Statistical modeling of interlocus interactions in a complex disease: Rejection of the multiplicative model of epistasis in type 1 diabetes

In general, common diseases do not follow a Mendelian inheritance pattern. To identify disease mechanisms and etiology, their genetic dissection may b e assisted by evaluation of linkage in mouse models of human disease. Stati stical modeling of multiple-locus linkage data from the nonobese diabetic ( NOD) mouse model of type 1 diabetes has previously provided evidence for ep istasis between alleles of several Idd (insulin-dependent diabetes) loci. T he construction of NOD congenic strains containing selected segments of the diabetes-resistant strain genome allows analysis of the joint effects of a lleles of different loci in isolation, without the complication of other se gregating Idd loci. In this article, we analyze data from congenic strains carrying two chromosome intervals (a double congenic strain) for two pairs of loci: Idd3 and Idd10 and Idd3 and Idd5. The joint action of both pairs i s consistent with models of additivity on either the log odds of the penetr ance, or the liability scale, rather than with the previously proposed mult iplicative model of epistasis. For Idd3 and Idd5 we would also not reject a model of additivity on the penetrance scale, which might indicate a diseas e model mediated by more than one pathway leading to beta -cell destruction and development of diabetes. However, there has been confusion between dif ferent definitions of interaction or epistasis as used in the biological, s tatistical, epidemiological, and quantitative and human genetics fields. Th e degree to which statistical analyses can elucidate underlying biologic me chanisms may be limited and may require prior knowledge of the underlying e tiology.