Psychopathological and Temperamental Stratification of Eating Disorders With Clustering: From Diagnosis to Phenotypic Diversity.

OBJECTIVE: Eating disorders are highly heterogeneous, challenging diagnostic classification and treatment personalisation. This study aimed to identify data-driven phenotypes of anorexia nervosa and bulimia nervosa and examine their relationship with DSM-5 diagnoses and short-term treatment outcomes. METHODS: We analysed 809 female patients with anorexia nervosa (restricting or binge-purge subtype) or bulimia nervosa treated in a specialist eating disorders unit. Baseline clinical, sociodemographic, eating-disorder-specific, and general psychopathology variables were assessed. Nineteen variables entered a Repeated Spectral Clustering pipeline, while body mass index and related measures were reserved for external validation. Associations with DSM-5 diagnoses and remission at discharge were examined. RESULTS: A four-cluster solution best fit the data. Two clusters largely corresponded to restricting-type anorexia nervosa and bulimia nervosa, respectively. Two additional diagnostically mixed clusters were characterised by either greater psychopathological severity and trauma exposure or by older age, longer illness duration, and more marked malnutrition. Cluster membership was associated with remission at the end of treatment, though the effect was weak and no pairwise contrast survived correction. Descriptively, full remission was most frequent in the bulimia-like cluster. CONCLUSIONS: Computational phenotyping captured clinically meaningful heterogeneity beyond DSM-5 categories including two diagnostically mixed subgroups not identified by categorical diagnosis. Cluster membership at intake was weakly associated with end-of-treatment remission, and the resulting subgroups may provide candidate strata for precision psychiatry approaches in eating disorders.