Yafei Li1, Bo Wu, Hongyan Xiong, Caizhong Zhu, Lu Zhang. 1. Department of Epidemiology, College of Preventive Medicine, Third Military Medical University, Chongqing 400038, PR China. yafeilye@yahoo.com.cn
Abstract
BACKGROUND: Asthma is a complex disease resulting from multiple gene-gene and gene-environment interactions. Study on gene-gene interactions could provide insight into the pathophysiologic mechanisms of the disease. OBJECTIVES: We investigated the single nucleotide polymorphisms and interactions among three different loci in three candidate genes (STAT-6 G2964A, STAT-4 T90089C and IFN-gamma T874A) in 95 Chinese asthmatic subjects and 95 matched controls to determine the possible associations with asthma. METHODS: Genotyping of the gene polymorphisms was performed by means of PCR-SSCP analysis. Genotype-phenotype associations were examined in dominant and recessive genetic models using logistic regression. The method of multifactor dimensionality reduction was used to analyze gene-gene interactions. RESULTS: No statistically significant difference was found in the distribution of the STAT-6 G2964A polymorphisms between asthmatic patients and controls in this case-control study. The STAT-4 T90089C polymorphisms were significantly associated with asthma in the dominant model (p=0.007). As for the IFN-gamma T874A, the significant associations were found in both dominant model (p=0.004) and recessive model (p=0.006). A significant gene-gene interaction was found among STAT-6, STAT-4 and IFN-gamma on the risk of asthma. In the best 3-locus model, the odds ratio for the high-risk to the low-risk group was 6.9 (95% CI, 3.5-13.7; p<0.0001). CONCLUSIONS: Our findings suggest that STAT-4 T90089C and IFN-gamma T874A polymorphisms might be the genetic factors for the risk of asthma in the Chinese population. In addition, the significant interactions among STAT-6 G2964A, STAT-4 T90089C and IFN-gamma T874A may increase an individual's susceptibility and contribute to the pathogenesis of asthma.
BACKGROUND:Asthma is a complex disease resulting from multiple gene-gene and gene-environment interactions. Study on gene-gene interactions could provide insight into the pathophysiologic mechanisms of the disease. OBJECTIVES: We investigated the single nucleotide polymorphisms and interactions among three different loci in three candidate genes (STAT-6G2964A, STAT-4T90089C and IFN-gammaT874A) in 95 Chinese asthmatic subjects and 95 matched controls to determine the possible associations with asthma. METHODS: Genotyping of the gene polymorphisms was performed by means of PCR-SSCP analysis. Genotype-phenotype associations were examined in dominant and recessive genetic models using logistic regression. The method of multifactor dimensionality reduction was used to analyze gene-gene interactions. RESULTS: No statistically significant difference was found in the distribution of the STAT-6G2964A polymorphisms between asthmatic patients and controls in this case-control study. The STAT-4T90089C polymorphisms were significantly associated with asthma in the dominant model (p=0.007). As for the IFN-gammaT874A, the significant associations were found in both dominant model (p=0.004) and recessive model (p=0.006). A significant gene-gene interaction was found among STAT-6, STAT-4 and IFN-gamma on the risk of asthma. In the best 3-locus model, the odds ratio for the high-risk to the low-risk group was 6.9 (95% CI, 3.5-13.7; p<0.0001). CONCLUSIONS: Our findings suggest that STAT-4T90089C and IFN-gammaT874A polymorphisms might be the genetic factors for the risk of asthma in the Chinese population. In addition, the significant interactions among STAT-6G2964A, STAT-4T90089C and IFN-gammaT874A may increase an individual's susceptibility and contribute to the pathogenesis of asthma.
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