| 1. |
- Patin, Etienne, et al.
(författare)
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Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors
- 2018
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Ingår i: Nature Immunology. - : Springer Science and Business Media LLC. - 1529-2908 .- 1529-2916. ; 19, s. 302-314
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Tidskriftsartikel (refereegranskat)abstract
- The quantification and characterization of circulating immune cells provide key indicators of human health and disease. To identify the relative effects of environmental and genetic factors on variation in the parameters of innate and adaptive immune cells in homeostatic conditions, we combined standardized flow cytometry of blood leukocytes and genome-wide DNA genotyping of 1,000 healthy, unrelated people of Western European ancestry. We found that smoking, together with age, sex and latent infection with cytomegalovirus, were the main non-genetic factors that affected variation in parameters of human immune cells. Genome-wide association studies of 166 immunophenotypes identified 15 loci that showed enrichment for disease-associated variants. Finally, we demonstrated that the parameters of innate cells were more strongly controlled by genetic variation than were those of adaptive cells, which were driven by mainly environmental exposure. Our data establish a resource that will generate new hypotheses in immunology and highlight the role of innate immunity in susceptibility to common autoimmune diseases.
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| 2. |
- Piasecka, Barbara, et al.
(författare)
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Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges
- 2017
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Ingår i: Proceedings of the National Academy of Sciences. - 1091-6490. ; 115:3, s. 488-497
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Tidskriftsartikel (refereegranskat)abstract
- The contribution of host genetic and nongenetic factors to immunological differences in humans remains largely undefined. Here, we generated bacterial-, fungal-, and viral-induced immune transcriptional profiles in an age- and sex-balanced cohort of 1,000 healthy individuals and searched for the determinants of immune response variation. We found that age and sex affected the transcriptional response of most immune-related genes, with age effects being more stimulus-specific relative to sex effects, which were largely shared across conditions. Although specific cell populations mediated the effects of age and sex on gene expression, including CD8+ T cells for age and CD4+ T cells and monocytes for sex, we detected a direct effect of these intrinsic factors for the majority of immune genes. The mapping of expression quantitative trait loci (eQTLs) revealed that genetic factors had a stronger effect on immune gene regulation than age and sex, yet they affected a smaller number of genes. Importantly, we identified numerous genetic variants that manifested their regulatory effects exclusively on immune stimulation, including a Candida albicans-specific master regulator at the CR1 locus. These response eQTLs were enriched in disease-associated variants, particularly for autoimmune and inflammatory disorders, indicating that differences in disease risk may result from regulatory variants exerting their effects only in the presence of immune stress. Together, this study quantifies the respective effects of age, sex, genetics, and cellular heterogeneity on the interindividual variability of immune responses and constitutes a valuable resource for further exploration in the context of different infection risks or disease outcomes.
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| 3. |
- Urrutia, Alejandra, et al.
(författare)
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Standardized Whole-Blood Transcriptional Profiling Enables the Deconvolution of Complex Induced Immune Responses
- 2016
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Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 16:10, s. 2777-2791
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Tidskriftsartikel (refereegranskat)abstract
- Systems approaches for the study of immune signaling pathways have been traditionally based on purified cells or cultured lines. However, in vivo responses involve the coordinated action of multiple cell types, which interact to establish an inflammatory microenvironment. We employed standardized whole-blood stimulation systems to test the hypothesis that responses to Toll-like receptor ligands or whole microbes can be defined by the transcriptional signatures of key cytokines. We found 44 genes, identified using Support Vector Machine learning, that captured the diversity of complex innate immune responses with improved segregation between distinct stimuli. Furthermore, we used donor variability to identify shared inter-cellular pathways and trace cytokine loops involved in gene expression. This provides strategies for dimension reduction of large datasets and deconvolution of innate immune responses applicable for characterizing immunomodulatory molecules. Moreover, we provide an interactive R-Shiny application with healthy donor reference values for induced inflammatory genes.
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