An international study led by scientists from Ben-Gurion University of the Negev has characterized the populations of fat cells in various fat tissues in the human body. Using innovative technology, the researchers were able to identify for the first time unique subpopulations of fat cells, with more complex predicted functions than previously known, and even identified differences between human fat tissues in intercellular communication. The findings provide a basis for further research to advance personalized medicine in obesity.
The diversity of fat cells in the different fat tissues in humans is more complex, interesting, and surprising than we previously thought. For example, in addition to the ‘classical’ fat (adipocyte) cells, we found subpopulations of adipocytes, characterized here for the first time, that express RNA molecules indicating unique functions, such as regulation of inflammatory processes, blood vessel formation, extracellular protein deposition, and scarring (fibrosis).
Searching for the source of the differences between subcutaneous and visceral fat, the researchers found that most of the fat cell subpopulations were similar between subcutaneous and intra-abdominal fat. Nevertheless, significant, albeit more subtle, differences were identified between fat cells from the two tissues. For example, intercellular communication in the two tissues differs: fat cells in the intra-abdominal tissue express genes indicating more active communication with immune system cells within the tissue and are involved in pro-inflammatory processes.
The new insights into the cellular composition and function of human fat tissues provide a basis for further applied research aimed at promoting personalized medicine in obesity.
“We found that the prevalence of the unique fat cells we identified was related to the metabolic complications of obesity: their relative proportion in the tissue is higher the more severe the insulin resistance is. If it turns out that the prevalence of unique fat cells also predicts the degree of personal risk for future development of obesity complications, and/or can predict the individual response to treatment—the findings may have great significance in the pursuit of more personalised treatment for obesity. To this end, we are already working to develop tools that can bring our findings to clinical medicine, for example, developing microscopic examinations of fat tissue and identifying unique fat cells by a clinical pathologist.”
