title: The human miRNA repertoire of different blood compounds.
abstract: BACKGROUND
  MiRNAs from body fluids gain more and more attraction as biomarker candidates. Besides serum, patterns from whole blood are increasingly considered as markers for human pathologies. Usually, the contribution of different cell types to the respective signature remains however unknown. In this study we provide insights into the human miRNome of different compounds of the blood including CD3, CD14, CD15, CD19, CD56 positive cells as well as exosomes.
  
  
  METHODS
  We measured the miRNA repertoire for each cell type and whole blood for two individuals at three time points over the course of one year in order to provide evidence that the cell type miRNomes can be reproducibly detected.
  
  
  RESULTS
  For measurements repeated after 24 hours we found on average correlation of 0.97, even after one year profiles still correlated with 0.96, demonstrating the enormous stability of the cell type specific miRNomes. Highest correlation was found for CD15 positive cells, exceeding Pearson correlation of 0.99. For exosomes a significantly higher variability of miRNA expression was detected. In order to estimate the complexity and variability of the cell type specific miRNomes, we generated profiles for all considered cell types in a total of seven unaffected individuals. While CD15 positive cells showed the most complex miRNome consisting of 328 miRNAs, we detected significantly less miRNAs (186, p = 1.5*10(-5)) in CD19 positive cells. Moreover, our analysis showed functional enrichment in many relevant categories such as onco-miRNAs and tumor miRNA suppressors. Interestingly, exosomes were enriched just for onco-miRNAs but not for miRNA tumor suppressors.
  
  
  CONCLUSIONS
  In sum, our results provide evidence that blood cell type specific miRNomes are very consistent between individuals and over time.
authors.forename: Petra
authors.initials: P
authors.lastname: Leidinger
authors.forename: Christina
authors.initials: C
authors.lastname: Backes
authors.forename: Benjamin
authors.initials: B
authors.lastname: Meder
authors.forename: Eckart
authors.initials: E
authors.lastname: Meese
authors.affiliation: Chair for Clinical Bioinformatics, Saarland University, Saarbrücken, Germany. andreas.keller@ccb.uni-saarland.de.
authors.forename: Andreas
authors.initials: A
authors.lastname: Keller
mesh_terms: D000954:Antigens, Surface / Q000378:metabolism; D001773:Blood Cells / Q000378:metabolism*; D016000:Cluster Analysis; D019295:Computational Biology; D055354:Exosomes; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D035683:MicroRNAs / Q000235:genetics*; D009928:Organ Specificity / Q000235:genetics; D010641:Phenotype; D059467:Transcriptome
chemical_list: D000954:Antigens, Surface; D035683:MicroRNAs