Direct Comparison of Cardiac Myosin-Binding Protein C With Cardiac Troponins for the Early Diagnosis of Acute Myocardial Infarction

Evaluating Biomarkers as Tools for Early Detection and Prognosis of Heart Failure: A Comprehensive Review

There is a high prevalence of heart failure (HF) worldwide, which has significant consequences for healthcare costs, patient death and quality of life. Therefore, there has been much focus on finding and using biomarkers for early diagnosis, prognostication and therapy of HF. This overview of the research presents a thorough examination of the current state of HF biomarkers and their many uses. Their function in diagnosing HF, gauging its severity and monitoring its response to therapy are all discussed. Particularly promising in HF diagnosis and risk stratification are the cardiac-specific biomarkers, B-type natriuretic peptide and N-terminal pro-B-type natriuretic peptide. Markers of oxidative stress, extracellular matrix, renal function, inflammation and cardiac peptides have shown promise in evaluating HF severity and prognosis. MicroRNAs and insulin-like growth factor are two emerging biomarkers that have shown potential in helping with HF diagnosis and prognosis.

Insights into the Novel Cardiac Biomarker in Acute Heart Failure: Mybp-C

(1) Background: Given its high cardiac specificity and its capacity to directly assess the cardiac function, cardiac myosin-binding protein (MyBP-C) is a promising biomarker in patients with acute heart failure (AHF). The aim of our study was to investigate the clinical utility of this novel marker for diagnosis and short-term prognosis in subjects with AHF. (2) Methods: We measured plasma levels of MyBP-C at admission in 49 subjects (27 patients admitted with AHF and 22 controls). (3) Results: The plasma concentration of MyBP-C was significantly higher in patients with AHF compared to controls (54.88 vs. 0.01 ng/L, p < 0.001). For 30-day prognosis, MyBP-C showed significantly greater AUC (0.972, p < 0.001) than NT-proBNP (0.849, p = 0.001) and hs-TnI (0.714, p = 0.047). In a multivariate logistic regression analysis, an elevated level of MyBP-C was the best independent predictor of 30-day mortality (OR = 1.08, p = 0.039) or combined death/recurrent 30-days rehospitalization (OR = 1.12, p = 0.014). (4) Conclusions: Our data show that circulating MyBP-C is a sensitive and cardiac-specific biomarker with potential utility for the accurate diagnosis and prognosis of AHF.

Machine Learning for Myocardial Infarction Compared With Guideline-Recommended Diagnostic Pathways

BACKGROUND

Collaboration for the Diagnosis and Evaluation of Acute Coronary Syndrome (CoDE-ACS) is a validated clinical decision support tool that uses machine learning with or without serial cardiac troponin measurements at a flexible time point to calculate the probability of myocardial infarction (MI). How CoDE-ACS performs at different time points for serial measurement and compares with guideline-recommended diagnostic pathways that rely on fixed thresholds and time points is uncertain.

METHODS

Patients with possible MI without ST-segment-elevation were enrolled at 12 sites in 5 countries and underwent serial high-sensitivity cardiac troponin I concentration measurement at 0, 1, and 2 hours. Diagnostic performance of the CoDE-ACS model at each time point was determined for index type 1 MI and the effectiveness of previously validated low- and high-probability scores compared with guideline-recommended European Society of Cardiology (ESC) 0/1-hour, ESC 0/2-hour, and High-STEACS (High-Sensitivity Troponin in the Evaluation of Patients With Suspected Acute Coronary Syndrome) pathways.

RESULTS

In total, 4105 patients (mean age, 61 years [interquartile range, 50-74]; 32% women) were included, among whom 575 (14%) had type 1 MI. At presentation, CoDE-ACS identified 56% of patients as low probability, with a negative predictive value and sensitivity of 99.7% (95% CI, 99.5%-99.9%) and 99.0% (98.6%-99.2%), ruling out more patients than the ESC 0-hour and High-STEACS (25% and 35%) pathways. Incorporating a second cardiac troponin measurement, CoDE-ACS identified 65% or 68% of patients as low probability at 1 or 2 hours, for an identical negative predictive value of 99.7% (99.5%-99.9%); 19% or 18% as high probability, with a positive predictive value of 64.9% (63.5%-66.4%) and 68.8% (67.3%-70.1%); and 16% or 14% as intermediate probability. In comparison, after serial measurements, the ESC 0/1-hour, ESC 0/2-hour, and High-STEACS pathways identified 49%, 53%, and 71% of patients as low risk, with a negative predictive value of 100% (99.9%-100%), 100% (99.9%-100%), and 99.7% (99.5%-99.8%); and 20%, 19%, or 29% as high risk, with a positive predictive value of 61.5% (60.0%-63.0%), 65.8% (64.3%-67.2%), and 48.3% (46.8%-49.8%), resulting in 31%, 28%, or 0%, who require further observation in the emergency department, respectively.

CONCLUSIONS

CoDE-ACS performs consistently irrespective of the timing of serial cardiac troponin measurement, identifying more patients as low probability with comparable performance to guideline-recommended pathways for MI. Whether care guided by probabilities can improve the early diagnosis of MI requires prospective evaluation.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT00470587.

Translational bioinformatics approach to combat cardiovascular disease and cancers

Bioinformatics is an interconnected subject of science dealing with diverse fields including biology, chemistry, physics, statistics, mathematics, and computer science as the key fields to answer complicated physiological problems. Key intention of bioinformatics is to store, analyze, organize, and retrieve essential information about genome, proteome, transcriptome, metabolome, as well as organisms to investigate the biological system along with its dynamics, if any. The outcome of bioinformatics depends on the type, quantity, and quality of the raw data provided and the algorithm employed to analyze the same. Despite several approved medicines available, cardiovascular disorders (CVDs) and cancers comprises of the two leading causes of human deaths. Understanding the unknown facts of both these non-communicable disorders is inevitable to discover new pathways, find new drug targets, and eventually newer drugs to combat them successfully. Since, all these goals involve complex investigation and handling of various types of macro- and small- molecules of the human body, bioinformatics plays a key role in such processes. Results from such investigation has direct human application and thus we call this filed as translational bioinformatics. Current book chapter thus deals with diverse scope and applications of this translational bioinformatics to find cure, diagnosis, and understanding the mechanisms of CVDs and cancers. Developing complex yet small or long algorithms to address such problems is very common in translational bioinformatics. Structure-based drug discovery or AI-guided invention of novel antibodies that too with super-high accuracy, speed, and involvement of considerably low amount of investment are some of the astonishing features of the translational bioinformatics and its applications in the fields of CVDs and cancers.

Differential gene expression patterns in ST-elevation Myocardial Infarction and Non-ST-elevation Myocardial Infarction

The ST-elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI) might occur because of coronary artery stenosis. The gene biomarkers apply to the clinical diagnosis and therapeutic decisions in Myocardial Infarction. The aim of this study was to introduce, enrich and estimate timely the blood gene profiles based on the high-throughput data for the molecular distinction of STEMI and NSTEMI. The text mining data (50 genes) annotated with DisGeNET data (144 genes) were merged with the GEO gene expression data (5 datasets) using R software. Then, the STEMI and NSTEMI networks were primarily created using the STRING server, and improved using the Cytoscape software. The high-score genes were enriched using the KEGG signaling pathways and Gene Ontology (GO). Furthermore, the genes were categorized to determine the NSTEMI and STEMI gene profiles. The time cut-off points were identified statistically by monitoring the gene profiles up to 30 days after Myocardial Infarction (MI). The gene heatmaps were clearly created for the STEMI (high-fold genes 69, low-fold genes 45) and NSTEMI (high-fold genes 68, low-fold genes 36). The STEMI and NSTEMI networks suggested the high-score gene profiles. Furthermore, the gene enrichment suggested the different biological conditions for STEMI and NSTEMI. The time cut-off points for the NSTEMI (4 genes) and STEMI (13 genes) gene profiles were established up to three days after Myocardial Infarction. The study showed the different pathophysiologic conditions for STEMI and NSTEMI. Furthermore, the high-score gene profiles are suggested to measure up to 3 days after MI to distinguish the STEMI and NSTEMI.

High-Sensitivity Cardiac Troponin Assays: Ready for Prime Time!

Rapid and accurate triage of patients presenting with chest pain to an emergency department (ED) is critical to prevent ED overcrowding and unnecessary resource use in individuals at low risk of acute myocardial infarction (AMI) and to efficiently and effectively guide patients at high risk to definite therapy. The use of biomarkers for rule-out or rule-in of suspected AMI has evolved substantially over the last several decades. Previously well-established biomarkers have been replaced by cardiac troponin (cTn). High-sensitivity cTn (hs-cTn) assays represent the newest generation of cTn assays and offer tremendous advantages, including improved sensitivity and precision. Still, implementation of these assays in the United States lags behind several other areas of the world. Within this educational review, we discuss the evolution of biomarker testing for detection of myocardial injury, address the specifics of hs-cTn assays and their recommended use within triage algorithms, and highlight potential challenges in their use. Ultimately, we focus on implementation strategies for hs-cTn assays, as they are now clearly ready for prime time.

Hemodialysis and biomarkers of myocardial infarction - a cohort study

OBJECTIVES

End-stage renal disease is associated with a high risk of cardiovascular disease. We compared the concentration and prognostic ability of high sensitivity cardiac troponin T (hs-cTnT) and I (hs-cTnI) and cardiac myosin-binding protein C (cMyC) among stable hemodialysis patients.

METHODS

Patients were sampled before and after hemodialysis. We measured hs-cTnI, hs-cTnT and cMyC and used Cox regressions to assess the association between quartiles of concentrations and all-cause mortality and a combination of cardiovascular events and all-cause mortality during follow-up.

RESULTS

A total of 307 patients were included, 204 males, mean age 66 years (SD 14). Before dialysis, 299 (99 %) had a hs-cTnT concentration above the 99th percentile, compared to 188 (66 %) for cMyC and 35 (11 %) for hs-cTnI. Hs-cTnT (23 %, p<0.001) and hs-cTnI (15 %, p=0.049) but not cMyC (4 %, p=0.256) decreased during dialysis. Follow-up was a median of 924 days (492-957 days); patients in the 3rd and 4th quartiles of hs-cTnT (3rd:HR 3.0, 95 % CI 1.5-5.8, 4th:5.2, 2.7-9.8) and the 4th quartile of hs-cTnI (HR 3.8, 2.2-6.8) had an increased risk of mortality. Both were associated with an increased risk of the combined endpoint for patients in the 3rd and 4th quartiles. cMyC concentrations were not associated with risk of mortality or cardiovascular event.

CONCLUSIONS

Hs-cTnT was above the 99th percentile in almost all patients. This was less frequent for hs-cTnI and cMyC. High cTn levels were associated with a 3-5-fold higher mortality. This association was not present for cMyC. These findings are important for management of hemodialysis patients.

Role of serum CAP1 protein in the diagnosis of patients with first-time acute myocardial infarction

The dysregulation of adenylate cyclase-associated protein 1 (CAP1) is associated with a variety of inflammatory conditions. Here, we aimed to assess the role of serum CAP1 protein in predicting acute myocardial infarction (AMI), and to explore its effect and mechanism in vascular endothelial cells injury. ELISA was utilized to detected CAP1 protein expression in serum from 70 patients with first-time AMI at 0, 6, 12, 24, 48 hours and 7 days of the onset of chest pain. Receiver operating characteristic (ROC) curve analysis was administered to analyze the diagnostic power of CAP1 for AMI. The CCK-8 and 5-BrdU assays were applied to measure cell proliferation and inflammation in a model of oxidized low-density lipoprotein (ox-LDL) induced human umbilical vein endothelial cells (HUVEC). Luciferase reporter gene assay and Western blotting were used to assess the activity of NF-κB pathway. Results showed that serum CAP1 protein expression was upregulated in patients with first-time AMI, its expression was highest at 12 hours of the onset of chest pain. CAP1 protein was positively associated with the levels of cTnI and ox-LDL. CAP1 showed a relatively high diagnostic accuracy in patients with first-time AMI compared with cTnI, and CAP1 combined with cTnI had superior diagnostic value than CAP1 and cTnI alone. The expression of CAP1 protein was increased in supernatants of ox-LDL induced HUVEC in a dose- and time-dependent manner. CAP1 inhibited cell proliferation but promoted inflammation, and induced the activation of NF-κB pathway in vitro. To sum up, increased serum CAP1 expression might serve as a novel diagnostic biomarker for patients with first-time AMI, the mechanism might be related to its induction of NF-κB pathway activation causing abnormal proliferation and inflammation and thus mediating vascular endothelial cell injury.

Anthracyclines and Biomarkers of Myocardial Injury: The Effect of Remote Ischemic Conditioning

Background

Remote ischemic conditioning (RIC) has been beneficial in laboratory studies of anthracycline cardiotoxicity, but its effects in patients is not established.

Objectives

The authors studied the effect of RIC on cardiac biomarkers and function during and after anthracycline chemotherapy.

Methods

The ERIC-Onc study (Effect of Remote Ischaemic Conditioning in Oncology Patients; NCT02471885) was a randomized, single-blind, sham-controlled study of RIC at each chemotherapy cycle. The primary endpoint was troponin T (TnT) during chemotherapy and up to 1 year. Secondary outcomes included cardiac function, major adverse cardiovascular events (MACE), and MACE or cancer death. Cardiac myosin-binding-protein C (cMyC) was investigated in parallel with TnT.

Results

The study was prematurely halted after the evaluation of 55 patients (RIC n = 28, sham n = 27). Biomarkers increased from baseline to cycle 6 of chemotherapy for all patients (median TnT 6 [IQR: 4-9] ng/L to 33 [IQR: 16-36)] ng/L; P ≤ 0.001; cMyC 3 (IQR: 2-5) ng/L to 47 (IQR: 18-49) ng/L; P ≤ 0.001). Mixed-effects regression analysis for repeated measures showed no difference in TnT between the 2 groups (RIC vs sham, mean difference 3.15 ng/L; 95% CI: -0.04 to 6.33; P = 0.053), or cMyC (RIC vs sham, mean difference 4.17 ng/L; 95% CI: -0.12 to 8.45; P = 0.056). There were more MACE and cancer deaths in the RIC group (11 vs 3; HR: 0.25; 95% CI: 0.07-0.90; P = 0.034), with more cancer deaths (8 vs 1; HR: 0.21; 95% CI: 0.04-0.95; P = 0.043) at 1 year.

Conclusions

TnT and cMyC significantly increased during anthracycline chemotherapy with 81% having a TnT ≥14 ng/L at cycle 6. RIC did not affect the rise in biomarkers, but there was a small increase in early cancer deaths, possibly related to the greater proportion of patients with metastatic disease randomized to the RIC group (54%vs 37%). (Effect of Remote Ischaemic Conditioning in Oncology Patients [ERIC-ONC]; NCT02471885).

[Cardiac biomarkers and their clinical relevance]

Cardiac biomarkers are an integral, guideline-recommended part of the diagnosis and follow-up of heart diseases. High sensitivity tests for troponin I or T allow for the early diagnosis of myocardial infarction. Rule-in and rule-out algorithms based on the dynamic of plasma concentrations in the first hour after admission improve safe, evidence-based decision making for patients with acute chest pain. Low concentrations of brain natriuretic peptides (BNP or NT-proBNP) reliably exclude heart failure. Elevated BNP/NT-proBNP concentrations are part of the definition of all types of heart failure but require additional tests to diagnose heart failure. Chronic elevations of troponins and BNP/NT-proBNP identify subpopulations at increased risk of cardiovascular events even in the absence of manifest cardiac disease. Whether and how this risk can be reduced requires further evaluation. Several novel biomarkers were recently discovered and characterised. Their place in cardiovascular medicine has yet to be defined.

Serial measurements of protein and microRNA biomarkers to specify myocardial infarction subtypes

Background

While cardiac-specific troponin (cTn) allows for rapid diagnosis of acute type 1 myocardial infarction (T1MI), its performance to differentiate acute myocardial injury (AI) or type 2 myocardial infarction (T2MI) is limited. The objective was to combine biomarkers to improve discrimination of different myocardial infarction (MI) aetiologies.

Methods

We determined levels of cardiac troponin T and I (cTnT, cTnI), cardiac myosin-binding protein C (cMyBP-C), NT-proBNP and ten miRNAs, known to be associated with cardiac pathology in a total of n = 495 serial plasma samples at three time points (on admission, after 1 h and 3 h) from 57 NSTEMI (non-ST-elevation myocardial infarction), 18 AI, and 31 STEMI patients, as defined by fourth universal definition of MI (UDMI4) and 59 control individuals. We then applied linear mixed effects model to compare the kinetics of all molecules in these MI sub-types.

Results

Established (cTnT, cTnI) and novel (cMyBP-C) cardiac necrosis markers failed in differentiating T1MI vs T2MI at early time points. All cardiac necrosis markers were higher in T1MI than in T2MI at 3 h after admission. Muscle-enriched miRNAs (miR-1 and miR-133a) were correlated with cardiac necrosis protein markers and did not offer better discrimination. Established cardiac strain marker NT-proBNP differentiated AI and T1MI at all time points but failed to discriminate T2MI from T1MI. However, the combination of NT-proBNP and cTnT along with age returned an overall AUC of 0.76 [95 % CI 0.67-0.84] for differentiating T1MI, T2MI and AI.

Conclusions

Rather than using single biomarkers of myocardial necrosis, a combination of clinical biomarkers for cardiac necrosis (troponin) and cardiac strain (NT-proBNP) might aid in differentiating T1MI, T2MI and AI.

From Classic to Modern Prognostic Biomarkers in Patients with Acute Myocardial Infarction

Despite all the important advances in its diagnosis and treatment, acute myocardial infarction (AMI) is still one of the most prominent causes of morbidity and mortality worldwide. Early identification of patients at high risk of poor outcomes through the measurement of various biomarker concentrations might contribute to more accurate risk stratification and help to guide more individualized therapeutic strategies, thus improving prognoses. The aim of this article is to provide an overview of the role and applications of cardiac biomarkers in risk stratification and prognostic assessment for patients with myocardial infarction. Although there is no ideal biomarker that can provide prognostic information for risk assessment in patients with AMI, the results obtained in recent years are promising. Several novel biomarkers related to the pathophysiological processes found in patients with myocardial infarction, such as inflammation, neurohormonal activation, myocardial stress, myocardial necrosis, cardiac remodeling and vasoactive processes, have been identified; they may bring additional value for AMI prognosis when included in multi-biomarker strategies. Furthermore, the use of artificial intelligence algorithms for risk stratification and prognostic assessment in these patients may have an extremely important role in improving outcomes.

Multiomics technologies: role in disease biomarker discoveries and therapeutics

 

Medical research has been revolutionized after the publication of the full human genome. This was the major landmark that paved the way for understanding the biological functions of different macro and micro molecules. With the advent of different high-throughput technologies, biomedical research was further revolutionized. These technologies constitute genomics, transcriptomics, proteomics, metabolomics, etc. Collectively, these high-throughputs are referred to as multi-omics technologies. In the biomedical field, these omics technologies act as efficient and effective tools for disease diagnosis, management, monitoring, treatment and discovery of certain novel disease biomarkers. Genotyping arrays and other transcriptomic studies have helped us to elucidate the gene expression patterns in different biological states, i.e. healthy and diseased states. Further omics technologies such as proteomics and metabolomics have an important role in predicting the role of different biological molecules in an organism. It is because of these high throughput omics technologies that we have been able to fully understand the role of different genes, proteins, metabolites and biological pathways in a diseased condition. To understand a complex biological process, it is important to apply an integrative approach that analyses the multi-omics data in order to highlight the possible interrelationships of the involved biomolecules and their functions. Furthermore, these omics technologies offer an important opportunity to understand the information that underlies disease. In the current review, we will discuss the importance of omics technologies as promising tools to understand the role of different biomolecules in diseases such as cancer, cardiovascular diseases, neurodegenerative diseases and diabetes.

SUMMARY POINTS

A 0/1h-algorithm using cardiac myosin-binding protein C for early diagnosis of myocardial infarction

AIMS

Cardiac myosin-binding protein C (cMyC) demonstrated high diagnostic accuracy for the early detection of non-ST-elevation myocardial infarction (NSTEMI). Its dynamic release kinetics may enable a 0/1h-decision algorithm that is even more effective than the ESC hs-cTnT/I 0/1 h rule-in/rule-out algorithm.

METHODS AND RESULTS

In a prospective international diagnostic study enrolling patients presenting with suspected NSTEMI to the emergency department, cMyC was measured at presentation and after 1 h in a blinded fashion. Modelled on the ESC hs-cTnT/I 0/1h-algorithms, we derived a 0/1h-cMyC-algorithm. Final diagnosis of NSTEMI was centrally adjudicated according to the 4th Universal Definition of Myocardial Infarction. Among 1495 patients, the prevalence of NSTEMI was 17%. The optimal derived 0/1h-algorithm ruled-out NSTEMI with cMyC 0 h concentration below 10 ng/L (irrespective of chest pain onset) or 0 h cMyC concentrations below 18 ng/L and 0/1 h increase <4 ng/L. Rule-in occurred with 0 h cMyC concentrations of at least 140 ng/L or 0/1 h increase ≥15 ng/L. In the validation cohort (n = 663), the 0/1h-cMyC-algorithm classified 347 patients (52.3%) as 'rule-out', 122 (18.4%) as 'rule-in', and 194 (29.3%) as 'observe'. Negative predictive value for NSTEMI was 99.6% [95% confidence interval (CI) 98.9-100%]; positive predictive value 71.1% (95% CI 63.1-79%). Direct comparison with the ESC hs-cTnT/I 0/1h-algorithms demonstrated comparable safety and even higher triage efficacy using the 0h-sample alone (48.1% vs. 21.2% for ESC hs-cTnT-0/1 h and 29.9% for ESC hs-cTnI-0/1 h; P < 0.001).

CONCLUSION

The cMyC 0/1h-algorithm provided excellent safety and identified a greater proportion of patients suitable for direct rule-out or rule-in based on a single measurement than the ESC 0/1h-algorithm using hs-cTnT/I.

TRIAL REGISTRATION

ClinicalTrials.gov number, NCT00470587.

Emerging Biomarkers in Acute Coronary Syndromes - A Pathophysiologic Perspective

Diagnosis and prognostication in acute coronary syndromes (ACS) is achieved using a combination of clinical factors and biomarkers, notably cardiac troponin and B type natriuretic peptide and its N terminal fragment NT-proBNP. However, there are numerous biomarkers that have been shown to be associated with ACS, with variable incremental utility. This brief review focusses on some promising emerging biomarkers in ACS, discussed according to pathophysiologic mechanism, as well as diagnostic and prognostic utility.

Biological variation of cardiac myosin-binding protein C in healthy individuals

OBJECTIVES

Cardiac myosin-binding protein C (cMyC) is a novel biomarker of myocardial injury, with a promising role in the triage and risk stratification of patients presenting with acute cardiac disease. In this study, we assess the weekly biological variation of cMyC, to examine its potential in monitoring chronic myocardial injury, and to suggest analytical quality specification for routine use of the test in clinical practice.

METHODS

Thirty healthy volunteers were included. Non-fasting samples were obtained once a week for ten consecutive weeks. Samples were tested in duplicate on the Erenna® platform by EMD Millipore Corporation. Outlying measurements and subjects were identified and excluded systematically, and homogeneity of analytical and within-subject variances was achieved before calculating the biological variability (CVI and CVG), reference change values (RCV) and index of individuality (II).

RESULTS

Mean age was 38 (range, 21-64) years, and 16 participants were women (53%). The biological variation, RCV and II with 95% confidence interval (CI) were: CVA (%) 19.5 (17.8-21.6), CVI (%) 17.8 (14.8-21.0), CVG (%) 66.9 (50.4-109.9), RCV (%) 106.7 (96.6-120.1)/-51.6 (-54.6 to -49.1) and II 0.42 (0.29-0.56). There was a trend for women to have lower CVG. The calculated RCVs were comparable between genders.

CONCLUSIONS

cMyC exhibits acceptable RCV and low II suggesting that it could be suitable for disease monitoring, risk stratification and prognostication if measured serially. Analytical quality specifications based on biological variation are similar to those for cardiac troponin and should be achievable at clinically relevant concentrations.

Cardiac troponin and defining myocardial infarction

The 4th Universal Definition of Myocardial Infarction has stimulated considerable debate since its publication in 2018. The intention was to define the types of myocardial injury through the lens of their underpinning pathophysiology. In this review, we discuss how the 4th Universal Definition of Myocardial Infarction defines infarction and injury and the necessary pragmatic adjustments that appear in clinical guidelines to maximize triage of real-world patients.

Prognostically relevant periprocedural myocardial injury and infarction associated with percutaneous coronary interventions: a Consensus Document of the ESC Working Group on Cellular Biology of the Heart and European Association of Percutaneous Cardiovascular Interventions (EAPCI)

A substantial number of chronic coronary syndrome (CCS) patients undergoing percutaneous coronary intervention (PCI) experience periprocedural myocardial injury or infarction. Accurate diagnosis of these PCI-related complications is required to guide further management given that their occurrence may be associated with increased risk of major adverse cardiac events (MACE). Due to lack of scientific data, the cut-off thresholds of post-PCI cardiac troponin (cTn) elevation used for defining periprocedural myocardial injury and infarction, have been selected based on expert consensus opinions, and their prognostic relevance remains unclear. In this Consensus Document from the ESC Working Group on Cellular Biology of the Heart and European Association of Percutaneous Cardiovascular Interventions (EAPCI), we recommend, whenever possible, the measurement of baseline (pre-PCI) cTn and post-PCI cTn values in all CCS patients undergoing PCI. We confirm the prognostic relevance of the post-PCI cTn elevation >5× 99th percentile URL threshold used to define type 4a myocardial infarction (MI). In the absence of periprocedural angiographic flow-limiting complications or electrocardiogram (ECG) and imaging evidence of new myocardial ischaemia, we propose the same post-PCI cTn cut-off threshold (>5× 99th percentile URL) be used to define prognostically relevant ‘major’ periprocedural myocardial injury. As both type 4a MI and major periprocedural myocardial injury are strong independent predictors of all-cause mortality at 1 year post-PCI, they may be used as quality metrics and surrogate endpoints for clinical trials. Further research is needed to evaluate treatment strategies for reducing the risk of major periprocedural myocardial injury, type 4a MI, and MACE in CCS patients undergoing PCI.

Early Rule-Out Strategies in the Emergency Department Utilizing High-Sensitivity Cardiac Troponin Assays

BACKGROUND

Over the past decade, intense collaboration between academic investigators and the diagnostic industry have allowed the integration of high-sensitivity cardiac troponin (hs-cTn) assays into clinical practice worldwide. The hs-cTn assays, with their increased diagnostic accuracy for acute myocardial infarction (AMI), have facilitated the maturation of early rule-out strategies. The first iteration was complex and required the combination of a biomarker panel, the electrocardiogram, and a clinical risk score and allowed the safe rule-out of AMI in only 10% of patients with acute chest pain. In contrast, the latest iterations, including the European Society of Cardiology (ESC) 0/1-h algorithm, are simple. They are based on hs-cTn concentrations only and allow the safe rule-out or rule-in of AMI in up to 75% of patients.

CONTENT

The purposes of this minireview are (a) to describe the best validated hs-cTn-based strategies for early rule-out of AMI, (b) to discuss the advantages and limitations of the different strategies, (c) to identify patient subgroups requiring particular attention, (d) to recognize challenges for widespread clinical implementation, and (e) to provide guidance on strategies for their safe and effective clinical implementation.

SUMMARY

Physicians and institutions may choose among several well-validated rule-out algorithms. The ESC 0/1-h algorithm for hs-cTnT or hs-cTnI seems to be the most attractive option today. It best balances safety and efficacy, and it has been derived and validated for all currently available hs-cTnT/I assays, facilitating widespread clinical implementation.

Cardiovascular Biomarkers in the Early Discrimination of Type 2 Myocardial Infarction

Importance

Rapid and accurate noninvasive discrimination of type 2 myocardial infarction (T2MI), which is because of a supply-demand mismatch, from type 1 myocardial infarction (T1MI), which arises via plaque rupture, is essential, because treatment differs substantially. Unfortunately, this is a major unmet clinical need, because even high-sensitivity cardiac troponin (hs-cTn) measurement provides only modest accuracy.

Objective

To test the hypothesis that novel cardiovascular biomarkers quantifying different pathophysiological pathways involved in T2MI and/or T1MI may aid physicians in the rapid discrimination of T2MI vs T1MI.

Design, Setting, and Participants

This international, multicenter prospective diagnostic study was conducted in 12 emergency departments in 5 countries (Switzerland, Spain, Italy, Poland, and the Czech Republic) with patients presenting with acute chest discomfort to the emergency departments. The study quantified the discrimination of hs-cTn T, hs-cTn I, and 17 novel cardiovascular biomarkers measured in subsets of consecutively enrolled patients against a reference standard (final diagnosis), centrally adjudicated by 2 independent cardiologists according to the fourth universal definition of MI, using all information, including cardiac imaging and serial measurements of hs-cTnT or hs-cTnI.

Results

Among 5887 patients, 1106 (18.8%) had an adjudicated final diagnosis of MI; of these, 860 patients (77.8%) had T1MI, and 246 patients (22.2%) had T2MI. Patients with T2MI vs those with T1MI had lower concentrations of biomarkers quantifying cardiomyocyte injury hs-cTnT (median [interquartile range (IQR)], 30 (17-55) ng/L vs 58 (28-150) ng/L), hs-cTnI (median [IQR], 23 [10-83] ng/L vs 115 [28-576] ng/L; P < .001), and cardiac myosin-binding protein C (at presentation: median [IQR], 76 [38-189] ng/L vs 257 [75-876] ng/L; P < .001) but higher concentrations of biomarkers quantifying endothelial dysfunction, microvascular dysfunction, and/or hemodynamic stress (median [IQR] values: C-terminal proendothelin 1, 97 [75-134] pmol/L vs 68 [55-91] pmol/L; midregional proadrenomedullin, 0.97 [0.67-1.51] pmol/L vs 0.72 [0.53-0.99] pmol/L; midregional pro-A-type natriuretic peptide, 378 [207-491] pmol/L vs 152 [90-247] pmol/L; and growth differentiation factor 15, 2.26 [1.44-4.35] vs 1.56 [1.02-2.19] ng/L; all P < .001). Discrimination for these biomarkers, as quantified by the area under the receiver operating characteristics curve, was modest (hs-cTnT, 0.67 [95% CI, 0.64-0.71]; hs-cTn I, 0.71 [95% CI, 0.67-0.74]; cardiac myosin-binding protein C, 0.67 [95% CI, 0.61-0.73]; C-terminal proendothelin 1, 0.73 [95% CI, 0.63-0.83]; midregional proadrenomedullin, 0.66 [95% CI, 0.60-0.73]; midregional pro-A-type natriuretic peptide, 0.77 [95% CI, 0.68-0.87]; and growth differentiation factor 15, 0.68 [95% CI, 0.58-0.79]).

Conclusions and Relevance

In this study, biomarkers quantifying myocardial injury, endothelial dysfunction, microvascular dysfunction, and/or hemodynamic stress provided modest discrimination in early, noninvasive diagnosis of T2MI.

High retinoic acid receptor-related orphan receptor A gene expression in peripheral blood leukocytes may be related to acute myocardial infarction

OBJECTIVE

This study aimed to investigate whether differential expression of the retinoic acid receptor-related orphan receptor A (RORA) gene is related to occurrence of acute myocardial infarction (AMI).

METHODS

This was a retrospective study. White blood cells of 93 patients with acute myocardial infarction and 74 patients with stable coronary artery disease were collected. Reverse transcription quantitative polymerase chain reaction and western blotting were used to measure RORA mRNA and protein expression, respectively.

RESULTS

RORA mRNA expression levels in peripheral blood leukocytes in patients with AMI were 1.57 times higher than those in patients with stable coronary artery disease. Protein RORA levels in peripheral blood of patients with AMI were increased. Binary logistic regression analysis showed that high expression of RORA was an independent risk factor for AMI, and it increased the risk of AMI by 2.990 times.

CONCLUSION

RORA expression levels in patients with AMI is significantly higher than that in patients with stable coronary artery disease. High expression of RORA is related to AMI and it may be an independent risk factor for AMI.

The C0-C1f Region of Cardiac Myosin Binding Protein-C Induces Pro-Inflammatory Responses in Fibroblasts via TLR4 Signaling

Myocardial injury is associated with inflammation and fibrosis. Cardiac myosin-binding protein-C (cMyBP-C) is cleaved by µ-calpain upon myocardial injury, releasing C0-C1f, an N-terminal peptide of cMyBP-C. Previously, we reported that the presence of C0-C1f is pathogenic within cardiac tissue and is able to activate macrophages. Fibroblasts also play a crucial role in cardiac remodeling arising from ischemic events, as they contribute to both inflammation and scar formation. To understand whether C0-C1f directly modulates fibroblast phenotype, we analyzed the impact of C0-C1f on a human fibroblast cell line in vitro by performing mRNA microarray screening, immunofluorescence staining, and quantitative real-time PCR. The underlying signaling pathways were investigated by KEGG analysis and determined more precisely by targeted inhibition of the potential signaling cascades in vitro. C0-C1f induced pro-inflammatory responses that might delay TGFβ-mediated myofibroblast conversion. TGFβ also counteracted C0-C1f-mediated fibroblast activation. Inhibition of TLR4 or NFκB as well as the delivery of miR-146 significantly reduced C0-C1f-mediated effects. In conclusion, C0-C1f induces inflammatory responses in human fibroblasts that are mediated via TRL4 signaling, which is decreased in the presence of TGFβ. Specific targeting of TLR4 signaling could be an innovative strategy to modulate C0-C1f-mediated inflammation.

Past, Present, and Future of Blood Biomarkers for the Diagnosis of Acute Myocardial Infarction-Promises and Challenges

Despite important advancements in acute myocardial infarction (AMI) management, it continues to represent a leading cause of mortality worldwide. Fast and reliable AMI diagnosis can significantly reduce mortality in this high-risk population. Diagnosis of AMI has relied on biomarker evaluation for more than 50 years. The upturn of high-sensitivity cardiac troponin testing provided extremely sensitive means to detect cardiac myocyte necrosis, but this increased sensitivity came at the cost of a decrease in diagnostic specificity. In addition, although cardiac troponins increase relatively early after the onset of AMI, they still leave a time gap between the onset of myocardial ischemia and our ability to detect it, thus precluding very early management of AMI. Newer biomarkers detected in processes such as inflammation, neurohormonal activation, or myocardial stress occur much earlier than myocyte necrosis and the diagnostic rise of cardiac troponins, allowing us to expand biomarker research in these areas. Increased understanding of the complex AMI pathophysiology has spurred the search of new biomarkers that could overcome these shortcomings, whereas multi-omic and multi-biomarker approaches promise to be game changers in AMI biomarker assessment. In this review, we discuss the evolution, current application, and emerging blood biomarkers for the diagnosis of AMI; we address their advantages and promises to improve patient care, as well as their challenges, limitations, and technical and diagnostic pitfalls. Questions that remain to be answered and hotspots for future research are also emphasized.

Systems biology in cardiovascular disease: a multiomics approach

Omics techniques generate large, multidimensional data that are amenable to analysis by new informatics approaches alongside conventional statistical methods. Systems theories, including network analysis and machine learning, are well placed for analysing these data but must be applied with an understanding of the relevant biological and computational theories. Through applying these techniques to omics data, systems biology addresses the problems posed by the complex organization of biological processes. In this Review, we describe the techniques and sources of omics data, outline network theory, and highlight exemplars of novel approaches that combine gene regulatory and co-expression networks, proteomics, metabolomics, lipidomics and phenomics with informatics techniques to provide new insights into cardiovascular disease. The use of systems approaches will become necessary to integrate data from more than one omic technique. Although understanding the interactions between different omics data requires increasingly complex concepts and methods, we argue that hypothesis-driven investigations and independent validation must still accompany these novel systems biology approaches to realize their full potential.

High-sensitivity troponin assays for early rule-out of acute myocardial infarction in people with acute chest pain: a systematic review and economic evaluation

BACKGROUND

Early diagnosis of acute myocardial infarction is important, but only 20% of emergency admissions for chest pain will actually have an acute myocardial infarction. High-sensitivity cardiac troponin assays may allow rapid rule out of myocardial infarction and avoid unnecessary hospital admissions.

OBJECTIVES

To assess the clinical effectiveness and cost-effectiveness of high-sensitivity cardiac troponin assays for the management of adults presenting with acute chest pain, in particular for the early rule-out of acute myocardial infarction.

METHODS

Sixteen databases were searched up to September 2019. Review methods followed published guidelines. Studies were assessed for quality using appropriate risk-of-bias tools. The bivariate model was used to estimate summary sensitivity and specificity for meta-analyses involving four or more studies; otherwise, random-effects logistic regression was used. The health economic analysis considered the long-term costs and quality-adjusted life-years associated with different troponin testing methods. The de novo model consisted of a decision tree and a state-transition cohort model. A lifetime time horizon (of 60 years) was used.

RESULTS

Thirty-seven studies (123 publications) were included in the review. The high-sensitivity cardiac troponin test strategies evaluated are defined by the combination of four factors (i.e. assay, number and timing of tests, and threshold concentration), resulting in a large number of possible combinations. Clinical opinion indicated a minimum clinically acceptable sensitivity of 97%. When considering single test strategies, only those using a threshold at or near to the limit of detection for the assay, in a sample taken at presentation, met the minimum clinically acceptable sensitivity criterion. The majority of the multiple test strategies that met this criterion comprised an initial rule-out step, based on high-sensitivity cardiac troponin levels in a sample taken on presentation and a minimum symptom duration, and a second stage for patients not meeting the initial rule-out criteria, based on presentation levels of high-sensitivity cardiac troponin and absolute change after 1, 2 or 3 hours. Two large cluster randomised controlled trials found that implementation of an early rule-out pathway for myocardial infarction reduced length of stay and rate of hospital admission without increasing cardiac events. In the base-case analysis, standard troponin testing was both the most effective and the most costly. Other testing strategies with a sensitivity of 100% (subject to uncertainty) were almost equally effective, resulting in the same life-year and quality-adjusted life-year gain at up to four decimal places. Comparisons based on the next best alternative showed that for willingness-to-pay values below £8455 per quality-adjusted life-year, the Access High Sensitivity Troponin I (Beckman Coulter, Brea, CA, USA) [(symptoms > 3 hours AND < 4 ng/l at 0 hours) OR (< 5 ng/l AND Δ < 5 ng/l at 0 to 2 hours)] would be cost-effective. For thresholds between £8455 and £20,190 per quality-adjusted life-year, the Elecsys® Troponin-T high sensitive (Roche, Basel, Switzerland) (< 12 ng/l at 0 hours AND Δ < 3 ng/l at 0 to 1 hours) would be cost-effective. For a threshold > £20,190 per quality-adjusted life-year, the Dimension Vista® High-Sensitivity Troponin I (Siemens Healthcare, Erlangen, Germany) (< 5 ng/l at 0 hours AND Δ < 2 ng/l at 0 to 1 hours) would be cost-effective.

CONCLUSIONS

High-sensitivity cardiac troponin testing may be cost-effective compared with standard troponin testing.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42019154716.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Evidence Synthesis programme and will be published in full in Health Technology Assessment; Vol. 25, No. 33. See the NIHR Journals Library website for further project information.

Critical appraisal of the 2020 ESC guideline recommendations on diagnosis and risk assessment in patients with suspected non-ST-segment elevation acute coronary syndrome

Multiple new recommendations have been introduced in the 2020 ESC guidelines for the management of acute coronary syndromes with a focus on diagnosis, prognosis, and management of patients presenting without persistent ST-segment elevation. Most recommendations are supported by high-quality scientific evidence. The guidelines provide solutions to overcome obstacles presumed to complicate a convenient interpretation of troponin results such as age-, or sex-specific cutoffs, and to give practical advice to overcome delays of laboratory reporting. However, in some areas, scientific support is less well documented or even missing, and other areas are covered rather by expert opinion or subjective recommendations. We aim to provide a critical appraisal on several recommendations, mainly related to the diagnostic and prognostic assessment, highlighting the discrepancies between Guideline recommendations and the existing scientific evidence.

Cardiac myosin-binding protein C in the diagnosis and risk stratification of acute heart failure

AIMS

Cardiac myosin-binding protein C (cMyC) seems to be even more sensitive in the quantification of cardiomyocyte injury vs. high-sensitivity cardiac troponin, and may therefore have diagnostic and prognostic utility.

METHODS AND RESULTS

In a prospective multicentre diagnostic study, cMyC, high-sensitivity cardiac troponin T (hs-cTnT), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) plasma concentrations were measured in blinded fashion in patients presenting to the emergency department with acute dyspnoea. Two independent cardiologists centrally adjudicated the final diagnosis. Diagnostic accuracy for acute heart failure (AHF) was quantified by the area under the receiver operating characteristic curve (AUC). All-cause mortality within 360 days was the prognostic endpoint. Among 1083 patients eligible for diagnostic analysis, 51% had AHF. cMyC concentrations at presentation were higher among AHF patients vs. patients with other final diagnoses [72 (interquartile range, IQR 39-156) vs. 22 ng/L (IQR 12-42), P < 0.001)]. cMyC's AUC was high [0.81, 95% confidence interval (CI) 0.78-0.83], higher than hs-cTnT's (0.79, 95% CI 0.76-0.82, P = 0.081) and lower than NT-proBNP's (0.91, 95% CI 0.89-0.93, P < 0.001). Among 794 AHF patients eligible for prognostic analysis, 28% died within 360 days; cMyC plasma concentrations above the median indicated increased risk of death (hazard ratio 2.19, 95% CI 1.66-2.89; P < 0.001). cMyC's prognostic accuracy was comparable with NT-proBNP's and hs-cTnT's. cMyC did not independently predict all-cause mortality when used in validated multivariable regression models. In novel multivariable regression models including medication, age, left ventricular ejection fraction, and discharge creatinine, cMyC remained an independent predictor of death and had no interactions with medical therapies at discharge.

CONCLUSION

Cardiac myosin-binding protein C may aid physicians in the rapid triage of patients with suspected AHF.

Diagnostic and Prognostic Biomarkers for Myocardial Infarction

The incidence of myocardial infarction (MI) increases every year worldwide. Better diagnostic and prognostic biomarkers for clinical applications are the consistent pursuit of MI research. In addition to electrocardiogram, echocardiography, coronary angiography, etc., circulating biomarkers are essential for the diagnosis, prognosis, and treatment effect monitoring of MI patients. In this review, we assessed both strength and weakness of MI circulating biomarkers including: (1) originated from damaged myocardial tissues including current golden standard cardiac troponin, (2) released from non-myocardial tissues due to MI-induced systems reactions, and (3) preexisted in blood circulation before the occurrence of MI event. We also summarized newly reported MI biomarkers. We proposed that the biomarkers preexisting in blood circulation before MI incidents should be emphasized in research and development for MI prevention in near future.

Biomarkers for Heart Failure Prognosis: Proteins, Genetic Scores and Non-coding RNAs

Heart failure (HF) is a complex disease in which cardiomyocyte injury leads to a cascade of inflammatory and fibrosis pathway activation, thereby causing decrease in cardiac function. As a result, several biomolecules are released which can be identified easily in circulating body fluids. The complex biological processes involved in the development and worsening of HF require an early treatment strategy to stop deterioration of cardiac function. Circulating biomarkers provide not only an ideal platform to detect subclinical changes, their clinical application also offers the opportunity to monitor disease treatment. Many of these biomarkers can be quantified with high sensitivity; allowing their clinical application to be evaluated beyond diagnostic purposes as potential tools for HF prognosis. Though the field of biomarkers is dominated by protein molecules, non-coding RNAs (microRNAs, long non-coding RNAs, and circular RNAs) are novel and promising biomarker candidates that encompass several ideal characteristics required in the biomarker field. The application of genetic biomarkers as genetic risk scores in disease prognosis, albeit in its infancy, holds promise to improve disease risk estimation. Despite the multitude of biomarkers that have been available and identified, the majority of novel biomarker candidates are not cardiac-specific, and instead may simply be a readout of systemic inflammation or other pathological processes. Thus, the true value of novel biomarker candidates in HF prognostication remains unclear. In this article, we discuss the current state of application of protein, genetic as well as non-coding RNA biomarkers in HF risk prognosis.

Noncoding RNAs versus Protein Biomarkers in Cardiovascular Disease

The development of more sensitive protein biomarker assays results in continuous improvements in detectability, extending the range of clinical applications to the detection of subclinical cardiovascular disease (CVD). However, these efforts have not yet led to improvements in risk assessment compared with existing risk scores. Noncoding RNAs (ncRNAs) have been assessed as biomarkers, and miRNAs have attracted most attention. More recently, other ncRNA classes have been identified, including long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs). Here, we compare emerging ncRNA biomarkers in the cardiovascular field with protein biomarkers for their potential in clinical application, focusing on myocardial injury.

The Biomarkers for Acute Myocardial Infarction and Heart Failure

The use of a large number of cardiovascular biomarkers, meant to complement the use of the electrocardiogram, echocardiography cardiac imaging, and clinical symptom assessment, has become a routine in clinical diagnosis, differential diagnosis, risk stratification, and prognosis and guides the management of patients with suspected cardiovascular diseases. There is a broad consensus that cardiac troponin and natriuretic peptides are the preferred biomarkers in clinical practice for the diagnosis of the acute coronary syndrome and heart failure, respectively, while the roles and possible clinical applications of several other potential biomarkers are still under study. This review mainly focuses on the recent studies of the roles and clinical applications of troponin and natriuretic peptides, which seem to be the best-validated markers in distinguishing and predicting the future cardiac events of patients with suspected cardiovascular diseases. Additionally, the review briefly discusses some of the large number of potential markers that may play a more prominent role in the future.

Biomarkers in primary prevention : Meaningful diagnosis based on biomarker scores?

Cardiovascular (CV) risk assessment is based on the utilization of risk scores, enabling clinicians to estimate an individual's risk to develop CV pathologies and events. Such risk scores comprise classic CV risk factors such as smoking, diabetes, hypertension, and blood cholesterol levels. Recently, other CV biomarkers such as cardiac troponins have been suggested and evaluated as alternative biomarkers not only in the acute diagnostic setting of myocardial infarction, but also as markers for risk stratification in the general population. In this review, we summarize the current knowledge on biomarkers in the field of primary prevention in cardiovascular disease (CVD). Furthermore, we present potential alternative biomarker-based strategies for CV risk assessment. In this respect we provide an outlook on the potential use of genomic variation as well as circulating non-coding RNAs to complement current risk assessment strategies so as to further personalize risk stratification in CVD.

Combining High-Sensitivity Cardiac Troponin I and Cardiac Troponin T in the Early Diagnosis of Acute Myocardial Infarction

BACKGROUND

Combining 2 signals of cardiomyocyte injury, cardiac troponin I (cTnI) and T (cTnT), might overcome some individual pathophysiological and analytical limitations and thereby increase diagnostic accuracy for acute myocardial infarction with a single blood draw. We aimed to evaluate the diagnostic performance of combinations of high-sensitivity (hs) cTnI and hs-cTnT for the early diagnosis of acute myocardial infarction.

METHODS

The diagnostic performance of combining hs-cTnI (Architect, Abbott) and hs-cTnT (Elecsys, Roche) concentrations (sum, product, ratio, and a combination algorithm) obtained at the time of presentation was evaluated in a large multicenter diagnostic study of patients with suspected acute myocardial infarction. The optimal rule-out and rule-in thresholds were externally validated in a second large multicenter diagnostic study. The proportion of patients eligible for early rule-out was compared with the European Society of Cardiology 0/1 and 0/3 hour algorithms.

RESULTS

Combining hs-cTnI and hs-cTnT concentrations did not consistently increase overall diagnostic accuracy as compared with the individual isoforms. However, the combination improved the proportion of patients meeting criteria for very early rule-out. With the European Society of Cardiology 2015 guideline recommended algorithms and cut-offs, the proportion meeting rule-out criteria after the baseline blood sampling was limited (6% to 24%) and assay dependent. Application of optimized cut-off values using the sum (9 ng/L) and product (18 ng²/L²) of hs-cTnI and hs-cTnT concentrations led to an increase in the proportion ruled-out after a single blood draw to 34% to 41% in the original (sum: negative predictive value [NPV] 100% [95% confidence interval (CI), 99.5% to 100%]; product: NPV 100% [95% CI, 99.5% to 100%]) and in the validation cohort (sum: NPV 99.6% [95% CI, 99.0-99.9%]; product: NPV 99.4% [95% CI, 98.8-99.8%]). The use of a combination algorithm (hs-cTnI <4 ng/L and hs-cTnT <9 ng/L) showed comparable results for rule-out (40% to 43% ruled out; NPV original cohort 99.9% [95% CI, 99.2-100%]; NPV validation cohort 99.5% [95% CI, 98.9-99.8%]) and rule-in (positive predictive value [PPV] original cohort 74.4% [95% Cl, 69.6-78.8%]; PPV validation cohort 84.0% [95% Cl, 79.7-87.6%]).

CONCLUSIONS

New strategies combining hs-cTnI and hs-cTnT concentrations may significantly increase the number of patients eligible for very early and safe rule-out, but do not seem helpful for the rule-in of acute myocardial infarction.

CLINICAL TRIAL REGISTRATION

URL (APACE): https://www.clinicaltrial.gov . Unique identifier: NCT00470587. URL (ADAPT): www.anzctr.org.au . Unique identifier: ACTRN12611001069943.

Cardiac Myosin-Binding Protein C to Diagnose Acute Myocardial Infarction in the Pre-Hospital Setting

Background Early triage is essential to improve outcomes in patients with suspected acute myocardial infarction (AMI). This study investigated whether cMyC (cardiac myosin-binding protein), a novel biomarker of myocardial necrosis, can aid early diagnosis of AMI and risk stratification. Methods and Results cMyC and high-sensitivity cardiac troponin T were retrospectively quantified in blood samples obtained by ambulance-based paramedics in a prospective, diagnostic cohort study. Patients with ongoing or prolonged periods of chest discomfort, acute dyspnoea in the absence of known pulmonary disease, or clinical suspicion of AMI were recruited. Discrimination power was evaluated by calculating the area under the receiver operating characteristics curve; diagnostic performance was assessed at predefined thresholds. Diagnostic nomograms were derived and validated using bootstrap resampling in logistic regression models. Seven hundred seventy-six patients with median age 68 [58;78] were recruited. AMI was the final adjudicated diagnosis in 22%. Median symptom to sampling time was 70 minutes. cMyC concentration in patients with AMI was significantly higher than with other diagnoses: 98 [43;855] versus 17 [9;42] ng/L. Discrimination power for AMI was better with cMyC than with high-sensitivity cardiac troponin T (area under the curve, 0.839 versus 0.813; P=0.005). At a previously published rule-out threshold (10 ng/L), cMyC reaches 100% sensitivity and negative predictive value in patients after 2 hours of symptoms. In logistic regression analysis, cMyC is superior to high-sensitivity cardiac troponin T and was used to derive diagnostic and prognostic nomograms to evaluate risk of AMI and death. Conclusions In patients undergoing blood draws very early after symptom onset, cMyC demonstrates improved diagnostic discrimination of AMI and could significantly improve the early triage of patients with suspected AMI.

Comparative Analysis of Circulating Noncoding RNAs Versus Protein Biomarkers in the Detection of Myocardial Injury

RATIONALE

Noncoding RNAs (ncRNAs), including microRNAs (miRNAs), circular RNAs (circRNAs), and long noncoding RNAs (lncRNAs), are proposed novel biomarkers of myocardial injury. Their release kinetics have not been explored without confounding by heparin nor has their relationship to myocardial protein biomarkers.

OBJECTIVE

To compare ncRNA types in heparinase-treated samples with established and emerging protein biomarkers for myocardial injury.

METHODS AND RESULTS

Screening of 158 circRNAs and 21 lncRNAs in human cardiac tissue identified 12 circRNAs and 11 lncRNAs as potential biomarkers with cardiac origin. Eleven miRNAs were included. At low spike-in concentrations of myocardial tissue, significantly higher regression coefficients were observed across ncRNA types compared with cardiac troponins and cMyBP-C (cardiac myosin-binding protein C). Heparinase treatment of serial plasma and serum samples of patients undergoing transcoronary ablation of septal hypertrophy removed spurious correlations between miRNAs in non-heparinase-treated samples. After transcoronary ablation of septal hypertrophy, muscle-enriched miRNAs (miR-1 and miR-133a) showed a steeper and earlier increase than cardiac-enriched miRNAs (miR-499 and miR-208b). Putative cardiac lncRNAs, including LIPCAR (long intergenic noncoding RNA predicting cardiac remodeling and survival), did not rise, refuting a predominant cardiac origin. Cardiac circRNAs remained largely undetectable. In a validation cohort of acute myocardial infarction, receiver operating characteristic curve analysis revealed noninferiority of cardiac-enriched miRNAs, but miRNAs failed to identify cases presenting with low troponin values. cMyBP-C was validated as a biomarker with highly sensitive properties, and the combination of muscle-enriched miRNAs with high-sensitive cardiac troponin T and cMyBP-C returned the highest area under the curve values.

CONCLUSIONS

In a comparative assessment of ncRNAs and protein biomarkers for myocardial injury, cMyBP-C showed properties as the most sensitive cardiac biomarker while miRNAs emerged as promising candidates to integrate ncRNAs with protein biomarkers. Sensitivity of current miRNA detection is inferior to cardiac proteins but a multibiomarker combination of muscle-enriched miRNAs with cMyBP-C and cardiac troponins could open a new path of integrating complementary characteristics of different biomarker types.

Cardiac Myosin-Binding Protein C Release Profile After Cardiac Surgery in Intensive Care Unit

BACKGROUND

Cardiac surgical procedures produce iatrogenic myocardial cell injury with necrosis that result in an obligatory release of biomarkers. Cardiac myosin binding protein C (cMyBP-C) has recently emerged as a specific and sensitive biomarker in patients with acute myocardial injury. We therefore aimed to investigate the release profiles of cMyBP-C after cardiac surgical procedures.

METHODS

Enzyme-linked immunosorbent assay to detect blood cMyBP-C was established by using two monoclonal antibodies against N-terminus of human cMyBP-C. Consecutive patients undergoing cardiac operations (N = 151) were recruited in this study. Blood cMyBP-C was assayed preoperatively, at intensive care unit arrival (0 hour after the operation), at 2 to 48 hours, and before discharge. The characteristics and detailed surgical procedure were recorded.

RESULTS

The established immunoassay was capable of detecting human cMyBP-C (0 to 1000 ng/L). The released cMyBP-C peaked immediately after cardiac surgery (0 h), attaining 3.8-fold higher than before the operation, dropped abruptly within 24 hours, and stayed at a higher level until discharge. Postoperative cMyBP-C levels correlated positively with high-sensitivity cardiac troponin T (hs-cTnT), creatine kinase, myoglobin, and creatine kinase MB isoenzyme. Different cardiac surgical procedures were characterized by different levels of release of cardiac biomarkers. Isolated off-pump coronary artery bypass grafting was associated with the smaller amount of cMyBP-C release, whereas valve replacement/plasty surgery produced higher release, in particular the multiple-valve surgery. Both cMyBP-C and hs-cTnT correlated with surgical techniques, postoperative intensive care unit stay, and hospital stay.

CONCLUSIONS

Circulating cMyBP-C is a promising novel biomarker for evaluating cardiac surgical trauma in patients undergoing a cardiac operation.