14 research outputs found
Epitranscriptomics in atherosclerosis : unraveling RNA modifications, editing and splicing and their implications in vascular disease
No full textAtherosclerosis remains a leading cause of morbidity and mortality worldwide, driven by complex molecular
mechanisms involving gene regulation and post-transcriptional processes. Emerging evidence highlights the
critical role of epitranscriptomics, the study of chemical modifications occurring on RNA molecules, in atherosclerosis
development. Epitranscriptomics provides a new layer of regulation in vascular health, influencing
cellular functions in endothelial cells, smooth muscle cells, and macrophages, thereby shedding light on the
pathogenesis of atherosclerosis and presenting new opportunities for novel therapeutic targets. This review
provides a comprehensive overview of the epitranscriptomic landscape, focusing on key RNA modifications such
as N6-methyladenosine (m6A), 5-methylcytosine (m5C), pseudouridine (Ψ), RNA editing mechanisms including
A-to-I and C-to-U editing and RNA isoforms. The functional implications of these modifications in RNA stability,
alternative splicing, and microRNA biology are discussed, with a focus on their roles in inflammatory signaling,
lipid metabolism, and vascular cell adaptation within atherosclerotic plaques. We also highlight how these
modifications influence the generation of RNA isoforms, potentially altering cellular phenotypes and contributing
to disease progression. Despite the promise of epitranscriptomics, significant challenges remain, including
the technical limitations in detecting RNA modifications in complex tissues and the need for deeper mechanistic
insights into their causal roles in atherosclerotic pathogenesis. Integrating epitranscriptomics with other omics
approaches, such as genomics, proteomics, and metabolomics, holds the potential to provide a more holistic
understanding of the disease.peer-reviewe
Multiomics tools for improved atherosclerotic cardiovascular disease management
No full textMultiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple ‘omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care
Multiomics tools for improved atherosclerotic cardiovascular disease management
No full textFunding Information: This article is based upon work from EU-AtheroNET COST Action CA21153 funded by European Cooperation in Science and Technology (COST). M.S. is supported by the Ministry of Education, Science and Technological Development , Republic of Serbia through Grant Agreement with University of Belgrade-Faculty of Pharmacy No: 451-03-9/2021-14/200161, European Union (HORIZON-MSCA-2021-SE-01-01 - MSCA Staff Exchanges 2021 CardioSCOPE 101086397, HORIZON-MSCA-2021-PF- MAACS 101064175). E.G. is supported by the Research Council of Norway co-founding of the European Union AtheroNET COST Action CA21153. F.T. is supported by a postdoctoral research grant by the Portuguese Foundation for Science and Technology (FCT) through Cardiovascular R&D Center (UnIC, UIDP/00051/2020). S.K. is supported by a Tel-Hai college fellowship and the Israel Innovation Authority. S.B.W. is supported by the MCST COVID-19 R&D Fund 2020 COV.RD.2020-11: TargetID, HORIZON-WIDERA-2022-TALENTS-01 Project 101086768 BioGeMT and HORIZON EIC 2022 PATHFINDER CHALLENGE CARDIOGENOMICS Project 101114924 TargetMI, the latter two being funded by the European Union . However, views and opinions expressed are those of the author only and do not necessarily reflect those of the European Union or of the granting authorities. Neither the European Union nor the granting authorities can be held responsible for them. Y.D. has received funding from the EU Horizon 2020 project COVIRNA (grant agreement # 101016072 ), the National Research Fund (grants # C14/BM/8225223 , C17/BM/11613033 and COVID-19/2020-1/14719577/miRCOVID ), the Ministry of Higher Education and Research, and the Heart Foundation-Daniel Wagner of Luxembourg. P.M. is supported by the European Union (AtheroNET COST Action CA21153; HORIZON-MSCA-2021-SE-01-01 - MSCA Staff Exchanges 2021 CardioSCOPE 101086397). Publisher Copyright: © 2023 The AuthorsMultiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple ‘omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care.Peer reviewe
Guidelines for mitochondrial RNA analysis
No full textMitochondria 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.Peer reviewe
Integration of epigenetic regulatory mechanisms in heart failure
No full textThe number of “omics” approaches is continuously growing. Among others, epigenetics has appeared as an attractive area of investigation by the cardiovascular research community, notably considering its association with disease development. Complex diseases such as cardiovascular diseases have to be tackled using methods integrating different omics levels, so called “multi-omics” approaches. These approaches combine and co-analyze different levels of disease regulation. In this review, we present and discuss the role of epigenetic mechanisms in regulating gene expression and provide an integrated view of how these mechanisms are interlinked and regulate the development of cardiac disease, with a particular attention to heart failure. We focus on DNA, histone, and RNA modifications, and discuss the current methods and tools used for data integration and analysis. Enhancing the knowledge of these regulatory mechanisms may lead to novel therapeutic approaches and biomarkers for precision healthcare and improved clinical outcomes
Progress toward Implementing Multiomic Approaches in Atherosclerotic Cardiovascular Disease: Update from the 4 th AtheroNET Meeting in Sarajevo (Bosnia and Herzegovina)
No full textThe COST Action CA21153 “Network for Implementing Multiomic Approaches in Atherosclerotic Cardiovascular Disease Prevention and Research” (AtheroNET; https://atheronet.eu) was launched in October 2022 with the mission to accelerate the application of multiomics in atherosclerosis research and to foster collaboration among experts from diverse disciplines. Born from the pressing need to advance atherosclerosis management and overcome existing challenges, AtheroNET creates a collaborative arena where innovation thrives through dialogue. The initiative was spearheaded by Prof. Miron Sopić (Faculty of Pharmacy, University of Belgrade), the primary proposer of the Action. The Action is led by Chair Prof. Paolo Magni (Università degli Studi di Milano) and Vice-Chair Prof. Yvan Devaux (Luxembourg Institute of Health), with strategic support from a dedicated leadership team:
• Grant Holder Scientific Representative: Dr. Ines Potočnjak
• Science Communication Coordinator: Prof. Georgios Kararigas
• Grant Awarding Coordinator: Dr. Susana Novella
• WG1 - Pathophysiological mechanisms: applying multiomics to uncover novel pathogenic players and processes; Leader: Prof. Dimitris Kardassis
• WG2 - Personalized clinical models: translating omics insights into improved management of ASCVD; Leader: Prof. Alberico Catapano
• WG3 - Standardization and harmonization: developing SOPs and guidelines to enhance reproducibility across omics research; Leader: Dr. Marie Mardal
• WG4 - Data integration and ML/AI: optimizing algorithms for integrating complex multiomic datasets; Leader: Dr. Aleksandra Gruca
• WG5 - Dissemination and communication: sharing advances with scientists, clinicians, patients, and the public; Leader: Prof. Georgios Kararigas
Since its inception, AtheroNET has grown to 475 members from across Europe, embracing COST’s core values of inclusiveness and excellence across geography, gender, and career stage. A significant proportion of members come from Inclusive Target Countries (n=282), with strong representation of women (n=277) and early-career researchers (n=223)
RNA modifications in peripheral blood are associated with acute coronary syndrome
No full textAcute coronary syndromes (ACS) trigger inflammatory and immune reactions, yet whether this response is associated with changes in RNA modifications remains poorly understood. We investigated global epitranscriptomic patterns in peripheral blood mononuclear cells (PBMC) from patients with ST-elevation myocardial infarction (STEMI, n = 118), non-ST-elevation myocardial infarction (NSTEMI, n = 22), unstable angina pectoris (UAP, n = 10), and stable angina pectoris (SAP, n = 152). Using liquid chromatography–mass spectrometry, we quantified N1-methyladenosine (m1A), 2′-O-methyladenosine (2′-O-mA), N6-methyladenosine (m6A), N6,2′-O-dimethyladenosine (m6Am), and pseudouridine (Ψ), together with their ratios to unmodified nucleotides. Levels of 2′-O-mA (P = 0.004), m6Am (P < 0.001), and Ψ (P = 0.021) were significantly decreased in STEMI compared with SAP. m6Am was also reduced in UAP (P = 0.037) and NSTEMI (P = 0.012), whereas m1A and m6A did not differ between groups. Among modification ratios, only the m6Am/A ratio declined across ACS subtypes (UAP P = 0.015; NSTEMI P = 0.032; STEMI P = 0.007), indicating relative cap-adjacent hypomethylation. Reduced m6Am correlated inversely with hsCRP (r = −0.19, P < 0.001) and hsTnI (r = −0.24, P < 0.001). In multivariable logistic regression adjusting for age, sex, BMI, and hsCRP, m6Am remained independently associated with STEMI (OR = 0.14, 95% CI 0.02–0.81; P = 0.028). These findings demonstrate selective RNA modification changes in ACS and identify m6Am as an independent epitranscriptomic marker associated with myocardial infarction
Call for participation in the AtheroNET COST Action to implement multiomics in atherosclerotic cardiovascular disease research
No full textMultiomics in atherosclerotic cardiovascular disease
No full textBackground and aims: Atherosclerotic cardiovascular disease (ASCVD) is among the leading causes of death worldwide, and technological advances have made it possible to expand the repertoire of biomarkers used in diagnostics and treatment of ASCVD. These include different omics (genomics, epigenomics, transcriptomics, proteomics, and metabolomics). We introduce the various layers of omic data and how they can be used in diagnostics and treatment of ASCVD. Further, we discuss future possibilities of combining multiomic data with machine learning (ML) and artificial intelligence (AI) to develop algorithms for facilitating precision medicine. Methods: we reviewed the current literature on omic data in ASCVD and its integration with ML/AI. Results: Genomics has been used to generate polygenic risk scores (PRS), which have shown promising results in risk prediction of ASCVD. Key epigenetic changes implicated in atherosclerosis include deoxyribonucleic acid (DNA) methylation. Transcriptomics has been used to identify transcripts, including micro ribonucleic acid (miRNAs), implicated in atherosclerosis progression. Proteomic risk scores have shown independent predictive information and outperformed clinical risk models, and within the metabolomics field, lipidomics has emerged as a promising predictive tool. The combination of multiomic data analysis with ML and AI methods has already demonstrated potential in the development of clinical models. Conclusions: A major effort is necessary to bring omic data and technologies to the clinical field. Further support will be offered by the generation of clinically applicable/approved AI/ML algorithms able to translate large datasets into valuable information for accurate precision medicine approaches
Transcriptomic research in atherosclerosis: Unravelling plaque phenotype and overcoming methodological challenges
No full textAtherosclerotic disease is a major cause of acute cardiovascular events. A deeper understanding of its underlying
mechanisms will allow advancing personalized and patient-centered healthcare. Transcriptomic research has
proven to be a powerful tool for unravelling the complex molecular pathways that drive atherosclerosis. However,
low reproducibility of research findings and lack of standardization of procedures pose significant challenges
in this field. In this review, we discuss how transcriptomic research can help in understanding the different
phenotypes of the atherosclerotic plaque that contribute to the development and progression of atherosclerosis.
We highlight the methodological challenges that need to be addressed to improve research outputs, and
emphasize the importance of research protocols harmonization. We also discuss recent advances in transcriptomic
research, including bulk or single-cell sequencing, and their added value in plaque phenotyping.
Finally, we explore how integrated multiomics data and machine learning improve understanding of atherosclerosis
and provide directions for future research
