基于组学数据探究前驱期至亨廷顿病症状期的转变。

Investigating the Transition of Pre-Symptomatic to Symptomatic Huntington's Disease Status Based on Omics Data.

机构信息

Bioinformatics Department; Cyprus Institute of Neurology and Genetics; Cyprus School of Molecular Medicine, 2371 Nicosia, Cyprus.

Neurology Clinic D; Cyprus Institute of Neurology and Genetics; Cyprus School of Molecular Medicine, 2371 Nicosia, Cyprus.

出版信息

Int J Mol Sci. 2020 Oct 8;21(19):7414. doi: 10.3390/ijms21197414.

Abstract

Huntington's disease is a rare neurodegenerative disease caused by a cytosine-adenine-guanine (CAG) trinucleotide expansion in the Huntingtin () gene. Although Huntington's disease (HD) is well studied, the pathophysiological mechanisms, genes and metabolites involved in HD remain poorly understood. Systems bioinformatics can reveal synergistic relationships among different omics levels and enables the integration of biological data. It allows for the overall understanding of biological mechanisms, pathways, genes and metabolites involved in HD. The purpose of this study was to identify the differentially expressed genes (DEGs), pathways and metabolites as well as observe how these biological terms differ between the pre-symptomatic and symptomatic HD stages. A publicly available dataset from the Gene Expression Omnibus (GEO) was analyzed to obtain the DEGs for each HD stage, and gene co-expression networks were obtained for each HD stage. Network rewiring, highlights the nodes that change most their connectivity with their neighbors and infers their possible implication in the transition between different states. The gene was the mostly highly rewired node among pre-symptomatic and symptomatic HD network. Furthermore, we identified to be common between the rewired genes and DEGs of symptomatic HD. and between the DEGs of pre-symptomatic and DEGs of symptomatic HD and and between the rewired genes and DEGs of pre-symptomatic HD. The proteins encoded by these genes are involved in various biological pathways such as phosphatidylinositol-4,5-bisphosphate 3-kinase activity, cAMP response element-binding protein binding, protein tyrosine kinase activity, voltage-gated calcium channel activity, ubiquitin protein ligase activity, adenosine triphosphate (ATP) binding, and protein serine/threonine kinase. Additionally, prominent molecular pathways for each HD stage were then obtained, and metabolites related to each pathway for both disease stages were identified. The transforming growth factor beta (TGF-β) signaling (pre-symptomatic and symptomatic stages of the disease), calcium (Ca) signaling (pre-symptomatic), dopaminergic synapse pathway (symptomatic HD patients) and Hippo signaling (pre-symptomatic) pathways were identified. The in silico metabolites we identified include Ca, inositol 1,4,5-trisphosphate, sphingosine 1-phosphate, dopamine, homovanillate and L-tyrosine. The genes, pathways and metabolites identified for each HD stage can provide a better understanding of the mechanisms that become altered in each disease stage. Our results can guide the development of therapies that may target the altered genes and metabolites of the perturbed pathways, leading to an improvement in clinical symptoms and hopefully a delay in the age of onset.

摘要

亨廷顿病是一种罕见的神经退行性疾病,由亨廷顿 () 基因中的胞嘧啶-腺嘌呤-鸟嘌呤 (CAG) 三核苷酸扩展引起。尽管亨廷顿病 (HD) 研究得很好,但与 HD 相关的病理生理机制、基因和代谢物仍知之甚少。系统生物信息学可以揭示不同组学水平之间的协同关系,并能够整合生物数据。它可以全面了解与 HD 相关的生物学机制、途径、基因和代谢物。本研究的目的是鉴定差异表达基因 (DEGs)、途径和代谢物,并观察这些生物学术语在 HD 的无症状和有症状阶段之间的差异。分析了来自基因表达综合数据库 (GEO) 的公开数据集,以获得每个 HD 阶段的 DEGs,并获得每个 HD 阶段的基因共表达网络。网络重布线突出了与其邻居连接变化最大的节点,并推断了它们在不同状态之间转换中的可能作用。在无症状和有症状的 HD 网络中, 基因是变化最大的节点。此外,我们发现 是有症状的 HD 中重布线基因和 DEGs 的共同基因。在无症状和有症状的 HD 之间, 和 是 DEGs 的共同基因,在无症状的 HD 中, 和 是重布线基因和 DEGs 的共同基因。这些基因编码的蛋白质参与各种生物途径,如磷脂酰肌醇-4,5-二磷酸 3-激酶活性、cAMP 反应元件结合蛋白结合、蛋白酪氨酸激酶活性、电压门控钙通道活性、泛素蛋白连接酶活性、三磷酸腺苷 (ATP) 结合和蛋白丝氨酸/苏氨酸激酶。此外,还获得了每个 HD 阶段的主要分子途径,并确定了与两个疾病阶段相关的每个途径的代谢物。转化生长因子-β (TGF-β) 信号通路 (疾病的无症状和有症状阶段)、钙 (Ca) 信号通路 (无症状阶段)、多巴胺能突触途径 (有症状的 HD 患者)和 Hippo 信号通路 (无症状阶段)。我们鉴定的计算机代谢物包括 Ca、肌醇 1,4,5-三磷酸、鞘氨醇 1-磷酸、多巴胺、高香草酸和 L-酪氨酸。为每个 HD 阶段鉴定的基因、途径和代谢物可以更好地了解每个疾病阶段中发生改变的机制。我们的研究结果可以指导开发可能针对受干扰途径的改变基因和代谢物的治疗方法,从而改善临床症状,并希望延缓发病年龄。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cbc7/7582902/8c284b250660/ijms-21-07414-g001.jpg

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