MicroRNAs (miRNAs) are small, non-coding, RNA molecules approximately 22 nucleotides in length which act as post-transcriptional regulators of gene expression. Individual miRNAs have been shown to regulate the expression of multiple genes. Conversely, the expression of individual genes can be regulated by multiple miRNAs. Consequently, since their discovery just over 20 years ago, miRNAs have been identified as key regulators of complex biological processes linked to multiple cardiovascular pathologies, including left ventricular hypertrophy, ischaemic heart disease, heart failure, hypertension and arrhythmias. Furthermore, since the finding that miRNAs are present in the circulation, they have been investigated as novel biomarkers, especially in the context of acute myocardial infarction (AMI) and heart failure. While there is little convincing evidence that miRNAs can outperform traditional biomarkers, such as cardiac troponins, in the diagnosis of AMI, there is potential for miRNAs to complement existing risk prediction models and act as valuable markers of post-AMI prognosis. Encouragingly, the concept of miRNA-based therapeutics is developing, with synthetic antagonists of miRNAs (antagomiRs) currently in phase II trials for the treatment of chronic hepatitis C virus infection. In the cardiovascular field, promising preclinical studies suggest that they could be useful in treating disorders ranging from heart failure to dyslipidaemia, although several challenges related to specificity and targeted delivery remain to be overcome. Through this review, we provide clinicians with a brief overview of the ever-expanding world of miRNAs.

Rationale Abdominal aortic aneurysm (AAA) is a complex disease with both genetic and environmental risk factors. Together, 6 previously identified risk loci only explain a small proportion of the heritability of AAA. Objective To identify additional AAA risk loci using data from all available genome-wide association studies (GWAS). Methods and Results Through a meta-analysis of 6 GWAS datasets and a validation study totalling 10,204 cases and 107,766 controls we identified 4 new AAA risk loci: 1q32.3 (SMYD2), 13q12.11 (LINC00540), 20q13.12 (near PCIF1/MMP9/ZNF335), and 21q22.2 (ERG). In various database searches we observed no new associations between the lead AAA SNPs and coronary artery disease, blood pressure, lipids or diabetes. Network analyses identified ERG, IL6R and LDLR as modifiers of MMP9, with a direct interaction between ERG and MMP9. Conclusions The 4 new risk loci for AAA appear to be specific for AAA compared with other cardiovascular diseases and related traits suggesting that traditional cardiovascular risk factor management may only have limited value in preventing the progression of aneurysmal disease.

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.

Background Secretion of adrenomedullin (ADM) is stimulated by volume overload to maintain endothelial barrier function, and higher levels of biologically active (bio‐) ADM in heart failure (HF) are a counteracting response to vascular leakage and tissue oedema. This study aimed to establish the value of plasma bio‐ADM as a marker of congestion in patients with worsening HF. Methods and results The association of plasma bio‐ADM with clinical markers of congestion, as well as its prognostic value was studied in 2179 patients with new‐onset or worsening HF enrolled in BIOSTAT‐CHF. Data were validated in a separate cohort of 1703 patients. Patients with higher plasma bio‐ADM levels were older, had more severe HF and more signs and symptoms of congestion (all P < 0.001). Amongst 20 biomarkers, bio‐ADM was the strongest predictor of a clinical congestion score (r2 = 0.198). In multivariable regression analysis, higher bio‐ADM was associated with higher body mass index, more oedema, and higher fibroblast growth factor 23. In hierarchical cluster analysis, bio‐ADM clustered with oedema, orthopnoea, rales, hepatomegaly and jugular venous pressure. Higher bio‐ADM was independently associated with impaired up‐titration of angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers after 3 months, but not of beta‐blockers. Higher bio‐ADM levels were independently associated with an increased risk of all‐cause mortality and HF hospitalization (hazard ratio 1.16, 95% confidence interval 1.06–1.27, P = 0.002, per log increase). Analyses in the validation cohort yielded comparable findings. Conclusions Plasma bio‐ADM in patients with new‐onset and worsening HF is associated with more severe HF and more oedema, orthopnoea, hepatomegaly and jugular venous pressure. We therefore postulate bio‐ADM as a congestion marker, which might become useful to guide decongestive therapy.