Systems genetics applications in metabolism research.
Systems genetics applications in metabolism research.
复制标题
系统遗传学在代谢研究中的应用。
DOI：
10.1038/s42255-019-0132-x
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发表时间：
2019
影响因子：
20.8
通讯作者：
Lusis,AldonsJ
中科院分区：
文献类型：
--
作者：
Seldin,Marcus;Yang,Xia;Lusis,AldonsJ
代谢疾病的常见形式非常复杂，涉及数百个基因、环境和生活方式因素、年龄相关变化、性别差异和肠道微生物组相互作用。系统遗传学是一种基于群体的方法来解决这种复杂性。与通常使用的“简化”方法（如功能的获得或丧失）不同，系统遗传学使用高通量“组学”技术来定量评估群体中个体之间的许多分子差异，然后将这些与生理功能或疾病状态联系起来。与全基因组关联研究不同，系统遗传学试图超越致病基因的识别，以了解分子水平上的高阶相互作用。本文就系统遗传学在代谢和心血管疾病中的应用作一综述。在这里，我们解释了来自人类和动物群体的大量临床和组学水平的数据和数据库，以帮助研究人员将基因置于通路和网络的背景下，并制定假设，然后进行实验检验。我们提供了这样的数据库和还原论和系统遗传学数据的整合的例子列表。新兴的重要应用之一是开发改进的营养和药理学策略，以应对代谢疾病的增加。
The common forms of metabolic diseases are highly complex, involving hundreds of genes, environmental and lifestyle factors, age-related changes, sex differences and gut–microbiome interactions. Systems genetics is a population-based approach to address this complexity. In contrast to commonly used ‘reductionist’ approaches, such as gain or loss of function, that examine one element at a time, systems genetics uses high-throughput ‘omics’ technologies to quantitatively assess the many molecular differences among individuals in a population and then to relate these to physiologic functions or disease states. Unlike genome-wide association studies, systems genetics seeks to go beyond the identification of disease-causing genes to understand higher-order interactions at the molecular level. The purpose of this review is to introduce the systems genetics applications in the areas of metabolic and cardiovascular disease. Here, we explain how large clinical and omics-level data and databases from both human and animal populations are available to help researchers place genes in the context of pathways and networks and formulate hypotheses that can then be experimentally examined. We provide lists of such databases and examples of the integration of reductionist and systems genetics data. Among the important applications emerging is the development of improved nutritional and pharmacological strategies to address the rise of metabolic diseases.