Objectives/Goals: Biological heterogeneity within psychosis spectrum disorders has proven to be a major obstacle in identifying reproducible pathophysiologic markers of disease. Here, we used normative modeling to assess cortical thickness deviations at the individual level. We then grouped patients into subgroups based on number of deviations. Methods/Study Population: T1 MPRAGE scans from 113 antipsychotic-naive first-episode psychosis patients were normatively modeled as well as 397 unrelated individuals from HCP Young Adult. The patients were subdivided by whether they had a greater than expected number of large deviations in cortical thickness across all regions by comparing norms established in the HCP dataset. Results/Anticipated Results: We identified four distinct subgroups of patients who more commonly share spatial deviation patterns compared to the overall group. The positive deviation subgroup, negative deviations subgroup, and both positive and negative deviations subgroups were larger in the first-episode psychosis sample than would be predicted from the healthy control data. Discussion/Significance of Impact: Our data provide further evidence for the existence of subtypes of psychosis spectrum disorder that differ in patterns of cortical thickness, specifically a subtype with increased cortical thickness. Normative modeling approaches might constitute an important step toward precision psychiatry.
Bryant et al. (2026) studied this question.