Novel Autism Subtype-Dependent Genetic Variants Are Revealed by Quantitative Trait and Subphenotype Association Analyses of Published GWAS Data

George Mason University, United States of America
PLoS ONE (Impact Factor: 3.23). 04/2011; 6(4):e19067. DOI: 10.1371/journal.pone.0019067
Source: PubMed


The heterogeneity of symptoms associated with autism spectrum disorders (ASDs) has presented a significant challenge to genetic analyses. Even when associations with genetic variants have been identified, it has been difficult to associate them with a specific trait or characteristic of autism. Here, we report that quantitative trait analyses of ASD symptoms combined with case-control association analyses using distinct ASD subphenotypes identified on the basis of symptomatic profiles result in the identification of highly significant associations with 18 novel single nucleotide polymorphisms (SNPs). The symptom categories included deficits in language usage, non-verbal communication, social development, and play skills, as well as insistence on sameness or ritualistic behaviors. Ten of the trait-associated SNPs, or quantitative trait loci (QTL), were associated with more than one subtype, providing partial replication of the identified QTL. Notably, none of the novel SNPs is located within an exonic region, suggesting that these hereditary components of ASDs are more likely related to gene regulatory processes (or gene expression) than to structural or functional changes in gene products. Seven of the QTL reside within intergenic chromosomal regions associated with rare copy number variants that have been previously reported in autistic samples. Pathway analyses of the genes associated with the QTL identified in this study implicate neurological functions and disorders associated with autism pathophysiology. This study underscores the advantage of incorporating both quantitative traits as well as subphenotypes into large-scale genome-wide analyses of complex disorders.

Download full-text


Available from: Anjene Addington, Oct 26, 2015
  • Source
    • "Of note, our result of microarray and qRT-PCR shows significant down-regulation in the expression of Htr4 in the cerebral hemispheres of male newborn pups of higher maternal FA. Htr4 is considered as a putative candidate gene for autism and was found to be differentially expressed in lymphoblastoid cell lines from individuals with autism spectrum disorders [36], [37]. Htr4 is known to modulate the release of neurotransmitters, and irregularities in serotonergic neurotransmission have been linked to a variety of neuropsychiatric diseases [38]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Studies have indicated that altered maternal micronutrients and vitamins influence the development of newborns and altered nutrient exposure throughout the lifetime may have potential health effects and increased susceptibility to chronic diseases. In recent years, folic acid (FA) exposure has significantly increased as a result of mandatory FA fortification and supplementation during pregnancy. Since FA modulates DNA methylation and affects gene expression, we investigated whether the amount of FA ingested during gestation alters gene expression in the newborn cerebral hemisphere, and if the increased exposure to FA during gestation and throughout the lifetime alters behavior in C57BL/6J mice.
    Full-text · Article · Jul 2014 · PLoS ONE
  • Source
    • ") or in lymphoblastoid cell lines (Gregg et al., 2008; Hu et al., 2011 "
    [Show abstract] [Hide abstract]
    ABSTRACT: Autism spectrum disorders (ASD) are highly heritable complex neurodevelopmental disorders with a 4:1 male: female ratio. Common genetic variation could explain 40-60% of the variance in liability to autism. Because of their small effect, genome-wide association studies (GWASs) have only identified a small number of individual single-nucleotide polymorphisms (SNPs). To increase the power of GWASs in complex disorders, methods like convergent functional genomics (CFG) have emerged to extract true association signals from noise and to identify and prioritize genes from SNPs using a scoring strategy combining statistics and functional genomics. We adapted and applied this approach to analyze data from a GWAS performed on families with multiple children affected with autism from Autism Speaks Autism Genetic Resource Exchange (AGRE). We identified a set of 133 candidate markers that were localized in or close to genes with functional relevance in ASD from a discovery population (545 multiplex families); a gender specific genetic score (GS) based on these common variants explained 1% (P = 0.01 in males) and 5% (P = 8.7 × 10(-7) in females) of genetic variance in an independent sample of multiplex families. Overall, our work demonstrates that prioritization of GWAS data based on functional genomics identified common variants associated with autism and provided additional support for a common polygenic background in autism.
    Full-text · Article · Feb 2014 · Frontiers in Genetics
  • Source
    • "The exact structure of the communities is likely to become more refined as more data become available in the Allen Brain Atlas. In general, receptor network analyses hold great promise for understanding the brain in health and disease, as has been demonstrated by recent research [36,67-69]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The activity of neurons is controlled by groups of neurotransmitter receptors rather than by individual receptors. Experimental studies have investigated some receptor interactions, but currently little information is available about transcriptional associations among receptors at the whole-brain level. A total of 4950 correlations between 100 G protein-coupled neurotransmitter receptors were examined across 169 brain regions in the human brain using expression data published in the Allen Human Brain Atlas. A large number of highly significant correlations were found, many of which have not been investigated in hypothesis-driven studies. The highest positive and negative correlations of each receptor are reported, which can facilitate the construction of receptor sets likely to be affected by altered transcription of one receptor (such sets always exist, but their members are difficult to predict). A graph analysis isolated two large receptor communities, within each of which receptor mRNA levels were strongly cross-correlated. The presented systematic analysis shows that the mRNA levels of many G protein-coupled receptors are interdependent. This finding is not unexpected, since the brain is a highly integrated complex system. However, the analysis also revealed two novel properties of global brain structure. First, receptor correlations are described by a simple statistical distribution, which suggests that receptor interactions may be guided by qualitatively similar processes. Second, receptors appear to form two large functional communities, which might be differentially affected in brain disorders.
    Full-text · Article · Jan 2014 · BMC Neuroscience
Show more