Multiomic biomarkers after cardiac arrest.

Cardiac arrest is a sudden cessation of heart function, leading to an abrupt loss of blood flow and oxygen to vital organs. This life-threatening emergency requires immediate medical intervention and can lead to severe neurological injury or death. Methods and biomarkers to predict neurological outcome are available but lack accuracy. Such methods would allow personalizing healthcare and help clinical decisions. Extensive research has been conducted to identify prognostic omic biomarkers of cardiac arrest. With the emergence of technologies allowing to combine different levels of omics data, and with the help of artificial intelligence and machine learning, there is a potential to use multiomic signatures as prognostic biomarkers after cardiac arrest. This review article delves into the current knowledge of cardiac arrest biomarkers across various omic fields and suggests directions for future research aiming to integrate multiple omics data layers to improve outcome prediction and cardiac arrest patient's care.

Guidelines for mitochondrial RNA analysis.

Mitochondria are the energy-producing organelles of mammalian cells with critical involvement in metabolism and signaling. Studying their regulation in pathological conditions may lead to the discovery of novel drugs to treat, for instance, cardiovascular or neurological diseases, which affect high-energy-consuming cells such as cardiomyocytes, hepatocytes, or neurons. Mitochondria possess both protein-coding and noncoding RNAs, such as microRNAs, long noncoding RNAs, circular RNAs, and piwi-interacting RNAs, encoded by the mitochondria or the nuclear genome. Mitochondrial RNAs are involved in anterograde-retrograde communication between the nucleus and mitochondria and play an important role in physiological and pathological conditions. Despite accumulating evidence on the presence and biogenesis of mitochondrial RNAs, their study continues to pose significant challenges. Currently, there are no standardized protocols and guidelines to conduct deep functional characterization and expression profiling of mitochondrial RNAs. To overcome major obstacles in this emerging field, the EU-CardioRNA and AtheroNET COST Action networks summarize currently available techniques and emphasize critical points that may constitute sources of variability and explain discrepancies between published results. Standardized methods and adherence to guidelines to quantify and study mitochondrial RNAs in normal and disease states will improve research outputs, their reproducibility, and translation potential to clinical application.

Machine learning for catalysing the integration of noncoding RNA in research and clinical practice.

The human transcriptome predominantly consists of noncoding RNAs (ncRNAs), transcripts that do not encode proteins. The noncoding transcriptome governs a multitude of pathophysiological processes, offering a rich source of next-generation biomarkers. Toward achieving a holistic view of disease, the integration of these transcripts with clinical records and additional data from omic technologies ("multiomic" strategies) has motivated the adoption of artificial intelligence (AI) approaches. Given their intricate biological complexity, machine learning (ML) techniques are becoming a key component of ncRNA-based research. This article presents an overview of the potential and challenges associated with employing AI/ML-driven approaches to identify clinically relevant ncRNA biomarkers and to decipher ncRNA-associated pathogenetic mechanisms. Methodological and conceptual constraints are discussed, along with an exploration of ethical considerations inherent to AI applications for healthcare and research. The ultimate goal is to provide a comprehensive examination of the multifaceted landscape of this innovative field and its clinical implications.

CD66b+/CD68+ circulating extracellular vesicles, lactate dehydrogenase and neutrophil-to-lymphocyte ratio can differentiate coronavirus disease 2019 severity during and after infection.

Coronavirus disease 2019 (COVID-19) has been a major public health burden. We hypothesised that circulating extracellular vesicles (cEVs), key players in health and disease, could trace the cell changes during COVID-19 infection and recovery. Therefore, we studied the temporal trend of cEV and inflammatory marker levels in plasma samples of COVID-19 patients that were collected within 24 h of patient admission (baseline, n = 80) and after hospital discharge at day-90 post-admission (n = 59). Inflammatory markers were measured by standard biochemical methods. cEVs were quantitatively and phenotypically characterized by high-sensitivity nano flow cytometry. In patients recovered from COVID-19 lower levels of inflammatory markers were detected. cEVs from vascular (endothelial cells) and blood (platelets, distinct immune subsets) cells were significantly reduced at day-90 compared to admission levels, a pattern also observed for cEVs from progenitor, perivascular and epithelial cells. The best discriminatory power for COVID-19 severity was found for inflammatory markers lactate dehydrogenase and neutrophil-to-lymphocyte ratio and for granulocyte/macrophage-released CD66b+/CD68+-cEVs. Albeit inflammatory markers were good indicators of systemic inflammatory response and discriminators of COVID-19 remission, they do not completely reveal cell stress and organ damage states. cEVs reaching baseline pre-infection levels at 90 days post-infection in recovered patients discriminate parental cells affected by disease.

Smartphone use and cerebro-cardio-vascular health: opportunity or public health threat?

Graphical AbstractImpact of smartphone (over)use on cerebro-cardio-vascular health.

Cardiovascular history and risk of idiopathic Parkinson's disease: a cross-sectional observational study.

BACKGROUND: Parkinson's disease (PD), while often associated with its distinctive motor symptoms, can also exert a notable impact on the cardiovascular system due to the development of severe autonomic dysfunction. One of the initial indicators of PD is the appearance of cardiovascular dysautonomia. As such, it is vital to monitor and manage cardiovascular health of individuals with PD, as it may have clinical implications in the development of commonly recognized motor and non-motor aspects of the disease. To study the association of history of cardiovascular disease (CVD) with occurrence and severity of PD, here, we lend data on the association of CVD history with the frequency and the occurrence of idiopathic PD (iPD) using data from the Luxembourg Parkinson's study (iPD n = 676 patients and non-PD n = 874 controls). RESULTS: We report that patients with a history of CVD are at high risk of developing iPD (odds ratio; OR = 1.56, 95% confidence interval; CI 1.09-2.08). This risk is stronger in males and remains significant after adjustment with confounders (OR 1.55, 95% CI 1.05-2.30). This increased susceptibility to iPD is linked to the severity of iPD symptoms mainly the non-motor symptoms of daily living (MDS-UPDRS I) and motor complications (MDS-UPDRS IV) in the affected individuals. CONCLUSION: Individuals with history of CVD have a high risk of developing severe forms of iPD. This observation suggests that careful monitoring and management of patients with a history of cardiac problems may reduce the burden of iPD.

Increased [18F]FDG uptake in the infarcted myocardial area displayed by combined PET/CMR correlates with snRNA-seq-detected inflammatory cell invasion.

Combined [18F]FDG PET-cardiac MRI imaging (PET/CMR) is a useful tool to assess myocardial viability and cardiac function in patients with acute myocardial infarction (AMI). Here, we evaluated the prognostic value of PET/CMR in a porcine closed-chest reperfused AMI (rAMI) model. Late gadolinium enhancement by PET/CMR imaging displayed tracer uptake defect at the infarction site by 3 days after the rAMI in the majority of the animals (group Match, n = 28). Increased [18F]FDG uptake at the infarcted area (metabolism/contractility mismatch) with reduced tracer uptake in the remote viable myocardium (group Mismatch, n = 12) 3 days after rAMI was observed in the animals with larger infarct size and worse left ventricular ejection fraction (LVEF) (34 ± 8.7 vs 42.0 ± 5.2%), with lower LVEF also at the 1-month follow-up (35.8 ± 9.5 vs 43.0 ± 6.3%). Transcriptome analyses by bulk and single-nuclei RNA sequencing of the infarcted myocardium and border zones (n = 3 of each group, and 3 sham-operated controls) revealed a strong inflammatory response with infiltration of monocytes and macrophages in the infarcted and border areas in Mismatch animals. Our data indicate a high prognostic relevance of combined PET/MRI in the subacute phase of rAMI for subsequent impairment of heart function and underline the adverse effects of an excessive activation of the innate immune system in the initial phase after rAMI.

Biomarkers of food intake and their relevance to metabolic syndrome.

Metabolic syndrome (MetS) constitutes a prevalent risk factor associated with non communicable diseases such as cardiovascular disease and type 2 diabetes. A major factor impacting the etiology of MetS is diet. Dietary patterns and several individual food constituents have been related to the risk of developing MetS or have been proposed as adjuvant treatment. However, traditional methods of dietary assessment such as 24 h recalls rely greatly on intensive user-interaction and are subject to bias. Hence, more objective methods are required for unbiased dietary assessment and efficient prevention. While it is accepted that some dietary-derived constituents in blood plasma are indicators for certain dietary patterns, these may be too unstable (such as vitamin C as a marker for fruits/vegetables) or too broad (e.g. polyphenols for plant-based diets) or reflect too short-term intake only to allow for strong associations with prolonged intake of individual food groups. In the present manuscript, commonly employed biomarkers of intake including those related to specific food items (e.g. genistein for soybean or astaxanthin and EPA for fish intake) and novel emerging ones (e.g. stable isotopes for meat intake or microRNA for plant foods) are emphasized and their suitability as biomarker for food intake discussed. Promising alternatives to plasma measures (e.g. ethyl glucuronide in hair for ethanol intake) are also emphasized. As many biomarkers (i.e. secondary plant metabolites) are not limited to dietary assessment but are also capable of regulating e.g. anti-inflammatory and antioxidant pathways, special attention will be given to biomarkers presenting a double function to assess both dietary patterns and MetS risk.

Circular RNA regulatory role in pathological cardiac remodelling.

Cardiac remodelling involves structural, cellular and molecular alterations in the heart after injury, resulting in progressive loss of heart function and ultimately leading to heart failure. Circular RNAs (circRNAs) are a recently rediscovered class of non-coding RNAs that play regulatory roles in the pathogenesis of cardiovascular diseases, including heart failure. Thus, a more comprehensive understanding of the role of circRNAs in the processes governing cardiac remodelling may set the ground for the development of circRNA-based diagnostic and therapeutic strategies. In this review, the current knowledge about circRNA origin, conservation, characteristics and function is summarized. Bioinformatics and wet-lab methods used in circRNA research are discussed. The regulatory function of circRNAs in cardiac remodelling mechanisms such as cell death, cardiomyocyte hypertrophy, inflammation, fibrosis and metabolism is highlighted. Finally, key challenges and opportunities in circRNA research are discussed, and orientations for future work to address the pharmacological potential of circRNAs in heart failure are proposed.

Navigating the path of reproducibility in microRNA-based biomarker research with ring trials.

The development of microRNA (miRNA)-based biomarkers has gained significant attention due to their potential diagnostic, prognostic and therapeutic applications. However, the reproducibility of miRNA biomarker research faces unique challenges, primarily due to the influence of pre-analytical and analytical factors. The absence of standardized procedures contributes to inconsistencies across studies, alongside challenges in reference gene selection, data analysis methods and miRNA profiling platforms. Inter-laboratory comparison trials, or ring trials, offer a strategic approach to address technical and biological variability in miRNA biomarker studies. These trials promote standardization, identify sources of variability and strengthen the correlation between miRNAs and clinical outcomes. Despite their underutilization in miRNA biomarker research, ring trials represent a valuable tool for enhancing reproducibility and expediting the translation of miRNA-based biomarkers into clinical applications.

Targeting noncoding RNAs to treat atherosclerosis.

Noncoding RNAs (ncRNAs) are pivotal for various pathological processes, impacting disease progression. The potential for leveraging ncRNAs to prevent or treat atherosclerosis and associated cardiovascular diseases is of great significance, especially given the increasing prevalence of atherosclerosis in an ageing and sedentary population. Together, these diseases impose a substantial socio-economic burden, demanding innovative therapeutic solutions. This review explores the potential of ncRNAs in atherosclerosis treatment. We commence by examining approaches for identifying and characterizing atherosclerosis-associated ncRNAs. We then delve into the functional aspects of ncRNAs in atherosclerosis development and progression. Additionally, we review current RNA and RNA-targeting molecules in development or under approval for clinical use, offering insights into their pharmacological potential. The importance of improved ncRNA delivery strategies is highlighted. Finally, we suggest avenues for advanced research to accelerate the use of ncRNAs in treating atherosclerosis and mitigating its societal impact.

Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality.

Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital mortality post-SARS-CoV-2 infection. Blood samples and clinical data from 1286 COVID-19 patients collected from 2020 to 2023 across four cohorts in Europe and Canada were analyzed, with 2906 long non-coding RNAs profiled using targeted sequencing. From a discovery cohort combining three European cohorts and 804 patients, age and the long non-coding RNA LEF1-AS1 were identified as predictive features, yielding an AUC of 0.83 (95% CI 0.82-0.84) and a balanced accuracy of 0.78 (95% CI 0.77-0.79) with a feedforward neural network classifier. Validation in an independent Canadian cohort of 482 patients showed consistent performance. Cox regression analysis indicated that higher levels of LEF1-AS1 correlated with reduced mortality risk (age-adjusted hazard ratio 0.54, 95% CI 0.40-0.74). Quantitative PCR validated LEF1-AS1's adaptability to be measured in hospital settings. Here, we demonstrate a promising predictive model for enhancing COVID-19 patient management.

Addressing the unsolved challenges in microRNA-based biomarker development: Suitable endogenous reference microRNAs for SARS-CoV-2 infection severity.

Circulating cell-free microRNAs (miRNAs) are promising biomarkers for medical decision-making. Suitable endogenous controls are essential to ensure reproducibility. We aimed to identify and validate endogenous reference miRNAs for qPCR data normalization in samples from SARS-CoV-2-infected hospitalized patients. We used plasma samples (n = 170) from COVID-19 patients collected at hospital admission (COVID-Ponent project, www.clinicaltrials.gov/NCT04824677). First, 179 miRNAs were profiled using RT-qPCR. After stability assessment, candidates were validated using the same methodology. miRNA stability was analyzed using the geNorm, NormFinder and BestKeeper algorithms. Stability was further evaluated using an RNA-seq dataset derived from COVID-19 hospitalized patients, along with plasma samples from patients with critical COVID-19 profiled using RT-qPCR. In the screening phase, after strict control of expression levels, stability assessment selected eleven candidates (miR-17-5p, miR-20a-5p, miR-30e-5p, miR-106a-5p, miR-151a-5p, miR-185-5p, miR-191-5p, miR-423-3p, miR-425-5p, miR-484 and miR-625-5p). In the validation phase, all algorithms identified miR-106a-5p and miR-484 as top endogenous controls. No association was observed between these miRNAs and clinical or sociodemographic characteristics. Both miRNAs were stably detected and showed low variability in the additional analyses. In conclusion, a 2-miRNA panel composed of miR-106a-5p and miR-484 constitutes a first-line normalizer for miRNA-based biomarker development using qPCR in hospitalized patients infected with SARS-CoV-2.

Non-coding RNAs as therapeutic targets and biomarkers in ischaemic heart disease.

The adult heart is a complex, multicellular organ that is subjected to a series of regulatory stimuli and circuits and has poor reparative potential. Despite progress in our understanding of disease mechanisms and in the quality of health care, ischaemic heart disease remains the leading cause of death globally, owing to adverse cardiac remodelling, leading to ischaemic cardiomyopathy and heart failure. Therapeutic targets are urgently required for the protection and repair of the ischaemic heart. Moreover, personalized clinical biomarkers are necessary for clinical diagnosis, medical management and to inform the individual response to treatment. Non-coding RNAs (ncRNAs) deeply influence cardiovascular functions and contribute to communication between cells in the cardiac microenvironment and between the heart and other organs. As such, ncRNAs are candidates for translation into clinical practice. However, ncRNA biology has not yet been completely deciphered, given that classes and modes of action have emerged only in the past 5 years. In this Review, we discuss the latest discoveries from basic research on ncRNAs and highlight both the clinical value and the challenges underscoring the translation of these molecules as biomarkers and therapeutic regulators of the processes contributing to the initiation, progression and potentially the prevention or resolution of ischaemic heart disease and heart failure.

Evolution of journal clubs: fostering collaborative learning in modern research.

Journal clubs have been a staple in scientific communities, facilitating discussions on recent publications. However, the overwhelming volume of biomedical information poses a challenge in literature selection. This article provides an overview of journal club types and their efficacy in training potential peer reviewers, enhancing communication skills, and critical thinking. Originating in the 19th century, journal clubs have evolved from traditional in-person meetings to virtual or hybrid formats, accelerated by the COVID-19 pandemic. Face-to-face interactions offer personal connections, while virtual events ensure wider participation and accessibility. Organizing journal clubs demands effort, but it has several benefits, including promoting new publications and providing a platform for meaningful discussions. The virtual CardioRNA J-club experience exemplifies successful multidisciplinary collaboration, fostering international connections and inspiring new research. Journal clubs remain a vital component of academic research, equipping senior researchers with the latest developments and nurturing the next generation of scientists. As millennial and Gen Z researchers join the scientific field, journal clubs continue to evolve as a fertile ground for education and collaborative learning in an ever-changing scientific landscape.

Multicomponent (bio)markers for obesity risk prediction: a scoping review protocol.

INTRODUCTION: Despite international efforts, the number of individuals struggling with obesity is still increasing. An important aspect of obesity prevention relates to identifying individuals at risk at early stage, allowing for timely risk stratification and initiation of countermeasures. However, obesity is complex and multifactorial by nature, and one isolated (bio)marker is unlikely to enable an optimal risk stratification and prognosis for the individual; rather, a combined set is required. Such a multicomponent interpretation would integrate biomarkers from various domains, such as classical markers (eg, anthropometrics, blood lipids), multiomics (eg, genetics, proteomics, metabolomics), lifestyle and behavioural attributes (eg, diet, physical activity, sleep patterns), psychological traits (mental health status such as depression) and additional host factors (eg, gut microbiota diversity), also by means of advanced interpretation tools such as machine learning. In this paper, we will present a protocol that will be employed for a scoping review that attempts to summarise and map the state-of-the-art in the area of multicomponent (bio)markers related to obesity, focusing on the usability and effectiveness of such biomarkers. METHODS AND ANALYSIS: PubMed, Scopus, CINAHL and Embase databases will be searched using predefined key terms to identify peer-reviewed articles published in English until January 2024. Once downloaded into EndNote for deduplication, CADIMA will be employed to review and select abstracts and full-text articles in a two-step procedure, by two independent reviewers. Data extraction will then be carried out by several independent reviewers. Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews and Peer Review of Electronic Search Strategies guidelines will be followed. Combinations employing at least two biomarkers from different domains will be mapped and discussed. ETHICS AND DISSEMINATION: Ethical approval is not required; data will rely on published articles. Findings will be published open access in an international peer-reviewed journal. This review will allow guiding future directions for research and public health strategies on obesity prevention, paving the way towards multicomponent interventions.

miR-619-5p and cardiogenic shock in patients with ST-segment elevation myocardial infarction.

BACKGROUND: Cardiogenic shock (CS) is a severe myocardial dysfunction secondary to various cardiac conditions including ST-segment elevation acute myocardial infarction (STEMI) and associated with a high risk of death. Little is known on epigenetic determinants in CS. Here, we investigated plasma miRNAs in relation to CS stratification in STEMI-patients. METHODS: STEMI-patients (n = 49), with (CS, n = 25) and without CS (non-CS, n = 24) fulfilling inclusion criteria were included from HSCSP-cohort (Derivation-cohort). CS-miRNAs were analysed by Affymetrix-microarray and RT-PCR. Results were validated in a second cohort of CS-patients (CardShock: n = 35) with similar inclusion/exclusion criteria as the derivation cohort. In silico analysis were performed to identify potential miRNA target genes. RESULTS: Of the 5-miRNA signature obtained from microarray analysis, miR-619-5p showed higher levels in CS than in Non-CS patients (p = .003) and discriminating power for CS by ROC (AUC: .752, p = .003). miR-619-5p directly associated with risk scores [GRACE, p = .001; CardShock, p < .001]. Furthermore, miR-619-5p showed discrimination power for death in CS. Thus, miRNA levels were significantly higher in patients with mortality outcome both in the Derivation HSCSP-cohort (p = .02; AUC: .78 ± .095) and the Validation CardShock-cohort (p = .017; AUC: .737 ± .086) By in silico analysis, miR-619-5p target genes and TNF-alpha were involved in the regulation of inflammation. miR-619-5p and TNF-alpha levels discriminated mortality outcome in CS-patients during 30-day follow-up (Validation-Cohort: ROC: .812, p = .002; HR: 9.99, p = .003). CONCLUSIONS: Up-regulation of miR-619-5p is found in the plasma of STEMI-patients with CS and mortality outcome. These findings highlight the specificity of epigenetic regulation of inflammation on the disease severity of MI.

Recommendations for detection, validation, and evaluation of RNA editing events in cardiovascular and neurological/neurodegenerative diseases.

RNA editing, a common and potentially highly functional form of RNA modification, encompasses two different RNA modifications, namely adenosine to inosine (A-to-I) and cytidine to uridine (C-to-U) editing. As inosines are interpreted as guanosines by the cellular machinery, both A-to-I and C-to-U editing change the nucleotide sequence of the RNA. Editing events in coding sequences have the potential to change the amino acid sequence of proteins, whereas editing events in noncoding RNAs can, for example, affect microRNA target binding. With advancing RNA sequencing technology, more RNA editing events are being discovered, studied, and reported. However, RNA editing events are still often overlooked or discarded as sequence read quality defects. With this position paper, we aim to provide guidelines and recommendations for the detection, validation, and follow-up experiments to study RNA editing, taking examples from the fields of cardiovascular and brain disease. We discuss all steps, from sample collection, storage, and preparation, to different strategies for RNA sequencing and editing-sensitive data analysis strategies, to validation and follow-up experiments, as well as potential pitfalls and gaps in the available technologies. This paper may be used as an experimental guideline for RNA editing studies in any disease context.