학술논문
BATLAS: Deconvoluting Brown Adipose Tissue
Document Type
article
Author
Aliki Perdikari; Germán Gastón Leparc; Miroslav Balaz; Nuno D. Pires; Martin E. Lidell; Wenfei Sun; Francesc Fernandez-Albert; Sebastian Müller; Nassila Akchiche; Hua Dong; Lucia Balazova; Lennart Opitz; Eva Röder; Holger Klein; Patrik Stefanicka; Lukas Varga; Pirjo Nuutila; Kirsi A. Virtanen; Tarja Niemi; Markku Taittonen; Gottfried Rudofsky; Jozef Ukropec; Sven Enerbäck; Elia Stupka; Heike Neubauer; Christian Wolfrum
Source
Cell Reports, Vol 25, Iss 3, Pp 784-797.e4 (2018)
Subject
Language
English
ISSN
2211-1247
Abstract
Summary: 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. : By combining mouse and human transcriptome data, Perdikari et al. identify a gene signature that can classify brown and white adipocytes. Using a machine-learning-based cell deconvolution approach, they develop an algorithm proficient in calculating the brown adipocyte content in complex biopsies. This web tool allows in-depth characterization of adipose tissue samples. Keywords: pure adipocyte populations, gene signature, deconvolution, BAT content