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

Olivier B. Bakker, Raul Aguirre-Gamboa, Serena Sanna, Marije Oosting, Sanne P. Smeekens, Martin Jaeger, Maria Zorro, Urmo Vosa, Sebo Withoff, Romana T. Netea-Maier, Hans J. P. M. Koenen, Irma Joosten, Ramnik J. Xavier, Lude Franke, Leo A. B. Joosten, Vinod Kumar, Cisca Wijmenga, Mihai G. Netea, Yang Li

Research output: Contribution to journalArticleAcademicpeer-review

91 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)776-786
Number of pages16
JournalNature Immunology
Volume19
Issue number7
DOIs
Publication statusPublished - Jul-2018

Keywords

  • GENOME-WIDE ASSOCIATION
  • CHAIN FATTY-ACIDS
  • INFLAMMATORY-BOWEL-DISEASE
  • RECENT POSITIVE SELECTION
  • SUSCEPTIBILITY LOCI
  • GENETIC RISK
  • HUMAN GUT
  • TESTOSTERONE
  • LEPTIN
  • POPULATIONS

Fingerprint

Dive into the research topics of 'Integration of multi-omics data and deep phenotyping enables prediction of cytokine responses'. Together they form a unique fingerprint.

Cite this