A data-driven computational model for obesity-driven diabetes onset and remission through weight loss

Protocol for analyzing emergence dynamics of diabetes with obesity using numerical continuation and bifurcation analysis

“…Here, we use the protocol to analyze the slow progression dynamics of T2D with obesity using a recently published model. 1 However, the protocol can easily be adapted for analyzing behaviors of other dynamical systems, whose dynamics are described with ordinary differential equations (ODEs). Although, some software packages are developed specifically for this protocol, they can easily be adapted for analyzing other dynamical systems.…”

“…The protocol is implemented for a recently published computational model that describes the dynamics of the obesity driven progression of type 2 diabetes and remission through weight loss. 1 The model describes system dynamics by a system of nonlinear ordinary differential equations (ODEs). An XPPAUT implementation of the model and other necessary programs are freely available under MIT license on GitHub repository.…”

“…The protocol is implemented using a recently published computational model that describes the dynamics of the obesity driven progression of type 2 diabetes (T2D) and remission through weight loss. 1 Here we provide some background information and briefly describe the model.…”

“…The details of the definitions of model variables and their mathematical formulations are described in Yildirim et al. 1 In short, the system is at a healthy state at the baseline, where the total daily energy intake and expenditure are in balance, and a healthy BMI is preserved. A perpetual imbalance between energy intake and expenditure results in weight gain that initiates a chain of events that pushes the system out of the healthy state and eventually results in insulin resistance and diabetes.…”

Special Issue—Diabetes Mellitus: Current Research and Future Perspectives

“…Twelve biochemical parameters were considered in subjects with T2D; HDL was found to be inversely correlated with most of the parameters, and the principal predictors of HDLs were triglycerides, LDL cholesterol, and HbA1c levels. These results suggest that the same approach could be used to derive novel management strategies and therapeutic approaches in T2D [ 10 , 11 ], performing complex analyses with minimal computational and software resources using the available measurements on subjects with T2D and healthy controls.…”