A. Jeremy Willsey

De novo mutations revealed by whole-exome sequencing are strongly associated with autism

Multiple studies have confirmed the contribution of rare de novo copy number variations to the risk for autism spectrum disorders. But whereas de novo single nucleotide variants have been identified in affected individuals, their contribution to risk has yet to be clarified. Specifically, the frequency and distribution of these mutations have not been well characterized in matched unaffected controls, and such data are vital to the interpretation of de novo coding mutations observed in probands. Here we show, using whole-exome sequencing of 928 individuals, including 200 phenotypically discordant sibling pairs, that highly disruptive (nonsense and splice-site) de novo mutations in brain-expressed genes are associated with autism spectrum disorders and carry large effects. On the basis of mutation rates in unaffected individuals, we demonstrate that multiple independent de novo single nucleotide variants in the same gene among unrelated probands reliably identifies risk alleles, providing a clear path forward for gene discovery. Among a total of 279 identified de novo coding mutations, there is a single instance in probands, and none in siblings, in which two independent nonsense variants disrupt the same gene, SCN2A (sodium channel, voltage-gated, type II, α subunit), a result that is highly unlikely by chance.

The contribution of de novo coding mutations to autism spectrum disorder

Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.

Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci

Analysis of de novo CNVs (dnCNVs) from the full Simons Simplex Collection (SSC) (N = 2,591 families) replicates prior findings of strong association with autism spectrum disorders (ASDs) and confirms six risk loci (1q21.1, 3q29, 7q11.23, 16p11.2, 15q11.2-13, and 22q11.2). The addition of published CNV data from the Autism Genome Project (AGP) and exome sequencing data from the SSC and the Autism Sequencing Consortium (ASC) shows that genes within small de novo deletions, but not within large dnCNVs, significantly overlap the high-effect risk genes identified by sequencing. Alternatively, large dnCNVs are found likely to contain multiple modest-effect risk genes. Overall, we find strong evidence that de novo mutations are associated with ASD apart from the risk for intellectual disability. Extending the transmission and de novo association test (TADA) to include small de novo deletions reveals 71 ASD risk loci, including 6 CNV regions (noted above) and 65 risk genes (FDR ≤ 0.1).

Common genetic variants, acting additively, are a major source of risk for autism.

BackgroundAutism spectrum disorders (ASD) are early onset neurodevelopmental syndromes typified by impairments in reciprocal social interaction and communication, accompanied by restricted and repetitive behaviors. While rare and especially de novo genetic variation are known to affect liability, whether common genetic polymorphism plays a substantial role is an open question and the relative contribution of genes and environment is contentious. It is probable that the relative contributions of rare and common variation, as well as environment, differs between ASD families having only a single affected individual (simplex) versus multiplex families who have two or more affected individuals.MethodsBy using quantitative genetics techniques and the contrast of ASD subjects to controls, we estimate what portion of liability can be explained by additive genetic effects, known as narrow-sense heritability. We evaluate relatives of ASD subjects using the same methods to evaluate the assumptions of the additive model and partition families by simplex/multiplex status to determine how heritability changes with status.ResultsBy analyzing common variation throughout the genome, we show that common genetic polymorphism exerts substantial additive genetic effects on ASD liability and that simplex/multiplex family status has an impact on the identified composition of that risk. As a fraction of the total variation in liability, the estimated narrow-sense heritability exceeds 60% for ASD individuals from multiplex families and is approximately 40% for simplex families. By analyzing parents, unaffected siblings and alleles not transmitted from parents to their affected children, we conclude that the data for simplex ASD families follow the expectation for additive models closely. The data from multiplex families deviate somewhat from an additive model, possibly due to parental assortative mating.ConclusionsOur results, when viewed in the context of results from genome-wide association studies, demonstrate that a myriad of common variants of very small effect impacts ASD liability.

The autism-associated chromatin modifier CHD8 regulates other autism risk genes during human neurodevelopment

Recent studies implicate chromatin modifiers in autism spectrum disorder (ASD) through the identification of recurrent de novo loss of function mutations in affected individuals. ASD risk genes are co-expressed in human midfetal cortex, suggesting that ASD risk genes converge in specific regulatory networks during neurodevelopment. To elucidate such networks, we identify genes targeted by CHD8, a chromodomain helicase strongly associated with ASD, in human midfetal brain, human neural stem cells (hNSCs) and embryonic mouse cortex. CHD8 targets are strongly enriched for other ASD risk genes in both human and mouse neurodevelopment, and converge in ASD-associated co-expression networks in human midfetal cortex. CHD8 knockdown in hNSCs results in dysregulation of ASD risk genes directly targeted by CHD8. Integration of CHD8-binding data into ASD risk models improves detection of risk genes. These results suggest loss of CHD8 contributes to ASD by perturbing an ancient gene regulatory network during human brain development.

Complete Haplotype Sequence of the Human Immunoglobulin Heavy-Chain Variable, Diversity, and Joining Genes and Characterization of Allelic and Copy-Number Variation

The immunoglobulin heavy-chain locus (IGH) encodes variable (IGHV), diversity (IGHD), joining (IGHJ), and constant (IGHC) genes and is responsible for antibody heavy-chain biosynthesis, which is vital to the adaptive immune response. Programmed V-(D)-J somatic rearrangement and the complex duplicated nature of the locus have impeded attempts to reconcile its genomic organization based on traditional B-lymphocyte derived genetic material. As a result, sequence descriptions of germline variation within IGHV are lacking, haplotype inference using traditional linkage disequilibrium methods has been difficult, and the human genome reference assembly is missing several expressed IGHV genes. By using a hydatidiform mole BAC clone resource, we present the most complete haplotype of IGHV, IGHD, and IGHJ gene regions derived from a single chromosome, representing an alternate assembly of ∼1 Mbp of high-quality finished sequence. From this we add 101 kbp of previously uncharacterized sequence, including functional IGHV genes, and characterize four large germline copy-number variants (CNVs). In addition to this germline reference, we identify and characterize eight CNV-containing haplotypes from a panel of nine diploid genomes of diverse ethnic origin, discovering previously unmapped IGHV genes and an additional 121 kbp of insertion sequence. We genotype four of these CNVs by using PCR in 425 individuals from nine human populations. We find that all four are highly polymorphic and show considerable evidence of stratification (Fst = 0.3-0.5), with the greatest differences observed between African and Asian populations. These CNVs exhibit weak linkage disequilibrium with SNPs from two commercial arrays in most of the populations tested.

The PsychENCODE project

Recent research on disparate psychiatric disorders has implicated rare variants in genes involved in global gene regulation and chromatin modification, as well as many common variants located primarily in regulatory regions of the genome. Understanding precisely how these variants contribute to disease will require a deeper appreciation for the mechanisms of gene regulation in the developing and adult human brain. The PsychENCODE project aims to produce a public resource of multidimensional genomic data using tissue- and cell type–specific samples from approximately 1,000 phenotypically well-characterized, high-quality healthy and disease-affected human post-mortem brains, as well as functionally characterize disease-associated regulatory elements and variants in model systems. We are beginning with a focus on autism spectrum disorder, bipolar disorder and schizophrenia, and expect that this knowledge will apply to a wide variety of psychiatric disorders. This paper outlines the motivation and design of PsychENCODE.

Increased Frequency of De Novo Copy Number Variants in Congenital Heart Disease by Integrative Analysis of Single Nucleotide Polymorphism Array and Exome Sequence Data

Rationale: Congenital heart disease (CHD) is among the most common birth defects. Most cases are of unknown pathogenesis. Objective: To determine the contribution of de novo copy number variants (CNVs) in the pathogenesis of sporadic CHD. Methods and Results: We studied 538 CHD trios using genome-wide dense single nucleotide polymorphism arrays and whole exome sequencing. Results were experimentally validated using digital droplet polymerase chain reaction. We compared validated CNVs in CHD cases with CNVs in 1301 healthy control trios. The 2 complementary high-resolution technologies identified 63 validated de novo CNVs in 51 CHD cases. A significant increase in CNV burden was observed when comparing CHD trios with healthy trios, using either single nucleotide polymorphism array (P=7×10−5; odds ratio, 4.6) or whole exome sequencing data (P=6×10−4; odds ratio, 3.5) and remained after removing 16% of de novo CNV loci previously reported as pathogenic (P=0.02; odds ratio, 2.7). We observed recurrent de novo CNVs on 15q11.2 encompassing CYFIP1, NIPA1, and NIPA2 and single de novo CNVs encompassing DUSP1, JUN, JUP, MED15, MED9, PTPRE SREBF1, TOP2A, and ZEB2, genes that interact with established CHD proteins NKX2-5 and GATA4. Integrating de novo variants in whole exome sequencing and CNV data suggests that ETS1 is the pathogenic gene altered by 11q24.2-q25 deletions in Jacobsen syndrome and that CTBP2 is the pathogenic gene in 10q subtelomeric deletions. Conclusions: We demonstrate a significantly increased frequency of rare de novo CNVs in CHD patients compared with healthy controls and suggest several novel genetic loci for CHD.

De Novo Insertions and Deletions of Predominantly Paternal Origin Are Associated with Autism Spectrum Disorder

Whole-exome sequencing (WES) studies have demonstrated the contribution of de novo loss-of-function single-nucleotide variants (SNVs) to autism spectrum disorder (ASD). However, challenges in the reliable detection of de novo insertions and deletions (indels) have limited inclusion of these variants in prior analyses. By applying a robust indel detection method to WES data from 787 ASD families (2,963 individuals), we demonstrate that de novo frameshift indels contribute to ASD risk (OR = 1.6; 95% CI = 1.0-2.7; p = 0.03), are more common in female probands (p = 0.02), are enriched among genes encoding FMRP targets (p = 6 × 10(-9)), and arise predominantly on the paternal chromosome (p < 0.001). On the basis of mutation rates in probands versus unaffected siblings, we conclude that de novo frameshift indels contribute to risk in approximately 3% of individuals with ASD. Finally, by observing clustering of mutations in unrelated probands, we uncover two ASD-associated genes: KMT2E (MLL5), a chromatin regulator, and RIMS1, a regulator of synaptic vesicle release.

A genome-wide association study of autism using the Simons simplex collection: Does reducing phenotypic heterogeneity in autism increase genetic homogeneity?

BACKGROUND Phenotypic heterogeneity in autism has long been conjectured to be a major hindrance to the discovery of genetic risk factors, leading to numerous attempts to stratify children based on phenotype to increase power of discovery studies. This approach, however, is based on the hypothesis that phenotypic heterogeneity closely maps to genetic variation, which has not been tested. Our study examines the impact of subphenotyping of a well-characterized autism spectrum disorder (ASD) sample on genetic homogeneity and the ability to discover common genetic variants conferring liability to ASD. METHODS Genome-wide genotypic data of 2576 families from the Simons Simplex Collection were analyzed in the overall sample and phenotypic subgroups defined on the basis of diagnosis, IQ, and symptom profiles. We conducted a family-based association study, as well as estimating heritability and evaluating allele scores for each phenotypic subgroup. RESULTS Association analyses revealed no genome-wide significant association signal. Subphenotyping did not increase power substantially. Moreover, allele scores built from the most associated single nucleotide polymorphisms, based on the odds ratio in the full sample, predicted case status in subsets of the sample equally well and heritability estimates were very similar for all subgroups. CONCLUSIONS In genome-wide association analysis of the Simons Simplex Collection sample, reducing phenotypic heterogeneity had at most a modest impact on genetic homogeneity. Our results are based on a relatively small sample, one with greater homogeneity than the entire population; if they apply more broadly, they imply that analysis of subphenotypes is not a productive path forward for discovering genetic risk variants in ASD.