Friday, May 21, 2010
Franklin Hall B Level 4 (Philadelphia Marriott Downtown)
9:00 AM
Background: Recent genome-wide association (GWA) studies, have implicated a range of genes from discrete biological pathways in the aetiology of autism. However, despite the strong influence of genetic factors autism, linkage studies and association studies have yet to identify robust major effect genes or SNPs. Objectives: It is possible and plausible that real genetic risk exists within the milieu of nominal to strong association signal observed in the GWAS data. One approach to data-mine the GWA data for additional information is to formally test for enrichment of signal in groups of biologically linked genes such as gene pathways. Here we present a modification to the SNP-ratio test (SRT) methodology described by O’Dushlaine et al., (2009) to apply to family-based designs. Methods: Using the modified family-based SRT, we performed a hypothesis-free analysis of all gene-ontology gene sets and identify four pathways that show enriched signals in a GWAS of a narrow diagnosis of autism from the Autism Genome Project (AGP). Empirical P-values were calculated from 10000 simulation GWAS using affection shuffling between probands and pseudo-probands generated from the non-transmitted chromosomes. Sensitivity to single genes of the top-pathways was examined. Results: Five pathways with multiple genes driving the association were identified. These include gene sets involved in neuron migration, brain development, glial-cell differentiation, neuro-immunological response and fidelity of mitosis. These processes have previously been proposed as important in the aetiology of autism. Conclusions: The application of a pathway approach to the AGP GWAS data has provided additional evidence to support hypothesised biological processes implicated in autism. Further characterisation of these sets of genes may offer additional data from the GWA to understand genetic risk of autism.