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.

  • Article
  • Published:

The benefit of diagnostic whole genome sequencing in schizophrenia and other psychotic disorders

Abstract

Schizophrenia has a multifactorial etiology, involving a polygenic architecture. The potential benefit of whole genome sequencing (WGS) in schizophrenia and other psychotic disorders is not well studied. We investigated the yield of clinical WGS analysis in 251 families with a proband diagnosed with schizophrenia (N = 190), schizoaffective disorder (N = 49), or other conditions involving psychosis (N = 48). Participants were recruited in Israel and USA, mainly of Jewish, Arab, and other European ancestries. Trio (parents and proband) WGS was performed for 228 families (90.8%); in the other families, WGS included parents and at least two affected siblings. In the secondary analyses, we evaluated the contribution of rare variant enrichment in particular gene sets, and calculated polygenic risk score (PRS) for schizophrenia. For the primary outcome, diagnostic rate was 6.4%; we found clinically significant, single nucleotide variants (SNVs) or small insertions or deletions (indels) in 14 probands (5.6%), and copy number variants (CNVs) in 2 (0.8%). Significant enrichment of rare loss-of-function variants was observed in a gene set of top schizophrenia candidate genes in affected individuals, compared with population controls (N = 6,840). The PRS for schizophrenia was significantly increased in the affected individuals group, compared to their unaffected relatives. Last, we were also able to provide pharmacogenomics information based on CYP2D6 genotype data for most participants, and determine their antipsychotic metabolizer status. In conclusion, our findings suggest that WGS may have a role in the setting of both research and genetic counseling for individuals with schizophrenia and other psychotic disorders and their families.

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: Demographic and clinical characteristics of participants.
Fig. 2: Detection and classification of clinically relevant variants.
Fig. 3: Case/control enrichment of qualified variants in selected gene sets.

Similar content being viewed by others

Data availability

WGS data from consenting participants is available via the ATAV data browser (http://atavdb.org/) and will be deposited in dbGaP (44515). ATAV code is freely provided on GitHub at https://github.com/nickzren/atav.

References

  1. Bray NJ, O’Donovan MC. The genetics of neuropsychiatric disorders. Brain Neurosci Adv 2019;2:2398212818799271.

  2. Legge SE, Santoro ML, Periyasamy S, Okewole A, Arsalan A, Kowalec K. Genetic architecture of schizophrenia: a review of major advancements. Psychol Med. 2021;51:2168–77.

  3. Peay HL. Genetic risk assessment in psychiatry. Cold Spring Harb Perspect Med. 2019;10:a036616.

  4. Austin JC. Evidence-based genetic counseling for psychiatric disorders: a road map. Cold Spring Harb Perspect Med. 2019;10:a036608.

  5. Finucane BM, Ledbetter DH, Vorstman JA. Diagnostic genetic testing for neurodevelopmental psychiatric disorders: closing the gap between recommendation and clinical implementation. Curr Opin Genet Dev. 2021;68:1–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Sullivan PF, Geschwind DH. Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders. Cell. 2019;177:162–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Schizophrenia Working Group of the Psychiatric Genomics C. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–7.

    Article  CAS  Google Scholar 

  8. Pardinas AF, Holmans P, Pocklington AJ, Escott-Price V, Ripke S, Carrera N, et al. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nat Genet. 2018;50:381–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Reay WR, Atkins JR, Quide Y, Carr VJ, Green MJ, Cairns MJ. Polygenic disruption of retinoid signalling in schizophrenia and a severe cognitive deficit subtype. Mol Psychiatry. 2020;25:719–31.

    Article  CAS  PubMed  Google Scholar 

  10. Agerbo E, Sullivan PF, Vilhjalmsson BJ, Pedersen CB, Mors O, Borglum AD, et al. Polygenic risk score, parental socioeconomic status, family history of psychiatric disorders, and the risk for schizophrenia: A Danish Population-Based Study and Meta-analysis. JAMA Psychiatry. 2015;72:635–41.

    Article  PubMed  Google Scholar 

  11. 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 

  12. 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.

    Article  CAS  PubMed  Google Scholar 

  13. Guipponi M, Santoni FA, Setola V, Gehrig C, Rotharmel M, Cuenca M, et al. Exome sequencing in 53 sporadic cases of schizophrenia identifies 18 putative candidate genes. PLoS One. 2014;9:e112745.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Balakrishna T, Curtis D. Assessment of Potential Clinical Role for Exome Sequencing in Schizophrenia. Schizophr Bull. 2019;46:328–35.

  15. Singh T, Kurki MI, Curtis D, Purcell SM, Crooks L, McRae J, et al. Rare loss-of-function variants in SETD1A are associated with schizophrenia and developmental disorders. Nat Neurosci. 2016;19:571–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Steinberg S, Gudmundsdottir S, Sveinbjornsson G, Suvisaari J, Paunio T, Torniainen-Holm M, et al. Truncating mutations in RBM12 are associated with psychosis. Nat Genet. 2017;49:1251–4.

    Article  CAS  PubMed  Google Scholar 

  17. Singh T, Neale BM, Daly MJ. Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia. 2020: 2020.2009.2018.20192815.

  18. Curtis D, Coelewij L, Liu SH, Humphrey J, Mott R. Weighted burden analysis of exome-sequenced case-control sample implicates synaptic genes in schizophrenia aetiology. Behav Genet. 2018;48:198–208.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Fromer M, Pocklington AJ, Kavanagh DH, Williams HJ, Dwyer S, Gormley P, et al. De novo mutations in schizophrenia implicate synaptic networks. Nature. 2014;506:179–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Genovese G, Fromer M, Stahl EA, Ruderfer DM, Chambert K, Landen M, et al. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat Neurosci. 2016;19:1433–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Halvorsen M, Huh R, Oskolkov N, Wen J, Netotea S, Giusti-Rodriguez P, et al. Increased burden of ultra-rare structural variants localizing to boundaries of topologically associated domains in schizophrenia. Nat Commun. 2020;11:1842.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Singh T, Walters JTR, Johnstone M, Curtis D, Suvisaari J, Torniainen M, et al. The contribution of rare variants to risk of schizophrenia in individuals with and without intellectual disability. Nat Genet. 2017;49:1167–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Wright CF, McRae JF, Clayton S, Gallone G, Aitken S, FitzGerald TW, et al. Making new genetic diagnoses with old data: iterative reanalysis and reporting from genome-wide data in 1,133 families with developmental disorders. Genet Med. 2018;20:1216–23.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Jiang YH, Yuen RK, Jin X, Wang M, Chen N, Wu X, et al. Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing. Am J Hum Genet. 2013;93:249–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Howrigan DP, Rose SA, Samocha KE, Fromer M, Cerrato F, Chen WJ, et al. Exome sequencing in schizophrenia-affected parent-offspring trios reveals risk conferred by protein-coding de novo mutations. Nat Neurosci. 2020;23:185–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Rees E, Han J, Morgan J, Carrera N, Escott-Price V, Pocklington AJ, et al. De novo mutations identified by exome sequencing implicate rare missense variants in SLC6A1 in schizophrenia. Nat Neurosci. 2020;23:179–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Mojarad BA, Yin Y, Manshaei R, Backstrom I, Costain G, Heung T, et al. Genome sequencing broadens the range of contributing variants with clinical implications in schizophrenia. Transl Psychiatry. 2021;11:84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Petrovski S, Aggarwal V, Giordano JL, Stosic M, Wou K, Bier L, et al. Whole-exome sequencing in the evaluation of fetal structural anomalies: a prospective cohort study. Lancet. 2019;393:758–67.

    Article  CAS  PubMed  Google Scholar 

  29. Zhu X, Petrovski S, Xie P, Ruzzo EK, Lu YF, McSweeney KM, et al. Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios. Genet Med. 2015;17:774–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Need AC, Shashi V, Hitomi Y, Schoch K, Shianna KV, McDonald MT, et al. Clinical application of exome sequencing in undiagnosed genetic conditions. J Med Genet. 2012;49:353–61.

    Article  CAS  PubMed  Google Scholar 

  31. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 5th edn. Washington, DC: American Psychiatric Association 2013.

  32. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th edn. Washington, DC: American Psychiatric Association 2000.

  33. Fernandez A, Drozd MM, Thummler S, Dor E, Capovilla M, Askenazy F, et al. Childhood-onset schizophrenia: a systematic overview of its genetic heterogeneity from classical studies to the genomic era. Front Genet. 2019;10:1137.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Fernandez A, Dor E, Maurin T, Laure G, Menard ML, Drozd M, et al. Exploration and characterisation of the phenotypic and genetic profiles of patients with early onset schizophrenia associated with autism spectrum disorder and their first-degree relatives: a French multicentre case series study protocol (GenAuDiss). BMJ Open. 2018;8:e023330.

    PubMed  PubMed Central  Google Scholar 

  35. Ren Z, Povysil G, Hostyk JA, Cui H, Bhardwaj N, Goldstein DB. ATAV: a comprehensive platform for population-scale genomic analyses. BMC Bioinforma. 2021;22:149.

    Article  Google Scholar 

  36. 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 

  37. Abou Tayoun AN, Pesaran T, DiStefano MT, Oza A, Rehm HL, Biesecker LG, et al. Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion. Hum Mutat. 2018;39:1517–24.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Rausch T, Zichner T, Schlattl A, Stutz AM, Benes V, Korbel JO. DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics. 2012;28:i333–i339.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  40. 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.

    Article  CAS  PubMed  Google Scholar 

  41. Chen K, Wallis JW, McLellan MD, Larson DE, Kalicki JM, Pohl CS, et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods. 2009;6:677–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Abyzov A, Urban AE, Snyder M, Gerstein M. CNVnator: an approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing. Genome Res. 2011;21:974–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Pedersen BS, Quinlan AR. Duphold: scalable, depth-based annotation and curation of high-confidence structural variant calls. GigaScience. 2019;8:giz040.

  44. Jeffares DC, Jolly C, Hoti M, Speed D, Shaw L, Rallis C, et al. Transient structural variations have strong effects on quantitative traits and reproductive isolation in fission yeast. Nat Commun. 2017;8:14061.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Geoffroy V, Herenger Y, Kress A, Stoetzel C, Piton A, Dollfus H, et al. AnnotSV: an integrated tool for structural variations annotation. Bioinformatics. 2018;34:3572–4.

    Article  CAS  PubMed  Google Scholar 

  46. 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 

  47. Dolzhenko E, Deshpande V, Schlesinger F, Krusche P, Petrovski R, Chen S, et al. ExpansionHunter: a sequence-graph-based tool to analyze variation in short tandem repeat regions. Bioinformatics. 2019;35:4754–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Alkelai A, Greenbaum L, Heinzen EL, Baugh EH, Teitelbaum A, Zhu X, et al. New insights into tardive dyskinesia genetics: Implementation of whole-exome sequencing approach. Prog Neuropsychopharmacol Biol Psychiatry. 2019;94:109659.

    Article  CAS  PubMed  Google Scholar 

  49. Povysil G, Chazara O, Carss KJ, Deevi SVV, Wang Q, Armisen J et al. Assessing the role of rare genetic variation in patients with heart failure. JAMA Cardiol. 2020;6:379–86.

  50. Euesden J, Lewis CM, O’reilly PF. PRSice: polygenic risk score software. Bioinformatics. 2014;31:1466–8.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Martin J, Walters RK, Demontis D, Mattheisen M, Lee SH, Robinson E, et al. A genetic investigation of sex bias in the prevalence of attention-deficit/hyperactivity disorder. Biol psychiatry. 2018;83:1044–53.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Ripke S, Neale BM, Corvin A, Walters JT, Farh K-H, Holmans PA, et al. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421.

    Article  CAS  PubMed Central  Google Scholar 

  53. Nagel M, Jansen PR, Stringer S, Watanabe K, de Leeuw CA, Bryois J, et al. Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways. Nat Genet. 2018;50:920–7.

    Article  CAS  PubMed  Google Scholar 

  54. 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 

  55. Stahl EA, Breen G, Forstner AJ, McQuillin A, Ripke S, Trubetskoy V, et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat Genet. 2019;51:793–803.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Howard DM, Adams MJ, Clarke TK, Hafferty JD, Gibson J, Shirali M, et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019;22:343–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Chen X, Shen F, Gonzaludo N, Malhotra A, Rogert C, Taft RJ et al. Cyrius: accurate CYP2D6 genotyping using whole-genome sequencing data. Pharmacogenomics J. 2021;21:251–61.

  58. Caudle KE, Sangkuhl K, Whirl-Carrillo M, Swen JJ, Haidar CE, Klein TE, et al. Standardizing CYP2D6 Genotype to Phenotype Translation: Consensus Recommendations from the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group. Clin Transl Sci. 2020;13:116–24.

    Article  PubMed  Google Scholar 

  59. Jukic MM, Smith RL, Haslemo T, Molden E, Ingelman-Sundberg M. Effect of CYP2D6 genotype on exposure and efficacy of risperidone and aripiprazole: a retrospective, cohort study. Lancet Psychiatry. 2019;6:418–26.

    Article  PubMed  Google Scholar 

  60. van Westrhenen R, Aitchison KJ, Ingelman-Sundberg M, Jukic MM. Pharmacogenomics of antidepressant and antipsychotic treatment: how far have we got and where are we going? Front Psychiatry. 2020;11:94.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Smith HS, Swint JM, Lalani SR, Yamal JM, de Oliveira Otto MC, Castellanos S, et al. Clinical application of genome and exome sequencing as a diagnostic tool for pediatric patients: a scoping review of the literature. Genet Med. 2019;21:3–16.

    Article  CAS  PubMed  Google Scholar 

  62. Clark MM, Stark Z, Farnaes L, Tan TY, White SM, Dimmock D, et al. Meta-analysis of the diagnostic and clinical utility of genome and exome sequencing and chromosomal microarray in children with suspected genetic diseases. NPJ Genom Med. 2018;3:16.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. van Schaik RHN, Muller DJ, Serretti A, Ingelman-Sundberg M. Pharmacogenetics in psychiatry: an update on clinical usability. Front Pharm. 2020;11:575540.

    Article  CAS  Google Scholar 

  64. Foley C, Heron EA, Harold D, Walters J, Owen M, O’Donovan M et al. Identifying schizophrenia patients who carry pathogenic genetic copy number variants using standard clinical assessment: retrospective cohort study. Br J Psychiatry. 2020;216:275–9.

  65. Lowther C, Merico D, Costain G, Waserman J, Boyd K, Noor A, et al. Impact of IQ on the diagnostic yield of chromosomal microarray in a community sample of adults with schizophrenia. Genome Med. 2017;9:105.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Russo M, Levine SZ, Demjaha A, Di Forti M, Bonaccorso S, Fearon P, et al. Association between symptom dimensions and categorical diagnoses of psychosis: a cross-sectional and longitudinal investigation. Schizophr Bull. 2014;40:111–9.

    Article  PubMed  Google Scholar 

  67. Potuzak M, Ravichandran C, Lewandowski KE, Ongur D, Cohen BM. Categorical vs dimensional classifications of psychotic disorders. Compr Psychiatry. 2012;53:1118–29.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Gaebel W, Zielasek J. Focus on psychosis. Dialogues Clin Neurosci. 2015;17:9–18.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Owen MJ, Craddock N, Jablensky A. The genetic deconstruction of psychosis. Schizophr Bull. 2007;33:905–11.

    Article  PubMed  PubMed Central  Google Scholar 

  70. 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  CAS  Google Scholar 

  71. Yu X, Yang L, Li J, Li W, Li D, Wang R, et al. De novo and inherited SETD1A variants in early-onset epilepsy. Neurosci Bull. 2019;35:1045–57.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Alkelai A, Shohat S, Greenbaum L, Schechter T, Draiman B, Chitrit-Raveh E, et al. Expansion of the GRIA2 phenotypic representation: a novel de novo loss of function mutation in a case with childhood onset schizophrenia. J Hum Genet. 2021;66:339–43.

    Article  CAS  PubMed  Google Scholar 

  73. Ohi K, Nishizawa D, Shimada T, Kataoka Y, Hasegawa J, Shioiri T et al. Polygenetic risk scores for major psychiatric disorders among schizophrenia patients, their first-degree relatives and healthy subjects. Int J Neuropsychopharmacol. 2020;23:157–64.

  74. Taniguchi S, Ninomiya K, Kushima I, Saito T, Shimasaki A, Sakusabe T, et al. Polygenic risk scores in schizophrenia with clinically significant copy number variants. Psychiatry Clin Neurosci. 2020;74:35–39.

    Article  CAS  PubMed  Google Scholar 

  75. Ranlund S, Calafato S, Thygesen JH, Lin K, Cahn W, Crespo-Facorro B, et al. A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains. Am J Med Genet B Neuropsychiatr Genet. 2018;177:21–34.

    Article  PubMed  Google Scholar 

  76. Reay WR, Atkins JR, Carr VJ, Green MJ, Cairns MJ. Pharmacological enrichment of polygenic risk for precision medicine in complex disorders. Sci Rep. 2020;10:879.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Gauthier J, Champagne N, Lafreniere RG, Xiong L, Spiegelman D, Brustein E, et al. De novo mutations in the gene encoding the synaptic scaffolding protein SHANK3 in patients ascertained for schizophrenia. Proc Natl Acad Sci USA. 2010;107:7863–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Gulsuner S, Walsh T, Watts AC, Lee MK, Thornton AM, Casadei S, et al. Spatial and temporal mapping of de novo mutations in schizophrenia to a fetal prefrontal cortical network. Cell. 2013;154:518–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Wang S, van Rhijn JR, Akkouh I, Kogo N, Maas N, Bleeck A et al. Loss-of-function variants in the schizophrenia risk gene SETD1A alter neuronal network activity in human neurons through cAMP/PKA pathway. bioRxiv. 2021;05.25.445613.

  80. Deciphering Developmental Disorders S. Prevalence and architecture of de novo mutations in developmental disorders. Nature. 2017;542:433–8.

    Article  CAS  Google Scholar 

  81. RK CY, Merico D, Bookman M JLH, 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.

    Article  CAS  Google Scholar 

  82. Ehlers MD. Synapse structure: glutamate receptors connected by the shanks. Curr Biol. 1999;9:R848–850.

    Article  CAS  PubMed  Google Scholar 

  83. Boeckers TM, Bockmann J, Kreutz MR, Gundelfinger ED. ProSAP/Shank proteins - a family of higher order organizing molecules of the postsynaptic density with an emerging role in human neurological disease. J Neurochem. 2002;81:903–10.

    Article  CAS  PubMed  Google Scholar 

  84. Grabrucker AM, Schmeisser MJ, Schoen M, Boeckers TM. Postsynaptic ProSAP/Shank scaffolds in the cross-hair of synaptopathies. Trends Cell Biol. 2011;21:594–603.

    Article  CAS  PubMed  Google Scholar 

  85. Li Y, Jia X, Wu H, Xun G, Ou J, Zhang Q, et al. Genotype and phenotype correlations for SHANK3 de novo mutations in neurodevelopmental disorders. Am J Med Genet A. 2018;176:2668–76.

    CAS  PubMed  Google Scholar 

  86. Uchino S, Waga C. SHANK3 as an autism spectrum disorder-associated gene. Brain Dev. 2013;35:106–10.

    Article  PubMed  Google Scholar 

  87. 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 

  88. Ba W, Yan Y, Reijnders MR, Schuurs-Hoeijmakers JH, Feenstra I, Bongers EM, et al. TRIO loss of function is associated with mild intellectual disability and affects dendritic branching and synapse function. Hum Mol Genet. 2016;25:892–902.

    Article  CAS  PubMed  Google Scholar 

  89. Sadybekov A, Tian C, Arnesano C, Katritch V, Herring BE. An autism spectrum disorder-related de novo mutation hotspot discovered in the GEF1 domain of Trio. Nat Commun. 2017;8:601.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  90. Ba W, Yan Y, Reijnders MRF, Schuurs-Hoeijmakers JHM, Feenstra I, Bongers EMHF, et al. TRIO loss of function is associated with mild intellectual disability and affects dendritic branching and synapse function. Hum Mol Genet. 2016;25:892–902.

    Article  CAS  PubMed  Google Scholar 

  91. Dissen GA, Lomniczi A, Heger S, Neff TL, Ojeda SR. Hypothalamic EAP1 (enhanced at puberty 1) is required for menstrual cyclicity in nonhuman primates. Endocrinology. 2012;153:350–61.

    Article  CAS  PubMed  Google Scholar 

  92. Marcogliese PC, Shashi V, Spillmann RC, Stong N, Rosenfeld JA, Koenig MK, et al. IRF2BPL is associated with neurological phenotypes. Am J Hum Genet. 2018;103:456.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Tran Mau-Them F, Guibaud L, Duplomb L, Keren B, Lindstrom K, Marey I, et al. De novo truncating variants in the intronless IRF2BPL are responsible for developmental epileptic encephalopathy. Genet Med. 2019;21:1008–14.

    Article  CAS  PubMed  Google Scholar 

  94. Skorvanek M, Dusek P, Rydzanicz M, Walczak A, Kosinska J, Kostrzewa G, et al. Neurodevelopmental disorder associated with IRF2BPL gene mutation: expanding the phenotype? Parkinsonism Relat D. 2019;62:239–41.

    Article  Google Scholar 

  95. 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 

  96. Feng J, Han Q, Zhou L. Planar cell polarity genes, Celsr1-3, in neural development. Neurosci Bull. 2012;28:309–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Vilboux T, Malicdan MC, Roney JC, Cullinane AR, Stephen J, Yildirimli D, et al. CELSR2, encoding a planar cell polarity protein, is a putative gene in Joubert syndrome with cortical heterotopia, microophthalmia, and growth hormone deficiency. Am J Med Genet A. 2017;173:661–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Brennand KJ, Simone A, Jou J, Gelboin-Burkhart C, Tran N, Sangar S, et al. Modelling schizophrenia using human induced pluripotent stem cells. Nature. 2011;473:221–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Wang X, Herberg FW, Laue MM, Wullner C, Hu B, Petrasch-Parwez E, et al. Neurobeachin: a protein kinase A-anchoring, beige/Chediak-higashi protein homolog implicated in neuronal membrane traffic. J Neurosci. 2000;20:8551–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Mulhern MS, Stumpel C, Stong N, Brunner HG, Bier L, Lippa N, et al. NBEA: developmental disease gene with early generalized epilepsy phenotypes. Ann Neurol. 2018;84:788–95.

    Article  PubMed  PubMed Central  Google Scholar 

  101. Bowling KM, Thompson ML, Amaral MD, Finnila CR, Hiatt SM, Engel KL, et al. Genomic diagnosis for children with intellectual disability and/or developmental delay. Genome Med. 2017;9:43.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  102. Castermans D, Wilquet V, Parthoens E, Huysmans C, Steyaert J, Swinnen L, et al. The neurobeachin gene is disrupted by a translocation in a patient with idiopathic autism. J Med Genet. 2003;40:352–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Smith M, Woodroffe A, Smith R, Holguin S, Martinez J, Filipek PA, et al. Molecular genetic delineation of a deletion of chromosome 13q12->q13 in a patient with autism and auditory processing deficits. Cytogenet Genome Res. 2002;98:233–9.

    Article  CAS  PubMed  Google Scholar 

  104. de Kovel CGF, Syrbe S, Brilstra EH, Verbeek N, Kerr B, Dubbs H, et al. Neurodevelopmental disorders caused by de novo variants in KCNB1 genotypes and phenotypes. JAMA Neurol. 2017;74:1228–36.

    Article  PubMed  PubMed Central  Google Scholar 

  105. Li XN, Herrington J, Petrov A, Ge L, Eiermann G, Xiong Y, et al. The role of voltage-gated potassium channels Kv2.1 and Kv2.2 in the regulation of insulin and somatostatin release from pancreatic islets. J Pharm Exp Ther. 2013;344:407–16.

    Article  CAS  Google Scholar 

  106. Peltola MA, Kuja-Panula J, Liuhanen J, Voikar V, Piepponen P, Hiekkalinna T, et al. AMIGO-Kv2.1 Potassium Channel Complex Is Associated With Schizophrenia-Related Phenotypes. Schizophr Bull. 2016;42:191–201.

    PubMed  Google Scholar 

  107. Marini C, Romoli M, Parrini E, Costa C, Mei D, Mari F, et al. Clinical features and outcome of 6 new patients carrying de novo KCNB1 gene mutations. Neurol Genet. 2017;3:e206.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Matsumura K, Seiriki K, Okada S, Nagase M, Ayabe S, Yamada I, et al. Pathogenic POGZ mutation causes impaired cortical development and reversible autism-like phenotypes. Nat Commun. 2020;11:859.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Stessman HAF, Willemsen MH, Fenckova M, Penn O, Hoischen A, Xiong B, et al. Disruption of POGZ is associated with intellectual disability and autism spectrum disorders. Am J Hum Genet. 2016;98:541–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Deciphering Developmental Disorders S. Large-scale discovery of novel genetic causes of developmental disorders. Nature. 2015;519:223–8.

    Article  CAS  Google Scholar 

  111. Camargo LM, Collura V, Rain JC, Mizuguchi K, Hermjakob H, Kerrien S, et al. Disrupted in schizophrenia 1 interactome: evidence for the close connectivity of risk genes and a potential synaptic basis for schizophrenia. Mol Psychiatry. 2007;12:74–86.

    Article  CAS  PubMed  Google Scholar 

  112. Laquerriere A, Maillard C, Cavallin M, Chapon F, Marguet F, Molin A, et al. Neuropathological Hallmarks of Brain Malformations in Extreme Phenotypes Related to DYNC1H1 Mutations. J Neuropathol Exp Neurol. 2017;76:195–205.

    CAS  PubMed  Google Scholar 

  113. Lin Z, Liu Z, Li X, Li F, Hu Y, Chen B, et al. Whole-exome sequencing identifies a novel de novo mutation in DYNC1H1 in epileptic encephalopathies. Sci Rep. 2017;7:258.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  114. Kury S, van Woerden GM, Besnard T, Proietti Onori M, Latypova X, Towne MC, et al. De novo mutations in protein kinase genes CAMK2A and CAMK2B cause intellectual disability. Am J Hum Genet. 2017;101:768–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Akita T, Aoto K, Kato M, Shiina M, Mutoh H, Nakashima M, et al. De novo variants in CAMK2A and CAMK2B cause neurodevelopmental disorders. Ann Clin Transl Neurol. 2018;5:280–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Angelini C, Van Gils J, Bigourdan A, Jouk PS, Lacombe D, Menegon P, et al. Major intra-familial phenotypic heterogeneity and incomplete penetrance due to a CACNA1A pathogenic variant. Eur J Med Genet. 2019;62:103530.

    Article  PubMed  Google Scholar 

  117. Spranger M, Spranger S, Schwab S, Benninger C, Dichgans M. Familial hemiplegic migraine with cerebellar ataxia and paroxysmal psychosis. Eur Neurol. 1999;41:150–2.

    Article  CAS  PubMed  Google Scholar 

  118. Reijnders MRF, Miller KA, Alvi M, Goos JAC, Lees MM, de Burca A, et al. De novo and inherited loss-of-function variants in TLK2: clinical and genotype-phenotype evaluation of a distinct neurodevelopmental disorder. Am J Hum Genet. 2018;102:1195–203.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Weise A, Mrasek K, Klein E, Mulatinho M, Llerena JC Jr., Hardekopf D, et al. Microdeletion and microduplication syndromes. J Histochem Cytochem. 2012;60:346–58.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Brunetti-Pierri N, Grange DK, Ou Z, Peiffer DA, Peacock SK, Cooper ML, et al. Characterization of de novo microdeletions involving 17q11.2q12 identified through chromosomal comparative genomic hybridization. Clin Genet. 2007;72:411–9.

    Article  CAS  PubMed  Google Scholar 

  121. Willatt L, Cox J, Barber J, Cabanas ED, Collins A, Donnai D, et al. 3q29 microdeletion syndrome: clinical and molecular characterization of a new syndrome. Am J Hum Genet. 2005;77:154–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Quintero-Rivera F, Sharifi-Hannauer P, Martinez-Agosto JA. Autistic and psychiatric findings associated with the 3q29 microdeletion syndrome: case report and review. Am J Med Genet A. 2010;152A:2459–67.

    Article  PubMed  Google Scholar 

  123. Stelzer G, Plaschkes I, Oz-Levi D, Alkelai A, Olender T, Zimmerman S, et al. VarElect: the phenotype-based variation prioritizer of the GeneCards Suite. BMC Genomics. 2016;17:444.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  124. Gelfman S, Wang Q, McSweeney KM, Ren Z, La Carpia F, Halvorsen M, et al. Annotating pathogenic non-coding variants in genic regions. Nat Commun. 2017;8:236.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  125. Clifton NE, Rees E, Holmans PA, Pardinas AF, Harwood JC, Di Florio A et al. Genetic association of FMRP targets with psychiatric disorders. Mol Psychiatry. 2020;26:2977–90.

Download references

Acknowledgements

This paper is dedicated to the memory of Prof. Deborah L. Levy, PhD, Director of the Psychology Research Laboratory at McLean Hospital and Associate Professor of Psychiatry, Harvard Medical School, who passed away while this paper was being prepared. Research reported in this publication was funded by the National Institute of Mental Health (5U01MH105670).

Author information

Authors and Affiliations

Authors

Contributions

AA, LG, ARD, ELH, AEP, VA, and DBG designed the study and supervised the project. BL, AEP, SLD, and MBH enrolled and phenotyped participants EPP and JM contributed to data collection and sample preparation. DH, AM GP, and AA developed analysis tools and generated the data AA, LG, AAS, ARD, GP, AM, DH, SG, EHB, AWZ, HH, VJ, ELH, VA, and AG analyzed the data AA and LG wrote the manuscript with input from all authors. All authors reviewed the manuscript.

Corresponding author

Correspondence to Anna Alkelai.

Ethics declarations

Competing interests

DBG reports holding equity in the publicly traded precision medicine company Praxis Precision Medicine, Apostle Inc, and Q-State Biosciences and has in the past been a paid advisor to AstraZeneca, Gilead Sciences, GoldFinch Bio, and Johnson & Johnson.

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

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Alkelai, A., Greenbaum, L., Docherty, A.R. et al. The benefit of diagnostic whole genome sequencing in schizophrenia and other psychotic disorders. Mol Psychiatry 27, 1435–1447 (2022). https://doi.org/10.1038/s41380-021-01383-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-021-01383-9

This article is cited by

Search

Quick links