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This article is part of the supplement: The International Conference on Intelligent Biology and Medicine (ICIBM): Systems Biology

Open Access Research

Potential metabolic mechanism of girls' central precocious puberty: a network analysis on urine metabonomics data

Linlin Yang12, Kailin Tang2, Ying Qi3, Hao Ye24, Wenlian Chen5, Yongyu Zhang3* and Zhiwei Cao126*

Author affiliations

1 School of Life Science and Technology, Tongji University, Shanghai 200092, China

2 Shanghai Center for Bioinformation Technology, Shanghai 200235, China

3 Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China

4 State Key Laboratory of Bioreactor Engineering, East China University of Science & Technology, Shanghai 200237, China

5 State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Rui Jin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China

6 Key Laboratory of Liver and Kidney Diseases (Shanghai University of Traditional Chinese Medicine), Ministry of Education, Shanghai 200021, China

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Citation and License

BMC Systems Biology 2012, 6(Suppl 3):S19  doi:10.1186/1752-0509-6-S3-S19

Published: 17 December 2012

Abstract

Background

Central precocious puberty (CPP) is a common pediatric endocrine disease caused by early activation of hypothalamic-putuitary-gonadal (HPG) axis, yet the exact mechanism was poorly understood. Although there were some proofs that an altered metabolic profile was involved in CPP, interpreting the biological implications at a systematic level is still in pressing need. To gain a systematic understanding of the biological implications, this paper analyzed the CPP differential urine metabolites from a network point of view.

Results

In this study, differential urine metabolites between CPP girls and age-matched normal ones were identified by LC-MS. Their basic topological parameters were calculated in the background network. The network decomposition suggested that CPP differential urine metabolites were most relevant to amino acid metabolism. Further proximity analysis of CPP differential urine metabolites and neuro-endocrine metabolites showed a close relationship between CPP metabolism and neuro-endocrine system. Then the core metabolic network of CPP was successfully constructed among all these differential urine metabolites. As can be demonstrated in the core network, abnormal aromatic amino acid metabolism might influence the activity of HPG and hypothalamic pituitary adrenal (HPA) axis. Several adjustments to the early activation of puberty in CPP girls could also be revealed by urine metabonomics.

Conclusions

The present article demonstrated the ability of urine metabonomics to provide several potential metabolic clues for CPP's mechanism. It was revealed that abnormal metabolism of amino acid, especially aromatic amino acid, might have a close correlation with CPP's pathogenesis by activating HPG axis and suppressing HPA axis. Such a method of network-based analysis could also be applied to other metabonomics analysis to provide an overall perspective at a systematic level.