Del 24 - Translational Epigenetics

Epigenetics in Cardiovascular Disease

Häftad, Engelska, 2021

Av Yvan Devaux, Emma Louise Robinson, EU-CardioRNA COST) Devaux, Yvan (Chair, USA.) Robinson, Emma Louise (School of Medicine, Division of Cardiology, University of Colorado Denver, Anschutz Medical Campus, Aurora, Colorado

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Epigenetics in Cardiovascular Disease, a new volume in the Translational Epigenetics series, offers a comprehensive overview of the epigenetics mechanisms governing cardiovascular disease development, as well as instructions in research methods and guidance in pursing new studies. More than thirty international experts provide an (i) overview of the epigenetics mechanisms and their contribution to cardiovascular disease development, (i) high-throughput methods for RNA profiling including single-cell RNA-seq, (iii) the role of nucleic acid methylation in cardiovascular disease development, (iv) epigenetic actors as biomarkers and drug targets, (v) and the potential of epigenetics to advance personalized medicine. Here, readers will discover strategies to combat research challenges, improve quality of their epigenetic research and reproducibility of their findings. Additionally, discussion of assay and drug development for personalized healthcare pave the way for a new era of understanding in cardiovascular disease.

Offers a thorough overview of role of epigenetics mechanisms in cardiovascular disease
Includes guidance to improve research plans, experimental protocols design, quality and reproducibility of results in new epigenetics research
Explores biomarkers and drug targets of therapeutic potential to advance personalized healthcare
Features chapter contributions from a wide range of international researchers in the field

Produktinformation

Utgivningsdatum2021-03-10
Mått191 x 235 x 33 mm
Vikt970 g
FormatHäftad
SpråkEngelska
SerieTranslational Epigenetics
Antal sidor498
FörlagElsevier Science
ISBN9780128222584

Tillhör följande kategorier

Biovetenskap inom Naturvetenskap och teknik

Dr Devaux is Chairing the EU-CardioRNA COST Action, an international network of 30 European countries focusing on Transcriptomics in Cardiovascular Disease. Dr Robinson is leading a Working Group on Dissemination activities in the Action. The network, with 100+ individual experts in the field of Epigenetics in cardiovascular disease, constitutes an invaluable reservoir of co-authors for the Volume.

SECTION I INTRODUCTORY INFORMATION1. The ever-growing burden of cardiovascular disease2. Epigenetics concepts: An overview3. From classical signaling pathways to the nucleusSECTION II EPIGENETICS MECHANISMS IN CARDIOVASCULAR DISEASE4. DNA methylation in heart failure5. Histone modifications in cardiovascular disease initiation and progression6. RNA modifications in cardiovascular disease—An experimental and computational perspective7. Regulatory RNAs in cardiovascular disease8. Regulation of splicing in cardiovascular disease9. Cardiac transcriptomic remodeling in metabolic syndrome10. Sex differences in epigenetics mechanisms of cardiovascular disease11. Epigenetics in cardiac development and human induced pluripotent stem cellsSECTION III BIOMARKER VALUE12. Peripheral blood DNA and RNA biomarkers of cardiovascular disease in clinical practice13. Epigenetics and physical exercise14. Long noncoding RNAs and circular RNAs as heart failure biomarkers15. Artificial intelligence in clinical decision-making for diagnosis of cardiovascular disease using epigenetics mechanismsSECTION IV THERAPEUTIC POTENTIAL16. Therapeutic strategies for modulating epigenetic mechanisms in cardiovascular diseaseSECTION V METHODOLOGICAL ISSUES17. Single-cell RNA sequencing in cardiovascular science18. Good laboratory and experimental practices for microRNA analysis in cardiovascular research19. Analytical challenges in microRNA biomarker development: Best practices for analyzing microRNAs in cell-free biofluids20. Concept of biological reference materials for RNA analysis in cardiovascular disease21. Unbiased bioinformatics analysis of microRNA transcriptomics datasets and network theoretic target prediction