Background: Asthma is a common complex genetic disease. While the T-helper cell 1 pathway is determined by cytokine interferon-gamma (IFN-γ), the T-helper cell 2 pathway is determined by IL-4. These comprise two alternative CD4+ T-cell fates with functional consequences for the host immune system. W...
Background: Asthma is a common complex genetic disease. While the T-helper cell 1 pathway is determined by cytokine interferon-gamma (IFN-γ), the T-helper cell 2 pathway is determined by IL-4. These comprise two alternative CD4+ T-cell fates with functional consequences for the host immune system. We investigated the effect of interaction between and IL-4 SNPs on asthma or atopy. Method: Three hundred asthmatics and 300 unrelated normal controls were enrolled. Two candidate SNPs of the IFN-γ gene and two SNPs of the IL-4 gene were selected. Gene-gene interactions were tested using the multi-factor dimensionality reduction (MDR) method and interaction information analysis on the basis of Shannon entropy. Result: In MDR analysis, a combination of IFN-γ+2459A>G and IL-4-589C>T was the best model to predict atopy. In interaction information analysis, there was a strong effect of interaction between theses two SNPs on atopy. This combination showed a stronger effect than each SNP alone. In addition, IL-4-589C>T showed a strong effect on atopy with IFN-γ+2671C>T and with IFN-γ+2459A>G. Theses effects were prominent in normal controls. Conclusion: From the findings of a statistical interaction model, it is suggested that IFN-γ and IL-4 gene SNPs may contributes to the development of atopy by interacting with each other.
Background: Asthma is a common complex genetic disease. While the T-helper cell 1 pathway is determined by cytokine interferon-gamma (IFN-γ), the T-helper cell 2 pathway is determined by IL-4. These comprise two alternative CD4+ T-cell fates with functional consequences for the host immune system. We investigated the effect of interaction between and IL-4 SNPs on asthma or atopy. Method: Three hundred asthmatics and 300 unrelated normal controls were enrolled. Two candidate SNPs of the IFN-γ gene and two SNPs of the IL-4 gene were selected. Gene-gene interactions were tested using the multi-factor dimensionality reduction (MDR) method and interaction information analysis on the basis of Shannon entropy. Result: In MDR analysis, a combination of IFN-γ+2459A>G and IL-4-589C>T was the best model to predict atopy. In interaction information analysis, there was a strong effect of interaction between theses two SNPs on atopy. This combination showed a stronger effect than each SNP alone. In addition, IL-4-589C>T showed a strong effect on atopy with IFN-γ+2671C>T and with IFN-γ+2459A>G. Theses effects were prominent in normal controls. Conclusion: From the findings of a statistical interaction model, it is suggested that IFN-γ and IL-4 gene SNPs may contributes to the development of atopy by interacting with each other.
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