中国组织工程研究 ›› 2024, Vol. 28 ›› Issue (16): 2568-2573.doi: 10.12307/2024.306

• 组织构建相关数据分析 Date analysis of organization construction • 上一篇    下一篇

胰高血糖素样肽1受体激动剂治疗阿尔茨海默病的潜在靶点预测及验证

韩维娜1,徐晓庆1,史晋宁1,李欣儒2,蔡红艳3   

  1. 1邵阳学院普爱医学院(医学部)生理学教研室,湖南省邵阳市  422000;山西医科大学,2生理学系,3基础医学院微生物与免疫教研室,山西省太原市  030000
  • 收稿日期:2023-03-22 接受日期:2023-04-20 出版日期:2024-06-08 发布日期:2023-07-31
  • 通讯作者: 韩维娜,邵阳学院普爱医学院(医学部)生理学教研室,湖南省邵阳市 422000
  • 作者简介:韩维娜,女,1986年生,山西省人,汉族,2012年山西医科大学毕业,硕士,副教授,主要从事阿尔茨海默病的神经生物学研究。
  • 基金资助:
    国家自然科学基金委员会面上项目(82171428),项目负责人:蔡红艳;湖南省自然科学基金青年项目(2020JJ5517),项目负责人:韩维娜;湖南省教育厅科学研究项目(20C1671);项目负责人:韩维娜

Prediction and validation of potential targets for the glucagon-like peptide-1 receptor agonist in the treatment of Alzheimer’s disease

Han Weina1, Xu Xiaoqing1, Shi Jinning1, Li Xinru2, Cai Hongyan3   

  1. 1Department of Physiology, Puai School of Medicine (Health Science Center), Shaoyang University, Shaoyang 422000, Hunan Province, China; 2Department of Physiology, 3Department of Microbiology and Immunology, School of Basic Medical Sciences, Shanxi Medical University, Taiyuan 030000, Shanxi Province, China
  • Received:2023-03-22 Accepted:2023-04-20 Online:2024-06-08 Published:2023-07-31
  • Contact: Han Weina, Department of Physiology, Puai School of Medicine (Health Science Center), Shaoyang University, Shaoyang 422000, Hunan Province, China
  • About author:Han Weina, Master, Associate professor, Department of Physiology, Puai School of Medicine (Health Science Center), Shaoyang University, Shaoyang 422000, Hunan Province, China
  • Supported by:
    National Natural Science Foundation of China (General Program), No. 82171428 (to CHY); Natural Science Foundation of Hunan Province for Young Scholars, No. 2020JJ5517 (to HWN); Scientific Research Project of Education Department of Hunan Province, No. 20C1671 (to HWN)

摘要:


文题释义:

阿尔茨海默病:是一种起病隐匿的进行性发展的神经退行性疾病,在临床上以记忆障碍、执行功能障碍以及人格和行为改变等全面性痴呆表现为特征,缺乏明确的治疗手段。
生物信息学:是一门包括以信息科学的原理和方法对生物信息进行获取、处理、存储、传播、分析和解释等方面知识和方法的学科,通常用来预测药物治疗靶点和疾病差异基因。


背景:阿尔茨海默病的机制探究过程中揭示了生物信息学对共同靶点筛选的重要作用,能够利用其筛选结果为基础,探究药物对该疾病的治疗效果。

目的:采用生物信息学与分子生物学等方法预测胰高血糖素样肽1受体激动剂利拉鲁肽治疗阿尔茨海默病的作用靶点。
方法:利用DisGeNET数据库及SEA数据库获取阿尔茨海默病和利拉鲁肽作用的共同基因;利用DAVID在线数据库对共同靶点进行GO/KEGG富集分析;使用STRING数据库构建蛋白互作网络;使用CCK-8判断利拉鲁肽的最佳使用剂量;使用免疫荧光和免疫印迹技术对关键蛋白的表达情况进行分析。采用小鼠海马神经元HT22细胞系进行体外实验,细胞被随机分为3组:HT22组、HT22+Aβ组和HT22+Aβ+Lir组。HT22组不做特殊处理,HT22+Aβ组使用Aβ1-42干预HT22细胞系24 h构建Aβ损伤细胞模型,HT22+Aβ+Lir组在HT22+Aβ组的基础上添加利拉鲁肽12 h。

结果与结论:①从DisGeNET数据库筛选出阿尔茨海默病相关联的基因,共得到3 333个关联基因。再从SEA数据库中,得到利拉鲁肽的潜在作用靶点147个。最后使用R包筛选出阿尔茨海默病与利拉鲁肽共同靶点64个。②用DAVID数据库进行共同靶点的GO/KEGG分析,结果提示共同靶点主要富集在:神经活性配体-受体相互作用、肾素-血管紧张素系统、膀胱癌、内肽酶活性、肽受体活性、G蛋白偶联肽受体活性和转运囊泡等生物进程。③将已经得到的64个共同靶点蛋白导入至SRTING在线数据库进行蛋白互作网络构建,得到排名前3位的基因为基质金属蛋白酶2,9和白细胞介素1β。④采用CCK-8试剂盒检测了培养细胞的活性,确定利拉鲁肽拮抗Aβ1-42的最佳浓度为100 nmol/L。⑤在免疫印迹实验与免疫荧光实验中,较HT22组相比,在HT22+Aβ组内基质金属蛋白酶2,9和白细胞介素1β表达量明显上升(P < 0.05);HT22+Aβ+Lir组较HT22+Aβ组相比基质金属蛋白酶2,9和白细胞介素1β的表达量显著下降(P < 0.05)。⑥结合上述生物信息学数据及在GEO数据库的差异基因二次验证结果提示,基质金属蛋白酶2,9和白细胞介素1β均可作为利拉鲁肽治疗阿尔茨海默病的潜在作用靶点。

https://orcid.org/0000-0002-1459-5725(韩维娜)

中国组织工程研究杂志出版内容重点:组织构建;骨细胞;软骨细胞;细胞培养;成纤维细胞;血管内皮细胞;骨质疏松;组织工程

关键词: 阿尔茨海默病, 利拉鲁肽, 胰高血糖素样肽1受体, 生物信息学, DisGeNET数据库, SEA数据库, GEO数据库, MMP9, MMP2, 白细胞介素1β

Abstract: BACKGROUND: In the process of exploring the mechanism of Alzheimer’s disease, the important role of bioinformatics for common target screening has been revealed, enabling the use of its screening results as a basis for exploring the therapeutic effects of drugs on the disease.
OBJECTIVE: To predict the targets of liraglutide, a glucagon-like peptide-1 receptor agonist, in the treatment of Alzheimer’s disease by bioinformatics and molecular biology.
METHODS: DisGeNET database and SEA database were used to obtain the common genes of Alzheimer’s disease and liraglutide. GO/KEGG enrichment analysis of common targets was conducted using DAVID online database. Protein-protein interaction networks were constructed using STRING database. The optimal dosage of liraglutide was determined using cell counting kit-8 assay. Expression of key proteins was analyzed using immunofluorescence and immunoblotting techniques. The mouse hippocampal neuron HT22 cell line was used for ex vivo experiments, and the cells were randomly divided into three groups: HT22 group, HT22+Aβ group, and HT22+Aβ+Lir group. No special treatment was done in the HT22 group, while Aβ1-42 was used to intervene in the HT22 cell line for 24 hours to construct an Aβ injury cell model in the HT22+Aβ group. In additional to modeling, liraglutide was added to the HT22+Aβ+Lir group for 12 hours. 
RESULTS AND CONCLUSION: A total of 3 333 genes associated with Alzheimer’s disease were screened from DisGeNET database. Then 147 potential targets of liraglutide were obtained from SEA database. Finally, 64 common targets of Alzheimer’s disease and Liraglutide were determined using R packets. GO/KEGG analysis of common targets using DAVID online database suggested that common targets were mainly enriched in the following biological processes: neuroactive ligand-receptor interaction, renin-angiotensin system, bladder cancer, endopeptidase activity, peptide receptor activity, G protein-coupled peptide receptor activity, and transport vesicles. The obtained 64 common target proteins were imported into SRTING online database for protein-protein interaction network construction, and the top three genes, matrix metalloproteinases 2, 9 and interleukin 1β, were obtained. The activity of cultured cells was detected by the cell counting kit-8 kit. Liraglutide at 100 nmol/L was the optimal concentration for antagonizing Aβ1-42. In the western blot and immunofluorescence assays, the expression of matrix metalloproteinases 2, 9 and interleukin 1β was significantly increased in the HT22+Aβ group compared with the HT22 group (P < 0.05) but significantly decreased in the HT22+Aβ+Lir group compared with the HT22+Aβ group (P < 0.05). To conclude, the above bioinformatics data and secondary validation of differential genes in the GEO database suggest that both matrix metalloproteinases 2,9 and interleukin 1β could be potential targets of liraglutide in the treatment of Alzheimer’s disease.

Key words: Alzheimer’s disease, liraglutide, glucagon-like peptide-1 receptor, bioinformatics, DisGeNET database, SEA database, GEO database, MMP9, MMP2, interleukin 1β

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