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Non-coding de novo mutations in chromatin interactions are implicated in autism spectrum disorder

Molecular Psychiatry volume 27, pages 4680–4694 (2022)Cite this article

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Abstract

Three-dimensional chromatin interactions regulate gene expressions. The significance of de novo mutations (DNMs) in chromatin interactions remains poorly understood for autism spectrum disorder (ASD). We generated 813 whole-genome sequences from 242 Korean simplex families to detect DNMs, and identified target genes which were putatively affected by non-coding DNMs in chromatin interactions. Non-coding DNMs in chromatin interactions were significantly involved in transcriptional dysregulations related to ASD risk. Correspondingly, target genes showed spatiotemporal expressions relevant to ASD in developing brains and enrichment in biological pathways implicated in ASD, such as histone modification. Regarding clinical features of ASD, non-coding DNMs in chromatin interactions particularly contributed to low intelligence quotient levels in ASD probands. We further validated our findings using two replication cohorts, Simons Simplex Collection (SSC) and MSSNG, and showed the consistent enrichment of non-coding DNM-disrupted chromatin interactions in ASD probands. Generating human induced pluripotent stem cells in two ASD families, we were able to demonstrate that non-coding DNMs in chromatin interactions alter the expression of target genes at the stage of early neural development. Taken together, our findings indicate that non-coding DNMs in ASD probands lead to early neurodevelopmental disruption implicated in ASD risk via chromatin interactions.

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Fig. 1: Target gene characterization using regulatory elements and chromatin interactions.
Fig. 2: Target genes recurrently affected by non-coding DNMs in chromatin interactions.
Fig. 3: Spatiotemporal expression pattern and network pathway implicated in ASD risk of non-coding DNMs in chromatin interactions.
Fig. 4: Collective impact of non-coding DNMs in chromatin interactions and deleterious coding DNMs on IQ in ASD.
Fig. 5: Transcriptional dysregulation by non-coding DNMs in chromatin interactions in hiPSC-derived pNSCs.

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Data availability

All sequencing and phenotype data are hosted by the Korean Autism Genomics Database (KAGD) and are available for approved researchers, upon reasonable request, after additional approval from IRB at https://kagd.kisti.re.kr.

References

  1. Iossifov I, O’roak BJ, Sanders SJ, Ronemus M, Krumm N, Levy D, et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature. 2014;515:216.

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Krumm N, Turner TN, Baker C, Vives L, Mohajeri K, Witherspoon K, et al. Excess of rare, inherited truncating mutations in autism. Nat Genet. 2015;47:582.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Gratten J, Visscher PM, Mowry BJ, Wray NR. Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease. Nat Genet. 2013;45:234.

    CAS  PubMed  Google Scholar 

  4. Turner TN, Hormozdiari F, Duyzend MH, McClymont SA, Hook PW, Iossifov I, et al. Genome sequencing of autism-affected families reveals disruption of putative noncoding regulatory DNA. Am J Hum Genet. 2016;98:58–74.

    CAS  PubMed  Google Scholar 

  5. Yuen RK, Merico D, Cao H, Pellecchia G, Alipanahi B, Thiruvahindrapuram B, et al. Genome-wide characteristics of de novo mutations in autism. NPJ Genom Med. 2016;1:16027.

    PubMed Central  Google Scholar 

  6. Turner TN, Coe BP, Dickel DE, Hoekzema K, Nelson BJ, Zody MC, et al. Genomic patterns of de novo mutation in simplex autism. Cell. 2017;171:710–22.e12.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. An J-Y, Lin K, Zhu L, Werling DM, Dong S, Brand H, et al. Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder. Science. 2018;362:eaat6576.

    PubMed  PubMed Central  Google Scholar 

  8. Zhou J, Park CY, Theesfeld CL, Wong AK, Yuan Y, Scheckel C, et al. Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk. Nat Genet. 2019;51:973.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Werling DM, Brand H, An J-Y, Stone MR, Zhu L, Glessner JT, et al. An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder. Nat Genet. 2018;50:727.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Jin F, Li Y, Dixon JR, Selvaraj S, Ye Z, Lee AY, et al. A high-resolution map of the three-dimensional chromatin interactome in human cells. Nature. 2013;503:290.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Rao SS, Huntley MH, Durand NC, Stamenova EK, Bochkov ID, Robinson JT, et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell. 2014;159:1665–80.

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Won H, de La Torre-Ubieta L, Stein JL, Parikshak NN, Huang J, Opland CK, et al. Chromosome conformation elucidates regulatory relationships in developing human brain. Nature. 2016;538:523.

    PubMed  PubMed Central  Google Scholar 

  13. Zheng H, Xie W. The role of 3D genome organization in development and cell differentiation. Nat Rev Mol Cell Biol. 2019:20;535–50.

  14. Imakaev M, Fudenberg G, McCord RP, Naumova N, Goloborodko A, Lajoie BR, et al. Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Nat Methods. 2012;9:999.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Lieberman-Aiden E, Van Berkum NL, Williams L, Imakaev M, Ragoczy T, Telling A, et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science. 2009;326:289–93.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Lord C, Rutter M, Le Couteur A. Autism diagnostic interview-revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord. 1994;24:659–85.

    CAS  PubMed  Google Scholar 

  17. Wechsler D. Manual for the Wechsler intelligence scale for children, revised. New York: Psychological Corporation; 1974.

  18. Roid GH, Miller LJ. Leiter International Performance Scale-Revised (Leiter-R). Wood Dale, IL: Stoelting Co. 1997.

  19. Constantino JN, Gruber CP. Social responsiveness scale (SRS). Torrance, CA: Western Psychological Services; 2012.

  20. Lord C, Rutter M. Social communication questionnaire (SCQ). Torrance, CA: WPS; 2003.

  21. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv. 2013, https://arxiv.org/abs/1303.3997?context=q-bio.

  22. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010:20:1297–303.

  23. Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. arXiv. 2012, https://arxiv.org/abs/1207.3907.

  24. Wei Q, Zhan X, Zhong X, Liu Y, Han Y, Chen W, et al. A Bayesian framework for de novo mutation calling in parents-offspring trios. Bioinformatics. 2014;31:1375–81.

    PubMed  PubMed Central  Google Scholar 

  25. Snijders Blok L, Hiatt SM, Bowling KM, Prokop JW, Engel KL, Cochran JN, et al. De novo mutations in MED13, a component of the Mediator complex, are associated with a novel neurodevelopmental disorder. Hum Genet. 2018;137:375–88.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Yang D, Jang I, Choi J, Kim M-S, Lee AJ, Kim H, et al. 3DIV: a 3D-genome interaction viewer and database. Nucleic Acids Res. 2017;46:D52–D7.

    PubMed Central  Google Scholar 

  27. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26:841–2.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Parikshak NN, Swarup V, Belgard TG, Irimia M, Ramaswami G, Gandal MJ, et al. Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature. 2016;540:423.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Liu X, Han D, Somel M, Jiang X, Hu H, Guijarro P, et al. Disruption of an evolutionarily novel synaptic expression pattern in autism. PLoS Biol. 2016;14:e1002558.

    PubMed  PubMed Central  Google Scholar 

  30. Harrow J, Frankish A, Gonzalez JM, Tapanari E, Diekhans M, Kokocinski F, et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 2012;22:1760–74.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Matys V, Fricke E, Geffers R, Gößling E, Haubrock M, Hehl R, et al. TRANSFAC®: transcriptional regulation, from patterns to profiles. Nucleic Acids Res. 2003;31:374–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Grant CE, Bailey TL, Noble WS. FIMO: scanning for occurrences of a given motif. Bioinformatics. 2011;27:1017–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Vissers MC, Jester SA, Fantone JC. Rapid purification of human peripheral blood monocytes by centrifugation through Ficoll-Hypaque and Sepracell-MN. J Immunol Methods. 1988;110:203–7.

    CAS  PubMed  Google Scholar 

  34. Li W, Sun W, Zhang Y, Wei W, Ambasudhan R, Xia P, et al. Rapid induction and long-term self-renewal of primitive neural precursors from human embryonic stem cells by small molecule inhibitors. Proceedings of the National Academy of Sciences. 2011;108:8299–8304.

  35. Ernst J, Kellis M. Chromatin-state discovery and genome annotation with ChromHMM. Nat Protoc. 2017;12:2478–92.

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Kursa MB, Rudnicki WR. Feature selection with the Boruta package. J Stat Softw. 2010;36:1–13.

    Google Scholar 

  37. Kircher M, Witten DM, Jain P, O’roak BJ, Cooper GM, Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet. 2014;46:310.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Adzhubei I, Jordan DM, Sunyaev SR. Predicting functional effect of human missense mutations using PolyPhen-2. Curr Protoc Hum Genet. 2013;76:1–7. 7.2041.

    Google Scholar 

  39. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, et al. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7:248.

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Pollard KS, Hubisz MJ, Rosenbloom KR, Siepel A. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 2010;20:110–21.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Siepel A, Bejerano G, Pedersen JS, Hinrichs AS, Hou M, Rosenbloom K, et al. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005;15:1034–50.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Ng PC, Henikoff S. SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003;31:3812–4.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Abrahams BS, Arking DE, Campbell DB, Mefford HC, Morrow EM, Weiss LA, et al. SFARI Gene 2.0: a community-driven knowledgebase for the autism spectrum disorders (ASDs). Mol Autism. 2013;4:36.

    PubMed  PubMed Central  Google Scholar 

  44. King IF, Yandava CN, Mabb AM, Hsiao JS, Huang H-S, Pearson BL, et al. Topoisomerases facilitate transcription of long genes linked to autism. Nature. 2013;501:58.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Basu SN, Kollu R, Banerjee-Basu S. AutDB: a gene reference resource for autism research. Nucleic Acids Res. 2009;37:D832–D6.

    CAS  PubMed  Google Scholar 

  46. Samocha KE, Robinson EB, Sanders SJ, Stevens C, Sabo A, McGrath LM, et al. A framework for the interpretation of de novo mutation in human disease. Nat Genet. 2014;46:944.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Ware JS, Samocha KE, Homsy J, Daly MJ. Interpreting de novo variation in human disease using denovolyzeR. Curr Protoc Hum Genet. 2015;87:1–15. 7 25

    Google Scholar 

  48. Weinhold N, Jacobsen A, Schultz N, Sander C, Lee W. Genome-wide analysis of noncoding regulatory mutations in cancer. Nat Genet. 2014;46:1160.

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H, et al. Systematic localization of common disease-associated variation in regulatory DNA. Science. 2012;337:1190–5.

  50. Kang HJ, Kawasawa YI, Cheng F, Zhu Y, Xu X, Li M, et al. Spatio-temporal transcriptome of the human brain. Nature. 2011;478:483.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Krishnan A, Zhang R, Yao V, Theesfeld CL, Wong AK, Tadych A, et al. Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder. Nat Neurosci. 2016;19:1454.

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Yuen RKC, Merico D, Bookman M, Howe JL, Thiruvahindrapuram B, Patel RV, et al. Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder. Nat Neurosci. 2017;20:602–11.

    CAS  PubMed Central  Google Scholar 

  53. Kong A, Frigge ML, Masson G, Besenbacher S, Sulem P, Magnusson G, et al. Rate of de novo mutations and the importance of father’s age to disease risk. Nature. 2012;488:471.

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Wong WS, Solomon BD, Bodian DL, Kothiyal P, Eley G, Huddleston KC, et al. New observations on maternal age effect on germline de novo mutations. Nat Commun. 2016;7:10486.

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Rahbari R, Wuster A, Lindsay SJ, Hardwick RJ, Alexandrov LB, Al Turki S, et al. Timing, rates and spectra of human germline mutation. Nat Genet. 2016;48:126.

    CAS  PubMed  Google Scholar 

  56. Goldmann JM, Wong WS, Pinelli M, Farrah T, Bodian D, Stittrich AB, et al. Parent-of-origin-specific signatures of de novo mutations. Nat Genet. 2016;48:935.

    CAS  PubMed  Google Scholar 

  57. Sanyal A, Lajoie BR, Jain G, Dekker J. The long-range interaction landscape of gene promoters. Nature. 2012;489:109.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Mifsud B, Tavares-Cadete F, Young AN, Sugar R, Schoenfelder S, Ferreira L, et al. Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C. Nat Genet. 2015;47:598.

    CAS  PubMed  Google Scholar 

  59. Willsey AJ, Sanders SJ, Li M, Dong S, Tebbenkamp AT, Muhle RA, et al. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell. 2013;155:997–1007.

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Parikshak NN, Luo R, Zhang A, Won H, Lowe JK, Chandran V, et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell. 2013;155:1008–21.

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Lemon B, Tjian R. Orchestrated response: a symphony of transcription factors for gene control. Genes Dev. 2000;14:2551–69.

    CAS  PubMed  Google Scholar 

  62. Williams SM, An JY, Edson J, Watts M, Murigneux V, Whitehouse AJ, et al. An integrative analysis of non-coding regulatory DNA variations associated with autism spectrum disorder. Mol Psychiatry. 2019;24:1707–19.

    CAS  PubMed  Google Scholar 

  63. Fulco CP, Nasser J, Jones TR, Munson G, Bergman DT, Subramanian V, et al. Activity-by-contact model of enhancer–promoter regulation from thousands of CRISPR perturbations. Nat Genet. 2019;51:1664–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  64. De Rubeis S, Buxbaum JD. Genetics and genomics of autism spectrum disorder: embracing complexity. Hum Mol Genet. 2015;24:R24–R31.

    PubMed  PubMed Central  Google Scholar 

  65. Isohanni P, Linnankivi T, Buzkova J, Lönnqvist T, Pihko H, Valanne L, et al. DARS2 mutations in mitochondrial leukoencephalopathy and multiple sclerosis. J Med Genet. 2010;47:66–70.

  66. Miyake N, Yamashita S, Kurosawa K, Miyatake S, Tsurusaki Y, Doi H, et al. A novel homozygous mutation of DARS2 may cause a severe LBSL variant. Clin Genet. 2011;80:293–6.

    CAS  PubMed  Google Scholar 

  67. Rooryck C, Diaz-Font A, Osborn DP, Chabchoub E, Hernandez-Hernandez V, Shamseldin H, et al. Mutations in lectin complement pathway genes COLEC11 and MASP1 cause 3MC syndrome. Nat Genet. 2011;43:197.

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Hellman-Aharony S, Smirin-Yosef P, Halevy A, Pasmanik-Chor M, Yeheskel A, Har-Zahav A, et al. Microcephaly thin corpus callosum intellectual disability syndrome caused by mutated TAF2. Pediatr Neurol. 2013;49:411–6.e1.

    PubMed  Google Scholar 

  69. Iritani S, Torii Y, Habuchi C, Sekiguchi H, Fujishiro H, Yoshida M, et al. The neuropathological investigation of the brain in a monkey model of autism spectrum disorder with ABCA13 deletion. Int J Dev Neurosci. 2018;71:130–9.

    CAS  PubMed  Google Scholar 

  70. Poelmans G, Franke B, Pauls D, Glennon J, Buitelaar J. AKAPs integrate genetic findings for autism spectrum disorders. Transl Psychiatry. 2013;3:e270-e.

    Google Scholar 

  71. Pinggera A, Lieb A, Benedetti B, Lampert M, Monteleone S, Liedl KR, et al. CACNA1D de novo mutations in autism spectrum disorders activate Cav1. 3 L-type calcium channels. Biol Psychiatry. 2015;77:816–22.

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Zhiling Y, Fujita E, Tanabe Y, Yamagata T, Momoi T, Momoi MY. Mutations in the gene encoding CADM1 are associated with autism spectrum disorder. Biochem Biophys Res Commun. 2008;377:926–9.

    CAS  PubMed  Google Scholar 

  73. Stephenson JR, Wang X, Perfitt TL, Parrish WP, Shonesy BC, Marks CR, et al. A novel human CAMK2A mutation disrupts dendritic morphology and synaptic transmission, and causes ASD-related behaviors. J Neurosci. 2017;37:2216–33.

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Meyer R, Begemann M, Demuth S, Kraft F, Dey D, Schüler H, et al. Inherited cases of CNOT3-associated intellectual developmental disorder with speech delay, autism, and dysmorphic facies. Clin Genet. 2020;98:408–12.

    CAS  PubMed  Google Scholar 

  75. Neves-Pereira M, Müller B, Massie D, Williams J, O’Brien P, Hughes A, et al. Deregulation of EIF4E: a novel mechanism for autism. J Med Genet. 2009;46:759–65.

    CAS  PubMed  Google Scholar 

  76. Mejias R, Adamczyk A, Anggono V, Niranjan T, Thomas GM, Sharma K, et al. Gain-of-function glutamate receptor interacting protein 1 variants alter GluA2 recycling and surface distribution in patients with autism. Proc Natl Acad Sci USA. 2011;108:4920–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Puangpetch A, Suwannarat P, Chamnanphol M, Koomdee N, Ngamsamut N, Limsila P, et al. Significant association of HLA-B alleles and genotypes in Thai children with autism spectrum disorders: a case-control study. Dis Markers. 2015;2015:724935.

  78. Johansen A, Rosti RO, Musaev D, Sticca E, Harripaul R, Zaki M, et al. Mutations in MBOAT7, encoding lysophosphatidylinositol acyltransferase I, lead to intellectual disability accompanied by epilepsy and autistic features. Am J Hum Genet. 2016;99:912–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  79. Bowton E, Saunders C, Reddy IA, Campbell NG, Hamilton PJ, Henry LK, et al. SLC6A3 coding variant Ala559Val found in two autism probands alters dopamine transporter function and trafficking. Transl Psychiatry. 2014;4:e464.

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Stewart LR, Hall AL, Kang SH, Shaw CA, Beaudet AL. High frequency of known copy number abnormalities and maternal duplication 15q11-q13 in patients with combined schizophrenia and epilepsy. BMC Med Genet. 2011;12:154.

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Alinaghi S, Alehabib E, Johari AH, Vafaei F, Salehi S, Darvish H, et al. Expression analysis and genotyping of dgkz: a gwas-derived risk gene for schizophrenia. Mol Biol Rep. 2019;46:4105–11.

    CAS  PubMed  Google Scholar 

  82. Bizzari S, Hamzeh AR, Nair P, Mohamed M, Bastaki F. Characterization of an Emirati TMEM138 mutation leading to Joubert syndrome. Pediatr Int. 2017;59:113–4.

    CAS  PubMed  Google Scholar 

  83. Martin J, Cooper M, Hamshere ML, Pocklington A, Scherer SW, Kent L, et al. Biological overlap of attention-deficit/hyperactivity disorder and autism spectrum disorder: evidence from copy number variants. J Am Acad Child Adolesc Psychiatry. 2014;53:761–70.e26.

    PubMed  PubMed Central  Google Scholar 

  84. Kaplanis J, Samocha KE, Wiel L, Zhang Z, Arvai KJ, Eberhardt RY, et al. Evidence for 28 genetic disorders discovered by combining healthcare and research data. Nature. 2020;586:757–62.

    CAS  PubMed  PubMed Central  Google Scholar 

  85. Satterstrom FK, Kosmicki JA, Wang J, Breen MS, De Rubeis S, An J-Y, et al. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell. 2020;180:568–84.e23.

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Ashwin C, Chapman E, Colle L, Baron-Cohen S. Impaired recognition of negative basic emotions in autism: a test of the amygdala theory. Soc Neurosci. 2006;1:349–63.

    PubMed  Google Scholar 

  87. Sanders SJ, He X, Willsey AJ, Ercan-Sencicek AG, Samocha KE, Cicek AE, et al. Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci. Neuron. 2015;87:1215–33.

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Wang SS, Kloth AD, Badura A. The cerebellum, sensitive periods, and autism. Neuron. 2014;83:518–32.

    CAS  PubMed  PubMed Central  Google Scholar 

  89. Nicolson R, DeVito TJ, Vidal CN, Sui Y, Hayashi KM, Drost DJ, et al. Detection and mapping of hippocampal abnormalities in autism. Psychiatry Res Neuroimaging. 2006;148:11–21.

    Google Scholar 

  90. Edgar JC, Fisk CL IV, Berman JI, Chudnovskaya D, Liu S, Pandey J, et al. Auditory encoding abnormalities in children with autism spectrum disorder suggest delayed development of auditory cortex. Mol Autism. 2015;6:1–14.

    Google Scholar 

  91. Wymbs NF, Nebel MB, Ewen JB, Mostofsky SH. Altered inferior parietal functional connectivity is correlated with praxis and social skill performance in children with autism spectrum disorder. Cereb Cortex. 2021;31:2639–52.

    PubMed  Google Scholar 

  92. Sun W, Poschmann J, del Rosario RC-H, Parikshak NN, Hajan HS, Kumar V, et al. Histone acetylome-wide association study of autism spectrum disorder. Cell. 2016;167:1385–97. e11.

    CAS  PubMed  Google Scholar 

  93. Guo H, Wang T, Wu H, Long M, Coe BP, Li H, et al. Inherited and multiple de novo mutations in autism/developmental delay risk genes suggest a multifactorial model. Mol Autism. 2018;9:64.

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Zaqout S, Bessa P, Krämer N, Stoltenburg-Didinger G, Kaindl AM. CDK5RAP2 is required to maintain the germ cell pool during embryonic development. Stem Cell Rep. 2017;8:198–204.

    CAS  Google Scholar 

  95. Sukumaran SK, Stumpf M, Salamon S, Ahmad I, Bhattacharya K, Fischer S, et al. CDK5RAP2 interaction with components of the Hippo signaling pathway may play a role in primary microcephaly. Mol Genet Genom. 2017;292:365–83.

    CAS  Google Scholar 

  96. Ravindran E, Hu H, Yuzwa SA, Hernandez-Miranda LR, Kraemer N, Ninnemann O, et al. Homozygous ARHGEF2 mutation causes intellectual disability and midbrain-hindbrain malformation. PLoS Genet. 2017;13:e1006746.

    PubMed  PubMed Central  Google Scholar 

  97. Stocker AM, Chenn A. Differential expression of alpha-E-catenin and alpha-N-catenin in the developing cerebral cortex. Brain Res. 2006;1073:151–8.

    PubMed  Google Scholar 

  98. Abe K, Chisaka O, Van Roy F, Takeichi M. Stability of dendritic spines and synaptic contacts is controlled by αN-catenin. Nat Neurosci. 2004;7:357.

    CAS  PubMed  Google Scholar 

  99. Uemura M, Takeichi M. αN-catenin deficiency causes defects in axon migration and nuclear organization in restricted regions of the mouse brain. Dev Dyn. 2006;235:2559–66.

    CAS  PubMed  Google Scholar 

  100. Schaffer AE, Breuss MW, Caglayan AO, Al-Sanaa N, Al-Abdulwahed HY, Kaymakçalan H, et al. Biallelic loss of human CTNNA2, encoding αN-catenin, leads to ARP2/3 complex overactivity and disordered cortical neuronal migration. Nat Genet. 2018;50:1093.

    CAS  PubMed  PubMed Central  Google Scholar 

  101. Plasschaert RN, Bartolomei MS. Tissue-specific regulation and function of Grb10 during growth and neuronal commitment. Proc Natl Acad Sci USA. 2015;112:6841–7.

    CAS  PubMed  Google Scholar 

  102. Garfield AS, Cowley M, Smith FM, Moorwood K, Stewart-Cox JE, Gilroy K, et al. Distinct physiological and behavioural functions for parental alleles of imprinted Grb10. Nature. 2011;469:534.

    CAS  PubMed  PubMed Central  Google Scholar 

  103. Yu Y, Yoon S-O, Poulogiannis G, Yang Q, Ma XM, Villén J, et al. Phosphoproteomic analysis identifies Grb10 as an mTORC1 substrate that negatively regulates insulin signaling. Science. 2011;332:1322–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  104. Magdalon J, Sanchez-Sanchez SM, Griesi-Oliveira K, Sertie AL. Dysfunctional mTORC1 signaling: a convergent mechanism between syndromic and nonsyndromic forms of autism spectrum disorder? Int J Mol Sci. 2017;18:659.

  105. Gkogkas CG, Khoutorsky A, Ran I, Rampakakis E, Nevarko T, Weatherill DB, et al. Autism-related deficits via dysregulated eIF4E-dependent translational control. Nature. 2013;493:371.

    CAS  PubMed  Google Scholar 

  106. Mattar P, Cayouette M. Mechanisms of temporal identity regulation in mouse retinal progenitor cells. Neurogenesis. 2015;2:e1125409.

    PubMed  PubMed Central  Google Scholar 

  107. Alsiö JM, Tarchini B, Cayouette M, Livesey FJ. Ikaros promotes early-born neuronal fates in the cerebral cortex. Proc Natl Acad Sci USA. 2013;110:E716–E25.

    PubMed  PubMed Central  Google Scholar 

  108. Sahu A. Intracellular leptin-signaling pathways in hypothalamic neurons: the emerging role of phosphatidylinositol-3 kinase-phosphodiesterase-3B-cAMP pathway. Neuroendocrinology. 2011;93:201–10.

    CAS  PubMed  PubMed Central  Google Scholar 

  109. McGregor G, Harvey J. Leptin regulation of synaptic function at hippocampal TA-CA1 and SC-CA1 synapses: implications for health and disease. Neurochem Res. 2019;44:650–60.

    CAS  PubMed  Google Scholar 

  110. Hansel C. Deregulation of synaptic plasticity in autism. Neurosci Lett. 2019;688:58–61.

    CAS  PubMed  Google Scholar 

  111. Ashwood P, Kwong C, Hansen R, Hertz-Picciotto I, Croen L, Krakowiak P, et al. Brief report: plasma leptin levels are elevated in autism: association with early onset phenotype? J Autism Dev Disord. 2008;38:169–75.

    PubMed  Google Scholar 

  112. Vargas DL, Nascimbene C, Krishnan C, Zimmerman AW, Pardo CA. Neuroglial activation and neuroinflammation in the brain of patients with autism. Ann Neurol. 2005;57:67–81.

    CAS  PubMed  Google Scholar 

  113. Valleau JC, Sullivan EL. The impact of leptin on perinatal development and psychopathology. J Chem Neuroanat. 2014;61-62:221–32.

    CAS  PubMed  Google Scholar 

  114. Chatila ZK, Kim E, Berlé C, Bylykbashi E, Rompala A, Oram MK, et al. BACE1 regulates proliferation and neuronal differentiation of newborn cells in the adult hippocampus in mice. eNeuro. 2018;5:ENEURO.0067-18.2018.

  115. Thakker DR, Sankaranarayanan S, Weatherspoon MR, Harrison J, Pierdomenico M, Heisel JM, et al. Centrally delivered BACE1 inhibitor activates microglia, and reverses amyloid pathology and cognitive deficit in aged Tg2576 mice. J Neurosci. 2015;35:6931–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  116. Madore C, Leyrolle Q, Lacabanne C, Benmamar-Badel A, Joffre C, Nadjar A, et al. Neuroinflammation in autism: plausible role of maternal inflammation, dietary omega 3, and microbiota. Neural Plast. 2016;2016:3597209.

  117. Thomas MS, Davis R, Karmiloff-Smith A, Knowland VC, Charman T. The over-pruning hypothesis of autism. Dev Sci. 2016;19:284–305.

    PubMed  Google Scholar 

  118. Bindea G, Mlecnik B, Hackl H, Charoentong P, Tosolini M, Kirilovsky A, et al. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics. 2009;25:1091–3.

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This paper is dedicated to the memory of my colleague Seok Jong Yu, who died in 2019. We are grateful to all the families participating in this research, including Korean, SSC, and MSSNG cohorts.

Funding

This work was supported by grants from the Suh Kyungbae Foundation (to JHL); the National Research Foundation of Korea funded by the Korea government, Ministry of Science and ICT (2019R1A3B2066619 to JHL); Brain Research Program through National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (2017M3C7A1048089 to JKC); Original Technology Research Program for Brain Science of the NRF, funded by the Korean government, MIST (2017M3C7A1027467 to HJY; 2020R1C1C1003426 to JYA; 2021M3E5D9021878 to HJY); Research grant from Seoul National University Bundang Hospital (14–2015-011 to HJY); Institute for Basic Science (IBS) (IBS-R002-D1 to EK); Korea Institute of Science and Technology Information (K-19-L02-C07 to JL, YC, and SJY); Bio & Medical Technology Development Program of the National Research Foundation of Korea funded by the Ministry of Health and Welfare, Ministry of Science and ICT, Ministry of Trade Industry and Energy, Korea Disease Control and Prevention Agency (The National Project of Bio Big Data) (NRF-2020M3E5D7085175 to IBK).

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Author notes

  1. These authors contributed equally: Il Bin Kim, Taeyeop Lee, Junehawk Lee.

Authors and Affiliations

  1. Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea

    Il Bin Kim, Taeyeop Lee, Woo Kyeong Kim, Young Seok Ju & Jeong Ho Lee

  2. Department of Psychiatry, Hanyang University Guri Hospital, Guri, 11923, Republic of Korea

    Il Bin Kim

  3. Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea

    Taeyeop Lee & Jung Kyoon Choi

  4. Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, 05505, Republic of Korea

    Taeyeop Lee

  5. Center for Supercomputing Applications, Division of National Supercomputing, Korea Institute of Science and Technology Information, Daejeon, 34141, Republic of Korea

    Junehawk Lee, Yongseong Cho & Seok Jong Yu

  6. Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT, 06520, USA

    Jonghun Kim

  7. Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, 34141, Republic of Korea

    Suho Lee & Eunjoon Kim

  8. Industry-University Cooperation Foundation, Hanyang University, Seoul, 04763, Republic of Korea

    In Gyeong Koh

  9. Department of Integrated Biomedical and Life Science, Korea University, Seoul, 02841, Republic of Korea

    Jae Hyun Kim & Joon-Yong An

  10. BK21FOUR R&E Center for Learning Health Systems, Korea University, Seoul, 02841, Republic of Korea

    Jae Hyun Kim & Joon-Yong An

  11. School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, 02841, Republic of Korea

    Jae Hyun Kim & Joon-Yong An

  12. Department of Stem Cell Biology, School of Medicine, Konkuk University, Seoul, 05030, Republic of Korea

    Hyunseong Lee

  13. Department of Pharmacology, Eulji University, Daejeon, 13135, Republic of Korea

    Soon Ae Kim

  14. Department of Psychiatry, Kyung Hee University Hospital, Seoul, 02447, Republic of Korea

    Miae Oh

  15. School of Biotechnology and Health Sciences, Wuyi University, Jiangmen, 529020, China

    Dong Wook Han

  16. Organoid sciences, Ltd., Bundang-gu, Seongnam, 13488, Republic of Korea

    Dong Wook Han

  17. Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea

    Eunjoon Kim

  18. Department of Psychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, Republic of Korea

    Hee Jeong Yoo

  19. Department of Psychiatry, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea

    Hee Jeong Yoo

  20. Sovargen Co. Ltd., Daejeon, 34051, Republic of Korea

    Jeong Ho Lee

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  1. Il Bin Kim
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Contributions

Conceptualization, EK, JKC, HJY and JHL; study design, IBK, TL, and JL; sample collection, SAK, MO, and HJY; data generation, IBK, TL, JL, JK, SL, HL, WKK, YSJ, YC, and SJY; data processing, IBK, TL, JL, JK, and SL; annotation of functional regions, IBK, TL and JL; data analysis, IBK, TL, and JL; statistical analysis, IBK, TL, and JL; experimental validation, JK, SL, HL, and DWH; manuscript preparation, IBK, TL, JL, and JHL; revision, IBK, TL, JL, IGK, JHK, J-YA, and JHL.

Corresponding authors

Correspondence to Eunjoon Kim, Jung Kyoon Choi, Hee Jeong Yoo or Jeong Ho Lee.

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Competing interests

JHL is co-founder of SoVarGen, Inc., which seeks to develop new diagnostics and therapeutics for brain disorders. YSJ is a founder and chief executive officer of GENOME INSIGHT Inc. The remaining authors declare no competing interests.

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Kim, I.B., Lee, T., Lee, J. et al. Non-coding de novo mutations in chromatin interactions are implicated in autism spectrum disorder. Mol Psychiatry 27, 4680–4694 (2022). https://doi.org/10.1038/s41380-022-01697-2

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