Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients.

Abstract:

BACKGROUND: Monogenetic inborn errors of metabolism cause a wide phenotypic heterogeneity that may even differ between family members carrying the same genetic variant. Computational modelling of metabolic networks may identify putative sources of this inter-patient heterogeneity. Here, we mainly focus on medium-chain acyl-CoA dehydrogenase deficiency (MCADD), the most common inborn error of the mitochondrial fatty acid oxidation (mFAO). It is an enigma why some MCADD patients-if untreated-are at risk to develop severe metabolic decompensations, whereas others remain asymptomatic throughout life. We hypothesised that an ability to maintain an increased free mitochondrial CoA (CoASH) and pathway flux might distinguish asymptomatic from symptomatic patients. RESULTS: We built and experimentally validated, for the first time, a kinetic model of the human liver mFAO. Metabolites were partitioned according to their water solubility between the bulk aqueous matrix and the inner membrane. Enzymes are also either membrane-bound or in the matrix. This metabolite partitioning is a novel model attribute and improved predictions. MCADD substantially reduced pathway flux and CoASH, the latter due to the sequestration of CoA as medium-chain acyl-CoA esters. Analysis of urine from MCADD patients obtained during a metabolic decompensation showed an accumulation of medium- and short-chain acylcarnitines, just like the acyl-CoA pool in the MCADD model. The model suggested some rescues that increased flux and CoASH, notably increasing short-chain acyl-CoA dehydrogenase (SCAD) levels. Proteome analysis of MCADD patient-derived fibroblasts indeed revealed elevated levels of SCAD in a patient with a clinically asymptomatic state. This is a rescue for MCADD that has not been explored before. Personalised models based on these proteomics data confirmed an increased pathway flux and CoASH in the model of an asymptomatic patient compared to those of symptomatic MCADD patients. CONCLUSIONS: We present a detailed, validated kinetic model of mFAO in human liver, with solubility-dependent metabolite partitioning. Personalised modelling of individual patients provides a novel explanation for phenotypic heterogeneity among MCADD patients. Further development of personalised metabolic models is a promising direction to improve individualised risk assessment, management and monitoring for inborn errors of metabolism.

SEEK ID: https://fairdomhub.org/publications/692

PubMed ID: 37667308

Projects: PoLiMeR - Polymers in the Liver: Metabolism and Regulation

Publication type: Journal

Journal: BMC Biol

Citation: BMC Biol. 2023 Sep 4;21(1):184. doi: 10.1186/s12915-023-01652-9.

Date Published: 4th Sep 2023

Registered Mode: by PubMed ID

Authors: C. Odendaal, E. A. Jager, A. M. F. Martines, M. A. Vieira-Lara, N. C. A. Huijkman, L. A. Kiyuna, A. Gerding, J. C. Wolters, R. Heiner-Fokkema, K. van Eunen, T. G. J. Derks, B. M. Bakker

help Submitter
Activity

Views: 159

Created: 28th Feb 2024 at 06:36

help Tags

This item has not yet been tagged.

help Attributions

None

Powered by
(v.1.14.2)
Copyright © 2008 - 2023 The University of Manchester and HITS gGmbH