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阿尔茨海默病中的基因网络和系统生物学:多组学方法的见解。

Gene networks and systems biology in Alzheimer's disease: Insights from multi-omics approaches.

机构信息

Mathematical, Computational, and Systems Biology (MCSB) Program, University of California Irvine, Irvine, California, USA.

Department of Computer Science, University of California, Irvine, California, USA.

出版信息

Alzheimers Dement. 2024 May;20(5):3587-3605. doi: 10.1002/alz.13790. Epub 2024 Mar 27.

Abstract

Despite numerous studies in the field of dementia and Alzheimer's disease (AD), a comprehensive understanding of this devastating disease remains elusive. Bulk transcriptomics have provided insights into the underlying genetic factors at a high level. Subsequent technological advancements have focused on single-cell omics, encompassing techniques such as single-cell RNA sequencing and epigenomics, enabling the capture of RNA transcripts and chromatin states at a single cell or nucleus resolution. Furthermore, the emergence of spatial omics has allowed the study of gene responses in the vicinity of amyloid beta plaques or across various brain regions. With the vast amount of data generated, utilizing gene regulatory networks to comprehensively study this disease has become essential. This review delves into some techniques employed in the field of AD, explores the discoveries made using these techniques, and provides insights into the future of the field.

摘要

尽管在痴呆症和阿尔茨海默病(AD)领域进行了大量研究,但对这种毁灭性疾病的全面了解仍难以捉摸。大量转录组学提供了对潜在遗传因素的高层次见解。随后的技术进步集中在单细胞组学上,包括单细胞 RNA 测序和表观基因组学等技术,能够以单细胞或核分辨率捕获 RNA 转录本和染色质状态。此外,空间组学的出现使得可以研究淀粉样β斑块附近或不同脑区的基因反应。随着大量数据的产生,利用基因调控网络来全面研究这种疾病变得至关重要。本综述深入探讨了 AD 领域中使用的一些技术,探讨了使用这些技术取得的发现,并对该领域的未来提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e024/11095483/d4dd7b481aaa/ALZ-20-3587-g002.jpg

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