Bioinformatic meta-analysis reveals novel differentially expressed genes and pathways in sarcoidosis.

Introduction: Sarcoidosis is a multi-system inflammatory disease of unknown origin with heterogeneous clinical manifestations varying from a single organ non-caseating granuloma site to chronic systemic inflammation and fibrosis. Gene expression studies have suggested several genes and pathways implicated in the pathogenesis of sarcoidosis, however, due to differences in study design and variable statistical approaches, results were frequently not reproducible or concordant. Therefore, meta-analysis of sarcoidosis gene-expression datasets is of great importance to robustly establish differentially expressed genes and signalling pathways. Methods: We performed meta-analysis on 22 published gene-expression studies on sarcoidosis. Datasets were analysed systematically using same statistical cut-offs. Differentially expressed genes were identified by pooling of Results: A consistent and significant signature of novel and well-known genes was identified, those collectively implicated both type I and type II interferon mediated signalling pathways in sarcoidosis. Discussion: Our analysis provides a concise gene signature in sarcoidosis and expands our knowledge about the pathogenesis. Our results are of importance to improve current diagnostic approaches and monitoring strategies as well as in the development of targeted therapeutics.