The expression of NFAT family genes in subcutaneous adipose tissue before and after weight loss in obese individuals

Background and aims: Adipose tissue (AT) serves as a vital energy storage site and plays a pivotal role in metabolic regulation, exhibiting a high response to insulin. Impairment in this response may closely associate with obesity, and NFAT (nuclear factor of activated T cells) family genes may be involved in the process. However, human data linking NFAT and AT remains elusive. The aim of this study was to assess the expression of NFAT family genes and markers of adipogenesis in subcutaneous adipose tissue (SAT) among normal-weight and overweight/obese individuals before and after weight loss, in relation to insulin sensitivity. Methods and results: The study included 45 participants, 15 normal-weight (control group) and 30 overweight or obese, who underwent a 12-week dietary intervention (DI) program. Before and after the program hyperinsulinemic-euglycemic clamp and SAT biopsy were conducted. Before DI, a positive correlations was observed in the expression of NFATc1, NFATc4, and NFAT5 with insulin sensitivity. The expression of NFAT family genes and markers of adipogenesis in SAT was lower in individuals with overweight or obesity compared to normal-weight. Additionally, a positive correlation was noted between NFAT family genes and adipogenesis markers both before and after weight loss. Following the DI program, there was an increase in the expression of NFATc3, NFATc4, and NFAT5 in SAT. Conclusion: Decreased SAT expression of NFAT genes in obesity is partly reversed in response to weight loss. NFAT genes in SAT are associated with insulin sensitivity and adipogenesis. Registration number for clinical trial: NCT01393210. (c) 2024 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.