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BATLAS: Deconvoluting Brown Adipose Tissue

Journal article
Authors A. Perdikari
G. G. Leparc
M. Balaz
N. D. Pires
Martin Lidell
W. F. Sun
F. Fernandez-Albert
S. Muller
N. Akchiche
H. Dong
L. Balazova
L. Opitz
E. Roder
H. Klein
P. Stefanicka
L. Varga
P. Nuutila
K. A. Virtanen
T. Niemi
M. Taittonen
G. Rudofsky
J. Ukropec
Sven Enerbäck
E. Stupka
H. Neubauer
C. Wolfrum
Published in Cell Reports
Volume 25
Issue 3
Pages 784-+
ISSN 2211-1247
Publication year 2018
Published at Institute of Biomedicine, Department of Medical and Clinical Genetics
Pages 784-+
Language en
Keywords functional-characterization, white adipocytes, receptor agonist, adult, humans, fat, activation, distinct, brite, cold, cell
Subject categories Cell biology


Recruitment and activation of thermogenic adipocytes have received increasing attention as a strategy to improve systemic metabolic control. The analysis of brown and brite adipocytes is complicated by the complexity of adipose tissue biopsies. Here, we provide an in-depth analysis of pure brown, brite, and white adipocyte transcriptomes. By combining mouse and human transcriptome data, we identify a gene signature that can classify brown and white adipocytes in mice and men. Using a machine-learning-based cell deconvolution approach, we develop an algorithm proficient in calculating the brown adipocyte content in complex human and mouse biopsies. Applying this algorithm, we can show in a human weight loss study that brown adipose tissue (BAT) content is associated with energy expenditure and the propensity to lose weight. This online available tool can be used for in-depth characterization of complex adipose tissue samples and may support the development of therapeutic strategies to increase energy expenditure in humans.

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Utskriftsdatum: 2020-08-10