Identification of Jak-STAT signaling involvement in sarcoidosis severity via a novel microRNA-regulated peripheral blood mononuclear cell gene signature.
Tong ZhouNancy G CasanovaNima PouladiTing WangYves A LussierKenneth S KnoxJoe G N GarciaPublished in: Scientific reports (2017)
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.
Keyphrases
- peripheral blood
- gene expression
- genome wide
- signaling pathway
- copy number
- single cell
- transcription factor
- multiple sclerosis
- chronic kidney disease
- heart failure
- end stage renal disease
- stem cells
- rheumatoid arthritis
- long non coding rna
- epithelial mesenchymal transition
- machine learning
- amino acid
- atrial fibrillation
- ejection fraction