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Schizophrenia (SZ), Bipolar Disorder (BD) and Depression (D) run in families. This susceptibility is partly due to hundreds or thousands of common genetic variants, each conferring a fractional risk. The cumulative effects of the associated variants can be summarised as a polygenic risk score (PRS). Using data from the EUGEI case-control study, we aimed to test whether PRSs for three major psychiatric disorders (SZ, BD, D) and for intelligent quotient (IQ) as a neurodevelopmental proxy, can discriminate affective psychosis (AP) from schizophrenia-spectrum disorder (SSD). Participants (573 cases, 1005 controls) of european ancestry from 17 sites as part of the EUGEI study were successfully genotyped following standard quality control procedures. Using standardised PRS for SZ, BD, D, and IQ built from the latest available summary statistics, we performed simple or multinomial logistic regression models adjusted for 10 principal components for the different clinical comparisons. In case-control comparisons PRS-SZ, PRS-BD and PRS-D distributed differentially across psychotic subcategories. In case-case comparison, both PRS-SZ (OR=0.7, 95 %CI 0.53-0.92) and PRS-D (OR=1.29, 95%CI 1.05-1.6) differentiated global AP from SSD; and within AP categories, only PRS-SZ differentiated BD from psychotic depression (OR=2.38, 95%CI 1.32-4.29). Combining PRS for severe psychiatric disorders in prediction models for psychosis phenotypes can increase discriminative ability and improve our understanding of these phenotypes. Our results point towards potential usefulness of PRSs for diagnostic prediction in specific populations such as high-risk or early psychosis phases.

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