Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases

Ali Kishk, Maria Pires Pacheco, Tony Heurtaux, Lasse Sinkkonen, Jun Pang, Sabrina Fritah, Simone P. Niclou, Thomas Sauter*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)

Abstract

Brain disorders represent 32% of the global disease burden, with 169 million Europeans affected. Constraint-based metabolic modelling and other approaches have been applied to predict new treatments for these and other diseases. Many recent studies focused on enhancing, among others, drug predictions by generating generic metabolic models of brain cells and on the contextualisation of the genome-scale metabolic models with expression data. Experimental flux rates were primarily used to constrain or validate the model inputs. Bi-cellular models were reconstructed to study the interaction between different cell types. This review highlights the evolution of genome-scale models for neurodegenerative diseases and glioma. We discuss the advantages and drawbacks of each approach and propose improvements, such as building bi-cellular models, tailoring the biomass formulations for glioma and refinement of the cerebrospinal fluid composition.

Original languageEnglish
Article number2486
JournalCells
Volume11
Issue number16
DOIs
Publication statusPublished - Aug 2022

Keywords

  • astrocyte
  • brain metabolism
  • glioma
  • metabolic modelling
  • neurodegenerative diseases
  • neuron

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