Cellular Signaling Pathways in Insulin Resistance-Systems Biology Analyses of Microarray Dataset Reveals New Drug Target Gene Signatures of Type 2 Diabetes Mellitus.
Purpose:Type 2 diabetes mellitus (T2DM) is a chronic and metabolic disorder affecting large set of population of the world. To widen the scope of understanding of genetic causes of this disease, we performed interactive and toxicogenomic based systems biology study to find potential T2DM related genes after cDNA differential analysis.Methods:From the list of 50-differential expressed genes (p< 0.05), we found 9-T2DM related genes using extensive data mapping. In our constructed gene-network, T2DM-related differentially expressed seeder genes (9-genes) are found to interact with functionally related gene signatures (31-genes). The genetic interaction network of both T2DM-associated seeder as well as signature genes generally relates well with the disease condition based on toxicogenomic and data curation.Results:These networks showed significant enrichment of insulin signaling, insulin secretion and other T2DM-related pathways including JAK-STAT, MAPK, TGF, Toll-like receptor, p53 and mTOR, adipocytokine, FOXO, PPAR, P13-AKT, and triglyceride metabolic pathways. We found some enriched pathways that are common in different conditions. We recognized 11-signaling pathways as a connecting link between gene signatures in insulin resistance and T2DM. Notably, in the drug-gene network, the interacting genes showed significant overlap with 13-FDA approved and few non-approved drugs. This study demonstrates the value of systems genetics for identifying 18 potential genes associated with T2DM that are probable drug targets.Conclusions:This integrative and network based approaches for finding variants in genomic data expect to accelerate identification of new drug target molecules for different diseases and can speed up drug discovery outcomes.
Institute of Molecular Biology and Biotechnology, Bahauddin Zakariya UniversityMultan, Pakistan; Institute of Biopharmaceutical Informatics and Technologies, Wenzhou Medical UniversityWenzhou, China; Wenzhou Medical University, 1st Affiliate Hospital WenzhouWenzhou, China.
Syed Aun
SA
Muhammad
Institute of Molecular Biology and Biotechnology, Bahauddin Zakariya University Multan, Pakistan.
Waseem
W
Raza
Institute of Biopharmaceutical Informatics and Technologies, Wenzhou Medical UniversityWenzhou, China; Wenzhou Medical University, 1st Affiliate Hospital WenzhouWenzhou, China; Department of Computer and Information Science, Purdue UniversityIndianapolis, IN, USA.
Thanh
T
Nguyen
Institute of Biopharmaceutical Informatics and Technologies, Wenzhou Medical University Wenzhou, China.
Baogang
B
Bai
Institute for Systems Biology Seattle, WA, USA.
Xiaogang
X
Wu
Institute of Biopharmaceutical Informatics and Technologies, Wenzhou Medical UniversityWenzhou, China; Wenzhou Medical University, 1st Affiliate Hospital WenzhouWenzhou, China; Department of Computer and Information Science, Purdue UniversityIndianapolis, IN, USA; Indiana Center for Systems Biology and Personalized Medicine, Indiana University-Purdue UniversityIndianapolis, IN, USA; Informatics Institute, School of Medicine, The University of AlabamaBirmingham, AL, USA.
Jake
J
Chen
T2DM; drug targets; gene signatures; microarray dataset; pathways enrichment analysis