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Potential biomarkers and latent pathways for vasculitis based on latent pathway identification analysis
Author(s) -
Zhou Tao,
Zhang Yudong,
Wu Peng,
Sun Qiang,
Guo Yanan,
Yang Yanfei
Publication year - 2014
Publication title -
international journal of rheumatic diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.795
H-Index - 41
eISSN - 1756-185X
pISSN - 1756-1841
DOI - 10.1111/1756-185x.12391
Subject(s) - kegg , vasculitis , computational biology , signal transduction , biological pathway , identification (biology) , gene , biology , medicine , immunology , bioinformatics , genetics , disease , gene expression , transcriptome , pathology , botany
Aim We aimed in this study to identify the significant latent pathways and precise molecular mechanisms underlying the syndrome of vasculitis. Methods Agilent dual‐channel data of peripheral blood mononuclear cells ( PBMC s) from healthy controls and vasculitis patients were downloaded from EBI Array Express database. Differentially expressed genes ( DEG s) between normal and vasculitis PBMC s samples were selected. Gene Ontology ( GO ) and Kyoto Encyclopedia of Genes and Genomes ( KEGG ) pathway analyses were carried out to identify significant biological processes and pathways. DEG s were matched to NetBox software database to obtain LINKER genes with statistical significance. Protein–protein interaction ( PPI ) network was constructed with LINKER genes and DEG s according to STRING database. Latent pathway identification analysis ( LPIA ) was used to identify the most significant interactions among different pathways involved by DEG s. Results A total of 266 DEG s were selected. GO and KEGG pathway analysis showed that the up‐regulated genes were significantly enriched in defense and wounding response; the down‐regulated genes were enriched in immune response. The modules analysis of PPI network suggested that ISG 15 and IFIT 3 were the potential biomarkers for vasculitis. The results of LPIA showed that NOD ‐like receptor signaling pathway and shigellosis related pathway were the two most significant latent pathway interactions for vasculitis. ISG 15 and IFIT 3 were the potential biomarkers for vasculitis identification. Conclusion NOD ‐like receptor signaling pathway and shigellosis related pathway were the most significant latent pathway interactions for vasculitis. Moreover, LPIA was a useful method for revealing systemic biological pathways and cellular mechanisms of diseases.