Type 2 diabetes (T2D) is a chronic complex disease which is difficult to cure using existing drugs so new, it is essential to identify novel disease-associated genes/proteins which can be targeted for effective treatment. In this study, we identified that key genes (proteins) whose involvement in T2D have been mined from multiple level of evidence, that is, their presence in large-scale meta-analysis of T2D, and insulin resistance (IR) gene-expression datasets, their reported association with T2D, their enrichment in T2D-implicated cellular pathways, as well as their topological positions in the disease-network. We have carried out probably the most comprehensive meta-analysis of T2D, and IR gene expression datasets to identify meta-signature of genes. These genes were further subjected to pathway- and network-based analysis to extract a small number of genes. We foresee that modulation of their protein-products by small molecules could be a promising strategy for therapy. We expect that our identified genes can be validated by qPCR and/or western blot experiments and, further, investigated as their potential role in T2D and IR. Our approach is generic and can be used for other disorders.
Key words: Type 2 Diabetes, Insulin resistance, Meta-analysis, Network Biology, Microarray data, hyperglycemia
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