Generic placeholder image

Current Bioinformatics

Editor-in-Chief

ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

Research Article

Screening Differential Hub Genes Related with the Hypoglycemic Effect of Quercetin Through Data Mining

Author(s): Ji-Ping Wei, Tao Luo*, Yuchen Wang and Wenyu Lu*

Volume 16 , Issue 9 , 2021

Published on: 17 June, 2021

Page: [1152 - 1160] Pages: 9

DOI: 10.2174/1574893616666210617110314

Price: $65

Abstract

Background: The effect of quercetin on blood glucose levels has been widely studied. However, the mechanism of hypoglycemic effect of quercetin remains unclear.

Objective: To elucidate hypoglycemic effect of quercetin, microarray data of GSE38067 dataset have been used to screen Differential Hub Genes (DHGs) by differential expression analysis, weighted gene co-expression network analysis and protein-protein interaction analysis.

Methods: Through systematic data mining in this study, the hypoglycemic effect of quercetin was exerted via affecting the gene expression of seven candidate DHGs, especially Cdkn1a and Cd36 genes, to relieve insulin resistance, prevent oxidative damage and protect pancreatic β-cells in streptozotocin (STZ) induced diabetic mice.

Result: As a result, this work provides a possible way to fight against diabetes by using quercetin as functional food ingredients or medicine.

Conclusion: Microarray data of GSE38067 dataset were analyzed by differential expression analysis, WGCNA, and PPI analysis to identify DHGs of hypoglycemic effect of quercetin.

Keywords: Quercetin, Differential Hub Gene (DHGs), hypoglycemic effect, screening, Weighted Gene Co-Expression NetworkAnalysis (WGCNA), systematic mining.

Graphical Abstract

Rights & Permissions Print Export Cite as
© 2022 Bentham Science Publishers | Privacy Policy