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多组学分析与心血管疾病的网络生物学。

Multi-omic analyses and network biology in cardiovascular disease.

机构信息

Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.

Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada.

出版信息

Proteomics. 2023 Nov;23(21-22):e2200289. doi: 10.1002/pmic.202200289. Epub 2023 Sep 10.

Abstract

Heart disease remains a leading cause of death in North America and worldwide. Despite advances in therapies, the chronic nature of cardiovascular diseases ultimately results in frequent hospitalizations and steady rates of mortality. Systems biology approaches have provided a new frontier toward unraveling the underlying mechanisms of cell, tissue, and organ dysfunction in disease. Mapping the complex networks of molecular functions across the genome, transcriptome, proteome, and metabolome has enormous potential to advance our understanding of cardiovascular disease, discover new disease biomarkers, and develop novel therapies. Computational workflows to interpret these data-intensive analyses as well as integration between different levels of interrogation remain important challenges in the advancement and application of systems biology-based analyses in cardiovascular research. This review will focus on summarizing the recent developments in network biology-level profiling in the heart, with particular emphasis on modeling of human heart failure. We will provide new perspectives on integration between different levels of large "omics" datasets, including integration of gene regulatory networks, protein-protein interactions, signaling networks, and metabolic networks in the heart.

摘要

心脏病仍然是北美和全球的主要死亡原因。尽管治疗方法有所进步,但心血管疾病的慢性性质最终导致频繁住院和稳定的死亡率。系统生物学方法为揭示疾病中细胞、组织和器官功能障碍的潜在机制提供了一个新的前沿。绘制基因组、转录组、蛋白质组和代谢组中分子功能的复杂网络具有极大的潜力,可以促进我们对心血管疾病的理解、发现新的疾病生物标志物并开发新的治疗方法。解释这些数据密集型分析的计算工作流程以及不同层次的探究之间的整合仍然是系统生物学分析在心血管研究中应用和发展的重要挑战。这篇综述将重点总结心脏网络生物学水平分析的最新进展,特别强调人类心力衰竭的建模。我们将提供在不同层次的大型“组学”数据集之间进行整合的新视角,包括心脏中基因调控网络、蛋白质-蛋白质相互作用、信号网络和代谢网络的整合。

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