Models

Dataset Information

0

Brännmark2013 - Insulin signalling in human adipocytes (normal condition)


ABSTRACT: Brännmark2013 - Insulin signalling in human adipocytes (normal condition) The paper describes insulin signalling in human adipocytes under normal and diabetic states using mathematical models based on experimental data. This model corresponds to insulin signalling under normal condtion This model is described in the article: Insulin Signaling in Type 2 Diabetes: EXPERIMENTAL AND MODELING ANALYSES REVEAL MECHANISMS OF INSULIN RESISTANCE IN HUMAN ADIPOCYTES. Brännmark C, Nyman E, Fagerholm S, Bergenholm L, Ekstrand EM, Cedersund G, Strålfors P. J Biol Chem. 2013 Apr 5;288(14):9867-80. Abstract: Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems level mechanistic understanding of insulin resistance, using systems wide and internally consistent data from human adipocytes. Based on quantitative steady-state and dynamic time course data on signaling intermediaries, normally and in diabetes, we developed a dynamic mathematical model of insulin signaling. The model structure and parameters are identical in the normal and diabetic states of the model, except for three parameters that change in diabetes: (i) reduced concentration of insulin receptor, (ii) reduced concentration of insulin-regulated glucose transporter GLUT4, and (iii) changed feedback from mammalian target of rapamycin in complex with raptor (mTORC1). Modeling reveals that at the core of insulin resistance in human adipocytes is attenuation of a positive feedback from mTORC1 to the insulin receptor substrate-1, which explains reduced sensitivity and signal strength throughout the signaling network. Model simulations with inhibition of mTORC1 are comparable with experimental data on inhibition of mTORC1 using rapamycin in human adipocytes. We demonstrate the potential of the model for identification of drug targets, e.g. increasing the feedback restores insulin signaling, both at the cellular level and, using a multilevel model, at the whole body level. Our findings suggest that insulin resistance in an expanded adipose tissue results from cell growth restriction to prevent cell necrosis. This model is hosted on BioModels Database and identified by: MODEL1304190000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

DISEASE(S): Type 2 Diabetes Mellitus

SUBMITTER: Elin Nyman  

PROVIDER: BIOMD0000000448 | BioModels | 2024-09-02

REPOSITORIES: BioModels

altmetric image

Publications

Insulin signaling in type 2 diabetes: experimental and modeling analyses reveal mechanisms of insulin resistance in human adipocytes.

Brännmark Cecilia C   Nyman Elin E   Fagerholm Siri S   Bergenholm Linnéa L   Ekstrand Eva-Maria EM   Cedersund Gunnar G   Strålfors Peter P  

The Journal of biological chemistry 20130211 14


Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems level mechanistic understanding of insulin resistance, using systems wide and internally consistent data from human adipocytes. Based on quantitative steady-state and dynamic time course data on signaling intermediaries, normally an  ...[more]

Similar Datasets

2024-09-02 | BIOMD0000000449 | BioModels
2022-12-05 | MTBLS6505 | MetaboLights
2022-06-17 | GSE201908 | GEO
2019-06-21 | GSE133099 | GEO
2017-03-29 | MSV000080798 | MassIVE
2016-02-02 | PXD003095 | Pride
2019-06-06 | GSE132261 | GEO
2011-03-15 | E-GEOD-27784 | biostudies-arrayexpress
2010-11-30 | E-GEOD-24422 | biostudies-arrayexpress
2015-05-18 | E-GEOD-58952 | biostudies-arrayexpress