1Universitätsklinikum Tübingen Innere Medizin III, Kardiologie und Angiologie Tübingen, Deutschland; 2Universitätsklinikum Tübingen Diagnostische und Interventionelle Radiologie Tübingen, Deutschland; 3Universitätsklinikum Tübingen Kardiopathologie Tübingen, Deutschland
Background
Heart failure (HF) remains a tremendous socioeconomic burden with repeated hospitalization associated with HF and an increasing incidence and. Cardiomyopathies are the main cause of progressive HF and outstanding advances of diagnostics, pharmacological and device-based therapies have significantly improved cardiovascular outcomes during the last decade. However, mortality rates worldwide remain high. The current phenotype-based classification of non-ischemic cardiomyopathies facilitates risk stratification of patients with HF but nonetheless risk factors often remain inapparent prior to disease incidence.
Methods
We prospectively enrolled patients with symptomatic HF due to non-ischemic heart disease in a large-scale consecutive cohort (n=703) and all patients underwent endomyocardial biopsy for suspected non-ischemic cardiomyopathy. RNA data were acquired using Nanostring sequencing-technology alongside histological analyses within the cardiac tissue. We then performed a ten-year follow-up to screen for adverse cardiovascular (CV) events associated with NIHD.
Results
A guideline-based classification of patients with cardiomyopathy resulted in a phenotyping of risk groups. We found that characteristic changes of pro-inflammatory and pro-fibrotic cytokine/chemokine expression within the myocardium occurred in patients with symptomatic cardiomyopathy (Figure 1A-B). We found that elevated expression of Gremlin (Grem) was associated with pro-fibrotic cardiac remodelling and a significant decrease of left ventricular functional capacity in the inflamed myocardium (Figure 1C-D). Further, the expression of Gremlin was enriched with pro-fibrotic and inflammatory RNA signaling pathways within the cardiac tissue material hinting at underlying pathophysiological cascades (Figure 2A-D).
Most strikingly, the expression of Gremlin was independently associated with an increased CV risk during the ten-year follow-up (Figure 2E-F). Thus, patients with Grem+ EMB were at elevated risk to suffer from cardiac death and number of patients eligible for ICD implantation during the clinical follow-up was critically enhanced in patients with Grem+ EMB (Figure 2G). Lastly, the estimation of an elevated CV risk by machine learning including Gremlin improved the ten-year risk stratification among all patients with symptomatic cardiomyopathy (Figure 2H).
Conclusion
Our results unveiled that Gremlin promotes inflammatory and pro-fibrotic cardiac remodeling in patients with symptomatic cardiomyopathy and patients with Grem+ EMB are at elevated risk to develop adverse CV events. Thus, the histological evaluation of pathophysiological cascades including Gremlin demonstrated an increased diagnostic value in patients with symptomatic cardiomyopathies and might thus improve early risk discrimination and patient management.