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Yiming Cheng, Li Jiang, Susanne Keipert, Shuyue Zhang, Andreas Hauser, Elisabeth Graf, Tim Strom, Matthias Tschoep, Martin Jastroch, and Fabiana Perocchi (Institute for Diabetes and Obesity, Helmholtz Diabetes Center, Helmholtz Zentrum Muenchen and German National Diabetes Center (DZD), 85764 Neuherberg, Germany)
Activation and recruitment of thermogenic cells in human white adipose tissues (‘‘browning’’) can counteract obesity and associated metabolic disorders. However, quantifying the effects of therapeutic interventions on browning remains enigmatic. Here, we devise a computational tool, named ProFAT (profiling of fat tissue types), for quantifying the thermogenic potential of heterogeneous fat biopsies based on prediction of white and brown adipocyte content from raw gene expression datasets. ProFAT systematically integrates 103 mouse-fat-derived transcriptomes to identify unbiased and robust gene signatures of brown and white adipocytes. We validate ProFAT on 80 mouse and 97 human transcriptional profiles from 14 independent studies and correctly predict browning capacity upon various physiological and pharmacological stimuli. Our study represents the most exhaustive comparative analysis of public data on adipose biology toward quantification of browning after personalized medical intervention. ProFAT is freely available and should become increasingly powerful.https://www.sciencedirect.com/science/article/pii/S221112471830754X?via=ihub