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  4. Development of a physiological insulin resistance model in human stem cell–derived adipocytes

Development of a physiological insulin resistance model in human stem cell–derived adipocytes

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sword-2022-12-12T14:37:24.original.xml (130 B)
Original SWORD entry document
Author(s)
Friesen, Max
•
Khalil, Andrew S
•
Barrasa, M Inmaculada
•
Jeppesen, Jacob F
•
Mooney, David J
•
Jaenisch, Rudolf
Date Issued
2022
Journal
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Citation
Friesen, Max, Khalil, Andrew S, Barrasa, M Inmaculada, Jeppesen, Jacob F, Mooney, David J et al. 2022. "Development of a physiological insulin resistance model in human stem cell–derived adipocytes." Science Advances, 8 (24).
Version
Final published version
Abstract
Adipocytes are key regulators of human metabolism, and their dysfunction in insulin signaling is central to metabolic diseases including type II diabetes mellitus (T2D). However, the progression of insulin resistance into T2D is still poorly understood. This limited understanding is due, in part, to the dearth of suitable models of insulin signaling in human adipocytes. Traditionally, adipocyte models fail to recapitulate in vivo insulin signaling, possibly due to exposure to supraphysiological nutrient and hormone conditions. We developed a protocol for human pluripotent stem cell–derived adipocytes that uses physiological nutrient conditions to produce a potent insulin response comparable to in vivo adipocytes. After systematic optimization, this protocol allows robust insulin-stimulated glucose uptake and transcriptional insulin response. Furthermore, exposure of sensitized adipocytes to physiological hyperinsulinemia dampens insulin-stimulated glucose uptake and dysregulates insulin-responsive transcription. Overall, our methodology provides a novel platform for the mechanistic study of insulin signaling and resistance using human pluripotent stem cell–derived adipocytes.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Creative Commons Attribution NonCommercial License 4.0
https://creativecommons.org/licenses/by-nc/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/146840
DOI of Published Version
https://doi.org/10.1126/SCIADV.ABN7298
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