@article{7eef878bef344879b7303f3b1d4b1d33,
title = "NURR1 activation in skeletal muscle controls systemic energy homeostasis",
abstract = "Skeletal muscle plays a central role in the control of metabolism and exercise tolerance. Analysis of muscle enhancers activated after exercise in mice revealed the orphan nuclear receptor NURR1/NR4A2 as a prominent component of exercise-responsive enhancers. We show that exercise enhances the expression of NURR1, and transgenic overexpression of NURR1 in skeletal muscle enhances physical performance in mice. NURR1 expression in skeletal muscle is also sufficient to prevent hyperglycemia and hepatic steatosis, by enhancing muscle glucose uptake and storage as glycogen. Furthermore, treatment of obese mice with putative NURR1 agonists increases energy expenditure, improves glucose tolerance, and confers a lean phenotype, mimicking the effects of exercise. These findings identify a key role for NURR1 in governance of skeletal muscle glucose metabolism, and reveal a transcriptional link between exercise and metabolism. Our findings also identify NURR1 agonists as possible exercise mimetics with the potential to ameliorate obesity and other metabolic abnormalities.",
keywords = "Exercise, Mediator complex, Metabolic syndrome, Nuclear receptor, Obesity",
author = "Leonela Amoasii and Efrain Sanchez-Ortiz and Teppei Fujikawa and Elmquist, {Joel K.} and Rhonda Bassel-Duby and Olson, {Eric N.}",
note = "Funding Information: We thank John Shelton for his help with histology. We thank Joyce Repa for her assistance with lipid absorption experiments. We thank Beibei Chen and Wenduo Ye for their expertise and assistance with bioinformatics analysis. We also thank Spencer Barnes (Department of Bioinformatics) for help with bioinformatics. We thank Jose Cabrera, Cheryl Nolen, John McAnally, Dylan Tennison, Evelyn Tennison, and Jennifer Brown for their assistance. We appreciate the services of the UT Southwestern Mouse Metabolic Phenotyping Core Facility. This work was supported by grants from the NIH (AR-067294, HL-130253, and DK-099653), American Diabetes Association (1-16-PDF-006 to L.A.), American Heart Association (14SDG17950008 to T.F.), and Robert A. Welch Foundation (1-0025 to E.N.O.). Funding Information: ACKNOWLEDGMENTS. We thank John Shelton for his help with histology. We thank Joyce Repa for her assistance with lipid absorption experiments. We thank Beibei Chen and Wenduo Ye for their expertise and assistance with bioinformatics analysis. We also thank Spencer Barnes (Department of Bioinformatics) for help with bioinformatics. We thank Jose Cabrera, Cheryl Nolen, John McAnally, Dylan Tennison, Evelyn Tennison, and Jennifer Brown for their assistance. We appreciate the services of the UT Southwestern Mouse Metabolic Phenotyping Core Facility. This work was supported by grants from the NIH (AR-067294, HL-130253, and DK-099653), American Diabetes Association (1-16-PDF-006 to L.A.), American Heart Association (14SDG17950008 to T.F.), and Robert A. Welch Foundation (1-0025 to E.N.O.). Publisher Copyright: {\textcopyright} 2019 National Academy of Sciences. All rights reserved.",
year = "2019",
doi = "10.1073/pnas.1902490116",
language = "English (US)",
volume = "166",
pages = "11299--11308",
journal = "Proceedings of the National Academy of Sciences of the United States of America",
issn = "0027-8424",
publisher = "National Academy of Sciences",
number = "23",
}