Modelling the role of enzymatic pathways in the metabolism of docosahexaenoic acid by monocytes and its association with osteoarthritic pain.

Autor: Franks SJ; School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK. Electronic address: susan.franks@nottingham.ac.uk., Gowler PRW; Pain Centre Versus Arthritis, University of Nottingham Medical School, Queen's Medical Centre, Nottingham, UK; School of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK., Dunster JL; Institute for Cardiovascular and Metabolic Research, University of Reading, UK., Turnbull J; School of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK; Centre for Analytical Bioscience, Advanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham, UK., Gohir SA; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK., Kelly A; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK., Valdes AM; Pain Centre Versus Arthritis, University of Nottingham Medical School, Queen's Medical Centre, Nottingham, UK; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK., King JR; School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK., Barrett DA; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK; Centre for Analytical Bioscience, Advanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham, UK., Chapman V; Pain Centre Versus Arthritis, University of Nottingham Medical School, Queen's Medical Centre, Nottingham, UK; School of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK., Preston S; School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK.
Jazyk: angličtina
Zdroj: Mathematical biosciences [Math Biosci] 2024 Aug; Vol. 374, pp. 109228. Date of Electronic Publication: 2024 Jun 06.
DOI: 10.1016/j.mbs.2024.109228
Abstrakt: Chronic pain is a major cause of disability and suffering in osteoarthritis (OA) patients. Endogenous specialised pro-resolving molecules (SPMs) curtail pro-inflammatory responses. One of the SPM intermediate oxylipins, 17-hydroxydocasahexaenoic acid (17-HDHA, a metabolite of docosahexaenoic acid (DHA)), is significantly associated with OA pain. The aim of this multidisciplinary work is to develop a mathematical model to describe the contributions of enzymatic pathways (and the genes that encode them) to the metabolism of DHA by monocytes and to the levels of the down-stream metabolites, 17-HDHA and 14-hydroxydocasahexaenoic acid (14-HDHA), motivated by novel clinical data from a study involving 30 participants with OA. The data include measurements of oxylipin levels, mRNA levels, measures of OA severity and self-reported pain scores. We propose a system of ordinary differential equations to characterise associations between the different datasets, in order to determine the homeostatic concentrations of DHA, 17-HDHA and 14-HDHA, dependent upon the gene expression of the associated metabolic enzymes. Using parameter-fitting methods, local sensitivity and uncertainty analysis, the model is shown to fit well qualitatively to experimental data. The model suggests that up-regulation of some ALOX genes may lead to the down-regulation of 17-HDHA and that dosing with 17-HDHA increases the production of resolvins, which helps to down-regulate the inflammatory response. More generally, we explore the challenges and limitations of modelling real data, in particular individual variability, and also discuss the value of gathering additional experimental data motivated by the modelling insights.
Competing Interests: Declaration of competing interest We have no conflicts of interest to disclose.
(Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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