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

Author

Lukovic, Dominika, Gyöngyösi, Mariann, Pavo, Imre J., Mester-Tonczar, Julia, Einzinger, Patrick, Zlabinger, Katrin, Kastner, Nina, Spannbauer, Andreas, Traxler, Denise, Pavo, Noemi, Goliasch, Georg, Pils, Dietmar, Jakab, Andras, Szankai, Zsuzsanna, Michel-Behnke, Ina, Zhang, Lu, Devaux, Yvan, Graf, Senta, Beitzke, Dietrich, and Winkler, Johannes

Published
2024
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4. Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality

Author

Devaux, Yvan, Zhang, Lu, Lumley, Andrew I., Karaduzovic-Hadziabdic, Kanita, Mooser, Vincent, Rousseau, Simon, Shoaib, Muhammad, Satagopam, Venkata, Adilovic, Muhamed, Srivastava, Prashant Kumar, Emanueli, Costanza, Martelli, Fabio, Greco, Simona, Badimon, Lina, Padro, Teresa, Lustrek, Mitja, Scholz, Markus, Rosolowski, Maciej, Jordan, Marko, Brandenburger, Timo, Benczik, Bettina, Agg, Bence, Ferdinandy, Peter, Vehreschild, Jörg Janne, Lorenz-Depiereux, Bettina, Dörr, Marcus, Witzke, Oliver, Sanchez, Gabriel, Kul, Seval, Baker, Andy H., Fagherazzi, Guy, Ollert, Markus, Wereski, Ryan, Mills, Nicholas L., and Firat, Hüseyin

Published
2024
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5. The challenges of research data management in cardiovascular science: a DGK and DZHK position paper—executive summary

Author

Steffens, Sabine, Schröder, Katrin, Krüger, Martina, Maack, Christoph, Streckfuss-Bömeke, Katrin, Backs, Johannes, Backofen, Rolf, Baeßler, Bettina, Devaux, Yvan, Gilsbach, Ralf, Heijman, Jordi, Knaus, Jochen, Kramann, Rafael, Linz, Dominik, Lister, Allyson L., Maatz, Henrike, Maegdefessel, Lars, Mayr, Manuel, Meder, Benjamin, Nussbeck, Sara Y., Rog-Zielinska, Eva A., Schulz, Marcel H., Sickmann, Albert, Yigit, Gökhan, and Kohl, Peter

Published
2024
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6. Guidelines for mitochondrial RNA analysis

Author

Jusic, Amela, Erpapazoglou, Zoi, Dalgaard, Louise Torp, Lakkisto, Päivi, de Gonzalo-Calvo, David, Benczik, Bettina, Ágg, Bence, Ferdinandy, Péter, Fiedorowicz, Katarzyna, Schroen, Blanche, Lazou, Antigone, and Devaux, Yvan

Published
2024
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8. Addressing the unsolved challenges in microRNA-based biomarker development: Suitable endogenous reference microRNAs for SARS-CoV-2 infection severity

Author

Belmonte, Thalia, Perez-Pons, Manel, Benítez, Iván D., Molinero, Marta, García-Hidalgo, María C., Rodríguez-Muñoz, Carlos, Gort-Paniello, Clara, Moncusí-Moix, Anna, Madè, Alisia, Devaux, Yvan, Martelli, Fabio, Ortega, Alicia, González, Jessica, Torres, Gerard, Barbé, Ferran, and de Gonzalo-Calvo, David

Published
2024
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9. HCG18, LEF1AS1 and lncCEACAM21 as biomarkers of disease severity in the peripheral blood mononuclear cells of COVID-19 patients

Author

Greco, Simona, Made’, Alisia, Mutoli, Martina, Zhang, Lu, Piella, Santiago Nicolas, Vausort, Mélanie, Lumley, Andrew I., Beltrami, Antonio Paolo, Srivastava, Prashant Kumar, Milani, Valentina, Boveri, Sara, Ranucci, Marco, Renna, Laura Valentina, Firat, Hüseyin, Bruno, Antonino, Spinetti, Gaia, Emanueli, Costanza, Devaux, Yvan, and Martelli, Fabio

Published
2023
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16. The circadian clock remains intact, but with dampened hormonal output in heart failure

Author

Crnko, Sandra, Printezi, Markella I., Zwetsloot, Peter-Paul M., Leiteris, Laurynas, Lumley, Andrew I., Zhang, Lu, Ernens, Isabelle, Jansen, Tijn P.J., Homsma, Lilian, Feyen, Dries, van Faassen, Martijn, du Pré, Bastiaan C., Gaillard, Carlo A.J.M., Kemperman, Hans, Oerlemans, Marish I.F.J., Doevendans, Pieter A.F.M., May, Anne M., Zuithoff, Nicolaas P.A., Sluijter, Joost P.G., Devaux, Yvan, and van Laake, Linda W.

Published
2023
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23. Navigating the path of reproducibility in microRNA-based biomarker research with ring trials.

Author

Sopić, Miron, Devaux, Yvan, and de Gonzalo-Calvo, David

Subjects
*BIOMARKERS, *MICRORNA, *CLINICAL medicine, *DATA analysis, *TREATMENT effectiveness
Abstract

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. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Increased [18F]FDG uptake in the infarcted myocardial area displayed by combined PET/CMR correlates with snRNA-seq-detected inflammatory cell invasion.

Author

Lukovic, Dominika, Gyöngyösi, Mariann, Pavo, Imre J., Mester-Tonczar, Julia, Einzinger, Patrick, Zlabinger, Katrin, Kastner, Nina, Spannbauer, Andreas, Traxler, Denise, Pavo, Noemi, Goliasch, Georg, Pils, Dietmar, Jakab, Andras, Szankai, Zsuzsanna, Michel-Behnke, Ina, Zhang, Lu, Devaux, Yvan, Graf, Senta, Beitzke, Dietrich, and Winkler, Johannes

Abstract

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. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Multicomponent (bio)markers for obesity risk prediction: a scoping review protocol

Author

Vahid, Farhad, primary, Dessenne, Coralie, additional, Tur, Josep A, additional, Bouzas, Cristina, additional, Devaux, Yvan, additional, Malisoux, Laurent, additional, Monserrat-Mesquida, Margalida, additional, Sureda, Antoni, additional, Desai, Mahesh S, additional, Turner, Jonathan D, additional, Lamy, Elsa, additional, Perez-Jimenez, Maria, additional, Ravn-Haren, Gitte, additional, Andersen, Rikke, additional, Forberger, Sarah, additional, Nagrani, Rajini, additional, Ouzzahra, Yacine, additional, Fontefrancesco, Michele Filippo, additional, Onorati, Maria Giovanna, additional, Bonetti, Gino Gabriel, additional, de-Magistris, Tiziana, additional, and Bohn, Torsten, additional

Published
2024
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30. Joining European Scientific Forces to Face Pandemics

Author

Vasconcelos, M. Helena, Alcaro, Stefano, Arechavala-Gomeza, Virginia, Baumbach, Jan, Borges, Fernanda, Brevini, Tiziana A.L., Rivas, Javier De Las, Devaux, Yvan, Hozak, Pavel, Keinänen-Toivola, Minna M., Lattanzi, Giovanna, Mohr, Thomas, Murovska, Modra, Prusty, Bhupesh K., Quinlan, Roy A., Pérez-Sala, Dolores, Scheibenbogen, Carmen, Schmidt, Harald H.H.W., Silveira, Isabel, Tieri, Paolo, Tolios, Alexander, and Riganti, Chiara

Published
2021
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31. The challenges of research data management in cardiovascular science:a DGK and DZHK position paper—executive summary

Author

Steffens, Sabine, Schröder, Katrin, Krüger, Martina, Maack, Christoph, Streckfuss-Bömeke, Katrin, Backs, Johannes, Backofen, Rolf, Baeßler, Bettina, Devaux, Yvan, Gilsbach, Ralf, Heijman, Jordi, Knaus, Jochen, Kramann, Rafael, Linz, Dominik, Lister, Allyson L., Maatz, Henrike, Maegdefessel, Lars, Mayr, Manuel, Meder, Benjamin, Nussbeck, Sara Y., Rog-Zielinska, Eva A., Schulz, Marcel H., Sickmann, Albert, Yigit, Gökhan, Kohl, Peter, Steffens, Sabine, Schröder, Katrin, Krüger, Martina, Maack, Christoph, Streckfuss-Bömeke, Katrin, Backs, Johannes, Backofen, Rolf, Baeßler, Bettina, Devaux, Yvan, Gilsbach, Ralf, Heijman, Jordi, Knaus, Jochen, Kramann, Rafael, Linz, Dominik, Lister, Allyson L., Maatz, Henrike, Maegdefessel, Lars, Mayr, Manuel, Meder, Benjamin, Nussbeck, Sara Y., Rog-Zielinska, Eva A., Schulz, Marcel H., Sickmann, Albert, Yigit, Gökhan, and Kohl, Peter

Abstract

The sharing and documentation of cardiovascular research data are essential for efficient use and reuse of data, thereby aiding scientific transparency, accelerating the progress of cardiovascular research and healthcare, and contributing to the reproducibility of research results. However, challenges remain. This position paper, written on behalf of and approved by the German Cardiac Society and German Centre for Cardiovascular Research, summarizes our current understanding of the challenges in cardiovascular research data management (RDM). These challenges include lack of time, awareness, incentives, and funding for implementing effective RDM; lack of standardization in RDM processes; a need to better identify meaningful and actionable data among the increasing volume and complexity of data being acquired; and a lack of understanding of the legal aspects of data sharing. While several tools exist to increase the degree to which data are findable, accessible, interoperable, and reusable (FAIR), more work is needed to lower the threshold for effective RDM not just in cardiovascular research but in all biomedical research, with data sharing and reuse being factored in at every stage of the scientific process. A culture of open science with FAIR research data should be fostered through education and training of early-career and established research professionals. Ultimately, FAIR RDM requires permanent, long-term effort at all levels. If outcomes can be shown to be superior and to promote better (and better value) science, modern RDM will make a positive difference to cardiovascular science and practice. The full position paper is available in the supplementary materials.

Published
2024

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

Author

Vahid, Farhad, Dessenne, Coralie, Tur, Josep A., Bouzas, Cristina, Devaux, Yvan, Malisoux, Laurent, Monserrat-Mesquida, Margalida, Sureda, Antoni, Desai, Mahesh S., Turner, Jonathan D., Lamy, Elsa, Perez-Jimenez, Maria, Ravn-Haren, Gitte, Andersen, Rikke, Forberger, Sarah, Nagrani, Rajini, Ouzzahra, Yacine, Fontefrancesco, Michele Filippo, Onorati, Maria Giovanna, Bonetti, Gino Gabriel, de-Magistris, Tiziana, Bohn, Torsten, Vahid, Farhad, Dessenne, Coralie, Tur, Josep A., Bouzas, Cristina, Devaux, Yvan, Malisoux, Laurent, Monserrat-Mesquida, Margalida, Sureda, Antoni, Desai, Mahesh S., Turner, Jonathan D., Lamy, Elsa, Perez-Jimenez, Maria, Ravn-Haren, Gitte, Andersen, Rikke, Forberger, Sarah, Nagrani, Rajini, Ouzzahra, Yacine, Fontefrancesco, Michele Filippo, Onorati, Maria Giovanna, Bonetti, Gino Gabriel, de-Magistris, Tiziana, and Bohn, Torsten

Abstract

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. Eth

Published
2024

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

Author

Escate, Rafael, Padró, Teresa, Suades, Rosa, Sans‐Roselló, Jordi, Devaux, Yvan, Lakkisto, Päivi, Harjola, Veli‐Pekka, Sionis, Alessandro, and Badimon, Lina

Subjects
ST elevation myocardial infarction, CARDIOGENIC shock, DISEASE risk factors
Abstract

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. [ABSTRACT FROM AUTHOR]

Published
2024
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35. CD66b+/CD68+ circulating extracellular vesicles, lactate dehydrogenase and neutrophil‐to‐lymphocyte ratio can differentiate coronavirus disease 2019 severity during and after infection.

Author

Suades, Rosa, Greco, Maria Francesca, Prieto, Paula, Padró, Teresa, Devaux, Yvan, Domingo, Pere, and Badimon, Lina

Subjects
COVID-19, EXTRACELLULAR vesicles, NEUTROPHIL lymphocyte ratio, SARS-CoV-2, COVID-19 pandemic
Abstract

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. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Preface

Author

Devaux, Yvan, primary and Robinson, Emma Louise, additional

Published
2021
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45. Contributors

Author

Ágg, Bence, primary, Aghagolzadeh, Parisa, additional, Anene-Nzelu, Chukwuemeka George, additional, Backs, Johannes, additional, Barbé, Ferran, additional, Betsou, Fay, additional, Bezzina Wettinger, Stephanie, additional, Codreanu, Andrei, additional, Devaux, Yvan, additional, Dieterich, Christoph, additional, Durán, Javier, additional, Farrugia, Rosienne, additional, Felekkis, Kyriacos, additional, Ferdinandy, Péter, additional, Foo, Roger S-Y, additional, Galatou, Eleftheria, additional, de Gonzalo-Calvo, David, additional, Greco, Simona, additional, Grillari, Johannes, additional, Gunes, Hakan, additional, Hackl, Matthias, additional, Hamdani, Nazha, additional, Hein, Lutz, additional, Hermenegildo, Carlos, additional, Iglesias-Gutiérrez, Eduardo, additional, Izzi, Benedetta, additional, Jaquet, Kornelia, additional, Jusic, Amela, additional, Karađuzović-Hadžiabdić, Kanita, additional, Kuster, Gabriela M., additional, Madè, Alisia, additional, De Majo, Federica, additional, Martelli, Fabio, additional, Mügge, Andreas, additional, Ngo, Vivien, additional, Novella, Susana, additional, Paes, Ana Belén, additional, Papaneophytou, Christos, additional, Pedrazzini, Thierry, additional, Peters, Antje, additional, Pinilla, Lucía, additional, Robinson, Emma Louise, additional, Semmelrock, Elisabeth, additional, Stenzig, Justus, additional, Vanhaverbeke, Maarten, additional, Völkers, Mirko, additional, De Windt, Leon J., additional, Winkler, Johannes, additional, Xuereb Anastasi, Angela, additional, and Yilmaz, Mehmet Birhan, additional

Published
2021
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46. Development of a long noncoding RNAbased machine learning model to predict COVID-19 in-hospital mortality.

Author

Devaux, Yvan, Lu Zhang, Lumley, Andrew I., Karaduzovic-Hadziabdic, Kanita, Mooser, Vincent, Rousseau, Simon, Shoaib, Muhammad, Satagopam, Venkata, Adilovic, Muhamed, Srivastava, Prashant Kumar, Emanueli, Costanza, Martelli, Fabio, Greco, Simona, Badimon, Lina, Padro, Teresa, Lustrek, Mitja, Scholz, Markus, Rosolowski, Maciej, Jordan, Marko, and Brandenburger, Timo

Abstract

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. [ABSTRACT FROM AUTHOR]

Published
2024
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48. The challenges of research data management in cardiovascular science: a DGK and DZHK position paper—executive summary

Author

Steffens, Sabine, primary, Schröder, Katrin, additional, Krüger, Martina, additional, Maack, Christoph, additional, Streckfuss-Bömeke, Katrin, additional, Backs, Johannes, additional, Backofen, Rolf, additional, Baeßler, Bettina, additional, Devaux, Yvan, additional, Gilsbach, Ralf, additional, Heijman, Jordi, additional, Knaus, Jochen, additional, Kramann, Rafael, additional, Linz, Dominik, additional, Lister, Allyson L., additional, Maatz, Henrike, additional, Maegdefessel, Lars, additional, Mayr, Manuel, additional, Meder, Benjamin, additional, Nussbeck, Sara Y., additional, Rog-Zielinska, Eva A., additional, Schulz, Marcel H., additional, Sickmann, Albert, additional, Yigit, Gökhan, additional, and Kohl, Peter, additional

Published
2023
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