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.
Similar content being viewed by others
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Zheng H, Xie W. The role of 3D genome organization in development and cell differentiation. Nat Rev Mol Cell Biol. 2019:20;535–50.
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.
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.
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.
Wechsler D. Manual for the Wechsler intelligence scale for children, revised. New York: Psychological Corporation; 1974.
Roid GH, Miller LJ. Leiter International Performance Scale-Revised (Leiter-R). Wood Dale, IL: Stoelting Co. 1997.
Constantino JN, Gruber CP. Social responsiveness scale (SRS). Torrance, CA: Western Psychological Services; 2012.
Lord C, Rutter M. Social communication questionnaire (SCQ). Torrance, CA: WPS; 2003.
Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv. 2013, https://arxiv.org/abs/1303.3997?context=q-bio.
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.
Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. arXiv. 2012, https://arxiv.org/abs/1207.3907.
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.
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.
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.
Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26:841–2.
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.
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.
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.
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.
Grant CE, Bailey TL, Noble WS. FIMO: scanning for occurrences of a given motif. Bioinformatics. 2011;27:1017–8.
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.
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.
Ernst J, Kellis M. Chromatin-state discovery and genome annotation with ChromHMM. Nat Protoc. 2017;12:2478–92.
Kursa MB, Rudnicki WR. Feature selection with the Boruta package. J Stat Softw. 2010;36:1–13.
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.
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.
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.
Pollard KS, Hubisz MJ, Rosenbloom KR, Siepel A. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 2010;20:110–21.
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.
Ng PC, Henikoff S. SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003;31:3812–4.
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.
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.
Basu SN, Kollu R, Banerjee-Basu S. AutDB: a gene reference resource for autism research. Nucleic Acids Res. 2009;37:D832–D6.
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.
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
Weinhold N, Jacobsen A, Schultz N, Sander C, Lee W. Genome-wide analysis of noncoding regulatory mutations in cancer. Nat Genet. 2014;46:1160.
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.
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.
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.
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.
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.
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.
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.
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.
Sanyal A, Lajoie BR, Jain G, Dekker J. The long-range interaction landscape of gene promoters. Nature. 2012;489:109.
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.
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.
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.
Lemon B, Tjian R. Orchestrated response: a symphony of transcription factors for gene control. Genes Dev. 2000;14:2551–69.
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.
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.
De Rubeis S, Buxbaum JD. Genetics and genomics of autism spectrum disorder: embracing complexity. Hum Mol Genet. 2015;24:R24–R31.
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.
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.
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.
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.
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.
Poelmans G, Franke B, Pauls D, Glennon J, Buitelaar J. AKAPs integrate genetic findings for autism spectrum disorders. Transl Psychiatry. 2013;3:e270-e.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Wang SS, Kloth AD, Badura A. The cerebellum, sensitive periods, and autism. Neuron. 2014;83:518–32.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Mattar P, Cayouette M. Mechanisms of temporal identity regulation in mouse retinal progenitor cells. Neurogenesis. 2015;2:e1125409.
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.
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.
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.
Hansel C. Deregulation of synaptic plasticity in autism. Neurosci Lett. 2019;688:58–61.
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.
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.
Valleau JC, Sullivan EL. The impact of leptin on perinatal development and psychopathology. J Chem Neuroanat. 2014;61-62:221–32.
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.
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.
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.
Thomas MS, Davis R, Karmiloff-Smith A, Knowland VC, Charman T. The over-pruning hypothesis of autism. Dev Sci. 2016;19:284–305.
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.
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).
Author information
Authors and Affiliations
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
Ethics declarations
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.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
About this article
Cite this article
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
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41380-022-01697-2
- Springer Nature Limited
This article is cited by
-
TrkB-dependent regulation of molecular signaling across septal cell types
Translational Psychiatry (2024)
-
Protocol for the development of joint attention-based subclassification of autism spectrum disorder and validation using multi-modal data
BMC Psychiatry (2023)