Most human diseases result from complex interactions among multiple genes that yield weak or modest effects. Despite the growing awareness of the importance of gene-gene interactions, the paradigm of detectable effects of individual variants remains the cornerstone of genome association studies with tagSNPs. The interactive effect of two variants is only tested once the individual effect of one variant is detected. Both genes, however, may have at the same time a weak (or even no) marginal effect but an important effect through their interaction. In such a situation, current approaches may fail to detect variants having a crucial role in the causal chain. Here, we propose a new strategy: the 2-locus TDT. It allows the detection of the involvement of two genes without individual effect. Our strategy simultaneously uses information on biallelic candidate polymorphisms in two genes M and N. We first estimate the relative marginal penetrances of the genotype at each locus and of the joint (two-locus) genotype and then we test for the interactive effect of the two genes using a likelihood ratio test. We show that our approach has good power to detect the effect of two genes in situations for which a locus-by-locus strategy would have been unsuccessful. At a time where genome-wide association studies are fashionable, we think it is important to consider the strategy of studying good candidate pathways with our approach. Copyright (c) 2007 S. Karger AG, Basel.