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A gene expression signature for insulin resistance.

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.

journal_name

Physiol Genomics

journal_title

Physiological genomics

authors

Konstantopoulos N,Foletta VC,Segal DH,Shields KA,Sanigorski A,Windmill K,Swinton C,Connor T,Wanyonyi S,Dyer TD,Fahey RP,Watt RA,Curran JE,Molero JC,Krippner G,Collier GR,James DE,Blangero J,Jowett JB,Walder KR

doi

10.1152/physiolgenomics.00115.2010

subject

Has Abstract

pub_date

2011-02-11 00:00:00

pages

110-20

issue

eissn

1094-8341

issn

1531-2267

pii

physiolgenomics.00115.2010

journal_volume

pub_type

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A gene expression signature for insulin resistance.