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Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept

Franke, B., Stein, J. L., Ripke, S., Anttila, V., Hibar, D. P., van Hulzen, K. J. E., Arias-Vasquez, A., Smoller, J. W., Nichols, T. E., Neale, M. C., McIntosh, A. M., Lee, P., McMahon, F. J., Meyer-Lindenberg, A., Mattheisen, M., Andreassen, O. A., Gruber, O., Sachdev, P. S., Roiz-Santianez, R., Saykin, A. J., Ehrlich, S., Mather, K. A., Turner, J. A., Wright, M. J., O'Donovan, M. C., Thompson, P. M., Neale, B. M., Medland, S. E., Sullivan, P. F., ENIGMA Consortium & Psychiat Genomics Consortium, Mar-2016, In : Nature neuroscience. 19, 3, p. 420-431 12 p.

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  • Genetic influences on schizophrenia and subcortical brain volumes large-scale proof

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DOI

  • Barbara Franke
  • Jason L. Stein
  • Stephan Ripke
  • Verneri Anttila
  • Derrek P. Hibar
  • Kimm J. E. van Hulzen
  • Alejandro Arias-Vasquez
  • Jordan W. Smoller
  • Thomas E. Nichols
  • Michael C. Neale
  • Andrew M. McIntosh
  • Phil Lee
  • Francis J. McMahon
  • Andreas Meyer-Lindenberg
  • Manuel Mattheisen
  • Ole A. Andreassen
  • Oliver Gruber
  • Perminder S. Sachdev
  • Roberto Roiz-Santianez
  • Andrew J. Saykin
  • Stefan Ehrlich
  • Karen A. Mather
  • Jessica A. Turner
  • Margaret J. Wright
  • Michael C. O'Donovan
  • Paul M. Thompson
  • Benjamin M. Neale
  • Sarah E. Medland
  • Patrick F. Sullivan
  • ENIGMA Consortium
  • Psychiat Genomics Consortium

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.

Original languageEnglish
Pages (from-to)420-431
Number of pages12
JournalNature neuroscience
Volume19
Issue number3
Publication statusPublished - Mar-2016

    Keywords

  • GENOME-WIDE ASSOCIATION, METAANALYSIS, ENDOPHENOTYPE, INDIVIDUALS, PERSPECTIVE, PHENOTYPES, DISORDERS, DISCOVERY, RELATIVES, VARIANTS

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