Biomarker in cardiology: DGK welcomes ESC Munich 2018

Biomarkers Utility: At the Borderline between Cardiology and Neurology

Biomarkers are important diagnostic and prognostic tools as they provide results in a short time while still being an inexpensive, reproducible and accessible method. Their well-known benefits have placed them at the forefront of research in recent years, with new and innovative discoveries being implemented. Cardiovascular and neurological diseases often share common risk factors and pathological pathways which may play an important role in the use and interpretation of biomarkers' values. Among the biomarkers used extensively in clinical practice in cardiology, hs-TroponinT, CK-MB and NTproBNP have been shown to be strongly influenced by multiple neurological conditions. Newer ones such as galectin-3, lysophosphatidylcholine, copeptin, sST2, S100B, myeloperoxidase and GDF-15 have been extensively studied in recent years as alternatives with an increased sensitivity for cardiovascular diseases, but also with significant results in the field of neurology. Thus, given their low specificity, the values interpretation must be correlated with the clinical judgment and other available investigations.

VCAM-1 as a predictor biomarker in cardiovascular disease

The vascular cellular adhesion molecule-1 (VCAM-1) is a protein that canonically participates in the adhesion and transmigration of leukocytes to the interstitium during inflammation. VCAM-1 expression, together with soluble VCAM-1 (sVCAM-1) induced by the shedding of VCAM-1 by metalloproteinases, have been proposed as biomarkers in immunological diseases, cancer, autoimmune myocarditis, and as predictors of mortality and morbidity in patients with chronic heart failure (HF), endothelial injury in patients with coronary artery disease, and arrhythmias. This revision aims to discuss the role of sVCAM-1 as a biomarker to predict the occurrence, development, and preservation of cardiovascular disease.

State of the Art-High-Sensitivity Troponins in Acute Coronary Syndromes

In cases of suspected acute coronary syndrome (ACS), rapid and accurate diagnosis is essential to establish effective evidence-based medical treatment. Patients' history, clinical examination, 12-lead electrocardiogram, and cardiac biomarkers are cornerstones in initial management. Since high-sensitivity cardiac troponins were established, they have markedly expedited and revolutionized rule-in and rule-out pathways of patients with ACS and changed our everyday clinical practice. Thus, they have become an indispensable tool in daily routine in emergency units. This review focuses on historical and contemporary standards in laboratory biomarkers of myocardial injury and discusses their implication in the context of the updated universal definition of myocardial infarction.

Soluble neprilysin, NT-proBNP, and growth differentiation factor-15 as biomarkers for heart failure in dialysis patients (SONGBIRD)

Background

Dialysis patients are at increased risk of HF. However, diagnostic utility of NT-proBNP as a biomarker is decreased in patients on dialysis. GDF-15 and cNEP are biomarkers of distinct mechanisms that may contribute to HF pathophysiology in such cohorts. The aim of this study was to determine whether growth differentiation factor-15 (GDF-15) and circulating neprilysin (cNEP) improve the diagnosis of congestive heart failure (HF) in patients on dialysis.

Methods and results

We compared circulating concentrations of NT-proBNP, GDF-15, and cNEP along with cNEP activity in patients on chronic dialysis without (n = 80) and with HF (n = 73), as diagnosed by clinical parameters and post-dialysis echocardiography. We used correlation, linear and logistic regression as well as receiver operating characteristic (ROC) analyses. Compared to controls, patients with HF had higher median values of NT-proBNP (16,216 [interquartile range, IQR = 27739] vs. 2883 [5866] pg/mL, p < 0.001), GDF-15 (7512 [7084] vs. 6005 [4892] pg/mL, p = 0.014), but not cNEP (315 [107] vs. 318 [124] pg/mL, p = 0.818). Median cNEP activity was significantly lower in HF vs. controls (0.189 [0.223] vs. 0.257 [0.166] nmol/mL/min, p < 0.001). In ROC analyses, a multi-marker model combining clinical covariates, NT-proBNP, GDF-15, and cNEP activity demonstrated best discrimination of HF from controls (AUC = 0.902, 95% CI 0.857–0.947, p < 0.001 vs. base model AUC = 0.785).

Conclusion

We present novel comparative data on physiologically distinct circulating biomarkers for HF in patients on dialysis. cNEP activity but not concentration and GDF-15 provided incremental diagnostic information over clinical covariates and NT-proBNP and may aid in diagnosing HF in dialysis patients.

Graphic abstract

Electronic supplementary material

The online version of this article (10.1007/s00392-020-01597-x) contains supplementary material, which is available to authorized users.

A novel risk score to predict survival in advanced heart failure due to cardiac amyloidosis

BACKGROUND

Cardiac amyloidosis, caused by deposition of immunoglobulin light chains (AL) or transthyretin (ATTR), carries a poor prognosis. Established risk scores for amyloidosis may not predict outcomes in those patients who develop advanced heart failure and who are potential candidates for heart transplantation. Here, we aimed to identify predictive parameters for patients with severe heart failure due to amyloidosis.

METHODS

Out of > 1000 patients with cardiac amyloidosis (AL or ATTR) admitted to our centre between September 1998 and January 2016, a cohort of 120 patients with a complete cardiac assessment at diagnosis, including right heart catheterization, echocardiography and biomarkers, was analysed retrospectively in this study. Primary endpoint was all-cause mortality. We performed univariate and multivariate Cox regression analysis, generated risk scores to predict outcomes in AL and ATTR amyloidosis and compared those to established risk models for amyloidosis.

RESULTS

In the Cox multivariate model, high-sensitivity troponin T (hsTnT; hazard ratio (HR) 1.003; confidence interval (CI) 1.001-1.005; p = 0.009) and mean pulmonary artery pressure (HR 1.061; CI 1.024-1.100; p = 0.001) were found to significantly and independently predict outcomes for AL amyloidosis, whereas QRS duration (HR 1.021; CI 1.004-1.039; p = 0.013), hsTnT (HR 1.021; CI 1.006-1.036; p = 0.006) and N-terminal pro-brain natriuretic peptide (HR 1.0003; CI 1.0001-1.0004; p = 0.002) were the best predictors for ATTR amyloidosis. A simple risk score ("HeiRisk") including these parameters for AL and ATTR allowed a more precise risk stratification in our patient population compared to established risk models.

CONCLUSIONS

Risk stratification for cardiac amyloidosis with the newly developed "HeiRisk" score may be superior to other staging systems for patients with advanced heart failure due to amyloid cardiomyopathy.

[Evidence-based drug therapy for heart failure-an update]

Chronic heart failure affects millions of people worldwide and is associated with high morbidity and mortality. Because of steadily increasing ageing populations and improved survival rates after myocardial infarction, the incidence of chronic heart failure is rising. As acute decompensated heart failure is one of the leading causes for hospitalization in Germany, heart failure imposes a huge economic burden on its health care system. Guideline directed therapy is important to improve prognosis. In the following, we give an overview about novel heart failure clinical trial results and point to important comorbidities.