Search

Background: The value of the nosological distinction between non-affective and affective psychosis has consistently been challenged. Indeed, psychotic syndromes are composed of dimensions of psychopathology cutting across diagnostic boundaries. Such transdiagnostic symptom dimensions might be enhanced phenotypes to test for association with common genetic variants for Major Mental Disorders (MMDs) as summarized by Polygenic Risk Scores (PRSs) for Schizophrenia (SZ), Bipolar Disorder (BP), and Major Depressive Disorder (MDD). The objectives of this study were to: 1) identify the symptom dimension structure at First Episode Psychosis (FEP); 2) examine the extent to which MMDs PRSs explain the phenotypic variance due to symptom dimensions. Methods: OPCRIT psychopathology items were analysed using multidimensional item response modelling in Mplus to estimate unidimensional, multidimensional, and bi-factor models of psychosis. Model fit statistics included LogLikelihood, and Akaike and Bayesian Information Criteria to compare these models. SZ, BP, and MDD PRSs were built using the results from large mega-analyses from the Working Groups of the Psychiatric Genomics Consortium. In PRSice, individuals’ number of risk alleles in the target sample was weighted by the log odds ratio from the discovery samples, and summed into the three PRSs for SZ, BP, and MDD. These PRSs were calculated at a fixed 0.05 P-value SNP threshold. Regression models were fitted to predict symptom dimensions’ scores as continuous outcomes from the three PRSs. These model, conducted in STATA14, were adjusted for age, gender, and 20 principal components for population stratification. Results: The best model fit statistics was observed for the bi-factor model including one general and five specific dimensions of positive, negative, disorganization, manic and depressive symptoms. A positive linear association was observed between SZ PRS and the positive dimension t(789)=2.04, p