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System-wide assembly of pathways and modules hierarchically reveal metabolic mechanism of cerebral ischemia.

Zhu Y, Guo Z, Zhang L, Zhang Y, Chen Y, Nan J, Zhao B, Xiao H, Wang Z, Wang Y - Sci Rep (2015)

Bottom Line: The relationship between cerebral ischemia and metabolic disorders is poorly understood, which is partly due to the lack of comparative fusing data for larger complete systems and to the complexity of metabolic cascade reactions.Our analyses revealed 8 significantly altered pathways by MetPA (Metabolomics Pathway Analysis, impact score >0.10) and 15 significantly rewired modules in a complex ischemic network using the Markov clustering (MCL) method; all of these pathways became more homologous as the number of overlapping nodes was increased.We then detected 24 extensive pathways based on the total modular nodes from the network analysis, 12 of which were new discovery pathways.

View Article: PubMed Central - PubMed

Affiliation: Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China.

ABSTRACT
The relationship between cerebral ischemia and metabolic disorders is poorly understood, which is partly due to the lack of comparative fusing data for larger complete systems and to the complexity of metabolic cascade reactions. Based on the fusing maps of comprehensive serum metabolome, fatty acid and amino acid profiling, we identified 35 potential metabolic biomarkers for ischemic stroke. Our analyses revealed 8 significantly altered pathways by MetPA (Metabolomics Pathway Analysis, impact score >0.10) and 15 significantly rewired modules in a complex ischemic network using the Markov clustering (MCL) method; all of these pathways became more homologous as the number of overlapping nodes was increased. We then detected 24 extensive pathways based on the total modular nodes from the network analysis, 12 of which were new discovery pathways. We provided a new perspective from the viewpoint of abnormal metabolites for the overall study of ischemic stroke as well as a new method to simplify the network analysis by selecting the more closely connected edges and nodes to build a module map of stroke.

No MeSH data available.


Related in: MedlinePlus

(A) Total ion current chromatography (TIC) of plasma samples derived from the sham group; (B) Total ion current chromatography (TIC) of plasma samples derived from the ischemia group; (C) Profile of HPLC chromatogram of serum fatty acids in ischemic rats; (D) Profile of HPLC chromatogram of serum amino acids in ischemic rats.
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f2: (A) Total ion current chromatography (TIC) of plasma samples derived from the sham group; (B) Total ion current chromatography (TIC) of plasma samples derived from the ischemia group; (C) Profile of HPLC chromatogram of serum fatty acids in ischemic rats; (D) Profile of HPLC chromatogram of serum amino acids in ischemic rats.

Mentions: The total ion current chromatogram (TIC) of plasma samples derived from the sham and ischemia groups showed significant differences in metabolite abundance (Fig. 2A,B), which might contribute to the distinct separation between the sham and MCAO rats in principal component analysis (PCA) score plots (Fig. 3A). The potential biomarkers were discovered by Graphical Index of Separation (GIOS) (Fig. 3B) and were employed to build a PLS-DA model for sham and MCAO rats (Fig. 3C). The PLS score plots revealed various metabolites that could be responsible for the separation; thus, these metabolites were viewed as potential biomarkers. Finally, potentially significant biomarkers were characterized in ischemic rats (Table 1), including 15 significantly increased and 7 decreased metabolites in the ischemia group compared with the sham group.


System-wide assembly of pathways and modules hierarchically reveal metabolic mechanism of cerebral ischemia.

Zhu Y, Guo Z, Zhang L, Zhang Y, Chen Y, Nan J, Zhao B, Xiao H, Wang Z, Wang Y - Sci Rep (2015)

(A) Total ion current chromatography (TIC) of plasma samples derived from the sham group; (B) Total ion current chromatography (TIC) of plasma samples derived from the ischemia group; (C) Profile of HPLC chromatogram of serum fatty acids in ischemic rats; (D) Profile of HPLC chromatogram of serum amino acids in ischemic rats.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664864&req=5

f2: (A) Total ion current chromatography (TIC) of plasma samples derived from the sham group; (B) Total ion current chromatography (TIC) of plasma samples derived from the ischemia group; (C) Profile of HPLC chromatogram of serum fatty acids in ischemic rats; (D) Profile of HPLC chromatogram of serum amino acids in ischemic rats.
Mentions: The total ion current chromatogram (TIC) of plasma samples derived from the sham and ischemia groups showed significant differences in metabolite abundance (Fig. 2A,B), which might contribute to the distinct separation between the sham and MCAO rats in principal component analysis (PCA) score plots (Fig. 3A). The potential biomarkers were discovered by Graphical Index of Separation (GIOS) (Fig. 3B) and were employed to build a PLS-DA model for sham and MCAO rats (Fig. 3C). The PLS score plots revealed various metabolites that could be responsible for the separation; thus, these metabolites were viewed as potential biomarkers. Finally, potentially significant biomarkers were characterized in ischemic rats (Table 1), including 15 significantly increased and 7 decreased metabolites in the ischemia group compared with the sham group.

Bottom Line: The relationship between cerebral ischemia and metabolic disorders is poorly understood, which is partly due to the lack of comparative fusing data for larger complete systems and to the complexity of metabolic cascade reactions.Our analyses revealed 8 significantly altered pathways by MetPA (Metabolomics Pathway Analysis, impact score >0.10) and 15 significantly rewired modules in a complex ischemic network using the Markov clustering (MCL) method; all of these pathways became more homologous as the number of overlapping nodes was increased.We then detected 24 extensive pathways based on the total modular nodes from the network analysis, 12 of which were new discovery pathways.

View Article: PubMed Central - PubMed

Affiliation: Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China.

ABSTRACT
The relationship between cerebral ischemia and metabolic disorders is poorly understood, which is partly due to the lack of comparative fusing data for larger complete systems and to the complexity of metabolic cascade reactions. Based on the fusing maps of comprehensive serum metabolome, fatty acid and amino acid profiling, we identified 35 potential metabolic biomarkers for ischemic stroke. Our analyses revealed 8 significantly altered pathways by MetPA (Metabolomics Pathway Analysis, impact score >0.10) and 15 significantly rewired modules in a complex ischemic network using the Markov clustering (MCL) method; all of these pathways became more homologous as the number of overlapping nodes was increased. We then detected 24 extensive pathways based on the total modular nodes from the network analysis, 12 of which were new discovery pathways. We provided a new perspective from the viewpoint of abnormal metabolites for the overall study of ischemic stroke as well as a new method to simplify the network analysis by selecting the more closely connected edges and nodes to build a module map of stroke.

No MeSH data available.


Related in: MedlinePlus