Significance: To maintain homeostasis, gene expression has to be tightly regulated by complex and multiple mechanisms occurring at the epigenetic, transcriptional, and post-transcriptional levels. One crucial regulatory component is represented by long noncoding RNAs (lncRNAs), nonprotein-coding RNA species implicated in all of these levels. Thus, lncRNAs have been associated with any given process or pathway of interest in a variety of systems, including the heart. Recent Advances: Mounting evidence implicates lncRNAs in cardiovascular diseases (CVD) and progression and their presence in the blood of heart disease patients indicates that they are attractive potential biomarkers. Critical Issues: Our understanding of the regulation and molecular mechanisms of action of most lncRNAs remains rudimentary. A challenge is represented by their often low evolutionary sequence conservation that limits the use of animal models for preclinical studies. Nevertheless, a growing number of lncRNAs with an impact on heart function is rapidly accumulating. In this study, we will discuss (i) lncRNAs that control heart homeostasis and disease; (ii) concepts, approaches, and methodologies necessary to study lncRNAs in the heart; and (iii) challenges posed and opportunities presented by lncRNAs as potential therapeutic targets and biomarkers. Future Directions: A deeper knowledge of the molecular mechanisms underpinning CVDs is necessary to develop more effective treatments. Further studies are needed to clarify the regulation and function of lncRNAs in the heart before they can be considered as therapeutic targets and disease biomarkers. Antioxid. Redox Signal. 29, 880–901.

Parkinson’s disease (PD) is a complex and heterogeneous disorder involving multiple genetic and environmental influences. Although a wide range of PD risk factors and clinical markers for the symptomatic motor stage of the disease have been identified, there are still no reliable biomarkers available for the early pre-motor phase of PD and for predicting disease progression. High-throughput RNA-based biomarker profiling and modeling may provide a means to exploit the joint information content from a multitude of markers to derive diagnostic and prognostic signatures. In the field of PD biomarker research, currently, no clinically validated RNA-based biomarker models are available, but previous studies reported several significantly disease-associated changes in RNA abundances and activities in multiple human tissues and body fluids. Here, we review the current knowledge of the regulation and function of non-coding RNAs in PD, focusing on microRNAs, long non-coding RNAs, and circular RNAs. Since there is growing evidence for functional interactions between the heart and the brain, we discuss the benefits of studying the role of non-coding RNAs in organ interactions when deciphering the complex regulatory networks involved in PD progression. We finally review important concepts of harmonization and curation of high throughput datasets, and we discuss the potential of systems biomedicine to derive and evaluate RNA biomarker signatures from high-throughput expression data.

Cardiovascular disease (CVD) is the biggest cause of sickness and mortality worldwide in both males and females. Clinical statistics demonstrate clear sex differences in risk, prevalence, mortality rates, and response to treatment for different entities of CVD. The reason for this remains poorly understood. Non-coding RNAs (ncRNAs) are emerging as key mediators and biomarkers of CVD. Similarly, current knowledge on differential regulation, expression, and pathology-associated function of ncRNAs between sexes is minimal. Here, we provide a state-of-the-art overview of what is known on sex differences in ncRNA research in CVD as well as discussing the contributing biological factors to this sex dimorphism including genetic and epigenetic factors and sex hormone regulation of transcription. We then focus on the experimental models of CVD and their use in translational ncRNA research in the cardiovascular field. In particular, we want to highlight the importance of considering sex of the cellular and pre-clinical models in clinical studies in ncRNA research and to carefully consider the appropriate experimental models most applicable to human patient populations. Moreover, we aim to identify sex-specific targets for treatment and diagnosis for the biggest socioeconomic health problem globally.

Outcome prognostication after cardiac arrest (CA) is challenging. Current multimodal prediction approaches would benefit from new biomarkers. MicroRNAs constitute a novel class of disease markers and circulating levels of brain-enriched ones have been associated with outcome after CA. To determine whether these levels reflect the extent of brain damage in CA patients, we assessed their correlation with neuron-specific enolase (NSE), a marker of brain damage. Blood samples taken 48 h after return of spontaneous circulation from two groups of patients from the Targeted Temperature Management trial were used. Patients were grouped depending on their neurological outcome at six months. Circulating levels of microRNAs were assessed by sequencing. NSE was measured at the same time-point. Among the 673 microRNAs detected, brain-enriched miR9-3p, miR124-3p and miR129-5p positively correlated with NSE levels (all p < 0.001). Interestingly, these correlations were absent when only the good outcome group was analyzed (p > 0.5). Moreover, these correlations were unaffected by demographic and clinical characteristics. All three microRNAs predicted neurological outcome at 6 months. Circulating levels of brain-enriched microRNAs are correlated with NSE levels and hence can reflect the extent of brain injury in patients after CA. This observation strengthens the potential of brain-enriched microRNAs to aid in outcome prognostication after CA.

Cardiovascular disease in general, and sudden cardiac death in particular, have an enormous socio-economic burden worldwide. Despite significant efforts to improve cardiopulmonary resuscitation, survival rates remain low. Moreover, patients who survive to hospital discharge have a high risk of developing severe physical or neurological symptoms. Being able to predict outcomes after resuscitation from cardiac arrest would make it possible to tailor healthcare approaches, thereby maximising efforts for those who would mostly benefit from aggressive therapy. However, the identification of patients at risk of poor recovery after cardiac arrest is still a challenging task which could be facilitated by novel biomarkers. Recent investigations have recognised the potential of non-coding RNAs to aid in outcome prediction after cardiac arrest. In this review, we summarize recent discoveries and propose a handful of novel perspectives for the use of non-coding RNAs to predict outcome after cardiac arrest, discussing their use for precision medicine.