Objectives: Here, we examine two previously-unexplored models for the molecular genetic basis of this hypothesized phenomenon: the first to determine whether there exist systematic differences in common variant profiles of mothers of children with autism in known autism risk alleles; the second to identify a possible contribution of maternal genotype to environmental susceptibilities of their offspring.
Methods: These models are tested both utilizing genetic epidemiological approaches employing the IAN registry, as well as analysis of data from the Simons Simplex Collection(SSC) and Autism Genetic Research Exchange (AGRE). Parents of probands were selected from AGRE dataset, and individuals genotyped from the same platform were collected from iControlDB. Principal components analysis was done to identify population substructure using smartpca. Components were taken as covariates in eventual association tests to correct for population substructure. After data cleaning, we obtained 561 AGRE mothers, 547 AGRE fathers, 508 iControl females, and 547 iControl males. To identify alleles present specifically in mothers that may be contributing to autism risk in their offspring, we compared AGRE mothers to AGRE fathers as well as to iControl females. A two-way association analysis was done using PLINK based on the logistic model, with the assumption non-spurious results should be nominally significant in both comparisons. For replication, we repeated the same analysis using the SSC collection and independent controls.
Results: Within our power to detect differences in this initial exploration (OR>2.5), we did not discover polymorphisms that reached genome-wide significance in the mothers of children with autism. However, we identified 14 SNPs with p-value<10E-6 (compared to 8 expected by chance), suggesting alleles in the mothers’ genomes that may make a contribution to autism risk. None of the regions identified from previous common variant studies of autism were among our top candidates, indicating that if these eventually replicate they might index specific maternal genetic contribution to environmental risk.
Conclusions: This initial approach was not able to specify the molecular genetic variations underlying asymptomatic transmission of autism risk, and it is highly likely that larger samples will be required to elucidate these factors. This method for investigating family-based data formaternal and paternal genetic contribution to risk can be systematically applied to other available data sets, and with the evolution of larger-sample-size data repositories can be equally applied to studies of rare inherited variants influencing autism risk within families.
See more of: Genetic Factors in ASD
See more of: Biological Mechanisms