Deqiong Ma

Common genetic variants on 5p14.1 associate with autism spectrum disorders

Autism spectrum disorders (ASDs) represent a group of childhood neurodevelopmental and neuropsychiatric disorders characterized by deficits in verbal communication, impairment of social interaction, and restricted and repetitive patterns of interests and behaviour. To identify common genetic risk factors underlying ASDs, here we present the results of genome-wide association studies on a cohort of 780 families (3,101 subjects) with affected children, and a second cohort of 1,204 affected subjects and 6,491 control subjects, all of whom were of European ancestry. Six single nucleotide polymorphisms between cadherin 10 (CDH10) and cadherin 9 (CDH9)—two genes encoding neuronal cell-adhesion molecules—revealed strong association signals, with the most significant SNP being rs4307059 (P = 3.4 × 10-8, odds ratio = 1.19). These signals were replicated in two independent cohorts, with combined P values ranging from 7.4 × 10-8 to 2.1 × 10-10. Our results implicate neuronal cell-adhesion molecules in the pathogenesis of ASDs, and represent, to our knowledge, the first demonstration of genome-wide significant association of common variants with susceptibility to ASDs.

A Genome-wide Association Study of Autism Reveals a Common Novel Risk Locus at 5p14.1

Although 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.

A noise-reduction GWAS analysis implicates altered regulation of neurite outgrowth and guidance in autism

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 Fishers 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 Fishers 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.

Variation in WNT genes is associated with non-syndromic cleft lip with or without cleft palate

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.

Evaluation of copy number variations reveals novel candidate genes in autism spectrum disorder-associated pathways

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.

Copy number variants in extended autism spectrum disorder families reveal candidates potentially involved in autism risk

Copy number variations (CNVs) are a major cause of genetic disruption in the human genome with far more nucleotides being altered by duplications and deletions than by single nucleotide polymorphisms (SNPs). In the multifaceted etiology of autism spectrum disorders (ASDs), CNVs appear to contribute significantly to our understanding of the pathogenesis of this complex disease. A unique resource of 42 extended ASD families was genotyped for over 1 million SNPs to detect CNVs that may contribute to ASD susceptibility. Each family has at least one avuncular or cousin pair with ASD. Families were then evaluated for co-segregation of CNVs in ASD patients. We identified a total of five deletions and seven duplications in eleven families that co-segregated with ASD. Two of the CNVs overlap with regions on 7p21.3 and 15q24.1 that have been previously reported in ASD individuals and two additional CNVs on 3p26.3 and 12q24.32 occur near regions associated with schizophrenia. These findings provide further evidence for the involvement of ICA1 and NXPH1 on 7p21.3 in ASD susceptibility and highlight novel ASD candidates, including CHL1, FGFBP3 and POUF41. These studies highlight the power of using extended families for gene discovery in traits with a complex etiology.

Genetic analysis of biological pathway data through genomic randomization

Genome Wide Association Studies (GWAS) are a standard approach for large-scale common variation characterization and for identification of single loci predisposing to disease. However, due to issues of moderate sample sizes and particularly multiple testing correction, many variants of smaller effect size are not detected within a single allele analysis framework. Thus, small main effects and potential epistatic effects are not consistently observed in GWAS using standard analytical approaches that consider only single SNP alleles. Here, we propose unique methodology that aggregates variants of interest (for example, genes in a biological pathway) using GWAS results. Multiple testing and type I error concerns are minimized using empirical genomic randomization to estimate significance. Randomization corrects for common pathway-based analysis biases, such as SNP coverage and density, linkage disequilibrium, gene size and pathway size. Pathway Analysis by Randomization Incorporating Structure (PARIS) applies this randomization and in doing so directly accounts for linkage disequilibrium effects. PARIS is independent of association analysis method and is thus applicable to GWAS datasets of all study designs. Using the KEGG database as an example, we apply PARIS to the publicly available Autism Genetic Resource Exchange GWAS dataset, revealing pathways with a significant enrichment of positive association results.

Association and gene-gene interaction of SLC6A4 and ITGB3 in autism.

Autism is a heritable neurodevelopmental disorder with substantial genetic heterogeneity. Studies point to possible links between autism and two serotonin related genes: SLC6A4 and ITGB3 with a sex‐specific genetic effect and interaction between the genes. Despite positive findings, inconsistent results have complicated interpretation. This study seeks to validate and clarify previous findings in an independent dataset taking into account sex, family‐history (FH) and gene–gene effects. Family‐based association analysis was performed within each gene. Gene–gene interactions were tested using extended multifactor dimensionality reduction (EMDR) and MDR‐phenomics (MDR‐P) using sex of affecteds and FH as covariates. No significant associations with individual SNPs were found in the datasets stratified by sex, but associations did emerge when we stratified by family history. While not significant in the overall dataset, nominally significant association was identified at RS2066713 (P = 0.006) within SLC6A4 in family‐history negative (FH−) families, at RS2066713 (P = 0.038) in family‐history positive (FH+) families but with the opposite risk allele as in the FH− families. For ITGB3, nominally significant association was identified at RS3809865 overall (P = 0.040) and within FH+ families (P = 0.031). However, none of the associations survived the multiple testing correction. MDR‐P confirmed gene–gene effects using sex of affecteds (P = 0.023) and family history (P = 0.014, survived the multiple testing corrections) as covariates. Our results indicate the extensive heterogeneity within these two genes among families. The potential interaction between SLC6A4 and ITGB3 may be clarified using family history as an indicator of genetic architecture, illustrating the importance of covariates as markers of heterogeneity in genetic analyses.

The Expanding Role of MBD Genes in Autism: Identification of a MECP2 Duplication and Novel Alterations in MBD5, MBD6, and SETDB1

The methyl‐CpG‐binding domain (MBD) gene family was first linked to autism over a decade ago when Rett syndrome, which falls under the umbrella of autism spectrum disorders (ASDs), was revealed to be predominantly caused by MECP2 mutations. Since that time, MECP2 alterations have been recognized in idiopathic ASD patients by us and others. Individuals with deletions across the MBD5 gene also present with ASDs, impaired speech, intellectual difficulties, repetitive behaviors, and epilepsy. These findings suggest that further investigations of the MBD gene family may reveal additional associations related to autism. We now describe the first study evaluating individuals with ASD for rare variants in four autosomal MBD family members, MBD5, MBD6, SETDB1, and SETDB2, and expand our initial screening in the MECP2 gene. Each gene was sequenced over all coding exons and evaluated for copy number variations in 287 patients with ASD and an equal number of ethnically matched control individuals. We identified 186 alterations through sequencing, approximately half of which were novel (96 variants, 51.6%). We identified 17 ASD specific, nonsynonymous variants, four of which were concordant in multiplex families: MBD5 Tyr1269Cys, MBD6 Arg883Trp, MECP2 Thr240Ser, and SETDB1 Pro1067del. Furthermore, a complex duplication spanning of the MECP2 gene was identified in two brothers who presented with developmental delay and intellectual disability. From our studies, we provide the first examples of autistic patients carrying potentially detrimental alterations in MBD6 and SETDB1, thereby demonstrating that the MBD gene family potentially plays a significant role in rare and private genetic causes of autism. Autism Res 2012, 5: 385–397.

Variants in several genomic regions associated with asperger disorder

Asperger disorder (ASP) is one of the autism spectrum disorders (ASD) and is differentiated from autism largely on the absence of clinically significant cognitive and language delays. Analysis of a homogenous subset of families with ASP may help to address the corresponding effect of genetic heterogeneity on identifying ASD genetic risk factors. To examine the hypothesis that common variation is important in ASD, we performed a genome‐wide association study (GWAS) in 124 ASP families in a discovery data set and 110 ASP families in a validation data set. We prioritized the top 100 association results from both cohorts by employing a ranking strategy. Novel regions on 5q21.1 (P = 9.7 × 10−7) and 15q22.1–q22.2 (P = 7.3 × 10−6) were our most significant findings in the combined data set. Three chromosomal regions showing association, 3p14.2 (P = 3.6 × 10−6), 3q25–26 (P = 6.0 × 10–5) and 3p23 (P = 3.3 × 10−4) overlapped linkage regions reported in Finnish ASP families, and eight association regions overlapped ASD linkage areas. Our findings suggest that ASP shares both ASD‐related genetic risk factors, as well as has genetic risk factors unique to the ASP phenotype.