Identification of crucial extracellular genes as potential biomarkers in newly diagnosed Type 1 diabetes integrated bioinformatics analysis.

PURPOSE

In this study, we aimed to study the role of extracellular proteins as biomarkers associated with newly diagnosed Type 1 diabetes (NT1D) diagnosis and prognosis.

PATIENTS AND METHODS

We retrieved and analyzed the GSE55098 microarray dataset from the Gene Expression Omnibus (GEO) database. Using R software, we screened out the extracellular protein-differentially expressed genes (EP-DEGs) through several protein-related databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied to describe the role and function of these EP-DEGs. We used the STRING database to construct the interaction of proteins, Cytoscape software to visualize the protein-protein interaction (PPI) networks, and its plugin CytoHubba to identify the crucial genes between PPI networks. Finally, we used the comparative toxicogenomics database (CTD) to evaluate the connection between NT1D with the potential crucial genes and we validated our conclusions with another dataset (GSE33440) and some clinical samples.

RESULTS

We identified 422 DEGs and 122 EP-DEGs from a dataset that includes (12) NT1D patients compared with (10) healthy people. Protein digestion and absorption, toll-like receptor signaling, and T cell receptor signaling were the most meaningful pathways defined by KEGG enrichment analyses. We recognized nine important extracellular genes: , and . CTD analyses showed that , and had higher levels in NT1D and hypoglycemia; while and increased in hyperglycemia. Further verification showed that LCN2, MMP9, TNF and IFNG were elevated in NT1D patients.

CONCLUSION

The nine identified key extracellular genes, particularly , and , may be potential diagnostic biomarkers for NT1D. Our findings provide new insights into the molecular mechanisms and novel therapeutic targets of NT1D.