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:

One gene, many neuropsychiatric disorders: lessons from Mendelian diseases

Nature Neuroscience volume 17, pages 773–781 (2014)Cite this article

Subjects

Abstract

Recent human genetic studies have consistently shown that mutations in the same gene or same genomic region can increase the risk of a broad range of complex neuropsychiatric disorders. Despite the steadily increasing number of examples of such nonspecific effects on risk, the underlying biological causes remain mysterious. Here we investigate the phenomenon of such nonspecific risk by identifying Mendelian disease genes that are associated with multiple diseases and explore what is known about the underlying mechanisms in these more 'simple' examples. Our analyses make clear that there are a variety of mechanisms at work, emphasizing how challenging it will be to elucidate the causes of nonspecific risk in complex disease. Ultimately, we conclude that functional approaches will be critical for explaining the causes of nonspecific risk factors discovered by human genetic studies of neuropsychiatric disorders.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Figure 1: Nonspecific disease-causing genes that cause at least one Mendelian neurological disease.
Figure 2: Distribution of de novo mutations across controls and schizophrenia patients.
Figure 3: Venn diagram representing the overlap of genes affected by hot zone de novo mutations across four neuropsychiatric disorders.

Similar content being viewed by others

References

  1. Insel, T.R. & Landis, S.C. Twenty-five years of progress: the view from NIMH and NINDS. Neuron 80, 561–567 (2013).

    Article  CAS  PubMed  Google Scholar 

  2. Cross-Disorder Group of the Psychiatric Genomics Consoritum & Genetic Risk Outcome of Psychosis Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 381, 1371–1379 (2013). This is the first study showing that specific genetic variants are significantly associated with risk of different psychiatric disorders. By integrating genome-wide association study (GWAS) data of five different psychiatric disorders from multiple resources, this study uses statistical modeling strategies to convincingly demonstrate presence of nonspecific genetic risk factors in terms of both individual alleles and polygenic risk scores.

  3. Ruderfer, D.M. et al. Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia. Mol. Psychiatry published online, doi:10.1038/mp.2013.138 (November 26 2013).

    Article  CAS  PubMed  Google Scholar 

  4. Williams, H.J. et al. Fine mapping of ZNF804A and genome-wide significant evidence for its involvement in schizophrenia and bipolar disorder. Mol. Psychiatry 16, 429–441 (2011).

    Article  CAS  PubMed  Google Scholar 

  5. International Schizophrenia Consortium. et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).

  6. Cross-Disorder Group of the Psychiatric Genomics Consortium. et al. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat. Genet. 45, 984–994 (2013).

  7. Wray, N.R., Lee, S.H. & Kendler, K.S. Impact of diagnostic misclassification on estimation of genetic correlations using genome-wide genotypes. Eur. J. Hum. Genet. 20, 668–674 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Mefford, H.C. et al. Recurrent rearrangements of chromosome 1q21.1 and variable pediatric phenotypes. N. Engl. J. Med. 359, 1685–1699 (2008). This paper presents an excellent example of a rare, recurrent microdeletion associated with a wide spectrum of phenotypes including intellectual disability, microcephaly, cardiac abnormalities, and cataracts, emphasizing the importance of a genotype-based approach to clinical management of relevant patients.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Grayton, H.M., Fernandes, C., Rujescu, D. & Collier, D.A. Copy number variations in neurodevelopmental disorders. Prog. Neurobiol. 99, 81–91 (2012).

    Article  CAS  PubMed  Google Scholar 

  10. Bijlsma, E.K. et al. Extending the phenotype of recurrent rearrangements of 16p11.2: deletions in mentally retarded patients without autism and in normal individuals. Eur. J. Med. Genet. 52, 77–87 (2009).

    Article  CAS  PubMed  Google Scholar 

  11. Ben-Shachar, S. et al. Microdeletion 15q13.3: a locus with incomplete penetrance for autism, mental retardation, and psychiatric disorders. J. Med. Genet. 46, 382–388 (2009).

    Article  CAS  PubMed  Google Scholar 

  12. Morrow, E.M. Genomic copy number variation in disorders of cognitive development. J. Am. Acad. Child Adolesc. Psychiatry 49, 1091–1104 (2010).

    PubMed  PubMed Central  Google Scholar 

  13. Heinzen, E.L. et al. Rare deletions at 16p13.11 predispose to a diverse spectrum of sporadic epilepsy syndromes. Am. J. Hum. Genet. 86, 707–718 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ullmann, R. et al. Array CGH identifies reciprocal 16p13.1 duplications and deletions that predispose to autism and/or mental retardation. Hum. Mutat. 28, 674–682 (2007).

    Article  CAS  PubMed  Google Scholar 

  15. Bachmann-Gagescu, R. et al. Recurrent 200-kb deletions of 16p11.2 that include the SH2B1 gene are associated with developmental delay and obesity. Genet. Med. 12, 641–647 (2010).

    Article  PubMed  Google Scholar 

  16. Stefansson, H. et al. Large recurrent microdeletions associated with schizophrenia. Nature 455, 232–236 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Digilio, M.C. et al. Congenital heart defects in recurrent reciprocal 1q21.1 deletion and duplication syndromes: rare association with pulmonary valve stenosis. Eur. J. Med. Genet. 56, 144–149 (2013).

    Article  PubMed  Google Scholar 

  18. Rosenfeld, J.A. et al. Proximal microdeletions and microduplications of 1q21.1 contribute to variable abnormal phenotypes. Eur. J. Hum. Genet. 20, 754–761 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kirov, G. et al. Neurexin 1 (NRXN1) deletions in schizophrenia. Schizophr. Bull. 35, 851–854 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Rujescu, D. et al. Disruption of the neurexin 1 gene is associated with schizophrenia. Hum. Mol. Genet. 18, 988–996 (2009).

    Article  CAS  PubMed  Google Scholar 

  21. Friedman, J.I. et al. CNTNAP2 gene dosage variation is associated with schizophrenia and epilepsy. Mol. Psychiatry 13, 261–266 (2008).

    Article  CAS  PubMed  Google Scholar 

  22. Ching, M.S. et al. Deletions of NRXN1 (neurexin-1) predispose to a wide spectrum of developmental disorders. Am. J. Med. Genet. B. Neuropsychiatr. Genet. 153B, 937–947 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Gregor, A. et al. Expanding the clinical spectrum associated with defects in CNTNAP2 and NRXN1. BMC Med. Genet. 12, 106 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Iossifov, I. et al. De novo gene disruptions in children on the autistic spectrum. Neuron 74, 285–299 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Neale, B.M. et al. Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature 485, 242–245 (2012). This is one of the first studies using a trio design to investigate the contribution of de novo mutations to a complex neuropsychiatric disorder (autism spectrum disorder, ASD). Importantly, this study establishes an analysis framework to statistically assess whether individual genes harbor significantly more de novo mutation than expected by chance. This study indicates an important, but limited, role of de novo mutations in the pathogenesis of ASD.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. O′Roak, B.J. et al. Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. Nature 485, 246–250 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Sanders, S.J. et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 485, 237–241 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. de Ligt, J. et al. Diagnostic exome sequencing in persons with severe intellectual disability. N. Engl. J. Med. 367, 1921–1929 (2012).

    Article  CAS  PubMed  Google Scholar 

  29. Rauch, A. et al. Range of genetic mutations associated with severe non-syndromic sporadic intellectual disability: an exome sequencing study. Lancet 380, 1674–1682 (2012).

    Article  CAS  PubMed  Google Scholar 

  30. Xu, B. et al. De novo gene mutations highlight patterns of genetic and neural complexity in schizophrenia. Nat. Genet. 44, 1365–1369 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Epi4K Consortium. et al. De novo mutations in epileptic encephalopathies. Nature 501, 217–221 (2013). This is the first study that comprehensively investigates the contribution of de novo mutations to epileptic encephalopathies (EE), a spectrum of devastating neurodevelopmental disorders that can overlap with ASD and/or intellectual disability (ID) in clinical presentation. Using statistical modeling, this study clearly implicates de novo mutations as genetic risk factors of EE in both individual genes and the group of ∼4,000 genes that are most intolerant to functional genetic variation.

  32. Sullivan, P.F., Daly, M.J. & O′Donovan, M. Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat. Rev. Genet. 13, 537–551 (2012). This paper provides an elegant review on genetic architectures of nine major neuropsychiatric disorders, based on discoveries from GWASs and structural variation studies.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Goldstein, D.B. et al. Sequencing studies in human genetics: design and interpretation. Nat. Rev. Genet. 14, 460–470 (2013). This paper provides an overview of implementation issues for sequencing study design, sequence data generation, variant discovery and prioritization, statistical analysis and interpretation, and functional evaluation of candidate variants along with genetic evidence to assess pathogenicity. This review introduces the idea of the 'narrative potential' inherent in sequence data and advocates for the importance of appropriate statistical criteria to secure genetic discoveries.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Stessman, H.A., Bernier, R. & Eichler, E.E. A genotype-first approach to defining the subtypes of a complex disease. Cell 156, 872–877 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. McKusick, V.A. Phenotypic diversity of human diseases resulting from allelic series. Am. J. Hum. Genet. 25, 446–456 (1973).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Stearns, F.W. One hundred years of pleiotropy: a retrospective. Genetics 186, 767–773 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Mackay, T.F. Epistasis and quantitative traits: using model organisms to study gene-gene interactions. Nat. Rev. Genet. 15, 22–33 (2014).

    Article  CAS  PubMed  Google Scholar 

  38. Online Mendelian Inheritance in Man. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University http://omim.org/ (accessed 2 September 2013).

  39. Gibbons, R.J. & Higgs, D.R. Molecular-clinical spectrum of the ATR-X syndrome. Am. J. Med. Genet. 97, 204–212 (2000).

    Article  CAS  PubMed  Google Scholar 

  40. Badens, C. et al. Mutations in PHD-like domain of the ATRX gene correlate with severe psychomotor impairment and severe urogenital abnormalities in patients with ATRX syndrome. Clin. Genet. 70, 57–62 (2006).

    Article  CAS  PubMed  Google Scholar 

  41. Revesz, T. et al. Genetics and molecular pathogenesis of sporadic and hereditary cerebral amyloid angiopathies. Acta Neuropathol. 118, 115–130 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Heinzen, E.L. et al. De novo mutations in ATP1A3 cause alternating hemiplegia of childhood. Nat. Genet. 44, 1030–1034 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Caputo, V. et al. A restricted spectrum of mutations in the SMAD4 tumor-suppressor gene underlies Myhre syndrome. Am. J. Hum. Genet. 90, 161–169 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Le Goff, C. et al. Mutations at a single codon in Mad homology 2 domain of SMAD4 cause Myhre syndrome. Nat. Genet. 44, 85–88 (2012).

    Article  CAS  Google Scholar 

  45. Blencowe, B.J. Alternative splicing: new insights from global analyses. Cell 126, 37–47 (2006).

    Article  CAS  PubMed  Google Scholar 

  46. Shekarabi, M. et al. Mutations in the nervous system–specific HSN2 exon of WNK1 cause hereditary sensory neuropathy type II. J. Clin. Invest. 118, 2496–2505 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Wilson, F.H. et al. Human hypertension caused by mutations in WNK kinases. Science 293, 1107–1112 (2001).

    Article  CAS  PubMed  Google Scholar 

  48. Gulsuner, S. et al. Spatial and temporal mapping of de novo mutations in schizophrenia to a fetal prefrontal cortical network. Cell 154, 518–529 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Willsey, A.J. et al. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell 155, 997–1007 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Parikshak, N.N. et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155, 1008–1021 (2013). This is one of the most successful studies mapping genes implicated by exome-based de novo mutation screens onto temporally and spatially resolved human brain transcriptomes. Notably, this study shows strong connections among the genes implicated in ASD in terms of developmental and spatial specificity, indicating involvement of specific brain circuits in the pathogenesis of ASD.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Ichinose, H. et al. Hereditary progressive dystonia with marked diurnal fluctuation caused by mutations in the GTP cyclohydrolase I gene. Nat. Genet. 8, 236–242 (1994).

    Article  CAS  PubMed  Google Scholar 

  52. Furukawa, Y. et al. Dystonia with motor delay in compound heterozygotes for GTP-cyclohydrolase I gene mutations. Ann. Neurol. 44, 10–16 (1998).

    Article  CAS  PubMed  Google Scholar 

  53. Koch, J. et al. Molecular cloning and characterization of a full-length complementary DNA encoding human acid ceramidase. Identification Of the first molecular lesion causing Farber disease. J. Biol. Chem. 271, 33110–33115 (1996).

    Article  CAS  PubMed  Google Scholar 

  54. Zhou, J. et al. Spinal muscular atrophy associated with progressive myoclonic epilepsy is caused by mutations in ASAH1. Am. J. Hum. Genet. 91, 5–14 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Otto, E.A. et al. Hypomorphic mutations in meckelin (MKS3/TMEM67) cause nephronophthisis with liver fibrosis (NPHP11). J. Med. Genet. 46, 663–670 (2009).

    Article  CAS  PubMed  Google Scholar 

  56. Mercuri, E. et al. Congenital muscular dystrophies with defective glycosylation of dystroglycan: a population study. Neurology 72, 1802–1809 (2009).

    Article  CAS  PubMed  Google Scholar 

  57. Kanai, K. et al. Physicochemical property changes of amino acid residues that accompany missense mutations in SCN1A affect epilepsy phenotype severity. J. Med. Genet. 46, 671–679 (2009).

    Article  CAS  PubMed  Google Scholar 

  58. Waxman, S.G. & Dib-Hajj, S.D. Erythromelalgia: a hereditary pain syndrome enters the molecular era. Ann. Neurol. 57, 785–788 (2005).

    Article  PubMed  Google Scholar 

  59. Cox, J.J. et al. An SCN9A channelopathy causes congenital inability to experience pain. Nature 444, 894–898 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. de Brouwer, A.P. et al. PRPS1 mutations: four distinct syndromes and potential treatment. Am. J. Hum. Genet. 86, 506–518 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Frischmeyer, P.A. & Dietz, H.C. Nonsense-mediated mRNA decay in health and disease. Hum. Mol. Genet. 8, 1893–1900 (1999).

    Article  CAS  PubMed  Google Scholar 

  62. Malan, V. et al. Distinct effects of allelic NFIX mutations on nonsense-mediated mRNA decay engender either a Sotos-like or a Marshall-Smith syndrome. Am. J. Hum. Genet. 87, 189–198 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Khajavi, M. et al. Curcumin treatment abrogates endoplasmic reticulum retention and aggregation-induced apoptosis associated with neuropathy-causing myelin protein zero-truncating mutants. Am. J. Hum. Genet. 77, 841–850 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Inoue, K. et al. Molecular mechanism for distinct neurological phenotypes conveyed by allelic truncating mutations. Nat. Genet. 36, 361–369 (2004).

    Article  CAS  PubMed  Google Scholar 

  65. Nelson, D.L., Orr, H.T. & Warren, S.T. The unstable repeats–three evolving faces of neurological disease. Neuron 77, 825–843 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. La Spada, A.R., Wilson, E.M., Lubahn, D.B., Harding, A.E. & Fischbeck, K.H. Androgen receptor gene mutations in X-linked spinal and bulbar muscular atrophy. Nature 352, 77–79 (1991).

    Article  CAS  PubMed  Google Scholar 

  67. Parvari, R. et al. Mutation of TBCE causes hypoparathyroidism-retardation-dysmorphism and autosomal recessive Kenny-Caffey syndrome. Nat. Genet. 32, 448–452 (2002).

    Article  CAS  PubMed  Google Scholar 

  68. Johnson, J.O. et al. Exome sequencing reveals VCP mutations as a cause of familial ALS. Neuron 68, 857–864 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Tran-Viet, K.N. et al. Mutations in SCO2 are associated with autosomal-dominant high-grade myopia. Am. J. Hum. Genet. 92, 820–826 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Parsons, D.W. et al. Intragenic telSMN mutations: frequency, distribution, evidence of a founder effect, and modification of the spinal muscular atrophy phenotype by cenSMN copy number. Am. J. Hum. Genet. 63, 1712–1723 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Lupski, J.R., Belmont, J.W., Boerwinkle, E. & Gibbs, R.A. Clan genomics and the complex architecture of human disease. Cell 147, 32–43 (2011). This paper proposes a unified genetic model for human morbidities, highlighting the role of recent mutations. There is an instructive discussion on genetic relationships between Mendelian and complex diseases.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Nadeau, J.H. Modifier genes in mice and humans. Nat. Rev. Genet. 2, 165–174 (2001).

    Article  CAS  PubMed  Google Scholar 

  73. Wong, A.H., Gottesman, I.I. & Petronis, A. Phenotypic differences in genetically identical organisms: the epigenetic perspective. Hum. Mol. Genet. 14, R11–R18 (2005).

    Article  CAS  PubMed  Google Scholar 

  74. Raj, A., Rifkin, S.A., Andersen, E. & van Oudenaarden, A. Variability in gene expression underlies incomplete penetrance. Nature 463, 913–918 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Burga, A. & Lehner, B. Beyond genotype to phenotype: why the phenotype of an individual cannot always be predicted from their genome sequence and the environment that they experience. FEBS J. 279, 3765–3775 (2012).

    Article  CAS  PubMed  Google Scholar 

  76. Tsankova, N., Renthal, W., Kumar, A. & Nestler, E.J. Epigenetic regulation in psychiatric disorders. Nat. Rev. Neurosci. 8, 355–367 (2007).

    Article  CAS  PubMed  Google Scholar 

  77. Jiang, Y.H., Bressler, J. & Beaudet, A.L. Epigenetics and human disease. Annu. Rev. Genomics Hum. Genet. 5, 479–510 (2004).

    Article  CAS  PubMed  Google Scholar 

  78. Chess, A. Random and non-random monoallelic expression. Neuropsychopharmacology 38, 55–61 (2013).

    Article  CAS  PubMed  Google Scholar 

  79. Antonellis, A. et al. Glycyl tRNA synthetase mutations in Charcot-Marie-Tooth disease type 2D and distal spinal muscular atrophy type V. Am. J. Hum. Genet. 72, 1293–1299 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. White, J.K. et al. Genome-wide generation and systematic phenotyping of knockout mice reveals new roles for many genes. Cell 154, 452–464 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Bilgüvar, K. et al. Whole-exome sequencing identifies recessive WDR62 mutations in severe brain malformations. Nature 467, 207–210 (2010). This paper demonstrates a mutation associated with a broad spectrum of malformations of cortical development that have been recognized as distinct in pathogenesis.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. McCarroll, S.A. & Hyman, S.E. Progress in the genetics of polygenic brain disorders: significant new challenges for neurobiology. Neuron 80, 578–587 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Blair, D.R. et al. A nondegenerate code of deleterious variants in mendelian Loci contributes to complex disease risk. Cell 155, 70–80 (2013). This is the first study that systematically examines the correlation between Mendelian and complex diseases. By mining medical records over 110 million patients, the study identifies widespread comorbidity between Mendelian-Mendelian and Mendelian-complex disease pairs. The analysis also highlights the effect of genetic interactions in both Mendelian and complex diseases.

    Article  CAS  PubMed  Google Scholar 

  84. Darnell, J.C. et al. FMRP stalls ribosomal translocation on mRNAs linked to synaptic function and autism. Cell 146, 247–261 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Fromer, M. et al. De novo mutations in schizophrenia implicate synaptic networks. Nature 506, 179–184 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Petrovski, S., Wang, Q., Heinzen, E.L., Allen, A.S. & Goldstein, D.B. Genic intolerance to functional variation and the interpretation of personal genomes. PLoS Genet. 9, e1003709 (2013). This study provides the first comprehensive gene prioritization scoring system based on human population genetic data. The basic approach is to predict common functional variation using total variation in a regression framework, thereby identifying genes that are intolerant to functional genetic variation and therefore likely under purifying selection. The authors showed that intolerant genes are much more likely to cause neurodevelopmental disorders than tolerant genes.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Adzhubei, I.A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Zaidi, S. et al. De novo mutations in histone-modifying genes in congenital heart disease. Nature 498, 220–223 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Girard, S.L. et al. Increased exonic de novo mutation rate in individuals with schizophrenia. Nat. Genet. 43, 860–863 (2011).

    Article  CAS  PubMed  Google Scholar 

  90. Cutting, G.R. Modifier genes in Mendelian disorders: the example of cystic fibrosis. Ann. NY Acad. Sci. 1214, 57–69 (2010). This paper provides an elegant review on genetic modifiers in Mendelian disorders, based on the well-studied example of cystic fibrosis.

    Article  CAS  PubMed  Google Scholar 

  91. Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Hou, Z. et al. Efficient genome engineering in human pluripotent stem cells using Cas9 from Neisseria meningitidis. Proc. Natl. Acad. Sci. USA 110, 15644–15649 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Spira, M.E. & Hai, A. Multi-electrode array technologies for neuroscience and cardiology. Nat. Nanotechnol. 8, 83–94 (2013).

    Article  CAS  PubMed  Google Scholar 

  94. Venkatachalam, V. et al. Flash memory: photochemical imprinting of neuronal action potentials onto a microbial rhodopsin. J. Am. Chem. Soc. 136, 2529–2537 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center for Human Genome Variation, Duke University School of Medicine, Durham, North Carolina, USA

    Xiaolin Zhu, Anna C Need, Slavé Petrovski & David B Goldstein

  2. Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK

    Anna C Need

  3. Department of Medicine, The University of Melbourne, Austin Health and Royal Melbourne Hospital, Melbourne, Victoria, Australia

    Slavé Petrovski

Authors
  1. Xiaolin Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anna C Need
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Slavé Petrovski
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. David B Goldstein
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David B Goldstein.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Table 1

Examples of genes associated with more than one Mendelian disease with literature supporting a relevant mechanism (XLSX 12 kb)

Supplementary Table 2

Schizophrenia ascertained “hot zone” de novo mutations from four schizophrenia trio sequencing studies (ref. 31, 48, 85, 89). The “hot zone” being defined as residual variation intolerance score (RVIS) ≤ 25% and variant-level PolyPhen-2 quantitative score2 ≥ 0.95 (ref. 86). (XLSX 28 kb)

Glossary

Genome-wide association study (GWAS)

A genome-wide association study (GWAS) is an unbiased screen of the genome for genetic variants that present at different frequencies in affected and unaffected individuals, that is, that associate with a phenotype. Although either rare or common variants can now be studied and analyzed for association in a genome-wide way, GWAS has historically referred to a specific, early type of genome-wide study in which a genome-wide set of common polymorphisms (single nucleotide polymorphisms) is analyzed using microarray-based technologies to find disease-associated common alleles.

Polygenic

Polygenic is a term meaning "many genes". A polygenic phenotype is influenced by more than one gene and can refer to common variants with small effects or rare variants with larger effects.

Single-nucleotide polymorphism (SNP)

A single-nucleotide polymorphism (SNP) is a single base-pair position in the genome that varies between members of a species. The terms polymorphism and SNP generally refer to sequence variations that segregate in a population at an allele frequency of at least 1%.

Copy number variation (CNV)

A common-variant association study (CVAS) is a genome-wide association study to find common variants that present at different allele frequencies in affected and unaffected individuals. The term CVAS has recently been proposed as a replacement for the term GWAS, as rare-variant association studies are also association studies and are also genome wide.

Exome

The exome is the part of a genome that encodes proteins, approximately 1% of the human genome.

Trio family study

A trio family study is an analysis of probands and both of their parents. Sequencing-based trio studies often focus on de novo mutations that are present in the proband's genome, but are not detected in the genomes of his or her parents.

Proband

A proband is an individual being studied or reported on. The term is often used to refer to an individual affected with a disease or disorder, as distinct from their unaffected relatives.

De novo mutation (DNM)

A de novo mutation (DNM) is a mutation that is part of an individual's genome that is not detected in the genome of either parent (although it may have arisen from a mutation in the parental germline). With the exception of de novo mutations in monozygotic twins, or those shared by siblings as a result of germline mosaicism, most new mutations are not shared by relatives and do not contribute to heritability estimates.

Pleiotropy

Pleiotropy is the phenomenon whereby a genetic variant influences variation in more than one trait or disease.

Locus

A locus is a place on a chromosome. A locus may contain one gene, multiple genes or no genes at all.

Allele

An allele is one of a number of alternative forms of a gene or locus. The minor allele is the less frequent allele at a locus and the major allele is the more frequent allele.

Next generation sequencing (NGS)

Next generation sequencing (NGS) refers to a set of technologies that sequence DNA in massively parallel ways; for example, by optically detecting the incorporation of specific bases into millions of different DNA molecules, spatially segregated on an imageable glass surface, at the same time.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, X., Need, A., Petrovski, S. et al. One gene, many neuropsychiatric disorders: lessons from Mendelian diseases. Nat Neurosci 17, 773–781 (2014). https://doi.org/10.1038/nn.3713

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn.3713

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research