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Analysis of In Vitro Insulin-Resistance Models and Their Physiological Relevance to In Vivo Diet-Induced Adipose Insulin Resistance

Author(s)
Lo, Kinyui Alice; Labadorf, Adam; Kennedy, Norman J.; Han, Myoung Sook; Yap, Yoon Sing; Matthews, Bryan; Xin, Xiaofeng; Sun, Lei; Davis, Roger J.; Lodish, Harvey F.; Fraenkel, Ernest; ... Show more Show less
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Abstract
Diet-induced obesity (DIO) predisposes individuals to insulin resistance, and adipose tissue has a major role in the disease. Insulin resistance can be induced in cultured adipocytes by a variety of treatments, but what aspects of the in vivo responses are captured by these models remains unknown. We use global RNA sequencing to investigate changes induced by TNF-α, hypoxia, dexamethasone, high insulin, and a combination of TNF-α and hypoxia, comparing the results to the changes in white adipose tissue from DIO mice. We found that different in vitro models capture distinct features of DIO adipose insulin resistance, and a combined treatment of TNF-α and hypoxia is most able to mimic the in vivo changes. Using genome-wide DNase I hypersensitivity followed by sequencing, we further examined the transcriptional regulation of TNF-α-induced insulin resistance, and we found that C/EPBβ is a potential key regulator of adipose insulin resistance.
Date issued
2013-10
URI
http://hdl.handle.net/1721.1/90558
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Biological Engineering; Massachusetts Institute of Technology. Department of Biology; Whitehead Institute for Biomedical Research
Journal
Cell Reports
Publisher
Elsevier
Citation
Lo, Kinyui Alice, Adam Labadorf, Norman J. Kennedy, Myoung Sook Han, Yoon Sing Yap, Bryan Matthews, Xiaofeng Xin, et al. “Analysis of In Vitro Insulin-Resistance Models and Their Physiological Relevance to In Vivo Diet-Induced Adipose Insulin Resistance.” Cell Reports 5, no. 1 (October 2013): 259–270.
Version: Final published version
ISSN
22111247

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