Differential network analysis between sex of the genes related to comorbidities of type 2 mellitus diabetes

Background: Some phenotypical changes may be related to changes in the associations among genes. The set of such associations is referred to as gene interaction (or association) networks. An association network represents the set of associations among genes in a given condition. Given two experimental conditions, Differential network analysis (DNA) algorithms analyse these differences by deriving a novel network representing the differences. Such algorithms receive as input experimental gene-expression data of two different conditions (e.g. healthy vs. diseased), then they derive experimental networks of associations among genes and, finally, they analyse differences among networks using statistical approaches. We explore the possibility to study possible rewiring due to sex factors, differently from classical approaches. Methods: We apply DNA methods to evidence possible sex based differences on genes responsible for comorbidities of type 2 diabetes mellitus. Results: Our analysis evidences the presence of differential networks in tissues that may explain the difference in the insurgence of comorbidities between males and females. Conclusion: Main contributions of this work are (1) the definition of a novel framework of analysis able to shed light on the differences between males and females; (2) the identification of differential networks related to diabetes comorbidities.