BACKGROUND: The relationships between tonsillar immune responses, and viral infection and allergy are incompletely known. OBJECTIVE: To study intratonsillar/nasopharyngeal virus detections and in vivo expressions of T-cell- and innate immune response-specific cytokines, transcription factors, and type I/II/III interferons in human tonsils. METHODS: Palatine tonsil samples were obtained from 143 elective tonsillectomy patients. Adenovirus, bocavirus-1, coronavirus, enteroviruses, influenza virus, metapneumovirus, parainfluenza virus, rhinovirus, and respiratory syncytial virus were detected using PCR. The mRNA expression levels of IFN-α, IFN-β, IFN-γ, IL-10, IL-13, IL-17, IL-28, IL-29, IL-37, TGF-β, FOXP3, GATA3, RORC2, and Tbet were directly analyzed by quantitative RT-PCR. RESULTS: Fifty percentage of subjects reported allergy, 59% had ≥1 nasopharyngeal viruses, and 24% had ≥1 intratonsillar viruses. Tonsillar virus detection showed a strong negative association with age; especially rhinovirus or parainfluenza virus detection showed positive association with IFN-γ and Tbet expressions. IL-37 expression was positively associated with atopic dermatitis, whereas IFN-α, IL-13, IL-28, and Tbet expressions were negatively associated with allergic diseases. Network analyses demonstrated strongly polarized clusters of immune regulatory (IL-10, IL-17, TGF-β, FOXP3, GATA3, RORC2, Tbet) and antiviral (IFN-α, IFN-β, IL-28, IL-29) genes. These two clusters became more distinctive in the presence of viral infection or allergy. A negative correlation between antiviral cytokines and IL-10, IL-17, IL-37, FOXP3, and RORC2 was observed only in the presence of viruses, and interestingly, IL-13 strongly correlated with antiviral cytokines. CONCLUSIONS: Tonsillar cytokine expression is closely related to existing viral infections, age, and allergic illnesses and shows distinct clusters between antiviral and immune regulatory genes.
Abstract
BACKGROUND: The relationships between tonsillar immune responses, and viral infection and allergy are incompletely known. OBJECTIVE: To study intratonsillar/nasopharyngeal virus detections and in vivo expressions of T-cell- and innate immune response-specific cytokines, transcription factors, and type I/II/III interferons in human tonsils. METHODS: Palatine tonsil samples were obtained from 143 elective tonsillectomy patients. Adenovirus, bocavirus-1, coronavirus, enteroviruses, influenza virus, metapneumovirus, parainfluenza virus, rhinovirus, and respiratory syncytial virus were detected using PCR. The mRNA expression levels of IFN-α, IFN-β, IFN-γ, IL-10, IL-13, IL-17, IL-28, IL-29, IL-37, TGF-β, FOXP3, GATA3, RORC2, and Tbet were directly analyzed by quantitative RT-PCR. RESULTS: Fifty percentage of subjects reported allergy, 59% had ≥1 nasopharyngeal viruses, and 24% had ≥1 intratonsillar viruses. Tonsillar virus detection showed a strong negative association with age; especially rhinovirus or parainfluenza virus detection showed positive association with IFN-γ and Tbet expressions. IL-37 expression was positively associated with atopic dermatitis, whereas IFN-α, IL-13, IL-28, and Tbet expressions were negatively associated with allergic diseases. Network analyses demonstrated strongly polarized clusters of immune regulatory (IL-10, IL-17, TGF-β, FOXP3, GATA3, RORC2, Tbet) and antiviral (IFN-α, IFN-β, IL-28, IL-29) genes. These two clusters became more distinctive in the presence of viral infection or allergy. A negative correlation between antiviral cytokines and IL-10, IL-17, IL-37, FOXP3, and RORC2 was observed only in the presence of viruses, and interestingly, IL-13 strongly correlated with antiviral cytokines. CONCLUSIONS: Tonsillar cytokine expression is closely related to existing viral infections, age, and allergic illnesses and shows distinct clusters between antiviral and immune regulatory genes.
TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.