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
“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 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 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
“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]
In 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
“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]
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
“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]
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
“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]
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]
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
“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]
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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Citations
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 11,457
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
Flagged first, then by citations
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Kosmicki, J. A., Samocha, K. E., Howrigan, D. P., Sanders, S. J., Slowikowski, K., Lek, M., Karczewski, K. J., Cutler, D. J., Devlin, B., Roeder, K., et al. (2017) · Nature Genetics · doi:10.1038/ng.3789 · Cited by 340
Self-citationMcCarthy, S. E., Gillis, J., Kramer, M., Lihm, J., Yoon, S. C., Berstein, Y., Mistry, M., Pavlidis, P., Solomon, R., Ghiban, E., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2014.29 · Cited by 338
Self-citationRecurrent de novo mutations implicate novel genes underlying simplex autism risk
O'Roak, B. J., Stessman, H. A., Boyle, E. A., Witherspoon, K. T., Martin, B., Lee, C., Vives, L., Baker, C., Hiatt, J. B., Nickerson, D. A., et al. (2014) · Nature Communications · doi:10.1038/ncomms6595 · Cited by 336
The Biology of Forgetting—A Perspective
Davis, R. L., & Zhong, Y. (2017) · Neuron · doi:10.1016/j.neuron.2017.05.039 · Cited by 341
Stamberger, H., Nikanorova, M., Willemsen, M. H., Accorsi, P., Angriman, M., Baier, H., Benkel-Herrenbrueck, I., Benoît, V., Budetta, M., Caliebe, A., et al. (2016) · Neurology · doi:10.1212/wnl.0000000000002457 · Cited by 326
Cukier, H. N., Dueker, N., Slifer, S. H., Lee, J. M., Whitehead, P. L., Lalanne, E., Leyva, N., Konidari, I., Gentry, R. C., Hulme, W. F., et al. (2014) · Molecular Autism · doi:10.1186/2040-2392-5-1 · Cited by 317
Xu, M., Xu, X., Li, J., & Li, F. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00473 · Cited by 309
Truncating mutations of MAGEL2 cause Prader-Willi phenotypes and autism
Schaaf, C. P., Gonzalez‐Garay, M. L., Xia, F., Potocki, L., Gripp, K. W., Zhang, B., Peters, B. A., McElwain, M. A., Drmanac, R., Beaudet, A. L., et al. (2013) · Nature Genetics · doi:10.1038/ng.2776 · Cited by 303
Genetic Risk for Schizophrenia: Convergence on Synaptic Pathways Involved in Plasticity
Hall, J., Trent, S., Thomas, K. L., O’Donovan, M. C., & Owen, M. J. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.07.011 · Cited by 290
Histone Acetylome-wide Association Study of Autism Spectrum Disorder
Sun, W., Poschmann, J., Cruz-Herrera del Rosario, R., Parikshak, N. N., Hajan, H. S., Kumar, V., Ramasamy, R., Belgard, T. G., Elanggovan, B., Wong, C. C. Y., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.031 · Cited by 306
X-exome sequencing of 405 unresolved families identifies seven novel intellectual disability genes
Hu, H., Haas, S. A., Chelly, J., Esch, H. V., Raynaud, M., de Brouwer, A. P. M., Weinert, S., Froyen, G., Frints, S. G. M., Laumonnier, F., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.193 · Cited by 317
Predicting Polygenic Risk of Psychiatric Disorders
Martin, A. R., Daly, M. J., Robinson, E., Hyman, S. E., & Neale, B. M. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.12.015 · Cited by 301
Self-citationJeste, S., Hyde, C., DiStefano, C., Halladay, A. K., Ray, S., Porath, M., Wilson, R. B., & Thurm, A. E. (2020) · Journal of Intellectual Disability Research · doi:10.1111/jir.12776 · Cited by 297
Girirajan, S., Dennis, M. Y., Baker, C. A., Malig, M., Coe, B. P., Campbell, C. D., Mark, K. M. K., Vu, T. H., Alkan, C., Cheng, Z., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.12.016 · Cited by 310
Exome sequencing reveals new causal mutations in children with epileptic encephalopathies
Veeramah, K. R., Johnstone, L. M., Karafet, T. M., Wolf, D., Sprissler, R. S., Salogiannis, J., Barth‐Maron, A., Greenberg, M. E., Stuhlmann, T., Weinert, S., et al. (2013) · Epilepsia · doi:10.1111/epi.12201 · Cited by 294
Determinants of Mutation Rate Variation in the Human Germline
Ségurel, L., Wyman, M. J., & Przeworski, M. (2014) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-031714-125740 · Cited by 289
Methylomic trajectories across human fetal brain development
Spiers, H., Hannon, E., Schalkwyk, L. C., Smith, R., Wong, C. C. Y., O’Donovan, M. C., Bray, N. J., & Mill, J. (2015) · Genome Research · doi:10.1101/gr.180273.114 · Cited by 287
Getting to the cores of autism
Iakoucheva, L. M., Muotri, A. R., & Sebat, J. (2019) · Cell · doi:10.1016/j.cell.2019.07.037 · Cited by 260
“, 2007) and protein-altering point mutations (Iossifov et al., 2012; Neale et al., 2012; O’Roak et al., 2012; Sanders et al., 2012) contribute to risk for ASD.”
BackgroundPaternal Age at Childbearing and Offspring Psychiatric and Academic Morbidity
D’Onofrio, B. M., Rickert, M. E., Frans, E., Kuja-Halkola, R., Almqvist, C., Sjölander, A., Larsson, H., & Lichtenstein, P. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.4525 · Cited by 282
Gene × Environment Interactions in Autism Spectrum Disorders: Role of Epigenetic Mechanisms
Tordjman, S., Somogyi, E., Coulon, N., Kermarrec, S., Cohen, D., Bronsard, G., Bonnot, O., Weismann-Arcache, C., Botbol, M., Lauth, B., et al. (2014) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2014.00053 · Cited by 283
Precise temporal regulation of alternative splicing during neural development
Weyn‐Vanhentenryck, S. M., Feng, H., Ustianenko, D., Duffié, R., Yan, Q., Jacko, M., Martinez, J. C., Goodwin, M., Zhang, X., Hengst, U., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04559-0 · Cited by 272
Advanced parental age and autism risk in children: a systematic review and meta‐analysis
Wu, S., Wu, F., Ding, Y., Hou, J., Bi, J., & Zhang, Z. (2017) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.12666 · Cited by 282
Xu, X., Wells, A., O’Brien, D. R., Nehorai, A., & Dougherty, J. D. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.4488-13.2014 · Cited by 276
Fundamental Elements in Autism: From Neurogenesis and Neurite Growth to Synaptic Plasticity
Gilbert, J. P., & Man, H. (2017) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2017.00359 · Cited by 286
Genetics and epigenetics of eating disorders
Bulik, C., Yilmaz, Z., & HArdaway, A. (2015) · Advances in Genomics and Genetics · doi:10.2147/agg.s55776 · Cited by 278
The discovery of integrated gene networks for autism and related disorders
Hormozdiari, F., Penn, O., Borenstein, E., & Eichler, E. E. (2015) · Genome Research · doi:10.1101/gr.178855.114 · Cited by 249
Properties and rates of germline mutations in humans
Campbell, C. D., & Eichler, E. E. (2013) · Trends in Genetics · doi:10.1016/j.tig.2013.04.005 · Cited by 292
Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms
Walker, R. L., Ramaswami, G., Hartl, C., Mancuso, N., Gandal, M. J., de la Torre-Ubieta, L., Paşaniuc, B., Stein, J. L., & Geschwind, D. H. (2019) · Cell · doi:10.1016/j.cell.2019.09.021 · Cited by 262
Extreme Polygenicity of Complex Traits Is Explained by Negative Selection
O'Connor, L. J., Schoech, A. P., Hormozdiari, F., Gazal, S., Patterson, N., & Price, A. L. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.07.003 · Cited by 268
Lim, E. T., Raychaudhuri, S., Sanders, S. J., Stevens, C., Sabo, A., MacArthur, D. G., Neale, B. M., Kirby, A., Ruderfer, D. M., Fromer, M., et al. (2013) · Neuron · doi:10.1016/j.neuron.2012.12.029 · Cited by 266
Self-citationDNA methylation analysis of the autistic brain reveals multiple dysregulated biological pathways
Nardone, S., Sharan Sams, D., Reuveni, E., Getselter, D., Oron, O., Karpuj, M., & Elliott, E. (2014) · Translational Psychiatry · doi:10.1038/tp.2014.70 · Cited by 266
McConnell, M. J., Moran, J. V., Abyzov, A., Akbarian, S., Bae, T., Cortes-Ciriano, I., Erwin, J. A., Fasching, L., Flasch, D. A., Freed, D., et al. (2017) · Science · doi:10.1126/science.aal1641 · Cited by 262
Signalling pathways in autism spectrum disorder: mechanisms and therapeutic implications
Jiang, C.-C., Lin, L., Long, S., Ke, X., Fukunaga, K., Lu, Y., & Han, F. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01081-0 · Cited by 295
Wang, P., Mokhtari, R., Pedrosa, E., Kirschenbaum, M. A., Bayrak, C., Zheng, D., & Lachman, H. M. (2017) · Molecular Autism · doi:10.1186/s13229-017-0124-1 · Cited by 260
Sequencing studies in human genetics: design and interpretation
Goldstein, D. B., Allen, A. S., Keebler, J., Margulies, E. H., Petrou, S., Petrovski, S., & Sunyaev, S. R. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3455 · Cited by 262
Self-citationThe Emerging Picture of Autism Spectrum Disorder: Genetics and Pathology
Chen, J. A., Peñagarikano, O., Belgard, T. G., Swarup, V., & Geschwind, D. H. (2015) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-012414-040405 · Cited by 254
Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons
Griesi-Oliveira, K., Acab, A., Gupta, A. R., Sunaga, D. Y., Chailangkarn, T., Nicol, X., Nunez, Y., Walker, M. F., Murdoch, J. D., Sanders, S. J., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.141 · Cited by 236
The BAF complex in development and disease
Alfert, A., Moreno, N., & Kerl, K. (2019) · Epigenetics & Chromatin · doi:10.1186/s13072-019-0264-y · Cited by 255
Whole-exome sequencing points to considerable genetic heterogeneity of cerebral palsy
McMichael, G., Bainbridge, M. N., Haan, E., Corbett, M. A., Gardner, A. E., Thompson, S. C., van Bon, B. W. M., van Eyk, C. L., Broadbent, J., Reynolds, C. A., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.189 · Cited by 249
Self-citationAdvancing epilepsy genetics in the genomic era
Myers, C. T., & Mefford, H. C. (2015) · Genome Medicine · doi:10.1186/s13073-015-0214-7 · Cited by 253
Chd8 mediates cortical neurogenesis via transcriptional regulation of cell cycle and Wnt signaling
Durak, O., Gao, F., Kaeser-Woo, Y. J., Rueda, R., Martorell, A. J., Nott, A., Liu, C. Y., Watson, L. A., & Tsai, L.-H. (2016) · Nature Neuroscience · doi:10.1038/nn.4400 · Cited by 243
Somatic mosaicism and neurodevelopmental disease
D’Gama, A. M., & Walsh, C. A. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0257-3 · Cited by 249
Persico, A. M., & Napolioni, V. (2013) · Behavioural Brain Research · doi:10.1016/j.bbr.2013.06.012 · Cited by 258
Chd8 Mutation Leads to Autistic-like Behaviors and Impaired Striatal Circuits
Platt, R. J., Zhou, Y., Slaymaker, I. M., Shetty, A. S., Weisbach, N. R., Kim, J.-A., Sharma, J., Desai, M., Sood, S., Kempton, H. R., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.03.052 · Cited by 240
Ciernia, A. V., Matheos, D. P., Barrett, R. M., Kramár, E. A., Azzawi, S., Chen, Y., Magnan, C. N., Zeller, M. D., Sylvain, A. S., Häettig, J., et al. (2013) · Nature Neuroscience · doi:10.1038/nn.3359 · Cited by 241
The road to precision psychiatry: translating genetics into disease mechanisms
Gandal, M. J., Leppa, V., Won, H., Parikshak, N. N., & Geschwind, D. H. (2016) · Nature Neuroscience · doi:10.1038/nn.4409 · Cited by 223
Clinical characteristics of children with autism spectrum disorder and co-occurring epilepsy.
Viscidi, E. W., Triche, E. W., Pescosolido, M. F., McLean, R. L., Joseph, R. M., Spence, S. J., & Morrow, E. M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067797 · Cited by 235
Genomics, convergent neuroscience and progress in understanding autism spectrum disorder
Willsey, H. R., Willsey, A. J., Wang, B., & State, M. W. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00576-7 · Cited by 239
Meredith, R. M. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.12.001 · Cited by 262
Neurodevelopmental and neuropsychiatric disorders represent an interconnected molecular system
Cristino, A. S., Williams, S. M., Hawi, Z., An, J., Bellgrove, M. A., Schwartz, C. E., Costa, L. D. F., & Claudianos, C. (2013) · Molecular Psychiatry · doi:10.1038/mp.2013.16 · Cited by 229
Genetics and epigenetics of autism spectrum disorder—current evidence in the field
Wiśniowiecka‐Kowalnik, B., & Nowakowska, B. (2019) · Journal of Applied Genetics · doi:10.1007/s13353-018-00480-w · Cited by 249
Doherty, J. L., & Owen, M. J. (2014) · Genome Medicine · doi:10.1186/gm546 · Cited by 228
Kim, Y. S., & LEVENTHAL, B. L. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.11.001 · Cited by 244
Koren, A., Polak, P. P., Nemesh, J. C., Michaelson, J. J., Sebat, J. L., Sunyaev, S. R., & McCarroll, S. A. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.10.018 · Cited by 235
Self-citationA Quantitative Framework to Evaluate Modeling of Cortical Development by Neural Stem Cells
Stein, J. L., de la Torre-Ubieta, L., Tian, Y., Parikshak, N. N., Hernández, I. A., Marchetto, M. C., Baker, D. K., Lu, D., Hinman, C. R., Lowe, J. K., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.035 · Cited by 201
The role of sex-differential biology in risk for autism spectrum disorder
Werling, D. M. (2016) · Biology of Sex Differences · doi:10.1186/s13293-016-0112-8 · Cited by 208
Paternally inherited cis-regulatory structural variants are associated with autism
Brandler, W. M., Antaki, D., Gujral, M., Kleiber, M. L., Whitney, J., Maile, M. S., Hong, O., Chapman, T. R., Tan, S., Tandon, P., et al. (2018) · Science · doi:10.1126/science.aan2261 · Cited by 209
Chromatin Remodeling BAF (SWI/SNF) Complexes in Neural Development and Disorders
Sokpor, G., Xie, Y., Rosenbusch, J., & Tuoc, T. (2017) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2017.00243 · Cited by 230
Suls, A., Jaehn, J. A., Kecskés, A., Weber, Y., Weckhuysen, S., Craiu, D. C., Siekierska, A., Djémié, T., Afrikanova, T., Gormley, P., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.09.017 · Cited by 219
Doorenweerd, N., Mahfouz, A. E., van Putten, M., Kaliyaperumal, R., Hoen, P. A. C. ’., Hendriksen, J. G. M., Aartsma-Rus, A. M., Verschuuren, J. J. G. M., Niks, E. H., Reinders, M. J. T., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-12981-5 · Cited by 235
Rare Inherited and De Novo CNVs Reveal Complex Contributions to ASD Risk in Multiplex Families
Leppä, V., Kravitz, S. N., Martin, C. L., Andrieux, J., Caignec, C. L., Martin‐Coignard, D., DyBuncio, C. T., Sanders, S., Lowe, J. K., Cantor, R. M., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.06.036 · Cited by 229
A Genotype-First Approach to Defining the Subtypes of a Complex Disease
Stessman, H. A. F., Bernier, R., & Eichler, E. E. (2014) · Cell · doi:10.1016/j.cell.2014.02.002 · Cited by 227
From obesity genetics to the future of personalized obesity therapy
Moustafa, J. S. E.-S., & Froguel, P. (2013) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2013.57 · Cited by 228
Genetics and genomics of autism spectrum disorder: embracing complexity
De Rubeis, S., & Buxbaum, J. D. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv273 · Cited by 208
Self-citationPak, C., Dankó, T., Zhang, Y., Aoto, J. N., Anderson, G. R., Maxeiner, S., Yi, F., Wernig, M., & Südhof, T. C. (2015) · Cell stem cell · doi:10.1016/j.stem.2015.07.017 · Cited by 227
Loss-of-Function Variants in Schizophrenia Risk and SETD1A as a Candidate Susceptibility Gene
Takata, A., Xu, B., Ionita-Laza, I., Roos, J. L., Gogos, J. A., & Karayiorgou, M. (2014) · Neuron · doi:10.1016/j.neuron.2014.04.043 · Cited by 204
Accurate de novo and transmitted indel detection in exome-capture data using microassembly
Narzisi, G., O'Rawe, J., Iossifov, I. H., Fang, H., Lee, Y.-H., Wang, Z., Wu, Y., Lyon, G. J., Wigler, M. H., & Schatz, M. C. (2014) · Nature Methods · doi:10.1038/nmeth.3069 · Cited by 216
Self-citationGenetics of autism spectrum disorder
Ramaswami, G., & Geschwind, D. H. (2018) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63233-3.00021-x · Cited by 233
Hamilton, P. J., Campbell, N. G., Sharma, S., Erreger, K., Herborg, F., Saunders, C., Belovich, A. N., Daly, M. J., Gibbs, R. A., Boerwinkle, E., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2013.102 · Cited by 209
Self-citationLi, J., Cai, T., Jiang, Y. W., Chen, H., He, X., Chen, C., Li, X., Shao, Q., Xia, R., Li, Z., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.40 · Cited by 212
A Discovery Resource of Rare Copy Number Variations in Individuals with Autism Spectrum Disorder
Prasad, A., Merico, D., Thiruvahindrapuram, B., Wei, J., Lionel, A. C., Sato, D., Rickaby, J., Lu, C., Szatmari, P., Roberts, W., et al. (2012) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.112.004689 · Cited by 206
iPSYCH-Broad Consortium, Satterstrom, F. K., Walters, R. K., Singh, T., Wigdor, E. M., Lescai, F., Demontis, D., Kosmicki, J. A., Grove, J., Stevens, C., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0527-8 · Cited by 209
Self-citationAutism spectrum disorder causes, mechanisms, and treatments: focus on neuronal synapses
Won, H., Mah, W., & Kim, E. (2013) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2013.00019 · Cited by 217
Collins, R. L., Brand, H., Redin, C. E., Hanscom, C., Antolik, C. W., Stone, M. R., Glessner, J., Mason, T., Pregno, G., Dorrani, N., et al. (2017) · Genome biology · doi:10.1186/s13059-017-1158-6 · Cited by 208
Exonic Mosaic Mutations Contribute Risk for Autism Spectrum Disorder
Krupp, D. R., Barnard, R. A., Duffourd, Y., Evans, S. A., Mulqueen, R. M., Bernier, R., Rivière, J.-B., Fombonne, E., & O’Roak, B. J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.07.016 · Cited by 204
A roadmap for precision medicine in the epilepsies
† (2015) · The Lancet Neurology · doi:10.1016/s1474-4422(15)00199-4 · Cited by 197
Insights into genetics, human biology and disease gleaned from family based genomic studies
Posey, J. E., O’Donnell‐Luria, A., Chong, J. X., Harel, T., Jhangiani, S. N., Coban‐Akdemir, Z., Buyske, S. G., Pehli̇van, D., Carvalho, C. M. B., Baxter, S. M., et al. (2019) · Genetics in Medicine · doi:10.1038/s41436-018-0408-7 · Cited by 202
Self-citationGrarup, N., Sandholt, C. H., Hansen, T. F., & Pedersen, O. B. (2014) · Diabetologia · doi:10.1007/s00125-014-3270-4 · Cited by 209
De Novo Coding Variants Are Strongly Associated with Tourette Disorder
Willsey, A. J., Fernandez, T. V., Yu, D., King, R. A., Dietrich, A., Xing, J., Sanders, S. J., Mandell, J. D., Huang, A. Y., Richer, P., et al. (2017) · Neuron · doi:10.1016/j.neuron.2017.04.024 · Cited by 187
Self-citationMilekic, M. H., Xin, Y., O’Donnell, A., Kumar, K. K., Bradley-Moore, M., Malaspina, D., Moore, H., Brunner, D., Ge, Y., Edwards, J., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.84 · Cited by 190
A Genetic Investigation of Sex Bias in the Prevalence of Attention-Deficit/Hyperactivity Disorder
Martin, J., Walters, R. K., Demontis, D., Mattheisen, M., Lee, S., Robinson, E., Brikell, I., Ghirardi, L., Larsson, H., Lichtenstein, P., et al. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.11.026 · Cited by 203
Self-citationCACNA1D de novo mutations in autism spectrum disorders activate Cav1.3 L-type calcium channels
Pinggera, A., Lieb, A., Benedetti, B., Lampert, M., Monteleone, S., Liedl, K. R., Tuluc, P., & Striessnig, J. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.11.020 · Cited by 180
Mutations in the β-Tubulin Gene TUBB5 Cause Microcephaly with Structural Brain Abnormalities
Breuss, M. W., Heng, J. I., Poirier, K., Tian, G., Jaglin, X. H., Qu, Z., Braun, A. D., Gstrein, T., Ngo, L., Haas, M., et al. (2012) · Cell Reports · doi:10.1016/j.celrep.2012.11.017 · Cited by 195
Shared Molecular Neuropathology Across Major Psychiatric Disorders Parallels Polygenic Overlap
Gandal, M. J., Haney, J. R., Parikshak, N., Leppä, V., Ramaswami, G., Hartl, C., Schork, A. J., Appadurai, V., Buil, A., Werge, T. M., et al. (2019) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.17103 · Cited by 212
Autism genetics: searching for specificity and convergence
Berg, J. M., & Geschwind, D. H. (2012) · Genome Biology · doi:10.1186/gb-2012-13-7-247 · Cited by 192
Tbr1 haploinsufficiency impairs amygdalar axonal projections and results in cognitive abnormality
Huang, T.-N., Chuang, H.-C., Chou, W.-H., Chen, C.-Y., Wang, H.-F., Chou, S.-J., & Hsueh, Y.-P. (2014) · Nature Neuroscience · doi:10.1038/nn.3626 · Cited by 180
Buxbaum, J. D., Daly, M. J., Devlin, B., Lehner, T., Roeder, K., & State, M. W. (2012) · Neuron · doi:10.1016/j.neuron.2012.12.008 · Cited by 194
Self-citationBehavior genetics and postgenomics
Charney, E. (2012) · Behavioral and Brain Sciences · doi:10.1017/s0140525x11002226 · Cited by 215
Urinary p-cresol in autism spectrum disorder
Persico, A. M., & Napolioni, V. (2013) · Neurotoxicology and Teratology · doi:10.1016/j.ntt.2012.09.002 · Cited by 189
Kenny, E. M., Cormican, P., Furlong, S., Heron, E. A., Kenny, G., Fahey, C., Kelleher, E., Ennis, S., Tropea, D., Anney, R., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2013.127 · Cited by 200
From Mouse to Human: Evolutionary Genomics Analysis of Human Orthologs of Essential Genes
Georgi, B., Voight, B. F., & Bućan, M. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003484 · Cited by 183
Self-citationUnifying Views of Autism Spectrum Disorders: A Consideration of Autoregulatory Feedback Loops
Mullins, C., Fishell, G., & Tsien, R. W. (2016) · Neuron · doi:10.1016/j.neuron.2016.02.017 · Cited by 167
Wöhr, M., & Scattoni, M. L. (2013) · Behavioural Brain Research · doi:10.1016/j.bbr.2013.05.047 · Cited by 189
Nordström, S. I., Magnusson, C., Lundberg, M., Ek, M., Rai, D., Svensson, A. C., Dalman, C., Karlsson, H., & Lee, B. K. (2014) · International Journal of Epidemiology · doi:10.1093/ije/dyt262 · Cited by 193
Aggarwala, V., & Voight, B. F. (2016) · Nature Genetics · doi:10.1038/ng.3511 · Cited by 189
Self-citationCarlsson, T., Molander, F., Taylor, M. J., Jonsson, U., & Bölte, S. (2020) · Development and Psychopathology · doi:10.1017/s0954579420000620 · Cited by 190
Genetic contributions to autism spectrum disorder
Havdahl, A., Niarchou, M., Starnawska, A., Uddin, M., van der Merwe, C., & Warrier, V. (2021) · Psychological Medicine · doi:10.1017/s0033291721000192 · Cited by 211
Autism traits in the RASopathies
Adviento, B., Corbin, I. L., Widjaja, F., Desachy, G., Enrique, N., Rosser, T., Risi, S., Marco, E. J., Hendren, R. L., Bearden, C. E., et al. (2014) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2013-101951 · Cited by 174
Behavioral phenotypes of genetic mouse models of autism
Kazdoba, T. M., Leach, P. T., & Crawley, J. N. (2015) · Genes Brain & Behavior · doi:10.1111/gbb.12256 · Cited by 187
NGS Technologies as a Turning Point in Rare Disease Research , Diagnosis and Treatment
Marmiesse, A. F., Gouveia, S., & Couce, M. L. (2017) · Current Medicinal Chemistry · doi:10.2174/0929867324666170718101946 · Cited by 188
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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