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Updated: Apr 23, 2026

Measuring the Rate of Lipolysis in Ex Vivo Murine Adipose Tissue and Primary Preadipocytes Differentiated In Vitro
Published on: March 17, 2023
An atlas of G-protein coupled receptor expression and function in human subcutaneous adipose tissue
Stefan Amisten1, Matt Neville2, Ross Hawkes3
1Diabetes Research Group, Division of Diabetes & Nutritional Sciences, King's College London, Faculty of Life Sciences & Medicine, London, UK; Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, UK.
Abstract:
G-protein coupled receptors (GPCRs) are involved in the regulation of adipose tissue function, but the total number of GPCRs expressed by human subcutaneous adipose tissue, as well as their function and interactions with drugs, is poorly understood. We have constructed an atlas of all GPCRs expressed by human subcutaneous adipose tissue: the 'adipose tissue GPCRome', to support the exploration of novel control nodes in metabolic and endocrine functions. This atlas describes how adipose tissue GPCRs regulate lipolysis, insulin resistance and adiponectin and leptin secretion. We also discuss how adipose tissue GPCRs interact with their endogenous ligands and with GPCR-targeting drugs, with a focus on how drug/receptor interactions may affect lipolysis, and present a model predicting how GPCRs with unknown effects on lipolysis might modulate cAMP-regulated lipolysis. Subcutaneous adipose tissue expresses 163 GPCRs, a majority of which have unknown effects on lipolysis, insulin resistance and adiponectin and leptin secretion. These GPCRs are activated by 180 different endogenous ligands, and are the targets of a large number of clinically used drugs. We identified 119 drugs, acting on 23 GPCRs, that are predicted to stimulate lipolysis and 173 drugs, acting on 25 GPCRs, that are predicted to inhibit lipolysis. This atlas highlights knowledge gaps in the current understanding of adipose tissue GPCR function, and identifies GPCR/ligand/drug interactions that might affect lipolysis, which is important for understanding and predicting metabolic side effects of drugs. This approach may aid in the design of new, safer therapeutic agents, with fewer undesired effects on lipid homeostasis.
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