Constructing regulatory networks to identify biomarkers for insulin resistance

Insulin resistance (IR) is a physiological condition in which cells fail to respond to the insulin hormone. Despite advances in the diagnosis and treatment of IR, novel molecular targets are still needed to improve the accuracy of diagnosis and the outcomes of therapy. Here, we present a systems approach to identify molecular biomarkers for IR. We downloaded the gene expression profile of IR from the Gene Expression Omnibus (GEO), generated a regulatory network by mapping co-expressed genes to transcription factors (TFs) and calculated the regulatory impact factor of each transcription factor. Finally, we selected a list of potential molecular targets that could be used as therapeutic targets or diagnostic biomarkers, including ETS1, AR, ESR1 and Myc. Our studies identified multiple TFs that could play an important role in the pathogenesis of IR and provided a systems understanding of the potential relationships among these genes. Our study has the potential to aid in the understanding of IR and provides a basis for IR biomarker discovery.