Abstract Functional impairments contribute to poor quality of life in schizophrenia spectrum disorders (SSD). We sought to (Objective I ) define the main functional phenotypes in SSD, then (Objective II ) identify key biopsychosocial correlates, emphasizing interpretable data-driven methods. Objective I was tested on independent samples: Dataset I ( N = 282) and Dataset II ( N = 317), with SSD participants who underwent assessment of multiple functioning areas. Participants were clustered based on functioning. Objective II was evaluated in Dataset I by identifying key features for classifying functional phenotype clusters from among 65 sociodemographic, psychological, clinical, cognitive, and brain volume measures. Findings were replicated across latent discriminant analyses (LDA) and one-vs.-rest binomial regularized regressions to identify key predictors. We identified three clusters of participants in each dataset, demonstrating replicable functional phenotypes: Cluster 1 —poor functioning across domains; Cluster 2 —impaired Role Functioning , but partially preserved Independent and Social Functioning ; Cluster 3 —good functioning across domains. Key correlates were Avolition, anhedonia, left hippocampal volume , and measures of emotional intelligence and subjective social experience. Avolition appeared more closely tied to role functioning , and anhedonia to independent and social functioning . Thus, we found three replicable functional phenotypes with evidence that recovery may not be uniform across domains. Avolition and anhedonia were both critical but played different roles for different functional domains. It may be important to identify critical functional areas for individual patients and target interventions accordingly.

Functional phenotypes in schizophrenia spectrum disorders: defining the constructs and identifying biopsychosocial correlates using data-driven methods