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Rout M, Lulu S S. Molecular and disease association of gestational diabetes mellitus affected mother and placental datasets reveal a strong link between insulin growth factor (IGF) genes in amino acid transport pathway: A network biology approach. J Cell Biochem. 2018;doi: 10.1002/jcb.27418.
Rout, M., & Lulu S, S. (2018). Molecular and disease association of gestational diabetes mellitus affected mother and placental datasets reveal a strong link between insulin growth factor (IGF) genes in amino acid transport pathway: A network biology approach. Journal of cellular biochemistry, . https://doi.org/10.1002/jcb.27418
Rout, Madhusmita, and Lulu S, Sajitha. "Molecular and disease association of gestational diabetes mellitus affected mother and placental datasets reveal a strong link between insulin growth factor (IGF) genes in amino acid transport pathway: A network biology approach." Journal of cellular biochemistry vol. (2018). doi: https://doi.org/10.1002/jcb.27418
Rout M, Lulu S S. Molecular and disease association of gestational diabetes mellitus affected mother and placental datasets reveal a strong link between insulin growth factor (IGF) genes in amino acid transport pathway: A network biology approach. J Cell Biochem. 2018 Oct 18; doi: 10.1002/jcb.27418. Epub 2018 Oct 18. PMID: 30335885.
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J Cell Biochem. 2018 Oct 18; doi: 10.1002/jcb.27418. Epub 2018 Oct 18.

Molecular and disease association of gestational diabetes mellitus affected mother and placental datasets reveal a strong link between insulin growth factor (IGF) genes in amino acid transport pathway: A network biology approach.

Journal of cellular biochemistry

Madhusmita Rout, Sajitha Lulu S

Affiliations

  1. Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.

PMID: 30335885 DOI: 10.1002/jcb.27418

Abstract

Discerning the relationship between molecules involved in diseases based on their underlying biological mechanisms is one of the greatest challenges in therapeutic development today. Gestational diabetes mellitus (GDM) is one of the most common complications during pregnancy, which adversely affects both mothers and offspring during and after pregnancy. We have constructed two datasets of (GDM associated genes from affected mother and placenta to systematically analyze and evaluate their interactions like gene-gene, gene-protein, gene-microRNA (miRNA), gene-transcription factors, and gene-associated diseases to enhance our current knowledge, which may lead to further advancements in disease diagnosis, prognosis, and treatment. The results identify the key genes with respect to maternal dataset as insulin receptor, insulin (INS), leptin (LEP), glucokinase, and hepatocyte nuclear factor 1 alpha, whereas from placenta include insulin-like growth factor 1, growth hormone receptor, and breast cancer anti-estrogen resistance protein 1, which are found to be highly enriched in pancreas, ovary, adipocyte, heart, and placental tissues. The key transcription factors include Sp1 transcription factor, pancreatic and duodenal homeobox 1, and hepatocyte nuclear factor 4 alpha, whereas miRNA includes has-miR-5699-5p and has-miR-3158-3p. The study also reveals that GDM has associations with diseases like type I and II diabetes mellitus, obesity, and preeclampsia. More significantly, we could trace out a significant connection between the key molecules like LEP and placental growth hormone from mother and placental dataset, which plays a critical role in INS secretion, INS signaling, and β-cell dysfunction pathways.

© 2018 Wiley Periodicals, Inc.

Keywords: gene regulatory networks; gestational diabetes mellitus (GDM); microRNAs (miRNAs); neonatal; transcription factors (TFs)

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