Review Article Published on July 1, 2024

 

Novel Biomarkers for Prediction of Cardiovascular
Morbidity

Devika Ja, Arun B Nairb

a. Department of Physiology, Government Medical College, Thiruvananthapuram;
b. Department of Psychiatry, Government Medical College, Thiruvananthapuram*


ABSTRACT

Cardiovascular diseases are still one of the most common causes of deaths in the world .The changing demographics of fatal cardiovascular events is a significant indicator to consider new approaches in risk prediction and risk stratification. This article aims to address a few probable bio markers which may help determine the probability of an underlying cardiovascular condition much before the onset of acute symptoms.

 

Keywords: Sudden Cardiac Death, Ventricular Tachyarrthmia, sST2, Galectin-3, GEH

 

Introduction

Sudden cardiac death (SCD) still remains a major cause of mortality (estimated 15–20% of all deaths worldwide) even though advanced preventive and therapeutic strategies are available now. Of all the reported sudden cardiac deaths, the majority (70-80%) is still due to coronary artery disease.1-5

Although anecdotal evidence suggests an increasing trend in the incidence of SCD in young adults of India, only one study6 was conducted in our country recently, exploring the incidence of SCD in rural India.  This study identified the prevalence as 17% in a South Indian rural population.  In comparison to other cardiac deaths including those due to  CAD, in India, the proportion of  SCD events and the risk factor profile of the individuals at risk for SCD still  remains largely unknown.

Sudden cardiac death (SCD) is defined, as sudden unexpected death occurring within 1 hour of onset of  cardiac symptoms,7 most often due to ventricular arrhythmias induced by coronary artery disease or cardiomyopathy.8 Most of the SCD s are seen in individuals without any symptoms nor an increased blood levels of classical biomarkers of cardiac arrest.9

Pathophysiology

The causes for Ventricular tachyarrhythmias  vary between enhanced automaticity, triggered activity and/or reentry.10,11 The  increased myocardial automaticity is due an acceleration of the spontaneous firing in cardiac myocyte. As a consequence, this leads to irregular activation patterns in the heart. Triggered activity is characterized by calcium-mediated premature action potentials that arise from early or delayed afterdepolarizations.

One of the most common mechanisms of cardiac reentry involves multiple excitation wave that moves around myocardial areas with impaired conduction and refractory tissue.

Most often this arrhythmogenic effect is a consequence of the electrophysiological remodelling processes in the heart, which induces changes in  cardiac ion channel expression and function in the heart. These, indeed are due to the fibrotic processes progressing in the myocardium thus affecting the cardiac conduction.9,10

These  mechanisms are often modulated or/and induced by different processes like myocardial necrosis, inflammation, myocardial stress or neurohormonal activation with the involvement of various biological signal proteins. While these proteins are often released during signalling processes, their levels can be measured in patient serum as indicator of signalling activation. Consequently, they can be useful for characterization of normal or pathogenic processes of the heart including electrophysiological remodelling. Indeed, biomarkers have become a useful tool, which refers to a broad subcategory of quantifiable and reproducible characteristics of biological signs. Therefore, their potential as a useful marker for cardiac risk stratification needs to be discussed.12

One interesting fact is that, other than the “classic” cardiac biomarkers like BNP or troponin,  inflammatory biomarkers like C-reactive protein (CRP) or high-sensitive (hsCRP), also  have been useful in diagnosing cardiac diseases.12

The novel or  emerging biomarkers being studied are probably the bye products of myocardial injury like myocardial necrosis, inflammation, plaque instability, platelet activation, myocardial stress and neurohormonal activation. Indeed, one of the “novel” cardiac biomarkers, soluble suppression of tumorigenicity 2 (sST2) protein, is gaining steady significance as a good prognostic marker for heart failure.13

In this review we will describe  few cardiac Biomarkers which might help to predict the risk of ventricular cardiac arrhythmias . The need and the  potential clinical implications of new cardiac Biomarkers also needs attention. In this article we discuss three “novel” cardiac biomarkers as potential predictors of fatal ventricular arrhythmias.

Novel and Alternative’ Biomarkers as Potential Predictors of Ventricular Arrhythmias

Soluble suppression of tumorigenicity 2 (sST2)

A number of Recent studies have demonstrated that blood levels of the molecule ‘suppression of tumorigenicity 2’ (ST2) is  remarkably  associated with risk for cardiac diseases.14,15, 23-25

ST2 is a member of the interleukin 1 receptor family and was discovered in 1989 as an inflammatory mediator in autoimmune conditions.16,17,40 The biological activity of ST2 is mediated by its interaction with its ligand, IL-33.18 Soluble ST2(sST2) is seen to be released from myocardial fibroblasts and  cardiomyocytes under stress.26,27 When cardiomyocytes stretch due to any stress, this molecule gets released.19,20 It is also associated with inflammation during the MI and HF.21 During normal response, Il-33 binds to the ST2 receptor has a cardioprotective ability but  when bound with sST2, Il-33 is unable to progress on its usual cellular pathways, resulting in the potential loss of cardioprotective characteristics.34 Consequently, higher levels of sST2 are linked to more severe stress responses in the heart39 as it suggests significant inhibition of signal transduction by Il-33/ST2 pathways.22   The ST2 pathway in CVD is shown in Figure 1.

Figure 1. ST2 pathway in CVD

The biomechanics of the IL-33/ST2 signalling pathway has been well established and has been found that it plays a significant role in cardiomyocyte hypertrophy and cardiac fibrosis.28 As mentioned earlier,  sST2 release as a result of myocyte stretch, neutralises its ligand IL-33, which is a key component in preventing myocardial fibrosis and hypertrophy.33,34 Any change in the geometry or load conditions of the heart, such as MI, hypertension, and valvular heart disease, may change the mechanical strain imposed on a single cardiomyocyte, leading to cardiomyocyte hypertrophy, enhanced extracellular protein deposition (ventricular fibrosis), and eventually HF.29,30,31 Cardiomyocyte hypertrophy is the most important of the pathophysiological changes in the heart, eventually contributing to ventricular wall thickening and stiffening.32 Therefore, both cardiomyocyte hypertrophy and cardiac fibrosis contribute to elevated serum sST2 levels in HF patients, which was corroborated by the recent researches.

During conditions of myocardial damage, either by high pressure or any other biological strain IL-33 is released from the fibroblasts, which in turn prevents apoptosis of the myocardial cells.35,36  This cardio protective effects are mediated via the membrane receptor for IL-33, ST2. The protective effects of IL-33 is lost in the presence of sST2 because sST2 acts as a competitive inhibitor of ST2L.22  In fact, elevated blood  sST2 concentrations denotes apoptosis, cardiomyocyte hypertrophy, and cardiac fibrosis, which denotes irreversible damage after MI, leading to HF.

We speculate that higher serum sST2 concentrations after MI may cause a worse prognosis because sST2 blocks the beneficial effects of IL-33, such as reducing fibrosis and hypertrophy, preventing apoptosis, preserving ventricular function, and improving survival.35 Therefore, sST2 may be used to evaluate risk of death after MI.

One meta-analysis result indicated that the sST2 level was not correlated with ischemic heart disease or Myocardial infarction but was significantly associated with Heart Failure.  sST2 levels did not differ significantly between patients with IHD or MI and healthy individuals. But it is a potential tool as an additional aid for the diagnosis of HF.38,41

Another study, The ARTEMIS study,43 also concluded that Elevated sST2 and hs-TnT predict the occurrence of Sudden cardiac deaths among patients with Coronary artery disease.  This study also suggested that Combination of elevated sST2 and hs-TnT  is the most useful predictor on the risk of SCD. These two biomarkers obviously reflect partly different aspects of cardiovascular stress and tissue damage leading to untoward cardiac events, either progressive heart failure or occurrence of SCD even without prior evidence of left ventricular systolic dysfunction. It can be hypothesized that elevated hs-TnT is a marker of ongoing myocyte loss and elevated sST2 reflects the consequent cardiac replacement fibrosis as a result of cell death, which eventually creates a substrate for fatal arrhythmia. Fibrotic scarring has been shown to correlate strongly with an increased incidence of arrhythmias and SCD.44

Galectin-3

Galectins are a family of proteins defined by two characteristics: functionally a beta-galactoside affinity and structurally a conserved carbohydrate recognition domain (CRD). Tissue damage activates this molecule45 and inside the cell it activates messenger ribonucleic acid (mRNA) splicing which in turn promotes anti-apoptotic signalling.  This becomes particularly relevant in fibroblasts as it promotes mitogenesis in these cells.49 Therefore, we can consider that galectin -3 is representative of  fibrotic processes in the damaged heart, including in heart failure.21  Infact, one study elicited that , elevated levels of galectin -3  in general population was associated with not only  more incidence of heart diseases , but also with an increased risk of all-cause mortality.46 It is to be noted that  galectin-3 has proven  to be a useful complementary biomarker in prognosis and risk stratification of  patients with cardiac failure.47

Recent evidence also suggests galectin-3 to be a good tool to predict  the onset of Ventricular tachycardia as well as Ventricular Fibrillation. They investigated a possible association with risk prediction of sudden cardiac death in Hypertrophic cardiomyopathy. The authors observed a positive correlation between the estimated five-year risk of SCD and serum levels of galectin-3, thus indicating a possible association between sudden cardiac deaths and this protein.48

ECG biomarkers

An electrocardiogram (ECG) can denote the presence and properties of the electrophysiological pathology of  SCD. One study recently showed that global electrical heterogeneity (GEH), as measured by five metrics [spatial QRS-T angle, spatial ventricular gradient (SVG) azimuth, elevation, and magnitude, and sum absolute QRST integral (SAI QRST)] is independently (after comprehensive adjustment for time-updated CVD events and their risk factors) associated with SCD, probably denoting the cause  of SCD .  They also developed a competing risk score of SCD and showed that the addition of GEH measures to clinical risk factors significantly improves the reclassification of SCD risk.50

They  proved that  a parameters like wide QRS-T angle, SVG vector pointing backward (towards LV), wide QRS, prolonged QTc, and increased heart rate points to a  non-SCD structural heart disease. While increased chances of SCD was seen in ECG s characterized by SVG vector pointing upward (towards the outflow tract). Dynamic predictive accuracy of ECG and VCG biomarkers of SCD should be taken into account for development of dynamic and life-long prediction of SCD and non- SCD.51,52

Other  Biomarkers

Heart-Type Fatty Acid Binding Protein (H-FABP)

Heart fatty acid-binding protein (H-FABP) is present on the myocyte cell membrane, during injury gets  released in the bloodstream.53 Three hours after myocardial infarction, the level rises to a maximum.54 It may be  established as a marker of ongoing myocardial membrane damage and has been reported to be a useful indicator for future cardiovascular events.55

Metalloproteinases (MMP) and Procollagens

Metalloproteinases (MMPs) are enzymes mainly concerned with the turnover of extracellular matrix.  These enzymes regulate the inflammatory and fibrotic components of myocardial wound healing.56  In hypertrophic cardiomyopathy which is characterised by cardiac remodelling, MMP-3 levels were significantly higher especially in patients prone to ventricular arrhythmias.57

Endothelin

As one of the most potent vasoconstrictive peptides, the endothelium-derived factor endothelin is still relevant as a predictor of sudden cardiac death.58 Endothelin 1 (ET 1) increases platelet aggregation. In  animal models, endothelin is associated with increased incidence of ventricular arrhythmias.59-61 In addition, endothelin was linked to ischemia induced ventricular arrhythmias62  and arrhythmogenic responses during myocardial reperfusion.63

Uric acid is the final product of the purine metabolism. In recent years, serum uric acid has gained interest as a determinant of cardiovascular risk. Indeed, patients with hyperuricemia are at higher risk of cardiovascular events.64  It has been suggested that high serum levels are a strong, independent marker of poor prognosis in HF.65

Fibrinogen is a glycoprotein involved in clotting processes. Furthermore, it is a known regulator of revascularization and wound healing, but also acts as an acute-phase protein, which is secreted in response to systemic inflammation and tissue injury.66 Consequently, fibrinogen plasma levels were shown to be higher in patients suffering from CVD, as indicated by a subgroup analysis of the Framingham population.67

Conclusion

Classical Biomarkers such as cardiac troponin (cTn), and CK-MB are still considered as the main indicators of any cardiac event.A Biomarker which is predictive of an acute cardiac event causing SCD is still not evident.Much evidence suggests elevated ST2 as a probable indicator to fit into the role of a marker for SCD in patients with heart failure.

It has been shown that an increase in ST2 levels show  poor prognosis in patients with acute MI.68 Blood levels of sST2 early after AMI predicts left ventricle (LV) function and recovery after AMI, which may interlink the RAAS and IL- 33/sST2 pathways.69

sST2 is in vogue as a promising prognostic indicator for Heart failure and a useful tool for risk stratification.37 as per the results of one meta-analysis of serum sST2 levels in different CVDs.  It  demonstrated that serum sST2 levels in HF patients are remarkably higher than those in healthy individuals. However, serum sST2 levels did not differ significantly between IHD or MI patients and healthy individuals. Therefore, ST2 may be used as an additional diagnostic biomarker of Heart Failure.26,27,41

The dynamic changes in electrical activity of heart due to the progressive myocardial inflammatory and fibrotic changes is another hopeful discovery in predicting the SCD.  One study investigated the dynamic predictive accuracy of GEH and traditional ECG biomarkers of SCD within a survival framework in comparison with competing non-sudden cardiac death (non-SCD) in the Atherosclerosis Risk in Community (ARIC) study participants.42

Despite multiple advances in the strategies for SCD risk stratification, the current available techniques have limitations related to sensitivity, specificity, and cost-effectiveness. The goal of developing effective, low-cost, and noninvasive risk stratification tools for SCD still remains elusive.9 When we take into consideration of the fact that risk of SCD is not based on a single myocardial strain but a continuous and dynamic process, the  current risk models fails in accurate prediction of SCD. The current methods used to  predict SCD are based on  using baseline risk factors measured at a single point in time. Therefore, innovative and accurate predictions of these dynamic cardiac changes is  necessary for  understanding the temporal relationship between substrate and events more better.  The next generation of medical devices would probably evolve to incorporate a continuous cardiac electrical monitoring and instantaneous predictive abilities of SCD way before the actual event happens. Further  investigations in this exciting field is imperative to generate novel risk assessment approaches in the future for predicting and preventing SCDs.

End Note

Author Information

  1. Dr Devika J, Assistant Professor, Department of Physiology, Government Medical College,
    Thiruvananthapuram.
  2. Dr Arun B Nair, Professor, Department of Psychiatry, Government Medical College,
    Thiruvananthapuram. 

Conflict of Interest: None declared

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