Integration of multi-omics data and deep phenotyping enables prediction of cytokine responses

Nat Immunol. 2018 Jul;19(7):776-786. doi: 10.1038/s41590-018-0121-3. Epub 2018 May 21.


The immune response to pathogens varies substantially among people. Whereas both genetic and nongenetic factors contribute to interperson variation, their relative contributions and potential predictive power have remained largely unknown. By systematically correlating host factors in 534 healthy volunteers, including baseline immunological parameters and molecular profiles (genome, metabolome and gut microbiome), with cytokine production after stimulation with 20 pathogens, we identified distinct patterns of co-regulation. Among the 91 different cytokine-stimulus pairs, 11 categories of host factors together explained up to 67% of interindividual variation in cytokine production induced by stimulation. A computational model based on genetic data predicted the genetic component of stimulus-induced cytokine production (correlation 0.28-0.89), and nongenetic factors influenced cytokine production as well.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Autoimmune Diseases / genetics
  • Autoimmune Diseases / immunology
  • Cytokines / biosynthesis*
  • Cytokines / genetics
  • Female
  • Gene Expression Profiling
  • Genomics
  • Humans
  • Male
  • Metabolomics
  • Metagenomics
  • Middle Aged
  • Phenotype
  • Systems Biology
  • Young Adult


  • Cytokines