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A Computational Model of Liver Iron Metabolism.pdf (951.01 kB)

A computational model of liver iron metabolism

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posted on 2023-06-09, 18:03 authored by Simon MitchellSimon Mitchell, Pedro Mendes
Iron is essential for all known life due to its redox properties; however, these same properties can also lead to its toxicity in overload through the production of reactive oxygen species. Robust systemic and cellular control are required to maintain safe levels of iron, and the liver seems to be where this regulation is mainly located. Iron misregulation is implicated in many diseases, and as our understanding of iron metabolism improves, the list of iron-related disorders grows. Recent developments have resulted in greater knowledge of the fate of iron in the body and have led to a detailed map of its metabolism; however, a quantitative understanding at the systems level of how its components interact to produce tight regulation remains elusive. A mechanistic computational model of human liver iron metabolism, which includes the core regulatory components, is presented here. It was constructed based on known mechanisms of regulation and on their kinetic properties, obtained from several publications. The model was then quantitatively validated by comparing its results with previously published physiological data, and it is able to reproduce multiple experimental findings. A time course simulation following an oral dose of iron was compared to a clinical time course study and the simulation was found to recreate the dynamics and time scale of the systems response to iron challenge. A disease state simulation of haemochromatosis was created by altering a single reaction parameter that mimics a human haemochromatosis gene (HFE) mutation. The simulation provides a quantitative understanding of the liver iron overload that arises in this disease. This model supports and supplements understanding of the role of the liver as an iron sensor and provides a framework for further modelling, including simulations to identify valuable drug targets and design of experiments to improve further our knowledge of this system.

History

Publication status

  • Published

File Version

  • Published version

Journal

PLoS Computational Biology

ISSN

1553-7358

Publisher

Public Library of Science

Issue

11

Volume

9

Page range

1-14

Article number

e1003299

Department affiliated with

  • BSMS Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2019-06-14

First Open Access (FOA) Date

2019-06-14

First Compliant Deposit (FCD) Date

2019-06-12

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