%A Meier,Sandra M. %A Kähler,Anna K. %A Bergen,Sarah E. %A Sullivan,Patrick F. %A Hultman,Christina M. %A Mattheisen,Manuel %D 2020 %J Frontiers in Psychiatry %C %F %G English %K Schizophrenia,Genetics,Polygenic risk score (PRS),sex categorization,course %Q %R 10.3389/fpsyt.2020.00313 %W %L %M %P %7 %8 2020-June-09 %9 Brief Research Report %+ Manuel Mattheisen,Department of Biomedicine, Aarhus University,Denmark,Manuel.mattheisen@dal.ca %+ Manuel Mattheisen,Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet,Sweden,Manuel.mattheisen@dal.ca %+ Manuel Mattheisen,Stockholm Health Care Services, Stockholm County Council,Sweden,Manuel.mattheisen@dal.ca %+ Manuel Mattheisen,Department of Psychiatry, Psychosomatics and Psychotherapy, University of Wuerzburg,Germany,Manuel.mattheisen@dal.ca %# %! Genetic risk prediction in schizophrenia %* %< %T Chronicity and Sex Affect Genetic Risk Prediction in Schizophrenia %U https://www.frontiersin.org/articles/10.3389/fpsyt.2020.00313 %V 11 %0 JOURNAL ARTICLE %@ 1664-0640 %X 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.