Temporal gene expression analysis of Sjögren's syndrome in C57BL/6.NOD-Aec1Aec2 mice based on microarray time-series data using an improved empirical Bayes approach.

Abstract

The purpose of this study was to analyze the temporal gene expression in salivary and lacrimal glands of Sjögren's syndrome (SS) based on time-series microarray data. We downloaded gene expression data GSE15640 and GSE48139 from gene expression omnibus and identified differentially expressed genes (DEGs) at varying time points using a modified Bayes analysis. Gene clustering was applied to analyze the expression differences in time series of the DEGs. Protein-protein interaction networks were used for searching the hub genes, and gene ontology (GO) and KEGG pathways were applied to analyze the DEGs at a functional level. A total of 744 and 1,490 DEGs were screened out from the salivary glands and lacrimal glands, respectively. Among these genes, 194 were overlapped between salivary glands and lacrimal glands, and these genes were compartmentalized into six clusters with different expression profiles. The GO terms of intracellular transport, protein transport and protein localization were significantly enriched by DEGs in salivary glands; while in the lacrimal glands, DEGs were significantly enriched in protein localization, establishment of protein localization and protein transport. Our results suggest that the SS pathogenesis was significantly different in time series in the salivary and lacrimal glands. The DEGs whose expressions may correlate with molecular mechanisms of SS in our study might provide new insight into the underlying cause or regulation of this disease.