TY - JOUR
T1 - Cellular signaling pathways in insulin resistance-systems biology analyses of microarray dataset reveals new drug target gene signatures of type 2 diabetes mellitus
AU - Muhammad, Syed Aun
AU - Raza, Waseem
AU - Nguyen, Thanh
AU - Bai, Baogang
AU - Wu, Xiaogang
AU - Chen, Jake
N1 - Publisher Copyright:
© 2017 Muhammad, Raza, Nguyen, Bai, Wu and Chen.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Drug targets
KW - Gene signatures
KW - Microarray dataset
KW - Pathways enrichment analysis
KW - T2DM
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U2 - 10.3389/fphys.2017.00013
DO - 10.3389/fphys.2017.00013
M3 - Article
C2 - 28179884
AN - SCOPUS:85011931512
SN - 1664-042X
VL - 8
JO - Frontiers in Physiology
JF - Frontiers in Physiology
IS - JAN
M1 - 13
ER -