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

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.

SUBMITTER: Bakker OB

PROVIDER: S-EPMC6022810 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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

Bakker Olivier B OB Aguirre-Gamboa Raul R Sanna Serena S Oosting Marije M Smeekens Sanne P SP Jaeger Martin M Zorro Maria M Võsa Urmo U Withoff Sebo S Netea-Maier Romana T RT Koenen Hans J P M HJPM Joosten Irma I Xavier Ramnik J RJ Franke Lude L Joosten Leo A B LAB Kumar Vinod V Wijmenga Cisca C Netea Mihai G MG Li Yang Y

Nature immunology 20180521 7

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 distin ...[more]

PMID: 29784908

Dataset Information

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

Publications

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

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