Systems biology approach reveals genome to phenome correlation in type 2 diabetes.

Genome-wide association studies (GWASs) have discovered association of several loci with Type 2 diabetes (T2D), a common complex disease characterized by impaired insulin secretion by pancreatic β cells and insulin signaling in target tissues. However, effect of genetic risk variants on continuous g...

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Autores principales:	Priyanka Jain, Saurabh Vig, Malabika Datta, Dinesh Jindel, Ashok Kumar Mathur, Sandeep Kumar Mathur, Abhay Sharma
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/4241b3e8725845e2bb1d7f883d0ba27b
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spelling	oai:doaj.org-article:4241b3e8725845e2bb1d7f883d0ba27b2021-11-18T08:02:28ZSystems biology approach reveals genome to phenome correlation in type 2 diabetes.1932-620310.1371/journal.pone.0053522https://doaj.org/article/4241b3e8725845e2bb1d7f883d0ba27b2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23308243/?tool=EBIhttps://doaj.org/toc/1932-6203Genome-wide association studies (GWASs) have discovered association of several loci with Type 2 diabetes (T2D), a common complex disease characterized by impaired insulin secretion by pancreatic β cells and insulin signaling in target tissues. However, effect of genetic risk variants on continuous glycemic measures in nondiabetic subjects mainly elucidates perturbation of insulin secretion. Also, the disease associated genes do not clearly converge on functional categories consistent with the known aspects of T2D pathophysiology. We used a systems biology approach to unravel genome to phenome correlation in T2D. We first examined enrichment of pathways in genes identified in T2D GWASs at genome-wide or lower levels of significance. Genes at lower significance threshold showed enrichment of insulin secretion related pathway. Notably, physical and genetic interaction network of these genes showed robust enrichment of insulin signaling and other T2D pathophysiology related pathways including insulin secretion. The network also overrepresented genes reported to interact with insulin secretion and insulin action targeting antidiabetic drugs. The drug interacting genes themselves showed overrepresentation of insulin signaling and other T2D relevant pathways. Next, we generated genome-wide expression profiles of multiple insulin responsive tissues from nondiabetic and diabetic patients. Remarkably, the differentially expressed genes showed significant overlap with the network genes, with the intersection showing enrichment of insulin signaling and other pathways consistent with T2D pathophysiology. Literature search led our genomic, interactomic, transcriptomic and toxicogenomic evidence to converge on TGF-beta signaling, a pathway known to play a crucial role in pancreatic islets development and function, and insulin signaling. Cumulatively, we find that GWAS genes relate directly to insulin secretion and indirectly, through collaborating with other genes, to insulin resistance. This seems to support the epidemiological evidence that environmentally triggered insulin resistance interacts with genetically programmed β cell dysfunction to precipitate diabetes.Priyanka JainSaurabh VigMalabika DattaDinesh JindelAshok Kumar MathurSandeep Kumar MathurAbhay SharmaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 1, p e53522 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Priyanka Jain Saurabh Vig Malabika Datta Dinesh Jindel Ashok Kumar Mathur Sandeep Kumar Mathur Abhay Sharma Systems biology approach reveals genome to phenome correlation in type 2 diabetes.
description	Genome-wide association studies (GWASs) have discovered association of several loci with Type 2 diabetes (T2D), a common complex disease characterized by impaired insulin secretion by pancreatic β cells and insulin signaling in target tissues. However, effect of genetic risk variants on continuous glycemic measures in nondiabetic subjects mainly elucidates perturbation of insulin secretion. Also, the disease associated genes do not clearly converge on functional categories consistent with the known aspects of T2D pathophysiology. We used a systems biology approach to unravel genome to phenome correlation in T2D. We first examined enrichment of pathways in genes identified in T2D GWASs at genome-wide or lower levels of significance. Genes at lower significance threshold showed enrichment of insulin secretion related pathway. Notably, physical and genetic interaction network of these genes showed robust enrichment of insulin signaling and other T2D pathophysiology related pathways including insulin secretion. The network also overrepresented genes reported to interact with insulin secretion and insulin action targeting antidiabetic drugs. The drug interacting genes themselves showed overrepresentation of insulin signaling and other T2D relevant pathways. Next, we generated genome-wide expression profiles of multiple insulin responsive tissues from nondiabetic and diabetic patients. Remarkably, the differentially expressed genes showed significant overlap with the network genes, with the intersection showing enrichment of insulin signaling and other pathways consistent with T2D pathophysiology. Literature search led our genomic, interactomic, transcriptomic and toxicogenomic evidence to converge on TGF-beta signaling, a pathway known to play a crucial role in pancreatic islets development and function, and insulin signaling. Cumulatively, we find that GWAS genes relate directly to insulin secretion and indirectly, through collaborating with other genes, to insulin resistance. This seems to support the epidemiological evidence that environmentally triggered insulin resistance interacts with genetically programmed β cell dysfunction to precipitate diabetes.
format	article
author	Priyanka Jain Saurabh Vig Malabika Datta Dinesh Jindel Ashok Kumar Mathur Sandeep Kumar Mathur Abhay Sharma
author_facet	Priyanka Jain Saurabh Vig Malabika Datta Dinesh Jindel Ashok Kumar Mathur Sandeep Kumar Mathur Abhay Sharma
author_sort	Priyanka Jain
title	Systems biology approach reveals genome to phenome correlation in type 2 diabetes.
title_short	Systems biology approach reveals genome to phenome correlation in type 2 diabetes.
title_full	Systems biology approach reveals genome to phenome correlation in type 2 diabetes.
title_fullStr	Systems biology approach reveals genome to phenome correlation in type 2 diabetes.
title_full_unstemmed	Systems biology approach reveals genome to phenome correlation in type 2 diabetes.
title_sort	systems biology approach reveals genome to phenome correlation in type 2 diabetes.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/4241b3e8725845e2bb1d7f883d0ba27b
work_keys_str_mv	AT priyankajain systemsbiologyapproachrevealsgenometophenomecorrelationintype2diabetes AT saurabhvig systemsbiologyapproachrevealsgenometophenomecorrelationintype2diabetes AT malabikadatta systemsbiologyapproachrevealsgenometophenomecorrelationintype2diabetes AT dineshjindel systemsbiologyapproachrevealsgenometophenomecorrelationintype2diabetes AT ashokkumarmathur systemsbiologyapproachrevealsgenometophenomecorrelationintype2diabetes AT sandeepkumarmathur systemsbiologyapproachrevealsgenometophenomecorrelationintype2diabetes AT abhaysharma systemsbiologyapproachrevealsgenometophenomecorrelationintype2diabetes
_version_	1718422598567591936

Systems biology approach reveals genome to phenome correlation in type 2 diabetes.

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