Manuel Mattheisen

Chronicity and Sex Affect Genetic Risk Prediction in Schizophrenia

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  • Sandra M. Meier, Dalhousie University
  • ,
  • Anna K. Kähler, Karolinska Institutet
  • ,
  • Sarah E. Bergen, Karolinska Institutet, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
  • ,
  • Patrick F. Sullivan, Karolinska Institutet, University of North Carolina
  • ,
  • Christina M. Hultman, Karolinska Institutet
  • ,
  • Manuel Mattheisen

Schizophrenia (SCZ) is a severe mental disorder with immense personal and societal costs; identifying individuals at risk is therefore of utmost importance. Genomic risk profile scores (GRPS) have been shown to significantly predict cases-control status. Making use of a large-population based sample from Sweden, we replicate a previous finding demonstrating that the GRPS is strongly associated with admission frequency and chronicity of SCZ. Furthermore, we were able to show a substantial gap in prediction accuracy between males and females. In sum, our results indicate that prediction accuracy by GRPS depends on clinical and demographic characteristics.

Original languageEnglish
Article number313
JournalFrontiers in Psychiatry
Publication statusPublished - Jun 2020

    Research areas

  • course, polygenic risk score, prediction, schizophrenia, sex

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