Systems biology and gene networks in Alzheimer’s disease
Systems biology and gene networks in Alzheimer’s disease
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DOI：
10.1016/j.neubiorev.2018.11.007
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发表时间：
2019-01
影响因子：
8.2
通讯作者：
Zuo-teng Wang;Chen‐Chen Tan;L. Tan;Jin-Tai Yu
中科院分区：
文献类型：
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作者：
Zuo-teng Wang;Chen‐Chen Tan;L. Tan;Jin-Tai Yu
基因挖掘是阿尔茨海默病(AD)研究中一种卓有成效的方法。作为研究阿尔茨海默病的新起点，遗传学和基因组研究一直致力于发现与疾病病理生理相关的致病变异。目前，遗传学和基因组学方法已经确定了大量的基因座。然而，AD发病机制的阐述滞后于基因的发现。并行、高通量、下一代测序技术的广泛使用提高了我们对基因变异在大脑最高功能层次上的作用的理解。在这篇综述中，我们重点介绍了三个分子系统(转录组、蛋白质组和表观基因组)，以确定在AD系统生物学研究中使用的方法是否有用。在这里，我们展示了高通量分子方法、集成方法和网络方法的许多优点，这可能为未来使用网络生物学方法和大数据集进行研究提供很好的参考。
Gene mining has been a fruitful approach in the study of Alzheimer’s disease (AD). As a new starting point for studying AD, genetic and genomic investigations consistently strive to discover causative variants that are related to disease pathophysiology. Currently, genetic and genomic approaches have identified numerous loci. However, the elaboration of AD mechanism lagged behind gene discovery. The extensive use of parallel, high-throughput, next-generation sequencing techniques has improved our understanding of the roles of genetic variants in the brain at the highest level of functional hierarchy. We highlight three molecular systems (the transcriptome, proteome and epigenome) in this review to ascertain whether the methods used in systems biology studies of AD are useful. Here, we present many advantages of the high-throughput molecular, integrative and network methods, which may provide a good reference for future studies employing network biology approaches and large datasets.