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Gene coexpression networks analysis of sickle stroke risk
Author(s) -
Liu FangFang,
Wang Juan,
Hu Fan,
Wei Qing,
Li Ke
Publication year - 2019
Publication title -
journal of cellular biochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.028
H-Index - 165
eISSN - 1097-4644
pISSN - 0730-2312
DOI - 10.1002/jcb.28780
Subject(s) - stroke (engine) , gene , computational biology , genetics , biology , engineering , mechanical engineering
Stroke is one of the most destructive complications of sickle cell disease (SCD), and SCD is also the most common cause of childhood stroke. Sickle cell stroke is complex and has a genetic endothelial basis. Here, we further investigated this genetic basis using weighted gene coexpression network analysis. This systems biology approach revealed the correlation between coexpressed gene modules and sickle stroke risk. The pink module was significantly correlated with stroke risk and genes in this module were mainly related to GO:0044877 (protein‐containing complex binding). In addition hub genes were identified through protein‐protein interaction enrichment analysis, including CXCR7, VCAM1, CD44, BMP2, SMAD3, BCL2L1, ITPR2, ITPR3, etc. These hub genes were significantly enriched for three Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways including “gastric acid secretion,” “pathways in cancer,” and “TGF‐ β signaling pathway.” Altogether, our results based on this innovative method provided some novel understanding of the pathology of sickle cell stroke. Hub genes identified in this study could be potential targets for screening and prevention of stroke risk in SCD children.