Background: MicroRNAs (miRNAs) are small, single-stranded RNA sequences that regulate gene expression on a post-transcriptional level. In the last few decades, various trials have investigated the diagnostic and therapeutic potential of miRNAs in several disease entities. Here, we provide a review of the available evidence on miRNAs in inflammatory heart diseases (myocarditis, endocarditis, and pericarditis) and sepsis-induced cardiac dysfunction. Methods: Systematic database research using the PubMed and Medline databases was conducted between July and September 2019 using predefined search terms. The whole review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: In total, 131 studies were screened, 96 abstracts were read, and 69 studies were included in the review. Discussion: In the future, circulating miRNAs could serve as biomarkers for diagnosis and disease monitoring in the context of inflammatory heart diseases and sepsis-induced cardiac dysfunction. Considering the promising results of different animal models, certain miRNAs could also emerge as novel therapeutic approaches in this setting.

ST-elevation myocardial infarction (STEMI) is one of the main reasons for morbidity and mortality worldwide. In addition to the classic biomarker NT-proBNP, new biomarkers like ST2 and Pentraxin-3 (Ptx-3) have emerged as potential tools in stratifying risk in cardiac patients. Indeed, multimarker approaches to estimate prognosis of STEMI patients have been proposed and their potential clinical impact requires investigation. In our study, in 147 patients with STEMI, NT-proBNP as well as serum levels of ST2 and Ptx-3 were evaluated. During two-year follow-up (FU; 734.2 ± 61.2 d) results were correlated with risk for cardiovascular mortality (CV-mortality). NT-proBNP (HR = 1.64, 95% CI = 1.21–2.21, p = 0.001) but also ST2 (HR = 1.000022, 95% CI = 1.00–1.001, p < 0.001) were shown to be reliable predictors of CV-mortality, while the highest predictive power was observed with Ptx-3 (HR = 3.1, 95% CI = 1.63–5.39, p < 0.001). When two biomarkers were combined in a multivariate Cox regression model, relevant improvement of risk assessment was only observed with NT-proBNP+Ptx-3 (AIC = 209, BIC = 214, p = 0.001, MER = 0.75, MEV = 0.64). However, the highest accuracy was seen using a three-marker approach (NT-proBNP + ST2 + Ptx-3: AIC = 208, BIC = 214, p < 0.001, MER = 0.77, MEV = 0.66). In conclusion, after STEMI, ST2 and Ptx-3 in addition to NT-proBNP were associated with the incidence of CV-mortality, with multimarker approaches enhancing the accuracy of prediction of CV-mortality.