基于三方比较的帕金森病基因共表达网络分析——寻找遗传标记物。

Gene co-expression network analysis for identifying genetic markers in Parkinson's disease - a three-way comparative approach.

机构信息

Department of Bioinformatics, Karunya University, Karunya Nagar, Tamil Nadu 641114, India.

Department of Bioinformatics, Karunya University, Karunya Nagar, Tamil Nadu 641114, India; Institute of Bio-Sciences and Technology, Shri Ramswaroop Memorial University, Deva Road, Uttar Pradesh 225003, India.

出版信息

Genomics. 2019 Jul;111(4):819-830. doi: 10.1016/j.ygeno.2018.05.005. Epub 2018 May 28.

DOI:10.1016/j.ygeno.2018.05.005

PMID:29852216

Abstract

Parkinson's disease (PD) is a neurodegenerative disorder involving progressive deterioration of dopaminergic neurons. Although few genetic markers for familial PD are known, the etiology of sporadic PD remains poorly understood. Microarray data was analysed for induced pluripotent stem cells (iPSCs) derived from PD patients and mature neuronal cells (mDA) differentiated from these iPSCs. Combining expression and semantic similarity, a highly-correlated PD interactome was constructed that included interactions of established Parkinson's disease marker genes. A novel three-way comparative approach was employed, delineating topologically and functionally important genes. These genes showed involvement in pathways like Parkin-ubiquitin proteosomal system (UPS), immune associated biological processes and apoptosis. Of interest are three genes, eEF1A1, CASK, and PSMD6 that are linked to PARK2 activity in the cell and thereby form attractive candidate genes for understanding PD. Network biology approach delineated in this study can be applied to other neurodegenerative disorders for identification of important genetic regulators.

摘要

帕金森病（PD）是一种涉及多巴胺能神经元进行性退化的神经退行性疾病。尽管已知少数家族性 PD 的遗传标志物，但散发性 PD 的病因仍知之甚少。对源自 PD 患者的诱导多能干细胞（iPSC）和这些 iPSC 分化而来的成熟多巴胺能神经元（mDA）的微阵列数据进行了分析。通过表达和语义相似性相结合，构建了一个高度相关的 PD 相互作用组，其中包括已确定的帕金森病标志物基因的相互作用。采用了一种新颖的三向比较方法，确定了拓扑和功能上重要的基因。这些基因参与了 Parkin-泛素蛋白酶体系统（UPS）、免疫相关的生物学过程和细胞凋亡等途径。有趣的是，有三个基因，eEF1A1、CASK 和 PSMD6，与细胞中的 PARK2 活性有关，因此它们成为了解 PD 的有吸引力的候选基因。本研究中描述的网络生物学方法可应用于其他神经退行性疾病，以鉴定重要的遗传调节剂。