A multi-scale digital twin for adiposity-driven insulin resistance in humans: diet and drug effects

Background The increased prevalence of insulin resistance is one of the major health risks in society today. Insulin resistance involves both short-term dynamics, such as altered meal responses, and long-term dynamics, such as the development of type 2 diabetes. Insulin resistance also occurs on different physiological levels, ranging from disease phenotypes to organ-organ communication and intracellular signaling. To better understand the progression of insulin resistance, an analysis method is needed that can combine different timescales and physiological levels. One such method is digital twins, consisting of combined mechanistic mathematical models. We have previously developed a model for short-term glucose homeostasis and intracellular insulin signaling, and there exist long-term weight regulation models. Herein, we combine these models into a first interconnected digital twin for the progression of insulin resistance in humans. Methods The model is based on ordinary differential equations representing biochemical and physiological processes, in which unknown parameters were fitted to data using a MATLAB toolbox. Results The interconnected twin correctly predicts independent data from a weight increase study, both for weight-changes, fasting plasma insulin and glucose levels, and intracellular insulin signaling. Similarly, the model can predict independent weight-change data in a weight loss study with the weight loss drug topiramate. The model can also predict non-measured variables. Conclusions The model presented herein constitutes the basis for a new digital twin technology, which in the future could be used to aid medical pedagogy and increase motivation and compliance and thus aid in the prevention and treatment of insulin resistance. Supplementary Information The online version contains supplementary material available at 10.1186/s13098-023-01223-6.

All the ODEs for the final model: All variables of final model:

Table S1 :
150) Parameters of the cell level that were not changed.The values used were the same as in(Brännmark  et al. 2013)for both the Topiramate Study and the Fast-food study.

Table S2 :
Parameters of the cell level that were changed.Fitted so that IRtot and GLUT 4 are at 100 % in steady state.The same values were used for both the Topiramate Study and the Fast-food study.

Table S3 :
Parameters on the organ/tissue level that were set to different values for the different studies.For the Fast-food study, the parameters were estimated on initial values of glucose and insulin.For the Topiramate study, the values from (Herrgårdh et al. 2021) were used.The meal, D (set to the same as the initial value of Q sto ), was set to 1 g/kg of body weight.The two values for D are for the meals simulated in the before/after scenarios respectively.

Table S4 :
Parameters of the organ/tissue level that were kept at the same values for both the Fast-food study and Topiramate study data.The values were come from (Herrgårdh et al. 2021).

Table S5 :
Parameters of the whole-body level that were set to different values for the different studies.For the Fast-food study, the parameters were estimated on initial values of glucose and insulin.For both studies, the values were either taken from the data (dosage, BWinit, height, age, Finit, Linit, EIrestriction), if not present in data calculated based on the equations in(Hall et al. 2011) and data (RMRinit, Ginit, ECFinit, Finit, Linit, ATinit), or estimated to data from the Topiramate study (k, lmax, IC 50 , and h2 to data for dosages 64 and 192, and h1, dEI ss , and t hal f to placebo data).The different values for dosage, BWinit, height, age, RMRinit, ECFinit, Finit, Linit, and EIrestriction are the data for the different dosages and their data sets.The meal, D (set to the same as the initial value of Q sto ), was set to 1 g/kg of body weight.The two values are for the before/after scenarios respectively.See(Hall et al. 2011)for descriptions of parameters.

Table S6 :
Parameters of the whole-body level that were kept at the same values for both the Fast-food study and Topiramate study data.The values come from(Hall et al. 2011).See (Hall et al. 2011)for descriptions of parameters.

Table S7 :
Parameters of the topiramate model used on the Topiramate study data.The values come from(Girgis  et al. 2010)

Table S9 :
Initial values of organ/tissue level model.For the Topiramate study, these values were only used for the predictions (Fig.5 E-G).These values were obtained through steady state simulation, except for Q sto1 (0) which was set to a meal corresponding to 1 g/kg body weight, or 0 if no meal.

Table S10 :
Initial values of whole-body level model used in model training and validating.The different values for the Topiramate study correspond to the different dosages 0 / 64 / 192 / 96.For both studies, the values were either taken from the data (F(0), and L(0)), or if not present in data calculated based on the equations in(Hall  et al. 2011) and data (RMR(0), Gly(0), ECF(0), F(0), L(0), AT (0)).

Table S11 :
Initial values of topiramate model used in model training and validating for Topiramate study.The dosage of topiramate is given as an initial value of the state A, and the different values for each dosage represents the escalation of dosage taken seen in the data in(Bray et al. 2003).