Circulating miRNAs and Vascular Injury Markers Associate with Cardiovascular Function in Older Patients Reaching End-Stage Kidney Disease

The prevalence of end-stage kidney disease (ESKD) is rapidly increasing and mostly occurring in patients aged 65 years or older. The main cause of death in these patients is cardiovascular disease (CVD). Novel markers of vascular integrity may thus be of clinical value for identifying patients at high risk for CVD. Here we associated the levels of selected circulating angiogenic miRNAs, angiopoietin-2 (Ang-2) and asymmetric dimethylarginine (ADMA) with cardiovascular structure and function (as determined by cardiovascular MRI) in 67 older patients reaching ESKD that were included from ‘The Cognitive decline in Older Patients with End stage renal disease’ (COPE) prospective, multicentered cohort study. We first determined the association between the vascular injury markers and specific heart conditions and observed that ESKD patients with coronary heart disease have significantly higher levels of circulating ADMA and miR-27a. Moreover, circulating levels of miR-27a were higher in patients with atrial fibrillation. In addition, the circulating levels of the vascular injury markers were associated with measures of cardiovascular structure and function obtained from cardiovascular MRI: pulse wave velocity (PWV), ejection fraction (EF) and cardiac index (CI). We found Ang-2 and miR-27a to be strongly correlated to the PWV, while Ang-2 also associated with ejection fraction. Finally, we observed that in contrast to miR-27a, Ang-2 was not associated with a vascular cause of the primary kidney disease, suggesting Ang-2 may be an ESKD-specific marker of vascular injury. Taken together, among older patients with ESKD, aberrant levels of vascular injury markers (miR-27a, Ang-2 and ADMA) associated with impaired cardiovascular function. These markers may serve to identify individuals at higher risk of CVD, as well as give insight into the underlying (vascular) pathophysiology.

The role of artificial intelligence in paediatric cardiovascular magnetic resonance imaging

Artificial intelligence (AI) offers the potential to change many aspects of paediatric cardiac imaging. At present, there are only a few clinically validated examples of AI applications in this field. This review focuses on the use of AI in paediatric cardiovascular MRI, using examples from paediatric cardiovascular MRI, adult cardiovascular MRI and other radiologic experience.