A new paper by Coutinho et al. that will be published later this year in Human Genetics uses MDR to identify nonadditive interactions that are predictive of autism susceptibility. There are several nice aspects of this paper that make it worth reading. First, this is one of the first papers to use the interaction dendrogram feature of the MDR software to provide a statistical intepretation of the multilocus model. Second, the authors used the Restricted Partitioning Method (RPM) of Culverhouse et al. (Genetic Epidemiology 2004) to identify similar interaction effects on seratonin levels. Thus, the discrete MDR analysis is showing the same thing as the the quantitative RPM analysis. This is the first time, to my knowledge, that epistasis has been documented at multiple levels of the hierarchy between genotype and phenotype in a human study of a complex disease.
Coutinho AM, Sousa I, Martins M, Correia C, Morgadinho T, Bento C, Marques C, Ataide A, Miguel TS, Moore JH, Oliveira G, Vicente AM. Evidence for epistasis between SLC6A4 and ITGB3 in autism etiology and in the determination of platelet serotonin levels. Human Genetics, in press (2007) [PubMed]
Autism is a neurodevelopmental disorder of unclear etiology. The consistent finding of platelet hyperserotonemia in a proportion of patients and its heritability within affected families suggest that genes involved in the serotonin system play a role in this disorder. The role in autism etiology of seven candidate genes in the serotonin metabolic and neurotransmission pathways and mapping to autism linkage regions (SLC6A4, HTR1A, HTR1D, HTR2A, HTR5A, TPH1 and ITGB3) was analyzed in a sample of 186 nuclear families. The impact of interactions among these genes in autism was assessed using the multifactor-dimensionality reduction (MDR) method in 186 patients and 181 controls. We further evaluated whether the effect of specific gene variants or gene interactions associated with autism etiology might be mediated by their influence on serotonin levels, using the quantitative transmission disequilibrium test (QTDT) and the restricted partition method (RPM), in a sample of 109 autistic children. We report a significant main effect of the HTR5A gene in autism (P = 0.0088), and a significant three-locus model comprising a synergistic interaction between the ITGB3 and SLC6A4 genes with an additive effect of HTR5A (P < 0.0010). In addition to the previously reported contribution of SLC6A4, we found significant associations of ITGB3 haplotypes with serotonin level distribution (P = 0.0163). The most significant models contributing to serotonin distribution were found for interactions between TPH1 rs4537731 and SLC6A4 haplotypes (P = 0.002) and between HTR1D rs6300 and SLC6A4 haplotypes (P = 0.013). In addition to the significant independent effects, evidence for interaction between SLC6A4 and ITGB3 markers was also found. The overall results implicate SLC6A4 and ITGB3 gene interactions in autism etiology and in serotonin level determination, providing evidence for a common underlying genetic mechanism and a molecular explanation for the association of platelet hyperserotonemia with autism.