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Genome-wide analysis reveals extensive genetic overlap between schizophrenia, bipolar disorder, and intelligence

Molecular Psychiatry volume 25, pages 844–853 (2020)Cite this article

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A Correction to this article was published on 15 July 2019

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Abstract

Schizophrenia (SCZ) and bipolar disorder (BD) are severe mental disorders associated with cognitive impairment, which is considered a major determinant of functional outcome. Despite this, the etiology of the cognitive impairment is poorly understood, and no satisfactory cognitive treatments exist. Increasing evidence indicates that genetic risk for SCZ may contribute to cognitive impairment, whereas the genetic relationship between BD and cognitive function remains unclear. Here, we combined large genome-wide association study data on SCZ (n = 82,315), BD (n = 51,710), and general intelligence (n = 269,867) to investigate overlap in common genetic variants using conditional false discovery rate (condFDR) analysis. We observed substantial genetic enrichment in both SCZ and BD conditional on associations with intelligence indicating polygenic overlap. Using condFDR analysis, we leveraged this enrichment to increase statistical power and identified 75 distinct genomic loci associated with both SCZ and intelligence, and 12 loci associated with both BD and intelligence at conjunctional FDR < 0.01. Among these loci, 20 are novel for SCZ, and four are novel for BD. Most SCZ risk alleles (61 of 75, 81%) were associated with poorer cognitive performance, whereas most BD risk alleles (9 of 12, 75%) were associated with better cognitive performance. A gene set analysis of the loci shared between SCZ and intelligence implicated biological processes related to neurodevelopment, synaptic integrity, and neurotransmission; the same analysis for BD was underpowered. Altogether, the study demonstrates that both SCZ and BD share genetic influences with intelligence, albeit in a different manner, providing new insights into their genetic architectures.

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References

  1. Wahlbeck K, Westman J, Nordentoft M, Gissler M, Laursen TM. Outcomes of Nordic mental health systems: life expectancy of patients with mental disorders. Br J Psychiatry. 2011;199:453–8.

    PubMed  Google Scholar 

  2. Nordentoft M, Wahlbeck K, Hallgren J, Westman J, Osby U, Alinaghizadeh H, et al. Excess mortality, causes of death and life expectancy in 270,770 patients with recent onset of mental disorders in Denmark, Finland and Sweden. PLoS ONE. 2013;8:e55176.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Keshavan MS, Morris DW, Sweeney JA, Pearlson G, Thaker G, Seidman LJ, et al. A dimensional approach to the psychosis spectrum between bipolar disorder and schizophrenia: the Schizo-Bipolar Scale. Schizophr Res. 2011;133:250–4.

    PubMed  PubMed Central  Google Scholar 

  4. Grande I, Berk M, Birmaher B, Vieta E. Bipolar disorder. Lancet. 2016;387:1561–72.

    PubMed  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  6. Green MF. Cognitive impairment and functional outcome in schizophrenia and bipolar disorder. J Clin Psychiatry. 2006;67:3–8. discussion36-42

    PubMed  Google Scholar 

  7. Simonsen C, Sundet K, Vaskinn A, Birkenaes AB, Engh JA, Faerden A, et al. Neurocognitive dysfunction in bipolar and schizophrenia spectrum disorders depends on history of psychosis rather than diagnostic group. Schizophr Bull. 2011;37:73–83.

    PubMed  Google Scholar 

  8. Kahn RS, Keefe RS. Schizophrenia is a cognitive illness: time for a change in focus. JAMA Psychiatry. 2013;70:1107–12.

    PubMed  Google Scholar 

  9. Keefe RS, Fenton WS. How should DSM-V criteria for schizophrenia include cognitive impairment? Schizophr Bull. 2007;33:912–20.

    PubMed  PubMed Central  Google Scholar 

  10. Dickinson D, Ragland JD, Gold JM, Gur RC. General and specific cognitive deficits in schizophrenia: Goliath defeats David? Biol Psychiatry. 2008;64:823–7.

    PubMed  PubMed Central  Google Scholar 

  11. Bourne C, Aydemir O, Balanza-Martinez V, Bora E, Brissos S, Cavanagh JT, et al. Neuropsychological testing of cognitive impairment in euthymic bipolar disorder: an individual patient data meta-analysis. Acta Psychiatr Scand. 2013;128:149–62.

    CAS  PubMed  Google Scholar 

  12. Kurtz MM, Gerraty RT. A meta-analytic investigation of neurocognitive deficits in bipolar illness: profile and effects of clinical state. Neuropsychology. 2009;23:551–62.

    PubMed  PubMed Central  Google Scholar 

  13. Arts B, Jabben N, Krabbendam L, van Os J. Meta-analyses of cognitive functioning in euthymic bipolar patients and their first-degree relatives. Psychol Med. 2008;38:771–85.

    CAS  PubMed  Google Scholar 

  14. Simonsen C, Sundet K, Vaskinn A, Birkenaes AB, Engh JA, Hansen CF, et al. Neurocognitive profiles in bipolar I and bipolar II disorder: differences in pattern and magnitude of dysfunction. Bipolar Disord. 2008;10:245–55.

    PubMed  Google Scholar 

  15. Johnson W, Bouchard TJ, Krueger RF, McGue M, Gottesman II. Just one g: consistent results from three test batteries. Intelligence. 2004;32:95–107.

    Google Scholar 

  16. Ree MJ, Earles JA. The stability of G across different methods of estimation. Intelligence. 1991;15:271–8.

    Google Scholar 

  17. Palmer BW, Heaton RK, Paulsen JS, Kuck J, Braff D, Harris MJ, et al. Is it possible to be schizophrenic yet neuropsychologically normal? Neuropsychology. 1997;11:437–46.

    CAS  PubMed  Google Scholar 

  18. Vaskinn A, Ueland T, Melle I, Agartz I, Andreassen OA, Sundet K. Neurocognitive decrements are present in intellectually superiors chizophrenia. Front Psychiatry. 2014;5:45.

    PubMed  PubMed Central  Google Scholar 

  19. MacCabe JH, Brebion G, Reichenberg A, Ganguly T, McKenna PJ, Murray RM, et al. Superior intellectual ability in schizophrenia: neuropsychological characteristics. Neuropsychology. 2012;26:181–90.

    PubMed  Google Scholar 

  20. Gale CR, Batty GD, McIntosh AM, Porteous DJ, Deary IJ, Rasmussen F. Is bipolar disorder more common in highly intelligent people? A cohort study of a million men. Mol Psychiatry. 2013;18:190–4.

    CAS  PubMed  Google Scholar 

  21. Tiihonen J, Haukka J, Henriksson M, Cannon M, Kieseppa T, Laaksonen I, et al. Premorbid intellectual functioning in bipolar disorder and schizophrenia: results from a cohort study of male conscripts. Am J Psychiatry. 2005;162:1904–10.

    PubMed  Google Scholar 

  22. MacCabe JH, Lambe MP, Cnattingius S, Sham PC, David AS, Reichenberg A, et al. Excellent school performance at age 16 and risk of adult bipolar disorder: national cohort study. Br J Psychiatry. 2010;196:109–15.

    PubMed  Google Scholar 

  23. Fusar-Poli P, Deste G, Smieskova R, Barlati S, Yung AR, Howes O, et al. Cognitive functioning in prodromal psychosis: a meta-analysis. Arch Gen Psychiatry. 2012;69:562–71.

    PubMed  Google Scholar 

  24. Reichenberg A, Caspi A, Harrington H, Houts R, Keefe RS, Murray RM, et al. Static and dynamic cognitive deficits in childhood preceding adult schizophrenia: a 30-year study. Am J Psychiatry. 2010;167:160–9.

    PubMed  PubMed Central  Google Scholar 

  25. Deary IJ. Intelligence. Annu Rev Psychol. 2012;63:453–82.

    PubMed  Google Scholar 

  26. Mackenbach JP, Stirbu I, Roskam AJ, Schaap MM, Menvielle G, Leinsalu M, et al. Socioeconomic inequalities in health in 22 European countries. N Engl J Med. 2008;358:2468–81.

    CAS  PubMed  Google Scholar 

  27. Mohamed S, Rosenheck R, Swartz M, Stroup S, Lieberman JA, Keefe RS. Relationship of cognition and psychopathology to functional impairment in schizophrenia. Am J Psychiatry. 2008;165:978–87.

    PubMed  Google Scholar 

  28. Wingo AP, Harvey PD, Baldessarini RJ. Neurocognitive impairment in bipolar disorder patients: functional implications. Bipolar Disord. 2009;11:113–25.

    PubMed  Google Scholar 

  29. Martinez-Aran A, Vieta E, Torrent C, Sanchez-Moreno J, Goikolea JM, Salamero M, et al. Functional outcome in bipolar disorder: the role of clinical and cognitive factors. Bipolar Disord. 2007;9:103–13.

    CAS  PubMed  Google Scholar 

  30. Lichtenstein P, Yip BH, Bjork C, Pawitan Y, Cannon TD, Sullivan PF, et al. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study. Lancet. 2009;373:234–9.

    CAS  PubMed  Google Scholar 

  31. 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  Google Scholar 

  32. Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium. Genomic dissection of bipolar disorder and schizophrenia, including 28 subphenotypes. Cell. 2018;173:1705–15 e1716.

    PubMed Central  Google Scholar 

  33. Toulopoulou T, Goldberg TE, Mesa IR, Picchioni M, Rijsdijk F, Stahl D, et al. Impaired intellect and memory: a missing link between genetic risk and schizophrenia? Arch Gen Psychiatry. 2010;67:905–13.

    PubMed  Google Scholar 

  34. Glahn DC, Almasy L, Blangero J, Burk GM, Estrada J, Peralta JM, et al. Adjudicating neurocognitive endophenotypes for schizophrenia. Am J Med Genet B Neuropsychiatr Genet. 2007;144B:242–9.

    PubMed  Google Scholar 

  35. Fowler T, Zammit S, Owen MJ, Rasmussen F. A population-based study of shared genetic variation between premorbid IQ and psychosis among male twin pairs and sibling pairs from Sweden. Arch Gen Psychiatry. 2012;69:460–6.

    PubMed  Google Scholar 

  36. Smeland OB, Frei O, Kauppi K, Hill WD, Li W, Wang Y, et al. Identification of genetic loci jointly influencing schizophrenia risk and the cognitive traits of verbal-numerical reasoning, reaction time, and general cognitive function. JAMA Psychiatry. 2017;74:1065–75.

    PubMed  PubMed Central  Google Scholar 

  37. Owen MJ, O’Donovan MC. Schizophrenia and the neurodevelopmental continuum:evidence from genomics. World Psychiatry. 2017;16:227–35.

    PubMed  PubMed Central  Google Scholar 

  38. Bora E, Yucel M, Pantelis C. Cognitive endophenotypes of bipolar disorder: a meta-analysis of neuropsychological deficits in euthymic patients and their first-degree relatives. J Affect Disord. 2009;113:1–20.

    PubMed  Google Scholar 

  39. Glahn DC, Almasy L, Barguil M, Hare E, Peralta JM, Kent JW, et al. Neurocognitive endophenotypes for bipolar disorder identified in multiplex multigenerational families. Arch General Psychiatry. 2010;67:168–77.

    Google Scholar 

  40. Hill SK, Reilly JL, Keefe RS, Gold JM, Bishop JR, Gershon ES, et al. Neuropsychological impairments in schizophrenia and psychotic bipolar disorder: findings from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Am J Psychiatry. 2013;170:1275–84.

    PubMed  PubMed Central  Google Scholar 

  41. Hagenaars SP, Harris SE, Davies G, Hill WD, Liewald DC, Ritchie SJ, et al. Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N = 112 151) and 24 GWAS consortia. Mol Psychiatry. 2016;21:1624–32.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Trampush JW, Yang ML, Yu J, Knowles E, Davies G, Liewald DC, et al. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Mol Psychiatry. 2017;22:336–45.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Hill WD, Davies G, Group CCW, Liewald DC, McIntosh AM, Deary IJ. Age-dependent pleiotropy between general cognitive function and major pasychiatric disorders. Biol Psychiatry. 2016;80:266–73.

    PubMed  PubMed Central  Google Scholar 

  44. Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, de Leeuw CA, et al. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nat Genet. 2018;50:912–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Sniekers S, Stringer S, Watanabe K, Jansen PR, Coleman JRI, Krapohl E, et al. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat Genet. 2017;49:1107–12.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Liebers DT, Pirooznia M, Seiffudin F, Musliner KL, Zandi PP, Goes FS. Polygenic risk of schizophrenia and cognition in a population-based survey of older adults. Schizophr Bull. 2016;42:984–91.

    PubMed  PubMed Central  Google Scholar 

  47. Brainstorm Consortium. Analysis of shared heritability in common disorders of the brain. Science. 2018;360:eaap8757.

  48. Davies G, Lam M, Harris SE, Trampush JW, Luciano M, Hill WD, et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nat Commun. 2018;9:2098.

    PubMed  PubMed Central  Google Scholar 

  49. Stahl E, Forstner A, McQuillin A, Ripke S, Ophoff R et al. Genomewide association study identifies 30 loci associated with bipolar disorder. bioRxiv 2017.

  50. Lyall DM, Cullen B, Allerhand M, Smith DJ, Mackay D, Evans J, et al. Cognitive test scores in UK biobank: data reduction in 480,416 participants and longitudinal stability in 20,346 participants. PLoS ONE. 2016;11:e0154222.

    PubMed  PubMed Central  Google Scholar 

  51. Davies G, Marioni RE, Liewald DC, Hill WD, Hagenaars SP, Harris SE, et al. Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N = 112 151). Mol Psychiatry. 2016;21:758–67.

    CAS  PubMed  PubMed Central  Google Scholar 

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

    PubMed Central  Google Scholar 

  53. Andreassen OA, Djurovic S, Thompson WK, Schork AJ, Kendler KS, O’Donovan MC, et al. Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors. Am J Hum Genet. 2013;92:197–209.

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Liu JZ, Hov JR, Folseraas T, Ellinghaus E, Rushbrook SM, Doncheva NT, et al. Dense genotyping of immune-related disease regions identifies nine new risk loci for primary sclerosing cholangitis. Nat Genet. 2013;45:670–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Schork AJ, Wang Y, Thompson WK, Dale AM, Andreassen OA. New statistical approaches exploit the polygenic architecture of schizophrenia–implications for the underlying neurobiology. Curr Opin Neurobiol. 2016;36:89–98.

    CAS  PubMed  Google Scholar 

  56. Deary IJ, Penke L, Johnson W. The neuroscience of human intelligence differences. Nat Rev Neurosci. 2010;11:201–11.

    CAS  PubMed  Google Scholar 

  57. Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017;8:1826.

    PubMed  PubMed Central  Google Scholar 

  58. The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature. 2015;526:68–74.

    Google Scholar 

  59. Kircher M, Witten DM, Jain P, O’Roak BJ, Cooper GM, Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet. 2014;46:310–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 2012;22:1790–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Roadmap Epigenomics C, Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518:317–30.

    Google Scholar 

  62. Zhu Z, Zhang F, Hu H, Bakshi A, Robinson MR, Powell JE, et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet. 2016;48:481–7.

    CAS  PubMed  Google Scholar 

  63. MacArthur J, Bowler E, Cerezo M, Gil L, Hall P, Hastings E, et al. The new NHGRI-EBI catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. 2017;45(D1):D896–D901.

    CAS  PubMed  Google Scholar 

  64. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–29.

    CAS  PubMed  PubMed Central  Google Scholar 

  65. GTEx Consortium. Genetic effects on gene expression across human tissues. Nature. 2017;550:204–13.

    PubMed Central  Google Scholar 

  66. Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh PR, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet. 2015;47:1236–41.

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  68. Moritz S, Klein JP, Desler T, Lill H, Gallinat J, Schneider BC. Neurocognitive deficits in schizophrenia.Are we making mountains out of molehills?. Psychol Med. 2017;47:2602–12.

    CAS  PubMed  Google Scholar 

  69. 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 

  70. Smeland OB, Wang Y, Frei O, Li W, Hibar DP, Franke B, et al. Genetic overlap between schizophrenia and volumes of hippocampus, putamen, and intracranial volume indicates shared molecular genetic mechanisms. Schizophr Bull. 2018;44:854–64.

    PubMed  Google Scholar 

  71. Hibar DP, Stein JL, Renteria ME, Arias-Vasquez A, Desrivieres S, Jahanshad N, et al. Common genetic variants influence human subcortical brain structures. Nature. 2015;520:224–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Hou L, Bergen SE, Akula N, Song J, Hultman CM, Landen M, et al. Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder. Hum Mol Genet. 2016;25:3383–94.

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Ikeda M, Takahashi A, Kamatani Y, Okahisa Y, Kunugi H, Mori N, et al. A genome-wide association study identifies two novel susceptibility loci and trans population polygenicity associated with bipolar disorder. Mol Psychiatry. 2018;23:639–47.

    CAS  PubMed  Google Scholar 

  74. Sklar P, Ripke S, Scott LJ, Andreassen OA, Cichon S, Craddock N, et al. Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nat Genet. 2011;43:977–83.

    CAS  PubMed Central  Google Scholar 

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Acknowledgements

We thank the Schizophrenia and Bipolar Disorder Working Groups of the Psychiatric Genomics Consortium for access to data, and the consortia for making available their GWAS summary statistics, and the many people who provided DNA samples. We gratefully acknowledge support from the Research Council of Norway (262656, 249711, 248980, 248778, 223273), South-East Norway Regional Health Authority (2017-112, 2016–064) and KG Jebsen Stiftelsen (SKGJ‐MED‐008); ABCD-USA Consortium (5U2 4DA041123)

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Authors and Affiliations

  1. NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway

    Olav B Smeland, Shahram Bahrami, Oleksandr Frei, Alexey Shadrin, Kevin O’Connell, Florian Krull, Francesco Bettella, Nils Eiel Steen, Torill Ueland & Ole A Andreassen

  2. Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, The Netherlands

    Jeanne Savage, Kyoko Watanabe & Danielle Posthuma

  3. Department of Psychology, University of Oslo, Oslo, Norway

    Torill Ueland

  4. Department of Clinical Genetics, section Complex Trait Genetics, Neuroscience Campus Amsterdam, VU Medical Center, Amsterdam, the Netherlands

    Danielle Posthuma

  5. Department of Medical Genetics, Oslo University Hospital, Oslo, Norway

    Srdjan Djurovic

  6. NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway

    Srdjan Djurovic

  7. Department of Cognitive Science, University of California, San Diego, La Jolla, CA, 92093, USA

    Anders M Dale

  8. Department of Neuroscience, University of California San Diego, La Jolla, CA, 92093, USA

    Anders M Dale

  9. Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, USA

    Anders M Dale

  10. Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, 92093, USA

    Anders M Dale

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  1. Olav B Smeland
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Correspondence to Olav B Smeland or Ole A Andreassen.

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Smeland, O.B., Bahrami, S., Frei, O. et al. Genome-wide analysis reveals extensive genetic overlap between schizophrenia, bipolar disorder, and intelligence. Mol Psychiatry 25, 844–853 (2020). https://doi.org/10.1038/s41380-018-0332-x

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