Reference : A compendium of inborn errors of metabolism mapped onto the human metabolic network
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/17463
A compendium of inborn errors of metabolism mapped onto the human metabolic network
English
Sahoo, Swagatika mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Franzson []
Jonsson, Jon J []
Thiele, Ines mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
2012
Molecular Biosystems
8
10
2545 - 2558
Yes (verified by ORBilu)
1742-206X
1742-2051
[en] Inborn errors of metabolism (IEMs) are hereditary metabolic defects, which are encountered in
almost all major metabolic pathways occurring in man. Many IEMs are screened for in neonates
through metabolomic analysis of dried blood spot samples. To enable the mapping of these
metabolomic data onto the published human metabolic reconstruction, we added missing
reactions and pathways involved in acylcarnitine (AC) and fatty acid oxidation (FAO)
metabolism. Using literary data, we reconstructed an AC/FAO module consisting of 352 reactions
and 139 metabolites. When this module was combined with the human metabolic reconstruction,
the synthesis of 39 acylcarnitines and 22 amino acids, which are routinely measured, was captured
and 235 distinct IEMs could be mapped. We collected phenotypic and clinical features for each
IEM enabling comprehensive classification. We found that carbohydrate, amino acid, and lipid
metabolism were most affected by the IEMs, while the brain was the most commonly affected
organ. Furthermore, we analyzed the IEMs in the context of metabolic network topology to gain
insight into common features between metabolically connected IEMs. While many known
examples were identified, we discovered some surprising IEM pairs that shared reactions as well
as clinical features but not necessarily causal genes. Moreover, we could also re-confirm that
acetyl-CoA acts as a central metabolite. This network based analysis leads to further insight of
hot spots in human metabolism with respect to IEMs. The presented comprehensive knowledge
base of IEMs will provide a valuable tool in studying metabolic changes involved in inherited
metabolic diseases.
http://hdl.handle.net/10993/17463
10.1039/c2mb25075f

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