Inborn errors of metabolism and the human interactome: a systems medicine approach
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Inborn errors of metabolism and the human interactome: a systems medicine approach. / Woidy, Mathias; Muntau, Ania C; Gersting, Søren W.
In: J INHERIT METAB DIS, Vol. 41, No. 3, 05.2018, p. 285-296.Research output: SCORING: Contribution to journal › SCORING: Review article › Research
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TY - JOUR
T1 - Inborn errors of metabolism and the human interactome: a systems medicine approach
AU - Woidy, Mathias
AU - Muntau, Ania C
AU - Gersting, Søren W
PY - 2018/5
Y1 - 2018/5
N2 - The group of inborn errors of metabolism (IEM) displays a marked heterogeneity and IEM can affect virtually all functions and organs of the human organism; however, IEM share that their associated proteins function in metabolism. Most proteins carry out cellular functions by interacting with other proteins, and thus are organized in biological networks. Therefore, diseases are rarely the consequence of single gene mutations but of the perturbations caused in the related cellular network. Systematic approaches that integrate multi-omics and database information into biological networks have successfully expanded our knowledge of complex disorders but network-based strategies have been rarely applied to study IEM. We analyzed IEM on a proteome scale and found that IEM-associated proteins are organized as a network of linked modules within the human interactome of protein interactions, the IEM interactome. Certain IEM disease groups formed self-contained disease modules, which were highly interlinked. On the other hand, we observed disease modules consisting of proteins from many different disease groups in the IEM interactome. Moreover, we explored the overlap between IEM and non-IEM disease genes and applied network medicine approaches to investigate shared biological pathways, clinical signs and symptoms, and links to drug targets. The provided resources may help to elucidate the molecular mechanisms underlying new IEM, to uncover the significance of disease-associated mutations, to identify new biomarkers, and to develop novel therapeutic strategies.
AB - The group of inborn errors of metabolism (IEM) displays a marked heterogeneity and IEM can affect virtually all functions and organs of the human organism; however, IEM share that their associated proteins function in metabolism. Most proteins carry out cellular functions by interacting with other proteins, and thus are organized in biological networks. Therefore, diseases are rarely the consequence of single gene mutations but of the perturbations caused in the related cellular network. Systematic approaches that integrate multi-omics and database information into biological networks have successfully expanded our knowledge of complex disorders but network-based strategies have been rarely applied to study IEM. We analyzed IEM on a proteome scale and found that IEM-associated proteins are organized as a network of linked modules within the human interactome of protein interactions, the IEM interactome. Certain IEM disease groups formed self-contained disease modules, which were highly interlinked. On the other hand, we observed disease modules consisting of proteins from many different disease groups in the IEM interactome. Moreover, we explored the overlap between IEM and non-IEM disease genes and applied network medicine approaches to investigate shared biological pathways, clinical signs and symptoms, and links to drug targets. The provided resources may help to elucidate the molecular mechanisms underlying new IEM, to uncover the significance of disease-associated mutations, to identify new biomarkers, and to develop novel therapeutic strategies.
KW - Journal Article
KW - Metabolomics
KW - Protein Interaction Maps/physiology
KW - Systems Analysis
KW - Humans
KW - Genomics/methods
KW - Gene Regulatory Networks/physiology
KW - Infant, Newborn
KW - Metabolism, Inborn Errors/genetics
U2 - 10.1007/s10545-018-0140-0
DO - 10.1007/s10545-018-0140-0
M3 - SCORING: Review article
C2 - 29404805
VL - 41
SP - 285
EP - 296
JO - J INHERIT METAB DIS
JF - J INHERIT METAB DIS
SN - 0141-8955
IS - 3
ER -