A modular approach to identify differentially expressed genes between men and women for inflammatory diseases

Inflammatory diseases show large differences in susceptibility between men and women. In previous study, genes that showed different expression patterns between patients and healthy controls in males and females were identified using modules in disease-gene interaction networks. In this work, genes were identified using different methods based on gene expressions in public available data sets. By counting the occurrences of genes identified in the interaction network in our results, we showed that they greatly overlap with genes identified by our methods and that the disease gene-interaction networks are able to identify genes that can be identified in a gene expression based analysis as well. Gene expression analysis was implemented in an automatic pipeline, which was designed for a general use. Thereby, future research with similar problems can be simplified. The Rpackages limma and WGCNA were used to identify genes that showed differences in males and females and GO terms and KEGG pathways were used to search for enriched functions of those genes. Further, a difference between males and females was found for systemic lupus erythematosus and Sjögren’s syndrome data sets in the expression of genes belonging to interferon signaling. Interferons are currently examined as drug targets for SLE and a difference between men and women could lead to different results of such a medication. However, the identified genes showed changes in expressions between patients and controls for both men and women. This supports a beneficial effect of such drugs in men and women