Understanding the Pathogenesis of Kawasaki Disease by Network and Pathway Analysis
Author(s) -
Yu-wen Lv,
Jing Wang,
Ling Sun,
Jianmin Zhang,
Lei Cao,
Yueyue Ding,
Ye Chen,
Ji-juan Dou,
Jie Huang,
Yifei Tang,
Wentao Wu,
Weirong Cui,
Haitao Lv
Publication year - 2013
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2013/989307
Subject(s) - pathogenesis , gene , immune system , biology , disease , signal transduction , immunology , genetics , transcription factor , genome wide association study , computational biology , medicine , single nucleotide polymorphism , pathology , genotype
Kawasaki disease (KD) is a complex disease, leading to the damage of multisystems. The pathogen that triggers this sophisticated disease is still unknown since it was first reported in 1967. To increase our knowledge on the effects of genes in KD, we extracted statistically significant genes so far associated with this mysterious illness from candidate gene studies and genome-wide association studies. These genes contributed to susceptibility to KD, coronary artery lesions, resistance to initial IVIG treatment, incomplete KD, and so on. Gene ontology category and pathways were analyzed for relationships among these statistically significant genes. These genes were represented in a variety of functional categories, including immune response, inflammatory response, and cellular calcium ion homeostasis. They were mainly enriched in the pathway of immune response. We further highlighted the compelling immune pathway of NF-AT signal and leukocyte interactions combined with another transcription factor NF- κ B in the pathogenesis of KD. STRING analysis, a network analysis focusing on protein interactions, validated close contact between these genes and implied the importance of this pathway. This data will contribute to understanding pathogenesis of KD.
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