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.

  • Original Article
  • Published:

Reciprocal causation models of cognitive vs volumetric cerebral intermediate phenotypes for schizophrenia in a pan-European twin cohort

Molecular Psychiatry volume 20, pages 1386–1396 (2015)Cite this article

Subjects

An Erratum to this article was published on 18 August 2015

Abstract

In aetiologically complex illnesses such as schizophrenia, there is no direct link between genotype and phenotype. Intermediate phenotypes could help clarify the underlying biology and assist in the hunt for genetic vulnerability variants. We have previously shown that cognition shares substantial genetic variance with schizophrenia; however, it is unknown if this reflects pleiotropic effects, direct causality or some shared third factor that links both, for example, brain volume (BV) changes. We quantified the degree of net genetic overlap and tested the direction of causation between schizophrenia liability, brain structure and cognition in a pan-European schizophrenia twin cohort consisting of 1243 members from 626 pairs. Cognitive deficits lie upstream of the liability for schizophrenia with about a quarter of the variance in liability to schizophrenia explained by variation in cognitive function. BV changes lay downstream of schizophrenia liability, with 4% of BV variation explained directly by variation in liability. However, our power to determine the nature of the relationship between BV deviation and schizophrenia liability was more limited. Thus, while there was strong evidence that cognitive impairment is causal to schizophrenia liability, we are not in a position to make a similar statement about the relationship between liability and BV. This is the first study to demonstrate that schizophrenia liability is expressed partially through cognitive deficits. One prediction of the finding that BV changes lie downstream of the disease liability is that the risk loci that influence schizophrenia liability will thereafter influence BV and to a lesser extent. By way of contrast, cognitive function lies upstream of schizophrenia, thus the relevant loci will actually have a larger effect size on cognitive function than on schizophrenia. These are testable predictions.

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
Figure 2
Figure 3

Similar content being viewed by others

References

  1. Waters-Metenier S, Toulopoulou T . Putative structural neuroimaging endophenotypes in schizophrenia: a comprehensive review of the current evidence. Future Neurol 2011; 6: 679–715.

    Article  Google Scholar 

  2. Jablensky A . The nature of psychiatric classification: issues beyond ICD-10 and DSM-IV. Aust NZ J Psychiatry 1999; 33: 137–144.

    Article  CAS  Google Scholar 

  3. Wessel J, Schork AJ, Tiwari HK, Schork NJ . Powerful designs for genetic association studies that consider twins and sibling pairs with discordant genotypes. Genet Epidemiol 2007; 31: 789–796.

    Article  Google Scholar 

  4. Greenwood TA, Braff DL, Light GA, Cadenhead KS, Calkins ME, Dobie DJ et al. Initial heritability analyses of endophenotypic measures for schizophrenia—the consortium on the genetics of schizophrenia. Arch Gen Psychiatry 2007; 64: 1242–1250.

    Article  Google Scholar 

  5. Toulopoulou T, Picchioni M, Rijsdijk F, Hua-Hall M, Ettinger U, Sham P et al. Substantial genetic overlap between neurocognition and schizophrenia—genetic modeling in twin samples. Arch Gen Psychiatry 2007; 64: 1348–1355.

    Article  Google Scholar 

  6. Aukes MF, Alizadeh BZ, Sitskoorn MM, Selten JP, Sinke RJ, Kemner C et al. Finding suitable phenotypes for genetic studies of schizophrenia: heritability and segregation analysis. Biol Psychiatry 2008; 64: 128–136.

    Article  CAS  Google Scholar 

  7. Waters-Metenier S, Toulopoulou T . Qualifying brain functional MRI parameters as endophenotypes in schizophrenia. Future Neurol 2010; 5: 817–838.

    Article  Google Scholar 

  8. 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: 905–913.

    Article  Google Scholar 

  9. Gur RC, Calkins ME, Satterthwaite TD, Ruparel K, Bilker WB, Moore TM et al. NEurocognitive growth charting in psychosis spectrum youths. JAMA Psychiatry 2014; 71: 366–374.

    Article  Google Scholar 

  10. Seidman LJ, Cherkerzian S, Goldstein JM, Agnew-Blais J, Tsuang MT, Buka SL . Neuropsychological performance and family history in children at age 7 who develop adult schizophrenia or bipolar psychosis in the New England Family Studies. Psychol Med 2013; 43: 119–131.

    Article  CAS  Google Scholar 

  11. Cannon TD, Bearden CE, Hollister JM, Rosso IM, Sanchez LE, Hadley T . Childhood cognitive functioning in schizophrenia patients and their unaffected siblings: a prospective cohort study. Schizophr Bull 2000; 26: 379–393.

    Article  CAS  Google Scholar 

  12. Cannon M, Caspi A, Moffitt TE, Harrington H, Taylor A, Murray RM et al. Evidence for early-childhood, pan-developmental impairment specific to schizophreniform disorder—results from a longitudinal birth cohort. Arch Gen Psychiatry 2002; 59: 449–456.

    Article  Google Scholar 

  13. Seidman LJ, Giuliano AJ, Meyer EC, Addington J, Cadenhead KS, Cannon TD et al. Neuropsychology of the prodrome to psychosis in the NAPLS consortium: relationship to family history and conversion to psychosis. Arch Gen Psychiatry 2010; 67: 578–588.

    Article  Google Scholar 

  14. Keshavan MS, DeLisi LE, Seidman LJ . Early and broadly defined psychosis risk mental states. Schizophr Res 2011; 126: 1–10.

    Article  Google Scholar 

  15. Joyce E, Hutton S, Mutsatsa S, Gibbins H, Webb E, Paul S et al. Executive dysfunction in first-episode schizophrenia and relationship to duration of untreated psychosis: the West London Study. Br J Psychiatry Suppl 2002; 181: S38–S44.

    Article  Google Scholar 

  16. Owens SF, Picchioni MM, Rijsdijk FV, Stahl D, Vassos E, Rodger AK et al. Genetic overlap between episodic memory deficits and schizophrenia: results from the Maudsley Twin Study. Psychol Med 2011; 41: 521–532.

    Article  CAS  Google Scholar 

  17. Owens SF, Rijsdijk F, Picchioni MM, Stahl D, Nenadic I, Murray RM et al. Genetic overlap between schizophrenia and selective components of executive function. Schizophr Res 2011; 127: 181–187.

    Article  Google Scholar 

  18. Wood SJ, Pantelis C, Velakoulis D, Yucel M, Fornito A, McGorry PD . Progressive changes in the development toward schizophrenia: studies in subjects at increased symptomatic risk. Schizophr Bull 2008; 34: 322–329.

    Article  Google Scholar 

  19. Pantelis C, Velakoulis D, McGorry PD, Wood SJ, Suckling J, Phillips LJ et al. Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison. Lancet 2003; 361: 281–288.

    Article  Google Scholar 

  20. Rijsdijk FV, Van Haren NEM, Picchioni MM, McDonald C, Toulopoulou T, Pol HEH et al. Brain MRI abnormalities in schizophrenia: same genes or same environment? Psychol Med 2005; 35: 1399–1409.

    Article  CAS  Google Scholar 

  21. van Haren NEM, Rijsdijk F, Schnack HG, Picchioni MM, Toulopoulou T, Weisbrod M et al. The genetic and environmental determinants of the association between brain abnormalities and schizophrenia: the schizophrenia twins and relatives consortium. Biol Psychiatry 2012; 71: 915–921.

    Article  Google Scholar 

  22. Owens SF, Picchioni MM, Ettinger U, McDonald C, Walshe M, Schmechtig A et al. Prefrontal deviations in function but not volume are putative endophenotypes for schizophrenia. Brain 2012; 135: 2231–2244.

    Article  Google Scholar 

  23. Need AC, Attix DK, McEvoy JM, Cirulli ET, Linney KL, Hunt P et al. A genome-wide study of common SNPs and CNVs in cognitive performance in the CANTAB. Hum Mol Genet 2009; 18: 4650–4661.

    Article  CAS  Google Scholar 

  24. Lencz T, Knowles E, Davies G, Guha S, Liewald D, Starr J et al. Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT). Mol Psychiatry 2013; 19: 168–174.

    Article  Google Scholar 

  25. 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: 234–239.

    Article  CAS  Google Scholar 

  26. Tan HY, Chen AG, Kolachana B, Apud JA, Mattay VS, Callicott JH et al. Effective connectivity of AKT1-mediated dopaminergic working memory networks and pharmacogenetics of anti-dopaminergic treatment. Brain 2012; 135: 1436–1445.

    Article  Google Scholar 

  27. Hulshoff Pol HE, Brans RG, van Haren NE, Schnack HG, Langen M, Baaré WF et al. Gray and white matter volume abnormalities in monozygotic and same-gender dizygotic twins discordant for schizophrenia. Biol Psychiatry 2004; 55: 126–130.

    Article  Google Scholar 

  28. Willemsen G, De Geus EJ, Bartels M, Van Beijsterveldt C, Brooks AI, Estourgie-van Burk GF et al. The Netherlands Twin Register biobank: a resource for genetic epidemiological studies. Twin Res Hum Genet 2010; 13: 231–245.

    Article  Google Scholar 

  29. Baare WFC, van Oel CJ, Pol HEH, Schnack HG, Durston S, Sitskoorn MM et al. Volumes of brain structures in twins discordant for schizophrenia. Arch Gen Psychiatry 2001; 58: 33–40.

    Article  CAS  Google Scholar 

  30. Picchioni M, Toulopoulou T, Pauli A, Valli I, Ettinger U, Fu C et al. Exploring genetic and environmental influences on brain function in schizophrenia. Schizophr Bull 2011; 37: 150.

    Google Scholar 

  31. Picchioni MM, Walshe M, Toulopoulou T, McDonald C, Taylor M, Waters-Metenier S et al. Genetic modelling of childhood social development and personality in twins and siblings with schizophrenia. Psychol Med 2010; 40: 1305–1316.

    Article  CAS  Google Scholar 

  32. Cannon TD, Kaprio J, Lonnqvist J, Huttunen M, Koskenvuo M . The genetic epidemiology of schizophrenia in a Finnish twin cohort—a population-based modeling study. Arch Gen Psychiatry 1998; 55: 67–74.

    Article  CAS  Google Scholar 

  33. Goldberg X, Alemany S, Rosa A, Picchioni M, Nenadic I, Owens SF et al. Substantial genetic link between iq and working memory: Implications for molecular genetic studies on schizophrenia. the European twin study of Schizophrenia (EUTwinsS). Am J Med Genet B 2013; 162B: 413–418.

    Article  Google Scholar 

  34. Wechsler D . Wechsler Adult Intelligence Scale–Revised Manual. The Psychological Corporation: New York, NY, USA, 1981.

    Google Scholar 

  35. Wechsler D . Wechsler Adult Intelligence Scale–Third Edition: Administration and Scoring Manual. The Psychological Corporation: London, UK, 1997.

    Google Scholar 

  36. Wechsler D . Manual for the Wechsler Memory Scale–Revised. The Psychological Corporation: San Antonio, TX, USA, 1987.

    Google Scholar 

  37. Wechsler D . Wechsler Memory Scale—Third edition. Administration and Scoring Manual. The Psychological Corporation: USA, 1997.

    Google Scholar 

  38. Schnack HG, van Haren NE, Hulshoff Pol HE, Picchioni M, Weisbrod M, Sauer H et al. Reliability of brain volumes from multicenter MRI acquisition: a calibration study. Hum Brain Mapp 2004; 22: 312–320.

    Article  Google Scholar 

  39. Corp. I. IBM . SPSS Statistics for Windows Version 20.0. IBM Corp: Armonk, NY, USA, 2011.

    Google Scholar 

  40. Kolde R . pheatmap: Pretty Heatmaps. R Package Version 0.7.4.,. 2014; http://CRAN.R-project.org/package=pheatmap.

  41. Wilkinson L, Friendly M . The history of the cluster heat map. Am Stat 2009; 63: 179–184.

    Article  Google Scholar 

  42. Boker S, Neale M, Maes H, Wilde M, Spiegel M, Brick T et al. OpenMx: an open source extended structural equation modeling framework. Psychometrika 2011; 76: 306–317.

    Article  Google Scholar 

  43. Sullivan PF, Kendler KS, Neale MC . Schizophrenia as a complex trait—evidence from a meta-analysis of twin studies. Arch Gen Psychiatry 2003; 60: 1187–1192.

    Article  Google Scholar 

  44. Neale M, Cardon L . Methodology for Genetic Studies of Twins and Families. Springer, 1992.

    Book  Google Scholar 

  45. Heath AC, Kessler RC, Neale MC, Hewitt JK, Eaves LJ, Kendler KS . Testing hypotheses about direction of causation using cross-sectional family data. Behav Genet 1993; 23: 29–50.

    Article  CAS  Google Scholar 

  46. Owens SF, Rijsdijk FV, Picchioni MM, Murray RM, Toulopoulou T . Genetic overlap between executive function and schizophrenia-the Maudsley Twin Study. Schizophr Bull 2009; 35: 109.

    Article  Google Scholar 

  47. Rodger AK, Owens SF, Rijsdijk FV, Picchioni MM, Waters-Metenier S, Murray RM et al. Genetic overlap between memory and schizophrenia. The Maudsley Twin Study. Schizophr Bull 2009; 35: 118.

    Google Scholar 

  48. Duffy DL, Martin NG . Inferring the direction of causation in cross-sectional twin data—theoretical and empirical considerations. Genet Epidemiol 1994; 11: 483–502.

    Article  CAS  Google Scholar 

  49. Neale MC, Walters E, Heath AC, Kessler RC, Perusse D, Eaves LJ et al. Depression and parental bonding—cause, consequence, or genetic covariance. Genet Epidemiol 1994; 11: 503–522.

    Article  CAS  Google Scholar 

  50. Meier MH, Caspi A, Reichenberg A, Keefe RS, Fisher HL, Harrington H et al. Neuropsychological decline in schizophrenia from the premorbid to the postonset period: evidence from a population-representative longitudinal study. Am J Psychiatry 2013; 171: 91–101.

    Article  Google Scholar 

  51. Jones P, Rodgers B, Murray R, Marmot M . Child developmental risk-factors for adult schizophrenia in the British 1946 birth cohort. Lancet 1994; 344: 1398–1402.

    Article  CAS  Google Scholar 

  52. MacCabe JH, Wicks S, Lofving S, David AS, Berndtsson A, Gustafsson JE et al. Decline in cognitive performance between ages 13 and 18 years and the risk for psychosis in adulthood. A Swedish longitudinal cohort study in males. JAMA Psychiatry 2013; 70: 261–270.

    Article  Google Scholar 

  53. 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: 160–169.

    Article  Google Scholar 

  54. Goldberg TE, Ragland JD, Torrey EF, Gold JM, Bigelow LB, Weinberger DR . Neuropsychological assessment of monozygotic twins discordant for schizophrenia. Arch Gen Psychiatry 1990; 47: 1066–1072.

    Article  CAS  Google Scholar 

  55. Toulopoulou T, Mapua-Filbey F, Quraishi S, Kravariti E, Morris RG, McDonald C et al. Cognitive performance in presumed obligate carriers for psychosis. Br J Psychiatry 2005; 187: 284–285.

    Article  Google Scholar 

  56. Prata DP, Mechelli A, Fu CHY, Picchioni M, Toulopoulou T, Bramon E et al. Epistasis between the DAT 3 ' UTR VNTR and the COMT Val158Met SNP on cortical function in healthy subjects and patients with schizophrenia. Proc Natl Acad Sci USA 2009; 106: 13600–13605.

    Article  CAS  Google Scholar 

  57. Catts VS, Fung SJ, Long LE, Joshi D, Vercammen A, Allen KM et al. Rethinking schizophrenia in the context of normal neurodevelopment. Front Cell Neurosci 2013; 7: 1–27.

    Article  Google Scholar 

  58. Insel TR . Rethinking schizophrenia. Nature 2010; 468: 187–193.

    Article  CAS  Google Scholar 

  59. Rothman K . Modern Epidemiology, vol. 31. Little, Brown and Co.: Boston, MA, USA 1986.

  60. Buxbaum AR, Wu B, Singer RH . Single β-actin mRNA detection in neurons reveals a mechanism for regulating its translatability. Science 2014; 343: 419–422.

    Article  CAS  Google Scholar 

  61. Park HY, Lim H, Yoon YJ, Follenzi A, Nwokafor C, Lopez-Jones M et al. Visualization of dynamics of single endogenous mRNA labeled in live mouse. Science 2014; 343: 422–424.

    Article  CAS  Google Scholar 

  62. Park HJ, Friston K . Structural and functional brain networks: from connections to cognition. Science 2013; 342: 579.

    Article  CAS  Google Scholar 

  63. Bilder RM, Howe AG, Sabb FW . Multilevel models from biology to psychology: mission impossible? J Abnorm Psychol 2013; 122: 917–927.

    Article  Google Scholar 

  64. Mercado E . Neural and cognitive plasticity: from maps to minds. Psychol Bull 2008; 134: 109–137.

    Article  Google Scholar 

  65. Martin-Loeches M, Bruner E, de la Cuetara JM, Colom R . Correlation between corpus callosum shape and cognitive performance in healthy young adults. Brain Struct Funct 2013; 218: 721–731.

    Article  Google Scholar 

  66. Karama S, Colom R, Johnson W, Deary IJ, Haier R, Waber DP et al. Cortical thickness correlates of specific cognitive performance accounted for by the general factor of intelligence in healthy children aged 6 to 18. Neuroimage 2011; 55: 1443–1453.

    Article  Google Scholar 

  67. Bruner E, Martin-Loeches M, Burgaleta M, Colom R . Midsagittal brain shape correlation with intelligence and cognitive performance. Intelligence 2011; 39: 141–147.

    Article  Google Scholar 

  68. Johnson W, Jung RE, Colom R, Haier RJ . Cognitive abilities independent of IQ correlate with regional brain structure. Intelligence 2008; 36: 18–28.

    Article  Google Scholar 

  69. Voineskos AN, Foussias G, Lerch J, Felsky D, Remington G, Rajji TK et al. Neuroimaging evidence for the deficit subtype of schizophrenia. JAMA Psychiatry 2013; 70: 472–480.

    Article  Google Scholar 

  70. McIntosh AM, Moorhead TWJ, McKirdy J, Hall J, Sussmann JED, Stanfield AC et al. Prefrontal gyral folding and its cognitive correlates in bipolar disorder and schizophrenia. Acta Psychiatry Scand 2009; 119: 192–198.

    Article  CAS  Google Scholar 

  71. Toulopoulou T, Grech A, Morris RG, Schulze K, McDonald C, Chapple B et al. The relationship between volumetric brain changes and cognitive function: a family study on schizophrenia. Biol Psychiatry 2004; 56: 447–453.

    Article  Google Scholar 

  72. Quan MN, Lee SH, Kubicki M, Kikinis Z, Rathi Y, Seidman LJ et al. White matter tract abnormalities between rostral middle frontal gyrus, inferior frontal gyrus and striatum in first-episode schizophrenia. Schizophr Res 2013; 145: 1–10.

    Article  Google Scholar 

  73. Meijer JH, Schmitz N, Nieman DH, Becker HE, van Amelsvoort TAMJ, Dingemans PM et al. Semantic fluency deficits and reduced grey matter before transition to psychosis: a voxelwise correlational analysis. Psychiatry Res 2011; 194: 1–6.

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge support from the Research Grant Council (Hong Kong) through a General Research Fund grant award (Toulopoulou, PI; Sham, co-PI), NARSAD (through a Young Investigator Award to Toulopoulou) and the European Community’s Sixth Framework Programme through a Marie Curie Training Network (MRTN-CT-2006-035987) called the European Twin Study Network on Schizophrenia (EUTwinsS).

Author information

Authors and Affiliations

  1. The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, SAR, China

    T Toulopoulou, P C Sham & S S Cherny

  2. Department of Psychology, The University of Hong Kong, Hong Kong, SAR, China

    T Toulopoulou

  3. Department of Basic and Clinical Neuroscience, The Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, UK

    T Toulopoulou

  4. Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands

    N van Haren, H H Pol, R Brouwer, H Schnack & R S Kahn

  5. Department of Psychiatry, The University of Hong Kong, Hong Kong, SAR, China

    X Zhang, P C Sham, S S Cherny & D D Campbell

  6. Centre for Genomic Sciences, The University of Hong Kong, Hong Kong, SAR, China

    X Zhang, P C Sham, S S Cherny & D D Campbell

  7. St Andrew’s Academic Centre, Cliftonville, Northampton, UK

    M Picchioni

  8. Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, London, UK

    M Picchioni

  9. Department of Psychosis, King’s College London, London, UK

    R Murray

  10. Department of Biological Psychology, VU University, Amsterdam, The Netherlands

    D I Boomsma

  11. Department of Animal Biology, Anthropology Unit, Biomedicine Institute of the University of Barcelona (IBUB), University of Barcelona, Barcelona, Spain

    L Fañanás

  12. Centre for Biomedical Research Network on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain

    L Fañanás

  13. Department of Psychiatry and Psychotherapy University Hospital of Jena, Jena, Germany

    H Sauer & I Nenadic

  14. Department of Psychiatry and Psychotherapy, SRH Clinic Karlsbad-Langensteinbach, Karlsbad-Langensteinbach, Germany

    M Weisbrod

  15. Section for Experimental Psychopathology and Neurophysiology, Centre for Psychosocial Medicine, University of Heidelberg, Heidelberg, Germany

    M Weisbrod

  16. Departments of Psychology and Psychiatry, Yale University, New Haven, CT, USA

    T D Cannon

Authors
  1. T Toulopoulou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N van Haren
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. X Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. P C Sham
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. S S Cherny
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. D D Campbell
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. M Picchioni
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. R Murray
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. D I Boomsma
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. H H Pol
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. R Brouwer
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. H Schnack
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. L Fañanás
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. H Sauer
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. I Nenadic
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. M Weisbrod
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. T D Cannon
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. R S Kahn
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to T Toulopoulou.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies the paper on the Molecular Psychiatry website

Supplementary information

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Toulopoulou, T., van Haren, N., Zhang, X. et al. Reciprocal causation models of cognitive vs volumetric cerebral intermediate phenotypes for schizophrenia in a pan-European twin cohort. Mol Psychiatry 20, 1386–1396 (2015). https://doi.org/10.1038/mp.2014.152

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/mp.2014.152

This article is cited by

Search

Advanced search

Quick links