Scientific Reports · 2017 · 83 citations · 39 references
Life SciencesImmunologyMolecular BiologyGene ExpressionImmunopathologyInflammationExpression Signature DiscoveryInflammatory SignalingMicrorna BiologyMicrorna-mediated RegulationNoncoding Rna TranscriptomicsTranscriptomic ProfilingClinical RemissionDifferential Protein-coding Gene ExpressionGranulomatous Lung InflammationMicrorna BiomarkersMicrorna Dysregulation In DiseaseMicrorna Expression ProfilingMicrorna GenesMicrorna Profiling
Sarcoidosis is a granulomatous lung disorder of unknown cause. The majority of individuals with sarcoidosis spontaneously achieve full remission (uncomplicated sarcoidosis), however, ~20% of sarcoidosis-affected individuals experience progressive lung disease or cardiac and nervous system involvement (complicated sarcoidosis). We investigated peripheral blood mononuclear cell (PBMC) microRNA and protein-coding gene expression data from healthy controls and patients with uncomplicated or complicated sarcoidosis. We identified 46 microRNAs and 1,559 genes that were differentially expressed across a continuum of sarcoidosis severity (healthy control → uncomplicated sarcoidosis → complicated sarcoidosis). A total of 19 microRNA-mRNA regulatory pairs were identified within these deregulated microRNAs and mRNAs, which consisted of 17 unique protein-coding genes yielding a 17-gene signature. Pathway analysis of the 17-gene signature revealed Jak-STAT signaling pathway as the most significantly represented pathway. A severity score was assigned to each patient based on the expression of the 17-gene signature and a significant increasing trend in the severity score was observed from healthy control, to uncomplicated sarcoidosis, and finally to complicated sarcoidosis. In addition, this microRNA-regulated gene signature differentiates sarcoidosis patients from healthy controls in independent validation cohorts. Our study suggests that PBMC gene expression is useful in diagnosis of sarcoidosis.
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Gene Ontology: tool for the unification of biology
Michael Ashburner, Catherine A. Ball, Judith A. Blake et al. · Nature Genetics · 2000 · 44.6K citations · Full text
The KEGG resource for deciphering the genome
M. Kanehisa · Nucleic Acids Research · 2003 · 5.3K citations · Full text