The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Patterns and rates of exonic de novo mutations in autism spectrum disorders
Open accessAbstract
Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified. To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case–control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.
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In the citing paper
“TADA requires a mutational model (Sanders et al., 2012; Neale et al., 2012; Samocha et al., 2014) which accounts for gene size and sequence composition to obtain an expectation for mutations per gene, given sample size.”
From Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism (2020) · cites this paper as Neale et al., 2012
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
“CNVs and SNPs have both been reported to play a major role in autism incidence (36–41).”
From Gene × Environment Interactions in Autism Spectrum Disorders: Role of Epigenetic Mechanisms (2014) · cites this paper as [38]
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
“Exome sequencing of ASD/ID families has revealed a significant excess of de novo mutations in probands when compared to unaffected siblings and has identified novel candidate genes contributing to the neurological deficits.”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [25]
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
“We note that the strongest effects are observed for de novo loss-of-function (or truncating) mutations”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [25]
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
“Simulations based on the observed number of recurrently disrupted genes have estimated that there are some 600-1200 ASD risk genes (21,24,26,51).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [21]
Experimental — accuracy not yet measured
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In the citing paper
“mutations in chromatin complexes have been observed in schizophrenia where synaptic gene regulation is disrupted, and these mutations are also high-confidence genetic risk factors for ASD”
From The clinical use of epigenetics in psychiatry: a narrative review of epigenetic mechanisms, key candidate genes, and precision psychiatry (2025) · cites this paper as [42]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“These studies demonstrate the ability of new sequencing technologies to significantly advance our understanding of the genetic basis of ASD.”
From Activity-dependent neuronal signalling and autism spectrum disorder (2013) · cites this paper as [8]
The cited source says what the claim attributes to it.
In the citing paper
“Many strong neurobiological candidates have emerged from the genes disrupted by de novo mutations in these studies, including mutations in previously identified ASD/ID genes.”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [25]
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In the citing paper
“One of the INH-M13 hub genes is CHD2, whose de novo variants have been identified in individuals with ASD.42,43”
From hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data (2023) · cites this paper as [43]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“One of the INH-M13 hub genes is CHD2, whose de novo variants have been identified in individuals with ASD.42,43”
From hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data (2023) · cites this paper as [43]
Experimental — accuracy not yet measuredIn the citing paper
“These estimates are similar to published results using somewhat different methods [1], [2].”
From Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes (2013) · cites this paper as [2]
In the citing paper
“Exome sequencing has uncovered de novo single nucleotide variations (SNVs) and insertion/deletion (indel) mutations that segregate with ASD.”
From Unifying Views of Autism Spectrum Disorders: A Consideration of Autoregulatory Feedback Loops (2016) · cites this paper as Neale et al., 2012
In the citing paper
“Hypomorphic, biallelic mutations, combined with CNVs and heterozygous stop mutations (Neale et al., 2012; O’Roak et al., 2012; Sanders et al., 2012) which completely inactivate one of two alleles, suggest that a common theme for ASD mutations in general might be partial loss of gene function and/or dosage sensitivity.”
From Using Whole-Exome Sequencing to Identify Inherited Causes of Autism (2013) · cites this paper as Neale et al., 2012
In the citing paper
“ASD is often due to newly arising gene copy number variants (CNVs) — such as a deletion or duplication of a region of a chromosome — or a rare mutation that arises in the germ cell, particularly in sperm of older fathers5–10.”
From Activity-dependent neuronal signalling and autism spectrum disorder (2013) · cites this paper as [8]
In the citing paper
“In addition, very recent exome sequencing of parent-offspring trios has identified de novo exonic mutations in SCN2A, KATNAL2, CHD8, FOXP1, NTNG1, GRIN2B, LAMC3(refs 7–9), extending further the number of genes for which mutation may contribute to ASD.”
From Activity-dependent neuronal signalling and autism spectrum disorder (2013) · cites this paper as [8]
In the citing paper
“References 7– 10 use exome and entire genome sequencing to demonstrate the importance of rare mutations in ASD and identify new genetic mutations associated with ASD.”
From Activity-dependent neuronal signalling and autism spectrum disorder (2013) · cites this paper as [8]
In the citing paper
“and also that the loci hit by these SNVs are highly heterogeneous”
From Sex differences in autism spectrum disorders (2013) · cites this paper as [48]
In the citing paper
“Together, results from these papers demonstrate a significant role for rare SNVs in genetic liability for ASD”
From Sex differences in autism spectrum disorders (2013) · cites this paper as [48]
In the citing paper
“finding a handful of genes that are recurrently hit by these rare variants”
From Sex differences in autism spectrum disorders (2013) · cites this paper as [48]
In the citing paper
“Exome and whole-genome sequencing studies have estimated at least another ∼6% contribution to ASD7–10,15”
From Convergence of genes and cellular pathways dysregulated in autism spectrum disorders (2014) · cites this paper as [8]
In the citing paper
“De novo SNVs in CHD2 have been reported in an ASD subject and in several individuals with a broad spectrum of neurodevelopmental disorders, including ID and epileptic encephalopathy8,49,50 (Figure S6).”
From Convergence of genes and cellular pathways dysregulated in autism spectrum disorders (2014) · cites this paper as [8]
In the citing paper
“and three other recent studies by Sanders et al.8, O’Roak et al.7 and Neale et al.23 (65 genes combined from all three; referred to as ‘SON-exomes’);”
From Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism (2014) · cites this paper as [23]
In the citing paper
“Genetic investigations in ASD have constructed seed-based networks with literature-curated PPIs to identify the convergence of ASD risk genes71,73.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [73]
In the citing paper
“In summary, only three genes [CHD8, SCN2A, and synaptic Ras GTPase activating protein 1 (SYNGAP1)] had two independent truncating de novo mutations in any single study, and no gene had more than three mutations.”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [25]
In the citing paper
“Notably, however, a follow-up case-control study by Neale and colleagues of 935 cases found three additional truncating CHD8 mutations and one splice-site mutation in SCN2A, further strengthening the initial disease associations of these genes [25].”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [25]
In the citing paper
“New exome sequencing technology has identified novel rare variants and has found that sporadic cases of ASD/ID are enriched for disruptive de novo mutations.”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [25]
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 [21]
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 [21]
In the citing paper
“At this point, it is clear that rare microscopically detectable chromosomal rearrangements (14,15), submicroscopic deletions or duplications (CNV or smaller structural variation) (27,(29)(30)(31)(32), single-nucleotide variation (SNV) and small deletions and duplications (indels) (21)(22)(23)(24)(25)(26)(33)(34)(35) all contribute to risk.”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [21]
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 [21]
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 [21]
In the citing paper
“Qualitatively, recent studies of rare variants also find it challenging to distinguish risk variation from the background stochastic noise (12–15).”
From Individual common variants exert weak effects on the risk for autism spectrum disorders (2012) · cites this paper as [14]
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 [254]
In the citing paper
“Recent exome sequencing studies only reported one de novo SHANK2 mutation out of 965 patients [32], [36], [37]”
From Meta-analysis of SHANK Mutations in Autism Spectrum Disorders: A Gradient of Severity in Cognitive Impairments (2014) · cites this paper as [37]
In the citing paper
“no truncating coding-sequence variation within SHANK1 and SHANK3”
From Meta-analysis of SHANK Mutations in Autism Spectrum Disorders: A Gradient of Severity in Cognitive Impairments (2014) · cites this paper as [37]
In the citing paper
“However, a central finding from these papers was that only a minority of cases had a de novo putatively functional variant”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [84]
In the citing paper
“Three recent papers describe the results from exome sequencing of ~600 trios, and identify roles for de novo exonic mutations in SCN2A, KATNAL2, and CHD8 in the pathogenesis of ASD. 83–85”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [84]
In the citing paper
“Intriguingly, all three studies noted an increased rate of de novo exonic mutations in older parents (with the mutations generally being of paternal origin), 83–85”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [84]
In the citing paper
“Unexpectedly, simplex and multiplex ASD pedigrees show relatively similar de novo mutation rates for SV 80,81 and exonic variation. 83–85”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [84]
In the citing paper
“pathway analyses reported in two of the studies found that genes containing de novo exonic variation were more closely connected in reference to protein-protein interaction databases. 83,84”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [84]
In the citing paper
“estimates from de novo exonic mutations (similar to those from SV data) suggest that ASD is highly polygenic (estimates ranged from 400–1000 genes). 84,85”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [84]
In the citing paper
“The published results for ASD 83–85 and unpublished data on SCZ suggest these issues will be important and underscore the need for sequencing studies to have the same emphasis on statistical rigor and large sample sizes that has enabled GWAS to realize success for multiple psychiatric disorders. 154”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [84]
In the citing paper
“Many studies of complex neuropsychiatric disorders have also concluded that disease-causing variants are often clustered in protein-interaction networks with a high degree of connectivity among themselves and that these clustered networks are often enriched with functional pathways relevant to brain functions [72–80].”
From An integrated analysis of genes and functional pathways for aggression in human and rodent models (2019) · cites this paper as [72]
In the citing paper
“These three studies report de novo mutations with a twofold to fourfold increase in de novo nonsense variants among affected subjects over that expected by chance”
From Autism risk factors: genes, environment, and gene-environment interactions (2012) · cites this paper as [36]
In the citing paper
“two of these studies report that spontaneous changes are correlated with paternal age”
From Autism risk factors: genes, environment, and gene-environment interactions (2012) · cites this paper as [36]
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Cites
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
Self-citationA method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Self-citationFast and accurate long-read alignment with Burrows-Wheeler transform.
Li, H., & Durbin, R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp698 · Cited by 12,063
A framework for variation discovery and genotyping using next-generation DNA sequencing data
DePristo, M. A., Banks, E., Poplin, R. E., Garimella, K. V., Maguire, J., Hartl, C., Philippakis, A., del Angel, G., Rivas, M. A., Hanna, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.806 · Cited by 11,508
Self-citationRare-Variant Association Testing for Sequencing Data with the Sequence Kernel Association Test
Wu, M. C., Lee, S., Cai, T., Li, Y., Boehnke, M., & Lin, X. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.05.029 · Cited by 2,373
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
De 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-citationFunctional impact of global rare copy number variation in autism spectrum disorders
Pinto, D., Pagnamenta, A. T., Klei, L., Anney, R., Merico, D., Regan, R., Conroy, J., Magalhaes, T. R., Correia, C., Abrahams, B. S., et al. (2010) · Nature · doi:10.1038/nature09146 · Cited by 2,013 · cited 1×
“Copy number variants (CNVs), often de novo and covering multiple adjacent genes, have been identified as conferring risk 3,4 .”
BackgroundSelf-citationGenetic Heritability and Shared Environmental Factors Among Twin Pairs With Autism
Hallmayer, J. (2011) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2011.76 · Cited by 1,970
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Panoutsopoulou, K., Tachmazidou, I., & Zeggini, E. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt376 · Cited by 90
Machol, K., Rousseau, J., Ehresmann, S., Garcia, T., Nguyen, T. T. M., Spillmann, R. C., Sullivan, J. A., Shashi, V., Jiang, Y., Stong, N., et al. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.11.007 · Cited by 86
Self-citationCandidate and non-candidate genes in behavior genetics
Flint, J., & Munafo, M. R. (2012) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.07.005 · Cited by 85
Guan, J., Cai, J. J., Ji, G., & Sham, P. C. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0488-4 · Cited by 86
Neggers, Y. H. (2014) · ISRN Nutrition · doi:10.1155/2014/514026 · Cited by 101
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Sanders, S. J. (2015) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2015.10.002 · Cited by 84
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Leblond, C. S., Cliquet, F., Carton-Buonafine, C., Huguet, G., Mathieu, A., Kergrohen, T., Buratti, J., Lemière, N., Cuisset, L., Bienvenu, T., et al. (2019) · npj Genomic Medicine · doi:10.1038/s41525-018-0075-2 · Cited by 86
Davarnia, B., Hu, H., Kahrizi, K., Musante, L., Fattahi, Z., Hosseini, M., Maqsoud, F., Farajollahi, R., Wienker, T. F., Ropers, H., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0129631 · Cited by 83
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Mohn, J. L., Alexander, J., Pirone, A., Palka, C., Lee, S.-Y., Mebane, L. M., Haydon, P. G., & Jacob, M. H. (2014) · Molecular Psychiatry · doi:10.1038/mp.2014.61 · Cited by 83
Helbig, I., & Lowenstein, D. H. (2013) · Current Opinion in Neurology · doi:10.1097/wco.0b013e32835ee6ff · Cited by 82
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Brunham, L. R., & Hayden, M. R. (2013) · Human Genetics · doi:10.1007/s00439-013-1286-3 · Cited by 84
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Suhl, J. A., Chopra, P., Anderson, B. R., Bassell, G. J., & Warren, S. T. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu272 · Cited by 81
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Pak, C., Dankó, T., Mirabella, V. R., Wang, J., Liu, Y., Vangipuram, M., Grieder, S. D., Zhang, X., Ward, T., Huang, Y. A., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2025598118 · Cited by 84
Lalli, M. A., Jang, J., Park, J.-H. C., Wang, Y., Guzman, E., Zhou, H., Audouard, M., Bridges, D. C., Tovar, K. R., Papuc, S. M., et al. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw010 · Cited by 79
Whole-genome sequencing in an autism multiplex family
Shi, L., Zhang, X., Golhar, R., Otieno, F. G., He, M., Hou, C., Kim, C., Keating, B. J., Lyon, G. J., Wang, K., et al. (2013) · Molecular Autism · doi:10.1186/2040-2392-4-8 · Cited by 82
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Kilpinen, H., & Barrett, J. C. (2012) · Trends in Genetics · doi:10.1016/j.tig.2012.10.001 · Cited by 81
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Kim, Y. J., Khoshkhoo, S., Frankowski, J. C., Zhu, B., Abbasi, S., Lee, S., Wu, Y. E., & Hunt, R. F. (2018) · Neuron · doi:10.1016/j.neuron.2018.09.049 · Cited by 81
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Kaushik, G., & Zarbalis, K. S. (2016) · Frontiers in Chemistry · doi:10.3389/fchem.2016.00012 · Cited by 80
Cartier, E., Hamilton, P. J., Belovich, A. N., Shekar, A., Campbell, N. G., Saunders, C., Andreassen, T. F., Gether, U., Veenstra-Vanderweele, J., Sutcliffe, J. S., et al. (2015) · EBioMedicine · doi:10.1016/j.ebiom.2015.01.007 · Cited by 74
Self-citationWang, W., Corominas, R., & Lin, G. N. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00258 · Cited by 70
An, J., Cristino, A. S., Zhao, Q., Edson, J., Williams, S. M., Ravine, D., Wray, J. A., Marshall, V. M., Hunt, A., Whitehouse, A., et al. (2014) · Translational Psychiatry · doi:10.1038/tp.2014.38 · Cited by 81
Cheng, M. H., Block, E. R., Hu, F., Çobanoğlu, M. C., Sorkin, A. D., & Bahar, İ. (2015) · Frontiers in Neurology · doi:10.3389/fneur.2015.00134 · Cited by 80
Dou, Y., Yang, X., Li, Z., Wang, S., Zhang, Z., Ye, A. Y., Yan, L., Yang, C., Wu, Q., Li, J., et al. (2017) · Human Mutation · doi:10.1002/humu.23255 · Cited by 75
Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease
Gratten, J., Visscher, P. M., Mowry, B. J., & Wray, N. R. (2013) · Nature Genetics · doi:10.1038/ng.2555 · Cited by 77
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Shen, T., Ji, F., Yuan, Z., & Jiao, J. (2015) · Stem Cells · doi:10.1002/stem.2001 · Cited by 78
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Dunleavy, J. E. M., Okuda, H., O’Connor, A. E., Merriner, D. J., O’Donnell, L., Jamsai, D., Bergmann, M., & O’Bryan, M. K. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1007078 · Cited by 71
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Autism genes keep turning up chromatin
LaSalle, J. M. (2013) · OA Autism · doi:10.13172/2052-7810-1-2-610 · Cited by 79
Mottron, L., Belleville, S., Rouleau, G. A., & Collignon, O. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.07.012 · Cited by 85
Genome-wide copy number variation analysis in a Chinese autism spectrum disorder cohort
Guo, H., Peng, Y., Hu, Z., Li, Y., Xun, G., Ou, J., Sun, L., Xiong, Z., Liu, Y., Wang, T., et al. (2017) · Scientific Reports · doi:10.1038/srep44155 · Cited by 71
Greenwood, T. A., Lazzeroni, L. C., Calkins, M. E., Freedman, R., Green, M. F., Gur, R. E., Gur, R. C., Light, G. A., Nuechterlein, K. H., D, A. O. M., et al. (2015) · Schizophrenia Research · doi:10.1016/j.schres.2015.11.008 · Cited by 79
Rapid Method for the Isolation of Mammalian Sperm DNA
Wu, H., de Gannes, M., Luchetti, G., & Pilsner, J. R. (2015) · BioTechniques · doi:10.2144/000114280 · Cited by 75
Tsiplova, K., Zur, R. M., Marshall, C. R., Stavropoulos, D. J., Pereira, S. L., Merico, D., Young, E. J., Sung, W. W. L., Scherer, S. W., & Ungar, W. J. (2017) · Genetics in Medicine · doi:10.1038/gim.2017.47 · Cited by 74
Chen, S., Fragoza, R., Klei, L., Liu, Y., Wang, J., Roeder, K., Devlin, B., & Yu, H. (2018) · Nature Genetics · doi:10.1038/s41588-018-0130-z · Cited by 75
Self-citationThongkorn, S., Kanlayaprasit, S., Jindatip, D., Tencomnao, T., Hu, V. W., & Sarachana, T. (2019) · Scientific Reports · doi:10.1038/s41598-019-39386-w · Cited by 66
Goodwin, L. R., & Picketts, D. J. (2017) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2017.10.008 · Cited by 76
Nava, C., Keren, B., Mignot, C., Rastetter, A., Chantot‐Bastaraud, S., Faudet, A., Fonteneau, E., Amiet, C., Laurent‐Levinson, C., Jacquette, A., et al. (2013) · European Journal of Human Genetics · doi:10.1038/ejhg.2013.88 · Cited by 75
Martin, E. A., Muralidhar, S., Wang, Z., Cervantes, D. C., Basu, R., Taylor, M. R., Hunter, J., Cutforth, T., Wilke, S. A., Ghosh, A., et al. (2015) · eLife · doi:10.7554/elife.09395 · Cited by 73
Cappi, C., Brentani, H., Lima, L., Sanders, S. J., Zai, G., Diniz, B. J., Reis, V. N. S., Hounie, A. G., Conceição do Rosário, M., Mariani, D., et al. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.30 · Cited by 71
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Talkowski, M. E., Minikel, E. V., & Gusella, J. F. (2014) · Harvard Review of Psychiatry · doi:10.1097/hrp.0000000000000002 · Cited by 72
AKAPs integrate genetic findings for autism spectrum disorders
Poelmans, G., Franke, B., Pauls, D. L., Glennon, J. C., & Buitelaar, J. K. (2013) · Translational Psychiatry · doi:10.1038/tp.2013.48 · Cited by 76
Szczurkowska, J., Pischedda, F., Pinto, B., Managò, F., Haas, C. A., Summa, M., Bertorelli, R., Papaleo, F., Schäfer, M. K. E., Piccoli, G., et al. (2018) · Brain · doi:10.1093/brain/awy190 · Cited by 81
Mutations in ASH1L confer susceptibility to Tourette syndrome
Liu, S., Tian, M., He, F., Li, J., Xie, H. B., Liu, W., Zhang, Y., Zhang, R., Yi, M., Che, F., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0560-8 · Cited by 73
Biomarkers for Psychiatric Disorders: Where Are We Standing?
Martins‐de‐Souza, D. (2013) · Disease Markers · doi:10.1155/2013/321071 · Cited by 78
Steinberg, J., & Webber, C. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.09.013 · Cited by 71
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Li, B., Chen, W., Zhan, X., Busonero, F., Sanna, S., Sidore, C., Cucca, F., Kang, H. M., & Abecasis, G. R. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002944 · Cited by 73
Katrancha, S. M., Wu, Y., Zhu, M., Eipper, B. A., Koleske, A. J., & Mains, R. E. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx355 · Cited by 68
Self-citationRare inherited variation in autism: Beginning to see the forest and a few trees
Stein, J. L., Parikshak, N. N., & Geschwind, D. H. (2013) · Neuron · doi:10.1016/j.neuron.2013.01.010 · Cited by 68
Xia, F., Bainbridge, M. N., Tan, T. Y., Wangler, M. F., Scheuerle, A. E., Zackai, E. H., Harr, M. H., Sutton, V. R., Nalam, R. L., Zhu, W., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.04.006 · Cited by 71
Self-citationVoineagu, I., & Eapen, V. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00738 · Cited by 74
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López, A. J., & Wood, M. A. (2015) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2015.00100 · Cited by 74
Advances in Dyslexia Genetics—New Insights Into the Role of Brain Asymmetries
Paracchini, S., Diaz, R., & Stein, J. F. (2016) · Advances in genetics · doi:10.1016/bs.adgen.2016.08.003 · Cited by 72
iTRAQ‐Based Proteomic Analysis Reveals Protein Profile in Plasma from Children with Autism
Shen, L., Zhang, K., Feng, C., Chen, Y., Li, S., Iqbal, J., Liao, L., Zhao, Y., & Zhai, J. (2017) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201700085 · Cited by 70
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Kikkawa, T., Casingal, C. R., Chun, S. H., Shinohara, H. M., Hiraoka, K., & Osumi, N. (2018) · Brain Research · doi:10.1016/j.brainres.2018.02.041 · Cited by 67
Murtaza, N., Cheng, A. A., Brown, C. O., Meka, D. P., Hong, S., Uy, J. A., El-Hajjar, J., Pipko, N., Unda, B. K., Schwanke, B., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111678 · Cited by 70
Yin, J., & Schaaf, C. P. (2016) · Prenatal Diagnosis · doi:10.1002/pd.4942 · Cited by 78
Longoni, M., High, F. A., Qi, H., Joy, M. P., Hila, R., Coletti, C. M., Wynn, J., Loscertales, M., Shan, L., Bult, C. J., et al. (2017) · Human Genetics · doi:10.1007/s00439-017-1774-y · Cited by 67
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Hakanen, J., Ruiz-Reig, N., & Tissir, F. (2019) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2019.00244 · Cited by 69
Middleton, S. J., Kneller Emily, M., Chen, S., Ogiwara, I., Montal, M., Yamakawa, K., & McHugh, T. J. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0163-8 · Cited by 70
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Lombardo, M. V., Bonnie Auyeung, B., Pramparo, T., Quartier, A., Courraud, J., Holt, R., Waldman, J., Ruigrok, A. N. V., Mooney, N., Bethlehem, R. A. I., et al. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0198-y · Cited by 67
Gowrishankar, R., Hahn, M. K., & Blakely, R. (2013) · Neurochemistry International · doi:10.1016/j.neuint.2013.10.016 · Cited by 66
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Lipson, M., Loh, P., Sankararaman, S., Patterson, N. J., Berger, B., & Reich, D. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005550 · Cited by 65
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Dölen, G. (2015) · Journal of Neuroendocrinology · doi:10.1111/jne.12284 · Cited by 65
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Duda, M., Zhang, H., Li, H., Wall, D. P., Burmeister, M., & Guan, Y. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0098-6 · Cited by 65
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Lamar, K., & Carvill, G. L. (2018) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2018.00208 · Cited by 69
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Hoehe, M. R., & Morris-Rosendahl, D. J. (2018) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2018.20.3/mhoehe · Cited by 69
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Kasippillai, T., MacArthur, D. G., Kirby, A. W., Thomas, B., Lambalk, C. B., Daly, M. J., & Welt, C. K. (2013) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2013-1102 · Cited by 66
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Menashe, I., Grange, P., Larsen, E. C., Banerjee‐Basu, S., & Mitra, P. P. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003128 · Cited by 68
Tordjman, S., Cohen, D., Anderson, G. M., Botbol, M., Canitano, R., Coulon, N., & Roubertoux, P. L. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.01.014 · Cited by 71
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Liu, A., Zhou, W., Qu, L., He, F., Wang, H., Wang, Y., Cai, C., Li, X., Zhou, W., & Wang, M. (2019) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2019.00007 · Cited by 64
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Kanduri, C., Kantojärvi, K., Salo, P., Vanhala, R., Buck, G., Blancher, C., Lähdesmäki, H. J., & Järvelä, I. E. (2015) · Autism Research · doi:10.1002/aur.1502 · Cited by 71
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Wenderski, W., Wang, L., Krokhotin, A., Walsh, J. J., Li, H., Shoji, H., Ghosh, S. G., George, R. D., Miller, E. L., Elias, L., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1908238117 · Cited by 60
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Ye, Y., Cho, M. T., Retterer, K., Alexander, N., Ben‐Omran, T., Al‐Mureikhi, M., Cristian, I., Wheeler, P. G., Crain, C., Zand, D. J., et al. (2015) · Molecular Case Studies · doi:10.1101/mcs.a000455 · Cited by 65
Emeny, R. T., Baumert, J., Zannas, A. S., Kunze, S., Wahl, S., Iurato, S., Arloth, J., Erhardt, A., Balsevich, G., Schmidt, M. V., et al. (2017) · Neuropsychopharmacology · doi:10.1038/npp.2017.102 · Cited by 66
Association Between Assisted Reproductive Technology Conception and Autism in California, 1997–2007
Fountain, C., Zhang, Y., Kissin, D. M., Schieve, L. A., Jamieson, D. J., Rice, C. E., & Bearman, P. (2015) · American Journal of Public Health · doi:10.2105/ajph.2014.302383 · Cited by 68
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Lund, C., Brodtkorb, E., Øye, A.-M., Røsby, O., & Selmer, K. K. (2014) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2014.02.005 · Cited by 64
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Pischedda, F., & Piccoli, G. (2016) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2015.00089 · Cited by 64
Missense variants in the chromatin remodeler CHD1 are associated with neurodevelopmental disability
Pilarowski, G. O. W., Vernon, H. J., Applegate, C. D., Boukas, L., Cho, M. T., Gurnett, C. A., Benke, P. J., Beaver, E. M., Heeley, J. M., Medne, L., et al. (2017) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2017-104759 · Cited by 67
De novo Mutations (DNMs) in Autism Spectrum Disorder (ASD): Pathway and Network Analysis
Alonso-González, A., Rodriguez‐Fontenla, C., & Carracedo, Á. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00406 · Cited by 73
Neurological Diseases With Autism Spectrum Disorder: Role of ASD Risk Genes
Xiong, J., Chen, S., Pang, N., Deng, X., Yang, L., He, F. P., Wu, L., Chen, C., Yin, F., & Peng, J. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00349 · Cited by 62
Hadley, D., Wu, Z.-L., Kao, C., Kini, A., Mohamed-Hadley, A. A., Thomas, K., Vazquez, L., Qiu, H., Mentch, F. D., Pellegrino, R., et al. (2014) · Nature Communications · doi:10.1038/ncomms5074 · Cited by 64
Self-citationSpeech and Language: Translating the Genome
Deriziotis, P., & Fisher, S. E. (2017) · Trends in Genetics · doi:10.1016/j.tig.2017.07.002 · Cited by 65
How rare and common risk variation jointly affect liability for autism spectrum disorder
Klei, L., McClain, L. L., Mahjani, B., Panayidou, K., Rubeis, S. D., Grahnat, A.-C. S., Karlsson, G., Lu, Y., Melhem, N., Xu, X., et al. (2021) · Molecular Autism · doi:10.1186/s13229-021-00466-2 · Cited by 65
Self-citationStrom, S. P., Lozano, R., Lee, H., Dorrani, N., Mann, J., O'Lague, P., MANS, N. Z., Deignan, J. L., Vilain, E. J. N., Nelson, S. F., et al. (2014) · BMC Medical Genetics · doi:10.1186/1471-2350-15-49 · Cited by 65
Griswold, A. J., Dueker, N., Booven, D. V., Rantus, J. A., Jaworski, J. M., Slifer, S. H., Schmidt, M. A., Hulme, W. F., Konidari, I., Whitehead, P. L., et al. (2015) · Molecular Autism · doi:10.1186/s13229-015-0034-z · Cited by 66
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Mosca‐Boidron, A., Gueneau, L., Huguet, G., Goldenberg, A., Henry, C., Gigot, N., Pallesi‐Pocachard, E., Falace, A., Duplomb, L., Thévenon, J., et al. (2015) · European Journal of Human Genetics · doi:10.1038/ejhg.2015.211 · Cited by 66
Cortical interneuron dysfunction in epilepsy associated with autism spectrum disorders
Jacob, J. (2015) · Epilepsia · doi:10.1111/epi.13272 · Cited by 65
Metadata
- Authors
- Neale, B. M., Kou, Y., Liu, L., Ma’ayan, A., Samocha, K. E., Sabo, A., Lin, C.-F., Stevens, C., Wang, L.-S., Makarov, V., Polak, P., Yoon, S., Maguire, J., Crawford, E. L., Campbell, N. G., Geller, E. T., Valladares, O., Schafer, C., Liu, H., Zhao, T., Cai, G., Lihm, J., Dannenfelser, R., Jabado, O., Peralta, Z., Nagaswamy, U., Muzny, D., Reid, J. G., Newsham, I., Wu, Y., Lewis, L., Han, Y., Voight, B. F., Lim, E., Rossin, E., Kirby, A., Flannick, J., Fromer, M., Shakir, K., Fennell, T., Garimella, K., Banks, E., Poplin, R., Gabriel, S., DePristo, M., Wimbish, J. R., Boone, B. E., Levy, S. E., Betancur, C., Sunyaev, S., Boerwinkle, E., Buxbaum, J. D., Cook Jr, E. H., Devlin, B., Gibbs, R. A., Roeder, K., Schellenberg, G. D., Sutcliffe, J. S., & Daly, M. J.
- Affiliations
- Harvard University (US)
- Icahn School of Medicine at Mount Sinai (US)
- Carnegie Mellon University (US)
- Broad Institute (US)
- Baylor College of Medicine (US)
- University of Pennsylvania (US)
- Vanderbilt University (US)
- Johns Hopkins University (US)
- HudsonAlpha Institute for Biotechnology (US)
- Centre National de la Recherche Scientifique (FR)
- University of Pittsburgh (US)
- Corresponding author
- Buxbaum, Joseph D.
- Roeder, Kathryn
- Daly, Mark J.
- ORCID
- Neale, Benjamin M.
- Liu, Li
- Ma’ayan, Avi
- Samocha, Kaitlin E.
- Sabo, Aniko
- Lin, Chiao-Feng
- Stevens, Christine
- Makarov, Vladimir
- Polak, Paz
- Geller, Evan T.
- Valladares, Otto
- Liu, Han
- Zhao, Tuo
- Lihm, Jayon
- Dannenfelser, Ruth
- Muzny, Donna
- Reid, Jeffrey G.
- Newsham, Irene
- Wu, Yuanqing
- Han, Yi
- Voight, Benjamin F.
- Lim, Elaine
- Rossin, Elizabeth
- Flannick, Jason
- Fromer, Menachem
- Fennell, Tim
- Garimella, Kiran
- Banks, Eric
- Gabriel, Stacey
- Levy, Shawn E.
- Betancur, Catalina
- Sunyaev, Shamil
- Boerwinkle, Eric
- Buxbaum, Joseph D.
- Devlin, Bernie
- Gibbs, Richard A.
- Roeder, Kathryn
- Schellenberg, Gerard D.
- Sutcliffe, James S.
- Daly, Mark J.
- Venue
- Nature
- Published
- 2012-04-04
- Volume
- 485
- Issue
- 7397
- Pages
- 242-245
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3613847
- OpenAlex
- W2024663595
- Semantic Scholar
- 7597cd398ad2874b3c231d70f97956fb53b1be57
- Cited by
- 1,734
- References
- 27
- Citations by year
- 2026: 32 · 2025: 44 · 2024: 56 · 2023: 56 · 2022: 75 · 2021: 99 · 2020: 110 · 2019: 121 · 2018: 125 · 2017: 144 · 2016: 158 · 2015: 180 · 2014: 245 · 2013: 194 · 2012: 92
- FWCI
- 116.56
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- HAL (submittedVersion, other-oa)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Vanderbilt University (UL1 RR024975)
- National Institutes of Health (MH057881, HD015052, HD055751, RR024975)
- Vanderbilt Kennedy Center, Vanderbilt University Medical Center
- National Institute of Mental Health (R01MH061009, R01MH089025, R01MH089175, R01MH089004, R01MH089208, R01MH057881, MH057881, R01MH089482, R01MH084676)
- National Human Genome Research Institute (U54HG003067, HG003273, U54HG003273)
- National Institute of General Medical Sciences (T32GM007753, P50GM071558)
- National Center for Research Resources (RR024975, KL2RR024977, TL1RR024978, UL1RR024975)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (P30HD015052, P50HD055751)
- 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, genetic heterogeneity, locus heterogeneity, polygenic risk, parent-child trios, exome sequencing, protein-protein interaction network, SCN2A, CHD8, β-catenin signaling, p53 pathway, mutation rate, penetrance, copy number variation, genetic risk
- MeSH terms
- Autistic Disorder, DNA-Binding Proteins, Exons, Family Health, Humans, Models, Genetic, Mutation, Phenotype, Transcription Factors, Poisson Distribution, Case-Control Studies, Genetic Predisposition to Disease, Multifactorial Inheritance, Exome, Protein Interaction Maps
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