The contribution of de novo coding mutations to autism spectrum disorder
Open accessAbstract
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.
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Most proteins encoded by ASD risk genes are involved either in synaptic structure and function or chromatin modification and regulation of gene expression.
“including that, prima facie , most proteins encoded by ASD risk genes are involved either in synaptic structure and function or chromatin modification and regulation of gene expression 38,46,47,58 (Fig. 3).”
From Autism spectrum disorder (2020) · cites this paper as [46]
The Results section (“Functional clustering in target genes”; page unavailable) reports enrichment of FMRP targets and chromatin modifiers among genes with de novo mutations. The Discussion (“Properties of target classes”; page unavailable) identifies synaptic proteins and transcriptional regulators among recurrent targets. Neither passage establishes that most proteins encoded by ASD risk genes fall into the two categories named in the claim. (LLM, conf=0.85)
Experimental — accuracy not yet measuredRare inherited and de novo variants are major contributors to individual risk for ASD.
“Rare inherited and de novo variants are major contributors to individual risk for autism spectrum disorder (ASD)”
From Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism (2020) · cites this paper as Iossifov et al., 2014
The Abstract reports that de novo coding mutations, including copy-number variants, contribute to about 30% of diagnoses in simplex families. The Introduction says a contribution from transmission has long been suspected, but the paper does not establish that rare inherited variants are major contributors to individual ASD risk. (LLM, conf=0.84)
Experimental — accuracy not yet measuredDe novo mutations, mostly copy number variants and gene disrupting point mutations, have larger individual effects but collectively explain less than 5% of the overall liability and far less of the heritability.
“By contrast, de novo mutations, mostly copy number variants (CNVs) and gene disrupting point mutations, have larger individual effects, but collectively explain <5% of the overall liability 1-3 and far less of the heritability.”
From Identification of common genetic risk variants for autism spectrum disorder (2019) · cites this paper as [3]
The Discussion (Gene vulnerability and molecular mechanisms; page unavailable) says many de novo likely gene-disrupting mutations strongly predispose to ASD, supporting the claim that individual mutations can have substantial effects. The Abstract reports contributions to diagnoses, including copy-number variants, but does not estimate that de novo mutations explain less than 5% of overall liability or far less of heritability. Searches for “liability” and “heritability” found no such estimate in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measuredASD affects 1-1.5% of individuals and is highly heritable, with both common and rare variants contributing to its etiology.
“ASD affects 1-1.5% of individuals and is highly heritable, with both common and rare variants contributing to its etiology 1-4 .”
From Identification of common genetic risk variants for autism spectrum disorder (2019) · cites this paper as [3]
The Introduction (page unavailable) links ASD to increased sibling risk and inherited transmission, while the Results report a contribution from de novo mutations. The Methods give sex-specific prevalence assumptions, not a 1–1.5% estimate for all individuals. The passages do not establish high heritability or a contribution from common variants. (LLM, conf=0.84)
Experimental — accuracy not yet measuredSeveral microdeletions lead to loss of various lengths of the C-terminal portion of Dock4 protein, which is responsible for its Rac1-activating ability.
“For instance, several microdeletions lead to loss of various lengths of the C-terminal portion of Dock4 protein 19, 21, 26, which is responsible for its Rac1-activating ability 27.”
From Autism-like social deficit generated by Dock4 deficiency is rescued by restoration of Rac1 activity and NMDA receptor function. (2021) · cites this paper as [21]
Citation 26 is attached to the claim about microdeletions removing portions of Dock4’s C-terminus; the Rac1-activating function is separately cited to reference 27. The supplied Results and Discussion passages discuss de novo coding mutations generally, but neither they nor searches for “Dock4” and “DOCK4 microdeletions C-terminal portion” yielded a passage addressing those deletions. (LLM, conf=0.76)
Experimental — accuracy not yet measured
Recent studies have identified DOCK4 variations associated with ASD, including single nucleotide variations and chromosome microdeletions or duplications.
“Recent studies have identified a number of DOCK4 variations associated with ASD, including both single nucleotide variations (SNVs) and chromosome microdeletions or duplications (Supplementary Table 1) 18–26.”
From Autism-like social deficit generated by Dock4 deficiency is rescued by restoration of Rac1 activity and NMDA receptor function. (2021) · cites this paper as [21]
The Introduction and Results discuss de novo coding variants and copy-number variation in ASD generally, but no passage identifies DOCK4 variants or links DOCK4 microdeletions or duplications to ASD. Searches for DOCK4 and for the specific variant types did not locate that gene in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measuredNext-generation sequencing identified one intronic, two missense, and two nonsense variants in NCKAP1L in autism patients.
“Next-generation sequencing identified one intronic114, two missense133,134, and two nonsense variants in autism patients104,114, and the functional consequences of these variants remain to be established (Table 2u).”
From The WAVE complex in developmental and adulthood brain disorders (2025) · cites this paper as [133]
The Results section describes exome sequencing in children with autism, but the passages retrieved for “NCKAP1L” and “intronic variants in NCKAP1L autism” do not identify that gene or give the claimed variant counts. Our copy therefore does not establish whether this study found an intronic, missense, or nonsense NCKAP1L variant. (LLM, conf=0.72)
Experimental — accuracy not yet measuredASD risk is influenced by both rare and common genetic variants, including de novo CNVs, large-effect protein-truncating SNPs and indels, and common polygenic risk made up of many small-effect alleles.
“The major risk factors for autism spectrum disorder (ASD) are genetic and include a variety of rare and common alleles, including rare de novo copy number variants (CNVs)1 or protein-truncating SNPs and indels of large effect2 and common polygenic risk that is measured as the sum of thousands of common alleles with small effects3.”
From A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex (2022) · cites this paper as [2]
Genetic studies of de novo variants have consistently supported a female protective effect against ASD.
“The possibility of a “female protective effect” (FPE) against ASD has been described extensively and has received consistent support from the results of genetic studies of de novo variants.4, 5, 6, 7, 8, 9, 10, 11, 12, 13”
From The female protective effect against autism spectrum disorder (2022) · cites this paper as [11]
Many types of ASD-associated de novo variants are observed more frequently in female cases.
“Many types of ASD-associated de novo variants are observed more frequently in female cases.4, 5, 6, 7, 8, 9, 10, 11, 12, 13”
From The female protective effect against autism spectrum disorder (2022) · cites this paper as [11]
The genetic architecture in the self-reported SPARK cohort is similar to published, clinically confirmed ASD cohorts.
“We also demonstrated that the genetic architecture in this self-reported cohort is similar to published, clinically confirmed ASD cohorts.3,4,7”
From Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes (2019) · cites this paper as [3]
Over the past decade, genomic studies focused on de novo likely gene disrupting variants have identified about 100 high-confidence ASD risk genes or loci.
“Over the past decade, genomic studies focused on de novo, likely gene disrupting (dnLGD) variants (stopgain, frameshift, and essential splice site) have identified ~100 high-confidence ASD risk genes or loci.3,4”
From Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes (2019) · cites this paper as [3]
ASD individuals have two- to three-fold more rare CNVs and de novo loss-of-function variants than unaffected siblings.
“individuals with ASD have a two- to three-fold increase in the number of rare copy number variations (CNVs) and de novo loss-of-function (nonsense, frameshift, and splice site) variants compared to their unaffected siblings11–14.”
From Genome-wide detection of tandem DNA repeats that are expanded in autism (2020) · cites this paper as [12]
Using two SNV callers identified 77 additional de novo SNVs that previous studies missed.
“the application of two SNV callers identified 77 additional de novo SNVs previously missed 9.”
From Excess of rare, inherited truncating mutations in autism (2015) · cites this paper as [9]
An additional 132 previously called but unconfirmed events were validated by Sanger sequencing, bringing the total to 209 validated de novo SNVs and indels.
“In addition, we also validated by Sanger sequencing another 132 previously called 9 but not confirmed events, resulting in a total of 209 validated de novo SNVs and indels (Supplementary Table 2).”
From Excess of rare, inherited truncating mutations in autism (2015) · cites this paper as [9]
Most of these ASD mutations also decrease IQ, and intellectual disability is an important comorbidity of ASD.
“Most of these mutations also decrease IQ and ID is an important comorbidity of ASD (Buja et al., 2018; Iossifov et al., 2014), which is consistent with previous work identifying dozens of known severe, rare medical genetic syndromes associated with ASD (reviewed in (Abrahams and Geschwind, 2008; Geschwind, 2009)).”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Iossifov et al., 2014
Rare de novo variation is predicted to account for about 15% of ASD cases, with each gene accounting for only a small fraction of cases.
“Although each gene accounts for only a small fraction of cases, rare de novo variation is predicted to account for ~15% of ASD cases (Iossifov et al., 2014).”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Iossifov et al., 2014
Applying TADA to exomes or whole genomes in large family samples is the most effective strategy for identifying ASD susceptibility genes.
“The application of this approach to exomes or whole genomes in large family samples has since become the most effective strategy for identifying ASD susceptibility genes (De Rubeis et al., 2014; Iossifov et al., 2014; Sanders et al., 2015; Satterstrom et al., 2018).”
From Getting to the cores of autism (2019) · cites this paper as Iossifov et al., 2014
Individuals carrying de novo mutations have lower non-verbal IQ than those who do not carry them.
“As would be expected for variants with large effects, subjects that carry de novo mutations have lower non-verbal IQs than subjects who do not (Iossifov et al., 2014).”
From Getting to the cores of autism (2019) · cites this paper as Iossifov et al., 2014
De novo mutations in genes account for about 30% of ASD cases, including 25% of boys and 45% of girls.
“It is estimated that de novo mutations of genes contribute in approximately 30% of cases, including 25% of boys and 45% of girls (Iossifov et al., 2014).”
From Getting to the cores of autism (2019) · cites this paper as Iossifov et al., 2014
For most large CNVs, studies have not found evidence for a single driver gene.
“However, for the majority of large CNVs, studies have not found evidence for the existence of a single driver gene (De Rubeis et al., 2014; Iossifov et al., 2014).”
From Getting to the cores of autism (2019) · cites this paper as Iossifov et al., 2014
FMRP mRNA targets are enriched in ASD risk genes.
“Moreover, 20 of these lncRNAs have been shown to interact with microRNA (miRNA)–protein complexes, and 9 with the fragile X mental retardation protein (FMRP), whose mRNA targets are enriched in ASD risk genes9,10.”
From Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism (2016) · cites this paper as [9]
The observed transcriptome changes are consistent with an ongoing process triggered largely by genetic and prenatal factors but evolving during the first decade of brain development.
“In this regard, it is notable that the observed transcriptome changes are consistent with an ongoing process that is triggered largely by genetic and prenatal factors3,9,10,23, but that evolves during the first decade of brain development.”
From Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism (2016) · cites this paper as [9]
Genes that carry de novo likely gene-disruptive mutations in children with autism spectrum disorder are highly vulnerable, and a disruptive mutation in many vulnerable autism genes is likely to lead to autism spectrum disorder.
“We previously computed that genes with de novo (DN) likely gene-disruptive (LGD) mutations in children with autism spectrum disorders (ASD) have high vulnerability: disruptive mutations in many of these genes, the vulnerable autism genes, will have a high likelihood of resulting in ASD.”
From Low load for disruptive mutations in autism genes and their biased transmission (2015) · cites this paper as [10]
Target genes in affected and unaffected individuals have closely matched length distributions.
“Moreover, the target genes in affected and unaffected individuals have length distributions that are closely matched (10).”
From Low load for disruptive mutations in autism genes and their biased transmission (2015) · cites this paper as [10]
There are 39 recurrent DN LGD targets in affected children, and about 90% are true causal targets.
“There are 39 such targets (10,18), and we previously estimated that ∼90% of these targets are true causal targets.”
From Low load for disruptive mutations in autism genes and their biased transmission (2015) · cites this paper as [10]
All gene classes enriched for autism targets show decreased load of UR LGD variants, especially FMRP-associated.
“All gene classes enriched for autism targets show a decreased load of UR LGD variants, especially the FMRP-associated class, as previously noted (10).”
From Low load for disruptive mutations in autism genes and their biased transmission (2015) · cites this paper as [10]
There is a strong signal of biased transmission in functional categories of genes previously linked to autism spectrum disorder.
“We also find a strong signal for biased transmission in the functional categories of genes previously associated with ASD (10).”
From Low load for disruptive mutations in autism genes and their biased transmission (2015) · cites this paper as [10]
In males, a de novo likely gene-disruptive mutation in an autism gene produces severe autism spectrum disorder about half the time.
“We computed that roughly half of the time in males, a DN LGD mutation within an autism gene will produce severe ASD (10).”
From Low load for disruptive mutations in autism genes and their biased transmission (2015) · cites this paper as [10]
Recurrence and overlap analysis of de novo likely gene-disruptive targets estimates about 500 causative autism spectrum disorder target genes in lower-IQ affected individuals, enriched in certain functional classes.
“From recurrence and overlap analysis of DN LGD targets, we estimate ∼500 causative ASD target genes in the affected individuals with lower intelligence quotients (IQ), and these targets are enriched in certain functional classes (10).”
From Low load for disruptive mutations in autism genes and their biased transmission (2015) · cites this paper as [10]
Increase in DN LGD rate in affected vs unaffected used to estimate 0.42 of 391 DN variants contribute to affected status.
“The increase in the rate of DN LGD mutation in affected children compared with the rate in their unaffected siblings was used to estimate the proportion (0.42) of 391 observed DN variants in the affected children that contribute to affected status (10).”
From Low load for disruptive mutations in autism genes and their biased transmission (2015) · cites this paper as [10]
Embryonic genes' involvement in transmission greater than predicted.
“Although our previous work had shown that embryonic genes were enriched as DN targets (10), their involvement in transmission is greater than we would have predicted.”
From Low load for disruptive mutations in autism genes and their biased transmission (2015) · cites this paper as [10]
Substantial signal from transmission seen in embryonic genes.
“First, a substantial signal from transmission is seen in the set of “embryonic” genes (10).”
From Low load for disruptive mutations in autism genes and their biased transmission (2015) · cites this paper as [10]
Many severe mutations do not converge on one specific phenotype but instead seem to cause a range of clinical disorders.
“Thus, many severe mutations do not converge on one specific phenotype but instead seem to cause a range of clinical disorders74,76,80,81,84,87,91.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [76]
Females with ASD are affected by more severe genetic hits.
“suggesting that females are affected by more severe genetic hits in ASD, an observation that has been replicated in exome-sequencing studies76,117.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [76]
The elevation of protein-compromising URVs in schizophrenia cases was several times larger than the analogous elevation for de novo mutations.
“This elevation of protein-compromising URVs was several times larger than an analogously elevated rate for de novo mutations”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [13]
Using trio data, the estimated elevation of protein-damaging/disruptive de novo mutations was about 0.03 per exome, based on rates 0.185 in affected and 0.156 in unaffected individuals.
“These data yielded an elevation of about 0.03 such DNMs per exome, based on the difference between rates of 0.185 (95% CI 0.151-0.219) for individuals with schizophrenia12 and 0.156 (95% CI 0.139-0.174) for unaffected individuals13.”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [13]
Subsets of human genes have been previously identified as missense constrained or loss-of-function intolerant.
“Subsets of human genes have been previously identified as “missense constrained” (based on a lack of functional coding variation in controls) or “loss-of-function intolerant” (based on a smaller-than-expected number of loss-of-function mutations in population-scale data)13,21.”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [13]
ANK2 has been consistently associated with ASD and also with cardiac arrhythmia.
“ANK2 has been consistently associated with ASD (22,26,80) and also with cardiac arrhythmia (OMIM no.600919) (78).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [22]
One mechanism mediating the paternal age effect on ASD risk is the higher rate of de novo single-nucleotide variants and copy number variants with advancing paternal age.
“In the case of paternal age, one mediating mechanism lies in the increased rate of de novo SNV and CNV with advancing paternal age (22,24,25,43,44).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [22]
More than 50 high-risk ASD genes have emerged from large-scale sequencing studies, most under an autosomal dominant model.
“To date, in addition to causal and highly penetrant genes and genomic loci identified before whole-exome sequencing (15,30), over 50 high-risk genes have emerged from the large-scale sequencing studies (21)(22)(23)(24)(25)(26), most under a model of autosomal dominant variation.”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [22]
The liability threshold model helps explain the relatively high sibling risk, the greater mutational burden in ASD probands than unaffected siblings, etiological heterogeneity within affected sibling pairs, and variable expressivity of certain loci.
“The model helps in the understanding of the relatively high risk for siblings of individuals diagnosed with ASD (13,46), the increased mutational burden in ASD probands compared with their unaffected siblings (22,28), etiological heterogeneity even within pairs of affected siblings (47,48) and, as we shall discuss further, the variable expressivity of certain loci (49,50) (Fig. 1).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [22]
Rare genetic risk variants identified so far have a very large effect on individual ASD risk.
“Rare genetic risk variation identified to date, in contrast, has a very substantial effect on individual risk.Recent whole-exome sequencing analyses of large ASD cohorts (21)(22)(23)(24)(25)(26)(27)(28)(29) have expanded the repertoire of known genes harboring ASD-linked mutations”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [22]
Whole-exome sequencing of large ASD cohorts has expanded the set of known ASD-linked genes beyond those found by traditional genetic approaches and targeted sequencing.
“Recent whole-exome sequencing analyses of large ASD cohorts (21)(22)(23)(24)(25)(26)(27)(28)(29) have expanded the repertoire of known genes harboring ASD-linked mutations that were previously identifiable only by traditional genetic approaches and targeted sequencing (14,15).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [22]
CHD2 has been associated with ASD, intellectual disability, epilepsy, and photosensitivity.
“CHD2 has been associated with ASD (22,23), ID (73), epilepsy (82,87) and photosensitivity (83).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [22]
TBR1 has been implicated in ASD and intellectual disability.
“TBR1 has been implicated in ASD (21,22,25,26) and ID (73).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [22]
CHD2 mutations have been detected in individuals diagnosed with ASD, intellectual disability, or epilepsy.
“Mutations in CHD2 have been detected in individuals with a diagnosis of ASD (22), ID (73) or epilepsy (82,83,87,89)”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [22]
Rare high-confidence mutations tend to be significantly enriched in genes involved in synaptic functions, transcriptional regulation, and chromatin remodeling functions, and/or are downstream targets of the fragile X syndrome protein (FMRP) complex.
“such rare high-confidence mutations tend to be significantly enriched in genes involved in synaptic functions, transcriptional regulation, and chromatin remodeling functions, and/or are downstream targets of the fragile X syndrome protein (FMRP) complex.1, 3”
From Maternal immune activation dysregulation of the fetal brain transcriptome and relevance to the pathophysiology of autism spectrum disorder (2018) · cites this paper as [3]
Known ASD-associated missense variants are substantially enriched in MIA-downregulated genes (33%, 48/145, OR=2.21, P=0.0021).
“When considering known ASD-associated missense variants,3 we also found substantial enrichment (33%, 48/145, OR=2.21, P=0.0021) (Figure 1b).”
From Maternal immune activation dysregulation of the fetal brain transcriptome and relevance to the pathophysiology of autism spectrum disorder (2018) · cites this paper as [3]
De novo mutations have emerged as substantial contributors to ASD risk.
“Albeit rare, de novo mutations have emerged as substantial contributors to ASD risk [83, 165, 166, 254, 261, 309].”
From Autism spectrum disorder: neuropathology and animal models (2017) · cites this paper as [165]
CHD8 is one of the high-penetrance ASD risk genes recently identified by sequencing studies.
“Chromodomain helicase DNA-binding protein 8 (CHD8), encoding a chromatin modifying gene on chromosome 14q11.2, is one of the high-penetrance ASD risk genes recently identified by sequencing studies [83, 165, 261, 347].”
From Autism spectrum disorder: neuropathology and animal models (2017) · cites this paper as [165]
Using WW data, INRICH enrichment analysis observed enrichment at empirical P ≤ .05 for the synaptic co-expression network M13, Mendelian disease genes, and human and primate-accelerated regions; none exceeded experiment-wise corrected P ≤ .05.
“Using the WW data, we observe enrichment at an empirical P ≤ .05 for the synaptic co-expression network M13 [48], Mendelian disease genes [11], and both human (HARs) and primate-accelerated regions (PARs) [49]. None of these enrichments exceeded the experiment-wise corrected P ≤ .05.”
FMRP biology has been implicated in ASD, schizophrenia and intellectual disability.
“For example, FMRP biology has also been implicated in all three diagnoses [11].”
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Self-citationThe Simons Simplex Collection: a resource for identification of autism genetic risk factors
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Rare de novo and transmitted copy-number variation in autistic spectrum disorders
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Self-citationAdvancing Paternal Age and Autism
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Exome sequencing supports a de novo mutational paradigm for schizophrenia
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Coming of age: ten years of next-generation sequencing technologies
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Schizophrenia risk from complex variation of complement component 4
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“Of the 102 ASDassociated genes, 60 were not discovered by our earlier analyses (De Rubeis et al., 2014; Iossifov et al., 2014; Sanders et al., 2015).”
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Self-citationGene expression elucidates functional impact of polygenic risk for schizophrenia
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Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap
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Self-citationFrom the genetic architecture to synaptic plasticity in autism spectrum disorder
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Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder
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“Extended Data Figure 2 | Transcriptome-wide DGE analysis. a , We applied a classification method robust to overfitting (elastic net model 47 ) by training on the RNA-seq data from samples previously analysed in ref.”
InfluentialExcess of rare, inherited truncating mutations in autism
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Self-citationThe Neurodiversity Approach(es): What Are They and What Do They Mean for Researchers?
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Inherited and de novo genetic risk for autism impacts shared networks
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Drug development in the era of precision medicine
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High Rate of Recurrent De Novo Mutations in Developmental and Epileptic Encephalopathies
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A complete reference genome improves analysis of human genetic variation
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Self-citationGenetic risk for autism spectrum disorders and neuropsychiatric variation in the general population
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The Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis
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Exogenous and evoked oxytocin restores social behavior in the <i>Cntnap2</i> mouse model of autism
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Self-citationRecurrent de novo mutations implicate novel genes underlying simplex autism risk
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“Aswould beexpected for variantswith large effects, subjects that carry de novo mutations have lower nonverbal IQs than subjects who do not (Iossifov et al., 2014).”
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- Authors
- Iossifov, I., O’Roak, B. J., Sanders, S. J., Ronemus, M., Krumm, N., Levy, D., Stessman, H. A., Witherspoon, K. T., Vives, L., Patterson, K. E., Smith, J. D., Paeper, B., Nickerson, D. A., Dea, J., Dong, S., Gonzalez, L. E., Mandell, J. D., Mane, S. M., Murtha, M. T., Sullivan, C. A., Walker, M. F., Waqar, Z., Wei, L., Willsey, A. J., Yamrom, B., Lee, Y.-H., Grabowska, E., Dalkic, E., Wang, Z., Marks, S., Andrews, P., Leotta, A., Kendall, J., Hakker, I., Rosenbaum, J., Ma, B., Rodgers, L., Troge, J., Narzisi, G., Yoon, S., Schatz, M. C., Ye, K., McCombie, W. R., Shendure, J., Eichler, E. E., State, M. W., & Wigler, M.
- Affiliations
- Cold Spring Harbor Laboratory (US)
- Oregon Health & Science University (US)
- University of California, San Francisco (US)
- University of Washington (US)
- Peking University (CN)
- Yale University (US)
- Albert Einstein College of Medicine (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Shendure, Jay
- Eichler, Evan E.
- State, Matthew W.
- Wigler, Michael
- ORCID
- Iossifov, Ivan
- O’Roak, Brian J.
- Sanders, Stephan J.
- Ronemus, Michael
- Krumm, Niklas
- Stessman, Holly A.
- Patterson, Karynne E.
- Smith, Joshua D.
- Nickerson, Deborah A.
- Dea, Jeanselle
- Dong, Shan
- Mandell, Jeffrey D.
- Mane, Shrikant M.
- Sullivan, Catherine A.
- Wei, Liping
- Willsey, A. Jeremy
- Yamrom, Boris
- Rodgers, Linda
- Narzisi, Giuseppe
- Schatz, Michael C.
- Ye, Kenny
- McCombie, W. Richard
- Shendure, Jay
- Eichler, Evan E.
- State, Matthew W.
- Wigler, Michael
- Venue
- Nature
- Published
- 2014-10-29
- Volume
- 515
- Issue
- 7526
- Pages
- 216-221
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4313871
- OpenAlex
- W2008627757
- Cited by
- 2,585
- References
- 51
- Citations by year
- 2026: 125 · 2025: 178 · 2024: 204 · 2023: 209 · 2022: 263 · 2021: 266 · 2020: 298 · 2019: 232 · 2018: 202 · 2017: 237 · 2016: 210 · 2015: 146 · 2014: 12
- FWCI
- 112.46
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
- Zonguldak Bülent Ecevit University Institutional Repository (submittedVersion, cc-by-nc-nd)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (1rc2hl103010-01, UL1TR000142)
- Canadian Institutes of Health Research
- National Heart, Lung, and Blood Institute (RC2HL102925, RC2HL102926, RC2HL102923, UC2HL102924, RC2HL-103010, UC2HL102925, UC2HL102923, UC2HL103010, RC2HL102924, UC2HL102926)
- National Institute of Mental Health (R01MH101221)
- National Institute of General Medical Sciences (T32GM007266)
- National Center for Advancing Translational Sciences
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (U54HD083091)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- autism spectrum disorder, de novo mutations, simplex families, missense mutations, copy number variation, sex differences, intellectual disability, schizophrenia, chromatin modifiers, exome sequencing, genetic architecture, affected siblings, synaptic genes, chromatin remodeling
- MeSH terms
- Child, Child Development Disorders, Pervasive, Female, Genes, Humans, Intelligence Tests, Male, Mutation, Reproducibility of Results, Cluster Analysis, Open Reading Frames, Genetic Predisposition to Disease, Exome
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