A multi-scale in silico mouse model for diet-induced insulin resistance
(2023) In Biochemical Engineering Journal 191.- Abstract
Insulin resistance causes compensatory insulin production, which in humans can eventually progress to β-cell failure and type 2 diabetes (T2D). This disease progression involves multi-scale processes, ranging from intracellular signaling to organ and whole-body level regulations, on timescales from minutes to years. T2D progression is commonly studied using overfed and genetically modified rodents. Available multi-scale data from rodents is too complex to fully comprehend using traditional analysis, not based on mathematical modelling. To help resolve these issues, we here present an in silico mouse model, featuring 38 ordinary differential equations and 78 parameters. This is the first mathematical model that simultaneously explains... (More)
Insulin resistance causes compensatory insulin production, which in humans can eventually progress to β-cell failure and type 2 diabetes (T2D). This disease progression involves multi-scale processes, ranging from intracellular signaling to organ and whole-body level regulations, on timescales from minutes to years. T2D progression is commonly studied using overfed and genetically modified rodents. Available multi-scale data from rodents is too complex to fully comprehend using traditional analysis, not based on mathematical modelling. To help resolve these issues, we here present an in silico mouse model, featuring 38 ordinary differential equations and 78 parameters. This is the first mathematical model that simultaneously explains (chi-square cost=28.1 <51 =cut-off, p = 0.05) multi-scale mouse insulin resistance data on all three levels – cells, organs, body – ranging from minutes to months. The model predicts new independent multi-scale simulations, on e.g., weight and meal response changes, which are corroborated by our own new experimental data. The thus validated model provides insights and non-trivial predictions regarding complex non-measured processes, such as the relation between insulin resistance and insulin-dependent glucose uptake for adipose tissue. Finally, we add a β-cell failure module to the in silico mouse model to simulate different human-like scenarios of progression towards T2D. In summary, our in silico mouse model is an extendable and interactive knowledge-base for the study of T2D, which could help simulate treatment scenarios in rodents and translate results to the human situation.
(Less)
- author
- Simonsson, Christian ; Lövfors, William ; Bergqvist, Niclas ; Nyman, Elin ; Gennemark, Peter ; Stenkula, Karin G. LU and Cedersund, Gunnar
- organization
- publishing date
- 2023-02
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Insulin resistance, Mechanistic and multi-level modelling, Systems biology, Type 2 diabetes
- in
- Biochemical Engineering Journal
- volume
- 191
- article number
- 108798
- publisher
- Elsevier
- external identifiers
-
- scopus:85146075585
- ISSN
- 1369-703X
- DOI
- 10.1016/j.bej.2022.108798
- language
- English
- LU publication?
- yes
- id
- f0a2102d-6c94-4372-bd22-322e7c293de1
- date added to LUP
- 2023-02-16 16:37:54
- date last changed
- 2023-02-16 16:37:54
@article{f0a2102d-6c94-4372-bd22-322e7c293de1,
abstract = {{<p>Insulin resistance causes compensatory insulin production, which in humans can eventually progress to β-cell failure and type 2 diabetes (T2D). This disease progression involves multi-scale processes, ranging from intracellular signaling to organ and whole-body level regulations, on timescales from minutes to years. T2D progression is commonly studied using overfed and genetically modified rodents. Available multi-scale data from rodents is too complex to fully comprehend using traditional analysis, not based on mathematical modelling. To help resolve these issues, we here present an in silico mouse model, featuring 38 ordinary differential equations and 78 parameters. This is the first mathematical model that simultaneously explains (chi-square cost=28.1 <51 =cut-off, p = 0.05) multi-scale mouse insulin resistance data on all three levels – cells, organs, body – ranging from minutes to months. The model predicts new independent multi-scale simulations, on e.g., weight and meal response changes, which are corroborated by our own new experimental data. The thus validated model provides insights and non-trivial predictions regarding complex non-measured processes, such as the relation between insulin resistance and insulin-dependent glucose uptake for adipose tissue. Finally, we add a β-cell failure module to the in silico mouse model to simulate different human-like scenarios of progression towards T2D. In summary, our in silico mouse model is an extendable and interactive knowledge-base for the study of T2D, which could help simulate treatment scenarios in rodents and translate results to the human situation.</p>}},
author = {{Simonsson, Christian and Lövfors, William and Bergqvist, Niclas and Nyman, Elin and Gennemark, Peter and Stenkula, Karin G. and Cedersund, Gunnar}},
issn = {{1369-703X}},
keywords = {{Insulin resistance; Mechanistic and multi-level modelling; Systems biology; Type 2 diabetes}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Biochemical Engineering Journal}},
title = {{A multi-scale in silico mouse model for diet-induced insulin resistance}},
url = {{http://dx.doi.org/10.1016/j.bej.2022.108798}},
doi = {{10.1016/j.bej.2022.108798}},
volume = {{191}},
year = {{2023}},
}