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Cited by 453Autism Spectrum Disorder ResearchGenetics and Neurodevelopmental DisordersGenomics and Rare Diseases

Integrating de novo and inherited variants in 42,607 autism cases identifies mutations in new moderate-risk genes

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Zhou, Xueya, Feliciano, Pamela, Shu, Chang, Wang, Tianyun, Astrovskaya, Irina, Hall, Jacob B., Obiajulu, Joseph U., Wright, Jessica R. +415 more·2022·Nature Genetics
DOI 10.1038/s41588-022-01148-2PMC PMC9470534

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Abstract

To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new cases recruited online by SPARK. We identified 60 genes with exome-wide significance ( P < 2.5 × 10 −6 ), including five new risk genes ( NAV3 , ITSN1 , MARK2 , SCAF1 and HNRNPUL2 ). The association of NAV3 with autism risk is primarily driven by rare inherited loss-of-function (LoF) variants, with an estimated relative risk of 4, consistent with moderate effect. Autistic individuals with LoF variants in the four moderate-risk genes ( NAV3 , ITSN1 , SCAF1 and HNRNPUL2 ; n = 95) have less cognitive impairment than 129 autistic individuals with LoF variants in highly penetrant genes ( CHD8, SCN2A, ADNP, FOXP1 and SHANK3 ) (59% vs 88%, P = 1.9 × 10 −6 ). Power calculations suggest that much larger numbers of autism cases are needed to identify additional moderate-risk genes.

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  • A nonsense WASF3 variant, p.Glu88Ter, was identified in a patient with neurodevelopmental disorders.

    “A nonsense WASF3 variant, p.Glu88Ter, was identified in a patient with NDDs103,104,106 (Table 2h).”

    From The WAVE complex in developmental and adulthood brain disorders (2025) · cites this paper as [104]

    The Results section discusses variants in genes including MARK2, ITSN1 and NAV3, but does not identify a WASF3 variant in a patient with a neurodevelopmental disorder. Searches of our copy for WASF3 and p.Glu88Ter found no passage addressing the claimed variant. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

  • Two missense WASF2 variants, c.113G > A (p.Arg38Gln) and c.494T > C (p.Leu165Pro), were identified in patients with autism and neurodevelopmental disorders.

    “Two missense WASF2 variants, c.113G > A (p.Arg38Gln) and c.494T > C (p.Leu165Pro), were identified in patients with autism and NDDs103–105, but the functional alterations associated with brain disorders remain to be studied (Table 2g).”

    From The WAVE complex in developmental and adulthood brain disorders (2025) · cites this paper as [104]

    The Results passages describe analyses of autism and neurodevelopmental-disorder variants, but none identifies a WASF2 variant. Searches of our copy for WASF2 and the two specified missense substitutions found no passage reporting them in affected patients. (LLM, conf=0.70)

    Experimental — accuracy not yet measured

  • The recurrent WASF1 variants p.Leu455Pro and p.Leu535Pro were detected in a patient with autism and another patient with developmental delay, respectively.

    “The recurrent variants p.Leu455Pro and p.Leu535Pro were detected in a patient with autism and another patient with DD, respectively103,104.”

    From The WAVE complex in developmental and adulthood brain disorders (2025) · cites this paper as [104]

    The Results sections on the study cohort and risk genes discuss autism-associated variants, but do not identify either claimed WASF1 variant or the patients described. Searches of our copy for WASF1, p.Leu455Pro, and p.Leu535Pro found no passage establishing those variant–patient pairings; page numbers were unavailable. (LLM, conf=0.74)

    Experimental — accuracy not yet measured

  • Two missense variants in ABI1, c.584C > T (p.Thr195Ile) and c.1238A > C (p.Glu413Ala), were found in patients with myelomeningocele and autism spectrum disorder, respectively.

    “Additionally, two missense variants, c.584C > T, p.Thr195Ile, and c.1238A > C, p.Glu413Ala, in ABI1 were found in patients with myelomeningocele (spina bifida)138 and ASD104,114, respectively.”

    From The WAVE complex in developmental and adulthood brain disorders (2025) · cites this paper as [104]

    The Results section discusses autism-associated variants in other genes but does not identify either specified ABI1 missense variant. Searches of our copy for ABI1, Glu413Ala, Thr195Ile, and myelomeningocele found no passage establishing the claimed patient findings; no page numbers were available. (LLM, conf=0.73)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 58

  1. [2]Iossifov I The contribution of de novo coding mutations to autism spectrum disorder Nature 2014 515 216 221 10.1038/nature13908 25363768 PMC4313871 · DOI · Paper page
  2. [4]O’Roak BJ Recurrent de novo mutations implicate novel genes underlying simplex autism risk Nat. Commun. 2014 5 5595 10.1038/ncomms6595 25418537 PMC4249945 · DOI · Paper page
  3. [5]Yuen RKC Whole-genome sequencing of quartet families with autism spectrum disorder Nat. Med. 2015 21 185 191 10.1038/nm.3792 25621899 · DOI · Paper page
  4. [6]Yuen RKC Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder Nat. Neurosci. 2017 20 602 611 10.1038/nn.4524 28263302 PMC5501701 · DOI · Paper page
  5. [7]Feliciano P Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes npj Genomic Med 2019 4 19 10.1038/s41525-019-0093-8 PMC6707204 31452935 · DOI · Paper page
  6. [10]The Deciphering Developmental Disorders Study. Prevalence and architecture of de novo mutations in developmental disorders Nature 2017 542 433 438 10.1038/nature21062 28135719 PMC6016744 · DOI · Paper page
  7. [11]Kaplanis J Evidence for 28 genetic disorders discovered by combining healthcare and research data Nature 2020 586 757 762 10.1038/s41586-020-2832-5 33057194 PMC7116826 · DOI · Paper page
  8. [13]Nguyen HT Integrated Bayesian analysis of rare exonic variants to identify risk genes for schizophrenia and neurodevelopmental disorders Genome Med. 2017 9 114 10.1186/s13073-017-0497-y 29262854 PMC5738153 · DOI
  9. [14]Gaugler T Most genetic risk for autism resides with common variation Nat. Genet. 2014 46 881 885 10.1038/ng.3039 25038753 PMC4137411 · DOI · Paper page
  10. [16]Sandin S The heritability of autism spectrum disorder JAMA 2017 318 1182 1184 10.1001/jama.2017.12141 28973605 PMC5818813 · DOI · Paper page
  11. [18]Lek M Analysis of protein-coding genetic variation in 60,706 humans Nature 2016 536 285 291 10.1038/nature19057 27535533 PMC5018207 · DOI · Paper page
  12. [19]Krumm N Excess of rare, inherited truncating mutations in autism Nat. Genet. 2015 47 582 588 10.1038/ng.3303 25961944 PMC4449286 · DOI · Paper page
  13. [21]Ruzzo EK Inherited and de novo genetic risk for autism impacts shared networks Cell 2019 178 850 866.e26 10.1016/j.cell.2019.07.015 31398340 PMC7102900 · DOI · Paper page
  14. [22]Wilfert AB Recent ultra-rare inherited variants implicate new autism candidate risk genes Nat. Genet. 2021 53 1125 1134 10.1038/s41588-021-00899-8 34312540 PMC8459613 · DOI
  15. [23]The SPARK Consortium. SPARK: a US cohort of 50,000 families to accelerate autism research Neuron 2018 97 488 493 10.1016/j.neuron.2018.01.015 29420931 PMC7444276 · DOI
  16. [24]MacArthur DG Tyler-Smith C Loss-of-function variants in the genomes of healthy humans Hum. Mol. Genet. 2010 19 R125 R130 10.1093/hmg/ddq365 20805107 PMC2953739 · DOI
  17. [25]MacArthur DG A systematic survey of loss-of-function variants in human protein-coding genes Science 2012 335 823 828 10.1126/science.1215040 22344438 PMC3299548 · DOI · Paper page
  18. [26]Karczewski KJ The mutational constraint spectrum quantified from variation in 141,456 humans Nature 2020 581 434 443 10.1038/s41586-020-2308-7 32461654 PMC7334197 · DOI · Paper page
  19. [27]Cummings BB Transcript expression-aware annotation improves rare variant interpretation Nature 2020 581 452 458 10.1038/s41586-020-2329-2 32461655 PMC7334198 · DOI
  20. [28]Cassa CA Estimating the selective effects of heterozygous protein-truncating variants from human exome data Nat. Genet. 2017 49 806 810 10.1038/ng.3831 28369035 PMC5618255 · DOI
  21. [29]Fuller ZL Berg JJ Mostafavi H Sella G Przeworski M Measuring intolerance to mutation in human genetics Nat. Genet. 2019 51 772 776 10.1038/s41588-019-0383-1 30962618 PMC6615471 · DOI
  22. [30]An J-Y Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder Science 2018 362 aat6576 10.1126/science.aat6576 PMC6432922 30545852 · DOI · Paper page
  23. [31]Ioannidis NM REVEL: an ensemble method for predicting the pathogenicity of rare missense variants Am. J. Hum. Genet. 2016 99 877 885 10.1016/j.ajhg.2016.08.016 27666373 PMC5065685 · DOI · Paper page
  24. [32]Fromer M De novo mutations in schizophrenia implicate synaptic networks Nature 2014 506 179 184 10.1038/nature12929 24463507 PMC4237002 · DOI · Paper page
  25. [33]Parikshak NN Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism Cell 2013 155 1008 1021 10.1016/j.cell.2013.10.031 24267887 PMC3934107 · DOI · Paper page
  26. [36]Cotney J The autism-associated chromatin modifier CHD8 regulates other autism risk genes during human neurodevelopment Nat. Commun. 2015 6 6404 10.1038/ncomms7404 25752243 PMC4355952 · DOI · Paper page
  27. [37]Brueggeman L Koomar T Michaelson JJ Forecasting risk gene discovery in autism with machine learning and genome-scale data Sci. Rep. 2020 10 4569 10.1038/s41598-020-61288-5 32165711 PMC7067874 · DOI
  28. [38]Chen, S. et al. Dissecting autism genetic risk using single-cell RNA-seq data. Preprint at https://www.bioRxiv.org/content/10.1101/2020.06.15.153031v1 (2020). · DOI
  29. [39]Ewens WJ Spielman RS The transmission/disequilibrium test: history, subdivision, and admixture Am. J. Hum. Genet. 1995 57 455 464 10.1002/ajmg.1320570319 7668272 PMC1801556 · DOI
  30. [42]Wright S Evolution in Mendelian populations Genetics 1931 16 97 159 10.1093/genetics/16.2.97 17246615 PMC1201091 · DOI
  31. [43]Skene NG Grant SGN Identification of vulnerable cell types in major brain disorders using single cell transcriptomes and expression weighted cell type enrichment Front. Neurosci. 2016 10 16 10.3389/fnins.2016.00016 26858593 PMC4730103 · DOI
  32. [44]Willsey AJ Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism Cell 2013 155 997 1007 10.1016/j.cell.2013.10.020 24267886 PMC3995413 · DOI · Paper page
  33. [46]Wang S De novo sequence and copy number variants are strongly associated with Tourette disorder and implicate cell polarity in pathogenesis Cell Rep. 2018 24 3441 3454.e12 10.1016/j.celrep.2018.08.082 30257206 PMC6475626 · DOI
  34. [47]Heyne HO De novo variants in neurodevelopmental disorders with epilepsy Nat. Genet. 2018 50 1048 1053 10.1038/s41588-018-0143-7 29942082 · DOI
  35. [49]Shu C Snyder LG Shen Y Chung WK The SPARK Consortium. Imputing cognitive impairment in SPARK, a large autism cohort Autism Res. 2022 15 156 170 10.1002/aur.2622 34636158 · DOI
  36. [50]Arnheim N Calabrese P Understanding what determines the frequency and pattern of human germline mutations Nat. Rev. Genet. 2009 10 478 488 10.1038/nrg2529 19488047 PMC2744436 · DOI
  37. [51]Rees E Moskvina V Owen MJ O’Donovan MC Kirov G De novo rates and selection of schizophrenia-associated copy number variants Biol. Psychiatry 2011 70 1109 1114 10.1016/j.biopsych.2011.07.011 21855053 · DOI · Paper page
  38. [52]Szklarczyk D STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets Nucleic Acids Res. 2019 47 D607 D613 10.1093/nar/gky1131 30476243 PMC6323986 · DOI · Paper page
  39. [53]Köhler S The Human Phenotype Ontology in 2021 Nucleic Acids Res. 2021 49 D1207 D1217 10.1093/nar/gkaa1043 33264411 PMC7778952 · DOI
  40. [55]Carlson J Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans Nat. Commun. 2018 9 3753 10.1038/s41467-018-05936-5 30218074 PMC6138700 · DOI
  41. [57]Yamabhai M Intersectin, a novel adaptor protein with two Eps15 homology and five Src homology 3 domains J. Biol. Chem. 1998 273 31401 31407 10.1074/jbc.273.47.31401 9813051 · DOI
  42. [58]Wang W ITSN-1 controls vesicle recycling at the neuromuscular junction and functions in parallel with DAB-1 Traffic 2008 9 742 754 10.1111/j.1600-0854.2008.00712.x 18298590 PMC3791081 · DOI
  43. [59]Stringham EG Schmidt KL Navigating the cell: UNC-53 and the navigators, a family of cytoskeletal regulators with multiple roles in cell migration, outgrowth and trafficking Cell Adhes. Migr. 2009 3 342 346 10.4161/cam.3.4.9451 PMC2802743 19684480 · DOI
  44. [60]Karenko L Primary cutaneous T-cell lymphomas show a deletion or translocation affecting NAV3, the human UNC-53 homologue Cancer Res. 2005 65 8101 8110 10.1158/0008-5472.CAN-04-0366 16166283 · DOI
  45. [61]Sanghvi-Shah R Weber GF Intermediate filaments at the junction of mechanotransduction, migration, and development Front Cell Dev. Biol. 2017 5 81 10.3389/fcell.2017.00081 28959689 PMC5603733 · DOI
  46. [62]Martin HC Quantifying the contribution of recessive coding variation to developmental disorders Science 2018 362 1161 1164 10.1126/science.aar6731 30409806 PMC6726470 · DOI · Paper page
  47. [64]Poplin, R. et al. Scaling accurate genetic variant discovery to tens of thousands of samples. Preprint at https://www.bioRxiv.org/content/10.1101/201178v3 (2018). · DOI
  48. [65]Garrison, E. & Marth, G. Haplotype-based variant detection from short-read sequencing. Preprint at https://arXiv.org/abs/1207.3907 (2012). · arXiv
  49. [68]Lin, M. F. et al. GLnexus: joint variant calling for large cohort sequencing. Preprint at https://www.bioRxiv.org/content/10.1101/343970v1 (2018). · DOI
  50. [69]Taliun D Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program Nature 2021 590 290 299 10.1038/s41586-021-03205-y 33568819 PMC7875770 · DOI · Paper page
  51. [70]Li H Toward better understanding of artifacts in variant calling from high-coverage samples Bioinformatics 2014 30 2843 2851 10.1093/bioinformatics/btu356 24974202 PMC4271055 · DOI
  52. [72]Power RA Fecundity of patients with schizophrenia, autism, bipolar disorder, depression, anorexia nervosa, or substance abuse vs their unaffected siblings JAMA Psychiatry 2013 70 22 30 10.1001/jamapsychiatry.2013.268 23147713 · DOI · Paper page
  53. [73]Wright CF Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data Lancet 2015 385 1305 1314 10.1016/S0140-6736(14)61705-0 25529582 PMC4392068 · DOI
  54. [77]Mo A Epigenomic signatures of neuronal diversity in the mammalian brain Neuron 2015 86 1369 1384 10.1016/j.neuron.2015.05.018 26087164 PMC4499463 · DOI · Paper page
  55. [80]Eppig JT Mouse Genome Informatics (MGI) Resource: genetic, genomic, and biological knowledgebase for the laboratory mouse ILAR J. 2017 58 17 41 10.1093/ilar/ilx013 28838066 PMC5886341 · DOI
  56. [81]Cutler A Breiman L Archetypal analysis Technometrics 1994 36 338 347 10.1080/00401706.1994.10485840 · DOI
  57. [82]Thorndike RL Who belongs in the family? Psychometrika 1953 18 267 276 10.1007/BF02289263 · DOI
  58. [84]Packer JS CLAMMS: a scalable algorithm for calling common and rare copy number variants from exome sequencing data Bioinformatics 2016 32 133 135 26382196 PMC4681995

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Authors
Zhou, X., Feliciano, P., Shu, C., Wang, T., Astrovskaya, I., Hall, J. B., Obiajulu, J. U., Wright, J. R., Murali, S. C., Xu, S. X., Brueggeman, L., Thomas, T. R., Marchenko, O., Fleisch, C., Barns, S. D., Snyder, L. G., Han, B., Chang, T. S., Turner, T. N., Harvey, W. T., Nishida, A., O’Roak, B. J., Geschwind, D. H., The SPARK Consortium, Adams, A., Amatya, A., Andrus, A., Bashar, A., Berman, A., Brown, A., Camba, A., Gulsrud, A. C., Krentz, A. D., Shocklee, A. D., Esler, A., Lash, A. E., Fanta, A., Fatemi, A., Fish, A., Goler, A., Gonzalez, A., Gutierrez, A., Hardan, A., Hess, A., Hirshman, A., Holbrook, A., Ace, A. J., Griswold, A. J., Gruber, A. J., Jarratt, A., Jelinek, A., Jorgenson, A., Juarez, A. P., Kim, A., Kitaygorodsky, A., Luo, A., Rachubinski, A. L., Wainer, A. L., Daniels, A. M., Mankar, A., Mason, A., Miceli, A., Milliken, A., Morales-Lara, A., Stephens, A. N., Nguyen, A. N., Nicholson, A., Paolicelli, A. M., McKenzie, A. P., Gupta, A. R., Raven, A., Rhea, A., Simon, A., Soucy, A., Swanson, A., Sziklay, A., Tallbull, A., Tesng, A., Ward, A., Zick, A., Hilscher, B. A., Bell, B., Enright, B., Robertson, B. E., Hauf, B., Jensen, B., Lobisi, B., Vernoia, B. M., Schwind, B., VanMetre, B., Erickson, C. A., Sullivan, C. A. W., Albright, C., Anglo, C., Buescher, C., Bradley, C. C., Campo-Soria, C., Cohen, C., Colombi, C., Diggins, C., Edmonson, C., Rice, C. E., Fassler, C., Gray, C., Gunter, C., Walston, C. H., Klaiman, C., Leonczyk, C., Martin, C. L., Lord, C., Taylor, C. M., McCarthy, C., Ochoa-Lubinoff, C., Ortiz, C., Pierre, C., Rosenberg, C. R., Rigby, C., Roche, C., Shrier, C., Smith, C., Van Wade, C., White-Lehman, C., Zaro, C., Zha, C., Bentley, D., Correa, D., Sarver, D. E., Giancarla, D., Amaral, D. G., Howes, D., Istephanous, D., Coury, D. L., Li, D., Limon, D., Limpoco, D., Phillips, D., Rambeck, D., Rojas, D., Srishyla, D., Stamps, D., Montes, D. V., Cho, D., Cho, D., Fox, E. A., Bahl, E., Berry-Kravis, E., Blank, E., Bower, E., Brooks, E., Courchesne, E., Dillon, E., Doyle, E., Given, E., Grimes, E., Jones, E., Fombonne, E. J., Kryszak, E., Wodka, E. L., Lamarche, E., Lampert, E., Butter, E. M., O’Connor, E., Ocampo, E., Orrick, E., Perez, E., Ruzzo, E., Singer, E., Matthews, E. T., Pedapati, E. V., Fazal, F., Miller, F. K., Aberbach, G., Baraghoshi, G., Duhon, G., Hooks, G., Fischer, G. J., Marzano, G., Schoonover, G., Dichter, G. S., Tiede, G., Cottrell, H., Kaplan, H. E., Ghina, H., Hutter, H., Koene, H., Schneider, H. L., Lechniak, H., Li, H., Morotti, H., Qi, H., Richardson, H., Zaydens, H., Zhang, H., Zhao, H., Arriaga, I., Tso, I. F., Acampado, J., Gerdts, J. A., Beeson, J., Brown, J., Comitre, J., Cordova, J., Delaporte, J., Cubells, J. F., Harris, J. F., Gong, J., Gunderson, J., Hernandez, J., Judge, J., Jurayj, J., Law, J. K., Manoharan, J., Montezuma, J., Neely, J., Orobio, J., Pandey, J., Piven, J., Polanco, J., Polite, J., Rosewater, J., Scherr, J., Sutcliffe, J. S., McCracken, J. T., Tjernagel, J., Toroney, J., Veenstra-Vanderweele, J., Wang, J., Ahlers, K., Schweers, K. A., Baalman, K., Beard, K., Callahan, K., Coleman, K., Fitzgerald, K. D., Dent, K., Diehl, K., Gonring, K., Pawlowski, K. G., Hirst, K., Pierce, K. L., Murillo, K., Murray, K., Nowell, K., O’Brien, K., Pama, K., Real, K., Singer, K., Smith, K., Stephenson, K., Tsai, K., Abbeduto, L., Cartner, L. A., Beeson, L., Carpenter, L., Casten, L., Coppola, L., Cordiero, L., DeMarco, L., Pacheco, L. D., Corzo, L. F., Shulman, L. H., Walsh, L. K., Lesher, L., Herbert, L. M., Prock, L. M., Malloch, L., Mann, L., Grosvenor, L. P., Simon, L., Soorya, L. V., Wasserburg, L., Yeh, L., Huang-Storms, L. Y., Alessandri, M., Popp, M. A., Baer, M., Beckwith, M., Casseus, M., Coughlin, M., Currin, M., Cutri, M., Mallardi, M. D., DuBois, M., Dunlevy, M., Butler, M. E., Frayne, M., Gwynette, M. F., Ghaziuddin, M., Haley, M., Heyman, M., Hojlo, M., Jordy, M., Morrier, M. J., Kowanda, M., Koza, M., Lopez, M., McTaggart, M., Norris, M., Hale, M. N., O’Neil, M., Printen, M., Rayos, M., Sabiha, M., Sahin, M., Sarris, M., Shir, M., Siegel, M., Steele, M., Sweeney, M., Tafolla, M., Valicenti-McDermott, M., Verdi, M., Dennis, M. Y., Alvarez, N., Bardett, N., Berger, N., Calderon, N., Decius, N., Gonzalez, N., Harris, N., Lawson, N., Lillie, N., Lo, N., Long, N., Russo-Ponsaran, N. M., Madi, N., Mccoy, N., Nagpal, N., Rodriguez, N., Russell, N., Shah, N., Takahashi, N., Targalia, N., Newman, O., Ousley, O. Y., Heydemann, P., Manning, P., Carbone, P. S., Bernier, R. A., Gordon, R. A., Shaffer, R. C., Annett, R. D., Clark, R. D., Jou, R., Landa, R. J., Earl, R. K., Libove, R., Marini, R., Doan, R. N., Goin-Kochel, R. P., Rana, R., Remington, R., Shikov, R., Schultz, R. T., Aberle, S., Birdwell, S., Boland, S., Booker, S., Carpenter, S., Chintalapalli, S., Conyers, S., D’Ambrosi, S., Eldred, S., Francis, S., Ganesan, S., Hepburn, S., Horner, S., Hunter, S., Brewster, S. J., Lee, S. J., Jacob, S., Jean, S., Hyun, S., Kramer, S., Friedman, S. L., Licona, S., Littlefield, S., Kanne, S. M., Mastel, S., Mathai, S., Melnyk, S., Michaels, S., Mohiuddin, S., Palmer, S., Plate, S., Qiu, S., Randall, S., Sandhu, S., Santangelo, S., Shah, S., Skinner, S., Thompson, S., White, S., White, S., Xiao, S., Xu, S., Xu, S., Chen, T., Greene, T., Ho, T., Ibanez, T., Koomar, T., Pramparo, T., Rutter, T., Shaikh, T., Tran, T., Yu, T. W., Galbraith, V., Gazestani, V., Myers, V. J., Ranganathan, V., Singh, V., Weaver, W. C., CaI, W., Chin, W., Yang, W. S., Choi, Y. B., Warren, Z. E., Michaelson, J. J., Volfovsky, N., Eichler, E. E., Shen, Y., & Chung, W. K.
Affiliations
  • Columbia University Irving Medical Center (US)
  • Simons Foundation (US)
  • University of Washington (US)
  • Howard Hughes Medical Institute (US)
  • University of Iowa (US)
  • University of California, Los Angeles (US)
  • Washington University in St. Louis (US)
  • Oregon Health & Science University (US)
  • Rush University Medical Center (US)
  • University of Utah (US)
  • Vanderbilt University Medical Center (US)
  • Kennedy Krieger Institute (US)
  • University of Missouri (US)
  • University of Minnesota (US)
  • Yale University (US)
  • University of Michigan (US)
  • University of Miami (US)
  • Stanford Medicine (US)
  • Nationwide Children's Hospital (US)
  • Cincinnati Children's Hospital Medical Center (US)
  • University of Colorado Anschutz (US)
  • University of California San Diego (US)
  • Boston Children's Hospital (US)
  • Albert Einstein College of Medicine (US)
  • Weill Cornell Medicine (US)
  • Medical University of South Carolina (US)
  • Baylor College of Medicine (US)
  • University of California, Davis (US)
  • Children's Specialized Hospital (US)
  • University of North Carolina at Chapel Hill (US)
  • Emory University (US)
  • Autism & Developmental Medicine Institute (US)
  • University of Mississippi Medical Center (US)
  • Children's Hospital of Philadelphia (US)
  • Vanderbilt University (US)
  • Maine Medical Center Research Institute (US)
Corresponding author
Chung, Wendy K.
ORCID
Venue
Nature Genetics
Publisher
Springer Science and Business Media LLC
Published
2022-08-18
Volume
54
Issue
9
Pages
1305-1319
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
DOI
10.1038/s41588-022-01148-2
PMC
PMC9470534
OpenAlex
W4293068416
Cited by
453
References
29
Citations by year
2026: 130 · 2025: 122 · 2024: 130 · 2023: 62 · 2022: 9
FWCI
40.94
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Genetics (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Digital Commons@Becker (Washington University School of Medicine) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
  • Howard Hughes Medical Institute
  • Simons Foundation Autism Research Initiative
  • National Institutes of Health (1k99mh117165-01)
  • National Institute of Mental Health (R01MH105527, R01MH122491, K99 MH117165, R01MH101221)
  • National Institute on Deafness and Other Communication Disorders (R01DC014489)
  • National Institute of General Medical Sciences (T32GM008629, R01GM120609, T32GM139776)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (P50HD103525, P50HD103537, P50HD103556)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
Keywords
autism spectrum disorder, de novo mutations, inherited mutations, rare coding variants, loss-of-function mutations, NAV3, ITSN1, MARK2, genetic risk, cognitive impairment, penetrance, exome-wide association
MeSH terms
Autism Spectrum Disorder, Exome Sequencing, Autistic Disorder, Humans, Mutation, Repressor Proteins, Genetic Predisposition to Disease, Forkhead Transcription Factors, Exome

About these checks

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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