Background: Molecular characterization of insulin resistance, a growing health issue
worldwide, will help to develop novel strategies and accurate biomarkers for disease diagnosis and
Objective: Integrative analysis of gene expression profiling and gene regulatory network was exploited
to identify potential biomarkers early in the development of insulin resistance.
Methods: RNA was isolated from livers of animals at three weeks of age, and whole-genome expression
profiling was performed and analyzed with Agilent mouse 4×44K microarrays. Differentially
expressed genes were subsequently validated by qRT-PCR. Functional characterizations of
genes and their interactions were performed by Gene Ontology (GO) analysis and gene regulatory
network (GRN) analysis.
Results: A total of 197 genes were found to be differentially expressed by fold
change ≥2 and P < 0.05 in BKS-db +/+ mice relative to sex and age-matched controls. Functional
analysis suggested that these differentially expressed genes were enriched in the regulation of
phosphorylation and generation of precursor metabolites which are closely associated with insulin
resistance. Then a gene regulatory network associated with insulin resistance (IRGRN) was constructed
by integration of these differentially expressed genes and known human protein-protein
interaction network. The principal component analysis demonstrated that 67 genes in IRGRN
could clearly distinguish insulin resistance from the non-disease state. Some of these candidate
genes were further experimentally validated by qRT-PCR, highlighting the predictive role as biomarkers
in insulin resistance.
Conclusion: Our study provides new insight into the pathogenesis and treatment of insulin resistance
and also reveals potential novel molecular targets and diagnostic biomarkers for insulin resistance.