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JOURNAL ARTICLE

Potential biomarkers and latent pathways for vasculitis based on latent pathway identification analysis

Tao Zhou, Yudong Zhang, Peng Wu, Qiang Sun, Yanan Guo, Yanfei Yang
International Journal of Rheumatic Diseases 2014, 17 (6): 671-8
24867262

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 (PBMCs) from healthy controls and vasculitis patients were downloaded from EBI Array Express database. Differentially expressed genes (DEGs) between normal and vasculitis PBMCs 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. DEGs were matched to NetBox software database to obtain LINKER genes with statistical significance. Protein-protein interaction (PPI) network was constructed with LINKER genes and DEGs according to STRING database. Latent pathway identification analysis (LPIA) was used to identify the most significant interactions among different pathways involved by DEGs.

RESULTS: A total of 266 DEGs 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 ISG15 and IFIT3 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. ISG15 and IFIT3 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.

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