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对中断模块的系统追踪识别出与唐氏综合征先天性心脏病相关的改变通路。

Systematic Tracking of Disrupted Modules Identifies Altered Pathways Associated with Congenital Heart Defects in Down Syndrome.

作者信息

Chen Denghong, Zhang Zhenhua, Meng Yuxiu

机构信息

Department of Obstetrics, Jining No. 1 People's Hospital, Jining, Shandong, China (mainland).

Department of Children's Health Prevention, Jining No. 1 People's Hospital, Jining, Shandong, China (mainland).

出版信息

Med Sci Monit. 2015 Nov 2;21:3334-42. doi: 10.12659/msm.896001.

Abstract

BACKGROUND

This work aimed to identify altered pathways in congenital heart defects (CHD) in Down syndrome (DS) by systematically tracking the dysregulated modules of reweighted protein-protein interaction (PPI) networks.

MATERIAL AND METHODS

We performed systematic identification and comparison of modules across normal and disease conditions by integrating PPI and gene-expression data. Based on Pearson correlation coefficient (PCC), normal and disease PPI networks were inferred and reweighted. Then, modules in the PPI network were explored by clique-merging algorithm; altered modules were identified via maximum weight bipartite matching and ranked in non-increasing order. Finally, pathways enrichment analysis of genes in altered modules was carried out based on Database for Annotation, Visualization, and Integrated Discovery (DAVID) to study the biological pathways in CHD in DS.

RESULTS

Our analyses revealed that 348 altered modules were identified by comparing modules in normal and disease PPI networks. Pathway functional enrichment analysis of disrupted module genes showed that the 4 most significantly altered pathways were: ECM-receptor interaction, purine metabolism, focal adhesion, and dilated cardiomyopathy.

CONCLUSIONS

We successfully identified 4 altered pathways and we predicted that these pathways would be good indicators for CHD in DS.

摘要

背景

本研究旨在通过系统追踪重新加权的蛋白质-蛋白质相互作用(PPI)网络中失调的模块,来识别唐氏综合征(DS)先天性心脏病(CHD)中改变的通路。

材料与方法

我们通过整合PPI和基因表达数据,对正常和疾病状态下的模块进行系统识别和比较。基于皮尔逊相关系数(PCC),推断并重新加权正常和疾病的PPI网络。然后,通过团合并算法探索PPI网络中的模块;通过最大权重二分匹配识别改变的模块,并按降序排列。最后,基于注释、可视化和综合发现数据库(DAVID)对改变模块中的基因进行通路富集分析,以研究DS中CHD的生物学通路。

结果

我们的分析表明,通过比较正常和疾病PPI网络中的模块,识别出348个改变的模块。对破坏模块基因的通路功能富集分析表明,4个改变最显著的通路是:细胞外基质-受体相互作用、嘌呤代谢、粘着斑和扩张型心肌病。

结论

我们成功识别出4条改变的通路,并预测这些通路将是DS中CHD的良好指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17bd/4635630/fd3d08f1edb7/medscimonit-21-3334-g001.jpg

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