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Synchronization of the Normal Human Peripheral Immune System: A Comprehensive Circadian Systems Immunology Analysis
In this study, we sought to fill an important gap in fundamental immunology research by conducting a comprehensive systems immunology analysis of daily variation in the normal human peripheral immune system. Although variation due to circadian rhythmicity was not a significant source of variation in...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6971086/ https://www.ncbi.nlm.nih.gov/pubmed/31959869 http://dx.doi.org/10.1038/s41598-019-56951-5 |
Sumario: | In this study, we sought to fill an important gap in fundamental immunology research by conducting a comprehensive systems immunology analysis of daily variation in the normal human peripheral immune system. Although variation due to circadian rhythmicity was not a significant source of variation in daily B-cell levels or any CD4+ functional subset, it accounted for more than 25% of CD4+ regulatory T-cell variation and over 50% of CD8+ central memory variation. Circadian rhythmicity demonstrated phase alignment within functional phenotypes. In addition, we observed that previously-described mechanistic relationships can also appear in the peripheral system as phase shifting in rhythmic patterns. We identified a set of immune factors which are ubiquitously correlated with other factors and further analysis also identified a tightly-correlated “core” set whose relational structure persisted after analytically removing circadian-related variation. This core set consisted of CD8+ and its subpopulations and the NK population. In sum, the peripheral immune system can be conceptualized as a dynamic, interconnected wave-field repeating its pattern on a daily basis. Our data provide a comprehensive inventory of synchronization and correlation within this wave-field and we encourage use of our data to discover unknown mechanistic relationships which can then be tested in the laboratory. |
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