TY - JOUR
T1 - Chronicity and Sex Affect Genetic Risk Prediction in Schizophrenia
AU - Meier, Sandra M.
AU - Kähler, Anna K.
AU - Bergen, Sarah E.
AU - Sullivan, Patrick F.
AU - Hultman, Christina M.
AU - Mattheisen, Manuel
N1 - Publisher Copyright:
© Copyright © 2020 Meier, Kähler, Bergen, Sullivan, Hultman and Mattheisen.
PY - 2020/6/9
Y1 - 2020/6/9
N2 - 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.
AB - 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.
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U2 - 10.3389/fpsyt.2020.00313
DO - 10.3389/fpsyt.2020.00313
M3 - Article
AN - SCOPUS:85087030913
SN - 1664-0640
VL - 11
JO - Frontiers in Psychiatry
JF - Frontiers in Psychiatry
M1 - 313
ER -