Division of Cardiovascular Medicine (R.-S.W., B.A.M., J.L.), Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Channing Division of Network Medicine (R.-S.W., J.L.), Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Arterioscler Thromb Vasc Biol. 2023 Apr;43(4):493-503. doi: 10.1161/ATVBAHA.122.318731. Epub 2023 Feb 16.
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.
心血管疾病（CVD）是全球范围内的主要死亡原因，表现出复杂的表型异质性，这是由许多趋同过程引起的，包括遗传变异和环境因素之间的相互作用。尽管已经确定了大量相关的基因和遗传位点，但这些基因系统地影响 CVD 表型异质性的确切机制仍不清楚。除了 DNA 序列，理解 CVD 的分子机制还需要来自其他组学水平的数据，包括表观基因组、转录组、蛋白质组以及代谢组。多组学技术的最新进展为超越基因组学的精准医学提供了新的机会，可以指导精准诊断和个性化治疗。同时，网络医学作为一个跨学科领域已经出现，它整合了系统生物学和网络科学，专注于健康和疾病中生物成分之间的相互作用，为系统地整合这些多组学数据提供了一个无偏见的框架。在这篇综述中，我们简要介绍了这些多组学技术，包括 bulk omics 和单细胞 omics 技术，并讨论了它们如何为精准医学做出贡献。然后，我们强调了基于网络医学的多组学数据整合在 CVD 的精准医学和治疗中的应用。我们还讨论了使用多组学网络医学方法研究 CVD 时当前的挑战、潜在的局限性和未来方向。
