Journal of North Khorasan

Abstract Background & objectives:. Despite extensive studies conducted on single nucleotide polymorphisms (SNPs) effects on different diseases, but the necessity of investigation into interaction of these SNPs together in diseases in particular genetic based diseases in one hand and existence of a large number of these variables and also weakness of classical statiscal models in including such variables in the other hand , underline the necessity of applying new statiscal method to determine these interaction effects .In this study we used logic feature selection approach to determine important SNP interactions associated with systemic lupus erythematosus. Material & Methods: We use information of 11 SNPs located in the genes IL-1 cluster ، IL-10 ، TNF-α، IL-4Rα for 376 subjects (188 control subjects and 188 case)to determine influential SNP interactions in patients affected with systemic lupus erythematosus disease using logic feature selection. Consequently, the results were used in logistic regression model. Results: the result of the logic feature selection approach led to the identification of two two-way interactions, but in the final logistic regression model only two-way interaction related to polymorphisms in TNF-α was shown to be significant on occurrence of systemic lupus erythematosus disease. Conclusion: According to our results, it seems that the results of the modern statistical methods like logic feature selection can helpful to find the important SNP interactions associated with disease in studies with large number of variables.