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Front. Physiol. | doi: 10.3389/fphys.2018.01841

Biological pathways leading from ANGPTL8 to Diabetes Mellitus - A co-expression network based analysis

  • 1Research Center for Modeling and Simulation, National University of Sciences and Technology, Pakistan
  • 2NUTRIM School of Nutrition and Translational Research in Metabolism, Faculty of Health, Medicine and Life Sciences, Maastricht University, Netherlands
  • 3Maastricht Centre for Systems Biology (MaCSBio) Maastricht University, Netherlands
  • 4Atta-ur-Rahman School of Applied Biosciences, National University of Sciences & Technology, Pakistan

Angiopoietin like protein 8 (ANGPTL8) is a newly identified hormone with unique nature due to its ability to regulate both glucose and lipid metabolic pathways. It is characterized as an important molecular player of insulin induced nutrient storage and utilization pathway during fasting to re-feeding metabolic transition. Several studies have contributed to increase our knowledge regarding its function and mechanism of action. Moreover, its altered expression levels have been observed in Insulin Resistance, Diabetes Mellitus (Types I $\&$ II) and Non Alcohlic Fatty Liver Disease emphasizing its assessment as a drug target. However, there is still a great deal of information that remains to be investigated including its associated biological processes, partner proteins in these processes, its regulators and its association with metabolic pathogenesis. In the current study, the analysis of a transcriptomic data set was performed for functional assessment of ANGPTL8 in liver. Weighted Gene Co-expression Network Analysis coupled with pathway analysis tools was performed to identify genes that are significantly co-expressed with ANGPTL8 in liver and investigate their presence in biological pathways. Gene ontology term enrichment analysis was performed to select the gene ontology classes that over-represent the hepatic ANGPTL8-co-expressed genes. Moreover, the presence of diabetes linked SNPs within the genes set co-expressed with ANGPTL8 was investigated. The co-expressed genes of ANGPTL8 identified in this study (n=460) provides narrowed down list of molecular targets which are either co-regulated with it and/or might be regulation partners at different levels of interaction. These results are coherent with previously demonstrated roles and regulators of ANGPTL8. Specifically, thirteen co-expressed genes (MAPK8, CYP3A4, PIK3R2, PIK3R4,PRKAB2, G6PC, MAP3K11, FLOT1, PIK3C2G, SHC1, SLC16A2, and RAPGEF1) are also present in the literature curated pathway of ANGPTL8 (WP3915\footnote{https://www.wikipathways.org/index.php/Pathway:WP3915}). Moreover, the gene-SNP analysis of highly associated biological processes with ANGPTL8 revealed significant genetic signals associated to Diabetes Mellitus and similar phenotypic traits. It provides meaningful insights on the influencing genes involved and co-expressed in these pathways. Findings of this study have implications in functional characterization of ANGPTL8 with emphasis on the identified genes and pathways and their possible involvement in the pathogenesis of Diabetes Mellitus and Insulin Resistance.

Keywords: ANGPTL8, co-expression network analysis, Diabetes Mellitus, Transcription, Genetic, WikiPathways

Received: 01 Jun 2018; Accepted: 06 Dec 2018.

Edited by:

Pierre De Meyts, de Duve Institute, Belgium

Reviewed by:

Steven G. Gray, St. James's Hospital, Ireland
Mohamed Abu-Farha, Dasman Diabetes Institute, Kuwait  

Copyright: © 2018 Siddiqa, Cirillo, Tareen, Ali, Kutmon, Eijssen, Ahmad, Evelo and Coort. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Jamil Ahmad, Research Center for Modeling and Simulation, National University of Sciences and Technology, Islamabad, Pakistan, dr.ahmad.jamil@gmail.com