Reference : Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegen...

	Document type :	Scientific journals : Article
	Discipline(s) :	Life sciences : Multidisciplinary, general & others
	To cite this reference:	http://hdl.handle.net/10993/52436

Title :	Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases.
Language :	English
Author, co-author :	Kishk, Ali [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
	Pires Pacheco, Maria Irene [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM) >]
	Heurtaux, Tony [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
	Sinkkonen, Lasse [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
	Pang, Jun [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)]
	Fritah, Sabrina [> >]
	Niclou, Simone [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > >]
	Sauter, Thomas [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
Publication date :	2022
Journal title :	Cells
Volume :	11
Issue/season :	16
Peer reviewed :	Yes
Audience :	International
ISSN :	2073-4409
e-ISSN :	2073-4409
Keywords :	[en] Biomass ; Brain Neoplasms/genetics ; Genome, Human ; Glioma ; Humans ; Neurodegenerative Diseases/genetics ; astrocyte ; brain metabolism ; glioma ; metabolic modelling ; neurodegenerative diseases ; neuron
Abstract :	[en] 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.
Permalink :	http://hdl.handle.net/10993/52436

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