:407–16.
87. Brunkwall J, Lammer J, Verhoeven E, Taylor P.ADSORB: a study on the efcacy of endovas-
cular grafting in uncomplicated acute dissection of the descending aorta. Eur J Vasc Endovasc
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M. Hamilton
Further Reading
Booher AM, Isselbacher EM, Nienaber CA, Trimarchi S, Evangelista A, Montgomery DG, etal.
The IRAD classication system for characterizing survival after aortic dissection. Am J Med.
2013;126:730 e19–24.
Dake MD, Thompson M, van Sambeek M, Vermassen F, Morales JP, Investigators D.DISSECT: a
new mnemonic-based approach to the categorization of aortic dissection. Eur J Vasc Endovasc
Surg. 2013;46:175–90.
Eggebrecht H, Plicht B, Kahlert P, Erbel R.Intramural hematoma and penetrating ulcers: indica-
tions to endovascular treatment. Eur J Vasc Endovasc Surg. 2009;38:659–65.
Erbel R, Aboyans V, Boileau C, Bossone E, Bartolomeo RD, Eggebrecht H, et al. 2014 ESC
Guidelines on the diagnosis and treatment of aortic diseases. Eur Heart J. 2014;35:2873–926.
Fillinger MF, Greenberg RK, JF MK, Chaikof EL, Society for Vascular Surgery Ad Hoc Committee
on TRS.Reporting standards for thoracic endovascular aortic repair (TEVAR). J Vasc Surg.
2010;52:1022–33, 33.e15.
Riambau V, Bockler D, Brunkwall J, Cao P, Chiesa R, Coppi G, etal. Editor’s choice—manage-
ment of descending thoracic aorta diseases: clinical practice guidelines of the european society
for vascular surgery (ESVS). Eur J Vasc Endovasc Surg. 2017;53:4–52.
Svensson LG, Labib SB, Eisenhauer AC, Butterly JR.Intimal tear without hematoma: an impor-
tant variant of aortic dissection that can elude current imaging techniques. Circulation.
1999;99:1331–6.
Chapter 15
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Biomarkers inVascular Disease
AshrafCadersa andIanM.Nordon
Key Learning Points
A biomarker is a “characteristic that is objectively measured as an indicator of
•
normal biological processes, pathological processes, or pharmacological
responses to a therapeutic intervention”.
• Biomarkers are indicators of a disease trait (risk factor or risk marker), disease
state (preclinical or clinical), or disease rate (progression). They may also serve
as surrogate end points used as an outcome measure to assess efcacy of therapy.
•
Biomarkers found in body uids may represent the active disease process or the
patient’s reaction to the disease. Disease-related biomarkers may be directly due
to the disease (e.g. Disease Progression Biomarkers) or be due to biological
changes caused by the host as it responds to disease (e.g. Host Response
Biomarkers). Disease progression biomarkers are very specic to the disease and
tend to be proteins of low abundance. Conversely, host response biomarkers are
less specic to the disease itself and are generally high abundance proteins.
• Biomarkers have the potential to enhance all aspects of vascular care of AAA,
carotid disease and peripheral vascular disease.
Identication of blood-based biomarkers capable of identication and individual
•
stratication of risk of progression and rupture would revolutionize the care of
aortic aneurysm disease. A blood test for a biomarker of aneurysm expansion or
aneurysm sac pressurization post-endovascular repair that could replace serial
imaging would reduce the cost and morbidity attributed to graft surveillance.
• Molecular processes such as inammation, lipid accumulation, apoptosis, throm-
bosis, proteolysis and angiogenesis have been shown to be highly related with
carotid plaque vulnerability. Serum biomarkers reecting these processes may
A. Cadersa · I. M. Nordon (*)
Cardiovascular and Thoracic, University Hospitals Southampton, Southampton, UK
Wessex Vascular Network, University Hospitals Southampton, Southampton, UK
e-mail: Ian.Nordon@uhs.nhs.uk
R. Fitridge (ed.), Mechanisms of Vascular Disease,
https://doi.org/10.1007/978-3-030-43683-4_15
341© Springer Nature Switzerland AG 2020
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distinguish stable from potentially unstable carotid stenosis and be a powerful
discriminator in the selection of patients for carotid surgery in asymptomatic
patients.
• There are two potential approaches to biomarker discovery. Firstly, there is a
knowledge-based approach exploring known candidates based on our under-
standing of disease pathophysiology. Alternatively, an inductive approach can be
undertaken, using non-hypothesis driven exploration to discover novel differ-
ences in genetic, proteomic or metabolomic expression.
• A number of methodologies can be used to discover novel biomarkers for aneu-
rysm disease and atherosclerotic plaque stability. These include genetics, pro-
teomics, metabolomics, bioinformatics and molecular imaging.
• Potential biomarkers for AAA presence and growth include circulating extracel-
lular matrix markers, matrix-degrading enzymes, thrombus-related and inam-
matory biomarkers.
• Possible biomarkers for carotid artery plaque behaviour include biomarkers
associated with inammation, lipid accumulation, apoptosis, thrombosis and
proteolysis.
A. Cadersa and I. M. Nordon
15.1 Introduction
Cardiovascular diseases (CVD) are the leading cause of morbidity and mortality in
the developed world. These diseases encompass the consequences of localized atherosclerosis and aneurysmal arterial degeneration. In both disease states, there is a
body of evidence demonstrating a natural life course to their development. Evolution
of risk factors contributes to the onset of subclinical disease; subclinical disease
progresses to overt and often catastrophic clinical sequelae. Primary and secondary
prevention strategies for CVD are public health priorities.
Whilst clinical assessment and cross-sectional imaging remain the cornerstones
of patient management, they have limitations. There is increasing interest in the use
of novel markers of cardiovascular disease as screening and risk-assessment tools to
enhance the ability to identify “vulnerable” patients. Biomarkers are one tool to aid
clinical assessment and identify high risk individuals, to ensure prompt and accurate
disease diagnosis and to aid prognostic scoring of individuals with disease.
15.2 What Is aBiomarker?
Initially described as a “measurable and quantiable biological parameter that could
serve as an index for health assessment”, the denition of a biomarker has since
been standardized. “A characteristic that is objectively measured as an indicator of
normal biological processes, pathogenic processes, or pharmacological responses
to a therapeutic intervention” [1].
Biomarker Concentration
Detection
Detection
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Biomarkers inVascular Disease
343
Biomarkers are indicators of disease trait (risk factor or risk marker), disease
state (preclinical or clinical), or disease rate (progression) [2]. They may also serve
as surrogate end points used as an outcome measure to assess efcacy of therapy. A
biomarker may be a recording taken from an individual (e.g. blood pressure), it may
be an imaging test (CT/PET scan), or it may be a biosample (blood, serum, urine).
Although each of these measurements constitutes a biomarker, the term biomarker
has become synonymous with a novel protein, enzyme or cytokine with discriminatory value in clinical care.
15.3 Types ofBiomarker
Biomarkers found in body uids may represent the active disease process or the
patient’s reaction to the disease. A disease condition is a combination of biological changes directly due to disease (e.g. Disease Progression Biomarkers)
and biological changes caused by the host as it responds to disease (e.g. Host
Response Biomarkers). Disease progression biomarkers are very specic to the
disease and tend to be proteins of low abundance. Conversely, host response
biomarkers are less specic to the disease itself and are generally high abundance proteins (Fig.15.1). When used in the correct clinical context, both have
discriminatory value.
Fig. 15.1 Comparison of
host response and disease
progression biomarkers
HighMediumLow
Threshold
Threshold
Detection
Disease
Host Response
Biomarkers
Time
Earlier
Disease
Progression
Biomarkers
Later
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A. Cadersa and I. M. Nordon
15.3.1 A Classical Clinical Example
Troponin is an established clinical biomarker. The diagnosis of myocardial infarction now stands on a convincing history, electrocardiogram changes and the detection of a protein biomarker for myocardial necrosis. The biomarker is a result of the
systemic spillover of structural, myocardial specic, myolament proteins (troponins). The levels of protein, due to the time course and extent of systemic release,
correlate well with myocardial injury. First discovered by Ebashi in 1963, troponin’s utility as a biomarker was highlighted in 1989 when a standardized immunoassay for circulating troponin T was developed. It underwent clinical validation
against the then best marker of myocardial ischaemia, CK-MB, and was found to
improve the efciency of diagnosis of myocardial cell necrosis [3]. In 2000 the
American Heart association incorporated a positive troponin T rise into its denition of myocardial infarction, and it remains the gold standard for the diagnosis of
cardiac ischaemia [4].
15.4 Potential Value ofBiomarkers inVascular Disease
Biomarkers have great potential to enhance all aspects of vascular care through
AAA, carotid disease and peripheral vascular disease. AAA development is likely
to represent a product of genetic predisposition and environment factors. They are
characterized by local inammation, matrix degradation and smooth muscle cell
apoptosis [5]. Once established, AAAs grow at a rate of 2.6mm/year (95% range
−1.0–6.1mm/year) [6]. Generally this growth is insidious and asymptomatic until
rupture. During this growth phase, the active processes of AAA formation are ongoing and both local and systemic cytokines and protein levels will be modied in
response to, or as a consequence of, this pathology.
The principal challenge in the management of AAAs is that they generally
remain asymptomatic until rupture. At rupture, survival is poor, with mortality rates
up to 70% [7]. In order to make a signicant impact on the outcome of AAA, a
number of signicant advances are required. Improved detection of AAAs is the
rst step. Aneurysm screening is now established in the UK and other countries,
however there remains doubt over the cost-effectiveness of these ultrasound-based
programs. Currently, maximum aortic diameter alone is generally the only means
of assessing AAA rupture risk. However the complications of AAA are not simply
correlated to aortic diameter alone. Some small AAAs rupture and some large
AAAs remain stable for prolonged periods [8, 9]. Patients continue to undergo
aneurysm repair on the probability of rupture, with the inevitability that some
patients will undergo unnecessary repair. An improved risk model is required.
Identication of blood-based biomarkers capable of identication and individual
stratication of risk of progression and rupture, would revolutionize the provision
of care for AAA.
Biomarkers inVascular Disease
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15
345
Endovascular AAA repair (EVAR) has signicantly reduced the peri-operative
mortality associated with elective AAA surgery. The current standard of care
requires regular post-deployment surveillance to ensure that the aneurysm sac is
excluded from the circulation and adequately depressurised. This surveillance is
dependent on Duplex ultrasound and computed tomographic imaging. A blood test,
for a biomarker of aneurysm expansion or aneurysm sac pressurization that could
replace serial imaging would reduce the cost and morbidity attributed to graft
surveillance.
Stroke is the third leading cause of death worldwide. Approximately 15% of strokes
and transient ischaemic attacks (TIAs) are caused by unstable carotid artery plaque.
Surgical treatment of a carotid artery stenosis by endarterectomy (CEA) can signicantly reduce stroke risk, but is accompanied by morbidity and mortality. Equally, not
all carotid plaques will become symptomatic and cause a stroke. Fundamental to the
selection of patients for intervention is the identication of plaques conferring an
excess risk of neurological events. Currently, selection for carotid intervention is
determined by the grade of stenosis and symptomatology. It is broadly accepted to
treat high-grade symptomatic carotid stenosis, but in lower grade stenoses and asymptomatic patients, interventions are still a matter of debate. There is growing evidence
that the degree of stenosis alone is a poor guide for intervention. Molecular processes
such as inammation, lipid accumulation, apoptosis, thrombosis, proteolysis and
angiogenesis have been shown to be highly related with plaque vulnerability. Serum
biomarkers reecting these processes may distinguish unstable from stable carotid
stenosis and be a powerful discriminator in the selection of patients for carotid surgery.
15.5 Biomarker Discovery Steps
Biomarkers must be measurable, add new information and aid the clinicians’ management of patients. To apply the biomarker to a risk prediction model, it must
allow discrimination, calibration and risk stratication (Table15.1). Discrimination
Table 15.1 Translating biomarker discovery from the laboratory to patients
Phase Title Explanation
P1 Discovery Exploratory studies to identify potential
biomarkers
P2 Validation Capacity of biomarker to discriminate between
health and disease
P3 Pre-clinical Capacity of biomarker to detect pre-clinical
disease
P4 Prospective Prospective screening studies for sensitivity of
biomarker
P5 Impact Large scale study to assess impact of biomarker on
survival
Estimated numbers
required
50
100
200
500
>1000
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Table 15.2 Glossary of “omics” methodologies used to discover novel biomarkers
Technology Objective Method Tissue
Genetics Gene identication SNP genotyping
Proteomics Protein or post-translational
Metabolomics Identication and characterization of
Bioinformatics Link array data to biological
Molecular
imaging
SNP single nucleotide polymorphism, NMR nuclear magnetic resonance, BLAST basic local alignment search tool, CT computed tomography, MRI magnetic resonance imaging, PET positron
emission tomography, SPECT single-photon emission computed tomography
modied protein identication
small molecule
pathway
Non-invasive identication of
molecular constituents of diseaseCTMRI
Gene array
analysis
2D-gel
electrophoresis
Mass
spectrometry
Mass
spectrometry
NMR
spectroscopy
BLAST
Hierarchical
clustering
PET
SPECT
Nucleated cells,
diseased tissue
Blood, saliva,
tissue, urine
Blood, saliva,
tissue, urine
Data from
combined methods
Patients
is the specicity and sensitivity of the marker. Calibration denotes the ability of the
marker to assign predicted risks that match actual observed risk, and risk stratication is the power to assign patients into clinically relevant categories.
There are two potential approaches to biomarker discovery. Firstly, there is a
knowledge-based approach exploring known candidates based on the understanding
of disease pathophysiology. Alternatively, an inductive approach can be undertaken
using non-hypothesis driven exploration to discover novel differences in genetic,
proteomic or metabolomic expression. The two methodologies are complementary.
Dependent on the understanding of molecular biology of disease and cell signaling
pathways, there is also cross-over between the “omic” sciences used to trawl for
novel candidates (Table15.2).
15.6 AAA Biomarkers
Candidate biomarkers have been studied based on current understanding of AAA
pathogenesis. Examination of aneurysmal aortic wall biopsies has demonstrated
pathological processes including medial arterial destruction, accumulation of
inammatory cells, elastin fragmentation, increased concentrations of proteolytic
cytokines and in-situ thrombus. Consequently, investigators have explored enzyme,
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