Identifying loci for the overlap between attention-deficit/hyperactivity disorder and autism spectrum disorder using a genome-wide QTL linkage approach

OBJECTIVE: The genetic basis for autism spectrum disorder (ASD) symptoms in children with attention-deficit/hyperactivity disorder (ADHD) was addressed using a genome-wide linkage approach. METHOD: Participants of the International Multi-Center ADHD Genetics study comprising 1,143 probands with ADHD and 1,453 siblings were analyzed. The total and subscale scores of the Social Communication Questionnaire (SCQ) were used as quantitative traits for multipoint regression-based linkage analyses on 5,407 autosomal single-nucleotide polymorphisms applying MERLIN-regress software, both without and with inclusion of ADHD symptom scores as covariates. RESULTS: The analyses without ADHD symptom scores as covariates resulted in three suggestive linkage signals, i.e., on chromosomes 15q24, 16p13, and 18p11. Inclusion of ADHD symptom scores as covariates resulted in additional suggestive loci on chromosomes 7q36 and 12q24, whereas the LOD score of the locus on chromosome 15q decreased below the threshold for suggestive linkage. The loci on 7q, 16p, and 18p were found for the SCQ restricted and repetitive subscale, that on 15q was found for the SCQ communication subscale, and that on 12q for the SCQ total score. CONCLUSIONS: Our findings suggest that QTLs identified in this study are ASD specific, although the 15q QTL potentially has pleiotropic effects for ADHD and ASD. This study confirms that genetic factors influence ASD traits along a continuum of severity, as loci potentially underlying ASD symptoms in children with ADHD were identified even though subjects with autism had been excluded from the IMAGE sample, and supports the hypothesis that differential genetic factors underlie the three ASD dimensions

Gene-ontology enrichment analysis in two independent family-based samples highlights biologically plausible processes for autism spectrum disorders

Recent genome-wide association studies (GWAS) have implicated a range of genes from discrete biological pathways in the aetiology of autism. However, despite the strong influence of genetic factors, association studies have yet to identify statistically robust, replicated major effect genes or SNPs. We apply the principle of the SNP ratio test methodology described by O'Dushlaine et al to over 2100 families from the Autism Genome Project (AGP). Using a two-stage design we examine association enrichment in 5955 unique gene-ontology classifications across four groupings based on two phenotypic and two ancestral classifications. Based on estimates from simulation we identify excess of association enrichment across all analyses. We observe enrichment in association for sets of genes involved in diverse biological processes, including pyruvate metabolism, transcription factor activation, cell-signalling and cell-cycle regulation. Both genes and processes that show enrichment have previously been examined in autistic disorders and offer biologically plausibility to these findings