The application of big data to cardiovascular disease: paths to precision medicine.

Publication date: Jan 02, 2020

Advanced phenotyping of cardiovascular diseases has evolved with the application of high-resolution omics screening to populations enrolled in large-scale observational and clinical trials. This strategy has revealed that considerable heterogeneity exists at the genotype, endophenotype, and clinical phenotype levels in cardiovascular diseases, a feature of the most common diseases that has not been elucidated by conventional reductionism. In this discussion, we address genomic context and (endo)phenotypic heterogeneity, and examine commonly encountered cardiovascular diseases to illustrate the genotypic underpinnings of (endo)phenotypic diversity. We highlight the existing challenges in cardiovascular disease genotyping and phenotyping that can be addressed by the integration of big data and interpreted using novel analytical methodologies (network analysis). Precision cardiovascular medicine will only be broadly applied to cardiovascular patients once this comprehensive data set is subjected to unique, integrative analytical strategies that accommodate molecular and clinical heterogeneity rather than ignore or reduce it.

Leopold, J.A., Maron, B.A., and Loscalzo, J. The application of big data to cardiovascular disease: paths to precision medicine. 06090. 2020 J Clin Invest (130):1.

Concepts Keywords
Cardiovascular Cardiovascular diseases
Cardiovascular Disease Big cardiovascular disease
Cardiovascular Diseases Branches of biology
Clinical Trials Polymorphism
Genotype Systems biology
Genotypic Evidence-based medicine
Genotyping Precision medicine
Heterogeneity Cardiovascular disease
Network Analysis Genotype
Omics Phenotype
Phenotype Genotyping
Precision Medicine Genotype
Reductionism

Semantics

Type Source Name
disease MESH cardiovascular disease

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