不同类型的脂质与阿尔茨海默病、帕金森病和癫痫之间的关联:孟德尔随机化和生物信息学分析

IF 1.2 4区 生物学 Q4 GENETICS & HEREDITY
Jiayu Zhang, Anqi Song, Yi Xiang, Jiaqi Liu, Baixiang Li, Xueting Li
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引用次数: 0

摘要

背景:随着阿尔茨海默病(AD)、帕金森病(PD)和癫痫(EP)等神经系统疾病在世界范围内的患病率不断上升,医疗卫生资源的负担越来越重。因此,确定这些疾病的病因,实施有针对性的预防、诊断和治疗措施,以解决现有医疗资源短缺的问题至关重要。脂质是生物膜的组成部分。它们不仅具有储存能量和维持细胞结构的功能,而且在细胞间通讯和信号传递中起着关键作用。因此,脂质可能在上述疾病的发病机制和进展中具有重要意义。方法:本研究采用双样本孟德尔随机化(MR)方法,分析IEU OpenGWAS数据库,探讨159种脂质与上述疾病的潜在因果关系,并进行敏感性分析。通过GEO数据库中这三种疾病的数据分析,获得差异表达基因(differential expression genes, DEGs),然后进行富集分析和蛋白-蛋白相互作用(protein-protein interaction, PPI)网络分析。结果:研究结果表明,这些疾病的发生和进展与20种脂质之间存在潜在的因果关系,这些脂质分为6类,包括甾醇酯(SEs)、神经酰胺(Cer)、磷脂酰胆碱(PC)、磷脂酰乙醇胺(PE)、磷脂酰肌醇(PI)和三酰甘油(TAG)。此外,这些脂质被发现调节与内吞作用、突触囊泡循环、信号释放、MAPK信号通路、PI3K激酶(PI3K)-AKT信号通路、多巴胺能突触和疟疾感染相关的生物过程和途径。值得注意的是,基于STRING数据库中蛋白质相互作用的综合评分,以及它们与网络中其他蛋白质的连通性和关联强度,热休克因子结合蛋白1 (HSPB1)被确定为AD的关键蛋白,该蛋白与脂质密切相关,与疾病的关系也相对密切。同样,RAB3A被鉴定为PD的关键蛋白。CD160是EP的关键蛋白。结论:本研究将MR与生物信息学分析相结合,分别发现了AD、PD和EP的潜在脂质生物学过程、途径和生物标志物,为我们提供了新的治疗靶点,加深了我们对神经系统疾病机制的认识,为未来的临床干预提供了支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association Between Different Types of Lipids and Alzheimer's Disease, Parkinson's Disease, and Epilepsy: A Mendelian Randomization and Bioinformatics Analysis.

Background: With the increasing prevalence of neurological disorders, such as Alzheimer's disease (AD), Parkinson's disease (PD), and epilepsy (EP) worldwide, there is a growing burden on medical and healthcare resources. Therefore, it is crucial to identify the etiology of these diseases and implement targeted preventive, diagnostic, and treatment measures to address the existing shortage of medical resources. Lipids are integral components of biological membranes. They not only function in energy storage and maintaining cell structure but also play a pivotal role in intercellular communication and signal transmission. Hence, lipids may hold significant implications in the pathogenesis and progression of the aforementioned disorders.

Methods: Utilizing two-sample Mendelian randomization (MR) in this investigation, the IEU OpenGWAS database was analyzed to explore the potential causal association between 159 lipids and the mentioned conditions, with sensitivity analysis being performed. Differentially expressed genes (DEGs) were obtained through data analysis of these three diseases in the GEO database, followed by enrichment analysis and protein-protein interaction (PPI) network analysis.

Results: The findings indicated a potential causal association between the onset and progression of these disorders and 20 lipids categorized into six groups, which include sterol esters (SEs), ceramides (Cer), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI), and triacylglycerol (TAG). Furthermore, these lipids were found to regulate biological processes and pathways associated with endocytosis, synaptic vesicular circulation, signal release, MAPK signaling pathway, PI3 kinase (PI3K)-AKT signaling pathway, dopaminergic synapses, and malaria infection. It is worth noting that based on the comprehensive scores of protein interactions in the STRING database, as well as their connectivity and association strength with other proteins in the network, heat shock factor binding protein 1 (HSPB1), which is closely related to lipids and has a relatively close relationship with diseases, was identified as a key protein for AD. Similarly, RAB3A was identified as a key protein for PD. CD160 serves as the key protein of EP.

Conclusion: This study, by combining MR with bioinformatics analysis, discovered the potential lipid-based biological processes, pathways, and biomarkers of AD, PD, and EP, respectively, suggesting new therapeutic targets for us, deepening our understanding of the mechanisms of neurological diseases, and providing support for future clinical interventions.

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来源期刊
Annals of Human Genetics
Annals of Human Genetics 生物-遗传学
CiteScore
4.20
自引率
0.00%
发文量
34
审稿时长
3 months
期刊介绍: Annals of Human Genetics publishes material directly concerned with human genetics or the application of scientific principles and techniques to any aspect of human inheritance. Papers that describe work on other species that may be relevant to human genetics will also be considered. Mathematical models should include examples of application to data where possible. Authors are welcome to submit Supporting Information, such as data sets or additional figures or tables, that will not be published in the print edition of the journal, but which will be viewable via the online edition and stored on the website.
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