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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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In the citing paper
“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“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
Experimental — accuracy not yet measured
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In the citing paper
“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]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“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]
Experimental — accuracy not yet measuredIn the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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 the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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.”
In the citing paper
“For example, FMRP biology has also been implicated in all three diagnoses [11].”
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Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895
Strong association of de novo copy number mutations with autism
Sebat, J., Lakshmi, B., Malhotra, D., Troge, J., Lese-Martin, C., Walsh, T., Yamrom, B., Yoon, S., Krasnitz, A., Kendall, J., et al. (2007) · Science · doi:10.1126/science.1138659 · Cited by 2,795
Self-citationDNA methylation and epigenetic inheritance
Holliday, R. (1990) · Philosophical transactions of the Royal Society of London. Series B, Biological sciences · doi:10.1098/rstb.1990.0015 · Cited by 2,290
Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs
Cross-Disorder Group of the Psychiatric Genomics Consortium (2013) · Nature Genetics · doi:10.1038/ng.2711 · Cited by 2,263
Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations
O’Roak, B. J., Vives, L., Girirajan, S., Karakoc, E., Krumm, N., Coe, B. P., Levy, R., Ko, A., Lee, C., Smith, J. D., et al. (2012) · Nature · doi:10.1038/nature10989 · Cited by 2,165
Self-citationRate of de novo mutations and the importance of father’s age to disease risk
Kong, A., Frigge, M. L., Masson, G., Besenbacher, S., Sulem, P., Magnusson, G., Gudjonsson, S. A., Sigurdsson, A., Jonasdottir, A., Jonasdottir, A., et al. (2012) · Nature · doi:10.1038/nature11396 · Cited by 2,134
Spatio-temporal transcriptome of the human brain
Kang, H. J., Kawasawa, Y. I., Cheng, F., Zhu, Y., Xu, X., Li, M., Sousa, A. M. M., Pletikos, M., Meyer, K. A., Sedmak, G., et al. (2011) · Nature · doi:10.1038/nature10523 · Cited by 2,084
Self-citationDe novo mutations revealed by whole-exome sequencing are strongly associated with autism
Sanders, S. J., Murtha, M. T., Gupta, A. R., Murdoch, J. D., Raubeson, M. J., Willsey, A. J., Ercan-Sencicek, A. G., DiLullo, N. M., Parikshak, N. N., Stein, J. L., et al. (2012) · Nature · doi:10.1038/nature10945 · Cited by 2,084
Self-citation
Cited by
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Items 701–800 of 1,014
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Mukherjee, J., Sharma, R., Dutta, P., & Bhunia, B. (2023) · Biotechnology and Genetic Engineering Reviews · doi:10.1080/02648725.2023.2196476 · Cited by 45
NSD1 deposits histone H3 lysine 36 dimethylation to pattern non-CG DNA methylation in neurons
Hamagami, N., Wu, D. Y., Clemens, A. W., Nettles, S. A., Li, A., & Gabel, H. W. (2023) · Molecular Cell · doi:10.1016/j.molcel.2023.04.001 · Cited by 45
Discovery of Rare Mutations in Autism: Elucidating Neurodevelopmental Mechanisms
Uzun, E. D. G., Sciarra, L. N., Maguire, A. M., Pescosolido, M. F., van Dyck, L. I., & Morrow, E. M. (2015) · Neurotherapeutics · doi:10.1007/s13311-015-0363-9 · Cited by 45
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Bishop, S. L., Thurm, A. E., Farmer, C., & Lord, C. (2016) · PEDIATRICS · doi:10.1542/peds.2015-2959 · Cited by 45
RareRELNvariants affect Reelin-DAB1 signal transduction in autism spectrum disorder
Sánchez-Sánchez, S. M., Magdalon, J., Griesi‐Oliveira, K., Yamamoto, G. L., Santacruz-Pérez, C., Fogo, M. S., Passos‐Bueno, M. R., & Sertie, A. L. (2018) · Human Mutation · doi:10.1002/humu.23584 · Cited by 45
Dissecting the genetic basis of comorbid epilepsy phenotypes in neurodevelopmental disorders
Chow, J. C., Jensen, M., Amini, H., Hormozdiari, F., Penn, O., Shifman, S., Girirajan, S., & Hormozdiari, F. (2019) · Genome Medicine · doi:10.1186/s13073-019-0678-y · Cited by 45
Li, Q., Zhao, L., Zeng, Y., Kuang, Y., Guan, Y., Chen, B., Xu, S., Tang, B., Wu, L., Mao, X., et al. (2023) · Genome biology · doi:10.1186/s13059-023-02894-0 · Cited by 44
Drosophila Studies on Autism Spectrum Disorders
Tian, Y., Zhang, Z. C., & Han, J. (2017) · Neuroscience Bulletin · doi:10.1007/s12264-017-0166-6 · Cited by 44
Vallée, A., Vallée, J.-N., & Lecarpentier, Y. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0131-4 · Cited by 44
Lu, C., Shi, X., Allen, A. S., Báez-Nieto, D., Nikish, A., Sanjana, N. E., & Pan, J. Q. (2019) · The FASEB Journal · doi:10.1096/fj.201801110rr · Cited by 44
Zhou, W., Zhang, J., Li, Z., Lin, X., Li, J., Wang, S., Yang, C., Wu, Q., Ye, A. Y., Wang, M., et al. (2019) · Human Mutation · doi:10.1002/humu.23724 · Cited by 44
Self-citationAssessing autism in females: The importance of a sex-specific comparison
Lundström, S., Mårland, C., Kuja‐Halkola, R., Anckarsäter, H. S., Lichtenstein, P., Gillberg, C., & Nilsson, T. (2019) · Psychiatry Research · doi:10.1016/j.psychres.2019.112566 · Cited by 44
Montenegro, E. M. D. S., Costa, C. S., Campos, G. D. S., Scliar, M. O., de Almeida, T. F., Zachi, E. C., Silva, I. M. W., Chan, A. J. S., Zarrei, M., Lourenço, N. C. V., et al. (2019) · Autism Research · doi:10.1002/aur.2238 · Cited by 44
Breen, M. S., Browne, A., Hoffman, G. E., Stathopoulos, S., Brennand, K., Buxbaum, J. D., & Drapeau, E. (2020) · Molecular Autism · doi:10.1186/s13229-020-00355-0 · Cited by 44
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Vallée, A., Lecarpentier, Y., Guillevin, R., & Vallée, J.-N. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-01086-9 · Cited by 44
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Eyring, K. W., & Geschwind, D. H. (2021) · Human Molecular Genetics · doi:10.1093/hmg/ddab176 · Cited by 46
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Yoon, S. C., Muñoz, A., Yamrom, B., Lee, Y.-H., Andrews, P., Marks, S., Wang, Z., Reeves, C., Winterkorn, L. H., Krieger, A. Μ., et al. (2021) · Communications Biology · doi:10.1038/s42003-021-02533-z · Cited by 44
Self-citationJiang, P., Ollodart, A. R., Sudhesh, V., Herr, A. J., Dunham, M. J., & Harris, K. (2021) · eLife · doi:10.7554/elife.68285 · Cited by 46
A randomized controlled trial of sertraline in young children with autism spectrum disorder
Potter, L. A., Scholze, D. A., Biag, H. M. B., Schneider, A., Chen, Y., Nguyen, D. V., Rajaratnam, A., Rivera, S. M., Dwyer, P. S., Tassone, F., et al. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00810 · Cited by 43
Sensory hypo-excitability in a rat model of fetal development in Fragile X Syndrome
Berzhanskaya, J., Phillips, M. A., Shen, J., & Colonnese, M. T. (2016) · Scientific Reports · doi:10.1038/srep30769 · Cited by 43
Lossi, L., Castagna, C., Granato, A., & Merighi, A. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm8122088 · Cited by 43
Bellott, D. W., & Page, D. C. (2021) · Genome Research · doi:10.1101/gr.268516.120 · Cited by 43
Jung, S., & Park, M. (2022) · Pharmacological Research · doi:10.1016/j.phrs.2022.106340 · Cited by 42
Zarrei, M., Merico, D., Kellam, B., Engchuan, W., Scriver, T., Jokhan, R., Wilson, M. D., Parr, J. R., Lemire, E. G., Stavropoulos, D. J., et al. (2017) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.38176 · Cited by 42
Arpi, M. N. T., & Simpson, T. I. (2022) · Scientific Reports · doi:10.1038/s41598-022-14077-1 · Cited by 42
Gillentine, M. A., Wang, T., & Eichler, E. E. (2022) · Biomedicines · doi:10.3390/biomedicines10112865 · Cited by 42
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Luo, Y., Lu, L., Song, H., Han, X., Zheng, Z.-W., Wu, Z., Jiang, C.-C., Tong, C., Yuan, H., Liu, X., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-01954-y · Cited by 42
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Gordon, A., Yoon, S., Bicks, L. K., Martín, J. M., Pintacuda, G., Arteaga, S. A., Wamsley, B., Guo, Q., Elahi, L. S., Dolmetsch, R. E., et al. (2026) · Nature · doi:10.1038/s41586-025-10047-5 · Cited by 42
Self-citationMechanisms of Long Non-Coding RNAs in the Assembly and Plasticity of Neural Circuitry
Wang, A., Wang, J., Liu, Y., & Zhou, Y. (2017) · Frontiers in Neural Circuits · doi:10.3389/fncir.2017.00076 · Cited by 42
Wu, H., Li, H., Bai, T., Han, L., Ou, J., Xun, G., Zhang, Y., Wang, Y., Duan, G., Zhao, N., et al. (2019) · Clinical Genetics · doi:10.1111/cge.13665 · Cited by 42
Self-citationHurley, S., Mohan, C., Suetterlin, P., Ellingford, R. A., Riegman, K. L. H., Ellegood, J., Caruso, A., Michetti, C., Brock, O., Evans, R., et al. (2021) · Molecular Autism · doi:10.1186/s13229-020-00409-3 · Cited by 42
DeSpenza, T., Carlson, M., Panchagnula, S., Robert, S. M., Duy, P. Q., Mermin‐Bunnell, K., Reeves, B. C., Kundishora, A. J., Elsamadicy, A. A., Smith, H. L., et al. (2021) · Trends in Neurosciences · doi:10.1016/j.tins.2021.08.007 · Cited by 42
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Uddin, M. J., Pellecchia, G., Thiruvahindrapuram, B., D’Abate, L., Merico, D., Chan, A. J. S., Zarrei, M., Tammimies, K., Walker, S., Gazzellone, M. J., et al. (2016) · Scientific Reports · doi:10.1038/srep28663 · Cited by 42
Bonnet-Brilhault, F., Alirol, S., Blanc, R., Bazaud, S., Marouillat, S., Thépault, R.-A., Andres, C. R., Lemonnier, É., Barthélémy, C., Raynaud, M., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.75 · Cited by 41
Huang, M., Liang, C., Li, S., Zhang, J., Guo, D., Zhao, B., Liu, Y., Peng, Y., Xu, J., Liu, W., et al. (2020) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2019.00577 · Cited by 41
“Among them, Dock4 has attracted recent attention as emerging evidence suggests DOCK4 as a candidate gene for several neuropsychiatric diseases, including autism spectrum disorder (ASD), dyslexia and schizophrenia (Maestrini et al., 2010; Pagnamenta et al., 2010; Poelmans et al., 2011; Alkelai et al., 2012; Iossifov et…”
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Lee, K. C., Mills, Z., Cheung, P. Y., Cheyne, J. E., & Montgomery, J. M. (2022) · Pharmaceuticals · doi:10.3390/ph16010001 · Cited by 42
Calame, D. G., Guo, T., Wang, C., Garrett, L., Jolly, A., Dawood, M., Kurolap, A., Henig, N. Z., Fatih, J. M., Herman, I., et al. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.06.013 · Cited by 42
Yang, Y., Yang, R., Kang, B., Qian, S., He, X., & Zhang, X. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113335 · Cited by 41
Yavuz, B. R., Arici, M. K., Demirel, H. C., Tsai, C., Jang, H., Nussinov, R., & Tunçbağ, N. (2023) · npj Genomic Medicine · doi:10.1038/s41525-023-00377-6 · Cited by 41
Xu, X., Jaehne, E. J., Greenberg, Z., McCarthy, P., Saleh, E., Parish, C. L., Camera, D., Heng, J. I., Haas, M., Baune, B. T., et al. (2015) · Scientific Reports · doi:10.1038/srep12434 · Cited by 41
Baig, D. N., Yanagawa, T., & Tabuchi, K. (2016) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2016.10.006 · Cited by 41
Grzadzinski, R., Lord, C., Sanders, S., Werling, D. M., & Bal, V. H. (2017) · Autism Research · doi:10.1002/aur.1856 · Cited by 41
Self-citationChildhood disintegrative disorder and autism spectrum disorder: a systematic review
Mehra, C., Sil, A., Hedderly, T. J., Kyriakopoulos, M., Lim, M. J., Turnbull, J., Happe, F. G. E., Baird, G., & Absoud, M. (2018) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.14126 · Cited by 41
Hypothesis‐driven investigations of diverse pharmacological targets in two mouse models of autism
Rhine, M. A., Parrott, J. M., Schultz, M. N., Kazdoba, T. M., & Crawley, J. N. (2019) · Autism Research · doi:10.1002/aur.2066 · Cited by 42
The use of iPSC technology for modeling Autism Spectrum Disorders
Russo, F. B., Brito, A., de Freitas, A. M., Castanha, A. G., Freitas, B. C. D., & Beltrão-Braga, P. C. B. (2019) · Neurobiology of Disease · doi:10.1016/j.nbd.2019.104483 · Cited by 41
Nakashima, M., Kato, M., Matsukura, M., Kira, R., Ngu, L. H., Lichtenbelt, K. D., van Gassen, K. L. I., Mitsuhashi, S., Saitsu, H., & Matsumoto, N. (2020) · Journal of Human Genetics · doi:10.1038/s10038-020-0758-2 · Cited by 41
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Jia, Z., & Wu, Q. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.587819 · Cited by 41
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Hoffmann, A., & Spengler, D. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10020366 · Cited by 41
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Rosenthal, S. B., Willsey, H. R., Xu, Y., Yuan, M., Dea, J., Wang, S., Curtis, C., Sempou, E., Khokha, M. K., Chi, N. C., et al. (2021) · Cell Systems · doi:10.1016/j.cels.2021.07.009 · Cited by 41
Self-citationeIF4E‐homologous protein (4EHP): a multifarious cap‐binding protein
Christie, M., & Igreja, C. (2021) · FEBS Journal · doi:10.1111/febs.16275 · Cited by 41
Dammann, O. (2020) · CRC Press eBooks · doi:10.1201/9780429184147 · Cited by 40
Berkowicz, S., Featherby, T. J., Qu, Z., Giousoh, A., Borg, N. A., Heng, J. I., Whisstock, J. C., & Bird, P. I. (2016) · Molecular Autism · doi:10.1186/s13229-016-0079-7 · Cited by 40
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Qi, H., Dong, C., Chung, W. K., Wang, K., & Shen, Y. (2016) · Human Mutation · doi:10.1002/humu.23040 · Cited by 40
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Jansen, A. G., Dieleman, G. C., Smit, A. B., Verhage, M., Verhulst, F. C., Polderman, T. J. C., & Posthuma, D. (2017) · European Journal of Human Genetics · doi:10.1038/ejhg.2017.55 · Cited by 40
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Qi, Y., Zheng, Y., Li, Z., & Xiong, L. (2017) · Brain Sciences · doi:10.3390/brainsci7100134 · Cited by 40
Brown, E., Lautz, J. D., Davis, T. R., Gniffke, E. P., VanSchoiack, A., Neier, S. C., Tashbook, N., Nicolini, C., Fahnestock, M. L., Schrum, A. G., et al. (2018) · Molecular Autism · doi:10.1186/s13229-018-0229-1 · Cited by 42
Janecka, M., Hansen, S. N., Modabbernia, A., Browne, H. A., Buxbaum, J. D., Schendel, D., Reichenberg, A., Parner, E. T., & Grice, D. E. (2019) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2018.09.447 · Cited by 40
Du, Y., Li, Z., Liu, Z., Zhang, N., Wang, R., Li, F., Zhang, T., Jiang, Y., Zhi, X., Wang, Z., et al. (2019) · Genetics in Medicine · doi:10.1038/s41436-019-0610-2 · Cited by 40
Self-citationWon, D., Kim, D., Woo, J., & Lee, K. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab529 · Cited by 40
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Chen, P., Liu, Z., Zhang, Q., Dong, L., Song, L., Liu, J., Jiao, H., Lai, X., Zou, S., Wang, S., et al. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1003-21.2021 · Cited by 40
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Bakken, T. E., Miller, J. A., Luo, R., Bernard, A., Bennett, J. L., Lee, C., Bertagnolli, D., Parikshak, N., Smith, K. A., Sunkin, S. M., et al. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv166 · Cited by 40
Jansen, S., Kleefstra, T., Willemsen, M. H., de Vries, P., Pfundt, R., Hehir‐Kwa, J. Y., Gilissen, C., Veltman, J. A., Vries, B. B. A. D., & Vissers, L. E. L. M. (2016) · Clinical Genetics · doi:10.1111/cge.12729 · Cited by 40
Amaral, D. G., Anderson, G. M., Bailey, A. J., Bernier, R., Bishop, S. L., Blatt, G. J., Canal‐Bedia, R., Charman, T., Dawson, G., de Vries, P. J., et al. (2019) · Autism Research · doi:10.1002/aur.2101 · Cited by 40
Torene, R. I., Sacoto, M. J. G., Millan, F., Zhang, Z., McGee, S., Oetjens, M. T., Heise, E. M., Chong, K., Sidlow, R., O’Grady, L., et al. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.11.007 · Cited by 39
Moreno-Ramos, O. A., Olivares, A. M., Haider, N. B., de Autismo, L. C., & Lattig, M. C. (2015) · PLoS ONE · doi:10.1371/journal.pone.0135927 · Cited by 39
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Bo, T., Zou, Y., Zhang, Y., Zhang, R., Ou, J., Shen, Y., Zhao, J., Luo, X., Guo, J., Zeng, L., et al. (2016) · Journal of Human Genetics · doi:10.1038/jhg.2015.156 · Cited by 39
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Wagner, S., & Harony‐Nicolas, H. (2017) · Current topics in behavioral neurosciences · doi:10.1007/7854_2017_15 · Cited by 39
Courchet, V., Roberts, A. J., Meyer-Dilhet, G., del Carmine, P., Lewis, T. L., Polleux, F., & Courchet, J. (2018) · Nature Communications · doi:10.1038/s41467-018-06584-5 · Cited by 39
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Jensen, M., & Girirajan, S. (2019) · PLoS Genetics · doi:10.1371/journal.pgen.1007879 · Cited by 39
Arnett, A. B., Trinh, S., & Bernier, R. (2018) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2018.07.004 · Cited by 39
Han, X., Chen, S., Flynn, E. D., Wu, S., Wintner, D., & Shen, Y. (2018) · Nature Communications · doi:10.1038/s41467-018-04552-7 · Cited by 39
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Becker, M., Mastropasqua, F., Reising, J. P., Maier, S. J., Ho, M., Rabkina, I., Li, D., Neufeld, J., Ballenberger, L., Myers, L., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-00994-0 · Cited by 40
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Tai, D. J. C., Razaz, P., Erdin, S., Gao, D., Wang, J. P., Nuttle, X., de Esch, C. E., Collins, R. L., Currall, B., O’Keefe, K., et al. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.08.012 · Cited by 39
Rubinstein, M., Patowary, A., Stanaway, I. B., McCord, E., Nesbitt, R., Archer, M., Scheuer, T., Nickerson, D. A., Raskind, W. H., Wijsman, E. M., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.222 · Cited by 39
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Schumann, C. M., Sharp, F. R., Ander, B. P., & Stamova, B. S. (2017) · Molecular Autism · doi:10.1186/s13229-017-0117-0 · Cited by 39
Russell, T. A., Grubisha, M. J., Remmers, C. L., Kang, S. K., Forrest, M. P., Smith, K. R., Kopeikina, K. J., Gao, R., Sweet, R. A., & Penzes, P. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.10.024 · Cited by 39
Montgomery, A. K., Shuffrey, L. C., Guter, S. J., Anderson, G. M., Jacob, S., Mosconi, M. W., Sweeney, J. A., Turner, J. B., Sutcliffe, J. S., Cook, E. H., et al. (2018) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2018.06.025 · Cited by 39
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Li, Y., Jia, X., Wu, H., Xun, G., Ou, J., Zhang, Q., Li, H., Bai, T., Hu, Z., Zou, X., et al. (2018) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.40666 · Cited by 40
Teter, O. M., McQuade, A., Hagan, V., Liang, W., Dräger, N. M., Sattler, S. M., Holmes, B. B., Castillo, V. C., Papakis, V., Leng, K., et al. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-02997-z · Cited by 38
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Guo, H., Zhang, Q., Dai, R., Yu, B., Hoekzema, K., Tan, J., Tan, S., Jia, X., Chung, W. K., Hernan, R., et al. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.10.002 · Cited by 38
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Ghanaeian, A., Majhi, S., McCafferty, C. L., Nami, B., Black, C. S., Yang, S. K., Legal, T., Papoulas, O., Poprzeczko, M., Valente-Paterno, M., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41480-7 · Cited by 38
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Mastrototaro, G., Zaghi, M., & Sessa, A. (2017) · Journal of Molecular Neuroscience · doi:10.1007/s12031-017-0900-6 · Cited by 38
Singh, G., Singh, V., & Schneider, J. S. (2018) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2018.10.016 · Cited by 38
Wade, A. A., Lim, K. J., Catta-Preta, R., & Nord, A. S. (2019) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2018.00481 · Cited by 38
Jansen, S., van der Werf, I., Innes, A. M., Afenjar, A., Agrawal, P. B., Anderson, I. J., Atwal, P. S., van Binsbergen, E., van den Boogaard, M. H., Castiglia, L., et al. (2019) · European Journal of Human Genetics · doi:10.1038/s41431-018-0292-2 · Cited by 38
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Tong, D.-L., Chen, R., Lu, Y., Li, W.-K., Zhang, Y., Lin, J.-K., He, L.-J., Dang, T., Shan, S., Xu, X., et al. (2019) · Neurobiology of Disease · doi:10.1016/j.nbd.2019.104486 · Cited by 39
Kayarian, F. B., Jannati, A., Rotenberg, A., & Santarnecchi, E. (2020) · Autism Research · doi:10.1002/aur.2312 · Cited by 38
Cunniff, M. M., Markenscoff-Papadimitriou, E., Ostrowski, J., Rubenstein, J. L. R., & Sohal, V. S. (2020) · eLife · doi:10.7554/elife.54835 · Cited by 40
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Weerts, M. J. A., Lanko, K., Guzmán‐Vega, F. J., Jackson, A., Ramakrishnan, R., Cardona‐Londoño, K. J., Peña‐Guerra, K. A., van Bever, Y., van Paassen, B. W., Kievit, A. J. A., et al. (2021) · Genetics in Medicine · doi:10.1038/s41436-021-01246-2 · Cited by 38
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Nishioka, M., Kazuno, A., Nakamura, T., Sakai, N., Hayama, T., Fujii, K., Matsuo, K., Komori, A., Ishiwata, M., Watanabe, Y., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23453-w · Cited by 38
Nassir, N., Bankapur, A., Samara, B., Ali, A. Y., Ahmed, A., Inuwa, I. M., Zarrei, M., Shabestari, S. A. S., Albanna, A., Howe, J., et al. (2021) · Human Genomics · doi:10.1186/s40246-021-00368-7 · Cited by 38
Arenella, M., Cadby, G., Witte, W. D., Jones, R., Whitehouse, A., Moses, E. K., Fornito, A., Bellgrove, M. A., Hawi, Z., Johnson, B. P., et al. (2021) · Autism · doi:10.1177/13623613211019547 · Cited by 38
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Clark, L. N., & Louis, E. D. (2015) · Revue Neurologique · doi:10.1016/j.neurol.2015.02.015 · Cited by 38
Halvorsen, M., Gould, L., Wang, X., Grant, G., Moya, R., Rabin, R., Ackerman, M. J., Tester, D. J., Lin, P. T., Pappas, J., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2115140118 · Cited by 38
CERT1 mutations perturb human development by disrupting sphingolipid homeostasis
Gehin, C. J. C., Lone, M. A., Lee, W., Capolupo, L., Ho, S., Adeyemi, A. M., Gerkes, E. H., Stegmann, A. P. A., Martín, E. L., Bermejo, E., et al. (2023) · Journal of Clinical Investigation · doi:10.1172/jci165019 · Cited by 38
Metadata
- 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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