CYP1B1, VEGFA, BCL2, and CDKN1A Affect the Development of Chronic Obstructive Pulmonary Disease

CYP1B1、VEGFA、BCL2 和 CDKN1A 影响慢性阻塞性肺病的发展

阅读:9
作者:Danlei Yang, Ying Yan, Fen Hu, Tao Wang

Conclusion

CYP1B1, VEGFA, BCL2, and CDKN1A may play important functions in the development and progression of COPD.

Methods

The mRNA expression profile GSE100281, consisting of 79 COPD and 16 healthy samples, was acquired from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) between COPD samples and healthy samples were analyzed using the limma package. Functional enrichment analysis for the DEGs was carried out using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool. Furthermore, DEG-compound pairs were predicted using the Comparative Toxicogenomics Database. The KEGG metabolite IDs corresponding to the compounds were also obtained through the MetaboAnalyst pipeline. Based on the diffusion algorithm, the metabolite network was constructed. Finally, the expression levels of key genes were determined using quantitative PCR (qPCR).

Purpose

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease characterized by poor airflow. The purpose of this study was to explore the mechanisms involved in the development of COPD. Patients and

Results

There were 594 DEGs identified between the COPD and healthy samples, including 242 upregulated and 352 downregulated genes. A total of 696 DEG-compound pairs, such as BCL2-C00469 (ethanol) and BCL2-C00389 (quercetin) pairs, were predicted. CYP1B1, VEGFA, BCL2, and CDKN1A were included in the top 10 DEG-compound pairs. Additionally, 57 metabolites were obtained. In particular, hsa04750 (inflammatory mediator regulation of TRP channels)-C00469 (ethanol) and hsa04152 (AMPK signaling pathway)-C00389 (quercetin) pairs were found in the metabolite network. The results of qPCR showed that the expression of CYP1B1, VEGFA, BCL2, and CDKN1A was consistent with that predicted using bioinformatic analysis.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。