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Identification of key genes and pathways in type 2 diabetes mellitus and vitamin C metabolism through bioinformatics analysis.

BACKGROUND AND OBJECTIVES
Type 2 diabetes mellitus (T2DM) is a major global public health problem. Vitamin C (VC) can improve metabolic dysfunctions associated with T2DM. To establish an association between T2DM and VC metabolism, it is necessary to investigate the biological mechanisms of T2DM and VC. Therefore, the aim of this study was to elucidate the underlying pathways and co-expression networks in T2DM and VC using bioinformatics analysis.


METHODS AND STUDY DESIGN
Data on 15 microarrays about T2DM were downloaded from the Gene Expression Omnibus (GEO) and analyzed for genes using the GEO2R online tool. VC- metabolism associated genes were obtained from the Comparative Toxicogenomics Database (CTD). Differentially expressed genes (DEGs) about T2DM and VC metabolism were identified using the jvenn online software. GO annotation and KEGG pathways for DEGs were enriched using DAVID. STRING and Cytoscape were used to construct PPI network and to predict the interaction relationships between T2DM-associated and VC- metabolism associated DEGs.


RESULTS
We identified 160 DEGs about T2DM and VC from the GEO and CTD. GO, KEGG and PPI network analysis suggested that DEGs might participate in crucial biological processes and pathways, such as negative regulation of apoptotic process, removal of superoxide radicals, and PERK-mediated unfolded protein response, insulin resistance, the TNF signaling pathway, and the FoxO signaling pathway.


CONCLUSIONS
These findings could significantly improve the understanding of the mechanisms underlying impact of VC on T2DM. However, further research is needed to validate our findings.