USING POLYGENIC SCORES BASED ON SCHNEIDERIAN FIRST RANK SYMPTOMS TO CHARACTERIZE DISEASE TRAJECTORIES IN SEVERE MENTAL ILLNESSES

Mental illnesses such as bipolar disorder (BD), schizoaffective disorder (SA) and schizophrenia (SZ) have a huge impact on people’s lives and due to expensive treatments also on our health systems. Despite our advances in genetic and clinical research, it is still unknown what determines the highly variable courses of illness. Recent studies have focused on determining phenotypes more suitable for genetic analyses. Most analyses use diagnostic criteria based on DSM or ICD, however, the question arises whether it may be useful to classify subgroups of patients based on domains of psychopathology across diagnostic classification systems. To date, few studies exist that examine phenotypes based on such domains. We examined the presence/absence of Schneiderian first-rank symptoms (FRS) as a potential phenotype in a genome-wide association study (GWAS) analysis. The results of this analysis were used to calculate polygenic risk scores in an independent sample in which longitudinal clusters of psychopathology have been defined. We aim to explore the association of cluster membership with the individual load on first-rank polygenic risk scores (FR-PRS).