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Comput Biol Chem. 2017 Jun;68:101-106. doi: 10.1016/j.compbiolchem.2017.02.007. Epub 2017 Feb 27.

Pathway cross-talk network analysis identifies critical pathways in neonatal sepsis.

Author information

1
Department of Neonatology, First People's Hospital of Jining, Jining, Shandong 272011, PR China.
2
Department of Neonatology, Maternal and Child Health Hospital of Sishui, Jining, Shandong 273200, PR China.
3
Department of Obstetrics, First People's Hospital of Jining, Jining, Shandong 272011, PR China. Electronic address: chendenghong1@163.com.
4
Department of Internal Medicine, Traditional Chinese Medicine Hospital of Yanzhou, Jining, Shandong 272000, PR China.

Abstract

BACKGROUND:

Despite advances in neonatal care, sepsis remains a major cause of morbidity and mortality in neonates worldwide. Pathway cross-talk analysis might contribute to the inference of the driving forces in bacterial sepsis and facilitate a better understanding of underlying pathogenesis of neonatal sepsis.

OBJECTIVE:

This study aimed to explore the critical pathways associated with the progression of neonatal sepsis by the pathway cross-talk analysis.

METHODS:

By integrating neonatal transcriptome data with known pathway data and protein-protein interaction data, we systematically uncovered the disease pathway cross-talks and constructed a disease pathway cross-talk network for neonatal sepsis. Then, attract method was employed to explore the dysregulated pathways associated with neonatal sepsis. To determine the critical pathways in neonatal sepsis, rank product (RP) algorithm, centrality analysis and impact factor (IF) were introduced sequentially, which synthetically considered the differential expression of genes and pathways, pathways cross-talks and pathway parameters in the network. The dysregulated pathways with the highest IF values as well as RP<0.01 were defined as critical pathways in neonatal sepsis.

RESULTS:

By integrating three kinds of data, only 6919 common genes were included to perform the pathway cross-talk analysis. By statistic analysis, a total of 1249 significant pathway cross-talks were selected to construct the pathway cross-talk network. Moreover, 47 dys-regulated pathways were identified via attract method, 20 pathways were identified under RP<0.01, and the top 10 pathways with the highest IF were also screened from the pathway cross-talk network. Among them, we selected 8 common pathways, i.e. critical pathways.

CONCLUSIONS:

In this study, we systematically tracked 8 critical pathways involved in neonatal sepsis by integrating attract method and pathway cross-talk network. These pathways might be responsible for the host response in infection, and of great value for advancing diagnosis and therapy of neonatal sepsis.

KEYWORDS:

Attractor; Differential pathway; Neonatal sepsis; Network; Pathway cross-talk

[Indexed for MEDLINE]

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