title: Potential biomarkers and latent pathways for vasculitis based on latent pathway identification analysis.
abstract: OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: The Second Hospital of Shandong University, Jinan, Shandong Province, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Zhou
authors.forename: Yudong
authors.initials: Y
authors.lastname: Zhang
authors.forename: Peng
authors.initials: P
authors.lastname: Wu
authors.forename: Qiang
authors.initials: Q
authors.lastname: Sun
authors.forename: Yanan
authors.initials: Y
authors.lastname: Guo
authors.forename: Yanfei
authors.initials: Y
authors.lastname: Yang
mesh_terms: D016022:Case-Control Studies; D016207:Cytokines / Q000235:genetics; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods; D005786:Gene Expression Regulation; D063990:Gene Ontology; D053263:Gene Regulatory Networks; D005819:Genetic Markers; D006801:Humans; D047908:Intracellular Signaling Peptides and Proteins / Q000235:genetics; D007963:Leukocytes, Mononuclear / Q000737:chemistry* / Q000276:immunology; D060066:Protein Interaction Maps; D015398:Signal Transduction / Q000235:genetics; D014452:Ubiquitins / Q000235:genetics; D014657:Vasculitis / Q000097:blood / Q000235:genetics* / Q000276:immunology
chemical_list: D016207:Cytokines; D005819:Genetic Markers; C116468:IFIT3 protein, human; D047908:Intracellular Signaling Peptides and Proteins; D014452:Ubiquitins; C074034:ISG15 protein, human
keywords: differentially expressed genes; latent pathway identification analysis; pathways; vasculitis