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Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients.
Odendaal, Christoff; Jager, Emmalie A; Martines, Anne-Claire M F; Vieira-Lara, Marcel A; Huijkman, Nicolette C A; Kiyuna, Ligia A; Gerding, Albert; Wolters, Justina C; Heiner-Fokkema, Rebecca; van Eunen, Karen; Derks, Terry G J; Bakker, Barbara M.
Afiliação
  • Odendaal C; Laboratory of Paediatrics, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • Jager EA; Laboratory of Paediatrics, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • Martines AMF; Section of Metabolic Diseases, Beatrix Children's Hospital, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • Vieira-Lara MA; Laboratory of Paediatrics, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • Huijkman NCA; Laboratory of Paediatrics, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • Kiyuna LA; Laboratory of Paediatrics, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • Gerding A; Laboratory of Paediatrics, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • Wolters JC; Laboratory of Paediatrics, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • Heiner-Fokkema R; Department of Laboratory Medicine, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • van Eunen K; Laboratory of Paediatrics, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • Derks TGJ; Department of Laboratory Medicine, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
  • Bakker BM; Laboratory of Paediatrics, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
BMC Biol ; 21(1): 184, 2023 09 04.
Article em En | MEDLINE | ID: mdl-37667308
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Metabolismo dos Lipídeos / Erros Inatos do Metabolismo Lipídico Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Metabolismo dos Lipídeos / Erros Inatos do Metabolismo Lipídico Idioma: En Ano de publicação: 2023 Tipo de documento: Article