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

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

Herrgårdh, Tilda (author): Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten

Simonsson, Christian (author): Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV

Ekstedt, Mattias (author): Linköpings universitet,Avdelningen för diagnostik och specialistmedicin,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Mag- tarmmedicinska kliniken

Lundberg, Peter (author): Linköpings universitet,Avdelningen för diagnostik och specialistmedicin,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Medicinsk strålningsfysik

Stenkula, Karin G. (author): Department of Experimental Medical Science, Lund University, Lund, Sweden,Lund Univ, Sweden

Nyman, Elin (author): Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten

Gennemark, Peter (author): Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten,AstraZeneca, Sweden

Cedersund, Gunnar, Associate Professor, 1978- (author): Linköpings universitet,Örebro universitet,Institutionen för medicinska vetenskaper,Department of Biomedical Engineering, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden,Avdelningen för medicinsk teknik,Tekniska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Orebro Univ, Sweden

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BioMed Central (BMC), 2023
2023
English.
In: Diabetology & Metabolic Syndrome. - : BioMed Central (BMC). - 1758-5996. ; 15:1

Related links:: https://doi.org/10.1...; show more...; https://urn.kb.se/re...; https://doi.org/10.1...; https://urn.kb.se/re...; show less...

Journal article (peer-reviewed)

Abstract Subject headings

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.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Endokrinologi och diabetes (hsv//swe)
MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Endocrinology and Diabetes (hsv//eng)

Keyword

Digital twin
Insulin resistance
Mathematical modelling

Publication and Content Type

ref (subject category)
art (subject category)

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By the author/editor: Herrgårdh, Tilda; Simonsson, Chris ...; Ekstedt, Mattias; Lundberg, Peter; Stenkula, Karin ...; Nyman, Elin; show more...; Gennemark, Peter; Cedersund, Gunna ...; show less...

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MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Clinical Medicin ...; and Endocrinology an ...

Articles in the publication: Diabetology & Me ...

By the university: Örebro University; Linköping University

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