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.

Psychiatric genetics and the structure of psychopathology

A Correction to this article was published on 14 March 2018

This article has been updated

Abstract

For over a century, psychiatric disorders have been defined by expert opinion and clinical observation. The modern DSM has relied on a consensus of experts to define categorical syndromes based on clusters of symptoms and signs, and, to some extent, external validators, such as longitudinal course and response to treatment. In the absence of an established etiology, psychiatry has struggled to validate these descriptive syndromes, and to define the boundaries between disorders and between normal and pathologic variation. Recent advances in genomic research, coupled with large-scale collaborative efforts like the Psychiatric Genomics Consortium, have identified hundreds of common and rare genetic variations that contribute to a range of neuropsychiatric disorders. At the same time, they have begun to address deeper questions about the structure and classification of mental disorders: To what extent do genetic findings support or challenge our clinical nosology? Are there genetic boundaries between psychiatric and neurologic illness? Do the data support a boundary between disorder and normal variation? Is it possible to envision a nosology based on genetically informed disease mechanisms? This review provides an overview of conceptual issues and genetic findings that bear on the relationships among and boundaries between psychiatric disorders and other conditions. We highlight implications for the evolving classification of psychopathology and the challenges for clinical translation.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1

Change history

  • 14 March 2018

    In the Table 1 legend, the reference numbers and symbols were not correctly presented in the footnotes. The corrected footnotes are presented below.

References

  1. 1.

    American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-5. 5th edn. Arlington, VA: American Psychiatric Association; 2013., xliv, p. 947.

  2. 2.

    Rudin E. Studien uber Vererbung und entstehung geistiger Storungen. I. Zur vererbung und neuentstehung der Dementia praecox (Studies on the inheritance and origin of mental illness. I. The problem of the inheritance and primary origin of dementia praecox). Monographien aus dem Gesamtgebiet der Neurologie und Psychiatrie, Number 12. Berlin: Springer; 1916.

  3. 3.

    Luxenburger H. Vorlaufiger Bericht uder psychiatrische Serienuntersuchungen und Zwillingen. Z Gesamt Neurol Psychiatr. 1928;116:297–326.

    Google Scholar 

  4. 4.

    Heston LL. Psychiatric disorder in foster home reared children of schizophrenic mothers. Br J Psychiatry. 1966;112:819–25.

    CAS  Google Scholar 

  5. 5.

    Kendler KS, Eaves LJ. Psychiatric genetics, review of psychiatry, Vol 24. Arlington, VA: American Psychiatric Publishing, Inc.; 2005.

  6. 6.

    Kendler KS. Twin studies of psychiatric illness: an update. Arch Gen Psychiatry. 2001;58:1005–14.

    CAS  Google Scholar 

  7. 7.

    Kendler KS, Prescott CA, Myers J, Neale MC. The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Arch Gen Psychiatry. 2003;60:929–37.

    Google Scholar 

  8. 8.

    Kety SS. The significance of genetic factors in the etiology of schizophrenia: results from the national study of adoptees in Denmark. J Psychiatr Res. 1987;21:423–9.

    CAS  Google Scholar 

  9. 9.

    Sprich S, Biederman J, Crawford MH, Mundy E, Faraone SV. Adoptive and biological families of children and adolescents with ADHD. J Am Acad Child Adolesc Psychiatry. 2000;39:1432–7.

    CAS  Google Scholar 

  10. 10.

    Verhulst B, Neale MC, Kendler KS. The heritability of alcohol use disorders: a meta-analysis of twin and adoption studies. Psychol Med. 2015;45:1061–72.

    CAS  Google Scholar 

  11. 11.

    Kendler KS, Aggen SH, Knudsen GP, Roysamb E, Neale MC, Reichborn-Kjennerud T. The structure of genetic and environmental risk factors for syndromal and subsyndromal common DSM-IV axis I and all axis II disorders. Am J Psychiatry. 2011;168:29–39.

    Google Scholar 

  12. 12.

    Purcell SM, Wray NR, Stone JL, Visscher PM, O’Donovan MC, et al. International Schizophrenia Consortium Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009;460:748–52.

    CAS  Google Scholar 

  13. 13.

    Stefansson H, Ophoff RA, Steinberg S, Andreassen OA, Cichon S, Rujescu D, et al. Common variants conferring risk of schizophrenia. Nature. 2009;460:744–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Stefansson H, Rujescu D, Cichon S, Pietilainen OP, Ingason A, Steinberg S, et al. Large recurrent microdeletions associated with schizophrenia. Nature. 2008;455:232–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    International Schizophrenia Consortium. Rare chromosomal deletions and duplications increase risk of schizophrenia. Nature. 2008;455:237–41.

    Google Scholar 

  16. 16.

    Psychiatric GWAS Consortium Coordinating Committee. Genomewide association studies: history, rationale, and prospects for psychiatric disorders. Am J Psychiatry. 2009;166:540–56.

    Google Scholar 

  17. 17.

    Visscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, et al. 10 Years of GWAS Discovery: biology, function, and translation. Am J Hum Genet. 2017;101:5–22.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

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

    Google Scholar 

  19. 19.

    Wray NR, Lee SH, Mehta D, Vinkhuyzen AA, Dudbridge F, Middeldorp CM. Research review: Polygenic methods and their application to psychiatric traits. J Child Psychol Psychiatry. 2014;55:1068–87.

    Google Scholar 

  20. 20.

    Otowa T, Hek K, Lee M, Byrne EM, Mirza SS, Nivard MG, et al. Meta-analysis of genome-wide association studies of anxiety disorders. Mol Psychiatry. 2016;21:1485.

    CAS  Google Scholar 

  21. 21.

    Duncan LE, Ratanatharathorn A, Aiello AE, Almli LM, Amstadter AB, Ashley-Koch AE et al. Largest GWAS of PTSD (N = 20 070) yields genetic overlap with schizophrenia and sex differences in heritability. Mol Psychiatry. 2017 Apr 25. doi:10.1038/mp.2017.77. [Epub ahead of print].

    PubMed  PubMed Central  Google Scholar 

  22. 22.

    Cross-Disorder Group of the Psychiatric Genomics C, Lee SH, Ripke S, Neale BM, Faraone SV, Purcell SM, et al. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet. 2013;45:984–94.

    Google Scholar 

  23. 23.

    Charney AW, Ruderfer DM, Stahl EA, Moran JL, Chambert K, Belliveau RA, et al. Evidence for genetic heterogeneity between clinical subtypes of bipolar disorder. Transl Psychiatry. 2017;7:e993.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    CNV Schizophrenia Working Groups of the Psychiatric Genomics Consortium. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat Genet. 2017;49:27–35.

    Google Scholar 

  25. 25.

    Genovese G, Fromer M, Stahl EA, Ruderfer DM, Chambert K, Landen M, et al. Increased burden of ultra-rare protein-altering variants among 4877 individuals with schizophrenia. Nat Neurosci. 2016;19:1433–41.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

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

    Google Scholar 

  27. 27.

    Willsey AJ, Fernandez TV, Yu D, King RA, Dietrich A, Xing J, et al. De novo coding variants are strongly associated with Tourette disorder. Neuron. 2017;94:486–99. e489

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Vorstman JA, Parr JR, Moreno-De-Luca D, Anney RJ, Nurnberger JI Jr., Hallmayer JF. Autism genetics: opportunities and challenges for clinical translation. Nat Rev Genet. 2017;18:362–76.

    CAS  Google Scholar 

  29. 29.

    de la Torre-Ubieta L, Won H, Stein JL, Geschwind DH. Advancing the understanding of autism disease mechanisms through genetics. Nat Med. 2016;22:345–61.

    PubMed  PubMed Central  Google Scholar 

  30. 30.

    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.

    CAS  Google Scholar 

  31. 31.

    Solovieff N, Cotsapas C, Lee PH, Purcell SM, Smoller JW. Pleiotropy in complex traits: challenges and strategies. Nat Rev Genet. 2013;14:483–95.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Malhotra D, Sebat J. CNVs: harbingers of a rare variant revolution in psychiatric genetics. Cell. 2012;148:1223–41.

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Tesli M, Espeseth T, Bettella F, Mattingsdal M, Aas M, Melle I, et al. Polygenic risk score and the psychosis continuum model. Acta Psychiatr Scand. 2014;130:311–7.

    CAS  Google Scholar 

  34. 34.

    Hatzimanolis A, Bhatnagar P, Moes A, Wang R, Roussos P, Bitsios P, et al. Common genetic variation and schizophrenia polygenic risk influence neurocognitive performance in young adulthood. Am J Med Genet B Neuropsychiatr Genet. 2015;168:392–401.

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    McIntosh AM, Gow A, Luciano M, Davies G, Liewald DC, Harris SE, et al. Polygenic risk for schizophrenia is associated with cognitive change between childhood and old age. Biol Psychiatry. 2013;73:938–43.

    Google Scholar 

  36. 36.

    Roussos P, Giakoumaki SG, Zouraraki C, Fiullard JF, Karagiorga V-E, Tsapakis E-M, et al. The relationship of common risk variants and polygenic risk for schizophrenia to sensorimotor gating. Biol Psychiatry. 2016;79:988–96.

    Google Scholar 

  37. 37.

    Kauppi K, Westlye LT, Tesli M, Bettella F, Brandt CL, Mattingsdal M, et al. Polygenic risk for schizophrenia associated with working memory-related prefrontal brain activation in patients with schizophrenia and healthy controls. Schizophr Bull. 2015;41:736–43.

    Google Scholar 

  38. 38.

    Riglin L, Collishaw S, Richards A, Thapar AK, Maughan B, O’Donovan MC, et al. Schizophrenia risk alleles and neurodevelopmental outcomes in childhood: a population-based cohort study. Lancet Psychiatry. 2017;4:57–62.

    Google Scholar 

  39. 39.

    Cross Disorder Group of the Psychiatric GWAS Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet. 2013;381:1371–9.

    Google Scholar 

  40. 40.

    Nivard MG, Gage SH, Hottenga JJ, van Beijsterveldt CE, Abdellaoui A, Bartels M, et al. Genetic overlap between schizophrenia and developmental psychopathology: longitudinal and multivariate polygenic risk prediction of common psychiatric traits during development. Schizophr Bull. 2017;43:1197–207.

    PubMed  PubMed Central  Google Scholar 

  41. 41.

    Jones HJ, Stergiakouli E, Tansey KE, Hubbard L, Heron J, Cannon M, et al. Phenotypic manifestation of genetic risk for schizophrenia during adolescence in the general population. JAMA Psychiatry. 2016;73:221–8.

    PubMed  PubMed Central  Google Scholar 

  42. 42.

    Lo MT, Hinds DA, Tung JY, Franz C, Fan CC, Wang Y, et al. Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders. Nat Genet. 2017;49:152–6.

    CAS  Google Scholar 

  43. 43.

    Zheng J, Erzurumluoglu AM, Elsworth BL, Kemp JP, Howe L, Haycock PC, et al. LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics. 2017;33:272–9.

    CAS  PubMed  Google Scholar 

  44. 44.

    Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium. Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways. Nat Neurosci. 2015;18:199–209.

    Google Scholar 

  45. 45.

    Sekar A, Bialas AR, de Rivera H, Davis A, Hammond TR, Kamitaki N, et al. Schizophrenia risk from complex variation of complement component 4. Nature. 2016;530:177–83.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Devor A, Andreassen OA, Wang Y, Maki-Marttunen T, Smeland OB, Fan CC, et al. Genetic evidence for role of integration of fast and slow neurotransmission in schizophrenia. Mol Psychiatry. 2017;22:792–801.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Gandal MJ, Leppa V, Won H, Parikshak NN, Geschwind DH. The road to precision psychiatry: translating genetics into disease mechanisms. Nat Neurosci. 2016;19:1397–407.

    CAS  Google Scholar 

  48. 48.

    Breen G, Li Q, Roth BL, O’Donnell P, Didriksen M, Dolmetsch R, et al. Translating genome-wide association findings into new therapeutics for psychiatry. Nat Neurosci. 2016;19:1392–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Kathiresan S. Developing medicines that mimic the natural successes of the human genome: lessons from NPC1L1, HMGCR, PCSK9, APOC3, and CETP. J Am Coll Cardiol. 2015;65:1562–6.

    Google Scholar 

  50. 50.

    Lahey BB, Applegate B, Hakes JK, Zald DH, Hariri AR, Rathouz PJ. Is there a general factor of prevalent psychopathology during adulthood? J Abnorm Psychol. 2012;121:971–7.

    PubMed  PubMed Central  Google Scholar 

  51. 51.

    Kerekes N, Brandstrom S, Lundstrom S, Rastam M, Nilsson T, Anckarsater H. ADHD, autism spectrum disorder, temperament, and character: phenotypical associations and etiology in a Swedish childhood twin study. Compr Psychiatry. 2013;54:1140–7.

    Google Scholar 

  52. 52.

    Plomin R, Haworth CM, Davis OS. Common disorders are quantitative traits. Nat Rev Genet. 2009;10:872–8.

    CAS  Google Scholar 

  53. 53.

    Larsson H, Anckarsater H, Rastam M, Chang Z, Lichtenstein P. Childhood attention-deficit hyperactivity disorder as an extreme of a continuous trait: a quantitative genetic study of 8500 twin pairs. J Child Psychol Psychiatry. 2012;53:73–80.

    Google Scholar 

  54. 54.

    Clarke TK, Lupton MK, Fernandez-Pujals AM, Starr J, Davies G, Cox S, et al. Common polygenic risk for autism spectrum disorder (ASD) is associated with cognitive ability in the general population. Mol Psychiatry. 2016;21:419–25.

    Google Scholar 

  55. 55.

    Groen-Blokhuis MM, Middeldorp CM, Kan KJ, Abdellaoui A, van Beijsterveldt CE, Ehli EA, et al. Attention-deficit/hyperactivity disorder polygenic risk scores predict attention problems in a population-based sample of children. J Am Acad Child Adolesc Psychiatry. 2014;53:1123–9. e1126

    Google Scholar 

  56. 56.

    Robinson EB, St Pourcain B, Anttila V, Kosmicki JA, Bulik-Sullivan B, Grove J, et al. Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population. Nat Genet. 2016;48:552–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Germine L, Robinson EB, Smoller JW, Calkins ME, Moore TM, Hakonarson H, et al. Association between polygenic risk for schizophrenia, neurocognition and social cognition across development. Transl Psychiatry. 2016;6:e924.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Insel T, Cuthbert B, Garvey M, Heinssen R, Pine DS, Quinn K, et al. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am J Psychiatry. 2010;167:748–51.

    Google Scholar 

  59. 59.

    Insel TR Director’s Blog: Transforming diagnosis. https://www.nimh.nih.gov/about/directors/thomas-insel/blog/2013/transforming-diagnosis.shtml. 2013.

  60. 60.

    Hyman SE. The diagnosis of mental disorders: the problem of reification. Annu Rev Clin Psychol. 2010;6:12.11–25.

    Google Scholar 

  61. 61.

    Kendler KS. Levels of explanation in psychiatric and substance use disorders: implications for the development of an etiologically based nosology. Mol Psychiatry. 2012;17:11–21.

    CAS  Google Scholar 

  62. 62.

    Duncan L, Yilmaz Z, Gaspar H, Walters R, Goldstein J, Anttila V, et al. Significant locus and metabolic genetic correlations revealed in genome-wide association study of anorexia nervosa. Am J Psychiatry. 2017;174:850–8.

    PubMed  PubMed Central  Google Scholar 

  63. 63.

    Robins E, Guze S. Establishment of diagnostic validity in psychiatric illness: its application to schizophrenia. Am J Psychiatry. 1970;126:983–7.

    CAS  Google Scholar 

  64. 64.

    Kendler KS. Toward a scientific psychiatric nosology. Strengths and limitations. Arch Gen Psychiatry. 1990;47:969–73.

    CAS  Google Scholar 

  65. 65.

    Tsuang M, Faraone S, Lyons M. Identification of the phenotype in psychiatric genetics. Eur Arch Psychiatry Clin Neurosci. 1993;243:131–42.

    CAS  Google Scholar 

  66. 66.

    Kendler KS. Reflections on the relationship between psychiatric genetics and psychiatric nosology. Am J Psychiatry. 2006;163:1138–46.

    Google Scholar 

  67. 67.

    Kendler KS. An historical framework for psychiatric nosology. Psychol Med. 2009;39:1935–41.

    PubMed  PubMed Central  Google Scholar 

  68. 68.

    Scassellati C, Bonvicini C, Faraone SV, Gennarelli M. Biomarkers and attention-deficit/hyperactivity disorder: a systematic review and meta-analyses. J Am Acad Child Adolesc Psychiatry. 2012;51:1003–19. e1020

    Google Scholar 

  69. 69.

    Okser S, Pahikkala T, Airola A, Salakoski T, Ripatti S, Aittokallio T. Regularized machine learning in the genetic prediction of complex traits. PLoS Genet. 2014;10:e1004754.

    PubMed  PubMed Central  Google Scholar 

  70. 70.

    Wray NR, Yang J, Hayes BJ, Price AL, Goddard ME, Visscher PM. Pitfalls of predicting complex traits from SNPs. Nat Rev Genet. 2013;14:507–15.

    CAS  PubMed  PubMed Central  Google Scholar 

  71. 71.

    Levinson DF, Mostafavi S, Milaneschi Y, Rivera M, Ripke S, Wray NR, et al. Genetic studies of major depressive disorder: why are there no genome-wide association study findings and what can we do about it? Biol Psychiatry. 2014;76:510–2.

    PubMed  PubMed Central  Google Scholar 

  72. 72.

    Holland D, Wang Y, Thompson WK, Schork A, Chen CH, Lo MT, et al. Estimating effect sizes and expected replication probabilities from GWAS summary statistics. Front Genet. 2016;7:15.

    PubMed  PubMed Central  Google Scholar 

  73. 73.

    Zuk O, Schaffner SF, Samocha K, Do R, Hechter E, Kathiresan S, et al. Searching for missing heritability: designing rare variant association studies. Proc Natl Acad Sci USA. 2014;111:E455–464.

    CAS  Google Scholar 

  74. 74.

    Moutsianas L, Agarwala V, Fuchsberger C, Flannick J, Rivas MA, Gaulton KJ, et al. The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease. PLoS Genet. 2015;11:e1005165.

    PubMed  PubMed Central  Google Scholar 

  75. 75.

    Sullivan PF, Agrawal A, Bulik CM, Andreassen OA, Borglum A, Breen G et al. Psychiatric genomics: an update and an agenda. BiorXiv. 2017. https://doi.org/10.1101/115600.

  76. 76.

    Boyle EA, Li YI, Pritchard JK. An expanded view of complex traits: from polygenic to omnigenic. Cell. 2017;169:1177–86.

    CAS  PubMed  PubMed Central  Google Scholar 

  77. 77.

    Anttila V, Bulik-Sullivan B, Finucane H, Bras J, Duncan L, Escott-Price V et al. Analysis of shared heritability in common disorders of the brain. BioRXiv. 2017. https://doi.org/10.1101/048991.

  78. 78.

    Smoller JW. The use of electronic health records for psychiatric phenotyping and genomics. Am J Med Genet B Neuropsychiatr Genet. 2017 May 30. doi:10.1002/ajmg.b.32548. [Epub ahead of print].

    Google Scholar 

  79. 79.

    Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12:e1001779.

    PubMed  PubMed Central  Google Scholar 

  80. 80.

    Precision Medicine Initiative (PMI) Working Group. The Precision Medicine Initiative Cohort Program—Building a Research Foundation for 21st Century Medicine September 17, 2015. https://www.nih.gov/sites/default/files/research-training/initiatives/pmi/pmi-working-group-report-20150917-2.pdf.

  81. 81.

    Bush WS, Oetjens MT, Crawford DC. Unravelling the human genome-phenome relationship using phenome-wide association studies. Nat Rev Genet. 2016;17:129–45.

    CAS  Google Scholar 

  82. 82.

    Riglin L, Collishaw S, Thapar AK, Dalsgaard S, Langley K, Smith GD, et al. Association of Genetic Risk Variants With Attention-Deficit/Hyperactivity Disorder Trajectories in the General Population. JAMA Psychiatry. 2016;73:1285–92.

    PubMed  PubMed Central  Google Scholar 

  83. 83.

    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.

    CAS  PubMed  PubMed Central  Google Scholar 

  84. 84.

    Willsey AJ, Sanders SJ, Li M, Dong S, Tebbenkamp AT, Muhle RA, et al. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell. 2013;155:997–1007.

    CAS  PubMed  PubMed Central  Google Scholar 

  85. 85.

    Niarchou M, Zammit S, Lewis G. The Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort as a resource for studying psychopathology in childhood and adolescence: a summary of findings for depression and psychosis. Soc Psychiatry Psychiatr Epidemiol. 2015;50:1017–27.

    Google Scholar 

  86. 86.

    Mors O, Perto GP, Mortensen PB. The Danish Psychiatric Central Research Register. Scand J Public Health. 2011;39(7 Suppl):54–57.

    Google Scholar 

  87. 87.

    Lee PH, Baker JT, Holmes AJ, Jahanshad N, Ge T, Jung JY, et al. Partitioning heritability analysis reveals a shared genetic basis of brain anatomy and schizophrenia. Mol Psychiatry. 2016;21:1680–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  88. 88.

    Bearden CE, Thompson PM. Emerging global initiatives in neurogenetics: the enhancing neuroimaging genetics through meta-analysis (ENIGMA) consortium. Neuron. 2017;94:232–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  89. 89.

    Cuthbert BN. Research domain criteria: toward future psychiatric nosologies. Dialogues Clin Neurosci. 2015;17:89–97.

    PubMed  PubMed Central  Google Scholar 

  90. 90.

    Evans DM, Davey Smith G. Mendelian randomization: new applications in the coming age of hypothesis-free causality. Annu Rev Genom Hum Genet. 2015;16:327–50.

    CAS  Google Scholar 

  91. 91.

    Emdin CA, Khera AV, Natarajan P, Klarin D, Zekavat SM, Hsiao AJ, et al. Genetic association of waist-to-hip ratio with cardiometabolic traits, type 2 diabetes, and coronary heart disease. JAMA. 2017;317:626–34.

    PubMed  PubMed Central  Google Scholar 

  92. 92.

    Voight BF, Peloso GM, Orho-Melander M, Frikke-Schmidt R, Barbalic M, Jensen MK, et al. Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. Lancet. 2012;380:572–80.

    CAS  PubMed  PubMed Central  Google Scholar 

  93. 93.

    Vaucher J, Keating BJ, Lasserre AM, Gan W, Lyall DM, Ward J et al. Cannabis use and risk of schizophrenia: a Mendelian randomization study. Mol Psychiatry. 2017 Jan 24. doi:10.1038/mp.2016.252. [Epub ahead of print].

    PubMed  PubMed Central  Google Scholar 

  94. 94.

    Pickrell JK, Berisa T, Liu JZ, Segurel L, Tung JY, Hinds DA. Detection and interpretation of shared genetic influences on 42 human traits. Nat Genet. 2016;48:709–17.

    CAS  PubMed  PubMed Central  Google Scholar 

  95. 95.

    Schaefer GB, Mendelsohn NJ, Professional P, Guidelines C. Clinical genetics evaluation in identifying the etiology of autism spectrum disorders: 2013 guideline revisions. Genet Med. 2013;15:399–407.

    CAS  Google Scholar 

  96. 96.

    Samocha KE, Robinson EB, Sanders SJ, Stevens C, Sabo A, McGrath LM, et al. A framework for the interpretation of de novo mutation in human disease. Nat Genet. 2014;46:944–50.

    CAS  PubMed  PubMed Central  Google Scholar 

  97. 97.

    Robinson EB, Samocha KE, Kosmicki JA, McGrath L, Neale BM, Perlis RH, et al. Autism spectrum disorder severity reflects the average contribution of de novo and familial influences. Proc Natl Acad Sci USA. 2014;111:15161–5.

    CAS  Google Scholar 

  98. 98.

    Zhu X, Need AC, Petrovski S, Goldstein DB. One gene, many neuropsychiatric disorders: lessons from Mendelian diseases. Nat Neurosci. 2014;17:773–81.

    CAS  Google Scholar 

  99. 99.

    Lichtenstein P, Carlstrom E, Rastam M, Gillberg C, Anckarsater H. The genetics of autism spectrum disorders and related neuropsychiatric disorders in childhood. Am J Psychiatry. 2010;167:1357–63.

    Google Scholar 

  100. 100.

    Polderman TJ, Benyamin B, de Leeuw CA, Sullivan PF, van Bochoven A, Visscher PM, et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat Genet. 2015;47:702–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  101. 101.

    Song J, Bergen SE, Kuja-Halkola R, Larsson H, Landen M, Lichtenstein P. Bipolar disorder and its relation to major psychiatric disorders: a family-based study in the Swedish population. Bipolar Disord. 2015;17:184–93.

    Google Scholar 

  102. 102.

    Cardno AG, Rijsdijk FV, Sham PC, Murray RM, McGuffin P. A twin study of genetic relationships between psychotic symptoms. Am J Psychiatry. 2002;159:539–45.

    Google Scholar 

  103. 103.

    McGuffin P, Rijsdijk F, Andrew M, Sham P, Katz R, Cardno A. The heritability of bipolar affective disorder and the genetic relationship to unipolar depression. Arch Gen Psychiatry. 2003;60:497–502.

    Google Scholar 

  104. 104.

    Bulik CM, Thornton LM, Root TL, Pisetsky EM, Lichtenstein P, Pedersen NL. Understanding the relation between anorexia nervosa and bulimia nervosa in a Swedish national twin sample. Biol Psychiatry. 2010;67:71–77.

    PubMed  PubMed Central  Google Scholar 

  105. 105.

    Mathews CA, Grados MA. Familiality of Tourette syndrome, obsessive-compulsive disorder, and attention-deficit/hyperactivity disorder: heritability analysis in a large sib-pair sample. J Am Acad Child Adolesc Psychiatry. 2011;50:46–54.

    Google Scholar 

  106. 106.

    Cederlof M, Thornton LM, Baker J, Lichtenstein P, Larsson H, Ruck C, et al. Etiological overlap between obsessive-compulsive disorder and anorexia nervosa: a longitudinal cohort, multigenerational family and twin study. World Psychiatry. 2015;14:333–8.

    PubMed  PubMed Central  Google Scholar 

  107. 107.

    Tick B, Bolton P, Happe F, Rutter M, Rijsdijk F. Heritability of autism spectrum disorders: a meta-analysis of twin studies. J Child Psychol Psychiatry. 2016;57:585–95.

    Google Scholar 

  108. 108.

    Sartor CE, Grant JD, Lynskey MT, McCutcheon VV, Waldron M, Statham DJ, et al. Common heritable contributions to low-risk trauma, high-risk trauma, posttraumatic stress disorder, and major depression. Arch General Psychiatry. 2012;69:293–9.

    Google Scholar 

  109. 109.

    Stein MB, Jang KL, Taylor S, Vernon PA, Livesley WJ. Genetic and environmental influences on trauma exposure and posttraumatic stress disorder symptoms: a twin study. Am J Psychiatry. 2002;159:1675–81.

    Google Scholar 

Download references

Acknowledgements

Supported in part by NIH awards K24MH094614 (JWS), the Research Council of Norway (223273) and KG Jebsen Stiftelsen (OAA). Dr. Smoller is a Tepper Family MGH Research Scholar. “All of Us” is a service mark of the U.S. Department of Health and Human Services. The authors thank Nicholas Merriam for assistance with producing the figure.

Author contributions

Dr. Smoller is an unpaid member of the Scientific Advisory Board of PsyBrain Inc. and the Bipolar/Depression Research Community Advisory Panel of 23andMe. Dr. Andreassen has received speaker’s honorarium from Lundbeck. The remaining authors have no disclosures.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Jordan W. Smoller.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

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

The original version of this article was revised: Modifications have been made to the Table 1 legend. Full information regarding corrections made can be found in the erratum/correction article for this article.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Smoller, J.W., Andreassen, O.A., Edenberg, H.J. et al. Psychiatric genetics and the structure of psychopathology. Mol Psychiatry 24, 409–420 (2019). https://doi.org/10.1038/s41380-017-0010-4

Download citation

Further reading

Search

Quick links