Literature DB >> 21081660

A gene expression signature for insulin resistance.

Nicky Konstantopoulos1, Victoria C Foletta, David H Segal, Katherine A Shields, Andrew Sanigorski, Kelly Windmill, Courtney Swinton, Tim Connor, Stephen Wanyonyi, Thomas D Dyer, Richard P Fahey, Rose A Watt, Joanne E Curran, Juan-Carlos Molero, Guy Krippner, Greg R Collier, David E James, John Blangero, Jeremy B Jowett, Ken R Walder.   

Abstract

Insulin resistance is a heterogeneous disorder caused by a range of genetic and environmental factors, and we hypothesize that its etiology varies considerably between individuals. This heterogeneity provides significant challenges to the development of effective therapeutic regimes for long-term management of type 2 diabetes. We describe a novel strategy, using large-scale gene expression profiling, to develop a gene expression signature (GES) that reflects the overall state of insulin resistance in cells and patients. The GES was developed from 3T3-L1 adipocytes that were made "insulin resistant" by treatment with tumor necrosis factor-α (TNF-α) and then reversed with aspirin and troglitazone ("resensitized"). The GES consisted of five genes whose expression levels best discriminated between the insulin-resistant and insulin-resensitized states. We then used this GES to screen a compound library for agents that affected the GES genes in 3T3-L1 adipocytes in a way that most closely resembled the changes seen when insulin resistance was successfully reversed with aspirin and troglitazone. This screen identified both known and new insulin-sensitizing compounds including nonsteroidal anti-inflammatory agents, β-adrenergic antagonists, β-lactams, and sodium channel blockers. We tested the biological relevance of this GES in participants in the San Antonio Family Heart Study (n = 1,240) and showed that patients with the lowest GES scores were more insulin resistant (according to HOMA_IR and fasting plasma insulin levels; P < 0.001). These findings show that GES technology can be used for both the discovery of insulin-sensitizing compounds and the characterization of patients into subtypes of insulin resistance according to GES scores, opening the possibility of developing a personalized medicine approach to type 2 diabetes.

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Year:  2010        PMID: 21081660     DOI: 10.1152/physiolgenomics.00115.2010

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


  11 in total

1.  3T3-L1 adipocytes display phenotypic characteristics of multiple adipocyte lineages.

Authors:  Shona Morrison; Sean L McGee
Journal:  Adipocyte       Date:  2015-04-18       Impact factor: 4.534

2.  Integrating genomic analysis with the genetic basis of gene expression: preliminary evidence of the identification of causal genes for cardiovascular and metabolic traits related to nutrition in Mexicans.

Authors:  Raúl A Bastarrachea; Esther C Gallegos-Cabriales; Edna J Nava-González; Karin Haack; V Saroja Voruganti; Jac Charlesworth; Hugo A Laviada-Molina; Rosa A Veloz-Garza; Velia Margarita Cardenas-Villarreal; Salvador B Valdovinos-Chavez; Patricia Gomez-Aguilar; Guillermo Meléndez; Juan Carlos López-Alvarenga; Harald H H Göring; Shelley A Cole; John Blangero; Anthony G Comuzzie; Jack W Kent
Journal:  Adv Nutr       Date:  2012-07-01       Impact factor: 8.701

Review 3.  Role of protein carbonylation in diabetes.

Authors:  Markus Hecker; Andreas H Wagner
Journal:  J Inherit Metab Dis       Date:  2017-11-06       Impact factor: 4.982

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Authors:  George H Gauss; Mark D Kleven; Anoop K Sendamarai; Mark D Fleming; C Martin Lawrence
Journal:  J Biol Chem       Date:  2013-06-03       Impact factor: 5.157

Review 5.  STEAP4 and insulin resistance.

Authors:  Xiaoling Chen; Zhiqing Huang; Bo Zhou; Huan Wang; Gang Jia; Guangmang Liu; Hua Zhao
Journal:  Endocrine       Date:  2014-03-14       Impact factor: 3.633

Review 6.  Insulin resistance and environmental pollutants: experimental evidence and future perspectives.

Authors:  Tine L M Hectors; Caroline Vanparys; Luc F Van Gaal; Philippe G Jorens; Adrian Covaci; Ronny Blust
Journal:  Environ Health Perspect       Date:  2013-09-20       Impact factor: 9.031

7.  Methazolamide is a new hepatic insulin sensitizer that lowers blood glucose in vivo.

Authors:  Nicky Konstantopoulos; Juan C Molero; Sean L McGee; Briana Spolding; Tim Connor; Melissa de Vries; Stephen Wanyonyi; Richard Fahey; Shona Morrison; Courtney Swinton; Sharon Jones; Adrian Cooper; Lucia Garcia-Guerra; Victoria C Foletta; Guy Krippner; Sofianos Andrikopoulos; Ken R Walder
Journal:  Diabetes       Date:  2012-05-14       Impact factor: 9.461

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Journal:  PLoS One       Date:  2013-10-23       Impact factor: 3.240

9.  CMap analysis identifies Atractyloside as a potential drug candidate for type 2 diabetes based on integration of metabolomics and transcriptomics.

Authors:  Hailong Li; Xiaodong Shi; Hua Jiang; Junren Kang; Miao Yu; Qifei Li; Kang Yu; Zhengju Chen; Hui Pan; Wei Chen
Journal:  J Cell Mol Med       Date:  2020-05-29       Impact factor: 5.310

10.  PGC-1α and PGC-1β Increase Protein Synthesis via ERRα in C2C12 Myotubes.

Authors:  Erin L Brown; Victoria C Foletta; Craig R Wright; Patricio V Sepulveda; Nicky Konstantopoulos; Andrew Sanigorski; Paul Della Gatta; David Cameron-Smith; Anastasia Kralli; Aaron P Russell
Journal:  Front Physiol       Date:  2018-09-25       Impact factor: 4.566

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