title: Sarcoidosis blood transcriptome reflects lung inflammation and overlaps with tuberculosis.
abstract: BACKGROUND
  Sarcoidosis is a granulomatous disease of unknown etiology, although M. tuberculosis may play a role in the pathogenesis. The traditional view holds that inflammation in sarcoidosis is compartmentalized to involved organs.
  
  
  OBJECTIVE
  To determine whether whole blood gene expression signatures reflect inflammatory pathways in the lung in sarcoidosis and whether these signatures overlap with tuberculosis.
  
  
  METHODS
  We analyzed transcriptomic data from blood and lung biopsies in sarcoidosis and compared these profiles with blood transcriptomic data from tuberculosis and other diseases.
  
  
  RESULTS
  Applying machine learning algorithms to blood gene expression data, we built a classifier that distinguished sarcoidosis from health in derivation and validation cohorts (92% sensitivity, 92% specificity). The most discriminative genes were confirmed by quantitative PCR and correlated with disease severity. Transcript profiles significantly induced in blood overlapped with those in lung biopsies and identified shared dominant inflammatory pathways (e.g., Type-I/II interferons). Sarcoidosis and tuberculosis shared more overlap in blood gene expression compared with other diseases using the 86-gene signature reported to be specific for tuberculosis and the sarcoidosis signature presented herein, although reapplication of machine learning algorithms could identify genes specific for sarcoidosis.
  
  
  CONCLUSIONS
  These data indicate that blood transcriptome analysis provides a noninvasive method for identifying inflammatory pathways in sarcoidosis, that these pathways may be leveraged to complement more invasive procedures for diagnosis or assessment of disease severity, and that sarcoidosis and tuberculosis share overlap in gene regulation of specific inflammatory pathways.
authors.affiliation: Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California, USA. Laura.Koth@ucsf.edu
authors.forename: Laura L
authors.initials: LL
authors.lastname: Koth
authors.forename: Owen D
authors.initials: OD
authors.lastname: Solberg
authors.forename: Jeffrey C
authors.initials: JC
authors.lastname: Peng
authors.forename: Nirav R
authors.initials: NR
authors.lastname: Bhakta
authors.forename: Christine P
authors.initials: CP
authors.lastname: Nguyen
authors.forename: Prescott G
authors.initials: PG
authors.lastname: Woodruff
mesh_terms: D000465:Algorithms; D001707:Biopsy, Needle; D016022:Case-Control Studies; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D007249:Inflammation / Q000235:genetics / Q000378:metabolism*; D008168:Lung / Q000276:immunology / Q000378:metabolism* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D060888:Real-Time Polymerase Chain Reaction; D017565:Sarcoidosis, Pulmonary / Q000097:blood / Q000235:genetics / Q000378:metabolism* / Q000473:pathology; D012720:Severity of Illness Index; D059467:Transcriptome / Q000235:genetics*; D014397:Tuberculosis, Pulmonary / Q000097:blood / Q000235:genetics / Q000378:metabolism*