CHD8 regulates neurodevelopmental pathways associated with autism spectrum disorder in neural progenitors
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Significance: Truncating mutation of chromodomain helicase DNA-binding protein 8 ( CHD8 ) represents one of the strongest known risk factors for autism spectrum disorder (ASD). We mimicked the effects of such heterozygous loss-of-function mutations in neural progenitor cells and integrated RNA sequencing with genome-wide delineation of CHD8 binding. Our results reveal that the molecular mechanism by which CHD8 alters neurodevelopmental pathways may involve both direct and indirect effects, the latter involving down-regulation following CHD8 suppression. We also find that chd8 suppression in zebrafish results in macrocephaly, consistent with observations in patients harboring loss-of-function mutations. We show that reduced expression of CHD8 impacts a variety of other functionally distinct ASD-associated genes, suggesting that the diverse functions of ASD risk factors may constitute multiple means of triggering a smaller number of final common pathways.
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Sugathan et al. identified 6,860 CHD8-binding sites in human neural progenitor cells.
“6,860 CHD8-binding sites in human neural progenitor cells using the intersection of signal-enriched regions detected by all three CHD8 antibodies used in the study (Sugathan et al., 2014).”
From Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism (2020) · cites this paper as Sugathan et al., 2014
The Results (p. 3) report 7,324 CHD8-binding sites replicated by all three antibodies, not 6,860. Materials and Methods (p. 10) confirms that 7,324 is the count of peaks detected by all three antibodies. (LLM, conf=0.92)
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Experimental — accuracy not yet measuredDysregulation of neural progenitor cell proliferation has been observed in genetically engineered mouse models involving ASD-associated genes (e.g., CHD8).
“Expansion of basal progenitor cells in rodent models 25 has been shown to regulate cerebral volume size and folding, while the dysregulation of neural progenitor cell proliferation has been observed in a genetically engineered mouse models involving ASD-associated genes (e.g., CHD8) 26 .”
From Early brain development in infants at high risk for autism spectrum disorder (2017) · cites this paper as [26]
The Results (p. 7) report increased numbers of proliferating brain cells after chd8 suppression, supporting the link between CHD8 and altered proliferation. But those experiments used zebrafish embryos, not genetically engineered mouse models; the paper's human neural progenitor experiments examined gene expression. (LLM, conf=0.88)
Experimental — accuracy not yet measuredEvidence for enrichment of ASD genes among genes dysregulated in iPSC models of CHD8 or FOXP1 was strongest for genes dysregulated in trans.
“Indeed, evidence for the enrichment of ASD genes amongi genes that are dysregulated in iPSC models of CHD8 (Sugathan et al., 2014) or FOXP1 (Araujo et al., 2015) was strongest for genes that were dysregulated in trans.”
From Getting to the cores of autism (2019) · cites this paper as Sugathan et al., 2014
Studies on CHD8 and iPS-derived ASD neurons indicate the dysregulation of proliferation and macrocephaly in ASD could be linked to the disruption of these signaling pathways and shortened G1/S transition.
“Studies on CHD8 and iPS-derived ASD neurons indicate the dysregulation of proliferation and macrocephaly in ASD could be linked to the disruption of these signaling pathways and shortened G1/S transition[54, 55, 57, 94, 183, 192, 193].”
From The ASD Living Biology: from cell proliferation to clinical phenotype (2019) · cites this paper as [192]
In human neural progenitor cells, both MIA-downregulated and MIA-upregulated genes are enriched in CHD8 targets.
“In human neural progenitor cells both MIA-downregulated (OR=1.66, P=1.58e-7) and upregulated genes (OR=2.71, P=8.29e-87) were enriched in CHD8 targets75 (Figure 2b).”
From Maternal immune activation dysregulation of the fetal brain transcriptome and relevance to the pathophysiology of autism spectrum disorder (2018) · cites this paper as [75]
Knock-down of the CHD8 ortholog results in macrocephaly in zebrafish and increased brain weight and volume in mice, phenotypes that reflect clinical observations in subjects with loss-of-function mutations in the gene.
“Knock-down of the CHD8 ortholog results in macrocephaly in zebrafish [32, 343] and increased brain weight and volume [187, 287] in mice, phenotypes that reflect clinical observations in subjects with loss-of-function mutations in the gene [32].”
From Autism spectrum disorder: neuropathology and animal models (2017) · cites this paper as [343]
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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 · see citing works
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888 · see citing works
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252 · see citing works
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386 · see citing works
Differential expression analysis for sequence count data
Anders, S., & Huber, W. (2010) · Genome Biology · doi:10.1186/gb-2010-11-10-r106 · Cited by 15,581 · see citing works
Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382 · see citing works
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577 · see citing works
The zebrafish book : a guide for the laboratory use of zebrafish (Danio rerio)
Westerfield, M. (1995) · Medical Entomology and Zoology · Cited by 6,813 · see citing works
GREAT improves functional interpretation of cis-regulatory regions
McLean, C. Y., Bristor, D., Hiller, M., Clarke, S. L., Schaar, B. T., Lowe, C. B., Wenger, A. M., & Bejerano, G. (2010) · Nature Biotechnology · doi:10.1038/nbt.1630 · Cited by 4,502 · see citing works
A census of human cancer genes
Futreal, P. A., Coin, L., Marshall, M., Down, T., Hubbard, T., Wooster, R., Rahman, N., & Stratton, M. R. (2004) · Nature Reviews Cancer · doi:10.1038/nrc1299 · Cited by 3,184 · see citing works
Discovery and saturation analysis of cancer genes across 21 tumour types
Lawrence, M. S., Stojanov, P., Mermel, C. H., Robinson, J. T., Garraway, L. A., Golub, T. R., Meyerson, M., Gabriel, S. B., Lander, E. S., & Getz, G. (2014) · Nature · doi:10.1038/nature12912 · Cited by 3,096 · see citing works
ToppGene Suite for gene list enrichment analysis and candidate gene prioritization
Chen, J., Bardes, E. E., Aronow, B. J., & Jegga, A. G. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp427 · Cited by 2,952 · see citing works
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 · cited 2× · see citing works
“These synthetic RNAs cover a 10(6) range of concentration, as well as varying in length and GC content to allow validation of dose response and the fidelity of the procedure in downstream analyses (3).”
BackgroundDe 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 · see citing works
FMRP Stalls Ribosomal Translocation on mRNAs Linked to Synaptic Function and Autism
Darnell, J. C., Van Driesche, S. J., Zhang, C., Hung, K. Y. S., Mele, A., Fraser, C. E., Stone, E. F., Chen, C., Fak, J. J., Chi, S. W., et al. (2011) · Cell · doi:10.1016/j.cell.2011.06.013 · Cited by 2,072 · see citing works
Fast and SNP-tolerant detection of complex variants and splicing in short reads
Wu, T. D., & Nacu, S. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq057 · Cited by 1,894 · see citing works
The NIH Roadmap Epigenomics Mapping Consortium
Bernstein, B. E., Stamatoyannopoulos, J. A., Costello, J. F., Ren, B., Milosavljevic, A., Meissner, A., Kellis, M., Marra, M. A., Beaudet, A. L., Ecker, J. R., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt1010-1045 · Cited by 1,892 · see citing works
Self-citationTranscriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology
Voineagu, I., Wang, X., Johnston, P., Lowe, J. K., Tian, Y., Horvath, S., Mill, J., Cantor, R. M., Blencowe, B. J., & Geschwind, D. H. (2011) · Nature · doi:10.1038/nature10110 · Cited by 1,874 · cited 1× · see citing works
“These studies have revealed coexpression modules containing multiple ASD genes and provided insights into developmental timing and regional specificity of transcriptional coexpression signatures (25, 26, 35).”
BackgroundPatterns and rates of exonic de novo mutations in autism spectrum disorders
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., et al. (2012) · Nature · doi:10.1038/nature11011 · Cited by 1,734 · see citing works
Genomic Maps and Comparative Analysis of Histone Modifications in Human and Mouse
Bernstein, B., Kamal, M., Lindblad‐Toh, K., Bekiranov, S., Bailey, D. K., Huebert, D. J., McMahon, S., Karlsson, E. K., Kulbokas, E. J., Gingeras, T., et al. (2005) · Cell · doi:10.1016/j.cell.2005.01.001 · Cited by 1,509 · see citing works
De Novo Gene Disruptions in Children on the Autistic Spectrum
Iossifov, I., Ronemus, M., Levy, D., Wang, Z., Hakker, I., Rosenbaum, J., Yamrom, B., Lee, Y.-H., Narzisi, G., Leotta, A., et al. (2012) · Neuron · doi:10.1016/j.neuron.2012.04.009 · Cited by 1,446 · see citing works
Multiplex Targeted Sequencing Identifies Recurrently Mutated Genes in Autism Spectrum Disorders
O’Roak, B. J., Vives, L., Fu, W., Egertson, J. D., Stanaway, I. B., Phelps, I. G., Carvill, G., Kumar, A., Lee, C., Ankenman, K., et al. (2012) · Science · doi:10.1126/science.1227764 · Cited by 1,240 · see citing works
Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism
Parikshak, N. N., Luo, R., Zhang, A., Won, H., Lowe, J. K., Chandran, V., Horvath, S., & Geschwind, D. H. (2013) · Cell · doi:10.1016/j.cell.2013.10.031 · Cited by 1,039 · see citing works
A human phenome-interactome network of protein complexes implicated in genetic disorders
Lage, K., Karlberg, E., Størling, Z. M., Olason, P., Pedersen, A., Rigina, O., Hinsby, A., Tümer, Z., Pociot, F., Tommerup, N., et al. (2007) · Nature Biotechnology · doi:10.1038/nbt1295 · Cited by 973 · see citing works
Willsey, A. J., Sanders, S. J., Li, M., Dong, S., Tebbenkamp, A. T., Muhle, R. A., Reilly, S. K., Lin, L., Fertuzinhos, S., Miller, J. A., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.020 · Cited by 934 · see citing works
Transcriptome analysis by strand-specific sequencing of complementary DNA
Parkhomchuk, D., Borodina, T. A., Amstislavskiy, V. S., Banaru, M., Hallen, L., Krobitsch, S., Lehrach, H. R., & Солдатов, А. В. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp596 · Cited by 934 · see citing works
SFARI Gene 2.0: a community-driven knowledgebase for the autism spectrum disorders (ASDs)
Abrahams, B. S., Arking, D. E., Campbell, D. B., Mefford, H. C., Morrow, E. M., Weiss, L. A., Menashe, I., Wadkins, T., Banerjee-Basu, S., & Packer, A. (2013) · Molecular Autism · doi:10.1186/2040-2392-4-36 · Cited by 873 · cited 2× · see citing works
“0 (19) (574 genes) and AutismKB (20) (171genes; 117 overlap with SFARI) databases, both of which have established varying levels of support for an association with ASD of each gene included (see SI Materials and Methods for details on supporting evidence for these gene lists).”
BackgroundMethodDisruptive CHD8 Mutations Define a Subtype of Autism Early in Development
Bernier, R., Golzio, C., Xiong, B., Stessman, H. A., Coe, B. P., Penn, O., Witherspoon, K., Gerdts, J., Baker, C., Vulto-van Silfhout, A. T., et al. (2014) · Cell · doi:10.1016/j.cell.2014.06.017 · Cited by 798 · see citing works
Self-citationComprehensive comparative analysis of strand-specific RNA sequencing methods
Levin, J. Z., Yassour, M., Adiconis, X., Nusbaum, C., Thompson, D. A., Friedman, N., Gnirke, A., & Regev, A. (2010) · Nature Methods · doi:10.1038/nmeth.1491 · Cited by 753 · see citing works
Identification of multiple distinct Snf2 subfamilies with conserved structural motifs
Flaus, A. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl295 · Cited by 727 · see citing works
Talkowski, M. E., Rosenfeld, J. A., Blumenthal, I., Pillalamarri, V., Chiang, C., Heilbut, A., Ernst, C., Hanscom, C., Rossin, E., Lindgren, A. M., et al. (2012) · Cell · doi:10.1016/j.cell.2012.03.028 · Cited by 577 · see citing works
Self-citationFrom neural development to cognition: unexpected roles for chromatin
Ronan, J. L., Wu, W., & Crabtree, G. R. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3413 · Cited by 544 · see citing works
CEAS: <i>cis</i>-regulatory element annotation system
Shin, H., Liu, T., Manrai, A. K., & Liu, X. S. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp479 · Cited by 461 · see citing works
Extracting Biological Meaning from Large Gene Lists with DAVID
Huang, D. W., Sherman, B. T., Zheng, X. M., Yang, J., Imamichi, T., Stephens, R. M., & Lempicki, R. A. (2009) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1311s27 · Cited by 457 · see citing works
Rossin, E. J., Lage, K., Raychaudhuri, S., Xavier, R. J., Tatar, D., Benita, Y., Constortium, I. I. B. D. G., Cotsapas, C., & Daly, M. J. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001273 · Cited by 438 · see citing works
A de novo convergence of autism genetics and molecular neuroscience
Krumm, N., O’Roak, B. J., Shendure, J., & Eichler, E. E. (2014) · Trends in Neurosciences · doi:10.1016/j.tins.2013.11.005 · Cited by 423 · see citing works
KCTD13 is a major driver of mirrored neuroanatomical phenotypes of the 16p11.2 copy number variant
Golzio, C., Willer, J., Talkowski, M. E., Oh, E. C., Taniguchi, Y., Jacquemont, S., Reymond, A., Sun, M., Sawa, A., Gusella, J. F., et al. (2012) · Nature · doi:10.1038/nature11091 · Cited by 410 · see citing works
Self-citationAyalew, M., Le-Niculescu, H., Levey, D. F., Jain, N., Changala, B., Patel, S. D., Winiger, E. A., Breier, A. F., Shekhar, A., AMDUR, R. L., et al. (2012) · Molecular Psychiatry · doi:10.1038/mp.2012.37 · Cited by 389 · see citing works
Sheridan, S. D., Theriault, K. M., Reis, S. A., Zhou, F., Madison, J. M., Daheron, L. M., Loring, J. F., & Haggarty, S. J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0026203 · Cited by 313 · see citing works
Self-citationCTCF-Dependent Chromatin Insulator Is Linked to Epigenetic Remodeling
Ishihara, K., Oshimura, M., & Nakao, M. (2006) · Molecular Cell · doi:10.1016/j.molcel.2006.08.008 · Cited by 267 · see citing works
Aurbach-Klipper, Y., Wasserman, M., Braunspiegel-Weintrob, N., Borstein, D., Peleg, S., ASSA, S., Karp, M., Benjamini, Y., Hochberg, Y., & Laron, Z. (1995) · Medical Hypotheses · doi:10.1016/0306-9877(95)90228-7 · Cited by 258 · see citing works
Talkowski, M. E., Mullegama, S. V., Rosenfeld, J. A., van Bon, B. W. M., Shen, Y., Repnikova, E. A., Gastier-Foster, J., Thrush, D. L., Kathiresan, S., Ruderfer, D. M., et al. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.09.011 · Cited by 249 · see citing works
Self-citationAutismKB: an evidence-based knowledgebase of autism genetics
Xu, L.-M., Li, J.-R., Huang, Y., Zhao, M., Tang, X., & Wei, L. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1145 · Cited by 179 · see citing works
Talkowski, M. E., Ernst, C., Heilbut, A. M., Chiang, C., Hanscom, C., Lindgren, A. M., Kirby, A. W., Liu, S., Muddukrishna, B., Ohsumi, T. K., et al. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.03.013 · Cited by 177 · see citing works
Self-citationA network module-based method for identifying cancer prognostic signatures
Wu, G., & Stein, L. D. (2012) · Genome biology · doi:10.1186/gb-2012-13-12-r112 · Cited by 159 · see citing works
Blumenthal, I., Ragavendran, A., Erdin, S., Klei, L., Sugathan, A., Guide, J. R., Manavalan, P., Zhou, J. Q., Wheeler, V. C., Levin, J. Z., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.05.004 · Cited by 145 · see citing works
Self-citationGenetic and expressional alterations of CHD genes in gastric and colorectal cancers
Kim, M. S., Chung, N. G., Kang, M. R., et al. (2011) · Histopathology · doi:10.1111/j.1365-2559.2011.03819.x · Cited by 101 · see citing works
Zahir, F., Firth, H. V., Baross, Á., Delaney, A. D., Eydoux, P., Gibson, W. T., Langlois, S., Martin, H., Willatt, L. R., Marra, M. A., et al. (2007) · Journal of Medical Genetics · doi:10.1136/jmg.2007.050823 · Cited by 98 · see citing works
Tahara, T., Yamamoto, E., Madireddi, P., Suzuki, H., Maruyama, R., Chung, W., Garriga, J., Jelı́nek, J., Yamano, H.-O., Sugai, T., et al. (2013) · Gastroenterology · doi:10.1053/j.gastro.2013.10.060 · Cited by 91 · see citing works
Potts, R. C., Zhang, P., Wurster, A. L., Precht, P., Mughal, M. R., Wood, W. H., Zhang, Y., Becker, K. G., Mattson, M. P., & Pazin, M. J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024515 · Cited by 87 · see citing works
Schwalie, P., Ward, M. C., Cain, C. E., Faure, A. J., Gilad, Y., Odom, D., & Flicek, P. (2013) · Genome Biology · doi:10.1186/gb-2013-14-12-r148 · Cited by 83 · see citing works
Chang, S., Gao, L., Zhao, L., Zhang, W., Du, Y., & Wang, J. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.04.016 · Cited by 48 · see citing works
Sawada, G., Ueo, H., Matsumura, T., Uchi, R., Ishibashi, M., Mima, K., Kurashige, J., TAKAHASHI, Y., AKIYOSHI, S., Sudo, T., et al. (2013) · Oncology Reports · doi:10.3892/or.2013.2597 · Cited by 48 · see citing works
Epigenetic regulation of neuronal fate determination: The role of CHD7
Feng, W., & Liu, H. (2013) · Cell Cycle · doi:10.4161/cc.26876 · Cited by 6 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Satterstrom, F. K., Kosmicki, J. A., Wang, J., Breen, M. S., De Rubeis, S., An, J.-Y., Peng, M., Collins, R., Grove, J., Klei, L., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.036 · Cited by 2,321 · see citing works
“, 2015); and 2) 6,860 CHD8-binding sites in human neural progenitor cells using the intersection of signal-enriched regions detected by all three CHD8 antibodies used in the study (Sugathan et al., 2014).”
BackgroundSelf-citationLord, C., Brugha, T. S., Charman, T., Cusack, J., Dumas, G., Frazier, T., Jones, E. J. H., Jones, R. M., Pickles, A., State, M. W., et al. (2020) · Nature Reviews Disease Primers · doi:10.1038/s41572-019-0138-4 · Cited by 1,859 · see citing works
Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci
Sanders, S. J., He, X., Willsey, A. J., Ercan-Sencicek, A. G., Samocha, K. E., Cicek, A. E., Murtha, M. T., Bal, V. H., Bishop, S. L., Dong, S., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.016 · Cited by 1,430 · see citing works
Self-citationEarly brain development in infants at high risk for autism spectrum disorder
The IBIS Network, Hazlett, H. C., Gu, H., Munsell, B. C., Kim, S. H., Styner, M., Wolff, J. J., Elison, J. T., Swanson, M. R., Zhu, H., et al. (2017) · Nature · doi:10.1038/nature21369 · Cited by 1,128 · see citing works
Individual brain organoids reproducibly form cell diversity of the human cerebral cortex
Velasco, S., Kedaigle, A. J., Simmons, S. K., Nash, A., Rocha, M., Quadrato, G., Paulsen, B., Nguyen, L., Adiconis, X., Regev, A., et al. (2019) · Nature · doi:10.1038/s41586-019-1289-x · Cited by 1,094 · see citing works
Advancing the understanding of autism disease mechanisms through genetics
de la Torre-Ubieta, L., Won, H., Stein, J. L., & Geschwind, D. H. (2016) · Nature Medicine · doi:10.1038/nm.4071 · Cited by 827 · see citing works
Stessman, H. A. F., Xiong, B., Coe, B. P., Wang, T., Hoekzema, K., Fenckova, M., Kvarnung, M., Gerdts, J., Trinh, S., Cosemans, N., et al. (2017) · Nature Genetics · doi:10.1038/ng.3792 · Cited by 559 · see citing works
Autism spectrum disorder: neuropathology and animal models
Varghese, M., Keshav, N., Jacot-Descombes, S., Warda, T., Wicinski, B., Dickstein, D. L., Harony-Nicolas, H., De Rubeis, S., Drapeau, E., Buxbaum, J. D., et al. (2017) · Acta Neuropathologica · doi:10.1007/s00401-017-1736-4 · Cited by 536 · see citing works
Inherited and de novo genetic risk for autism impacts shared networks
Ruzzo, E. K., Pérez-Cano, L., Jung, J.-Y., Wang, L.-K., Kashef-Haghighi, D., Hartl, C., Singh, C., Xu, J., Hoekstra, J. N., Leventhal, O., et al. (2019) · Cell · doi:10.1016/j.cell.2019.07.015 · Cited by 457 · see citing works
Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders
Sullivan, P. F., & Geschwind, D. H. (2019) · Cell · doi:10.1016/j.cell.2019.01.015 · Cited by 452 · see citing works
“Analysis of transcriptional (Cotney et al., 2015; Sugathan et al., 2014), splicing (Berto et al.”
BackgroundSystems biology and gene networks in neurodevelopmental and neurodegenerative disorders
Parikshak, N. N., Gandal, M. J., & Geschwind, D. H. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3934 · Cited by 430 · see citing works
Genetics and genomics of psychiatric disease
Geschwind, D. H., & Flint, J. (2015) · Science · doi:10.1126/science.aaa8954 · Cited by 424 · see citing works
Cotney, J., Muhle, R. A., Sanders, S. J., Liu, L., Willsey, A. J., Niu, W., Liu, W., Klei, L., Lei, J., Yin, J., et al. (2015) · Nature Communications · doi:10.1038/ncomms7404 · Cited by 350 · see citing works
CHD8 haploinsufficiency results in autistic-like phenotypes in mice
Katayama, Y., Nishiyama, M., Shoji, H., Ohkawa, Y., Kawamura, A., Sato, T., Suyama, M., Takumi, T., Miyakawa, T., & Nakayama, K. I. (2016) · Nature · doi:10.1038/nature19357 · Cited by 353 · see citing works
Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder
An, J.-Y., Lin, K., Zhu, L., Werling, D. M., Dong, S., Brand, H., Wang, H. Z., Zhao, X., Schwartz, G. B., Collins, R. L., et al. (2018) · Science · doi:10.1126/science.aat6576 · Cited by 316 · see citing works
Self-citationRedin, C., Brand, H., Collins, R. L., Kammin, T., Mitchell, E., Hodge, J. C., Hanscom, C., Pillalamarri, V., Seabra, C. M., Abbott, M.-A., et al. (2017) · Nature Genetics · doi:10.1038/ng.3720 · Cited by 334 · see citing works
Self-citationWerling, D. M., Brand, H., An, J.-Y., Stone, M. R., Zhu, L., Glessner, J. T., Collins, R. L., Dong, S., Layer, R. M., Markenscoff-Papadimitriou, E., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0107-y · Cited by 293 · see citing works
Self-citationThe ASD Living Biology: from cell proliferation to clinical phenotype
Courchesne, E., Pramparo, T., Gazestani, V. H., Lombardo, M. V., Pierce, K., & Lewis, N. E. (2019) · Molecular Psychiatry · doi:10.1038/s41380-018-0056-y · Cited by 333 · see citing works
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 · see citing works
“Indeed, evidence for the enrichment of ASD genes among genes that are dysregulated in induced pluripotent stem cell (iPSC) models of CHD8 (Sugathan et al., 2014) or FOXP1 (Araujo et al., 2015) was strongest for genes that were dysregulated in trans (i.e., their respective transcripts were differentially expressed in m…”
BackgroundInfluentialSpratt, P. W. E., Ben-Shalom, R., Keeshen, C. M., Burke, K. J., Clarkson, R. L., Sanders, S. J., & Bender, K. J. (2019) · Neuron · doi:10.1016/j.neuron.2019.05.037 · Cited by 244 · see citing works
Germline Chd8 haploinsufficiency alters brain development in mouse
Gompers, A. L., Su-Feher, L., Ellegood, J., Copping, N. A., Riyadh, M. A., Stradleigh, T. W., Pride, M. C., Schaffler, M. D., Wade, A. A., Catta-Preta, R., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4592 · Cited by 266 · see citing works
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 · see citing works
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 · see citing works
Lombardo, M. V., Moon, H. M., Su, J., Palmer, T. D., Courchesne, E., & Pramparo, T. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.15 · Cited by 201 · see citing works
SHANK2 mutations associated with autism spectrum disorder cause hyperconnectivity of human neurons
Zaslavsky, K., Zhang, W.-B., McCready, F. P., Rodrigues, D. C., Deneault, E., Loo, C., Zhao, M., Ross, P. J., El Hajjar, J., Romm, A., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0365-8 · Cited by 174 · see citing works
Sexually dimorphic behavior, neuronal activity, and gene expression in Chd8-mutant mice
Jung, H., Park, H., Choi, Y., Kang, H., Lee, E., Kweon, H., Roh, J. D., Ellegood, J., Choi, W., Kang, J., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0208-z · Cited by 157 · see citing works
Ernst, C. (2016) · Trends in Neurosciences · doi:10.1016/j.tins.2016.03.001 · Cited by 145 · see citing works
Neocortical neurogenesis and the etiology of autism spectrum disorder
Packer, A. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.03.002 · Cited by 138 · see citing works
Recurrent de novo mutations in neurodevelopmental disorders: properties and clinical implications
Wilfert, A. B., Sulovari, A., Turner, T. N., Coe, B. P., & Eichler, E. E. (2017) · Genome Medicine · doi:10.1186/s13073-017-0498-x · Cited by 144 · see citing works
Marie, C., Clavairoly, A., Frah, M., Hmidan, H., Yan, J., Zhao, C., Van Steenwinckel, J., Daveau, R., Zalc, B., Hassan, B., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1802620115 · Cited by 103 · see citing works
Pramparo, T., Lombardo, M. V., Campbell, K., Barnes, C. C., Marinero, S., Solso, S., Young, J., Mayo, M., Dale, A., Ahrens‐Barbeau, C., et al. (2015) · Molecular Systems Biology · doi:10.15252/msb.20156108 · Cited by 88 · see citing works
Gabriele, M., Lopez Tobon, A., D'Agostino, G., & Testa, G. (2018) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2017.12.013 · Cited by 103 · see citing works
Pierce, K., Courchesne, E., & Bacon, E. (2016) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2016.06.004 · Cited by 91 · see citing works
First glimpses of the neurobiology of autism spectrum disorder
Sanders, S. J. (2015) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2015.10.002 · Cited by 84 · see citing works
Cellular and Molecular Mechanisms Linking Human Cortical Development and Evolution
Libé-Philippot, B., & Vanderhaeghen, P. (2021) · Annual Review of Genetics · doi:10.1146/annurev-genet-071719-020705 · Cited by 78 · see citing works
Vogel Ciernia, A., Careaga, M., LaSalle, J. M., & Ashwood, P. (2018) · Glia · doi:10.1002/glia.23261 · Cited by 69 · see citing works
The 22q11.2 region regulates presynaptic gene-products linked to schizophrenia
Nehme, R., Pietiläinen, O., Artomov, M., Tegtmeyer, M., Valakh, V., Lehtonen, L., Bell, C., Singh, T., Trehan, A., Sherwood, J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-31436-8 · Cited by 58 · see citing works
The NuRD complex in neurodevelopment and disease: a case of sliding doors
Boulasiki, P., Tan, X. W., Spinelli, M., & Riccio, A. (2023) · Cells · doi:10.3390/cells12081179 · Cited by 22 · see citing works
Satterstrom, F. K., Kosmicki, J. A., Wang, J., Breen, M. S., De Rubeis, S., An, J.-Y., Peng, M., Collins, R., Grove, J., Klei, L., et al. (2018) · doi:10.1101/484113 · Cited by 2,323 · see citing works
“targets have been defined in neuronal tissues including human fetal cortex (90, 91), we show that 21”
BackgroundSelf-citation
- Authors
- Sugathan, A., Biagioli, M., Golzio, C., Erdin, S., Blumenthal, I., Manavalan, P., Ragavendran, A., Brand, H., Lucente, D., Miles, J., Sheridan, S. D., Stortchevoi, A., Kellis, M., Haggarty, S. J., Katsanis, N., Gusella, J. F., & Talkowski, M. E.
- Affiliations
- Massachusetts General Hospital (US)
- Molecular Neurogenetics Unit and
- Center for Human Disease Modeling and
- University of Missouri Hospital (US)
- Broad Institute (US)
- Duke University (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2014-10-07
- Volume
- 111
- Issue
- 42
- Pages
- E4468-77
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4210312
- OpenAlex
- W2057619579
- Semantic Scholar
- e8e7e984f6e42d8b5f15da5d380d19fc6a903b0b
- Cited by
- 342
- References
- 54
- Citations by year
- 2026: 25 · 2025: 19 · 2024: 26 · 2023: 23 · 2022: 30 · 2021: 29 · 2020: 47 · 2019: 33 · 2018: 33 · 2017: 34 · 2016: 19 · 2015: 23
- FWCI
- 16.60
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Iris (University of Trento) (submittedVersion)
- Funders
- National Institute of Mental Health (MH095867, MH095088, R01MH095088, R00MH095867, K99MH095867)
- National Human Genome Research Institute (R01HG004037)
- National Cancer Institute (P30CA014236)
- National Institute of General Medical Sciences (GM061354, P01GM061354)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Keywords
- CHD8, autism spectrum disorder, neural progenitor cells, brain development, transcriptional regulation, chromatin binding, gene regulatory networks, synaptogenesis, neuronal differentiation, axon guidance, chromatin modification, macrocephaly, zebrafish, truncating mutations
- MeSH terms
- Animals, Axons, Binding Sites, Child Development Disorders, Pervasive, Chromatin, DNA Helicases, DNA-Binding Proteins, Heterozygote, Humans, Mutation, Neoplasms, Neurons, Protein Binding, Risk Factors, Software, Transcription Factors, Zebrafish, Gene Expression Regulation, Neoplastic, Genome, Sequence Analysis, RNA, Gene Expression Regulation, Developmental, Gene Expression Profiling, Zebrafish Proteins, Gene Regulatory Networks, Megalencephaly, Neural Stem Cells
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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