This state-of-the-art review aims to provide an up-to-date look at breakthrough omic technologies that are helping to unravel heart failure (HF) disease mechanisms and heterogeneity. Genomics, transcriptomics, proteomics, and metabolomics in HF are reviewed in depth. In addition, there is a thorough, expert discussion regarding the value of omics in identifying novel disease pathways, advancing understanding of disease mechanisms, differentiating HF phenotypes, yielding biomarkers for diagnosis or prognosis, or identifying new therapeutic targets in HF. The combination of multiple omics technologies may create a more comprehensive picture of the factors and physiology involved in HF than achieved by either one alone and provides a rich resource for predictive phenotype modelling. However, the successful translation of omics tools as solutions to clinical HF requires that the observations are robust and reproducible and can be validated across multiple independent populations to ensure confidence in clinical decision-making.

Omics phenotyping in heart failure: The next frontier

Emdin M.;
2020-01-01

Abstract

This state-of-the-art review aims to provide an up-to-date look at breakthrough omic technologies that are helping to unravel heart failure (HF) disease mechanisms and heterogeneity. Genomics, transcriptomics, proteomics, and metabolomics in HF are reviewed in depth. In addition, there is a thorough, expert discussion regarding the value of omics in identifying novel disease pathways, advancing understanding of disease mechanisms, differentiating HF phenotypes, yielding biomarkers for diagnosis or prognosis, or identifying new therapeutic targets in HF. The combination of multiple omics technologies may create a more comprehensive picture of the factors and physiology involved in HF than achieved by either one alone and provides a rich resource for predictive phenotype modelling. However, the successful translation of omics tools as solutions to clinical HF requires that the observations are robust and reproducible and can be validated across multiple independent populations to ensure confidence in clinical decision-making.
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/537558
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