Clinical heterogeneity in schizophrenia complicates treatment optimization and contributes to substantial variability in antipsychotic response. Symptom-based stratification may help to identify more homogeneous patient groups and improve prediction of treatment outcomes. However, evidence from large longitudinal studies remain limited. Metabolic abnormalities are also highly prevalent in schizophrenia and may contribute to differential treatment response across clinical subgroups. We conducted a post hoc analysis of a multicenter randomized clinical trial including 2,990 patients with acute schizophrenia. Symptom-based subgroups were identified using K-means clustering. Baseline metabolic indices were compared across subgroups, and 6-week treatment outcomes were evaluated using logistic regression and mixed-effects models for longitudinal symptom trajectories. Mediation analyses were performed to assess whether metabolic markers contributed to subgroup-related differences in treatment response. There are three subgroups were identified: a negative symptom-predominant subgroup (N, n = 1,010), a positive symptom-predominant subgroup with lower overall severity (P, n = 1,226), and a globally severe subgroup (S, n = 754). Treatment response and symptom-improvement trajectories differed significantly across subgroups. Baseline triglyceride and low-density lipoprotein cholesterol (LDL-C) levels were higher in Cluster N, whereas high-density lipoprotein cholesterol levels were higher in Cluster S. Mediation analyses further showed that LDL-C significantly mediated subgroup differences in treatment response. Overall, our study suggested that symptom-based subgroups in acute schizophrenia showed differences in metabolic profiles and antipsychotic treatment responses. LDL-C may partially account for subgroup-related variability in short-term clinical outcomes, highlighting a potential link between metabolic status and treatment heterogeneity in schizophrenia.
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Zhou et al. (2026) studied this question.
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