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SummaryAlthough autism is one of the most heritable neuropsychiatric disorders, its underlying genetic architecture has largely eluded description. To comprehensively examine the hypothesis that common variation is important in autism, we performed a genome-wide association study (GWAS) using a discovery dataset of 438 autistic Caucasian families and the Illumina Human 1M beadchip. 96 single nucleotide polymorphisms (SNPs) demonstrated strong association with autism risk (p-value < 0.0001). The validation of the top 96 SNPs was performed using an independent dataset of 487 Caucasian autism families genotyped on the 550K Illumina BeadChip. A novel region on chromosome 5p14.1 showed significance in both the discovery and validation datasets. Joint analysis of all SNPs in this region identified 8 SNPs having improved p-values (3.24E-04 to 3.40E-06) than in either dataset alone. Our findings demonstrate that in addition to multiple rare variations, part of the complex genetic architecture of autism involves common variation.

BackgroundGenome-wide Association Studies (GWAS) have proved invaluable for the identification of disease susceptibility genes. However, the prioritization of candidate genes and regions for follow-up studies often proves difficult due to false-positive associations caused by statistical noise and multiple-testing. In order to address this issue, we propose the novel GWAS noise reduction (GWAS-NR) method as a way to increase the power to detect true associations in GWAS, particularly in complex diseases such as autism.MethodsGWAS-NR utilizes a linear filter to identify genomic regions demonstrating correlation among association signals in multiple datasets. We used computer simulations to assess the ability of GWAS-NR to detect association against the commonly used joint analysis and Fisher's methods. Furthermore, we applied GWAS-NR to a family-based autism GWAS of 597 families and a second existing autism GWAS of 696 families from the Autism Genetic Resource Exchange (AGRE) to arrive at a compendium of autism candidate genes. These genes were manually annotated and classified by a literature review and functional grouping in order to reveal biological pathways which might contribute to autism aetiology.ResultsComputer simulations indicate that GWAS-NR achieves a significantly higher classification rate for true positive association signals than either the joint analysis or Fisher's methods and that it can also achieve this when there is imperfect marker overlap across datasets or when the closest disease-related polymorphism is not directly typed. In two autism datasets, GWAS-NR analysis resulted in 1535 significant linkage disequilibrium (LD) blocks overlapping 431 unique reference sequencing (RefSeq) genes. Moreover, we identified the nearest RefSeq gene to the non-gene overlapping LD blocks, producing a final candidate set of 860 genes. Functional categorization of these implicated genes indicates that a significant proportion of them cooperate in a coherent pathway that regulates the directional protrusion of axons and dendrites to their appropriate synaptic targets.ConclusionsAs statistical noise is likely to particularly affect studies of complex disorders, where genetic heterogeneity or interaction between genes may confound the ability to detect association, GWAS-NR offers a powerful method for prioritizing regions for follow-up studies. Applying this method to autism datasets, GWAS-NR analysis indicates that a large subset of genes involved in the outgrowth and guidance of axons and dendrites is implicated in the aetiology of autism.

Non-syndromic cleft lip with or without cleft palate (NSCLP) is a common birth defect. Genetic and environmental factors have been causally implicated and studies have begun to delineate genetic contributions. The Wnt genes are involved in regulating mid-face development and upper lip fusion and are therefore strong candidates for an etiological role in NSCLP. Furthermore, the clf1 region in A/WyN clefting susceptible mice contains the Wnt3 and Wnt9B genes. To assess the role of the Wnt family of genes in NSCLP, we interrogated seven Wnt genes (Wnt3, Wnt3A, Wnt5A, Wnt7A, Wnt8A, Wnt9B and Wnt11) in our well-defined NSCLP dataset. Thirty-eight single nucleotide polymorphisms were genotyped in 132 multiplex NSCLP families and 354 simplex parent-child trios. In the entire dataset, single-nucleotide polymorphisms (SNPs) in three genes, Wnt3A (P = 0.006), Wnt 5A (P = 0.002) and Wnt11 (P = 0.0001) were significantly associated with NSCLP after correction for multiple testing. When stratified by ethnicity, the strongest associations were found for SNPs in Wnt3A (P = 0.0007), Wnt11 (P = 0.0012) and Wnt8A (P = 0.0013). Multiple haplotypes in Wnt genes were associated with NSCLP, and gene-gene interactions were observed between Wnt3A and both Wnt3 and Wnt5A (P = 0.004 and P = 0.039, respectively). This data suggests that alteration in Wnt gene function may perturb formation and/or fusion of the facial processes and predispose to NSCLP.

Autism spectrum disorders (ASDs) are highly heritable, yet relatively few associated genetic loci have been replicated. Copy number variations (CNVs) have been implicated in autism; however, the majority of loci contribute to <1% of the disease population. Therefore, independent studies are important to refine associated CNV regions and discover novel susceptibility genes. In this study, a genome-wide SNP array was utilized for CNV detection by two distinct algorithms in a European ancestry case-control data set. We identify a significantly higher burden in the number and size of deletions, and disrupting more genes in ASD cases. Moreover, 18 deletions larger than 1 Mb were detected exclusively in cases, implicating novel regions at 2q22.1, 3p26.3, 4q12 and 14q23. Case-specific CNVs provided further evidence for pathways previously implicated in ASDs, revealing new candidate genes within the GABAergic signaling and neural development pathways. These include DBI, an allosteric binder of GABA receptors, GABARAPL1, the GABA receptor-associated protein, and SLC6A11, a postsynaptic GABA transporter. We also identified CNVs in COBL, deletions of which cause defects in neuronal cytoskeleton morphogenesis in model vertebrates, and DNER, a neuron-specific Notch ligand required for cerebellar development. Moreover, we found evidence of genetic overlap between ASDs and other neurodevelopmental and neuropsychiatric diseases. These genes include glutamate receptors (GRID1, GRIK2 and GRIK4), synaptic regulators (NRXN3, SLC6A8 and SYN3), transcription factor (ZNF804A) and RNA-binding protein FMR1. Taken together, these CNVs may be a few of the missing pieces of ASD heritability and lead to discovering novel etiological mechanisms.