Anti-Diabetic Drugs Inhibit Bulimia Induced Obesity

Abstract

Background: Obesity is primarily a consequence of food addiction. Drugs have been confirmed effective for weight loss more or less related to the functional connectivity in neural networks and metabolic patterns. Recent studies have shown that some anti-diabetic drugs, such as Metformin and Dapagliflozin have similar weight loss effects, however, their mechanisms are unclear. We hypothesized that the functional connectivity and energy metabolism might be associated with the mechanisms.

Methods: Male ob/ob mice were fed with high-fructose-fat-diet (HFFD) for 4 weeks to esteblish obesity model. Then mice were divided into normal saline (NS, as control), Metformin (Metformin, 50 mg/kg/day by gavage), and Dapagliflozin (Dapagliflozin, 10 mg/kg/day by gavage) groups. Functional connectivity amplitude of low-frequency signal fluctuations and regional cerebral blood volume (rCBV) quantification were statistically analyzed in the linear mixed model, meanwhile, metabolic pattern of intestinal cells (IECs) were also tested.

Results: Our results showed that Blood Oxygen on Level Depending (Bold) signaling responses, functional connectivity, and rCBV quantification tended to be attenuated in the Metformin group compared to the control and Dapagliflozin groups. While only Dapagliflozin prevented HFFD induced hyper survival of intestinal cells and hypertrophy of intestinal villus by reducing glycolysis levels. Both Metformin and Dapagliflozin are effective for weight loss.

Conclusions: Our findings showed that Dapagliflozin and Metformin may inhibit bulimia induced obesity with different mechanisms. We speculate that Metformin may affect appetite regulation, while Dapagliflozin can affect the survival and metabolic patterns of intestinal cells, thus significantly affecting the absorption of nutrients. So, combining Metformin and Dapgliflozin may be more beneficial for clinical improvement in bulimia induced obesity.

Keywords: Dapagliflozin; Metformin; intestinal villus; metabolic patterns; neural networks; obesity.