@article{bb2afad0068140fe87434af3e0f811ed,
title = "A PRDM16-Driven Metabolic Signal from Adipocytes Regulates Precursor Cell Fate",
abstract = "The precursor cells for metabolically beneficial beige adipocytes can alternatively become fibrogenic and contribute to adipose fibrosis. We found that cold exposure or β3-adrenergic agonist treatment of mice decreased the fibrogenic profile of precursor cells and stimulated beige adipocyte differentiation. This fibrogenic-to-adipogenic transition was impaired in aged animals, correlating with reduced adipocyte expression of the transcription factor PRDM16. Genetic loss of Prdm16 mimicked the effect of aging in promoting fibrosis, whereas increasing PRDM16 in aged mice decreased fibrosis and restored beige adipose development. PRDM16-expressing adipose cells secreted the metabolite β-hydroxybutyrate (BHB), which blocked precursor fibrogenesis and facilitated beige adipogenesis. BHB catabolism in precursor cells, mediated by BDH1, was required for beige fat differentiation in vivo. Finally, dietary BHB supplementation in aged animals reduced adipose fibrosis and promoted beige fat formation. Together, our results demonstrate that adipocytes secrete a metabolite signal that controls beige fat remodeling.",
keywords = "BDH1, PRDM16, UCP1, adipose fibrosis, beige fat, beta hydroxybutyrate, brown fat, fibro-adipogenic progenitor",
author = "Wenshan Wang and Jeff Ishibashi and Sophie Trefely and Mengle Shao and Cowan, {Alexis J.} and Alexander Sakers and Lim, {Hee Woong} and Sean O'Connor and Doan, {Mary T.} and Paul Cohen and Baur, {Joseph A.} and King, {M. Todd} and Veech, {Richard L.} and Won, {Kyoung Jae} and Rabinowitz, {Joshua D.} and Snyder, {Nathaniel W.} and Gupta, {Rana K.} and Patrick Seale",
note = "Funding Information: We thank Lan Cheng and the Histology and Gene Expression Core of the Penn Cardiovascular Institute for immunohistochemistry and the Functional Genomics Core and Metabolomics Core of the Penn Diabetes and Endocrinology Center (DK19525) for high-throughput sequencing and metabolomic analyses. We are grateful to Shibiao Wan for help with bioinformatic analysis as well as Danielle Sanchez and Celeste Simon for help with HIF1α experiments. This work was supported by the American Heart Association (AHA) fellowship grant 15POST25700059 to W.W.; American Diabetes Association (ADA) fellowship grant 1-18-PDF-144 to S.T.; NIH/NICHD R03HD092630 to N.W.S.; NIH grants DK098656 and AG043483 to J.A.B; and ADA grant 1-16-IBS-269 and NIH/NIDDK grant DK103008 to P.S. W.W. J.I. and P.S. were responsible for conceptualization, data analysis, and writing/review. W.W. conducted the majority of the experiments. S.T. M.T.D. and N.W.S. performed mass spectrometry analysis of metabolite levels in medium and tissues. M.S. and R.K.G. performed adipocyte fate mapping experiments. A.J.C. and J.D.R. performed metabolomic analyses. A.S. conducted microscopy analysis. H.L. performed bioinformatics analyses. S.O. and P.C. provided samples from adipocyte-selective Prdm16-deficient mice. J.A.B. assisted with mouse aging experiments. M.T.K. and R.L.V. provided ketone ester and detailed procedures for ketone ester feeding. The authors declare no competing interests. Funding Information: We thank Lan Cheng and the Histology and Gene Expression Core of the Penn Cardiovascular Institute for immunohistochemistry and the Functional Genomics Core and Metabolomics Core of the Penn Diabetes and Endocrinology Center (DK19525) for high-throughput sequencing and metabolomic analyses. We are grateful to Shibiao Wan for help with bioinformatic analysis as well as Danielle Sanchez and Celeste Simon for help with HIF1α experiments. This work was supported by the American Heart Association (AHA) fellowship grant 15POST25700059 to W.W.; American Diabetes Association (ADA) fellowship grant 1-18-PDF-144 to S.T.; NIH/ NICHD R03HD092630 to N.W.S.; NIH grants DK098656 and AG043483 to J.A.B; and ADA grant 1-16-IBS-269 and NIH/ NIDDK grant DK103008 to P.S. Publisher Copyright: {\textcopyright} 2019 Elsevier Inc.",
year = "2019",
month = jul,
day = "2",
doi = "10.1016/j.cmet.2019.05.005",
language = "English (US)",
volume = "30",
pages = "174--189.e5",
journal = "Cell Metabolism",
issn = "1550-4131",
publisher = "Cell Press",
number = "1",
}