Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Molecular diagnosis of 405 individuals with autism spectrum disorder

Abstract

Autism spectrum disorder (ASD) is caused by combined genetic and environmental factors. Genetic heritability in ASD is estimated as 60–90%, and genetic investigations have revealed many monogenic factors. We analyzed 405 patients with ASD using family-based exome sequencing to detect disease-causing single-nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variations (CNVs) for molecular diagnoses. All candidate variants were validated by Sanger sequencing or quantitative polymerase chain reaction and were evaluated using the American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines for molecular diagnosis. We identified 55 disease-causing SNVs/indels in 53 affected individuals and 13 disease-causing CNVs in 13 affected individuals, achieving a molecular diagnosis in 66 of 405 affected individuals (16.3%). Among the 55 disease-causing SNVs/indels, 51 occurred de novo, 2 were compound heterozygous (in one patient), and 2 were X-linked hemizygous variants inherited from unaffected mothers. The molecular diagnosis rate in females was significantly higher than that in males. We analyzed affected sibling cases of 24 quads and 2 quintets, but only one pair of siblings shared an identical pathogenic variant. Notably, there was a higher molecular diagnostic rate in simplex cases than in multiplex families. Our simulation indicated that the diagnostic yield is increasing by 0.63% (range 0–2.5%) per year. Based on our simple simulation, diagnostic yield is improving over time. Thus, periodical reevaluation of ES data should be strongly encouraged in undiagnosed ASD patients.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Genetic architecture in our autism spectrum disorder (ASD) cohort.
Fig. 2: Gene ontology (GO) enrichment analysis for our autism spectrum disorder (ASD) cohort.

Similar content being viewed by others

Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to privacy or ethical restrictions but are available from the corresponding author on reasonable request.

References

  1. Maenner MJ, Shaw KA, Baio J, Washington A, Patrick M, DiRienzo M, et al. Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2016. MMWR Surveill Summ. 2020;69:1–12.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Zeidan J, Fombonne E, Scorah J, Ibrahim A, Durkin MS, Saxena S, et al. Global prevalence of autism: a systematic review update. Autism Res. 2022;15:778–90.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Bailey A, Le Couteur A, Gottesman I, Bolton P, Simonoff E, Yuzda E, et al. Autism as a strongly genetic disorder: evidence from a British twin study. Psychol Med. 1995;25:63–77.

    Article  CAS  PubMed  Google Scholar 

  4. Gaugler T, Klei L, Sanders SJ, Bodea CA, Goldberg AP, Lee AB, et al. Most genetic risk for autism resides with common variation. Nat Genet. 2014;46:881–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Ruzzo EK, Perez-Cano L, Jung JY, Wang LK, Kashef-Haghighi D, Hartl C, et al. Inherited and de novo genetic risk for autism impacts shared networks. Cell. 2019;178:850–66.e26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. 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;47:582–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. 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;515:216–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Grove J, Ripke S, Als TD, Mattheisen M, Walters RK, Won H, et al. Identification of common genetic risk variants for autism spectrum disorder. Nat Genet. 2019;51:431–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Dias CM, Walsh CA. Recent advances in understanding the genetic architecture of autism. Annu Rev Genomics Hum Genet. 2020;21:289–304.

    Article  CAS  PubMed  Google Scholar 

  12. Martinez-Granero F, Blanco-Kelly F, Sanchez-Jimeno C, Avila-Fernandez A, Arteche A, Bustamante-Aragones A, et al. Comparison of the diagnostic yield of aCGH and genome-wide sequencing across different neurodevelopmental disorders. NPJ Genom Med. 2021;6:25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Shen Y, Dies KA, Holm IA, Bridgemohan C, Sobeih MM, Caronna EB, et al. Clinical genetic testing for patients with autism spectrum disorders. Pediatrics. 2010;125:e727–35.

    Article  PubMed  Google Scholar 

  14. Tammimies K, Marshall CR, Walker S, Kaur G, Thiruvahindrapuram B, Lionel AC, et al. Molecular diagnostic yield of chromosomal microarray analysis and whole-exome sequencing in children with autism spectrum disorder. JAMA. 2015;314:895–903.

    Article  CAS  PubMed  Google Scholar 

  15. Feliciano P, Zhou X, Astrovskaya I, Turner TN, Wang T, Brueggeman L, et al. Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes. NPJ Genom Med. 2019;4:19.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Yang Y, Muzny DM, Xia F, Niu Z, Person R, Ding Y, et al. Molecular findings among patients referred for clinical whole-exome sequencing. JAMA 2014;312:1870–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Narita K, Muramatsu H, Narumi S, Nakamura Y, Okuno Y, Suzuki K, et al. Whole-exome analysis of 177 pediatric patients with undiagnosed diseases. Sci Rep. 2022;12:14589.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Lee H, Nelson SF. The frontiers of sequencing in undiagnosed neurodevelopmental diseases. Curr Opin Genet Dev. 2020;65:76–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Takata A, Miyake N, Tsurusaki Y, Fukai R, Miyatake S, Koshimizu E, et al. Integrative analyses of de novo mutations provide deeper biological insights into autism spectrum disorder. Cell Rep. 2018;22:734–47.

    Article  CAS  PubMed  Google Scholar 

  20. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–24.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Miyake N, Tsukaguchi H, Koshimizu E, Shono A, Matsunaga S, Shiina M, et al. Biallelic mutations in nuclear pore complex subunit NUP107 cause early-childhood-onset steroid-resistant nephrotic syndrome. Am J Hum Genet. 2015;97:555–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Fromer M, Moran JL, Chambert K, Banks E, Bergen SE, Ruderfer DM, et al. Discovery and statistical genotyping of copy-number variation from whole-exome sequencing depth. Am J Hum Genet. 2012;91:597–607.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Riggs ER, Andersen EF, Cherry AM, Kantarci S, Kearney H, Patel A, et al. Technical standards for the interpretation and reporting of constitutional copy-number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen). Genet Med. 2020;22:245–57.

    Article  PubMed  Google Scholar 

  24. Young MD, Wakefield MJ, Smyth GK, Oshlack A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 2010;11:R14.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Okuzono S, Fukai R, Noda M, Miyake N, Lee S, Kaku N, et al. An acute encephalopathy with reduced diffusion in BRAF-associated cardio-facio-cutaneous syndrome. Brain Dev. 2019;41:378–81.

    Article  PubMed  Google Scholar 

  27. Sarkozy A, Carta C, Moretti S, Zampino G, Digilio MC, Pantaleoni F, et al. Germline BRAF mutations in Noonan, LEOPARD, and cardiofaciocutaneous syndromes: molecular diversity and associated phenotypic spectrum. Hum Mutat. 2009;30:695–702.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Jaganathan K, Kyriazopoulou Panagiotopoulou S, McRae JF, Darbandi SF, Knowles D, Li YI, et al. Predicting splicing from primary sequence with deep learning. Cell 2019;176:535–48.e24.

    Article  CAS  PubMed  Google Scholar 

  29. Niranjan TS, Skinner C, May M, Turner T, Rose R, Stevenson R, et al. Affected kindred analysis of human X chromosome exomes to identify novel X-linked intellectual disability genes. PLoS One. 2015;10:e0116454.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Veerappa AM, Saldanha M, Padakannaya P, Ramachandra NB. Genome-wide copy number scan identifies disruption of PCDH11X in developmental dyslexia. Am J Med Genet B Neuropsychiatr Genet. 2013;162B:889–97.

    Article  PubMed  Google Scholar 

  31. Zahir FR, Baross A, Delaney AD, Eydoux P, Fernandes ND, Pugh T, et al. A patient with vertebral, cognitive and behavioural abnormalities and a de novo deletion of NRXN1alpha. J Med Genet. 2008;45:239–43.

    Article  CAS  PubMed  Google Scholar 

  32. Dabell MP, Rosenfeld JA, Bader P, Escobar LF, El-Khechen D, Vallee SE, et al. Investigation of NRXN1 deletions: clinical and molecular characterization. Am J Med Genet A. 2013;161A:717–31.

    Article  PubMed  Google Scholar 

  33. Chong JX, Buckingham KJ, Jhangiani SN, Boehm C, Sobreira N, Smith JD, et al. The genetic basis of Mendelian phenotypes: discoveries, challenges, and opportunities. Am J Hum Genet. 2015;97:199–215.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lim ET, Raychaudhuri S, Sanders SJ, Stevens C, Sabo A, MacArthur DG, et al. Rare complete knockouts in humans: population distribution and significant role in autism spectrum disorders. Neuron. 2013;77:235–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Martin HC, Jones WD, McIntyre R, Sanchez-Andrade G, Sanderson M, Stephenson JD, et al. Quantifying the contribution of recessive coding variation to developmental disorders. Science. 2018;362:1161–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Sebat J, Lakshmi B, Malhotra D, Troge J, Lese-Martin C, Walsh T, et al. Strong association of de novo copy number mutations with autism. Science. 2007;316:445–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Leppa VM, Kravitz SN, Martin CL, Andrieux J, Le Caignec C, Martin-Coignard D, et al. Rare inherited and de novo CNVs reveal complex contributions to ASD risk in multiplex families. Am J Hum Genet. 2016;99:540–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Werling DM. The role of sex-differential biology in risk for autism spectrum disorder. Biol Sex Differ. 2016;7:58.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Turner TN, Wilfert AB, Bakken TE, Bernier RA, Pepper MR, Zhang Z, et al. Sex-based analysis of de novo variants in neurodevelopmental disorders. Am J Hum Genet. 2019;105:1274–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. De Rubeis S, He X, Goldberg AP, Poultney CS, Samocha K, Cicek AE, et al. Synaptic, transcriptional and chromatin genes disrupted in autism. Nature 2014;515:209–15.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Blatt GJ, Fatemi SH. Alterations in GABAergic biomarkers in the autism brain: research findings and clinical implications. Anat Rec (Hoboken). 2011;294:1646–52.

    Article  CAS  PubMed  Google Scholar 

  42. Coghlan S, Horder J, Inkster B, Mendez MA, Murphy DG, Nutt DJ. GABA system dysfunction in autism and related disorders: from synapse to symptoms. Neurosci Biobehav Rev. 2012;36:2044–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Anagnostou E. Clinical trials in autism spectrum disorder: evidence, challenges and future directions. Curr Opin Neurol. 2018;31:119–25.

    Article  CAS  PubMed  Google Scholar 

  44. Kirov G, Rees E, Walters JT, Escott-Price V, Georgieva L, Richards AL, et al. The penetrance of copy number variations for schizophrenia and developmental delay. Biol Psychiatry. 2014;75:378–85.

    Article  CAS  PubMed  Google Scholar 

  45. Cook EH Jr., Lindgren V, Leventhal BL, Courchesne R, Lincoln A, Shulman C, et al. Autism or atypical autism in maternally but not paternally derived proximal 15q duplication. Am J Hum Genet. 1997;60:928–34.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Urraca N, Cleary J, Brewer V, Pivnick EK, McVicar K, Thibert RL, et al. The interstitial duplication 15q11.2-q13 syndrome includes autism, mild facial anomalies and a characteristic EEG signature. Autism Res. 2013;6:268–79.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Browne CE, Dennis NR, Maher E, Long FL, Nicholson JC, Sillibourne J, et al. Inherited interstitial duplications of proximal 15q: genotype-phenotype correlations. Am J Hum Genet. 1997;61:1342–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Miyatake S, Koshimizu E, Fujita A, Fukai R, Imagawa E, Ohba C, et al. Detecting copy-number variations in whole-exome sequencing data using the eXome Hidden Markov Model: an ‘exome-first’ approach. J Hum Genet. 2015;60:175–82.

    Article  CAS  PubMed  Google Scholar 

  49. Collins RL, Glessner JT, Porcu E, Lepamets M, Brandon R, Lauricella C, et al. A cross-disorder dosage sensitivity map of the human genome. Cell 2022;185:3041–55 e25.

    Article  CAS  PubMed  Google Scholar 

  50. Doan RN, Bae BI, Cubelos B, Chang C, Hossain AA, Al-Saad S, et al. Mutations in human accelerated regions disrupt cognition and social behavior. Cell. 2016;167:341–54.e12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. D’Gama AM. Somatic mosaicism and autism spectrum disorder. Genes (Basel). 2021;12:1699.

    Article  PubMed  Google Scholar 

  52. Balachandar V, Rajagopalan K, Jayaramayya K, Jeevanandam M, Iyer M. Mitochondrial dysfunction: A hidden trigger of autism? Genes Dis. 2021;8:629–39.

    Article  CAS  PubMed  Google Scholar 

  53. Sherman MA, Rodin RE, Genovese G, Dias C, Barton AR, Mukamel RE, et al. Large mosaic copy number variations confer autism risk. Nat Neurosci. 2021;24:197–203.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank the affected individuals and their families for participating in this study. We also thank Ms. Sayaka Sugimoto and Ms. Kaori Takabe from Yokohama City University Graduate School of Medicine for their technical assistance. This study makes use of data generated by the DECIPHER community. A full list of centers that contributed to the generation of the data is available from https://deciphergenomics.org/about/stats and via e-mail from contact@deciphergenomics.org. Funding for the DECIPHER project was provided by Wellcome. Finally, we thank Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript.

Funding

Funding

This work was supported by AMED under grant numbers JP22ek0109486, JP22ek0109549, JP22ek0109493 (NMa), JP21wm0425007, and JP21dk0307103 (NO); JSPS KAKENHI under grant numbers JP19H03621 and 22H03047 (NMi), the Takeda Science Foundation (TM and NMa), and the NCGM Intramural Research Fund under grant number 21A1011 (NMi).

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization: NMi, NaM. Data curation: YT, RF, EK, SM, CO Investigation: NMi, YT, RF, IK, NO, KO, KN, RH, YH, SSo, MK, YS, HO, KD, TMa, ST, AF-V, NE, JT, PY, KWT, HK, KT, TO, SSa, YY, TMu, KN, SO, AM, KIn, TS, YK, MM, AI, TH, YU, CS, KIs, ES, AF, EK, SM, AT, TMi, NO, Visualization and Writing-original draft: NMi. Writing-review & editing: NMi, NaM.

Corresponding authors

Correspondence to Noriko Miyake or Naomichi Matsumoto.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethical approval

This study was approved by the Institutional Review Board of Yokohama City University Faculty of Medicine. After obtaining written informed consent, peripheral blood leukocytes were collected from the patients and their parents.

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

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Miyake, N., Tsurusaki, Y., Fukai, R. et al. Molecular diagnosis of 405 individuals with autism spectrum disorder. Eur J Hum Genet (2023). https://doi.org/10.1038/s41431-023-01335-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41431-023-01335-7

Search

Quick links