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.

  • Review Article
  • Published:

Implications of germline copy-number variations in psychiatric disorders: review of large-scale genetic studies

Abstract

Copy number variants (CNVs), defined as genome sequences of ≥50 bp that differ in copy number from that in a reference genome, are a common form of structural variation. Germline CNVs account for some of the missing heritability that single nucleotide polymorphisms could not account for. Recent technological advances have had a huge impact on CNV research. Microarray technology enables relatively low-cost, high-throughput, genome-wide measurements, and short-read sequencing technology enables the detection of short CNVs that cannot be detected by microarrays. As a result, large-scale genetic studies have been able to identify a variety of common and rare germline CNVs and their associations with diseases. Rare germline CNVs have been reported to be associated with neuropsychiatric disorders. In this review, we focused on germline CNVs and briefly described their functional characteristics, formation mechanisms, detection methods, related databases, and the latest findings. Finally, we introduced recent large-scale genetic studies to assess associations of CNVs with diseases, especially psychiatric disorders, and discussed the use of CNV-based animal models to investigate the molecular and cellular mechanisms underlying these disorders. The development and implementation of improved detection methods, such as long-read single-molecule sequencing, are expected to provide additional insight into the molecular basis of psychiatric disorders and other complex diseases, thus facilitating basic and clinical research on CNVs.

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

Access options

Buy this article

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

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Feuk L, Carson AR, Scherer SW. Structural variation in the human genome. Nat Rev Genet. 2006;7:85–97.

    CAS  PubMed  Google Scholar 

  2. Zarrei M, MacDonald JR, Merico D, Scherer SW. A copy number variation map of the human genome. Nat Rev Genet. 2015;16:172–83.

    CAS  PubMed  Google Scholar 

  3. Sudmant PH, Rausch T, Gardner EJ, Handsaker RE, Abyzov A, Huddleston J, et al. An integrated map of structural variation in 2,504 human genomes. Nature. 2015;526:75–81.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Conrad DF, Pinto D, Redon R, Feuk L, Gokcumen O, Zhang Y, et al. Origins and functional impact of copy number variation in the human genome. Nature. 2010;464:704–12.

    CAS  PubMed  Google Scholar 

  5. Itsara A, Wu H, Smith JD, Nickerson DA, Romieu I, London SJ, et al. De novo rates and selection of large copy number variation. Genome Res. 2010;20:1469–81.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Roach JC, Glusman G, Smit AF, Huff CD, Hubley R, Shannon PT, et al. Analysis of genetic inheritance in a family quartet by whole-genome sequencing. Science. 2010;328:636–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Chiang C, Scott AJ, Davis JR, Tsang EK, Li X, Kim Y, et al. The impact of structural variation on human gene expression. Nat Genet. 2017;49:692–99.

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Carvalho CM, Lupski JR. Mechanisms underlying structural variant formation in genomic disorders. Nat Rev Genet. 2016;17:224–38.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Hastings PJ, Lupski JR, Rosenberg SM, Ira G. Mechanisms of change in gene copy number. Nat Rev Genet. 2009;10:551–64.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Bailey JA, Gu Z, Clark RA, Reinert K, Samonte RV, Schwartz S, et al. Recent segmental duplications in the human genome. Science. 2002;297:1003–7.

    CAS  PubMed  Google Scholar 

  11. Stankiewicz P, Lupski JR. Genome architecture, rearrangements and genomic disorders. Trends Genet. 2002;18:74–82.

    CAS  PubMed  Google Scholar 

  12. Lieber MR. The mechanism of double-strand DNA break repair by the nonhomologous DNA end-joining pathway. Annu Rev Biochem. 2010;79:181–211.

    CAS  PubMed  PubMed Central  Google Scholar 

  13. McVey M, Lee SE. MMEJ repair of double-strand breaks (director’s cut): deleted sequences and alternative endings. Trends Genet. 2008;24:529–38.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Lee JA, Carvalho CM, Lupski JR. A DNA replication mechanism for generating nonrecurrent rearrangements associated with genomic disorders. Cell. 2007;131:1235–47.

    CAS  PubMed  Google Scholar 

  15. Hupe P, Stransky N, Thiery JP, Radvanyi F, Barillot E. Analysis of array CGH data: from signal ratio to gain and loss of DNA regions. Bioinformatics. 2004;20:3413–22.

    CAS  PubMed  Google Scholar 

  16. Olshen AB, Venkatraman ES, Lucito R, Wigler M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics. 2004;5:557–72.

    PubMed  Google Scholar 

  17. Wang P, Kim Y, Pollack J, Narasimhan B, Tibshirani R. A method for calling gains and losses in array CGH data. Biostatistics. 2005;6:45–58.

    PubMed  Google Scholar 

  18. Picard F, Robin S, Lavielle M, Vaisse C, Daudin JJ. A statistical approach for array CGH data analysis. BMC Bioinforma. 2005;6:27.

    Google Scholar 

  19. Karimpour-Fard A, Dumas L, Phang T, Sikela JM, Hunter LE. A survey of analysis software for array-comparative genomic hybridisation studies to detect copy number variation. Hum Genom. 2010;4:421–7.

    CAS  Google Scholar 

  20. Alkan C, Coe BP, Eichler EE. Genome structural variation discovery and genotyping. Nat Rev Genet. 2011;12:363–76.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Peiffer DA, Le JM, Steemers FJ, Chang W, Jenniges T, Garcia F, et al. High-resolution genomic profiling of chromosomal aberrations using Infinium whole-genome genotyping. Genome Res. 2006;16:1136–48.

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Wang K, Li M, Hadley D, Liu R, Glessner J, Grant SF, et al. PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data. Genome Res. 2007;17:1665–74.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Korn JM, Kuruvilla FG, McCarroll SA, Wysoker A, Nemesh J, Cawley S, et al. Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs. Nat Genet. 2008;40:1253–60.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Pinto D, Pagnamenta AT, Klei L, Anney R, Merico D, Regan R, et al. Functional impact of global rare copy number variation in autism spectrum disorders. Nature. 2010;466:368–72.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Colella S, Yau C, Taylor JM, Mirza G, Butler H, Clouston P, et al. QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data. Nucleic Acids Res. 2007;35:2013–25.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Zhang X, Du R, Li S, Zhang F, Jin L, Wang H. Evaluation of copy number variation detection for a SNP array platform. BMC Bioinforma. 2014;15:50.

    Google Scholar 

  27. Zhang Z, Cheng H, Hong X, Di Narzo AF, Franzen O, Peng S, et al. EnsembleCNV: an ensemble machine learning algorithm to identify and genotype copy number variation using SNP array data. Nucleic Acids Res. 2019;47:e39.

    PubMed  PubMed Central  Google Scholar 

  28. Zhao M, Wang Q, Wang Q, Jia P, Zhao Z. Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives. BMC Bioinforma. 2013;14(Suppl 11):S1.

    Google Scholar 

  29. Kosugi S, Momozawa Y, Liu X, Terao C, Kubo M, Kamatani Y. Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing. Genome Biol. 2019;20:117.

    PubMed  PubMed Central  Google Scholar 

  30. Cameron DL, Schroder J, Penington JS, Do H, Molania R, Dobrovic A, et al. GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly. Genome Res. 2017;27:2050–60.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Layer RM, Chiang C, Quinlan AR, Hall IM. LUMPY: a probabilistic framework for structural variant discovery. Genome Biol. 2014;15:R84.

    PubMed  PubMed Central  Google Scholar 

  32. Zhang J, Wang J, Wu Y. An improved approach for accurate and efficient calling of structural variations with low-coverage sequence data. BMC Bioinforma. 2012;13(Suppl 6):S6.

    Google Scholar 

  33. Bartenhagen C, Dugas M. Robust and exact structural variation detection with paired-end and soft-clipped alignments: SoftSV compared with eight algorithms. Brief Bioinform. 2016;17:51–62.

    PubMed  Google Scholar 

  34. Chen X, Schulz-Trieglaff O, Shaw R, Barnes B, Schlesinger F, Kallberg M, et al. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics. 2016;32:1220–2.

    CAS  PubMed  Google Scholar 

  35. Kronenberg ZN, Osborne EJ, Cone KR, Kennedy BJ, Domyan ET, Shapiro MD, et al. Wham: identifying structural variants of biological consequence. PLoS Comput Biol. 2015;11:e1004572.

    PubMed  PubMed Central  Google Scholar 

  36. Tan R, Wang Y, Kleinstein SE, Liu Y, Zhu X, Guo H, et al. An evaluation of copy number variation detection tools from whole-exome sequencing data. Hum Mutat. 2014;35:899–907.

    CAS  PubMed  Google Scholar 

  37. Lappalainen I, Lopez J, Skipper L, Hefferon T, Spalding JD, Garner J, et al. DbVar and DGVa: public archives for genomic structural variation. Nucleic Acids Res. 2013;41:D936–41.

    CAS  PubMed  Google Scholar 

  38. Collins RL, Brand H, Karczewski KJ, Zhao X, Alfoldi J, Francioli LC, et al. A structural variation reference for medical and population genetics. Nature. 2020;581:444–51.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. MacDonald JR, Ziman R, Yuen RK, Feuk L, Scherer SW. The database of genomic variants: a curated collection of structural variation in the human genome. Nucleic Acids Res. 2014;42:D986–92.

    CAS  PubMed  Google Scholar 

  40. Bragin E, Chatzimichali EA, Wright CF, Hurles ME, Firth HV, Bevan AP, et al. DECIPHER: database for the interpretation of phenotype-linked plausibly pathogenic sequence and copy-number variation. Nucleic Acids Res. 2014;42:D993–D1000.

    CAS  PubMed  Google Scholar 

  41. Landrum MJ, Lee JM, Benson M, Brown G, Chao C, Chitipiralla S, et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 2016;44:D862–8.

    CAS  PubMed  Google Scholar 

  42. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, et al. Finding the missing heritability of complex diseases. Nature. 2009;461:747–53.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. de Cid R, Riveira-Munoz E, Zeeuwen PL, Robarge J, Liao W, Dannhauser EN, et al. Deletion of the late cornified envelope LCE3B and LCE3C genes as a susceptibility factor for psoriasis. Nat Genet. 2009;41:211–5.

    PubMed  PubMed Central  Google Scholar 

  44. McCarroll SA, Huett A, Kuballa P, Chilewski SD, Landry A, Goyette P, et al. Deletion polymorphism upstream of IRGM associated with altered IRGM expression and Crohn’s disease. Nat Genet. 2008;40:1107–12.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Wheeler E, Huang N, Bochukova EG, Keogh JM, Lindsay S, Garg S, et al. Genome-wide SNP and CNV analysis identifies common and low-frequency variants associated with severe early-onset obesity. Nat Genet. 2013;45:513–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Wellcome Trust Case Control C, Craddock N, Hurles ME, Cardin N, Pearson RD, Plagnol, et al. Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls. Nature. 2010;464:713–20.

    Google Scholar 

  47. Cooper GM, Coe BP, Girirajan S, Rosenfeld JA, Vu TH, Baker C, et al. A copy number variation morbidity map of developmental delay. Nat Genet. 2011;43:838–46.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Betancur C. Etiological heterogeneity in autism spectrum disorders: more than 100 genetic and genomic disorders and still counting. Brain Res. 2011;1380:42–77.

    CAS  PubMed  Google Scholar 

  49. Lionel AC, Crosbie J, Barbosa N, Goodale T, Thiruvahindrapuram B, Rickaby J, et al. Rare copy number variation discovery and cross-disorder comparisons identify risk genes for ADHD. Sci Transl Med. 2011;3:95ra75.

    CAS  PubMed  Google Scholar 

  50. Marshall CR, Howrigan DP, Merico D, Thiruvahindrapuram B, Wu W, Greer DS, et al. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat Genet. 2017;49:27–35.

    CAS  PubMed  Google Scholar 

  51. Olson H, Shen Y, Avallone J, Sheidley BR, Pinsky R, Bergin AM, et al. Copy number variation plays an important role in clinical epilepsy. Ann Neurol. 2014;75:943–58.

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Soemedi R, Wilson IJ, Bentham J, Darlay R, Topf A, Zelenika D, et al. Contribution of global rare copy-number variants to the risk of sporadic congenital heart disease. Am J Hum Genet. 2012;91:489–501.

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Verbitsky M, Westland R, Perez A, Kiryluk K, Liu Q, Krithi-vasan P, et al. The copy number variation landscape of congenital anomalies of the kidney and urinary tract. Nat Genet. 2019;51:117–27.

    CAS  PubMed  Google Scholar 

  54. Crawford K, Bracher-Smith M, Owen D, Kendall KM, Rees E, Pardinas AF, et al. Medical consequences of pathogenic CNVs in adults: analysis of the UK Biobank. J Med Genet. 2019;56:131–38.

    CAS  PubMed  Google Scholar 

  55. Owen MJ, Sawa A, Mortensen PB. Schizophrenia. Lancet 2016;388:86–97.

    PubMed  PubMed Central  Google Scholar 

  56. Lord C, Elsabbagh M, Baird G, Veenstra-Vanderweele J. Autism spectrum disorder. Lancet. 2018;392:508–20.

    PubMed  PubMed Central  Google Scholar 

  57. Hilker R, Helenius D, Fagerlund B, Skytthe A, Christensen K, Werge TM, et al. Heritability of schizophrenia and schizophrenia spectrum based on the nationwide danish twin register. Biol Psychiatry. 2018;83:492–98.

    PubMed  Google Scholar 

  58. Colvert E, Tick B, McEwen F, Stewart C, Curran SR, Woodhouse E, et al. Heritability of autism spectrum disorder in a UK population-based twin sample. JAMA Psychiatry. 2015;72:415–23.

    PubMed  PubMed Central  Google Scholar 

  59. Rees E, Walters JT, Georgieva L, Isles AR, Chambert KD, Richards AL, et al. Analysis of copy number variations at 15 schizophrenia-associated loci. Br J Psychiatry. 2014;204:108–14.

    PubMed  PubMed Central  Google Scholar 

  60. Hu Z, Xiao X, Zhang Z, Li M. Genetic insights and neurobiological implications from NRXN1 in neuropsychiatric disorders. Mol Psychiatry. 2019;24:1400–14.

    PubMed  Google Scholar 

  61. McDonald-McGinn DM, Sullivan KE, Marino B, Philip N, Swillen A, Vorstman JA, et al. 22q11.2 deletion syndrome. Nat Rev Dis Prim. 2015;1:15071.

    PubMed  Google Scholar 

  62. Fiksinski AM, Schneider M, Murphy CM, Armando M, Vicari S, Canyelles JM, et al. Understanding the pediatric psychiatric phenotype of 22q11.2 deletion syndrome. Am J Med Genet A. 2018;176:2182–91.

    PubMed  PubMed Central  Google Scholar 

  63. Schneider M, Debbane M, Bassett AS, Chow EW, Fung WL, van den Bree M, et al. Psychiatric disorders from childhood to adulthood in 22q11.2 deletion syndrome: results from the International Consortium on Brain and Behavior in 22q11.2 Deletion Syndrome. Am J Psychiatry. 2014;171:627–39.

    PubMed  PubMed Central  Google Scholar 

  64. Jonas RK, Montojo CA, Bearden CE. The 22q11.2 deletion syndrome as a window into complex neuropsychiatric disorders over the lifespan. Biol Psychiatry. 2014;75:351–60.

    CAS  PubMed  Google Scholar 

  65. Mok KY, Sheerin U, Simon-Sanchez J, Salaka A, Chester L, Escott-Price V, et al. Deletions at 22q11.2 in idiopathic Parkinson’s disease: a combined analysis of genome-wide association data. Lancet Neurol. 2016;15:585–96.

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Sobanski E. Psychiatric comorbidity in adults with attention-deficit/hyperactivity disorder (ADHD). Eur Arch Psychiatry Clin Neurosci. 2006;256(Suppl 1):i26–31.

    PubMed  Google Scholar 

  67. Cerda M, Sagdeo A, Johnson J, Galea S. Genetic and environmental influences on psychiatric comorbidity: a systematic review. J Affect Disord. 2010;126:14–38.

    CAS  PubMed  Google Scholar 

  68. Leyfer OT, Folstein SE, Bacalman S, Davis NO, Dinh E, Morgan J, et al. Comorbid psychiatric disorders in children with autism: interview development and rates of disorders. J Autism Dev Disord. 2006;36:849–61.

    PubMed  Google Scholar 

  69. Buckley PF, Miller BJ, Lehrer DS, Castle DJ. Psychiatric comorbidities and schizophrenia. Schizophr Bull. 2009;35:383–402.

    PubMed  Google Scholar 

  70. Girirajan S, Rosenfeld JA, Coe BP, Parikh S, Friedman N, Goldstein A, et al. Phenotypic heterogeneity of genomic disorders and rare copy-number variants. N Engl J Med. 2012;367:1321–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Girirajan S, Rosenfeld JA, Cooper GM, Antonacci F, Siswara P, Itsara A, et al. A recurrent 16p12.1 microdeletion supports a two-hit model for severe developmental delay. Nat Genet. 2010;42:203–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Oetjens MT, Kelly MA, Sturm AC, Martin CL, Ledbetter DH. Quantifying the polygenic contribution to variable expressivity in eleven rare genetic disorders. Nat Commun. 2019;10:4897.

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 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.

    CAS  PubMed  Google Scholar 

  74. Stefansson H, Meyer-Lindenberg A, Steinberg S, Magnusdottir B, Morgen K, Arnarsdottir S, et al. CNVs conferring risk of autism or schizophrenia affect cognition in controls. Nature. 2014;505:361–6.

    CAS  PubMed  Google Scholar 

  75. Kendall KM, Rees E, Escott-Price V, Einon M, Thomas R, Hewitt J, et al. Cognitive performance among carriers of pathogenic copy number variants: analysis of 152,000 UK biobank subjects. Biol Psychiatry. 2017;82:103–10.

    PubMed  Google Scholar 

  76. Kendall KM, Bracher-Smith M, Fitzpatrick H, Lynham A, Rees E, Escott-Price V, et al. Cognitive performance and functional outcomes of carriers of pathogenic copy number variants: analysis of the UK Biobank. Br J Psychiatry. 2019;214:297–304.

    PubMed  PubMed Central  Google Scholar 

  77. Writing Committee for the E-CNVWG, van der Meer D, Sonderby IE, Kaufmann T, Walters GB, Abdellaoui A, et al. Association of copy number variation of the 15q11.2 BP1-BP2 region with cortical and subcortical morphology and cognition. JAMA Psychiatry. 2019;77:1–11.

    Google Scholar 

  78. Kirov G, Pocklington AJ, Holmans P, Ivanov D, Ikeda M, Ruderfer D, et al. De novo CNV analysis implicates specific abnormalities of postsynaptic signalling complexes in the pathogenesis of schizophrenia. Mol Psychiatry. 2012;17:142–53.

    CAS  PubMed  Google Scholar 

  79. Pinto D, Delaby E, Merico D, Barbosa M, Merikangas A, Klei L, et al. Convergence of genes and cellular pathways dysregulated in autism spectrum disorders. Am J Hum Genet. 2014;94:677–94.

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Kushima I, Aleksic B, Nakatochi M, Shimamura T, Okada T, Uno Y, et al. Comparative analyses of copy-number variation in autism spectrum disorder and schizophrenia reveal etiological overlap and biological insights. Cell Rep. 2018;24:2838–56.

    CAS  PubMed  Google Scholar 

  81. Sullivan PF, Magnusson C, Reichenberg A, Boman M, Dalman C, Davidson M, et al. Family history of schizophrenia and bipolar disorder as risk factors for autism. Arch Gen Psychiatry. 2012;69:1099–103.

    PubMed  PubMed Central  Google Scholar 

  82. Zheng Z, Zheng P, Zou XB. Association between schizophrenia and autism spectrum disorder: a systematic review and meta-analysis. Autism Res. 2018;11:1110–19.

    PubMed  Google Scholar 

  83. Kushima I, Aleksic B, Nakatochi M, Shimamura T, Shiino T, Yoshimi A, et al. High-resolution copy number variation analysis of schizophrenia in Japan. Mol Psychiatry. 2017;22:430–40.

    CAS  PubMed  Google Scholar 

  84. 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.

    PubMed  PubMed Central  Google Scholar 

  85. Gilman SR, Chang J, Xu B, Bawa TS, Gogos JA, Karayiorgou M, et al. Diverse types of genetic variation converge on functional gene networks involved in schizophrenia. Nat Neurosci. 2012;15:1723–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Rossignol DA, Frye RE. Evidence linking oxidative stress, mitochondrial dysfunction, and inflammation in the brain of individuals with autism. Front Physiol. 2014;5:150.

    PubMed  PubMed Central  Google Scholar 

  87. Forsingdal A, Jorgensen TN, Olsen L, Werge T, Didriksen M, Nielsen J. Can animal models of copy number variants that predispose to schizophrenia elucidate underlying biology? Biol Psychiatry. 2019;85:13–24.

    CAS  PubMed  Google Scholar 

  88. Nakatani J, Tamada K, Hatanaka F, Ise S, Ohta H, Inoue K, et al. Abnormal behavior in a chromosome-engineered mouse model for human 15q11-13 duplication seen in autism. Cell. 2009;137:1235–46.

    PubMed  PubMed Central  Google Scholar 

  89. Isshiki M, Tanaka S, Kuriu T, Tabuchi K, Takumi T, Okabe S. Enhanced synapse remodelling as a common phenotype in mouse models of autism. Nat Commun. 2014;5:4742.

    CAS  PubMed  Google Scholar 

  90. Tamada K, Tomonaga S, Hatanaka F, Nakai N, Takao K, Miyakawa T, et al. Decreased exploratory activity in a mouse model of 15q duplication syndrome; implications for disturbance of serotonin signaling. PLoS ONE. 2010;5:e15126.

    CAS  PubMed  PubMed Central  Google Scholar 

  91. Baba M, Yokoyama K, Seiriki K, Naka Y, Matsumura K, Kondo M, et al. Psychiatric-disorder-related behavioral phenotypes and cortical hyperactivity in a mouse model of 3q29 deletion syndrome. Neuropsychopharmacology. 2019;44:2125–35.

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Fujitani M, Zhang S, Fujiki R, Fujihara Y, Yamashita T. A chromosome 16p13.11 microduplication causes hyperactivity through dysregulation of miR-484/protocadherin-19 signaling. Mol Psychiatry. 2017;22:364–74.

    CAS  PubMed  Google Scholar 

  93. Toyoshima M, Akamatsu W, Okada Y, Ohnishi T, Balan S, Hisano Y, et al. Analysis of induced pluripotent stem cells carrying 22q11.2 deletion. Transl Psychiatry. 2016;6:e934.

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Zhao DJ, Lin MY, Chen J, Pedrosa E, Hrabovsky A, Fourcade HM, et al. MicroRNA profiling of neurons generated using induced pluripotent stem cells derived from patients with schizophrenia and schizoaffective disorder, and 22q11.2 Del. Plos ONE. 2015;10:e0132387.

    PubMed  PubMed Central  Google Scholar 

  95. Yoon KJ, Nguyen HN, Ursini G, Zhang FY, Kim NS, Wen ZX, et al. Modeling a genetic risk for schizophrenia in iPSCs and mice reveals neural stem cell deficits associated with adherens junctions and polarity. Cell Stem Cell. 2014;15:79–91.

    CAS  PubMed  PubMed Central  Google Scholar 

  96. Sedlazeck FJ, Lee H, Darby CA, Schatz MC. Piercing the dark matter: bioinformatics of long-range sequencing and mapping. Nat Rev Genet. 2018;19:329–46.

    CAS  PubMed  Google Scholar 

  97. Cao H, Hastie AR, Cao D, Lam ET, Sun Y, Huang H, et al. Rapid detection of structural variation in a human genome using nanochannel-based genome mapping technology. Gigascience. 2014;3:34.

    PubMed  PubMed Central  Google Scholar 

  98. Lam ET, Hastie A, Lin C, Ehrlich D, Das SK, Austin MD, et al. Genome mapping on nanochannel arrays for structural variation analysis and sequence assembly. Nat Biotechnol. 2012;30:771–6.

    CAS  PubMed  Google Scholar 

  99. Merker JD, Wenger AM, Sneddon T, Grove M, Zappala Z, Fresard L, et al. Long-read genome sequencing identifies causal structural variation in a Mendelian disease. Genet Med. 2018;20:159–63.

    CAS  PubMed  Google Scholar 

  100. Audano PA, Sulovari A, Graves-Lindsay TA, Cantsilieris S, Sorensen M, Welch AE, et al. Characterizing the major structural variant alleles of the human genome. Cell. 2019;176:663–75 e19.

    CAS  PubMed  PubMed Central  Google Scholar 

  101. Chaisson MJP, Sanders AD, Zhao X, Malhotra A, Porubsky D, Rausch T, et al. Multi-platform discovery of haplotype-resolved structural variation in human genomes. Nat Commun. 2019;10:1784.

    PubMed  PubMed Central  Google Scholar 

  102. Levy-Sakin M, Pastor S, Mostovoy Y, Li L, Leung AKY, McCaffrey J, et al. Genome maps across 26 human populations reveal population-specific patterns of structural variation. Nat Commun. 2019;10:1025.

    PubMed  PubMed Central  Google Scholar 

  103. Green EK, Rees E, Walters JT, Smith KG, Forty L, Grozeva D, et al. Copy number variation in bipolar disorder. Mol Psychiatry. 2016;21:89–93.

    CAS  PubMed  Google Scholar 

  104. Nelis E, Van Broeckhoven C, De Jonghe P, Lofgren A, Vandenberghe A, Latour P, et al. Estimation of the mutation frequencies in Charcot-Marie-Tooth disease type 1 and hereditary neuropathy with liability to pressure palsies: a European collaborative study. Eur J Hum Genet. 1996;4:25–33.

    CAS  PubMed  Google Scholar 

  105. Kitada T, Asakawa S, Hattori N, Matsumine H, Yamamura Y, Minoshima S, et al. Mutations in the parkin gene cause autosomal recessive juvenile parkinsonism. Nature. 1998;392:605–8.

    CAS  PubMed  Google Scholar 

  106. Hooli BV, Mohapatra G, Mattheisen M, Parrado AR, Roehr JT, Shen Y, et al. Role of common and rare APP DNA sequence variants in Alzheimer disease. Neurology. 2012;78:1250–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  107. Kunkel LM, Hejtmancik JF, Caskey CT, Speer A, Monaco AP, Middlesworth W, et al. Analysis of deletions in DNA from patients with Becker and Duchenne muscular dystrophy. Nature. 1986;322:73–7.

    CAS  PubMed  Google Scholar 

  108. Gejman PV, Sanders AR, Kendler KS. Genetics of schizophrenia: new findings and challenges. Annu Rev Genom Hum Genet. 2011;12:121–44.

    CAS  Google Scholar 

  109. Kirov G. CNVs in neuropsychiatric disorders. Hum Mol Genet. 2015;24:R45–9.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported in part by AMED under grant nos. JP20km0405216, JP20dm0107087, JP20dm0207075, JP20ak0101113, JP20dk0307075, JP20dk0307081, JP20dm0107160, and JP20ek0109411; and the Japan Society for the Promotion of Science (JSPS) KAKENHI grant nos. 17H05090, 15K19720, and 18H04040.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Masahiro Nakatochi.

Ethics declarations

Conflict of interest

NO has received research support and speakers’ honoraria from, or consulted for Sumitomo Dainippon, Otsuka, DAIICHI SANKYO, Tsumura, Nihon Medi-Physics, Pfizer, KAITEKI, Eli Lilly, Mochida, Eisai, Takeda, Novartis, Astellas, MSD, Meiji Seika Pharma, Janssen, Mitsubishi Tanabe, Kyowa, Taisho Pharma, EA Pharma, UCB and Shionogi, outside the submitted work. MN and IK declare no potential conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nakatochi, M., Kushima, I. & Ozaki, N. Implications of germline copy-number variations in psychiatric disorders: review of large-scale genetic studies. J Hum Genet 66, 25–37 (2021). https://doi.org/10.1038/s10038-020-00838-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s10038-020-00838-1

This article is cited by

Search

Quick links