BackgroundAutism spectrum disorders (ASDs) comprise a range of neurodevelopmental conditions of varying severity, characterized by marked qualitative difficulties in social relatedness, communication, and behavior. Despite overwhelming evidence of high heritability, results from genetic studies to date show that ASD etiology is extremely heterogeneous and only a fraction of autism genes have been discovered.MethodsTo help unravel this genetic complexity, we performed whole exome sequencing on 100 ASD individuals from 40 families with multiple distantly related affected individuals. All families contained a minimum of one pair of ASD cousins. Each individual was captured with the Agilent SureSelect Human All Exon kit, sequenced on the Illumina Hiseq 2000, and the resulting data processed and annotated with Burrows-Wheeler Aligner (BWA), Genome Analysis Toolkit (GATK), and SeattleSeq. Genotyping information on each family was utilized in order to determine genomic regions that were identical by descent (IBD). Variants identified by exome sequencing which occurred in IBD regions and present in all affected individuals within each family were then evaluated to determine which may potentially be disease related. Nucleotide alterations that were novel and rare (minor allele frequency, MAF, less than 0.05) and predicted to be detrimental, either by altering amino acids or splicing patterns, were prioritized.ResultsWe identified numerous potentially damaging, ASD associated risk variants in genes previously unrelated to autism. A subset of these genes has been implicated in other neurobehavioral disorders including depression (SLIT3), epilepsy (CLCN2, PRICKLE1), intellectual disability (AP4M1), schizophrenia (WDR60), and Tourette syndrome (OFCC1). Additional alterations were found in previously reported autism candidate genes, including three genes with alterations in multiple families (CEP290, CSMD1, FAT1, and STXBP5). Compiling a list of ASD candidate genes from the literature, we determined that variants occurred in ASD candidate genes 1.65 times more frequently than in random genes captured by exome sequencing (P = 8.55 × 10-5).ConclusionsBy studying these unique pedigrees, we have identified novel DNA variations related to ASD, demonstrated that exome sequencing in extended families is a powerful tool for ASD candidate gene discovery, and provided further evidence of an underlying genetic component to a wide range of neurodevelopmental and neuropsychiatric diseases.

SummaryParkinson disease (PD) is a chronic neurodegenerative disorder with a cumulative prevalence of greater than one per thousand. To date three independent genome-wide association studies (GWAS) have investigated the genetic susceptibility to PD. These studies implicated several genes as PD risk loci with strong, but not genome-wide significant, associations.In this study, we combined data from two previously published GWAS of Caucasian subjects with our GWAS of 604 cases and 619 controls for a joint analysis with a combined sample size of 1752 cases and 1745 controls. SNPs in SNCA (rs2736990, p-value = 6.7 × 10 −8 ; genome-wide adjusted p = 0.0109, odds ratio (OR) = 1.29 [95% CI: 1.17-1.42] G vs. A allele, population attributable risk percent (PAR%) = 12%) and the MAPT region (rs11012, p-value = 5.6 × 10 −8 ; genome-wide adjusted p = 0.0079, OR = 0.70 [95% CI: 0.62-0.79] T vs. C allele, PAR% = 8%) were genomewide significant. No other SNPs were genome-wide significant in this analysis. This study confirms that SNCA and the MAPT region are major genes whose common variants are influencing risk of PD.

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.

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