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揭示导致阿尔茨海默病发生的2型糖尿病的遗传联系。

Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer's disease.

作者信息

Afzal Muhammad, Alharbi Khalid Saad, Alzarea Sami I, Alyamani Najiah M, Kazmi Imran, Güven Emine

机构信息

Department of Pharmacology, College of Pharmacy, Jouf University, Sakaka 72341, Aljouf, Saudi Arabia.

Biology Department, College of Science, University of Jeddah, Jeddah, Saudi Arabia.

出版信息

Heliyon. 2022 Dec 16;9(1):e12202. doi: 10.1016/j.heliyon.2022.e12202. eCollection 2023 Jan.

Abstract

BACKGROUND

A factor leading to Alzheimer's Disease (AD), portrayed by peripheral insulin resistance, is Type 2 diabetes mellitus (T2D). The likelihood of T2D cases would be at boosted danger in alternating AD cases has severe social consequences. Several genes have been detected via gene expression profiling or different techniques; despite the consideration of the utility of numerous of these genes stays insufficient.

METHODS

This project is designed to uncover the mutual genomics motifs between AD and T2D via non-negative matrix factorization (NMF) of differentially expressed genes (DEGs) of T2D Mellitus of human cortical neurons of the neurovascular unit gene expression data. A rank factorization value is calculated by employing the combination of the NMF model with the unit invariant knee (UIK) point method. The metagenes are further determined by remarking the enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) enrichment tools. In this study, the most highly expressed genes of metagenes are subjected to protein-protein interaction (PPI) network study to discover the most significant biomarkers of T2D Mellitus in the ageing brain.

RESULTS

We screened the most important shared genes (CDKN1A, COL22A1, EIF4A, GFAP, SLC1A1, and VIM) and essential human molecular pathways that motivate these diseases. The study aimed to validate the most significant hub genes using network-based methods which detected the corresponding relationship between AD and T2D.

CONCLUSIONS

Using in silico tools, the computational pipeline has broadly examined transformed pathways and discovered promising biomarkers and drug targets. We validated the most significant hub genes using network-based methods which detected the corresponding relationship between AD and T2D. These consequences on brain cells hypothetically reserve to diabetic Alzheimer's so-called type 3 diabetes (T3D) and may offer promising methodologies for curative intrusion.

摘要

背景

2型糖尿病(T2D)是导致阿尔茨海默病(AD)的一个因素,其特征为外周胰岛素抵抗。在交替出现的AD病例中,T2D病例的可能性会增加,这会产生严重的社会后果。通过基因表达谱分析或其他不同技术已经检测到了多个基因;尽管其中许多基因的实用性仍未得到充分考虑。

方法

本项目旨在通过对神经血管单元基因表达数据中人类皮质神经元的T2D Mellitus差异表达基因(DEG)进行非负矩阵分解(NMF),来揭示AD和T2D之间的共同基因组基序。通过将NMF模型与单位不变拐点(UIK)点方法相结合来计算秩分解值。通过注释富集的京都基因与基因组百科全书(KEGG)通路和基因本体(GO)富集工具来进一步确定元基因。在本研究中,对元基因中表达最高的基因进行蛋白质-蛋白质相互作用(PPI)网络研究,以发现衰老大脑中T2D Mellitus最重要的生物标志物。

结果

我们筛选出了最重要的共享基因(CDKN1A、COL22A1、EIF4A、GFAP、SLC1A1和VIM)以及引发这些疾病的重要人类分子通路。该研究旨在使用基于网络的方法验证最重要的枢纽基因,该方法检测到了AD和T2D之间的对应关系。

结论

使用计算机工具,该计算流程广泛研究了转化途径,发现了有前景的生物标志物和药物靶点。我们使用基于网络的方法验证了最重要的枢纽基因,该方法检测到了AD和T2D之间的对应关系。这些对脑细胞的影响可能会保留到糖尿病性阿尔茨海默病即所谓的3型糖尿病(T3D),并可能为治疗干预提供有前景的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af32/9876837/1580067f43e7/gr1.jpg

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