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

The immune response to pathogens varies substantially among people. While both genetic and non-genetic factors contribute to inter-person variation, their relative contributions and potential predictive power have remained largely unknown. By systematically correlating host factors in 534 healthy vo...

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Detalles Bibliográficos
Autores principales: Bakker, Olivier B., Aguirre-Gamboa, Raul, Sanna, Serena, Oosting, Marije, Smeekens, Sanne P., Jaeger, Martin, Zorro, Maria, Võsa, Urmo, Withoff, Sebo, Netea-Maier, Romana T., Koenen, Hans J.P.M., Joosten, Irma, Xavier, Ramnik J., Franke, Lude, Joosten, Leo A.B., Kumar, Vinod, Wijmenga, Cisca, Netea, Mihai G., Li, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022810/
https://www.ncbi.nlm.nih.gov/pubmed/29784908
http://dx.doi.org/10.1038/s41590-018-0121-3
Descripción
Sumario:The immune response to pathogens varies substantially among people. While both genetic and non-genetic factors contribute to inter-person 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 capacity 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 inter-individual 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), while non-genetic factors influenced cytokine production as well.