A Network-Based Meta-analysis Strategy for the Selection of Potential Gene Modules in Type 2 Diabetes

We propose an integrative network-based meta-analysis strategy to enable the selection of potential gene markers for one of the most prevalent diseases worldwide, Type 2 diabetes (T2D), formally known as the non-insulin dependent diabetes mellitus. Comprehensive elucidation of the genes regulated through this disorder and their wiring will provide a more complete understanding of the overall gene network topology and their role in disease progression and treatment. The proposed strategy was able to find conservative gene modules which play interesting role in T2D, pointing to gene markers such as NR3C1, ADIPOR1 and CDC123. Network-based meta-analysis by enumerating conserved gene modules pave a practical approach to the identification of candidate gene markers across several related transcriptomic studies. The NEMESIS R pipeline for network-based meta-analysis is also provided.