Multiomics Network Medicine Approaches to Precision Medicine and Therapeutics in Cardiovascular Diseases.
Rui-Sheng WangBradley A MaronJoseph LoscalzoPublished in: Arteriosclerosis, thrombosis, and vascular biology (2023)
Cardiovascular diseases (CVD) are the leading cause of death worldwide and display complex phenotypic heterogeneity caused by many convergent processes, including interactions between genetic variation and environmental factors. Despite the identification of a large number of associated genes and genetic loci, the precise mechanisms by which these genes systematically influence the phenotypic heterogeneity of CVD are not well understood. In addition to DNA sequence, understanding the molecular mechanisms of CVD requires data from other omics levels, including the epigenome, the transcriptome, the proteome, as well as the metabolome. Recent advances in multiomics technologies have opened new precision medicine opportunities beyond genomics that can guide precise diagnosis and personalized treatment. At the same time, network medicine has emerged as an interdisciplinary field that integrates systems biology and network science to focus on the interactions among biological components in health and disease, providing an unbiased framework through which to integrate systematically these multiomics data. In this review, we briefly present such multiomics technologies, including bulk omics and single-cell omics technologies, and discuss how they can contribute to precision medicine. We then highlight network medicine-based integration of multiomics data for precision medicine and therapeutics in CVD. We also include a discussion of current challenges, potential limitations, and future directions in the study of CVD using multiomics network medicine approaches.
Keyphrases
- single cell
- rna seq
- genome wide
- cardiovascular disease
- high throughput
- electronic health record
- public health
- small molecule
- big data
- mental health
- healthcare
- gene expression
- human health
- metabolic syndrome
- artificial intelligence
- network analysis
- risk assessment
- health information
- current status
- type diabetes
- transcription factor
- coronary artery disease
- genome wide identification
- single molecule
- climate change
- combination therapy
- circulating tumor
- amino acid