Abstract Background Cardiomyopathies are the main cause of progressive heart failure (HF) and despite outstanding advances of diagnostics and therapies, mortality remains high.1,2 The current phenotype-based classification of non-ischemic cardiomyopathies (NICM) is based on a clinical workflow including endomyocardial biopsy (EMB).3-5 Inflammation and fibrosis are essentially involved in progression of HF and lead to development of adverse cardiovascular (CV) events.6,7 The diagnostic algorithm facilitates risk stratification of HF patients but nonetheless risk factors often remain inapparent prior to disease incidence. Objective In this study we investigate EMB patters in patients with NICM and elucidate alterations associated with phenotypic diversity and progression of HF. Methods We prospectively enrolled patients with HF due to NICM in a large-scale all-comers cohort (n=703). All patients underwent guideline-based phenotypic classification including EMB, and RNA data were acquired alongside histological analyses within the myocardium. We then performed a ten-year follow-up to screen for disease progression. Results A guideline-based classification of patients with NICM resulted in a phenotyping of aetiological risk groups (Figure 1A). We found that characteristic expression of fibroinflammatory mediators within the myocardium occurred in patients with symptomatic NICM (Figure 1B). We found that elevated expression of Gremlin-1 (Grem), a potent downstream profibrotic mediator of TGFß pathway, was associated with pro-fibrotic cardiac remodelling (Figure 1C). Further, Gremlin-1 was associated with a significant decrease of left ventricular functional capacity and inversely correlated with late gadolinium enhancement (LGE) (Figure 1D&E). Moreover, the expression of Gremlin-1 was enriched with pro-fibrotic and inflammatory RNA signalling pathways hinting at underlying pathophysiological cascades (Figure 2A&B). Most strikingly, the expression of Gremlin-1 was independently associated with an increased CV risk during the ten-year follow-up (Figure 2C). Thus, patients with Gremlin-1+ EMB were at elevated risk to suffer from all-cause mortality and number of patients eligible for ICD implantation was critically enhanced in patients with Gremlin-1+ EMB (Figure 2D-F). In addition, the estimation of an elevated CV risk by machine learning including Gremlin-1 improved the ten-year risk stratification among all patients with NICM (Figure 2G). Thus, Gremlin-1 was associated with cardiac remodelling and disease activity in HF patients (Figure 2H). Conclusion Our results unveiled that Gremlin-1 is associated with inflammation and cardiac remodelling in patients with symptomatic cardiomyopathy and patients with Gremlin-1+ EMB are at elevated risk to develop adverse CV events. Thus, the histological evaluation of Gremlin-1 may help to identify pathophysiological cascades and improve early risk discrimination and management of HF patients.Figure 1Figure 2
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