Introduction

Asperger Syndrome (AS) is a neurodevelopmental condition and a subset of Autism Spectrum Conditions (ASC) [1]. Individuals with ASC have difficulties in social interaction and communication, alongside unusually repetitive and stereotyped behaviour and unusually narrow interests. In AS, language and cognitive development proceed on time. ASC is highly heritable [2], with monozygotic twin heritability rate estimated between 73 – 95% [3], and has a prevalence of approximately 1% [4]. ASC is characterized by high clinical and aetiological heterogeneity. Environmental, epigenetic and genetic factors have been implicated in ASC [3, 5–7]. Currently, more than 660 genes are implicated in ASC (https://gene.sfari.org/autdb/HG_Home.do), though no single gene or variant accounts for more than 1–2% of cases [5,8]. Additionally, several large copy number variants that duplicate or delete multiple genes have also been identified in association with ASC [3,9].

Though no common variant has been consistently associated with ASC across multiple Genome-wide Association Studies (GWAS) [3,5], it is clear now that they contribute considerably to the variation in ASC [10, 11]. Two recent studies have identified that common inherited variation contributes to between 40 – 60% of the variance in ASC [10, 11]. However, despite the majority of variance attributable to common inherited variants, as explained earlier, genome-wide association studies have failed to consistently identify causative variations. One explanation for this lack of success is that genome-wide association studies in ASC may be underpowered to detect small effect sizes; the largest ASC GWAS had less than 9000 participants (cases and controls) and, although this seems large, it has been argued that much larger sample sizes are needed (in the range of tens and hundreds of thousands) to successfully identify causative variants [9]. An alternative view is that the inability to consistently identify causative common variants is due to the underlying genetic and phenotypic heterogeneity. At a phenotypic level, delay and difficulties in language development is an important source of heterogeneity in ASC. Language delay in individuals with ASC is associated in changes in brain volume in both total grey matter and in specific regions in the brain [12]. This different brain architecture points to different biological and genetic networks involved in different forms of ASC. As mentioned earlier, AS is a subset of ASC where individuals have no language delay, suggesting it may have a genetic architecture distinct from the rest of ASC.

Only a few studies have specifically investigated the genetics of AS. In one of the first such studies, we tested for associations between 216 SNPs across 68 candidate genes. We identified nominal associations between SNPs in 14 genes and AS [13]. In the current study, we performed a pooled DNA genome wide association in individuals with AS and controls to identify SNPs in a hypothesis-free way. DNA pooling is a rapid, efficient and economical method to identify genetic associations in various conditions [14]. We hypothesized that genome-wide DNA pooling would detect the differences in allele frequencies between individuals with AS and controls. SNPs whose p-values were below a pre-defined threshold were then individually genotyped in the same sample using an established approach reported in several previous studies [15–17].

Methods

Results

In the DNA-pooling stage, 11 SNPS passed the threshold of significance and quality control. Additionally, 5 SNPs with p-values below 1 x 10⁻⁵ failed quality control at the pooling stage (Fig 1). All the 11 SNPs were individually genotyped and all the SNPs passed quality control in the individual genotyping phase. Three SNPs were nominally significant at p <0.05 in this stage (rs7785891, rs1268055, and rs2782448). None of the SNPs survived correction for multiple testing using Bonferroni correction. None of these three nominally significant SNPs from the individual genotyping stage were significant in the PGC ASC dataset. Results are summarised in Table 1. A Q-Q plot of the results from the pooling stage is provided in Fig 2.

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Fig 1. Manhattan plot of the SNPs tested in the pooled DNA association stage.

https://doi.org/10.1371/journal.pone.0131202.g001

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Fig 2. Quantile-quantile plot of the SNPs tested in the pooled DNA association stage.

https://doi.org/10.1371/journal.pone.0131202.g002

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Table 1. Summary of results.

https://doi.org/10.1371/journal.pone.0131202.t001

Discussion

The current study used pooled DNA analysis to identify common variants associated with AS. Using pooled DNA we scanned the genome for SNPs that had a difference in allele frequencies between the case groups and the control groups. A threshold of 1 x 10⁻⁵ was selected in the pooling stage due to the loss of power during DNA pooling and to control for false negatives. SNPs which had p-values below the pre-defined threshold were treated as candidate SNPs and genotyped individually in the same group of individuals to more accurately estimate allele frequencies. Of the 11 SNPs that crossed the threshold of significance in the pooling stage, only three remained nominally significant after the individual genotyping stage. These three SNPs were not significantly associated with ASC in a larger, more heterogeneous ASC cohort from the PGC consortium.

rs778589, the top performing SNP at the pooling stage, is an intronic SNP in DOCK4, a gene previously associated with ASC [25, 26]. rs2782448 is an intergenic SNP at 13q21. It is 371 kb from KLHL1 and 7.5 kb from the 3’ end of RP11- 459J23.1, a LincRNA identified by the Gencode project. 13q21 has been previously implicated in both autism [27, 28] and Specific Language Impairment [29]. The third nominally significant SNP, rs1268055, is an intronic SNP in ARMC2, a gene with uncertain function in humans.

The major limitation of this study is power. First, DNA pooling retains only 68% percent of the power [19]. Second, even after only selecting for individuals with AS, no SNP remained significant after Bonferroni correction. This indicates that larger sample sizes are required to detect causative alleles of small effect sizes. There is a considerably high correlation between the two stages of analysis, yet of the eleven SNPs selected for individual genotyping, only three remained nominally significant at this stage. The top two associated SNPs that passed quality control in the pooled DNA analysis stage were both nominally significant at the individual genotyping stage. However, they did not remain significant after correction for multiple comparisons. Of the three nominally significant alleles, rs7785891 has an odds ratio above 1, whereas rs1268055 and rs2782448 have odds ratio below 1 (see Table 1). Finally, while all our participants reported Caucasian ancestry for at least two generations, population stratification can confound the results and lead to false positives [30]. There are currently no known methods to correct for population stratification for pooled DNA association studies, taking into account the polygenicity of the condition.

While the current study tested for association with AS, we also checked to see if the three nominally significant SNPs were significant in an ASC cohort. The direction of effect for all three SNPs was similar to the effect direction in our sample. However, none of the three SNPs were nominally significant in the PGC ASC cohort. This may be due to a) the heterogeneity of the PGC cohort compared to our study cohort, since the former did not stratify for language delay, and/or b) the design of the association study being different (a family based association study based on trios vs a population based study), which may lead to different signal-to-noise ratios. However, it needs to be highlighted that the effect sizes for the SNPs in both the samples were small. This underscores the need for larger sample sizes to effectively identify common variants.

In conclusion, we report the identification three SNPs (rs1268055, rs7785891 and rs2782448) as nominally associated with AS using a genome-wide pooled DNA association study. rs2782448 and rs1268055 lie in genetic loci previously implicated in ASC. None of the SNPs remained significant after Bonferroni correction, underscoring the need for larger sample sizes to uncover alleles with small effect sizes. This is the first genome-wide case-control association study to test common variants for association with AS.

Acknowledgments

We are grateful to Jon Breidbord, Lindsey Kent and Frank Dudbridge for help, advice, and discussions. Professor Peltonen kindly facilitated the collaboration with the Wellcome Trust Sanger Institute, but tragically passed away before the study was completed.