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Complex networks of cytokines interact in a dynamic way to homeostatically regulate immune responses and other biological pathways. It is, therefore, not surprising that variation in cytokine level has been correlated with disease susceptibility and process. A fundamental issue is whether such variation is a primary cause for disease or reflects secondary inflammatory change. This can be unravelled by investigating cytokine gene polymorphism to determine whether a genetic basis for cytokine dysregulation is associated with disease. Thousands of disease association studies investigating cytokine gene polymorphisms have been reported although many have not been replicated. This is largely due to lack of statistical power, poor definition of clinical phenotype and lack of matching between cases and controls. An appropriate study design should include:• sufficient numbers of cases and controls to generate adequate statistical power;• cases and controls being well matched and taken from the same homogeneous population;• testing of multiple SNPs within the candidate gene and an analysis based on SNP haplotypes;• analysis of a second data set.Any genetic analysis of cytokine genes in disease studies should also take into account the fact that cytokines rarely manifest their effects in isolation but rather work in complex regulatory networks. Thus, gene–gene and gene–environment interactions may be at the centre of any disease association. Statistical methods are now being introduced to determine such relationships and this should ultimately allow a more accurate estimate of disease risk for individuals with particular cytokine gene profiles.