Polygenic Risk Scores for Subtyping of Schizophrenia

Schizophrenia is a complex disorder with many comorbid conditions. In this study, we used polygenic risk scores (PRSs) fromschizophrenia and comorbid traits to explore consistent cluster structure in schizophrenia patients. With 10 comorbid traits, wefound a stable 4-cluster structure in two datasets (MGS and SSCCS). When the same traits and parameters were applied for thepatients in a clinical trial of antipsychotics, the CATIE study, a 5-cluster structure was observed. One of the 4 clusters found inthe MGS and SSCCS was further split into two clusters in CATIE, while the other 3 clusters remained unchanged. For the 5CATIE clusters, we evaluated their association with the changes of clinical symptoms, neurocognitive functions, and laboratorytests between the enrollment baseline and the end of Phase I trial. Class I was found responsive to treatment, with significantreduction for the total, positive, and negative symptoms (p=0:0001, 0.0099, and 0.0028, respectively), and improvement forcognitive functions (VIGILANCE,p=0:0099; PROCESSING SPEED,p=0:0006; WORKING MEMORY,p=0:0023; andREASONING,p=0:0015). Class II had modest reduction of positive symptoms (p=0:0492) and better PROCESSING SPEED(p=0:0071). Class IV had a specific reduction of negative symptoms (p=0:0111) and modest cognitive improvement for alltested domains. Interestingly, Class IV was also associated with decreased lymphocyte counts and increased neutrophil counts,an indication of ongoing inflammation or immune dysfunction. In contrast, Classes III and V showed no symptom reductionbut a higher level of phosphorus. Overall, our results suggest that PRSs from schizophrenia and comorbid traits can be utilizedto classify patients into subtypes with distinctive clinical features. This genetic susceptibility based subtyping may be useful tofacilitate more effective treatment and outcome prediction